New Agents for the Treatment of Acute Lymphoblastic Leukemia

New Agents for the Treatment of Acute Lymphoblastic Leukemia

Vaskar Saha    Pamela Kearns ●

Editors

New Agents for the Treatment of Acute Lymphoblastic Leukemia

Editors Vaskar Saha Paediatric and Adolescent Oncology School of Cancer and Enabling Sciences Manchester Academic Health Science Centre The University of Manchester Manchester M20 4BX [email protected]

Pamela Kearns School of Cancer Sciences University of Birmingham  Edgbaston, Birmingham B15 2TT [email protected]

ISBN 978-1-4419-8458-6 e-ISBN 978-1-4419-8459-3 DOI 10.1007/978-1-4419-8459-3 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011925850 © Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Brief Overview

Over 80% of children with acute lymphoblastic leukemia (ALL) are cured by ­modern chemotherapeutic regimens. These are the results of carefully conducted randomised clinical trials. Mainly, current protocols have progressively intensified therapy for all children and now use risk stratification to intensify treatment for high-risk subgroups. As a result, therapy-related toxicity now outweighs disease recurrence as a determinant of outcome. The prognosis for those who relapse or do not respond to therapy remains poor. Further intensification is unlikely to benefit those who fail therapy and may increase toxicity for those who do. Perhaps, the most intense of therapies is allogeneic bone marrow transplantation. However, disease recurrence is the most common cause of transplantation failure in these patients. The drugs that we use for ALL are now over 30 years old. To improve outcome further and to decrease toxicity, we need new drugs. These are exciting times. At long last, new agents that can potentially be used in the ALL armamentarium are increasing rapidly. These include both conventional cytotoxics and targeted therapy. However, there are a number of problems that need to be solved. How does one evaluate the effect of a new drug in a disease where over 80% of patients are cured from what is otherwise a fatal disease? What are acce­ptable surrogate markers of response to treatment given that therapeutic failure can occur over a number of years? With shrinking number of patients suitable for phase I and II trials, what new models of trial design are required to obtain answers in the quickest possible time? What cellular and animal models will we accept as most predictive for the clinical effect of the drug in question? These are some of the questions that need to be answered before we can incorporate new agents into frontline therapy for patients with ALL.

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Acknowledgements

This work was funded in part by a programme grant from Cancer Research UK to Vaskar Saha. The editors thank Ms Charlotte O’Horo for editorial assistance.

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Contents

  1  The Need for New Agents........................................................................ Tim Eden 2  Identifying Targets for New Therapies in Children with Acute Lymphoblastic Leukemia..................................................... Shekhar Krishnan, Ashish Masurekar, and Vaskar Saha

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  3  Preclinical Evaluation.............................................................................. Barbara Szymanska, Hernan Carol, and Richard B. Lock

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  4  Design of Early-Phase Trials................................................................... James A. Whitlock and Terzah M. Horton

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  5  Strategies for Trial Design and Analyses............................................... Maria Grazia Valsecchi and Paola De Lorenzo

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  6  An Overview on Animal Models of ALL............................................... 105 Michael A. Batey and Josef H. Vormoor   7  Targeting Bcl-2 Family Proteins in Childhood Leukemia.................... 117 Guy Makin and Caroline Dive   8  Targeting Leukemia Stem Cells and Stem Cell Pathways in ALL...................................................................................... 143 Clare Pridans and Brian J.P. Huntly   9  Nucleoside Analogues.............................................................................. 167 Pamela Kearns and Vaskar Saha 10  FLT3 Inhibitors as Therapeutic Agents in MLL Rearranged Acute Lymphoblastic Leukemia........................................ 189 Ronald W. Stam and Rob Pieters

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11  The Role of Tyrosine Kinase Inhibitors in the Treatment of ALL......................................................................... 203 S. Wilson 12  Monoclonal Antibodies in Paediatric Acute Lymphoblastic Leukemia........................................................................ 221 Arend von Stackelberg 13  Therapeutic Utility of Proteasome Inhibitors for Acute Leukemia................................................................................. 273 Joya Chandra and Claudia P. Miller 14  Targeting Epigenetic Pathways in ALL................................................. 299 Pamela Kearns 15  Incorporating New Therapies into Frontline Protocols....................... 311 Paul S. Gaynon and Theresa M. Harned Index.................................................................................................................. 329

Contributors

Michael A. Batey Northern Institute for Cancer Research, Newcastle University, Paul O’ Gorman Building, Medical Science, Framlington Place, Newcastle upon Tyne NE2 4HH, UK Hernan Carol Leukemia Biology Program, Children’s Cancer Institute Australia for Medical Research, Lawy Cancer Research Center, UNSW PO Box 81, Randwick, NSW 2031, Australia; University of New South Wales, Sydney, NSW 2031, Australia Joya Chandra Department of Pediatrics Research, Children’s Cancer Hospital at M.D. Anderson, University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA [email protected] Caroline Dive Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester, UK; School of Cancer and Enabling Sciences, University of Manchester, Manchester, UK [email protected] Tim Eden 5 South Gillsland Road, Edinburgh, EH10 5DE [email protected] Paul S. Gaynon Therapeutic Advances in Childhood Leukemia Consortium, Institute for Pediatric Clinical Research, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, USA [email protected]

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Contributors

Theresa M. Harned Therapeutic Advances in Childhood Leukemia Consortium, Institute for Pediatric Clinical Research, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, USA Terzah M. Horton Department of Pediatrics, Division of Hematology/Oncology, Baylor College of Medicine, 1102 Bates, Suite 750, USA [email protected] Brian J.P. Huntly Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Hill Road, Cambridge CB2 OXY, UK [email protected] Pamela Kearns School of Cancer Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK [email protected] Shekhar Krishnan Cancer Research UK Children’s Cancer Group, School of Cancer and Enabling Sciences, Manchester Academic Health Sciences Centre, The Unversity of Manchester, Central Manchester and Manchester Children’s NHS Trust, Christie Hospital NHS Foundation Trust, Manchester M20 4BX, UK [email protected] Richard B. Lock Leukaemia Biology Program, Children’s Cancer Institute Australia for Medical Research, Lowy Cancer Research Centre, UNSW PO Box 81, Randwick, NSW 2031, Australia; University of New South Wales, Sydney, NSW 2031, Australia [email protected] Paola De Lorenzo Centre of Biostatistics for Clinical Epidemiology, Department of Clinical Medicine and Prevention, University of Milano-Bicocca, Via Cadore, 48, 20052 Monza (MI), Italy Guy Makin Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester, UK; School of Cancer and Enabling Sciences, University of Manchester, Manchester, UK [email protected]

Contributors

Ashish Masurekar Cancer Research UK Children’s Cancer Group, School of Cancer and Enabling Sciences, Manchester Academic Health Sciences Centre, The Unversity of Manchester, Central Manchester and Manchester Children’s NHS Trust, Christie Hospital NHS Foundation Trust, Manchester M20 4BX, UK [email protected] Claudia P. Miller Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, 38105, Memphis, TN, USA [email protected] Rob Pieters Erasmus MC – Sophia Children’s Hospital Pediatric Oncology/Hematology, Dr. Molewaterplein 60, 3000 CB, Rotterdam, the Netherlands [email protected] Clare Pridans Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Hill Road, Cambridge CB2 OXY, UK Vaskar Saha Cancer Research UK Children’s Cancer Group, School of Cancer and Enabling Sciences, Manchester Academic Health Sciences Centre, The Unversity of Manchester, Central Manchester and Manchester Children’s NHS Trust, Christie Hospital NHS Foundation Trust, Manchester M20 4BX, UK [email protected] Arend von Stackelberg Pädiatrische Onkologie/Hämatologie, Charité, OHC, Augustenburger Platz 13353, Berlin, Germany [email protected] Ronald W. Stam Erasmus MC – Sophia Children’s Hospital Pediatric Oncology/Hematology, Dr. Molewaterplein 60, 3000 CB, Rotterdam, The Netherlands [email protected] Barbara Szymanska Leukemia Biology Program, Children’s Cancer Institute Australia for Medical Research, Lawy Cancer Research Center, UNSW PO Box 81, Randwick, NSW 2031, Australia; University of New South Wales, Sydney, NSW 2031, Australia [email protected]

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Maria Grazia Valsecchi Centre of Biostatistics for Clinical Epidemiology, Department of Clinical Medicine and Prevention, University of Milano-Bicocca, Via Cadore, 48, 20052 Monza (MI), Italy [email protected] Josef H. Vormoor Northern Institute for Cancer Research, Newcastle University, Sir James Spence Institute, 4th floor, Royal Victoria Infirmary, Newcastle Upon Tyne, NE1 4LP, UK [email protected] James A. Whitlock Division of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada [email protected] S. Wilson School of Cancer Sciences, University of Birmingham, Birmingham, West Midlands, UK [email protected]

Contributors

Glossary

ACTH Adrenocorticotrophic hormone ADA Adenosine deaminase ADCC Antibody-dependent cellular cytotoxicity ADCP Antibody-dependent cell-mediated phagocytosis ALL Acute lymphoblastic leukemia Allo-SCT Allogeneic stem cell transplantation AML Acute myeloid leukemia ANC Absolute neutrophil count APCs Antigen-presenting cells APML Acute promyelocytic leukemia AS Asparagine synthetase ATM Ataxia telangiectasia mutated ATP Adenosine triphosphate ATRA All-trans retinoic acid AUC Area under the curve BCLL B-lymphocytic leukemia BCP B-cell precursor BFM Berlin-Frankfurt-Münster BH BCl-2 homology BITE Bispecific T-cell engaging antibodies C Constant CALLA Common acute lymphoblastic leukemia antigen CCG Children’s Cancer Group CDC Complement-dependent cytotoxicity CDDP Cisdiamminedichloridoplatinum CDR Complementarity-determining regions CHOP Cyclophosphamide, doxorubicin, vincristine, prednisone CI Confidence intervals CI50 Inhibitory concentration for 50% effect CLL Chronic lymphocytic leukemia CML Chronic myeloid leukemia CNS Central nervous system xv

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COG CR CRM CRp CSF CTLs

Glossary

Children’s Oncology Group Complete remission/response Continual reassessment method Complete response with insufficient platelet recovery Cerebrospinal fluid Cytotoxic T lymphocytes

DCs Dendritic cells dCK deoxyCytidine kinase dGuo deoxyGuanosine dHPLC Denaturing high performance liquid chromatography DLBCL Diffuse large B-cell lymphoma DLT Dose-limiting toxicities DNR Daunorubicin EC50 Effective concentration for 50% effect EFS Event-free survival time EGFP Enhanced green fluorescent protein EMEA European Medicine’s Agency EMSA Electrophoretic mobility shift assay ER Endoplasmic reticular ERK Extracellular signal-related kinase ESFT Ewing sarcoma family tumours FDA Food and Drug Administration FL FLT3 ligand FLK2 Fetal liver kinase 2 FLT3 Fms-like tyrosine kinase 3 FMS Macrophage colony-stimulating factor receptor GCP Good clinical practice GEP Gene expression profiling GFP Green fluorescent protein GMTZ Gemtuzumab ozogamicin GR Glucocorticoid receptors GSK3a Glycogen synthase kinase 3 isoforms a GSK3b Glycogen synthase kinase 3 isoforms b GvHD Graft-versus-host-disease HAMA Human anti-mouse antibodies HATs Histone acetylases HDAC Histone deacetylase HDACi Histone deacetylase inhibitors HSC Haematopoietic stem cell HSCT Haematopoietic stem cell transplant ICH ICN

International Conference on Harmonization Intracellular NOTCH

Glossary

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IFNa Interferon alpha IGF-1 Insulin-like growth factor 1 IL2rg IL-2 receptor common g chain INR International normalised ratio ITAM Immunoreceptor tyrosine-based activation motif ITD Internal tandem duplication ITIMs Immunoreceptor tyrosine-based inhibitory motifs ITT Intention to treat IV Intravenous JAK JM JNK KDR

Janus kinase Juxtamembrane Jun amino terminal kinase Kinase insertion domain receptor

Ki Inhibitory concentration KIR Killer Ig-like receptor KIT Steel factor receptor LAK Lymphokine-activated killer cells LASNASE l-Asparaginase LPD Lymphoproliferative diseases LSC Leukemia stem cell MAC Membrane attack complex MAPK Mitogen-activated protein kinase MCC Maleimidomethyl-cyclohexane-carboxylate MCR Maintained complete response MDS Myelodysplastic syndrome MEF Mouse embryonic fibroblast MEK MAPK kinase MHC Major histocompatibility complex MIMP Mitochondrial inner membrane potential miRNA microRNA MLL Mixed lineage leukemia MMRC Multiple myeloma research consortium MOMP Mitochondrial outer membrane potential MRC Medical Research Council MRD Minimal residual disease MTD Maximum tolerated dose MTOR Mammalian target of rapamycin MTT Methyl thiazolyl diphenyltetrazolium bromide NCI NHL NK NLS

National Cancer Institute Non-Hodgkin lymphoma Natural killer Nuclear localizing sequences

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Glossary

NNT NOD NSG

Number needed to treat Non-obese diabetic NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ immunodeficient mice

OMM

Outer mitochondrial membrane

PCR Polymerase chain reaction PD Progressive disease PDGFR Platelet-derived growth factor receptor PGP P-glycoprotein PMAS Prospective meta-analysis strategy PNP Purine Nucleoside Phosphorylase PP Per protocol PPTP Paediatric Preclinical Testing Program PR Partial remission/response PTL Parthenolide PTT Partial thrombo-plastin time ROS RPIID RTK

Reactive oxygen species Recommended phase II dose Receptor tyrosine kinase

SC Stem cell SCID Severe-combined immunodeficient SCT Stem cell transplantation SD Standard deviation SD Stable disease SiRNA Small interfering RNA Smac Second mitochondrial derived activator of caspases STK1 Stem cell tyrosine kinase 1 TK Tyrosine kinases TKD Tyrosine kinase domain TM Transmembrane TNF Tumour necrosis factor TPMT Thiopurine methyltransferase TRAIL TNF related apoptosis inducing ligand TRK Tropomyosin-related kinase UPR

Unfolded protein response

V Variable VEGFR Vascular endothelial growth factor receptor VOD Veno-occlusive disease VPA Valproic acid WBC 6MP

White blood cell 6-Mercaptopurine

Chapter 1

The Need for New Agents Tim Eden

1.1 Introduction Since the 1960s, we have progressed from little expectation of survival for children with acute lymphoblastic leukemia (ALL) to 80% 5-year event-free survival and probable long-term cure. Therapy is long and toxic in terms of the physical, emotional and psychological impact on our patients and their families. We can try to alleviate wherever possible those side effects but must not do so at the expense of significantly worsened survival. The balance to be achieved between efficacy and toxicity must be quantified and assessed. How that has been achieved is one of the medical success stories of the twentieth century. It is useful to explore the pathway along which the early pioneers made their progress towards finding potential curative therapy, what mistakes we have made along the way and how we can improve therapy further, to achieve 100% cure rates. Can we improve on the way in which we use our currently available cytotoxics, or do we need totally new approaches for some or all ALL patients?

1.2 Historical Background Following the first description in 1827 by Velpeau [1] of a patient with undoubtedly chronic leukemia, it was not until 1845 that Virchow [2] and Bennett [3] and Craigie [4] independently identified “white blood” as a distinct entity. Virchow [5] ­subsequently first used the term “leukemia” but it was only in 1857 that Friedreich [6] described what was clearly acute as against chronic leukemia [1], whilst 21 years later Neumann [7] reported on the first case of acute myeloid leukemia. Diagnosis was initially by light microscopy. With the development of distinguishing stains,

T. Eden (*) 5 South Gillsland Road, Edinburgh, EH10 5DE e-mail: [email protected]

V. Saha and P. Kearns (eds.), New Agents for the Treatment of Acute Lymphoblastic Leukemia, DOI 10.1007/978-1-4419-8459-3_1, © Springer Science+Business Media, LLC 2011

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more precise cytological classification was established. The application of ­cytogenetics and immunophenotyping has increasingly enabled more precise and definitive ­diagnosis of subtypes [8, 9]. ALL is now recognised to be a heterogeneous group of different entities with different biological characteristics and resistance patterns [9]. Advances in treatment lagged far behind the ability to make the diagnosis of acute leukemia. Between 1865, when arsenicals were first utilised [10], and the 1940s, when work commenced on folate and its antagonists, no progress was made for acute leukemia, although splenic radiation and subsequent use of radionuclides were utilised to produce at least some palliation in chronic myelogenous leukemia and polycythemia vera [11, 12]. In 1947, Farber et al. [13], realising that folate could possibly accelerate acute leukemia in children, utilised an antagonist aminopterin synthesised by Dr Subba Row of Lederle [14]. This induced remissions, some of which lasted for a few months. This heralded in a concentrated period of research into potential antileukemic agents. The anti-leukemic therapeutic value of adrenal corticosteroids was reported initially with the newly identified adrenocorticotrophic hormone (ACTH) in 1949 [15] but was rapidly replaced by the synthetic prednisolone. Methotrexate (4-amino-N10-methyl-folate analogue) replaced aminopterin as a more useful and tolerable agent [16] subsequently available for oral, systemic (IV and IM) plus intrathecal injection. Research into purine metabolism led to the production of a purine analogue, 6-mercaptopurine [17], which also induced remissions in acute leukemia especially if combined sequentially with, or alongside, prednisolone and methotrexate [16]. However, remissions were short-lived, and a generally pessimistic attitude to the potential for cure persisted. In 1959, the research yielded a new alkylating agent, cyclophosphamide, an analogue of nitrogen mustard. The latter had produced such a degree of myelosuppression when used to “gas” soldiers in the 1914–1918 war that its potential as an anti-leukemic agent had been queried and tested [18], but it carried with it excessive toxicity. Efficacy in ALL therapy was reported for cyclophosphamide by Fernbach et al. [19] with tolerable toxicity. In the same year, an alkaloid vincristine, extracted from the periwinkle plant, was shown to induce remission in ALL. Its mode of action was recognised to be quite different to the antimetabolites and alkylators. Subsequently, we know that its cytotoxicity results from an interaction with and disruption of microtubules especially those of the mitotic spindle apparatus [20]. The initial use of single-agent therapy that induced relatively short-term remissions was followed by an era in which researchers started to use combinations of drugs, e.g. prednisone, methotrexate and 6-mercaptopurine. A number of reports in the early 1960s suggested 3–5% 5-year survival rates with such approaches [21–23]. Krivit et al. [23] identified the need for ongoing treatment post-remission induction. Frei et  al. reported on National Cancer Institute [USA] studies using combination therapy [24], but still long-term cure appeared elusive [24]. Many paediatricians felt that children could not be cured and that only palliation was justified. Luckily, some “pioneers” persisted. A group of investigators at the St Jude Children’s Research Hospital in Memphis led by Don Pinkel identified the major reasons for failure: primary and secondary

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resistance, “isolated” extramedullary disease, especially within the central nervous system (CNS), which subsequently led to systemic failure and therapy-related toxicities that put restraints on investigators and induced “breaks” in therapy. Finally and possibly most significantly, the pessimism that shrouded the treatment of acute leukemia – “if you can’t cure why put patients through the ordeal of such toxic therapy” – was not helpful in finding solutions through collaboration of researchers. In such an environment, dedication and commitment was required by anyone continuing to try to find cures. Studies at St Jude started soon after the hospital opened in 1962. Critically, the group identified the need for four treatment phases: induction of remission, intensification or consolidation, CNS-directed therapy and prolonged continuation therapy. They designated their approach as “total therapy” [25]. Early on, they demonstrated the risk of infection especially the emergence of significant immunosuppression-induced pneumocystis carinii pneumonia [25, 26], but reduction of chemotherapy dosage to lessen immunosuppression led to more relapses [27] and was counterproductive. The second and most spectacular breakthrough was the use of effective CNSdirected therapy based on the premise that a majority of children with ALL (50–80% at least) had microscopic extramedullary spread of their ALL and a small minority (3–5%) had overt CNS disease at diagnosis. The application of CNS irradiation early on in treatment was tested in a randomised trial, and 5-year survival rose rapidly from 20% [26] to 50% [28]. This heralded in a new era, and optimism began to replace pessimism. From little expectation of cure in the 1960s, 75–80% overall cure rates are now reported, at least from resource-rich countries [29], so we need to look at what are the key elements and essential drugs. It is important to note as well that significant deviation from the “total therapy” strategy has almost uniformly been associated with decreased survival [30] and reversion to it, subsequent improvement [31]. What appears to be needed in ALL is an almost continuous sustained treatment.

1.3 Induction Therapy: Can We Improve Efficacy? 1.3.1 Basic Template All of the essential agents currently used in ALL therapy were in place by 1970, in particular the standard induction drugs: vincristine, prednisone, l-asparaginase and the anthracyclines daunorubicin or doxorubicin. The template for successful induction (remission rates of 94–96%) includes 4–6 weeks of oral steroid therapy, weekly vincristine injections intravenously (four to six doses), l-asparaginase therapy (dose and schedule, product dependent) and intrathecal methotrexate or triple intrathecal therapy. The use of an anthracycline has been tested but is now normally restricted to those with a higher risk of relapse.

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1.3.2 Steroids Prednisone (or prednisolone) has been the steroid of choice since the 1960s, sometimes given as a 7-day prephase to assess tumour response, which is a moderately good predictor of primary resistance and a potential modulator of cell lysis [32]. Following the report by Balis et  al. [33] regarding greater CNS penetrance by dexamethasone, the Dutch Childhood Leukemia Study Group demonstrated a significant improvement in survival in their ALL VI trial using dexamethasone compared with the previous most similar ALL study [34] that used prednisolone. Two large randomised trials have demonstrated significant benefits for dexamethasone. Both trials have shown significant reduction in CNS relapse rates and overall improvement in event-free survival [35, 36] for standard risk patients treated with dexamethasone during induction and in continuation therapy, compared with the use of prednisone [35] or prednisolone [36]. Mitchell et  al. [36] reported benefit across all risk groups. In a small randomised trial, Igarashi et al. [37] reported no benefit for dexamethasone when their comparative prednisolone dose was 60 mg/ m2/day compared with 40 mg/m2/day used in the other two trials. The dexamethasone dose used in the US, UK and Dutch studies were comparable at 6–6.5 mg/m2/day. Thus, it remains somewhat unclear whether the benefit of type of steroid is merely a matter of dosage or whether the reported lower clearance, larger volume of distribution, longer half-life and greater CNS penetrance of dexamethasone do all truly confer major benefits [33, 38]. Two smaller non-randomised studies raised anxiety about short-term induction morbidity and mortality regarding the use of dexamethasone especially in combination with anthracyclines during induction. However, no significant difference in morbidity or mortality was seen between the randomised arms of either of the UK or US trials [35, 36]. Corticosteroids bind intracellularly to glucocorticoid receptors (GR) and can induce apoptosis [39] through a series of potential pathways and interactions not yet fully defined but almost certainly involve differential regulation of BCL-2 gene family members [40]. More potent cytotoxicity has been reported in in vitro cell line studies with dexamethasone than in prednisolone. Prolonged and continuous exposures (greater than 48–60 h) are required for apoptosis to occur [41]. Reported differences in lineage sensitivity, with B cell lines (especially precursor B cells) being more sensitive than T cells to steroids may indeed relate to variation of receptor numbers in the different lineages [42]. Reduction of GR numbers in mutated cell lines is associated with steroid resistance. Using an MTT assay, Kaspers et  al. [43] showed a median 16-fold greater anti-leukemic activity with dexamethasone compared with prednisolone (with a considerably lower median half-maximal lethal concentration 50). However, for studies incorporating a stromal support for the leukemic blasts, in vitro, the difference between the two steroids was reduced to a sixfold greater cytotoxicity with dexamethasone [42]. Overall, there does appear to be a degree of correlation between low glucocorticoid receptor levels and high risk features, as defined by infancy, older age (>10 years) and overt CNS disease. Most patients with precursor B cell ALL have higher receptor levels than those with T and mature B cell ALL [44].

