WHITE PAPER
Executive Summary
Biomarkers hold promise in the diagnosis, prognosis and therapeutic stratification of hemato...
www.quintiles.com | 2
table of contents
Myelomas	4
Lymphomas	5
	 Hodgkin and Non-Hodgkin Disease	 5
	 Diffuse large B-cell...
3 | www.quintiles.com
The use of biomarkers is becoming an increasing focus of hematology clinical research,
providing pot...
www.quintiles.com | 4
This paper examines the potential of recent biomarker-related technological advances and
application...
5 | www.quintiles.com
Lymphomas
Hodgkin and Non-Hodgkin Disease
Lymphoma is actually a name covering a set of diseases ass...
www.quintiles.com | 6
In addition, various genetic features, such as IRF4 translocations, gains in 1q21, 18q21, 7p22,
and ...
7 | www.quintiles.com
Chronic Lymphocytic Leukemia
Chronic lymphocytic leukemia (CLL) is the most prevalent leukemia in th...
www.quintiles.com | 8
Acute Myeloid Leukemia
Acute myeloid leukemia (AML) is a disease in particular need of relevant biom...
9 | www.quintiles.com
most part have resulted in only small improvements in outcome.” Also, as the number
of molecularly a...
www.quintiles.com | 10
The challenges of patient stratification and treatment optimization through specific
biomarkers are...
11 | www.quintiles.com
References
1	 http://grants.nih.gov/grants/guide/pa-files/PA-12-220.html
2	 http://grants.nih.gov/g...
www.quintiles.com | 12
17	 Kamper P, Bendix K, Hamilton-Dutoit S, et al. Tumor-infiltrating macrophages correlate
with adv...
13 | www.quintiles.com
2011;43-50.
33	 http://seer.cancer.gov/statfacts/html/amyl.html#survival
34	 Transforming Clinical ...
14 | www.quintiles.com
Harish Dave, MD, MBA
Vice President, Global Medical Strategy Head, Hematology and Oncology,
Quintil...
15 | www.quintiles.com
Prior to joining Quintiles, Dr. Lieberman has had an active career in clinical development
with mor...
Copyright © 2013 Quintiles. 16.15.21-042013
Contact Us:
US Toll Free: 1 866 267 4479
Direct: +1 973 850 7571
On the web: q...
Upcoming SlideShare
Loading in …5
×

Biomarkers recent-advances-in-their-application-to-the-treatment-of-hematologic-malignancies

829 views

Published on

Published in: Health & Medicine
  • Be the first to comment

  • Be the first to like this

Biomarkers recent-advances-in-their-application-to-the-treatment-of-hematologic-malignancies