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Gene expression profiling has facilitated identification of unique leukemia associated markers, which can be monitored for therapeutic response, but it has also identified differentially expressed genes in drug-sensitive and resistant ALL. In steroid-resistant ALL, identified very early in those given a 7-day prephase of steroids, for example, there appears to be an over-expression of the anti-apoptotic MCL1 gene. Wei et al. [45] using a database of drug-associated gene expression profiles identified that the mTOR inhibitor rapamycin profile matched the signature of steroid sensitivity. This agent could sensitise blasts to steroid-induced apoptosis through modulation of MCL1 within primarily resistant cell lines and in vivo transgenic mice. In addition, several transcription genes were under-expressed. The potential to modulate glycolytic pathways and increase steroid responsiveness has emerged from these studies. Most of the acute toxicity of steroids, hyperglycaemia, behavioural change, myopathy, weight gain and immunosuppression do appear to recede with time, off treatment. A worrying feature of modern-era higher-dose steroid usage has been the development of osteonecrosis (avascular necrosis). For those under 10 years of age, the risk appears low at about 1% but increases to greater than 15% in those over 16 years of age in the UK and US steroid trials [35, 36]. A recent review of the latest UK data confirms, in ALL 2003 trial, rates of 1, 13 and 16%, respectively, for those aged 16 years with no sex difference (Vora A, personal communication 2011). In ALL 97/99, there was no overall difference in incidence of avascular necrosis by type of steroid used. This risk has led to the suggestion of a need to either cap steroid dosage in teenagers and young adults or adopt an intermittent strategy, for example, of alternative weeks on and off steroids during induction. No level-one evidence exists to support either of these strategies at present, in terms of reduced toxicity or equi-efficacy. Steroids are such a key component of induction and intensification that there is a great need to ensure optimal dosing and scheduling with early recognition of any steroid resistance for which modulation may be clinically possible, in the future. The long-term sequelae of steroids may be less if adopting the strategy pioneered by the BFM Group to remove all steroid and vincristine pulses from maintenance therapy where induction, consolidation and intensification therapy is so intensive in the first 6 months of treatment [46].

1.3.3 Vincristine This drug is the mainstay of many cancer treatments, not least ALL. Single-drug studies using a dose of 2  mg/m2/week (or 0.06  mg/kg/week), given weekly to relapsing patients in the 1960s induced remissions in 50–60% of patients [47]. Following a bolus intravenous injection, there is considerable inter and intrapatient variation of clearance, volume of distribution and elimination half-life. There is rapid cellular uptake (half life of approximately 5–8 min) and tissue binding, but a long terminal elimination phase of about 14  h so that low levels persist in the plasma. Cerebrospinal fluid (CSF) levels in adults are 20–30-fold lower than

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c­ oncurrent plasma levels. There appears to be poor correlation between vincristine exposure and the troublesome side effect of neuropathy [48]. However, in 2008, Lönnerholm et  al. [49] reported that in a series of 86 ALL patients, there was a trend for more relapses in those with higher median total plasma clearance (on day 1 of treatment) and lower area under the curve (AUC) for plasma concentration. This was only significant in the standard risk group of their series where the relative risk of relapse was significantly increased for patients with clearance values above the median (RR 5.2, p = 0.036) and AUC values below the median (RR 5.8, p = 0.025). They believed that vincristine was more likely to be important in ­standard risk patients who may receive less further intensification, and so getting the dosing right was more crucial. Resistance to vincristine has historically been related to decreased retention and cellular accumulation, related to the level of expression of P-glycoprotein and, consequently, the extent of cellular efflux of the drug. From Lönnerholm et  al.’s work [49], it is obvious that other genes or polymorphic variants play a part in the interpatient variation of handling intracellular levels of vincristine. Gene expression profiling has been used to screen leukemia cell lines and more importantly, individual patient-sourced blast cells to identify gene expression patterns that define subsets of ALL and those related to in vitro drug sensitivity/resistance and consequentially potential outcome of therapy [50, 51]. Holleman et al. [51] specifically looked at in vitro sensitivity to steroids, vincristine, l-asparaginase and daunomycin. There appeared to be a little overlap between the significant genes for each drug’s sensitivity/resistance profile. This clearly emphasises the value of multiagent chemotherapy and also that there is no single solution to resistance. The same team of international collaborators, in a further study, identified a subset of patients with a poor outcome who had a phenotype that was discordant for sensitivity to asparaginase and vincristine [118]. In both the studies, the genes identified had, by and large, not been identified before as resistance genes but were predictive for ­outcome. Cario et al. [52] extended our understanding by linking a set of 54 genes expressed in diagnostic blasts, which predicted for persistent minimal residual disease post-induction and which appeared to be related to proliferation and apoptotic pathway impairment. Increasingly, such studies are also identifying potential novel therapeutic targets. For example, the addition into therapy of inhibitors of enzymes encoded by overexpressed resistance-associated genes within blasts. Of considerable interest is where germ line polymorphisms might influence gene expression within ALL cells, particularly where the polymorphism lies in gene regulator regions [53].

1.3.4 l-Asparaginase In 1922, high levels of the enzyme l-asparaginase were identified in guinea pig serum, but it was not until 1953 that it was shown that this serum destroyed lymphoma cell lines. It took another 8 years to identify asparaginase as the active agent

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[54]. Early leukemia researchers used guinea pig serum to treat ALL and indeed considered harvesting it for more widespread usage even from the larger related animal, the agouti. Luckily for these animals, l-asparaginase was extracted from bacteria, most notably from Escherichia coli [55] and subsequently from the plant pathogen Erwinia carotovora [56] (subsequently reclassified as chrysanthemi). In early studies, a single dose of E. coli l-asparaginase was shown to achieve remission in 25–60% of patients with relapsed ALL, with a median remission duration of 122 days. However, a number of different products have been produced and marketed with varying degrees of purification, different physical and chemical characteristics, especially their half-lives, and elimination (presumed to be through the reticuloendothelial system). Essentially, there are now in use two forms of native E. coli asparaginase and one of Erwinia, and both forms of E. coli l-asparaginase have been pegylated [57]. This involves polymerisation of polyethylene glycol to l-asparaginase. PEG Asparaginase has two advantages over the native drug. Firstly, pegylating E. coli l-Asparaginase protects its catalytic moiety from degradation and increases the half-life of the product from 26–30 h (native E. coli l-Asparaginase) to 5–7 days (PEG Asparaginase) [119]. Secondly, pegylation prevents interaction between the highly immunogenic antigenic sites of this native bacterial enzyme and the immune cells. As a result of the aforementioned two reasons, fewer doses of the pegylated product are needed in comparison to the native bacterial enzyme to achieve a comparabale clinical response (for example, 1,000 international units of PEG Asparaginase every 14 days compared with 10,000 international units of Erwinase every second day). Clinically, the incidence of anaphylaxis has fallen from around 25% to less than 1% following the switch to PEG Asparaginase [120]. Although the exact impact of “silent neutralising anti-l-Asparaginase antibodies” following PEG Asparaginase needs to be determined, there is evidence from one randomised trial showing that contrary to the native E. coli l-Asparaginase, the silent neutralising anti-l-Asparaginase antibodies that develop following PEG Asparaginase are of low titre and are not associated with low l-Asparaginase activity [120]. In order to reduce the risk of antibody production during induction and consolidation [121], when asparaginase is mostly used, some trials now use the pegylated E. coli product de novo, but some only use it in relapsed ALL. For efficacy it has been recognised that adequate plasma levels of enzyme to fully deplete asparagine need to be greater than 100 units/litre and ideally maintained for 3–4 weeks during induction [57]. We have naively assumed that asparagine depletion is the mechanism of its cytotoxic effect on blast cells. However, intracellular asparagine and glutamine are not normally depleted [58]. Furthermore, it has long been postulated that lymphoblasts are deficient in asparagine synthetase (AS) and hence their vulnerability to deficiency of the non-essential amino acid asparagine. However, some cells with AS remain sensitive to l-asparaginase. Additionally, it has been reported that mesenchymal stem cells that form the microenvironment in which marrow blasts survive and grow have AS levels, on average, 20 times higher than leukemic blasts [59]. There are some differences in the expression of AS levels between B-lineage cells (low) and T-lineage cells (higher), which have been correlated with decreased sensitivity to asparaginase, but clearly the picture is very

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complex, and we do not really understand the mechanism of action of its resistance to this drug even after 40 years of use. Suffice to say that no matter how it works enzyme levels do require to be high and efficacy does appear to correlate with effective and prolonged asparagine depletion. Apoptosis may not be induced by this drug [57], but suboptimal asparagine depletion has been shown to affect survival. There has been some controversy about the dosage required; 1,000 international units of pegylated E.coli asparaginase is effective in depleting asparagine for 14–16 days given either intramuscularly or intravenously, but 2,500 units is more effective in depleting CSF asparagine [122, 123]. The enzyme itself does not cross the blood– brain barrier; nevertheless, the CSF can be depleted of asparagine. Monitoring of enzyme levels and antibody production has recently uncovered an interesting story. In a UK series of patients, nearly 80% attained high levels of enzyme during induction with doses of 1,000 international units of pegylated asparaginase (Oncaspar ò, Medac GmbH, Germany), but the remainder did not. About 5% had early inactivation and never recovered, but a similar number had low enzyme levels in induction but post-remission achieved good levels. The early inactivation was clearly not due to antibody production [60], but later inactivation was. The early inactivation by blast cells opens up the need to monitor both asparaginase levels, especially in highrisk patients where the problem principally lies, and the potential to overcome the problem of this unique resistance mechanism. Combined with a better understanding of the role of mesenchymal stem cells in protecting blast cells, we can clearly see that there is much still to learn about optimising asparaginase delivery. The potential to create recombinant asparaginase has led to early clinical trials. Finally, another intriguing piece of evidence was reported by Yang et al. [61]. Asparaginase induces hypoalbuminemia, which in turn is associated with lower dexamethasone clearance. This may enhance the effect of dexamethasone resulting in a degree of synergy. However, those who develop inhibiting antibodies to asparaginase or whose blasts produce a cleaving enzyme may have faster dexamethasone clearance. Once again, the potential complexity and interactions between drugs within combination therapy are emphasised. There is no doubt that we still have a lot to learn about the three key drugs universally used in ALL induction and how we can optimise their efficacy, let alone understand more accurately how they work and the nature of the resistance mechanisms that develop within blasts in response to exposure to these drugs.

1.3.5 Anthracyclines Anthracyclines produce their cytotoxicity via a number of intracellular interactions including free radical formation, inhibition of topoisomerase II, DNA intercalation, disturbance of helicase function and effects on signal transduction [62]. Their cytotoxicity appears to be concentration- and exposure-time-dependent. Klumper et al. [63] reported for childhood ALL leukemic blasts IC50 values of 0.117 mg/mL for daunorubicin and 0.347 mg/mL for doxorubicin. They have played a key role in

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AML, but in ALL their potential toxicity has led to a limitation on usage for standard-risk patients and reservation of their use in remission induction to higher risk patients. The largest single randomised trial for anthracyclines was the UK Medical Research Council trial VIII (1981–1984) [64]. Six hundred and thirty children were randomised to either receive or not receive two doses of daunorubicin (45 mg/m2/ dose) on the first 2 days of induction. The trial yielded a major improvement in disease-free survival (from 40 to 55%) in UK, which had been falling behind the results reported, for that era, from USA and Germany. This improvement was not due to the daunorubicin, which although improving early marrow clearance [65] and disease-free survival for those achieving remission was associated with more induction and early remission deaths. Long-term overall survival showed no benefit for inclusion of an anthracycline. This study demonstrated the degree of myelosuppression induced by anthracyclines. As confirmed in the ALL-BFM 90 study [46], survival can be improved even without anthracyclines. UKALL VIII, a trial without intensification or consolidation, comes from an historical era but clearly showed what could be achieved with a three drug induction and a sustained compliant approach to therapy. The results matched the results of the derivative CSG 162 protocol from USA but fell short of what is now possible [66]. Even then, it lagged behind those of the three BFM studies reported by Riehm et  al. [67]. The BFM studies were once again demonstrating the real value of consolidation and intensification in effective therapy. The late side effects of anthracycline therapy, most specifically cardiotoxicity [68] and the potential of any topoisomerase 2 inhibitor to induce second malignancies [69], have pushed investigators towards reducing total dose exposure to anthracyclines in ALL to less than 200 mg/m2, although it remains unclear whether there is a true threshold effect for either toxicity. The real long-term benefit of concurrent cardioprotectants and/or liposomal anthracyclines also remains unclear.

1.3.6 Summary of Induction Challenges The three most essential induction drugs for the majority of ALL patients are now well defined: vincristine, steroids and l-asparaginase. Identification of those with resistance to all or any single agent would improve early disease control especially for high-risk patients if therapy is suitably adjusted or altered. Anthracyclines probably should be reserved for higher-risk patients and those with slow early response to the standard three agents. Whenever extra agents or a pulsed therapeutic approach has been substituted for the standard approach, survival has decreased [70]. It is doubtful if new agents will improve remission induction for the majority of patients. The exceptions are the 5–6% of cases with potentially primary refractory disease identified by molecular genetics or cytogenetics (e.g. BCR-ABL positive ALL, hypodiploidy) or by slow early response. Traditionally, early response has been measured by peripheral blood and/or bone marrow clearance of blasts [65] but

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is now greatly enhanced by minimal residual disease monitoring by either molecular [71] or flow-cytometric [72] methods. The clinical parameters of age (10 years), gender, initial white cell count, etc. and standard marrow examination numerically failed to identify the majority of those who relapsed. This is where gene expression profiling for resistance patterns could play a role. Not only can those at risk be potentially identified more accurately by the new technology but it is also able to identify potential therapeutic targets (vide infra). Even in relapse, clinical remission can be achieved with vincristine, steroids and asparaginase in a high percentage of cases, but it is the depth of remission that is important in de  novo and relapse cases, and which we can now measure more accurately. Getting induction right for each patient is critical for survival.

1.4 Consolidation and Intensification Even with no evidence of peripheral or marrow blasts on morphological examination at the end of induction, it is likely that there remains a tumour burden even as high as 108 blasts. The St Jude team emphasised, in 1968, the importance of consolidation [25]. It is not clear what combinations work best; more of the same for favourable groups [73], high-dose methotrexate and mercaptopurine, reinduction with steroids, vincristine and high-dose asparaginase or an augmented programme interspersing standard drugs with intravenous methotrexate during periods of myelosuppression [46, 74, 75]. What is more certain is that early post-remission treatment, just like induction, needs to be almost continuous, sustained and without gaps. The MRC UKALL X protocol [76] introduced a randomisation between no post-induction consolidation (as in its predecessor UKALL VIII), an early pulse (week 5), a late pulse (week 20) or both (week 5 + week 20). Those receiving two pulses of therapy had a significantly improved overall 10-year event-free survival (all risk groups) of 60% (54% in UKALL VIII and 56% with no pulses). UKALL XI [77], its successor, used the two pulses and randomised for a third but without further event-free survival improvement (10-year event-free survival 60%) [66, 77]. These results were not as favourable as reported from many other groups [29]. Interestingly, overall survival for the three studies showed an improving trend (UKALL VIII, 65%, X 71%, XI 79%) due to better post-relapse rescue. The problem with the UKALL X pulses was that the five drug combination of cytarabine, etoposide, thioguanine, daunorubicin, prednisolone, vincristine and intrathecal methotrexate required a 3–4 week marrow recovery time. We presume that it also allowed some residual blast recovery. The third module used in UKALL XI (in a randomised fashion) more closely resembled the BFM form of intensification using a much less myelosuppressive combination of an 8-week schedule of more vincristine, asparaginase, intrathecal methotrexate, intravenous cyclophosphamide and cytarabine and oral thioguanine. Much less recovery time was required, and it is this form of intensification that is now more widely used because it provides a sustained cytotoxic attack on residual blasts using drugs with different mechanisms

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of action but without excessive myelosuppression. Since the change in therapy to such an approach, event-free and overall survival in UK has once again reached comparable levels of those reported by other groups [36]. Choice of what agents are optimal during consolidation and intensification may need to be adjusted to subgroups of patients with particular biological characteristics or in the future potentially completely individualised.

1.4.1 Sensitivity/Resistance Patterns It has long been recognised that some subtypes of ALL have differential sensitivity or resistance to all or some cytotoxics. For example, hyperdiploid ALL (25% of childhood ALL) appears to be very sensitive to methotrexate with blast cells accumulating high intracellular levels of methotrexate and its active polyglutamates. Most hyperdiploid ALL blasts carry three or more copies of chromosome 21 including the folate transporter gene for cellular influx of methotrexate and some related compounds. Conversely, B-cell lineage blasts with ETV6-RUNX1 or E2APBX1 fusion genes and T-lineage ALL appear to accumulate much lower levels of polyglutamates [78]. Kager et  al. [78] using oligonucleotide microarrays on diagnostic blasts showed lower expression of the reduced folate carrier (SLC19A1) in pre-B ALL with E2A-PBX1, high expression of the methotrexate efflux transporter ABCG2 in ETV6-RUNX1 ALL and reduced expression of FBGS, which catalyses the formation of polyglutamates in T-lineage ALL. As a result of these characteristics, surely, therapy should be modified by incorporating agents to which these blasts maybe more sensitive. Both the St Jude Total Therapy XIII protocol and the ALL-BFM 90 protocol used high-dose systemic methotrexate in consolidation and yielded 5-year event-free survival for pre-B ALL of 89.5 ± 7.3% and 93 ± 6%, respectively [79, 46]. Previous evidence had suggested less favourable outcome for this form of ALL when treated with standard antimetabolite therapy [80]. It is important to carefully schedule both hydration and leucoverin rescue (not too early or at too high a dose) following methotrexate; otherwise, its benefit can be reduced or even negated as reported by Skärby et al. [81] and observed in MRC UKALL XI [77]. ETV6-RUNX1 leukemia blasts appear to be selectively sensitive to l-asparaginase, whilst BCR-ABL and iAMP21 cells appear to be much less so. In the latter two forms of ALL, it has recently been identified that these blasts more commonly overexpress proteases, especially asparaginyl endopeptidase, which can cleave E. coli l-asparaginase and inactivate it [60]. The novel finding of AML1 gene amplification in ALL was reported by Niini et al. [82] and subsequently defined as representing multiple copies of the gene on a duplicated chromosome 21, dup(21) in near-diploid blast cell karyotypes of ­childhood ALL cases and in adult ALL [83]. This is now classified as iAMP21. The importance of this identification was that these patients (2% of cases) had a median age of 9 (higher than the childhood peak) median lower white cell counts (3.9) than other patients (12.4) amongst 1,630 childhood ALL patients screened [84]. All were

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of pre-B or precursor B-cell lineage. In the trial, ALL 97, they had all been treated as standard risk, but their 5-year event-free and overall survival were very low at 29 and 71%, respectively, compared with 78 and 87% for all other patients, and relapses were early. Having identified this “new high risk” group, in the following ALL trial 2003, these patients were treated on a high-risk strategy with four drug induction, two delayed intensifications and higher-dose systemic methotrexate. To date, none have relapsed. What component of therapy made the difference is difficult to define. iAMP21 blast cells are associated with a deletion of the reduced folate carrier, suggesting decreased sensitivity to methotrexate. In ALL 2003, highrisk patients received intravenous methotrexate, and this may have contributed to the improved results. Other groups using the strategy now adopted by the UK researchers did not report such an adverse outcome with iAMP21 leukemia. This emphasises that prognosis is ultimately therapy related, but we cannot always define which part works for whom with a great deal of precision. Leukemias with BCR-ABL fusion genes and those with MLL gene rearrangements are discussed later as particular challenges for which truly new approaches are being explored. However, in the context of sensitivity, those with t(4;11) in infancy and adult ALL appear to be more sensitive to high-dose cytarabine possibly related to an over-expression of hENT1 gene, another cell membrane transporter. There is no doubt that gene expression profiling of leukemic cells has greatly improved our understanding of disease response and the ability to predict outcome. It has also provided information about new potential targets for therapy especially in resistant disease. The fact whether it will lead in the future to individualisation of treatment remains unclear. Accuracy of predicting relapse in T ALL and hyperdiploid (>50 chromosomes) ALL was emphasised by Yeoh et  al. [50]. Since hyperdiploid ALL has such an overall good prognosis, predicting those with gene patterns that suggest a less good outcome is a major breakthrough.

1.5 Continuation Therapy The evidence from the earliest attempts to cure ALL demonstrated that, for reasons we still do not understand well, this disease requires continuation or “maintenance” therapy to prevent relapse. Some researchers have successfully truncated treatment following intensive initial therapy [85], but the definition of to whom this is safe is not currently possible. We routinely advocate 2–3 years of ongoing treatment with oral methotrexate (weekly) and a daily thiopurine, usually 6-mercaptopurine, both of which were originally discovered nearly 60 years ago. Adjustment of doses to maintain neutrophil counts in the range 0.5–1.5 × 109/L and platelets >75 × 109/L is advocated. We do not know how long continuation therapy really needs to be administered. Lennard et al. [86] reported higher relapse rates in children with lower red cells thioguanine nucleotide concentration and emphasised the importance of thiopurine methyltransferase (TPMT) in determining the cytotoxic effects of 6-mercaptopurine.

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Correlation between better survival and those with intermediate or low TPMT activity was reported by Relling et al. [87]. TPMT is subject to considerable genetic polymorphism. A very small minority of the population are homozygous for a mutant “null” allele, who are incredibly sensitive to mercaptopurine and can only be treated with very much reduced dosages. Stanulla et al. [88] reported from a series of 814 patients, treated on the ALL-BFM 2000 study, that those heterozygous for allelic variants of TPMT with low enzyme activity (55 patients) had a lower rate of minimal residual disease positivity (9.1%) after a 4-week cycle of 6-mercaptopurine (no previous exposure) than those with homozygous wild-type (755) alleles (22.8%). This amounted to a 2.9-fold reduction in risk of relapse for the wild-type heterozygotes. The threshold for MRD negativity was 10−4 using quantitative detection with allele-specific oligonucleotide-PCR methodology. This implies that dose modification on the basis of TPMT genotype might be extremely beneficial for the majority of patients who are in fact wild-type homozygotes and that 6MP may be a very useful component of early consolidation as it was in this study [88]. 6-thioguanine does not require to be metabolised to be activated, and leads to higher intracellular nucleotide levels, and in the CSF. Three recent trials have been randomised between 6-mercaptopurine and 6-thioguanine as the form of antimetabolite during consolidation and continuation therapy. 6-thioguanine at 60 mg/m2/ day proved to be too toxic to platelets [89], but even at 40  mg/m2/day profound thrombocytopenia, high rates of hepatic veno-occlusive disease (VOD) and increased rates of remission death were reported [89, 90]. In both these studies, a superior anti-leukemic response was noted, but this did not outweigh the toxic morbidity and mortality. The third study reported less toxicity but no advantage for 6-thioguanine over 6-mercaptopurine [91]. Low levels of TPMT may contribute to thioguanine-induced VOD but do not predict accurately enough. In the UK study (ALL 97/99) [90], all patients received a short course of thioguanine during intensification with a low level of toxicity especially of VOD. 6-Mercaptopurine, therefore, remains the purine of choice in ALL ongoing treatment, but in view of its increased anti-leukemic effect, short-term exposure to thioguanine in consolidation may be beneficial. Although pulses of vincristine and prednisone were included in continuation therapy, and demonstrated to be beneficial in an era before intensification [92], most therapy groups now omit them [46]. Indeed, Conter et  al. [93] reported no benefit for six pulses of dexamethasone and vincristine given in the early phase of continuing therapy compared with no such pulses. A proposed trial randomising patients to receive or not receive such pulses is planned to start in UK shortly. The impact of blast genotype on sensitivity to methotrexate has already been covered in the Section 1.4. Since methotrexate is a mainstay of continuation therapy, similar considerations must be made with reference to its effectiveness in specific ALL subtypes during remission. What we really do not fully understand is how such long-term relatively lowdosage continuation therapy works. Is it indeed by direct blast cell cytotoxicity? The study by Stanulla et al. [88] confirms that adequate 6MP therapy can lead to reduced MRD. However, the role of the niche where blasts survive and proliferate

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within the bone marrow and the role of mesenchymal/stroma cells in supporting their survival has already been alluded to [59]. Alternatively, could continuation therapy work by immune modulation? We just do not know, and when you do not know the mechanisms of action, it is often very difficult to improve effectiveness. Consequently, exploration of the role of the stroma and of immunomodulation would be advantageous. These may well be two areas where new agents are required in the future.

1.6 CNS-Directed Therapy The use of CNS irradiation and intensive therapy to provide both systemic and targeted extramedullary disease control, pioneered by the St Jude team, produced a dramatic increase in survival [28]. On the downside, cranio-spinal and subsequently cranial irradiation (24 and 18  Gy) were identified as causing significant growth retardation and impairment of intellectual development. Overt CNS disease at diagnosis is relatively rare (50) and an increase in BCR-ABL (25%), MLL rearrangements (10%) and hypodiploidy (2%) [9, 99]. There is a higher incidence of T-cell ALL in teenagers and adults and an increased expression of certain HOX genes. The change in subtype incidence goes some way to explain worsened outcome with increasing age. However, there have also been a series of reports demonstrating that teenagers and young adults treated on paediatric type protocols fare better than if treated on “adult” protocols. The biggest difference between the protocols in all of the reports are the higher dosages of vincristine, asparaginase and steroids and less cyclophosphamide and cytosine in the early stages of childhood therapy [100–105]. These findings have influenced policy decisions to change the upper age limit for childhood trial protocols (up to 25 or even older) with a subsequent reduction in relapse rates. However, poorer tolerance of therapy with increasing age, along with developing co-morbidities and decreased adherence to therapy by physicians and patients as a result of real or perceived increased toxicity also contribute to suboptimal outcome. The story of iAMP21 ALL has already been spelt out where outcome is clearly treatment protocol related. BCR-ABL acute ALL (and CML) treatment has been revolutionised by the addition of an inhibitor of the BCR-ABL tyrosine kinase. The BCR-ABL gene fusion product is a kinase affecting interacting signalling pathways that control cell proliferation, survival and self-renewal and in particular RAS [106]. The first inhibitor introduced into clinical practice, imatinib mesylate, does appear to improve remission duration considerably but resistance appears to develop at least in some. It is currently being tested in both European-wide and American paediatric trials. Alternative inhibitors are also now in trial alongside standard ALL treatment to see whether resistance can be overcome (Dasatinib and Nilotrinib). In ALL with MLL gene rearrangements most commonly seen during childhood in the first year of life (70–80% of cases at least), the selective greater sensitivity to cytarabine and the confusing monocytoid blast morphology (in many) have led to a mixed treatment strategy using elements of ALL and AML therapy with apparent improved outcome although still inferior to older children [107]. Many of these patients have blasts with over-expression of another receptor kinase FLT3.

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A number of inhibitors are now being tested in clinical trials, which are discussed elsewhere in this book. FLT3 is also over-expressed in some hyperdiploid blasts. Controversy still exists as to whether T-cell ALL carries increased risk, independent of the association with high initial white cell counts and bulky extramedullary disease (mediastinal, nodal and CNS disease). Modern intensive therapy appears to be negating the risks previously observed even in adult patients. Mature B-cell ALL now treated with pulsed Burkitt’s lymphoma type therapy is associated with very high cure rates [108, 109]. A majority of T-lineage ALL blasts carry mutations of NOTCH pathway genes especially NOTCH1 which is involved in cell regulation through a network of responder genes including MYC [110, 111]. NOTCH1 mutations sufficient to alter signalling may play a crucial role in initiating T-cell ALL [112]. This pathway is being exploited for potential new therapeutic targets, e.g. gamma-secretase inhibitors (the enzyme is essential for NOTCH1 signalling [112]). However, these inhibitors have marked toxicity profiles on other organs, e.g. on gastrointestinal stem cells, which may limit usefulness [113]. This is a cautionary tale regarding the targeting of cell regulation pathways. Ballerini et  al. [114] have recently reported on two interesting new features identified in T-cell ALL of childhood; the significantly adverse survival for those with TLX3 gene expression and especially when combined with expression of the fusion gene NUP214-ABL1 found in 3/18 of the TLX3 positive cases. This information is not only of prognostic significance but also points the way towards a need for alternative therapeutic approaches for such patients. Aberrant methylation (widespread hypomethylation, regional hypermethylation and increased cellular capacity for methylation) is a common feature in human neoplasia, including lymphoid malignancies. Researchers are beginning to explore ways to interfere with these abnormalities, e.g. use of decitabine, but it is too early to predict whether the approach will be valuable. There has also been a focus on anti-angiogenic agents, monoclonal antibodies (e.g. anti-CD20) inhibitors of signal transduction and, as alluded to earlier, increasing interest in the role of stromal cells. To date, again, it is premature to report real clinical success for any such approaches. Other authors cover the new agents in greater depth in their chapters. The question for this text is whether new agents are required at all and for what purpose and indeed for what form of ALL.

1.8 Conclusions The aim of this chapter is to review leukemia treatment and explore whether new agents are required and so what can we conclude. • Survival dramatically improved when the “total body therapy” concept was adopted. • The most critical feature has been to use the most effective induction drugs: vincristine, steroids and l-asparaginase with anthracyclines reserved for higherrisk patients.

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• However, recent evidence has suggested that we can deliver these standard drugs somewhat more effectively; higher-dose prednisone or dexamethasone; consider individual patient handling of vincristine with potential dose modification; and above all, recognise those patients who cleave l-asparaginase or develop antibodies to it. If we do not, we are impairing achievement of remission, increasing risk of relapse and giving ineffective potentially painful injections. • New forms of l-asparaginase, certainly pegylated, and probably recombinant forms are needed in routine practice. • The need for post-induction consolidation and intensification without any significant gaps has been demonstrated (almost continuous, not pulsed therapy, which itself may induce prolonged myelosuppression). • The first 6 months of therapy is crucial for survival, and the ability to identify minimal residual disease requiring intensification of therapy is the success story of the 1990s. • What is less clear is how this partial or complete resistance can be overcome, e.g. manipulation of the glycolytic pathway to overcome steroid resistance, selective use of specific agents for ALL subtypes, e.g. methotrexate for hyperdiploid patients or an increase in dosage where accumulation of polyglutamates is low (e.g. T-cell and E2A-PBX1 ALL). • Identification of subtypes with blast gene expression profiles that offer new targets, and hence new agents, can be developed to overcome resistance, e.g. BCR-ABL and FLT3 expressors with tyrosine kinase inhibitors and FLT3 inhibitors respectively, although how we deliver these alongside standard therapy is not yet fully defined. • Some of the identified targeted therapies, e.g. gamma secretase inhibitors, have had no totally predictable toxicity profiles. • All of these points to the potential to deliver very personalised ALL therapy for those at high risk. Stratification by MRD status at weeks 5 and 12/13 has ushered in such an era. • We have to be only too aware, however, that MRD measurement does not cure anyone but makes us aware of patients at low and high risk of relapse. It is how we respond to that with our therapy that matters. • What we have not yet fully exploited are identified individual polymorphisms in crucial metabolising genes, e.g. TPMT, which offer the opportunity to exploit slow or fast metabolism [115]. • So, yes, we need new agents for primary refractory/resistant disease, for optimal delivery of standard drugs and for matching both host genomics and “blast” characteristics to optimise cytotoxicity. • Above all, we need to understand the development of resistance, the role of stromal cells in protecting blasts and the mechanisms involved in extramedullary migration. • The era when we substantially decrease intensity and duration of therapy for most ALL patients is not yet here, but we must continue to strive to do so without loss of what we have achieved over the last four decades.

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• Finally, we must remember that the great improvement survival has been restricted to about 20% of the children who acquire ALL worldwide. The remainder receive little supportive care and certainly no curative therapy. We must all strive to reach out and provide them with the hope of cure [116, 117].

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23. Krivit W, Gilchrist G, Beatty E. The need for chemotherapy after prolonged complete remission in acute leukemia of childhood. J Pediatr. 1970; 76:138–141. 24. Frei E III, Karon M, Levin RH et  al. The effectiveness of combinations of antileukemia agents in inducing and maintaining remission in children with acute leukemia. Blood. 1965; 26:642–656. 25. George P, Hernandez K, Hustu O et  al. A study of ‘total therapy’ of acute leukemia in ­children. J Pediatr. 1968; 72:399–408. 26. Pinkel D. Five-year follow up of ‘total therapy’ of childhood lymphocytic leukemia. JAMA. 1971; 216:648–652. 27. Pinkel D, Hernandez K, Borella L et al. Drug dosage and remission duration in childhood lymphocytic leukemia. Cancer. 1971; 27:247–256. 28. Aur RJA, Simone JV, Hustu HO et al. A comparative study of central nervous system irradiation and intensive chemotherapy early in remission of childhood acute lymphocytic leukemia. Cancer. 1972; 29:381–391. 29. Schrappe M, Camitta B, Pui C-H et al. Spotlight on long term results of pediatric ALL clinical trials from 12 study groups worldwide. Leukemia. 2000; 14:2193–2195. 30. Medical Research Council. The treatment of acute lymphoblastic leukemia in childhood leukemia UK ALL III. The effects of added cytosine arabinoside and/or asparaginase and a comparison of continuous or discontinuous mercaptopurine in regimens for standard-risk ALL. Medical and Pediatric Oncology. 1982; 10:501–510. 31. Medical Research Council UK ALL Trials 1972–84. Improvement in treatment for children with acute lymphoblastic leukemia. Report to the Council by the Working Party on Leukemia in Childhood. Lancet. 1986; 1:408–411. 32. Schrappe M, Reiter A, Riehm H. Cyto reduction and prognosis in childhood acute lymphoblastic leukemia. Journal of Clinical Oncology. 1996; 14:2403–2406. 33. Balis FM, Lester CM, Chrousos GP et al. Differences in cerebro-spinal fluid penetration of cortico-steroids: possible relationship to the prevention of meningeal leukemia. Journal of Clinical Oncology. 1987; 5:202–207. 34. Veerman AJP, Hählen K, Kamps WA et al. High cure rate with a moderately intensive treatment regimen in non-high risk childhood acute lymphoblastic leukemia: results of protocol ALL VI from the Dutch Childhood Leukemia Study Group. Journal of Clinical Oncology. 1996; 14:911–918. 35. Bostrom BC, Sensel MR, Sather HN et  al. Dexamethasone versus prednisone and daily oral  versus weekly intravenous mercaptopurine for patients with standard-risk acute ­lymphoblastic leukemia: a report from the Children’s Cancer Group. Blood. 2003; 101: 3809–3817. 36. Mitchell CD, Richards SM, Kinsey SE et  al. Benefit of dexamethasone compared with prednisolone for childhood acute lymphoblastic leukemia: results of the UK Medical Research Council ALL 97 randomised trial. Br J Haematol. 2005; 128:734–745. 37. Igarashi S, Manabe A, Ohara A et  al. No advantage of dexamethasone over prednisolone for the outcome of standard- and intermediate-risk childhood acute lymphoblastic leukemia in the Toyko Children’s Cancer Study Group L 95 – 14 protocol. J Clin Oncol. 2005; 23:6489–98. 38. Richter O, Ern B, Reinhardt D, Becker B. Pharmacokinetics of dexamethasone in children. Pediatric Pharmacol. 1983; 3:329–337. 39. Thompson EB. Apoptosis and steroid hormones. Mol Endocrinol. 1994; 8:665–673. 40. Laane E, Panaretakis T, Pokrovskaja K et al. Dexamethasone induced apoptosis in acute lymphoblastic leukemia involves differential regulation of Bcl-2 family members. Haematologica. 2007; 92 (11):1460–1469. 41. Wood AC, Elvin P, Hickman JA. Induction of apoptosis by anti-cancer drugs with disparate modes of action: kinetics of cell death and changes in C-MYC expression. Br J Cancer. 1995; 71:937–941. 42. Ito C, Evans WE, McNinch L et al. Comparative cytotoxicity of dexamethasone and prenisolone in childhood acute lymphoblastic leukemia. J Clin Oncol. 1996; 14:2370–2376.

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43. Kaspers GJ, Veerman AJ, Popp-Snijders C et al. Comparison of the anti-leukemic activity in  vitro of dexamethasone and prednisolone in childhood acute lymphoblastic leukemia. Med Pediatr Oncol. 1996; 27:114–121. 44. Quddus FF, Leventhal BG, Boyett JM et  al. Glucocorticoid receptors in immunological subtypes of childhood acute lymphoblastic leukemia cells: a pediatric oncology group study. Cancer Res. 1985; 45:6482–6486. 45. Wei G, Twomey D, Lamb J et  al. Gene expression based chemical genomics identifies rapamycin as a modulator of MCL1 and glucocorticoid resistance. Cancer Cell. 2006; 10:331–342. 46. Schrappe M, Reiter A, Ludwig WD. Improved outcome in childhood acute lymphoblastic leukemia despite reduced use of anthracyclines and cranial radiotherapy: results of trial ALL – BFM90. Blood. 2000; 95:3310–3322. 47. Karon M, Freireich E, Frei E. The role of vincristine in the treatment of childhood acute leukemia. Clin Pharmacol Ther. 1966; 7:332–339. 48. Crom WR, Siebold SN, Syold T et al. Pharmacokinetics of vincristine in children and adolescents with acute lymphoblastic leukemia. J Pediatr. 1994; 125:642–649. 49. Lönnerholm G, Frost BM, Abrahamsson J et al. Vincristine pharmacokinetics is related to clinical outcome in children with standard-risk acute lymphoblastic leukemia. British Journal of Haematology. 2008; 142:616–621. 50. Yeoh E-J, Ross ME, Shurtleff SA et al. Classification, subtype discovery and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell. 2002; 1:133–143. 51. Holleman A, Cheok MH, den Boer ML et  al. Gene expression patterns in drug resistant acute  lymphoblastic leukemia cells and response to treatment. N Engl J Med. 2004; 351: 533–542. 52. Cario G, Stanulla M, Fine BM et al. Distinct gene expression profiles determine molecular treatment response in childhood acute lymphoblastic leukemia. Blood. 2005; 105:821–826. 53. Cheok MH, Evans WE. Acute lymphoblastic leukemia: a model for the pharmacogenomics of cancer therapy. Nature Reviews Cancer. 2006; 6:117–129. 54. Becker FF, Broome JD. L-asparaginase: inhibition of early mitoses in regenerating rat liver. Science. 1967; 156:1602–1603. 55. Mashburn LT, Wriston JC. Tumour inhibitory effect from Escherichia coli. Archives of Biochemistry and Biophysics. 1964; 105:450–452. 56. Wade HE, Elsworth R, Herbert E et  al. A new L-asparaginase with anti-tumour activity? Lancet. 1968; 2:776–777. 57. Pinheiro JPV, Boos J. The best way to use asparaginase in childhood acute lymphoblastic leukemia still to be defined. British Journal of Haematology. 2004; 125:117–127. 58. Appel IM, Kazemier KM, Boos J et al. Pharmacokinetic, pharmacodynamic and intracellular effects of PEG-asparaginase in newly diagnosed childhood acute lymphoblastic leukemia: results from a single agent window study. Leukemia. 2008;22:1665–1679. 59. Iwamoto S, Mihara K, Downing JR. Mesenchymal cells regulate the response of acute lymphoblastic leukemia cells to asparaginase. The Journal of Clinical Investigation. 2007; 117:1049–1057. 60. Patel N, Krishnan S, Offman MN et  al. A dyad of lymphoblastic lysosomal cysteine proteases degrade the key anti-leukemic drug L-asparaginase. Journal of Clinical Investigation. 2009; 119(7):1964–1973. 61. Yang L, Panetta JC, Cai X et al. Asparaginase may influence dexamethasone pharmacokinetics in acute lymphoblastic leukemia. Journal of Clinical Oncology. 2008; 26(12):1932–1939. 62. Doroshow JH. Anthracyclines and anthracenediones. In: Chabner BA, Longo DL (eds) Chemotherapy and biotherapy: principles and practice. JB Lippincott Company, Philadelphia. 1996; 409–434. 63. Klumper E, Pieters R, Veerman AP et al. In vitro cellular drug resistance in children with relapsed/ refractory acute lymphoblastic leukemia. Blood. 1995; 86:3861–3868.

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64. Eden OB, Lilleyman JS, Richards S et al. Results of Medical Research Council Childhood Leukemia Trial UK ALL VIII. British Journal of Haematology. 1991; 78:187–196. 65. Lilleyman JS, Gibson BS, Stevens RF et al. Clearance of marrow infiltration after one week therapy for childhood lymphoblastic leukemia: clinical importance and the effect of daunorubicin. Br J Haematol. 1997; 97:603–606. 66. Eden OB, Harrison G, Richards S et al. Long term follow up of the United Kingdom Medical Research Council protocols for childhood acute lymphoblastic leukemia, 1980–1997. Leukemia. 2000; 14(12):2307–2320. 67. Riehm H, Gadner H, Henze G et al. Acute lymphoblastic leukemia. Treatment results in 3 BFM studies (1970–1981). In: Murphy SB, Gilbert JR (eds) Leukemia Research: Advances in cell biology and treatment. Elsevier Biomedical, New York. 1998; 251–263. 68. Lipschultz SE, Colan SD, Gelber RD et al. Late cardiac effects of doxorubicin therapy for acute lymphoblastic leukemia in childhood. N Engl J Med. 1991; 324:808–815. 69. Ng A, Taylor GM, Eden OB. Treatment-related leukemia – a clinical and scientific challenge. Cancer Treatment Reviews. 2000; 6:377–391. 70. Eden OB, Lilleyman JS, Shaw MP et al. MRC Leukemia Trial VIII compared with trials II – VII: lessons for future management. Haematology, Blood Transfusion. 1987; 30:448–455. 71. Van Dongen JJ, Seriu T, Panzer-Grumayer ER et al. Prognostic value of minimal residual disease in acute lymphoblastic leukemia in childhood. Lancet. 1998; 352:1731–1738. 72. Coustan-Smith E, Sancho J, Behm FG et  al. Prognostic importance of measuring early clearance of leukemic cells by flow cytometry in childhood acute lymphoblastic leukemia. Blood. 2002; 100:52–58. 73. Loh ML, Goldwasser MA, Silverman LB et al. Prospective analysis of TEL/ AML1-positive patients treated on Dana-Farber Cancer Institute Consortium Protocol 95 – 01. Blood. 2006; 107:4508–4513. 74. Pui C-H, Evans WE. Treatment of acute lymphoblastic leukemia. N Engl J Med. 2006; 354(2):166–178. 75. Nachman JB, Sather HN, Sensel MG et al. Augmented post-induction therapy for children with high-risk acute lymphoblastic leukemia and a slow response to initial therapy. N Engl J Med. 1998; 338:1663–1671. 76. Chessells JM, Bailey CC, Richards SM. Intensification of treatment and survival in all children with lymphoblastic leukemia: results of the UK MRC Trial UKALL X. Lancet. 1995; 345:143–148. 77. Hill FGH, Richards SM, Gibson B et al. Successful treatment without cranial radiotherapy of children receiving intensified chemotherapy for acute lymphoblastic leukemia. Results of the risk stratified randomised CNS treatment trial MRC UKALL XI. Br J Haematol. 2004; 124 (1):33–46. 78. Kager L, Cheok M, Yang W et  al. Folate pathway gene expression differs in subtypes of acute lymphoblastic leukemia and influences methotrexate pharmacodynamics. The Journal of Clinical Investigation. 2005; 115(1):110–117. 79. Pui C-H, Relling MV, Downing JR. Acute lymphoblastic leukemia. N Engl J Med. 2004; 350:1535–1548. 80. Raimondi SC, Behm FG, Robertson PK et al. Cytogenetics of pro-B cell acute lymphoblastic leukemia with emphasis on prognostic implications of the t (1;19). J Clin Oncol. 1990; 8:1380–1388. 81. Skärby TV, Anderson H, Heldrup J et al. High leucovorin doses during high-dose methotrexate treatment may reduce the cure rate in childhood lymphoblastic leukemia. Leukemia. 2006; 20:1955–1962. 82. Niini T, Kanerva J, Vettenranta K et al. AML1 gene amplification: a novel finding in childhood ALL. Haematologica. 2000; 85:362–366. 83. Harewood L, Robinson H, Harris R et  al. Amplification of AMLI on a duplicated ­chromosome 21 in acute lymphoblastic leukemia: a study of 20 cases. Leukemia. 2003; 17:547–553.

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84. Moorman AV, Richards SM, Robinson HM et al. Prognosis of children with acute lymphoblastic leukemia (ALL) and intrachromosomal amplification of chromosome 21 (iAMP21). Blood. 2007; 109:2327–2330. 85. Toyoda Y, Manabe A, Tsuchida M et  al. Six months of maintenance chemotherapy after intensified treatment for acute lymphoblastic leukemia of childhood. J Clin Oncol. 2000; 18:1508–1516. 86. Lennard L, Lilleyman JS, Van Loon J et al. Genetic variation in response to 6 – mercaptopurine for childhood acute leukemia. Lancet. 1990; 336:225–229. 87. Relling MV, Hancock ML, Boyett JM et  al. Prognostic importance of 6 –mercaptopurine dose intensity in acute lymphoblastic leukemia. Blood. 1999; 93:2817–2823. 88. Stanulla M, Schaeffëler E, Flohr T et al. Thiopurine methyltransferase (TPMT) genotype and early treatment response to mercaptopurine in childhood acute lymphoblastic leukemia. JAMA. 2005; 293(12):1485–1489. 89. Stork LC, Sather H, Hutchinson RJ et al. Comparison of mercaptopurine (MP) with thioguanine (TG) and I/T methotrexate (ITM) with I/T “triples” (ITT) in children with standard-risk ALL: results CCG – 1952. Blood. 2002; 100:156a 90. Vora A, Mitchell CD, Lennard L et  al. Toxicity and efficacy of 6-thioguanine versus 6-mercaptopurine in childhood lymphoblastic leukemia: a randomised trial. Lancet. 2006; 368:1339–1348. 91. Harms DO, Gobel U, Spaar HJ et al. Thioguanine offers no advantage of mercaptopurine in maintenance treatment of childhood ALL: results of randomised trial COALL-92. Blood. 2003; 102:2736–2740. 92. ALL Collaborative Group. Duration and intensity of maintenance chemotherapy in acute lymphoblastic leukemia: overview of 42 trials involving 12,000 randomised children. Lancet. 1996; 346:1783–1788. 93. Conter V, Valsecchi MG, Silvestri D et  al. Pulses of vincristine and dexamethasone in addition to intensive chemotherapy for children with intermediate-risk acute lymphoblastic leukemia: a multicentre randomised trial. Lancet. 2007; 369:123–131. 94. Clarke M, Gaynon P, Hann I et al. CNS-directed therapy for childhood acute lymphoblastic leukemia: childhood ALL Collaborative Group overview of 43 randomised trials. J Clin Oncol. 2003; 21:1798–1809. 95. Gajjar A, Harison PL, Sandlund JT et al. Traumatic lumbar puncture at diagnosis adversely effects outcome in childhood acute lymphoblastic leukemia. Blood. 2000; 96:3381–3384. 96. Te Loo DM, Kamps WA, Van der Does-van den Berg AV et al. Prognostic significance of blasts in the cerebrospinal fluid without pleocytosis or a traumatic lumbar puncture in children with acute lymphoblastic leukemia: the experience of the Dutch Childhood Oncology Group. J Clin Oncol. 2006; 24:2332–2336. 97. Schrappe M, Reiter A, Zimmerman M et al. Long term results of four consecutive trials in childhood ALL performed by the ALL-BFM Study Group from 1981 – 1995. Leukemia. 2000; 14:2205–2222. 98. Matloub Y, Lindemulder S, Gaynon PS et al. Intrathecal triple therapy decreases central nervous system relapse but fails to improve event free survival when compared with intrathecal methotrexate: results of the Children’s Cancer Group (CCG) 1952 study for standard-risk acute lymphoblastic leukemia, reported by the Children’s Oncology Group. Blood. 2006; 108:1165–1173. 99. Chessells JM, Hall E, Prentice HG et al. The impact of age on outcome in lymphoblastic leukemia; MRC UKALL X and Xa compared: a report from the MRC Paediatric and Adult Working Parties. Leukemia. 2004; 12:463–473. 100. Nachman J, Sather HN, Buckley JD et al. Young adults 16 – 21 years of age at diagnosis entered on Children’s Cancer Group acute lymphoblastic leukemia and acute myeloblastic leukemia protocols. Cancer. 1993; 71:3377–3385. 101. Boissel N, Auclerc M-F, Lhėritier V et  al. Should adolescents with acute lymphoblastic leukemia be treated as old children or young adults? Comparison of the French FRALLE-93 and LALA-94 trials. J Clin Oncol. 2003; 21:774–780.

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102. De Bont JM, Holt B, Dekker Am et al. Significant difference in outcome for adolescents with acute lymphoblastic leukemia treated on pediatric versus adult protocols in the Netherlands. Leukemia. 2004; 18:2032–2035. 103. Ramanujachar R, Richards S, Hann I et al. Adolescents with acute lymphoblastic leukemia: outcome on UK National Paediatric (ALL97) and Adult (UKALL XII/ E2993) trials. Pediatric Blood and Cancer. 2007; 48:254–261. 104. Hallböök H, Gustafsson E, Smedmyr B et al. Treatment outcome in young adults and children > 10 years of age with acute lymphoblastic leukemia in Sweden: a comparison between a pediatric protocol and an adult protocol. Cancer. 2006; 107: 1551–1561. 105. Barry E, De Angelo DJ, Neuberg D et al. Favourable outcome for adolescents with acute lymphoblastic leukemia treated on Dana-Farber Cancer Institute Acute Lymphoblastic Leukemia Consortium protocols. J Clin Oncol. 2007; 25:813–819. 106. Ren R. Mechanisms of BCR-ABL in the pathogenesis of chronic myelogenous leukemia. Nat Rev Cancer. 2005; 5:172–183. 107. Pieters R, Schrappe M, De Lorenzo P et al. A treatment protocol for infants younger than 1 year with acute lymphoblastic leukemia (Interfant-99): a observational study and a multicentre randomised trial. Lancet. 2007; 370:240–250. 108. Patte C, Auperin A, Michon J et al. The Societe Francaise d’Oncologie Pediatrique LMB89 protocol: highly effective multiagent chemotherapy tailored to the tumor burden and initial response in 561 unselected children with B cell lymphomas and L3 leukemia. Blood. 2001; 97:3370–3379. 109. Reiter A, Schrappe M, Ludwig WD et al. Intensive ALL-type therapy without local radiotherapy provides a 90% event free survival for children with T cell lymphoblastic lymphoma: a BFM group report. Blood. 2000; 95:416–421. 110. Weng AP, Ferrando AL, Lee W et al. Activating mutations of NOTCH I in human T cell acute lymphoblastic leukemia. Science. 2004; 306:269–271. 111. Palomero T, Lim WK, Odom DT et al. Notch I directly regulates C-MYC and activates a feed-forward-loop transcriptional network promoting leukemic cell growth. Proc Natl Acad Sci. 2006; 103:18261–18266. 112. Armstrong SA, Look AT. Molecular genetics of acute lymphoblastic leukemia. J Clin Oncol. 2005; 23:6306–6315. 113. Wong GT, Manfra D, Poulet FM et al. Chronic treatment with the gamma-secretase inhibitor LY-411.575 inhibits beta-amyloid peptide production and alters lymphopoiesis and intestinal cell differentiation. J Bio Chem. 2004; 279:12876–12882. 114. Ballerini P, Landman-Parker J, Cayuela JM et al. Impact of genotype on survival of children with T cell acute lymphoblastic leukemia treated according to French protocol FRALL-93: the effect of TLX3/ HOX11L gene expression on outcome. Haematologica. 2008; 93(11): 1658–1668. 115. Rocha JCC, Cheng C, Lui W et  al. Pharmacogenetics of outcome in children with acute lymphoblastic leukemia. Blood. 2005; 105(12):4752–4758. 116. Eden T. Translation of cure for acute lymphoblastic leukemia to all children. Br J Haem. 2002; 118:945–951 117. Eden T, Pui C-H, Schrappe M et al. All children have the right to full access to treatment for cancer. Lancet. 2004; 364:1121–1122. 118. Lugthart S, Cheok MH, den Boer ML et al. Identification of genes associated with chemotherapy cross resistance and treatment response in childhood acute lymphoblastic leukemia. Cancer Cell. 2005; 7:375–386. 119. Asselin BL, Whitin JC, Coppola DJ. Comparative pharmacokinetic studies of three asparaginase preparations. J Clin Oncol. 1993; 11:1780–1786. 120. Avramis VI, Sense S, Periclou AP et al. A randomized comparison of native Escherichia coli asparaginase and polyethylene glycol conjugated asparaginase for treatment of children with newly diagnosed standard-risk acute lymphoblastic leukemia: a Children’s Cancer Group study. Blood. 2002; 99:1986–1994.

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121. Woo MH, Hak LJ, Storm MC et al. Anti-asparaginase antibodies following E. coli asparaginase therapy in pediatric acute lymphoblastic leukemia. Leukemia. 1998; 12:1527–1533. 122. Hawkins DS, Park JR, Thomson BG et al. Asparaginase pharmacokinetics after intensive polyethylene glycol-conjugated l-asparaginase therapy for children with relapsed acute lymphoblastic leukemia. Clin Cancer Res. 2004; 10:5335–5341. 123. Appel IM, Pinheiro JP, den Boer ML et al. Lack of asparagine depletion in the cerebrospinal fluid after one intravenous dose of PEG-asparaginase: a window study at initial diagnosis of childhood ALL. Leukemia. 2003; 17:2254–2256.

Chapter 2

Identifying Targets for New Therapies in Children with Acute Lymphoblastic Leukemia Shekhar Krishnan, Ashish Masurekar, and Vaskar Saha

Summary For those of us who look after children with acute lymphoblastic leukemia (ALL), these are heady times. Cure rates on current therapeutic regimens are now approaching 90% [1, 2]. Therapy is almost entirely chemotherapy-based with very few patients now receiving irradiation [3]. Why then in this group of patients should we be looking for new agents? The obvious one is that we are reaching the limits of what can be achieved with combination chemotherapy [4]. In a sense we have been lucky. Almost all of the earliest chemotherapeutic agents proved effective in childhood ALL. Children tolerate combination chemotherapy better than adults. This has allowed us to gradually intensify therapy in all groups and in particular those at a higher risk of relapse. This risk-stratified approach to intensification has proven to be highly effective [5–11]. One problem we now face is the high cost of cure. Treatment-related mortality and morbidity [12] is almost balancing out the relative risk of relapse. Allogeneic stem cell transplant (allo-SCT), the ultimate in treatment intensity, cannot cure patients unless disease burden is first reduced using chemotherapy [13, 14]. Thus, intensification of therapy is unlikely to improve outcome any further. We therefore need new drugs not only to cure those currently failed by therapy but also to decrease the morbidity of current treatment. At present most protocols use ten or more drugs over a period of 2–3 years to treat children with ALL. The cost of treatment and supportive care is prohibitive for countries with restricted resources. This includes the most heavily populated parts of the world. Thus, the remarkable success rates seen in developed countries are yet to be translated globally [15]. To provide a solution for all children with ALL we need shorter,

S. Krishnan (*) Cancer Research UK Children’s Cancer Group, School of Cancer and Enabling Sciences, Manchester Academic Health Sciences Centre, The University of Manchester, Central Manchester and Manchester Children’s NHS Trust, Christie Hospital NHS Foundation Trust, Manchester M20 4BX, UK e-mail: [email protected] V. Saha and P. Kearns (eds.), New Agents for the Treatment of Acute Lymphoblastic Leukemia, DOI 10.1007/978-1-4419-8459-3_2, © Springer Science+Business Media, LLC 2011

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cheaper therapeutic strategies. Finally, childhood ALL is a paradigm for successful cancer therapy. In terms of modern biology, it is one of the most heavily investigated. In a sense, having resolved the therapeutic dilemma we now have the luxury of dissecting out the mechanisms of cure and resistance. It is likely that the biological mechanisms that regulate the variations in the therapeutic response and side effects are common to more than one tumour type. Thus, the mechanisms identified are likely to have wider application in the treatment of cancer.

2.1 Understanding Disease Biology In the following sections, we pose key questions, the solutions to which we believe are ­fundamental in advancing and refining therapy in childhood ALL.

2.2 Can We Further Optimise Current Therapy? Biologically, childhood ALL is a heterogeneous disease. Cytogenetic analysis demonstrates this and outcome clearly varies by genetic subtype. However, even within a cytogenetic subset, there is disparity. A small proportion of those with hyperdiploidy relapse. Similarly, a small proportion of those with Philadelphia chromosome positive (Ph+) ALL respond well to chemotherapy. As hyperdiploidy is more common, relapse in this group poses a bigger clinical problem. Biological heterogeneity is also reflected in the therapy used. Drugs used ­predominantly affect nucleic acid integrity (intercalating agents, epipodophyllotoxins), synthesis (anti-metabolites), replication (mitotic spindle poisons) and transcription (steroids). Notable in this armamentarium is the drug l-asparaginase, which exerts a unique cytotoxic effect specific to this cancer and is a pivotal drug in the treatment of childhood ALL. The most sensitive predictor of outcome has proven to be the early response to therapy, measured either by a decrease in circulating blasts, percentage residual blasts in the marrow or molecular level of disease during initial therapy. Thus, the heterogeneity of disease has serendipitously been tackled by the use of multi-targeted therapy effective against the most frequent subtypes of childhood ALL. This accords with the Goldie–Coldman hypothesis [16] which avers that drug resistant clones are less likely to evolve in tumours treated with the most effective combination chemotherapy. However, while this sweeping approach may stochastically benefit the majority, a proportion of patients will necessarily be over treated and some will not receive appropriate therapy. Further fine-tuning is still possible with current chemotherapeutic agents. For example, there is evidence to suggest that patients with ETV6-RUNX1 ALL are more sensitive to asparaginase [17] and that overexpression of the folate reductase carrier gene through duplication of chromosome 21 renders patients with hyperdiploid ALL more sensitive to methotrexate [18]. Thus, protocols could be adapted to increase exposure of the specific drug in each cytogenetic category [19]. The problem we face is that we are still unsure about the precise

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mechanisms of actions of drugs and the ­consequences of their interactions. This limits our ability to predict recurrences. A better understanding of the biological processes is now ushering in an era of individualised therapy. An exemplar of this is the ABL tyrosine kinase inhibitors in Ph+ ALL [20].

2.3 What Are the Origins of Relapse? Relapsed ALL is broadly risk-stratified by the duration of first remission. Those who relapse early are often incurable, even with allo-SCT. In contrast those who relapse late, off therapy, have survival rates of over 70% with conventional chemotherapy [21–23]. Genome-wide analysis has recently shown that in almost 90% of cases, disease recurrence is due to a sub-clone present at original diagnosis [24]. This observation is supported by results of recent xenotransplantation experiments performed in more permissive immunodeficient mice recipients. In these studies, lymphoblast populations designated mature by immunophenotypic criteria also appear to possess stem cell properties, suggesting that “stemness” in ALL is more widely prevalent than previously recognised [25]. Gene expression profiling (GEP) has also been used to investigate relapsed disease [26–28]. GEP analyses suggest that transcriptional signatures differ between diagnostic and relapse blasts in early but not late relapses [28]. This suggests that early relapses occur as the result of a sub-clone already present at original diagnosis. Intriguingly, GEP analyses suggest that this clone is highly proliferative and thus the mechanisms by which it resists chemotherapy and allo-SCT remain to be elucidated. In contrast, in late relapses, there are at least two possibilities. There is evidence to suggest that these relapses are derived from the same ancestral clone that gave rise to the original leukemia [29, 30]. In essence, this is a second leukemia but as result of its origin, it retains the chemosensitivity of the original disease. Thus, these patients respond well to chemotherapy. Within this group of later relapses, we know that there are patients who show a slower clearance of disease. These patients often require allo-SCT to sustain remission. As discussed later, these differences may be accounted for by germline polymorphisms in genes regulating drug metabolism.

2.4 Why Do Relapses Occur at Extramedullary Sites? A conundrum in relapsed ALL is the high incidence of recurrence at extramedullary sites such as the central nervous system (CNS). Such relapses tend to occur late and can be either isolated or combined with a bone marrow relapse. Curiously, the ­outcome of combined or isolated extramedullary relapses is better than isolated marrow relapse. This is puzzling as in most cases of isolated extramedullary disease it is possible to detect low levels of marrow involvement using molecular ­techniques [31]. Why and how do lymphoblasts enter extramedullary compartments? The clue

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lies perhaps in the observation of a striking dichotomy in CNS disease incidence between diagnosis and relapse. While CNS disease is a rare feature of de  novo ALL, it is seen in around 30% of ALL relapses [19]. It could thus be argued that this phenomenon is selected for by chemotherapy [32]. One possibility is that residual leukemic cells, protected by interactions with the marrow microenvironment, proceed to breach endothelial-matrix barriers and infiltrate extramedullary niches. It is likely that within these sanctuary niches, cells are protected from chemotherapy-induced cell death and give rise to extramedullary recurrences.

2.5 How Do We Account for the Heterogeneity in Treatment Response? Heterogeneity in response to any single drug is commonly observed in patients with ALL. There is evidence to suggest that this is considerably influenced by host genome polymorphisms that regulate drug handling. Polymorphisms relating to increased drug clearance may be responsible for a slower clearance of disease [33–35]. Leukemic blasts may also contribute to the variations in therapeutic response. An example is the enzyme thiopurine S-methyltransferase (TPMT). The metabolism of thiopurines is regulated by TPMT. Lower levels of the enzyme are associated with higher toxicity and better outcomes. TPMT is located on chromosome 6p. Duplication of this region in the somatic genome can result in high levels of the enzyme in lymphoblasts, which are then able to clear the drug more rapidly [36]. Thus, the tolerated dose of thiopurine may be insufficient to kill blast cells in such cases. More recently, lymphoblasts have been shown to produce proteases capable of inactivating asparaginase [37].

2.6 What Is the Role of the Tumour Microenvironment? Host-tumour interactions are clearly an important component of the spectrum of mechanisms leading to therapeutic failure. Mesenchymal stem cells and ­haematopoietic stem cell (HSC) niches may provide a protective marrow ­microenvironment for leukemic cells [38]. As remarked earlier, intrinsically chemosensitive ALL blasts that have the ability to migrate to HSC niches may weather the chemotherapy storm under the umbrella of the microenvironment and re-emerge to cause disease recurrence. These patients may respond to allo-SCT, where ablative conditioning creates an empty marrow niche, thus removing the protective microenvironment. The niche is then colonised by donor HSCs that are presumably able to outcompete residual leukemic cells. Some leukemic cells are capable of modifying the HSC niche to their own advantage, creating their own microenvironment and displacing normal haematopoietic progenitors [39]. Clearly such disease is likely to be incurable with conventional chemotherapy and

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allo-SCT. As illustrated by the success of tyrosine kinase inhibitors in Ph+ ALL, such leukemias require targeted therapy. In this context, it is entirely plausible that the same ­signalling mechanisms that facilitate long-term survival of blasts also facilitate disease progression and extramedullary spread. If so, targeting these survival ­pathways may prevent disease recurrence.

2.7 How Do We Discover Novel Biological Targets? Transcriptional profiling has been shown to be predictive of in vitro chemosensitivity [40], as well as the rapidity of response to therapy [41, 42]. However overexpressed genes often lie at the end of a regulatory cascade and it is difficult to ascertain which if any of these genes are directly responsible for therapeutic failure. Additionally, global profiling, even if multi-omic and integrated, does not intrinsically have the resolution to detect expression signatures of minor sub-clones that later account for relapse. Yet, despite these limitations, microarray platforms are already aiding discovery of potential adverse prognostic markers amenable to therapeutic targeting. Aberrant kinase activity has recently been identified as a recurring feature of high-risk disease. Detailed analyses by a number of groups [43–46] show that as a result of either a somatic translocation or deletion, some patients overexpress the cytokine receptor, cytokine receptor-like factor 2 (CRLF2). CRLF2 overexpressing patients have a significantly worse outcome [43]. GEP analyses shows that these patients have an expression signature similar to that seen in Ph+ ALL [47, 48], which includes the adverse-risk Ikaros deletion [43]. More importantly CRLF2 overexpression is associated with somatic activating Janus family kinase (JAK) mutations [49]. These studies suggest that Ikaros, JAK and CRLF2 aberrations cooperate in leukemogenesis and targeting the JAK-STAT signalling mechanism may be an attractive therapeutic strategy.

2.8 ALL: A Conceptual Model for Treatment Figure 2.1 is a proposed conceptual model that integrates lymphoblast characteristics and reciprocal host-tumour interactions to establish a biological and therapeutic paradigm in childhood ALL. Using this model, disease may be categorised into three broad groups: Group 1. Highly proliferative, stroma-independent and exquisitely chemosensitive blasts. Group 2. Intrinsically chemosensitive blasts that evade chemotherapy by interacting with the host microenvironment; ablative allo-SCT here removes stromal chemoprotection and is curative. Inhibitors capable of disrupting adhesive tumour-stroma interactions (e.g., CXCR4 antagonists) may also have a role here [50].

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Fig. 2.1  An integrated disease paradigm for therapy in childhood ALL. See text for details

Group 3. B  lasts that evade chemotherapy by establishing stroma-independent tumour niches; ablative allo-SCT is ineffective in this group and strategies that target key survival mechanisms are required, exemplified by the ABL tyrosine kinase inhibitors in Ph+ ALL. Powerfully intersecting with this model are host germline polymorphisms that determine drug disposal and tolerance.

2.9 New Molecular and Cellular Treatment Targets As remarked previously, with the notable exception of asparaginase, all cytotoxic agents including steroids essentially target nuclear mechanisms. The cell nucleus continues to be a focus of drug targeting and many compounds in this class have entered early clinical trials. This includes a number of new nucleoside analogues, the aurora kinase inhibitors that target mitotic spindles [51] and the inhibitors of histone deacetylases [52] and DNA methyltransferases [53, 54] that target the ­dysregulated transcriptional programme in ALL blasts. The chapters in this monograph discuss a number of alternative approaches ­targeting cellular processes and molecules identified in Fig.  2.2. The alternative approaches may be loosely categorised as below. Not all targets have well identified pre-clinical agents in phase I trials.

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Fig. 2.2  A schematic representation of molecular and cellular targets of therapy in acute lymphoblastic leukemia. The lymphoblast nucleus is the principal therapeutic target. Tyrosine kinase inhibitors suppress constitutively activated receptor (e.g., FLT3) or downstream cytoplasmic tyrosine kinases (JAK, SRC, ABL1). Leukemic cell apoptosis is enhanced by suppressing mTOR kinase activity (Rapamycin and analogues) or by NFkB-mediated proteasome inhibition. Nonclassical (lysosomal) death pathways may also be triggered by BCL2 family antagonists or by antibody ligation of surface molecules. Monoclonal antibodies typically mediate leukemic cell clearance by activating immune effector mechanisms or by disrupting stromal adhesion. Targeting activated Notch signalling is a potential strategy in T-lineage disease. Asparaginase is unique in its cytotoxicity, selectively perturbing blast cell protein synthesis through substrate depletion. Response to therapy is strongly influenced by host germline polymorphisms governing drug disposal and tolerance. ABL Abelson murine leukemia viral oncogene homolog tyrosine kinase 1; BCL2 B-cell lymphoma 2 family of antiapoptotic molecules; CD cluster of differentiation antigens; HDAC histone deacetylase; JAK Janus family tyrosine kinases; FLT3 FMS-like tyrosine kinase receptor 3; mTOR mammalian target of rapamycin; NFkB nuclear factor kappa-light-chain enhancer of activated B cells complex of proteins; PI3K phosphoinositide-3-kinase; RTK receptor tyrosine kinase; SRC sarcoma protooncogene family of tyrosine kinases; STAT signal transducer and activator of transcription family of proteins. Stars indicate targeting agents in clinical trials in other diseases but not yet in ALL. Additional details in text

2.9.1 Steroid-Sensitising Adjuvants Steroid resistance may be overcome by antagonists of the mammalian target of rapamycin (mTOR) kinase or by pro-apoptotic small molecules. mTOR inhibitors have shown promise as steroid-sensitising agents, operating through down-regulation of the antiapoptotic BCL2 family molecule, MCL1 [55]. The BCL2 antagonist

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Obatoclax too is able to restore steroid sensitivity but appears to do this by activating autophagic necroptosis and thus bypassing a block in mitochondrial apoptosis [56].

2.9.2 Monoclonal Antibodies to Surface Molecules Surface molecules on the lymphoblast plasma membrane may be targeted using a number of naked and conjugated antibodies. These antibodies typically mediate blast clearance by binding to cognate proteins and activating cellular or non-cellular immune effectors. Alternatively, these antibodies disrupt the function of target molecules (as in the case of antibodies to integrins) or trigger alternative cell death mechanisms (see below).

2.9.3 Kinase Inhibitors As highlighted earlier, dysregulated kinase activity is consistently noted in ­high-risk ALL. We do not fully understand the mechanisms and molecules responsible for kinase survival signalling in pre-B lymphoblasts. This activation may be constitutive as in the case of activating JAK mutations. Alternatively, aberrant activation may be triggered by homotypic or heterotypic adhesion and maintained by paracrine or autocrine mechanisms [57]. Inhibitors targeting key activated kinases, including the receptor tyrosine kinase, FLT3 and the cytoplasmic kinases, SRC [58] and LYN [59], are now in clinical trials. Similarly, JAK and SYK inhibitors have entered trials for autoimmune and inflammatory diseases but have not yet been tested in childhood ALL. Phosphoinositide-3-kinase (PI3 kinase) inhibitors are gradually entering clinical trials but as this is a large family of kinases, further work is required to clarify the pertinent isoforms in childhood ALL.

2.9.4 Alternative Cell Death Pathway Triggers Exploring non-apoptotic cell-death mechanisms as a therapeutic strategy is in its nascence but holds promise. For instance in mature B-cell neoplasms, type II antibodies directed against surface CD20 molecules trigger cell death by destabilising lysosomes, leading to intracellular lysosomal leak and caspase-independent cell death [60]. Our observations suggest that aberrant lysosome trafficking is a feature of ALL blast cells and targeting lysosomal hydrolases is an approach that merits investigation. Proteasome inhibitors may similarly operate through both apoptotic and non-apoptotic cell death triggers and are discussed in detail in a later chapter.

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2.9.5 Others A number of alternative approaches also have the potential to be successful. Relapses in precursor T-lineage ALL (T-ALL) are an especial therapeutic challenge. More than 50% of T-ALL harbour activating NOTCH1 mutations. The enzyme g-secretase catalyses the activating cleavage of the NOTCH1 receptor and g-secretase inhibitors have entered clinical trials. g-Secretase is also required for the maturation of the intestinal mucosa and thus gut toxicity is dose limiting, though there is evidence from a murine model that this may be overcome by the concomitant use of steroids [61].

2.10 Concluding Remarks After decades marked by a dearth of new agents, the recently invigorated drug pipeline is an exciting development in the treatment of childhood ALL. But this presents its own challenges. How do we integrate these new agents within contemporary treatment protocols? How do we optimally investigate these drugs in clinical trials? How do we examine their specific effects in the context of multi-agent ­chemotherapy? And importantly, how do we make these agents available to resource-constrained populations? There are no easy answers as yet and radical unorthodox approaches are probably necessary. The issue of germline polymorphisms has not been addressed in this chapter or discussed elsewhere in the monograph. These polymorphisms are likely key determinants in eventual treatment response and drug toxicity. Suffice to say, we just do not know enough about the different pathways responsible for the degradation of drugs used in childhood ALL as we have not had the tools to investigate this in detail. With the advent of cheaper germline whole genome sequencing, this is set to change. So, to end from where we started, these are heady times for those of us who look after children with ALL. Among the first to show that a cancer can be cured, we as a community can now proceed to demonstrate how an understanding of the biology of the disease can be harnessed to individualise therapy. This will not only lead to more cures and less toxicity but hopefully cheaper and simpler ­treatment options that can be applied globally. Acknowledgement  This work was supported by a programme grant from Cancer Research UK (VS, AM) and a fellowship from the University of Manchester (SK).

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54. Horton TM, Thompson PA, Berg SL, Adamson PC, Ingle AM, Dolan ME, et  al. Phase I pharmacokinetic and pharmacodynamic study of temozolomide in pediatric patients with refractory or recurrent leukemia: a Children’s Oncology Group Study. J Clin Oncol. 2007 Nov 1;25(31):4922–8. 55. Wei G, Twomey D, Lamb J, Schlis K, Agarwal J, Stam RW, et  al. Gene expression-based chemical genomics identifies rapamycin as a modulator of MCL1 and glucocorticoid resistance. Cancer Cell. 2006 Oct;10(4):331–42. 56. Bonapace L, Bornhauser BC, Schmitz M, Cario G, Ziegler U, Niggli FK, et al. Induction of autophagy-dependent necroptosis is required for childhood acute lymphoblastic leukemia cells to overcome glucocorticoid resistance. J Clin Invest. 2010 Mar 1;120(4):1310–23. 57. Harwood NE, Batista FD. Early events in B cell activation. Annu Rev Immunol. 2010 Apr 23;28:185–210. 58. Li S. Src-family kinases in the development and therapy of Philadelphia chromosome-positive chronic myeloid leukemia and acute lymphoblastic leukemia. Leuk Lymphoma. 2008 Jan;49(1):19–26. 59. Kantarjian H, Coutre PL, Cortes J, Pinilla-Ibarz J, Nagler A, Hochhaus A, et al. Phase 1 study of INNO-406, a dual Abl/Lyn kinase inhibitor, in Philadelphia chromosome-positive leukemias after imatinib resistance or intolerance. Cancer. 2010 Mar 22;116(11):2665–72. 60. Ivanov A, Beers SA, Walshe CA, Honeychurch J, Alduaij W, Cox KL, et  al. Monoclonal antibodies directed to CD20 and HLA-DR can elicit homotypic adhesion followed by lysosome-mediated cell death in human lymphoma and leukemia cells. J Clin Invest. 2009 Aug;119(8):2143–59. 61. Real PJ, Tosello V, Palomero T, Castillo M, Hernando E, de Stanchina E, et  al. Gammasecretase inhibitors reverse glucocorticoid resistance in T cell acute lymphoblastic leukemia. Nat Med. 2009 Jan;15(1):50–8.

Chapter 3

Preclinical Evaluation Barbara Szymanska, Hernan Carol*, and Richard B. Lock

3.1  Introduction In contrast to paediatric disease, ALL in adults is not only relatively rare comprising approximately 20% of all adult leukemias, but is also much more resistant to ­currently available treatments [1]. At present, the first complete remission rates (80–90%) attained in adult ALL approach those achieved in paediatric cases [2]. Nevertheless, only 30–40% of adult patients achieve long-term disease-free survival, and new chemotherapeutic agents and novel approaches to treatment must be developed for adults with ALL in order to improve the relatively low cure rates. Although the incidence of paediatric ALL is close to twofold higher than that in adults [3], the high cure rates achieved with standard therapy limit the number of paediatric patients available for clinical trials of novel drugs. Therefore, validated and predictive preclinical models of ALL are likely to become essential to prioritise new drugs for clinical trials if a significant improvement in survival and a reduction in the long-term side effects of conventional therapy are to be achieved. It is an open question whether preclinical testing in ALL will, in fact, predict how a drug performs in the clinic. In the past, preclinical models have been criticised for overestimating a drug’s efficacy, leading to disappointing clinical activity. It is timely, therefore, to critically review the attributes of currently available experimental models, to attempt to understand the reasons for past failures, and to summarise contemporary efforts aimed at the systematic preclinical evaluation of new drugs for the treatment of ALL. While the challenges to develop better treatments for both

* Barbara Szymanska and Hernan Carol contributed equally to this chapter. R.B. Lock (*) Leukemia Biology Program, Children’s Cancer Institute Australia for Medical Research, Lowy Cancer Research Centre, UNSW PO Box 81, Randwick, NSW 2031, Australia and University of New South Wales, Sydney, NSW 2031, Australia e-mail: [email protected] V. Saha and P. Kearns (eds.), New Agents for the Treatment of Acute Lymphoblastic Leukemia, DOI 10.1007/978-1-4419-8459-3_3, © Springer Science+Business Media, LLC 2011

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paediatric and adult ALL remain considerable, validated and predictive preclinical models are likely to play an essential role in meeting these challenges.

3.2  Historical Perspective Initial anti-cancer drug screening and discovery programs were more empirical in nature, much smaller in scale and proceeded slower compared to contemporary projects. They utilised poorly characterised tumour models, which typically involved mice bearing rapidly growing murine leukemias (e.g. L1210 and P388) against which randomly produced molecules with insufficiently defined modes of action were tested [4, 5]. The foundation for progressing with development of a particular anti-cancer drug was based on its ability to inhibit tumour cell proliferation in vitro and/or in vivo without prior delineation of its molecular or cellular targets. Over the past four decades, the substantial progress made in our understanding of mechanisms of tumour development, progression, and resistance to therapy has led to a new era of rational drug development, in which molecules are screened, or designed, for interaction with specific targets [6, 7]. This new dawn has resulted in an unprecedented expansion in the number of new therapeutic agents with potential clinical activity.

3.2.1  Success and Failure: l-Asparaginase and Cisplatin Prior to the initiation of the anti-cancer screening program by the National Cancer Institute (NCI, USA) in 1955, the development of chemotherapeutic agents was often fortuitous, as illustrated by the steps that guided the discovery of l-asparaginase (l-ASNase) and cisplatin [cisplatinum, cis-diamminedichloridoplatinum(II), CDDP]. In 1953, while investigating immunotherapy for lymphoma, John Kidd used guinea pig serum as a source of complement. He fortuitously discovered that the growth of subcutaneously transplanted lymphoma cell lines in mice and rats was inhibited by intraperitoneal administration of guinea pig serum alone [8]. This effect was species-specific, as treatment with sera from other sources, such as rabbit or horse, did not have the same effect. Furthermore, the effect of guinea pig serum was confined to lymphomas, with mammary carcinomas and fibrosarcomas unaffected [8]. From this original observation it took another 8 years for the active component of the serum to be identified as l-ASNase [9]. During the same period it was reported that murine leukemia cell lines required l-asparagine to sustain their growth in vitro [10]. Subsequently, l-ASNase isolated from Escherichia coli was shown to be as effective as guinea pig serum, which provided a more readily available source of the enzyme [11]. Data from the first clinical trials using partially purified enzyme from guinea pig serum [12] or E. coli derived l-ASNase [13, 14] were published 5–6 years after its identification. Following successful clinical trials

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l-ASNase was incorporated into paediatric ALL protocols, which contributed to a remarkable improvement in outcome [15]. Cisplatin and other platinum based compounds are examples of drugs that are not effective in ALL, although they are a main component of many solid tumour treatment regimens. They were discovered in the early 1960s by Rosenberg et al. [16] as a fortuitous observation of the alteration of the growth pattern of bacterial cultures. In vitro anti-cancer activity was later described against the Sarcoma 180 and the L1210 (leukemia) cell lines [17], but clinical trials with cisplatin reported high levels of renal and gastrointestinal toxicity. Cisplatin was tested in the 1970s in children with cancer not responding to conventional chemotherapeutic drugs [18, 19]. No responses in children with ALL were observed, in contrast to some individuals with solid tumours. Retrospective experimental evaluation of cisplatin has confirmed little evidence for activity against paediatric ALL (see Sect. 3.5 and [20]).

3.2.2  The NCI In Vivo and In Vitro Panels Following reports that demonstrated correlations between the efficacy of compounds against transplanted tumours and their clinical activity (reviewed in [21]), the NCI (USA) initiated a large-scale anti-cancer drug screening program in the mid 1950s, which was based on syngeneic transplantable murine leukemias. Originally only rodent models were used and the screening program included the L1210 leukemia cell line. Later, another murine leukemia cell line (P388) was included [22]. It was not until 1975 that the P388 model was selected as the initial screen, followed by a panel of transplantable tumours. In the 1980s it became evident that these early models had a limited ability to predict activity in humans, and they predominantly identified the DNA-damaging classes of anti-cancer agents [23]. Activity against a range of tumour histiotypes, rather than specific to a certain cancer, was also considered of high priority, possibly in the hope of identifying the anticancer “magic bullet”. With the view of improving the outcome of drugs with potential activity for solid tumour treatment, early in the 90s this pre-screening was substituted by a panel of 60 cell lines cultured in vitro (the NCI60 panel) [24]. For a comprehensive recent review on the gestation of and a recount of the main findings by the NCI60 human tumour cell line drug screening see Shoemaker [25]. While of obvious utility, the validity of this screening program has been questioned mainly due to the fact that the in vitro assay used is based on inhibition of cell growth and not on cell kill, which is unlikely to differentiate between cytostatic and cytotoxic drugs [26]. As a consequence of the need to summarise the output of complex experiments and large sets of data the “COMPARE” format of reporting was created for the NCI60 panel [27]. In this way a unique profile of activity can be generated for each drug. It was also discovered that drugs with similar mechanisms of action or similar targets showed similar COMPARE profiles [28], thereby enabling preliminary classification of new drugs with unknown mechanisms of action [29].

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3.3  Evaluation Criteria for Robust Preclinical Models Currently, the pathway of anti-cancer drug development is lengthy and costly, taking on average 8–10 years from the initial hypothesis to completion of Phase III clinical trials and to gaining regulatory approval, with an estimated cost of US$0.8–2.0 billion per drug [30, 31]. Furthermore, the number of anti-cancer agents that fail in the clinic far outweighs those that prove effective. During 1991–2000, the attrition rate of potential anti-cancer drugs that entered clinical testing was very high, with only 5% of agents gaining US FDA approval [32]. While the reasons for drug failure in the clinic are multifactorial, the increased use of predictive preclinical evaluation measures may significantly reduce this alarming rate of attrition. The value of any preclinical model will ultimately depend on its ability to accurately predict clinical response, and models, by definition, only approximate the clinical setting. Nevertheless, we consider that the following criteria should be among those desired when selecting a model system in which to evaluate any new anti-leukaemic drug: 1. Homologous cancer biology. Does the model accurately reflect the biology of human cancer and recapitulate the molecular and cellular events associated with the particular tumour histiotype? 2. Heterogeneity. ALL is biologically, genetically, phenotypically, and clinically heterogenous disease; a relevant model should reflect this heterogeneity. 3. Penetrance/take rate/reproducibility. Most, or preferably all, animals in an experimental cohort should develop cancer in a timely and reproducible fashion. 4. Disease monitoring. A model should be amenable to routine, reliable, reproducible, and cost effective methods of monitoring disease progression and drug responses. 5. Stringent endpoints for determining the effects of therapy should be clearly defined. 6. Responses to established drugs should reflect those encountered in patients. 7. Pharmacokinetics and pharmacodynamics. Differences in these parameters between the selected species/strain and humans should be accommodated, since increased host tolerance leads to overestimation of drug efficacy, and viceversa. The following section briefly compares attributes of some of the models available for preclinical drug testing.

3.4  Preclinical Models of ALL Several experimental models of ALL are available for preclinical testing of new drugs, and they have been extensively analysed and compared in several articles and reviews [33–35]. Each model has advantages and limitations, and suffers from unknown predictive power of clinical response. Two recent meta-analyses evaluated

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the predictive accuracy of preclinical testing: Johnson et al. [36] analysed the predictive power of xenograft models retrospectively for a set of 39 compounds which had both Phase II clinical trials and in vivo xenotransplantation data. It was found that those compounds that exhibited activity in at least one third of the xenograft models were more likely to have positive Phase II clinical trial outcomes. A similar study of results obtained by the Canadian NCI [37] found that xenograft models were predictive of Phase II clinical trial outcome in non-small-cell lung cancer and ovarian cancer but not in colon and breast cancer. A similar analysis has yet to be carried out for ALL.

3.4.1  In Vitro Experimental Models Cell lines established from ALL patient biopsy specimens have become essential tools to study many aspects of leukemia, and it is difficult to deny their relevance to cancer research [38]. Nevertheless, while cell lines are useful for a multitude of studies, it is well known that leukemia cells selected for autonomous in vitro growth have sustained additional genetic abnormalities not present in the primary disease state, p53 and Bax mutations being obvious examples [39, 40]. Moreover, it is difficult to reconcile dynamic in vivo drug exposures with the more static situation in vitro, although adjustments to in vitro culture conditions to achieve higher correlations with the results observed in vivo have been proposed [41]. The greatest utility for ALL cell lines in preclinical drug testing may lie in their use for the rapid identification of synergistic drug combinations, which can then be further validated using in vivo models.

3.4.2  In Vivo Experimental Models Autochthonous (“originating in the place where found”) models of cancer include spontaneously occurring neoplasms or tumours induced using a variety of viral or chemical carcinogens in rodents and other species of animals [42–44]. In general, these models have proven valuable in studies of carcinogen-induce tumorigenesis [45] and chemoprevention [43], although for the most part they have been replaced by genetically engineered models. With the advances in technologies that allow manipulation of the genome it has become almost routine to model human cancers via transgenic or knockout animals (e.g. via aberrant activation of an oncogene, or conditional knockout of a tumour suppressor gene) [33, 46]. Such models have contributed significantly to our understanding of cancer [47]. These models are thus well suited for testing targeted therapies and “proof-of-principle” research, in which novel agents are directed at specific molecular targets within a well-characterised biochemical pathway. Furthermore, these genetically engineered strains are immunocompetent and can therefore be used for preclinical evaluation of immunomodulating agents.

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Transgenic mouse models of haematological malignancies have also been generated, such as Em-myc mice, which develop aggressive leukemias and lymphomas when the c-myc gene is placed under the control of the immunoglobulin heavy chain enhancer (Em) [48, 49]. These types of models are useful for preclinical drug testing in leukemia, and deficiencies associated with variable penetrance and rates of cancer development can be overcome by transplantation of primary tumours into syngeneic wild-type littermates [50]. In a novel approach, several transgenic zebrafish models of ALL have been developed [51–54]. The work that led to the establishment of the transgenic model of ALL in zebrafish was pioneered by Langenau et al. [53] who over-expressed mouse c-myc fused to enhanced green fluorescent protein (EGFP) under the control of the rag2 zebrafish promoter. The transparency of zebrafish tissues allows direct imaging of cancer progression, in real time, making this model useful for studying tumorigenesis. The zebrafish has been widely utilised for assessing drug toxicity. There is some evidence of similar toxicity profiles to those of mammalian species [55] and it could be adapted for preclinical testing of chemotherapeutics. The development of human cancer xenograft models in immune-deficient mice represents a milestone in the progression towards more clinically relevant experimental models of cancer. The discovery of the nude (nu/nu), athymic mouse strain [56] and the subsequent successful propagation of human cancer cells in these mice [57] were instrumental in this process. Nude mice lack the Foxn1 gene and are unable to generate functional T cells [58]. However, in contrast to solid tumours, human ALL only engrafted with relatively low efficiency in nude mice even when injected intraperitoneally following irradiation [59], and residual immunity negatively affected tumour take rates [60, 61]. The discovery of the severe-combined immunodeficient (SCID) mouse strain, which lacks functional lymphocytes of both T and B lineage [62, 63], dramatically improved xenograft models of human ALL [64, 65]. Leukemia cell lines and patient biopsy samples inoculated intravenously into SCID mice manifested as systemic disease with human cells detectable in peripheral blood, spleen, and bone marrow [64]. Despite the success with using SCID mice, this strain does retain some ability to reject xenografts via their natural killer (NK), NK-T cells and macrophages, and complement system activity [66]. Immunosuppression with irradiation or drugs can improve take rates of tumours but only transiently as immunity recovers with time, and this can undermine the validity of drug efficacy studies [66, 67]. A more severely immunocompromised strain was generated by crossing SCID mice with the non-obese diabetic (NOD) strain to generate NOD/SCID [67, 68]. NOD/SCIDs have lower NK and macrophage activity than SCIDs, and they also have impaired complement system activation due to lack of C5. Human spleen and peripheral blood mononuclear cells engraft more efficiently in NOD/SCID than SCID mice [68]. Additional strains of immune-deficient mice have been generated with the aim of further improving engraftment of human haematopoietic cells, including NOD/SCID/b2mnull [69, 70] Rag2null/γcnull [71] and NOD/SCID/γcnull [72], all of which appear to be more deficient in NK cell activity than NOD/SCID.

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Initially, ALL xenografts were established by subcutaneous inoculation of cell lines or patient samples [61, 73–75]. While ectopic xenograft models have the advantage of relatively fast growth and accessibility, the site of tumour growth represents neither the primary nor the metastatic site of ALL, nor does it provide the appropriate microenvironmental niche for ALL cells, and therefore it may have little resemblance to the clinical disease. Most of these problems appear to be overcome by the development of orthotopic xenotransplantation models, which involve intravenous inoculation, leukemia cell homing to the bone marrow, and eventual infiltration of haematolymphoid organs [76, 77]. Orthotopic ALL xenograft models utilising patient biopsy specimens established in NOD/SCID mice fulfil most of the desirable criteria of preclinical models listed in Sect. 3.3, including that relating to disease heterogeneity when panels of xenografts are used [76, 77]. Moreover, monitoring of ALL progression and response to therapy is straightforward, and endpoints for determining drug efficacy can be clearly defined [76–78]. Nevertheless, limitations of these models include: intraspecies differences in the bone marrow microenvironment; that immune-based therapies can only be partially evaluated in immune-deficient hosts; and that the pharmacokinetics of a particular drug may differ between mice and humans.

3.5 Application of Preclinical Models of ALL for Drug Testing With the recent explosion in the number of new drugs that have the potential to show clinical activity against ALL, a central purpose of preclinical testing should be to prioritise those entities for the limited number of clinical trials that can be carried out. The aim would be to eventually incorporate a new drug into existing therapies to further improve their efficacy, minimise the likelihood of relapse, and limit toxicity. The following recommendations may assist in the process of ranking new drugs: 1. Stringent criteria, analogous to the clinical setting, should be developed to assess anti-leukaemic efficacy, and not be limited to in vitro cell killing or delay of disease progression in vivo. 2. Single-agent efficacy should be observed across several experimental models that represent the heterogeneity of the disease. Where a single ALL subtype is targeted, multiple models representative of that subtype should also be tested. 3. Single-agent activity should be observed over a broad concentration range (³5fold), and not only at the maximum tolerated dose (MTD) for in vivo studies, and the concentration × time (C × T) of drug exposure at which in vitro or in vivo anti-leukaemic effects are observed should reflect those achievable in the plasma of humans. 4. Only novel drugs with ³50% complete response (CR) rates across several models should be considered for further testing [79].

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5. While cell lines studies are a very relevant component of the drug development process, their role in preclinical testing may be more suitable to rapid screening of lead compounds and in vitro identification of synergistic drug combinations for subsequent in vivo verification. 6. The properties of in vitro and in vivo synergistic anti-leukaemic activity, but not normal tissue toxicity, with established drugs used in the treatment of ALL are highly desirable. The following sections review several of the novel drugs that have been subjected to preclinical testing using various ALL models, as single agents and in combination with established drugs. Each section culminates in a description of contemporary approaches to systematically prioritise new drugs for clinical trials in ALL.

3.5.1  Preclinical Testing of Drugs as Single Agents Over the past two decades, diverse in vivo models of leukemia have been used to highlight the efficacy of novel chemotherapeutic agents. A large proportion of these models involved leukemia cell lines engrafted either subcutaneously [74, 75, 80, 81], intraperitoneally [82], or intravenously [74, 83–87] into SCID mice, or occasionally nude mice [81]. Using these models the efficacy of a long list of drugs has been demonstrated, including: desoxyepothilone B [80], nucleoside analogues [82], topoisomerase I inhibitors [85, 86], a proteasome inhibitor [83], aminophylline [84], flavopiridol [74], laminin-derived peptides [75], and monoclonal antibodies against CD47 [87]. In vivo ALL models based on mouse cell lines inoculated intraperitoneally into BALB/c mice [88] or human cell lines transplanted intravenously into SCID mice, were also used to demonstrate the efficacy of a number of immunotoxin conjugates, which included anti-CD19-pokeweed antiviral protein [88–90], anti-CD19-genistein [91], and anti-CD7-pokeweed antiviral protein [92]. Recent studies more frequently used primary ALL patient samples, rather than cell lines, engrafted into NOD/SCID mice [93–96]. Treatment with the thalidomide analogue CC-4047 reduced tumour volume in mice engrafted with primary human ALL cells as a subcutaneous model, and decreased dissemination into the spleen of a systemic model [93]. Treatment with an anti-FLT3 monoclonal antibody increased the event-free survival (EFS) of mice engrafted with an ALL cell line, as well as decreased the engraftment of patient biopsy samples in an orthotopic model of the disease [94]. Transgenic mouse models have also been used to test various chemotherapeutic agents. The farnesyl transferase inhibitor SCH66336 and a FLT3 tyrosine kinase inhibitor demonstrated single agent activity in Bcr/Abl-positive P190 transgenic mice and transgenic mice with a constitutively active FLT3 internal tandem duplication, respectively [97, 98]. Em-ret transgenic mice, which constitutively express activated RET tyrosine kinase in B-lineage precursors and develop ALL between 3 and 8 months of life, responded to the mTOR inhibitor rapamycin [99].

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Taken together, the results cited above give the impression that a sufficient number of new drugs have been identified to successfully treat and cure all patients with ALL. This is clearly not the case, possibly due to the necessity to interpret the results in the context of the recommendations set out in the previous section. In fact, based on the attrition rate of drugs that make it to clinical trials, HD MTX

HD Ara-C/Asp

/wkxx44 VCR 1.5 mg/m22 /wk PDN 40 mg2/m/ddays 1-29 PEG-ASP 2500 IU/m2/wk x 4 DOX 60 mg/m2 day 1 ITT (Imatinib for Ph+)

CTX 440 mg/m22xx55 ETOP 100 mg/m2 x 5 (Imatinib for Ph+) - then: MTX 5 g/m2 over 24 hr with leucovorin rescue

Ara -C 3 g/m2 x 8 L-asp 6000 IU/m2 x 2 (Imatinib for Ph+)

Raetz, JCO 26.3971, 2008

Fig. 4.1  COG AALL01P2 “triple re-induction”

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prednisone for 4 weeks, and doxorubicin on Day 1 [31]. Block 2 consists of (1) a 5-day course of cyclophosphamide and etoposide beginning on Day 1, based on a 40% CR rate attained with ifosfamide and etoposide in children with refractory ALL [43], with replacement of ifosfamide by equitoxic dosing with the less nephrotoxic cyclophosphamide and (2) an intravenous high-dose methotrexate on Day 22 at 5 gm/m2 over 24 h with leucovorin rescue as employed in the ALL-BFM 90 protocol [44]. Block 3 is the Capizzi II regimen of sequential high-dose Ara-C and l-asparaginase, which demonstrated a 45% CR rate in advanced ALL [45]. Reinduction rates in AALL01P2 were promising, with second remission attained in 96% of late marrow relapses (LR; defined as relapse ³36 months from diagnosis) and 68% of early marrow relapses (ER; defined as relapse 10% included stomatitis (24%), transaminase elevations (17%), diarrhea (17%), neurologic toxicities (10%), constitutional symptoms, transient ­laboratory abnormalities (electrolytes, coagulation abnormalities and liver function tests),

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transient blood pressure perturbations, skin toxicity, and tumor lysis syndrome. These toxicities were designated as Exclusion Set A. Lestaurtinib toxicities have been previously assessed in adults and in pediatric neuroblastoma study NANT N2007-001. Toxicities associated with lestaurtinib included vomiting, anorexia, nausea, and transient transaminase elevations. These were designated as Exclusion Set B. In the POG-9407 study, most severe toxicities resolved within 7 days, with the exception of febrile neutropenia and infections. These were designated as Exclusion Set C. These exclusion sets were combined to develop the following DLT definition: Nonhematologic DLT: • A  ny Grade 4 nonhematologic toxicity that occurs after the first dose of lestaurtinib and is at least possibly related to lestaurtinib, with the following exceptions: –– Febrile neutropenia or infection. –– Constitutional symptoms (e.g., fatigue, fever, weight change). –– Metabolic/laboratory abnormalities that resolve to £Grade 2 within: • 14 days, for ALT/SGPT, AST/SGOT, alkaline phosphatase. • 7 days, for amylase, lipase, total bilirubin. • 48 h for all other laboratory abnormalities. –– Coagulation abnormalities (INR, PTT, or fibrinogen) that resolve to £Grade 2 within 48 h. • Any Grade 3 nonhematologic toxicity that occurs after the first dose of lestaurtinib, is at least possibly attributable to lestaurtinib, and results in omission or delay of the beginning of the subsequent course of chemotherapy for greater than 7 days, with the following exceptions: –– Febrile neutropenia or infection. –– Mucositis or diaper area skin breakdown must result in omission or delay of the beginning of the subsequent course of chemotherapy for greater than 14 days to be considered a DLT. Hematologic DLT: No hematologic toxicity will be considered a DLT while a patient is receiving scheduled doses of lestaurtinib. After completion of a lestaurtinib course, persistent Grade 3 or greater neutrophils and/or platelets that result in a greater than 21-day delay in the start of the following course of chemotherapy will be considered a DLT, unless the delay in neutrophil or platelet recovery is due to another clearly identifiable factor such as relapse or myelosuppressive infection. 2. Proteasome inhibition for children with relapsed ALL:  The proteasome inhibitor bortezomib is being tested in a COG pilot phase II clinical trial (AALL07P1) that uses the same reinduction platform as the historical control trial AALL01P2 (9).

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Both nonhematologic and hematologic toxicities for the historical control study have been well characterized (Table 4.1), including the average time to ANC and platelet recovery. Although severe toxicities in the historical control trial were quite frequent, few toxicities (with the exception of infection) resulted in delay in therapy administration beyond 7 days. The DLT definition for AALL07P1 is summarized below: Nonhematologic DLT • Any Grade 4 nonhematologic toxicity that occurs after the first dose of bortezomib and is at least possibly attributable to bortezomib, with the following exceptions: • Any Grade 3 or 4 nonhematologic toxicity that occurs after the first dose of bortezomib is at least possibly attributable to bortezomib and results in omission or delay of the beginning of the subsequent course of chemotherapy for greater than 7 days, with the exception of the following. • Fever or infection • Gastrointestinal symptoms (anorexia, nausea, vomiting, dehydration, mucositis) • Constitutional symptoms (fatigue, anorexia, malaise) • Hypofibrinogenemia • Metabolic/laboratory abnormalities that resolve to 5 pmol/mg protein showed downregulation of Bcl-2 mRNA in bone marrow [18]. Oblimersen has potent activity as a single agent against imatinib-resistant Bcr-Abl-positive AML cell lines grown as subcutaneous xenografts in nude mice and is able to sensitise these cells to apoptosis induced by imatinib, cytarabine, daunorubicin and etoposide [19]. The combination of imatinib and oblimersen against imatinib resistant CML was studied in the Cancer and Leukemia Group B (CALGB) study 10107. Oblimersen was given as a continuous intravenous infusion over 10 days every 3 weeks, with daily imatinib, at doses of 4 mg/kg/day oblimersen and 600 mg daily imatinib, 7 mg/kg/day oblimersen and 600 mg daily imatinib and

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7  mg/kg/day oblimersen and 800  mg daily imatinib. Twenty-one patients were treated without significant toxicity. Six patients achieved complete haematological response, with one also achieving complete cytogenetic response. However, the aim of the study was to achieve a reduction of more than 30% in the number of Bcr-Abl-positive metaphase cells in 20% of patients, and thus the combination was not deemed to be a success [20]. Antisense oligonucleotides to Bcl-2 specifically inhibit the expression of Bcl-2 mRNA in chronic lymphocytic leukemia cell lines in vitro and are able to decrease Bcl-2 protein levels and induce apoptosis in primary leukemic cells as well as sensitising CLL cells to dexamethasone, fludarabine, chlorambucil and rituximab [21–23]. In phase I–II study in 40 patients with relapsed or refractory CLL at doses from 3 to 7 mg/kg/day as a 5-day continuous infusion, administration of oblimersen was limited by a cytokine release syndrome needing dose reduction from 7 mg/kg/ day down to 3 mg/kg/day. In the phase II phase of this study at 3 mg/kg/day as a continuous infusion for 5 days, there was little toxicity, and two partial responses were seen in 26 evaluable patients, lasting from 2 to 6 months. Thirteen patients had stable disease for more than 2 months, and 11 patients had progressive disease by the end of the second cycle of oblimersen [24]. In a large multicentre international phase III study, the addition of oblimersen to fludarabine and cyclophosphamide was of benefit. Two hundred and forty-one patients with CLL who had received at least one previous course of fludarabine containing chemotherapy were randomised to 28-day cycles of fludarabine 25 mg/m2/day with cyclophosphamide 250 mg/m2/ day for 3 days, with or without oblimersen 3  mg/kg/day as a 7-day continuous infusion beginning 4 days before chemotherapy. Twenty patients (17%) in the oblimersen group achieved CR or nodular PR (nPR), compared to eight patients (6%) receiving chemotherapy alone (and this difference was statistically significant). Maximum benefit from the addition of oblimersen was seen in those patients who had a partial or better response to fludarabine for at least 6 months. In this group, the CR/nPR rate was 25% with oblimersen compared to 6% without. At a minimum of 24 months of follow-up, 5 of 20 patients receiving oblimersen had relapsed compared to six of eight in the chemotherapy-only group, and median duration of response was 20 months in the chemotherapy-only group and greater than 31 months in the oblimersen group, which difference was highly significant [25]. In a phase II study in patients with relapsed multiple myeloma in combination with thalidomide and dexamethasone, oblimersen showed encouraging efficiency. Thirtythree patients received oblimersen as a 7-day continuous infusion at doses from 5–7 mg/kg/day, in combination with 4 days of dexamethasone and continuous thalidomide. Cycles were given at 21-day intervals for three cycles and then every 35 days with a reduced dose of dexamethasone. Patients with continued clinical response could receive up to 2 years of therapy. A median of eight cycles of therapy per patient was given. The most frequent toxicities were myelosuppression, which was manageable, and peripheral neuropathy, which required dose reduction of the thalidomide. Seventythree percent of patients had documented responses, including 2 CRs, 4 near CRs and 12 PRs. Median duration of response was 13 months, suggesting that this combination is safe and effective in patients with refractory and relapsed multiple myeloma [26].

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Bcl-2 is expressed in most EBV-associated lymphoproliferative disorders. Oblimersen is able to downregulate Bcl-2 protein, inhibit proliferation and induce apoptosis in EBV immortalised lymphoblastoid cell lines (LCL) in vitro. Although oblimersen was able to prevent the establishment of tumours by EBV-immortalised LCLs in SCID mice when given on the first day after tumour inoculation, it was not able to prevent the growth of established tumours, although it did significantly prolong the survival of these mice in comparison with nonsense oligonucleotide treatment [27]. When the humanised monoclonal anti-CD20 antibody rituximab was combined with oblimersen, there was significant enhancement of antiproliferative effect, and enhanced apoptosis in EBV transformed LCLs in vitro. In the SCID mouse model of human lymphoproliferative disease, the combination of rituximab and oblimersen led to significantly prolonged survival in comparison with either therapy alone, and the majority of animals receiving this combination had no detectable tumour [28]. Pre-clinical experiments in B-cell NHL cell lines have demonstrated that combining oblimersen with the proteasome inhibitor bortezomib enhances its growth inhibitory effect both in  vitro and against xenografts in SCID mice. The combination of oblimersen followed by bortezomib and cyclophosphamide was statistically superior to other combinations and led to a number of complete remissions [29]. In a phase II study in B-cell NHL, significant responses were seen in combination with rituximab. Forty-eight patients with recurrent or refractory B-cell NHL, of whom 70% had received prior rituximab, were treated with oblimersen at 3 mg/kg/day as a 7-day continuous infusion for alternate weeks in a 6-week block, in combination with 375 mg/m2 of rituximab given on days 3, 8, 22, 25, 29, 36. Of the 42 evaluable patients, ten achieved CR and eight achieved PR, giving an overall response rate of 42%. The combination was well tolerated with myelosuppression, the main toxicity seen. Thus, oblimersen can be safely administered in combination with rituximab and bortezomib and offers potential therapeutic benefit in B-cell NHL [30]. Infant acute leukemias often contain the MLL gene rearrangement, most commonly caused by the (4:11) translocation. This has been associated with cytotoxic drug resistance and is correlated with poor prognosis [31]. In  vitro data suggest that oblimersen is effective in reducing Bcl-2 mRNA and protein levels in t(4:11) MLL-rearranged cell lines and not only induces apoptosis by itself but also sensitises these cells to doxorubicin, 6-thioguanine, etoposide and cytarabine [32]. Oblimersen has completed phase 1 study in combination with doxorubicin and cyclophosphamide in children with relapsed solid tumours. Thirty-seven patients were enrolled, but eight were not evaluable for toxicity. The range of diagnoses included Ewing sarcoma, osteosarcoma, Wilms tumour and neuroblastoma. Oblimersen was given as a continuous 7-day infusion at doses from 3 to 7 mg/kg/ day. Doxorubicin 30 mg/m2/day and cyclophosphamide 500 mg/m2/day were given on days 5 and 6. The main toxicities were haematological, and these could be managed by dose reduction of the doxorubicin and cyclophosphamide. The MTD was 7 mg/kg/day oblimersen in combination with these agents. One patient with Ewing sarcoma had a partial response, and eight patients had prolonged stable

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disease, receiving a median of seven courses. Seventy-three percent of evaluable patients had a reduction in Bcl-2 protein level in PBMCs by day 5 or 6 of the oblimersen infusion [33].

7.4 Bcl-2 Small-Molecule Inhibitors 7.4.1 HA14-1 HA14-1 is a small non-peptide organic ligand that binds to the hydrophobic surface pocket of Bcl-2 that is required to mediate the protein–protein interactions between Bcl-2 family proteins. HA14-1 was discovered using a computer screening process that models the ligand structure needed to bind this pocket. HA14-1 is able to induce apoptosis in HL60 AML cells at micromolar concentrations in a caspasedependent fashion that involves loss of mitochondrial membrane potential [34] and activation of the mitochondrial pathway of apoptosis. HA14-1 is able to induce apoptosis in a range of haematopoietic cell lines, including ALL, AML, CML, histiocytic lymphoma and multiple myeloma. Sensitivity to HA14-1 across this panel of cell lines correlated with expression of Bcl-2; cell lines showing the lowest Bcl-2 expression were the least sensitive to HA14-1. HA14-1 also induced apoptosis in primary AML blasts derived from two separate patients and was relatively less toxic to normal bone marrow progenitor cells. HA14-1 was also able to sensitise lymphoblastic leukemia cells to cytarabineinduced apoptosis [35]. HA14-1 induced apoptosis in primary CLL cells with an EC50 of less than 50 mM in 26 of 36 patient samples, as well as in CD19-positive B cells from patients with mantle cell lymphoma and splenic marginal zone lymphoma. HA14-1 was also able to induce apoptosis in CLL cells with p53 mutations or loss of ATM [36]. In multiple myeloma cell lines, HA14-1 is able to enhance apoptosis induced by the proteasome inhibitor bortezomib (Velcade®), which has been one of the most promising novel agents against this traditionally very chemo-resistant malignancy. This enhancement of apoptosis by HA14-1 was only seen when multiple myeloma cell lines were exposed to bortezomib for 10 h before exposure to HA14-1 and not when the two agents were given simultaneously, nor when HA14-1 was given before bortezomib, and could not be blocked by IL-6, well documented as a survival factor for MM cells [37]. Similar interactions between these agents were seen in dexamethasone-resistant multiple myeloma cells and between HA14-1 and an alternative proteasome inhibitor MG132. Formal analysis demonstrated that this interaction was synergistic. The combination of bortezomib and HA14-1 produced a dramatic increase in all markers of activation of the mitochondrial pathway of apoptosis, as well as in reactive oxygen species (ROS), which was abrogated by co-treatment of cells with the free radical scavenger L-NAC, which also reduced the loss of mitochondrial membrane potential. The combination of bortezomib and

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HA14-1 produced a marked activation of JNK, which was blocked by the JNK inhibitor SP600125, which also significantly reduced bortezomib/HA14-1-induced apoptosis, implying that both ROS and JNK activation play a role in bortezomib/ HA14-1-induced apoptosis in MM cell lines. Constitutive mitogen-activated protein kinase (MAPK) signalling is frequent in primary AML blasts and promotes AML blast survival [38]. In AML cell lines with high constitutive MAPK activity, the simultaneous inhibition of the MAPK pathway with the MEK inhibitor PD184352 and treatment with HA14-1 resulted in a dramatic decrease in cell viability that was not observed in an AML cell line without constitutive MAPK activation. The combination increased loss of mitochondrial membrane potential and caspase activation, and inhibition of MAPK specifically inhibits the expression of survivin in AML cells with constitutive MAPK activity. The interaction between HA14-1 and the MEK inhibitor in AML cells was synergistic in three different fixed ratio combinations. Simultaneous exposure to PD184352 significantly enhanced the colony-inhibiting effect of HA14-1 against primary AML samples [39]. Macroautophagy (usually referred to as autophagy) is a tightly regulated lysosome dependent pathway that results in the formation of autophagosomes around cellular organelles, and their subsequent degradation. It is usually regarded as a cellular survival mechanism under conditions of nutrient deprivation. However, there is increasing evidence that autophagy may represent an important mode of cell death distinct from apoptosis in certain situations [40]. Anti-apoptotic Bcl-2 family proteins have been suggested to inhibit autophagy as well as apoptosis, through their interaction with the protein Beclin 1 [41]. However, data are also beginning to emerge to suggest that inhibition of steroid-induced apoptosis in lymphocytes by Bcl-2 over-expression leads to induction of autophagy instead and may be an important resistance mechanism [42]. Inhibition of Bcl-2 by HA14-1 induces both apoptosis and autophagy in L1210 murine leukemia cells, and inhibition of autophagy with the PI3K inhibitor wortmannin enhanced the induction of apoptosis, whilst blocking apoptosis with the caspase inhibitor zDEVD-fmk increased autophagy [43]. The induction of autophagy in L1210 cells by the novel anticancer agents XK469 or SH80 does not prevent the rapid induction of apoptosis by HA14-1, so at least in this model pre-existing autophagy does not reduce the efficacy of Bcl-2 targeting therapeutics [44].

7.5 Obatoclax (GX15-070) Obatoclax is a hydrophobic cycloprodigiosin-derived BH3 mimetic identified by chemical library screening. Unlike ABT-737, obatoclax is able to inhibit the binding of BH3 peptides to a wide range of Bcl-2 family proteins, including Mcl-1 and A1 [45]. The hydrophobic nature of the compound means that assays done in aqueous phase tend to underestimate the binding activity of obatoclax. An in silico docking algorithm predicts that obatoclax binds in a hydrophobic pocket at one end

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of the Bcl-2 BH3 binding groove, which would be in close proximity to a lipid bilayer in membrane integrated Bcl-2, which would thus facilitate the entry of obatoclax to the BH3 binding groove in vivo [46]. Pre-treatment of isolated mitochondria with obatoclax in nanomolar concentrations prevented the formation of dimers between Bak and Mcl-1 and the ability of obatoclax to induce apoptosis is dependent upon the presence of Bax or Bak. The ability of obatoclax to inhibit the binding of Mcl-1 to Bak/Bax allows it to function in concert with ABT-737, and the combination of the two agents was able to induce apoptosis in Mcl-1 over-expressing KB oral carcinoma cells, to the same extent as ABT-737 and Mcl-1 siRNA. Obatoclax is also able to overcome Mcl-1-mediated resistance to the proteasome inhibitor bortezomib (Velcade®) in multiple myeloma cells [46]. CLL is the most common leukemia in the developed world and is characterised by the presence of large numbers of CD5-positive B cells, which tend to express high levels of anti-apoptotic Bcl-2 family proteins that contribute to relative resistance to cytotoxic chemotherapy. Obatoclax induces apoptosis in B cells derived from 9 of 11 CLL patients with an EC50 of 1.7 mM, and showed additive toxicity with fludarabine and chlorambucil in cells derived from five of these nine patients [36]. In a separate study of cells derived from 20 CLL patients, a 40-h treatment with obatoclax induced apoptosis with the same EC50, and all patients showed response to obatoclax, despite the presence of known high-risk genetic variables/genotypes such as deletions of chromosome 11q and 17p [47]. In these CLL cells, obatoclax induces the dissociation of Mcl-1 from Bak and the release of Bim from Bcl-2, and this leads to the loss of mitochondrial membrane potential within 3 h of exposure to obatoclax. CLL cell lines transfected with mutant Bcl-2 that mimics the phosphorylation of Bcl-2 on serine 70 were more resistant to obatoclax than wildtype cells, and obatoclax was less able to release Bim from this phosphorylated form of Bcl-2. Blocking the phosphorylation of Bcl-2 on serine 70 with the ERK inhibitor PD98059 enhanced the toxicity of obatoclax in CLL cells, and indeed, the two agents were highly synergistic in combination. Increasing the amount of Bcl-2 phosphorylated at serine 70 with okadaic acid treatment significantly decreased the cytotoxicity of obatoclax. Obatoclax was synergistic with bortezomib in these CLL cells, and this synergy was increased further by reducing pBCL-2 (ser70) levels by pre-treatment with PD98059 [47]. In 15 of 16 multiple myeloma cells, submicromolar concentrations of obatoclax induced significant reductions in cell viability with a mean EC50 of 246 nM. Obatoclax was also effective against dexamethasone- and melphalanresistant MM cell lines. The presence of IGF-1 did not affect cellular response to obatoclax, and IL-6 had only modest protective effect. Importantly, obatoclax had minimal toxicity against bone marrow stem cells. In MM cell lines, obatoclax causes the dissociation of Mcl-1 from Bak and induces apoptosis via the mitochondrial pathway. Obatoclax is also able to induce apoptosis at nanomolar in primary MM cells from 8 of 14 patients without toxicity to normal peripheral blood lymphocytes. Obatoclax was synergistic with dexamethasone, and additive with melphalan and bortezomib, when given before the proteasome inhibitor [48].

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Micromolar concentrations of obatoclax inhibit the growth of AML cell lines by the induction of apoptosis, as well as by mitotic arrest. As in MM cells, obatoclax causes the dissociation of Bak from Mcl-1 but in addition efficiently caused the release of Bim from Bcl-2 and Mcl-1. Obatoclax was synergistic with ABT-737 in the ABT-737-resistant AML cell line OCI-AML3 and also synergised with cytarabine in a schedule-independent fashion. Micromolar concentrations of obatoclax were also able to induce apoptosis in primary AML samples and reduce their colonyforming ability without affecting that of normal bone marrow [49]. Obatoclax has now completed early-phase clinical trial in adults against CLL and refractory haematologic malignancies including AML, ALL, CML, CLL and myelodysplastic syndrome. In advanced CLL previously treated with a median of 4 chemotherapy regimes including fludarabine, 26 patients received a total of 74 cycles of obatoclax thrice weekly. Doses were 3.5–14 mg/m2 as a 1 h infusion or 20–40 mg/m2 as a 3 h infusion. The maximum tolerated dose was 28 mg/m2 over 3  h every 3 weeks. Dose-limiting toxicities were all neurological and included somnolence and euphoric mood at the time of the infusion. Biological effects of obatoclax were observed in 12 of 16 patients with serial samples, where activation of Bax and Bak in peripheral blood mononuclear cells persisted beyond the end of the infusion. A dose-related increase in circulating oligonucleasomal DNA–histone complexes was also observed, and 18 of 26 patients had a reduction in lymphocyte count. One patient had a PR, and sustained improvements in haemoglobin and platelet levels were seen across all dose levels. The biological effect and lack of conventional toxicity of obatoclax were very encouraging for future study [50]. In the second Phase I study, 44 patients with a range of diseases, which were mostly refractory AML (n = 25) or myelodysplastic syndrome (n = 14), received 24 h infusions of 7–40 mg/m2 of obatoclax every second week. After dose escalation was complete, patients received 20–28 mg/m2 over 24 h every week, and then 20–28 mg/m2 over 24 h for 2, 3, or 4 days every second week. Three hundred and six infusions were given in total with a median of 5 per patient (range 1–35). As with the other study, CNS effects were the most common with somnolence, dizziness, fatigue, euphoric mood and gait disturbance being observed in 34–43% of patients; patients reported feeling drunk. As before, these symptoms occurred during the infusion and ceased once the infusion was complete. Little haematologic toxicity was observed, and in general the drug was well tolerated. One patient with AML had CR, and 3 of 14 patients with MDS had haematologic improvement [51].

7.6 ABT-737/263 Technological advances have allowed a high-throughput NMR-based method [52] to be used to screen a chemical library to identify molecules that bind to the BH3binding pocket of Bcl-xL [53]. Modification of the compound 4¢-Fluoro-biphenyl4-carboxylic acid identified by this screen resulted in the formation of ABT-737. ABT-737 binds with high affinity to Bcl-2, Bcl-xL and Bcl-w (Ki 1nM), but does

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not bind to Mcl-1 or A1. In biological assays, ABT-737 functioned like a Bad BH3 protein; by itself, it was unable to cause the release of cytochrome c from isolated mitochondria, but it was able to prevent either Bcl-2 or Bcl-xL from inhibiting the release of cytochrome c by a Bid protein, and this function was dependent upon the presence of either Bax or Bak. Thus, ABT-737 does not activate Bak or Bax by itself, but rather prevents Bcl-2 or Bcl-xL from sequestering the activating BH3only proteins like Bid. ABT-737 disrupts a Bcl-2 family protein–protein interaction and displaces a GFP-tagged BH3-only protein from Bcl-xL in intact cells. ABT-737 is synergistic with both cytotoxic chemotherapy (etoposide, doxorubicin, cisplatin, paclitaxel) and radiotherapy in a range of cell types. As a single agent, ABT-7373 was potent against both small-cell lung cancer (SCLC) and lymphoid cell lines. ABT-737 was cytotoxic against t(14:18) containing lymphoma cell lines and primary patient-derived follicular lymphoma cells and significantly improved survival in a xenograft model of follicular lymphoma. Potent activity of ABT-737 with IC50 150% response Response < 150% No response T-cell:  ALL-8, ALL-16 B-cell precursor:  ALL-2, ALL-3, ALL-4 (PH+), ALL-7, ALL-17, ALL-19 Diagnosis:  ALL-3, ALL-4, ALL-7, ALL-16, ALL-17 Relapse:  ALL-2, ALL-8, ALL-19 Vcr vincristine; Cpm cyclophosphamide; DDP cisplatin; Bort bortezomib; Rpa rapamycin; Dasat dasatinib

controls and cisplatin as a negative control for pediatric ALL. Data for five drugs are depicted. Dasatinib shows most activity in a Ph+ ALL cell line. ABT 263, a bcl-2 inhibitor, shows most activity in T-cell ALL lines. Curiously, none of the new agents shows as much activity as our old standbys, cyclophosphamide and vincristine, themselves inadequate for relapse patients.

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Clinical value in other cancers and populations (i.e., “paraclinical” data) assures continued drug availability and improve prospects. Agents derived from an understanding of leukemia biology rather than high throughput screening in unvalidated “models” may prove more productive (see Fig. 15.2b). An understanding of the critical role of glucocorticoids in ALL and the pharmacokinetic advantages of dexamethasone [41] led to successful trials in newly diagnosed patients. An understanding of the role of BCR-ABL in Ph+ leukemia led to imatinib [42, 43]. In successive patient cohorts, the AALL0031 trial added more days of imatinib treatment to an intensive antileukemic platform for newly diagnosed patients [23]. While the aggressive platform alone showed no advantage over past efforts, the addition of imatinib resulted in a striking improvement in outcome. An understanding of imatinib resistance and tyrosine kinase domain mutations in chronic myelogenous leukemia next led to dasatinib [44, 45]. One looks to the day when some understanding of the molecular mechanisms of treatment failure will guide selection of agents for known, validated targets, rather than indiscriminate screening of candidate agents in various unvalidated “models” with secondary exploration of likely mechanisms for the apparently active compounds. If a “model” is not validated, what does it model? Simultaneously, means are required to identify the patient population where a specific resistance mechanism operates. Observations to date point to the simultaneous emergence of resistance to a variety of putatively non-cross-resistant agents [9]. However, agents with dissimilar mechanisms of action likely share common cell death pathways, which may prove to be the crucial bottleneck. Agents that enhance apoptosis by inhibiting BCL-2 [46, 47] or survivin [48], by lowering glutathione [49–51], by raising ceramide [52, 53], or by directly affecting mitochondria [54] may deserve special interest. Experience with targeted agents to date stresses the importance of target validation [55]. A cancer may proliferate independently of an overexpressed gene. Targeted agents often have effects beyond their putative targeted action [56]. Resistance mechanisms may be diverse and several distinct mechanisms may operate in various subclones in the same patient, above or below any threshold of detection. These considerations again stress that success may be more likely for patients with newly diagnosed disease than for patients with further evolved relapsed disease. Knowledge of drug pharmacology is also critical. Dexamethasone is less protein bound than prednisolone and provides better CNS levels [41]. Penetration may also be better for other, less well-recognized compartments [57]. Specific activity has been controversial but the most recent data suggest that dexamethasone is about 6–7 times more active than prednisolone in  vitro in keeping with the commonly accepted 6–7:1 clinical activity ratio [58]. Five randomized trials are depicted in Table 15.4. Two trials with prednisone and dexamethasone ratios of 7.5:1 and 10:1 show no advantage for dexamethasone [59, 60]. Three trials with ratios of 6.7, 6.1, and 6 find a statistically significant EFS advantage for dexamethasone [8, 21, 22]. BFM reports that replacement of 21 days of prednisone with dexamethasone

318 Table  15.4  Dexamethasone versus prednisone in childhood 21, 22, 59, 60] Dexamethasone Prednisone Study Population n mg/m2 CCG SR 1,060 6 40 Japan SR 231 8/6 IR 128 60/40 MRC All 1,603 6.5 40 BFM All 3,655 10 60 6 EORTC All 1,853 60 SR standard risk; IR intermediate risk

P.S. Gaynon and T.M. Harned acute lymphoblastric leukemia [8,

Ratio 6.7 7.5 6.1 6 10

EFS (%) 85 77 84 81 84 76 84 79 82 82

P value 0.002 0.625 0.01 0.008 0.94

resulted in a 1/3 reduction in relapses and an improvement in EFS, albeit with increased mortality (1.4 vs. 0.5%) in induction. Results show no advantage in ­survival to date except in the T-cell subset. A change in one agent in induction resulted in an improvement in 6-year EFS, a paradigm for the potential of “new” agents in newly diagnosed patients.

15.4 Right Accompanying Therapy, Right Dose, and Right Schedule in the Right Trial A useful test of an agent requires the proper agent be tested in the proper population and the proper dose and schedule with the proper accompanying therapy (Table 15.5). Proper controls are also mandatory. Phase III represents a candidate agent’s critical definitive test. A once-failed agent may not get a second chance. Drugs are used in combination in the treatment of childhood ALL. A drug may be active alone but adds nothing in combination. A drug may have no single-agent activity, e.g., leukovorin, but contribute when used in the proper sequence and combination, e.g., leukovorin fluorouracil [61]. Novel treatment elements must enhance or replace present elements. Ifosfamide has striking single activity in relapsed rhabdomyosarcoma [62] but offered no advantage when substituted for cyclophosphamide [63]. The best use of an agent requires the “right stuff” (Table 15.5). Ideally, some disease-specific activity data seem important prior to committing to a multiyear “definitive” randomized trial. The best therapy is the proper control in phase III trials. POG 9404 added methotrexate 5  g/m [2] to a DFCI platform for T-cell ALL [64]. Whole-brain ­irradiation was prudently delayed for 17 weeks in the experimental arm to allow for intravenous methotrexate and avoid leukoencephalopathy. However, radiation was

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Table 15.5  The right stuff [9] Right drug Right target Right disease Right population Right context Right schedule Right dose

also delayed in the bowdlerized “control” regimen with no clinical imperative, and outcomes were 15% points worse than the DFCI experience. In clinical trials, the experimental arm often elicits hope and enthusiasm. The control arm may lack zealous defenders and lie vulnerable to various supposedly “harmless” untested modifications. The Children’s Cancer Group first tested a “novel” agent, dexamethasone, in CCG-1922, where we substituted dexamethasone for prednisone in induction and maintenance [8]. The control arm kept dexamethasone in delayed intensification as the best therapy despite appeals for a “cleaner” pure dexamethasone versus pure prednisone comparison. The critical study question was the value of dexamethasone in induction and maintenance in the context of the best known treatment, not pure dexamethasone versus pure prednisone as our best therapy already included dexamethasone in delayed intensification. With better outcomes, the number of patients who must be subjected to a new intervention to earn the opportunity to cure one additional patient, i.e., the number needed to treat (NNT) has increased geometrically. Many novel interventions fail but increase morbidity with no compensatory gain [65]. Identification of patient subsets at higher risk of treatment failure balances potential harms and benefits and decreases NNT. Treatment intensity now approaches the limits of feasibility and insights into the biology of leukemia have led to promising candidate agents targeted to specific leukemic subsets. In parallel with identification of agents to address the specific ­mechanisms of treatment failure, we must develop methods to determine the patients in which these mechanisms likely operate. More effective, not necessarily more ­intensive, therapy is the goal.

15.5 Clinical Trials in the Children’s Oncology Group In the Children’s Cancer Group, dexamethasone was arguably the first new agent tested in newly diagnosed patients [8]. An immunotoxin, B43-PAP [66, 67], was examined briefly in newly diagnosed higher risk B-precursor ALL with a slow initial response to therapy on CCG-1961 [12]. Drug supply problems aborted the study and pose a challenge for any novel agent.

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Table 15.6  New agents in clinical trial in primary treatment of childhood ALL Preclinical Human toxicity Human “paraclinical”a Disease-specific In vitro Xenograft data activity data Agent activity data Dasatinib + + Adult + + Nelarabine + Pediatric adult + + Lestaurtinib + Adult + Clofarabine + Pediatric adult + + a  Paraclinical-response data in other human cancers and populations

The Children’s Oncology Group, successor to CCG and POG, studied imatinib successfully in newly diagnosed Ph+ ALL [23]. The COG ALL Committee has followed up on the success with imatinib and pursued novel agents in newly diagnosed patients with energy (Table  15.6). Cytogenetic/molecular subsets such as Ph+ ALL and infants with MLL gene rearrangements and higher-risk (HR) T-cell and B-precursor subsets have substantial risk of relapse and potential shared vulnerability. AALL0622 substitutes dasatinib [45, 68] for imatinib on an intensive AALL0031 chemotherapy platform for Ph+ ALL. AALL0434 adds nelarabine [32, 33] to the COG “augmented BFM platform” [29]. AALL0631 adds lestaurtinib [69, 70] to an intensive chemotherapy platform [71] for infants with MLL rearrangements. AALL0622 Ph+ ALL trial employs historical controls, while other trials include randomization after completion of a feasibility phase. Future plans include a trial of clofarabine, cyclophosphamide, and etoposide [72, 73] in newly diagnosed HR B-precursor ALL patients, who are MRD-positive at the end of induction in the successor to the current trial, AALL0232.

15.5.1 Dasatinib Dasatinib is a second-generation tyrosine kinase inhibitor with known activity in CML and Ph+ ALL [74]. As with imatinib, responses after relapse are common but transient. Dasatinib has greater tyrosine kinase activity than imatinib. Only the T315I mutation is resistant to dasatinib. Ottman et al. found that the single agent dasatinib induced complete cytogenetic remission in 21/36 imatinib-resistant or -intolerant CML patients [68]. None of the 6 patients with the kinase domain ­mutation, T315I, had a response. AALL0622 substitutes dasatinib for imatinib on the AALL0031 platform.

15.5.2 Lestaurtinib Lestaurtinib (CEP-701) is an orally active small-molecule inhibitor of several receptor tyrosine kinases, with specificity for the tropomyosin receptor kinases TrkA, TrkB, and TrkC and Fms-like tyrosine kinase 3 (FLT3) [69, 75]. AALL0631

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rests heavily on in vitro data showing major impact on infant ALL cell lines and patient samples with MLL rearrangements where FLT3 is consistently overexpressed though rarely mutated [76]. Cytotoxicity depended strongly on schedule. Lestaurtinib following chemotherapy had synergistic effect, while simultaneous administration was additive, and chemotherapy following lestaurtinib was antagonistic. Regrettably, no clinical data in adult ALL or infant ALL are available. Preliminary reports show a whiff of value for lestaurtinib in adult AML with FLT3 overexpression and internal tandem duplication [77].

15.5.3 Nelarabine Nelarabine, an ara-G prodrug, provided a 50% CR rate in first relapse T-cell ALL [32]. Curiously, little or no preclinical or clinical data are available for nelarabine in combination. A pilot trial inserted nelarabine in a BFM platform with promising preliminary results [78]. On AALL0434, “naked” nelarabine is being inserted on the augmented BFM platform [29] prior to each cyclophosphamide, cytarabine, and thiopurine pulse and in early maintenance for higher risk T-cell patients, with ­modest erosion of platform intensity.

15.5.4 Clofarabine The Children’s Oncology Group trials, CCG-1882, CCG-1961, and CCG-1991 highlight the importance of the first 6 months of post induction intensification [10, 11, 29]. Higher risk patients receive three 4-week blocks including cyclophosphamide, cytarabine, and thiopurine corresponding to BFM “Protocol IB and IIB” in the first 7 months of therapy [78, 79]. These blocks were first introduced in the BFM 70 study. CCG-105 randomized standard-risk patients to receive or not to receive Protocol IB and found no advantage [13]. An AIEOP trial omitted Ib and noted worsening outcomes [80]. A candidate regimen to test against Ib/IIb has long been sought. Clofarabine is a third-generation adenosine analog. In addition to effects on ribonucleotide reduction, incorporation into DNA and RNA, and interference with DNA repair, clofarabine also targets the mitochondria directly, inducing apoptosis in both resting and dividing cells [81]. The combination of clofarabine, cyclophosphamide, and etoposide has a substantial CR rate in second and subsequent relapse [72] and seems poised for a test to see whether this block may replace the BFM Ib and IIb blocks in newly diagnosed patients. Fine-tuning of this “block” from a “remission or bust” induction block to one component of multiblock therapy where subsequent therapy requires prompt predictable count recovery is critical.

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15.6 Conclusion Treatment is the most important prognostic factor. As with T-cell and mature B-cell ALL, and now possibly with Ph+ ALL, better primary treatment offers a better prospect of cure for former high-risk subsets. Leukemia is oligoclonal and evolves with each recurrence. Predominant leukemia blast population may hide rare ­subclones that ultimately determine clinical outcome. Understanding of the ­disease-specific mechanism(s) of treatment failure may provide insight into their remedies. As in the past, opportunities for cure are more likely in newly diagnosed than relapse patients and will require both boldness as well as careful integration of novel agents and combinations into current treatment platforms.

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Index

A Aberrant methylation, 16 Absolute neutrophil count (ANC), 77 ABT–263, 128–130 ABT–737, 128–130, 291–292 Accelerated titration designs, 64 Acute lymphoblastic leukemia (ALL), 131–132 Acute myeloid leukemia (AML), 132–133 Acute promyelocytic leukemia (APML), 157 ADCC. See Antibody dependent cellular cytotoxicity (ADCC) ADCP. See Antibody dependent cell-mediated phagocytosis (ADCP) Adenosine triphosphate (ATP), 204, 206, 207 Adrenocorticotrophic hormone (ACTH), 2 Alkaloid vincristine, 2 Allogeneic stem cell transplantation (Allo-SCT), 25, 67 All-trans retinoic acid (ATRA), 157 Animal models leukemic stem cell, 109–110 NOD/SCID mouse, 108 preclinical testing, 110–111 recipient animals, 108–109 SCID, 106–107 in vivo xenograft model, 106 Antagonist aminopterin, 2 Antibody dependent cell-mediated phagocytosis (ADCP), 229 Antibody dependent cellular cytotoxicity (ADCC), 229, 249 Anti-CD19 vs. anti-CD22 immunoconjugates, 223 Antigen presenting cells (APCs), 227 Antisense oligonucleotides, 122 APML. See Acute promyelocytic leukemia (APML)

Apoptosis and cancer Bcl–2 family protein interactions, 119, 120 Extrinsic and intrinsic pathways, 117, 118 Apoptotic defects, 160 Area under the curve (AUC) values, 6 Asparagine synthetase (AS), 7 Ataxia telangiectasia mutated (ATM), 179 Athymic mice, 106 ATP. See Adenosine triphosphate (ATP) Avascular necrosis, 5 B B-cell development, 193 B-cell precursor (BCP), 254–257 Bcl–2 family proteins ABT–737/263, 128–130 apoptosis and cancer, 117–121 HA14–1, 125–126 haematological malignancy doxycycline, 121 oblimersen, 122–125 leukemia acute lymphoblastic, 131–132 acute myeloid, 132–133 chronic lymphocytic, 134 chronic myeloid, 133–134 lymphoma, 130–131 myeloma, 134–135 obatoclax, 126–128 paediatrics, 135 Bcl–2 homology (BH), 118 BCLL. See B-lymphocytic leukemia (BCLL) BCP. See B-cell precursor (BCP) Beige mutation, 107 Berlin-Frankfurt-Munster (BFM), 9, 321 Bispecific T-cell engaging antibodies (BiTEs®), 228, 230

V. Saha and P. Kearns (eds.), New Agents for the Treatment of Acute Lymphoblastic Leukemia, DOI 10.1007/978-1-4419-8459-3, © Springer Science+Business Media, LLC 2011

329

330 Blinatumomab, 259 B-lymphocytic leukemia (BCLL), 237 Bortezomib, 273, 276 C CALLA. See Common acute lymphoblastic leukemia antigen (CALLA) Cancer therapeutics. See Proteasome inhibitors, therapeutic utility Carfilzomib, 278–279 CAT–8015, 259 CCG. See Children’s Cancer Group (CCG) CD2, 247, 248 CD3, 247–249 CD4, 248, 249 CD5, 248, 250 CD7, 248, 250 CD10, 234 CD25, 248, 250–251 CD19 antigen antibody–drug conjugates, 235, 237 biological characteristics, 234–235 bispecific antibodies, 236–238 preclinical and clinical uses, 235–236 unconjugated anti-CD19, 235 CD20 antigen biological characteristics, 238 bispecific antibodies, 241 immunoconjugates, 241–242 preclinical and clinical uses, 238–239 unconjugated anti-CD20, 239–240 CD22 antigen biological characteristics, 242 bispecific antibodies, 243, 244 immunoconjugates, 243, 245–246 preclinical and clinical uses, 242 unconjugated anti-CD22, 242–243 CD33 antigen biological characteristics, 251 bispecific antibodies, 252, 253 immunoconjugates, 252–254 preclinical and clinical uses, 251–252 unconjugated anti-CD33, 252, 253 CD52 antigen biological characteristics, 231 immunoconjugates, 232 preclinical and clinical uses, 231–232 CD79 anitgen, 246 CDC. See Complement dependent cytotoxicity (CDC) CDDP. See Cis–diamminedichloridoplatinum (CDDP) Cellular cytotoxic activity, 222 Central nervous system (CNS) disease, 170

Index Central neurotoxicity, 176 Cerebrospinal fluid (CSF), 170, 208 Childhood acute myeloid leukemia, 69 Children’s Cancer Group (CCG), 67–68, 319, 321 Children’s Oncology Group (COG), 61, 319–321 CHOP. See Cyclophosphamide, doxorubicin, vincristin, prednisone (CHOP) Chronic lymphocytic leukemia (CLL), 134 Chronic myeloid leukemia (CML), 133–134 Cis-diamminedichloridoplatinum (CDDP), 40 Cisplatin, 40–41 Clinical trials. See also Early phase trials; Trial design and analyses clofarabine, 170–174, 321 combination studies, 288 dasatinib, 320 epigenetic pathways DNA methyltransferase inhibitors, 303–305 histone deacetylase inhibitors (HDACi), 306 forodesine, 180–181 gemcitabine, 183 lestaurtinib, 320–321 nelarabine, 175–176, 321 proteasome inhibitors, therapeutic utility combination studies, 288 single-agent activity, 284–288 single-agent activity Assesment of Proteasome Inhibition for EXtending remission-trial (APEX), 286 bortezomib, 284–288 Clinical Response and Efficacy Study of bortezomib in the Treatment of refractory myeloma (CREST), 286 dexamethasone, 287 relapsed and refractory pre-B ALL, 288 SUMMIT, 285 Clofarabine, 167–174, 321 CNS-directed therapy, 14 COG. See Children’s Oncology Group (COG) Common acute lymphoblastic leukemia antigen (CALLA), 234 Complementarity-determining regions (CDR), 222 Complement dependent cytotoxicity (CDC), 222, 229 Complete remission/response (CR), 49, 285, 288, 315 Complete response with insufficient platelet recovery (CRp), 77, 171

Index Confidence intervals (CI), 89 Consolidation and intensification MRC UKALL X protocol, 10 sensitivity/resistance patterns, 11–12 Continual reassessment method (CRM), 63–64 Continuation therapy methotrexate, 13 thioguanine, 13 TPMT, 12–13 CpG island, 299 CRLF2. See Cytokine receptor-like factor 2 (CRLF2) CRM. See Continual reassessment method (CRM) CRp. See Complete response with insufficient platelet recovery (CRp) CSF. See Cerebrospinal fluid (CSF) Cyclophosphamide, doxorubicin, vincristin, prednisone (CHOP), 76, 239 Cytokine receptor-like factor 2 (CRLF2), 29 Cytotoxicity, 172, 178, 180, 182, 184 Cytotoxic T-cells, 228 Cytotoxic T lymphocytes (CTLs), 227 D Dasatinib, 320 Daunorubicin (DNR), 9, 122 Death receptor pathway. See Extrinsic pathway Decitabine, 303–305 Denaturing high performance liquid chromatography (dHPLC), 190 Dendritic cells (DCs), 227 Deoxycytidine kinase (dCK) activity, 180 dHPLC. See Denaturing high performance liquid chromatography (dHPLC) Diffuse large B-cell lymphoma (DLBCL ), 131 DLTs. See Dose-limiting toxicities (DLTs) DNA hypermethylation, 300–301 DNA hypomethylation, 300 DNA methylation, 299, 301–302 Dose-limiting toxicities (DLTs) backbone toxicity rate, 70, 71 non-hematologic definition, 70, 71 exclusion approach, 71–72 functional approach, 72 grade 3 and 4 toxicities, 70 Drug testing concentric model, 52 pharmacokinetics, 52–53 PPTP aim, 47

331 evaluation methods, 49, 50 heat map representation, 48, 49 types, response curves, 47–48 recommendations, 45–46 therapeutic synergy, 51 transgenic mouse models, 46 treatment outcomes, 318–319 E Early phase trials phase II trials and design issues endpoint, 77–78 randomized phase II designs, 76–77 single arm phase II design, 76 phase I trials and design issues accelerated titration designs, 64 continual reassessment method, 63–64 conventional, 62–63 conventional pediatric, 63 dose limiting toxicities, 69–70 obstacles, conventional phase I trials, 8 platform approach, 65–68 rolling six design, 64–65 window approach, 68–69 preclinical evaluation, childhood leukemia, 62 Ectopic models, 106 Effective concentration for 50% effect (EC50), 127 EFS. See Event-free survival (EFS) time EGFP. See Enhanced green fluorescent protein (EGFP) Electrophoretic mobility shift assay (EMSA), 283 Endoplasmic reticulum (ER) stress, 280–281 Enhanced green fluorescent protein (EGFP), 44 Epigenetic pathways aberrant DNA methylation, 301–303 clinical trials DNA methyltransferase inhibitors, 303–305 histone deacetylase inhibitors (HDACi), 306 definition, 299 DNA methylation, 299 dysregulation in cancer, 300–301 epigenetic modifiers, paediatric ALL, 307 epigenetic-targeted therapy, 306–307 histone acetylation, 300 microRNA (miRNA), 306 therapeutic target, 303 transcriptional silencing, 299 Epigenetic processes, 303

332 Epoxomicin, 276 Epratuzumab anti-CD22 antibody, 242–243 nomenclature of MoAbs, 230–231 platform approach, 67 unconjugated antibody, 255 window approach, 68 Equipoise, 85 ER stress. See Endoplasmic reticulum (ER) stress European Medicine’s Agency (EMEA), 87, 90 Event-free survival (EFS) time, 84, 86, 87, 318 Ewing sarcoma family tumours (ESFT), 135 Extracellular signal related kinase (ERK), 127, 206 Extrinsic pathway, 117, 118 F FDA. See Food and Drug Administration (FDA) Fetal liver kinase 2 (FLK2), 189 Fixed dose rate (FDR), 182 FLK2. See Fetal liver kinase 2 (FLK2) FLT3. See Fms-like tyrosine kinase 3 (FLT3) FLT3 inhibition, 73–74 FLT3 inhibitors aberrant activation, 190–191 acivation in MLL rearranged ALL, 192–193 in AML, 193–194 clinical evaluation in AML, 194–196 drug resistance mechanisms, 197 imatinib/dasatinib, 197 mutations, 191 mutations in AML and ALL, 191–192 regulation in hematopoietic cells, 189–190 therapeutics, 196–197 FLT3 ligand (FLT3L), 189 Fms-like tyrosine kinase 3 (FLT3), 15–16 Food and Drug Administration (FDA), 208 G Gemtuzumab ozogamicin (GMTZ) CD33, 252, 257 nomenclature, MoAbs, 231 preclinical testing, 111 Gene expression profiling (GEP), 5, 27 Glucocorticoid receptors (GR), 4 Glycogen synthase kinase 3 isoforms a(GSK3a), 151 Glycogen synthase kinase 3 isoforms b(GSK3b), 151

Index GMTZ. See Gemtuzumab ozogamicin (GMTZ) Graft-versus-host-disease (GvHD), 247 Green fluorescent protein (GFP), 129 GvHD. See Graft-versus-host-disease (GvHD) H Haematological malignancies, 170, 180, 181 Haematological toxicity, 176, 183 Haematopoietic stem cell (HSC), 28, 145 Haematopoietic stem cell transplant (HSCT), 173 HATs. See Histone acetylases (HATs) HDACi. See Histone deacetylase inhibitors (HDACi) Heat shock protein, 284 Hepatic toxicity, 170, 183 Histone acetylases (HATs), 289 Histone acetylation, 300 Histone deacetylase (HDAC), 289, 306 Histone deacetylase inhibitors (HDACi), 289–291 Histone methylation, 300 HSCT. See Haematopoietic stem cell transplant (HSCT) Hsp–27 protein, 284 Human anti-mouse antibodies (HAMA), 235 Hyperdiploid ALL, 192 Hypervariable region, 222, 223 I ICN. See Intracellular NOTCH (ICN) IL–2 receptor common g chain (IL2rg), 145 Immune effector cell mechanisms, 224–228 Immunoreceptor tyrosine-based activation motif (ITAM), 246 Immunoreceptor tyrosine-based inhibitory motifs (ITIMs), 242 Induction therapy anthracyclines, 8–9 basic template, 3 L-asparaginase dexamethasone, 8 Escherichia coli and Erwinia carotovora, 7 steroids corticosteroids, 4 dexamethasone, 4 gene expression profile, 5 vincristine, 5–6 Inhibitory concentration (Ki), 128, 129, 213

Index Inhibitory concentration for 50% effect (CI50), 130 Inotuzumab ozogamicin, 259 Insulin like growth factor 1 (IGF–1), 127 Interferon alpha (IFNa), 241 Internal tandem duplication (ITD), 190 International Conference on Harmonization (ICH), 97 International normalized ratio (INR), 74 Intracellular NOTCH (ICN), 153 Intravenous (IV), 10, 171, 172, 179, 305 Intrinsic pathway, 117, 118 In vitro experimental models, 43 In vivo experimental models orthotopic ALL xenograft models, 45 transgenic mouse models, 44 In vivo xenograft model, 106 ITAM. See Immunoreceptor tyrosine-based activation motif (ITAM) J Janus family kinase (JAK), 29 Jun amino terminal kinase (JNK), 126 Juxtamembrane (JM) domain, 189, 190 K Killer Ig-like receptor (KIR), 227 Kinase insertion domain receptor (KDR), 194 L Lactacystin, 275, 276 L-asparaginase induction therapy dexamethasone, 8 E. coli and Erwinia carotovora, 7 preclinical evaluation, 40–41 preclinical therapies, 26 Lestaurtinib, 193–194, 320–321 Lestaurtinib monotherapy, 194–195 Leukemia stem cells (LSC) animal models, 109–110 cancer stem cell hypothesis, 143 characteristics, 144, 145 critical stem cell pathways aberrant cell signaling, 157–160 apoptotic defects, 160 differentiation defects, 156–157 self-renewal, 151–156 identification and cellular characteristics hierarchy, 145, 147

333 immunocompromised recipient mouse strain, 145 pathways and potential therapeutic interventions, 148 xenotransplantation, 145, 146 Leukemogenesis, 191 Lymphokine activated killer cells (LAK), 107 Lymphoma, 130–131 Lymphoproliferative diseases (LPD), 232 M Macroautophagy, 126 Macrophage colony-stimulating factor receptor (FMS), 189 Macrophages, 227 Maintained complete response (MCR), 48, 49 Major histocompatibility complex (MHC), 227, 232 Maleimidomethyl-cyclohexane-carboxylate (MCC), 246 Mammalian target of rapamycin (mTOR), 31, 46, 62, 131 MAPK kinase (MEK), 126 Marizomib, 277–278 Maximum tolerated dose (MTD), 45, 53, 62–63, 183 MCR. See Maintained complete response (MCR) MDS. See Myelodysplastic syndrome (MDS) Medical Research Council (MRC), 10, 11 Membrane attack complex (MAC), 229 6-Mercaptopurine (6-MP), 2, 12, 13, 178 Methotrexate CNS-directed therapy, 14 consolidation and intensification, 10 continuation therapy, 13 induction therapy, 3 sensitivity/resistance patterns, 11–12 Methyl thiazolyl diphenyltetrazolium bromide (MTT), 4 MHC. See Major histocompatibility complex (MHC) Midostaurin, 193–195 MIMP. See Mitochondrial inner membrane potential (MIMP) Minimal residual disease (MRD) end-reinduction, 78 platform approach, 66–67 trial design, 91, 92 Missense point-mutation, 190 Mitochondrial inner membrane potential (MIMP), 134

334 Mitochondrial outer membrane potential (MOMP), 119 Mitochondrial pathway. See Intrinsic pathway Mitogen activated protein kinase (MAPK), 126 Mixed lineage leukemia (MLL). See FLT3 inhibitors moAbs. See Monoclonal antibodies (moAbs) Monoblastic/monocytic AML, 192 Monoclonal antibodies (moAbs) B-lineage specific antigens CD10, 234 CD19, 234–238 CD20, 238–242 CD22, 242–246 CD79, 246 clinical use bispecific antibodies, 230 immune effector cell mechanism, 224, 227–228 immunoconjugates, 229–230 lymphoblastic leukemia cell antigens, 224–226 nomenclature, 230–231 radioimmunotherapy, 229–230 unconjugated antibody activity, 228–229 human anti-mouse antibodies (HAMA), 221 leukaemic stem cell, 257–258 lineage independent antigens CD52, 231–233 HLA-DR, 232–234 myeloid antigens, 251–254 against precursor B-cell/T-ALL adult B-cell NHL, 254 conjugated antibodies, 256–257 cytotoxic mechanisms, 255 unconjugated antibodies, 255–256 structure, 221–222 T-lineage specific antigens CD2, 247, 248 CD3, 247–249 CD4, 248, 249 CD5, 248, 250 CD7, 248, 250 CD25, 248, 250–251 treatment/co-stimulatory strategies, duration of, 258–259 Mouse embryonic fibroblast (MEF), 129 Mouse models, 189 6MP. See 6-Mercaptopurine (6-MP) MRD. See Minimal residual disease (MRD) MTD. See Maximum tolerated dose (MTD)

Index mTOR. See Mammalian target of rapamycin (mTOR) Multiple Myeloma Research Consortium (MMRC), 277 Myelodysplastic syndrome (MDS), 128, 195, 304 Myeloid antigens. See CD33 antigen Myeloma, 134–135 Mylotarg® CD33, 252, 257 nomenclature, moAbs, 231 preclinical testing, 111 N National Cancer Institute (NCI), 40, 41, 62, 246, 276 Natural killer (NK), 44, 224, 247 NCI. See National Cancer Institute (NCI) Nelarabine, 321 Neurotoxicity, 176 Neutropenia, 172, 173, 177, 180 Neutrophils, 227 NHL. See Non-Hodgkin Lymphoma (NHL) NK cells, 227 NOD. See Non-obese diabetic (NOD) NOD/SCID mouse, 108 Non-Hodgkin Lymphoma (NHL), 124, 131, 230, 235, 241–243, 246, 287 Non-obese diabetic (NOD), 44, 109, 145, 148–149 NOTCH 1, 16 NPI–0052. See Marizomib NSG strain, 109–111 Nuclear localizing sequences (NLS), 254 Nucleoside analogues clofarabine ALL, 167 clinical trials, 170–174 paediatric leukemia, 167 pharmacokinetics, 169–170 pharmacology, 167–169 forodesine clinical trials, 180–181 immunodeficiency, 177 pharmacology, 178–180 PNP deficiency, 177 gemcitabine clinical trials, 183 pharmacokinetics, 182–183 pharmacology, 182 nelarabine clinical trials, 175–176 multiagent chemotherapy, 177

Index multidrug therapy, 177 pharmacokinetics, 175 pharmacology, 174–175 purine nucleoside phosphorylase (PNP) deficiency, 174 relapse, 177 T-cell ALL, 177 toxicities, 176–177 Nude mutation, 107 Number needed to treat (NNT), 319 O Obatoclax, 126–128 Orthotopic models, 106 Outer mitochondrial membrane (OMM), 134, 160 P Paediatrics, 135 Parthenolide (PTL), 160 Partial remission/response (PR), 48, 123, 171, 285, 287, 288 Partial thromboplastin time (PTT), 74 PD. See Progressive disease (PD) PDGFR. See Platelet-derived growth factor receptor (PDGFR) Pediatric preclinical testing program (PPTP) aim, 47 evaluation methods, drug testing, 49, 50 heat map representation, 48, 49 types, response curves, 47–48 PEG asparaginase, 7 Peptide aldehydes, 275 Peptide boronate PS–341. See Bortezomib Peripheral neurotoxicity, 176 Per protocol (PP), 100, 101 P-glycoprotein (PGP), 6, 134, 208, 229 Pharmacokinetics clofarabine, 169–170 gemcitabine, 182–183 nelarabine, 175 preclinical evaluation, 52–53 Pharmacology clofarabine, 167–169 forodesine, 178–180 gemcitabine, 182 nelarabine, 174–175 Pharmacore, 275 3+3 phase I trial design, 62 Phase I trials and design issues accelerated titration designs, 64 continual reassessment method, 63–64

335 conventional, 62–63 conventional pediatric, 63 dose limiting toxicities, 69–70 obstacles, conventional phase I trials, 65 platform approach, 65–68 rolling six design, 64–65 window approach, 68–69 Platelet-derived growth factor receptor (PDGFR), 189, 206–208, 210 Platform approach advantage and disadvantage, 68 COG AALL01P2 triple re-induction, 66 early and late marrow relapses, 67 MRD, 66–67 three-block approach, 67 Polymerase Chain Reaction (PCR), 13, 192, 312 Postamendment block 1 therapy, 66 PPTP. See Pediatric preclinical testing program (PPTP) PR. See Partial remission/response (PR) Preclinical evaluation drug testing concentric model, 52 pharmacokinetics, 52–53 PPTP, 47–50 recommendations, 45–46 therapeutic synergy, 51 transgenic mouse models, 46 evaluation criteria, robust preclinical models, 42 in vitro experimental models, 43 in vivo and in vitro panels, 41 in vivo experimental models orthotopic ALL xenograft models, 45 transgenic mouse models, 44 L-asparaginase and cisplatin, 40–41 Pre-clinical therapies cell-death pathway triggers, 32 conceptual model, 29–30 cytogenetic analysis, 26 global profile, 29 heterogeneity, treatment response, 28 kinase inhibitors, 32 L-asparaginase, 26 monoclonal antibodies, 32 relapse occurence, extramedullary sites, 27–28 origin, 27 g-secretase, 33 steroid-sensitising adjuvants, 31–32 T-lineage ALL, 33 transcriptional profile, 29 tumour microenvironment, 28–29

336 Progressive disease (PD), 48, 49, 68, 243 Prospective meta-analysis strategy (PMAS), 99 Proteasome inhibition, 74–76 Proteasome inhibitors, therapeutic utility ALL treatment, potential combination studies BCL–2 antagonists, 291–292 HDAC inhibitors, 289–291 bortezomib, 273 clinical trials combination studies, 288 single-agent activity, 284–288 development, 275–276 haematological malignancies, 273 molecular pharmacology caspase activation, 280–281 endoplasmic reticulum stress, 280–281 NFkB-inhibiting survival, 282–283 oxidative stress, 281–282 pro-apoptotic proteins, 279–280 resistance, 284 next-generation, 277–279 20S/26S proteasome, 274 ubiquitinated proteins, 274–275 ubiquitin-proteasome pathway, 273, 274 Puma, 280 R Randomized phase II designs, 76–77 Reactive oxygen species (ROS), 191, 281 Receptor tyrosine kinase (RTK), 189 Recommended phase II dose (RPIID) phase I end point, 69 single-arm phase II design, 76 Retinoblastoma gene (RB), 155–156 Ribonucleotide reductase, 182 Rolling six design, 64–65 ROS. See Reactive oxygen species (ROS) RPIID. See Recommended phase II dose (RPIID) RT-PCR analysis, 192 S SCID. See Severe-combined immunodeficient (SCID) SCT. See Stem cell transplantation (SCT) SD. See Stable disease (SD) Second mitochondrial derived activator of caspases (Smac), 118 Self potentiation, 182, 183

Index Serine/threonine aurora kinase, 213 Severe-combined immunodeficient (SCID), 106–107 Single arm phase II design, 76 Small interfering RNA (SiRNA), 127, 157 Sorafenib/Tandutinib, 195 Src-Abl Tyrosine kinase inhibition Activity Research Trials (START), 210 Stable disease (SD), 48, 123, 243, 285, 287 Standard dose schedule (STD), 183 Steel factor receptor (KIT), 189 Stem cell pathways aberrant cell signaling BCR-ABL1 and NUP241-ABL1 signaling, 158–159 FLT3-TKD mutant signaling, 159 and JAK mutations, 159–160 apoptotic defects, 160 differentiation defects, 156–157 self-renewal bHLH proteins and their binding partners, dysregulation, 154–155 clustered and non-clustered HOX genes, 151–152 NOTCH mutations, 152–153 PTEN pathway, 153–154 RB/TP53 tumour suppressor network, 155–156 Stem cell transplantation (SCT), 67, 158, 212, 256 Stem cell tyrosine kinase 1 (STK1), 189 Subcutaneous models, 106 Sunitinib, 193–194 T T-cell lymphoma, 176 T-cell malignancies, 174, 178, 179 Thioguanine, 13 Thiopurine methyltransferase (TPMT) continuation therapy, 12–13 location, 28 Thrombocytopenia, 177 TKD. See Tyrosine kinase domain (TKD) T-lymphoblasts, 175 TNF-related apoptosis inducing ligand (TRAIL), 237 TPMT. See Thiopurine methyltransferase (TPMT) Transgenic zebrafish models, 44 Transmembrane (TM) domain, 189, 190 Treatment outcomes Children’s Oncology Group, clinical trials

Index clofarabine, 321 dasatinib, 320 lestaurtinib, 320–321 nelarabine, 321 dexamethasone, 311 drug selection clinically active/inactive, 315 dexamethasone vs. prednisone, 317 imatinib, 317 positive/negative control, 315–316 resistance mechanisms, 317 drug testing, 318–319 hematopoietic stem cell transplant (HSCT), 311 imatinib, 312 relapse, operational definition blast proliferation, 313 blast re-accumulation, 314 cell death, 313 chemotherapeutic agents, 314 oligoclonal ALL, 312–313 refractory sub-clone, 314 Trial design and analyses adaptive designs adaptive seamless design, 95 group sequential designs, 94 heterogeneity, 94 Bayesian approach criticism, 96 hypothesis testing, 96–97 interval estimates, 97 posterior distribution, 95 biological activity, 91 efficacy, 92 experimental research clinical aspects, 83 comparative trials, 85 definition, 83 equipoise, 85 translational trials, 84 treatment tolerability, 84–85 good clinical practice (GCP) principles, 97–99 international clinical trial logistics and implementation, 99–100 prospective meta-analysis strategy (PMAS), 99 requirements, 99 lymphoblastic leukemia high-risk sub-populations, 85 intermediate risk patients, 86 regulatory approval process, 87 treatment optimization, 86

337 protocol structure and content, 97–98 statistical analysis frequentist approach, 101 heterogeneity, 101–102 intention to treat (ITT), 100 interim analyses, 101 per protocol (PP), 100 as treated (TP), 100 superiority and non-inferiority add-on trial, 88 confidence intervals, 89 head-to-head trial, 88 surrogate end points failure, 93 validation, 92–93 Tropomyosin-related kinase (TRK), 194 Tumour microenvironment, 28–29 Tumour Necrosis Factor (TNF), 227, 237 Tyrosine kinase domain (TKD), 157, 189–191 Tyrosine kinase (TK) inhibitors bafetinib, 207 BCR/ABL oncoprotein, 206–207 bosutinib, 207 clinical application bafetinib, 211 bosutinib, 210–211 CML, 209–211 combination therapy, 212 dasatinib, 210, 212, 213 haematological and cytogenetic responses, 211 imatinib, 208, 209, 211, 212 dasatinib, 207, 208 hepatic metabolism, 208 imatinib, 206–207, 209 intracellular signalling pathways, 204–205 JAK mutations, 213 leukemia aetiology childhood ALL, 205 chimeric oncoprotein, 205–206 Philadelphia positive ALL, 206 Philadelphia translocation protein, 205 multi-agent chemotherapy, 212 myeloproliferative disease, 213 nilotinib, 207–209, 213 Philadelphia positive ALL, 209–212 post stem cell transplantation, 212 protein phosphorylation, 203–204 receptor and non-receptor TK families, 203 regulatory mechanism, 204 staurosporine, 206

338

Index

U Unfolded protein response (UPR), 280

W Window approach, 68–69

V Valproic acid (VPA), 237 Variable (V) region, 221 Vascular endothelial growth factor receptor (VEGFR), 194, 208 Veno-occlusive disease (VOD), 13

X Xid mutation, 107 XmAb5574, 259