  1. 1. WHITE PAPER Executive Summary Biomarkers hold promise in the diagnosis, prognosis and therapeutic stratification of hematopoietic malignancies. These heterogeneous diseases – including multiple myeloma, lymphomas and leukemias – are frequently characterized cytogenetically with diagnoses supported by genetic, immunohistochemical and flow cytometric analyses. Biomarkers offer the hope of early detection as well as tracking disease progression and recurrence. Early detection may help improve survival, as it could help identify individuals most at risk for disease development, distinguish aggressive from indolent disease, and track disease progression. In therapeutic stratification, biomarkers potentially allow for patient-specific selection of agents that are likely to be effective and not cause unnecessary toxicity. Notable clinical advances were reported at the 54th Annual American Society for Hematology Conference (December 7-11, 2012; Atlanta, GA), suggesting that through innovative, biomarker-based approaches, better outcomes can be achieved with lower doses of drugs. Additionally, recent progress in the characterization of the molecular genetics of various hematologic malignancies may form the basis for improved patient stratification and future targeted/individualized therapies. Integration of clinical, cytogenetic and molecular data will be indispensible in translating this progress into better outcomes for patients. There is also a need for standardization of the technologies used for clinical assessment of minimal residual disease – enabling detection of lingering disease burden after treatment – and their interpretation. In the future, for treatment of hematologic malignancies to become affordable and value-driven, continued investment in biomarker discovery and the elucidation and application of prognostic/predictive biomarkers will be needed. This has the potential to identify genetic associations and profiles that can be drugged or targeted, ultimately putting the promise of personalized medicine within reach. Biomarkers: Recent Advances in their Application to the Treatment of Hematologic Malignancies Harish Dave, M.D., MBA, Vice President, Global Medical Strategy Head, Hematology and Oncology, Oncology Therapeutic Area, Quintiles Chris A. Learn, Ph.D., PMP, Senior Clinical Project Manager, Oncology Therapeutic Area, Therapeutic Delivery Unit, Quintiles Ronald Lieberman, M.D., Senior Director, Hematology, Oncology and Transplantation, Oncology Therapeutic Area, Quintiles
  2. 2. www.quintiles.com | 2 table of contents Myelomas 4 Lymphomas 5 Hodgkin and Non-Hodgkin Disease 5 Diffuse large B-cell Lymphoma 5 Other B cell Lymphomas 7 Chronic Lymphocytic Leukemia 7 Acute Myeloid Leukemia 8 Conclusion 9 References 11 About the Authors 14 table of contents
  3. 3. 3 | www.quintiles.com The use of biomarkers is becoming an increasing focus of hematology clinical research, providing potential support for the diagnosis, prognosis and therapeutic stratification of patients with hematopoietic malignancies. These uses are further supported by the fact that most hematopoietic malignancies are widely disseminated even in their “early” stages, and often do not have a well-defined localized phase, making them less amenable to conventional early screening methods such as imaging and observation. To this end, biomarkers offer the hope of early detection as well as for the tracking of disease progression and recurrence of hematopoietic malignancies.1 Early detection may help improve survival, as it would be particularly useful in (1) identifying individuals most at risk for disease development, (2) distinguishing aggressive from indolent disease, and (3) tracking disease progression from a benign or pre-neoplastic state. In therapeutic stratification, biomarkers potentially allow for patient-specific selection of therapeutic agents that are likely to be effective and not result in unnecessary toxicity. Hematopoietic malignancies, which include a heterogeneous group of diseases such as multiple myeloma, lymphomas and leukemias, are frequently characterized cytogenetically with diagnoses supported by genetic, immunohistochemical and flow cytometric analyses. To date, few biomarkers for the early detection, progression or risk assessment for such malignancies have been identified or clinically validated.2 These standard diagnostics work best in the setting of advanced disease. As a result, many patients are diagnosed at advanced disease stages when therapies are less effective and typically result in higher mortality rates. Furthermore, the vigorous interventions required for advanced disease also negatively affect quality of life and impose a significant financial burden on both patients and payers. Given that the diagnosis of these malignancies is still based largely on morphological criteria, as it has been for decades, improving outcomes without more detailed genetic and mechanistic information is a significant challenge, especially when trying to predict a given cancer’s potential for progression and response to treatment. Thus, the need to identify and validate clinically relevant biomarkers that yield informative associations with disease progression and outcome in myeloma, lymphomas and leukemias remains urgent. However, there are some reasons for optimism. At the 54th Annual American Society for Hematology Conference held December 7-11, 2012 in Atlanta, Georgia, USA, notable progress over the previous year was demonstrated regarding clinical advances in the treatment of various hematologic malignancies. A unifying theme that arose from those scientific presentations was that through innovative means, better outcomes with lower doses of drugs can be achieved. As noted with each publishable finding resulting from these studies, an improved understanding of underlying biology through biomarkers was the foundation for these clinical advances, and for their potential future advancement. Additionally, recent progress in the characterization of the molecular genetics of various hematologic malignancies has validated recurrent cytogenetic and mutational changes in leukemic blasts. These changes have been demonstrated to have high prognostic significance, and may serve as a future opportunity for treatment. Yet, despite this progress, the understanding of the mechanisms by which these changes influence cancer growth and response to treatment is still limited, restricting the development of rationally targeted therapies. The integration of clinical, cytogenetic and molecular data will therefore be indispensable in translating this current progress into better outcomes for patients with blood cancers. Biomarkers offer the hope of early detection, which would be particularly useful in: • identifying individuals most at risk for disease development • distinguishing aggressive from indolent disease, and • tracking disease progression from a benign or pre- neoplastic state.
  4. 4. www.quintiles.com | 4 This paper examines the potential of recent biomarker-related technological advances and applications for several key hematopoietic malignancies for the purpose of improving the current clinical picture of disease management and outcome. Myelomas Advances in genomics and proteomics have improved the understanding of myeloma pathogenesis, identifying novel mediators of the disease process, and potential therapeutic targets.3 These developments have allowed for molecular classification of the disease, yielding new diagnostic tools for myeloma, and better monitoring of disease status. Recent advances in investigative techniques that have refined the diagnostic work-up for myeloma include serum-free light chain ratios,4 use of MRI and PET scans in diagnosis and managing bone disease, and use of cytogenetics and fluorescent in situ hybridization (FISH) to assess prognosis. Newer risk stratification protocols include international staging systems and chromosomal changes detected using FISH. Given the application of these techniques, predictive risk stratification models are now used to guide treatment algorithms, and response categories are also being redefined as novel therapies have achieved complete responses in a significant number of patients. Recent studies have confirmed the importance of achieving complete remission in extending overall survival.5,6 Interrogation methods for cancer cell DNA, such as high-throughput expression profiling, high-density single nucleotide polymorphism (SNP) arrays and array-based comparative hybridization (aCGH), are now increasingly utilized to better understand myeloma pathobiology.7,8 Such efforts have also been applied to gene discovery, biomarker identification, and delineation of patient subgroups with the goal of offering individualized therapy. Novel biomarkers recently identified for myeloma include circulating progenitor endothelial cells,9 circulating micoRNAs,10 angiopoietins,11 and serum B-cell activating factor,12 all of which have demonstrated an association with worsened prognosis in patients. Multiple myeloma (MM) is the second most prevalent hematological malignancy in the U.S. (after non-Hodgkin lymphoma) and develops in 1–4 per 100,000 people per year in adults, and despite extensive information on its molecular biology and significant advances in therapeutics, this disease retains a high mortality.13 The identification of novel biomarkers, especially through the use of mass spectrometry, is expected to help in the diagnosis, prognosis and therapeutic stratification of MM. Mass spectral analysis has been used to identify new serum biomarkers that may distinguish between MM patients and normal individuals. Additionally, this technique has enabled the identification of biomarkers indicating resistance to several chemotherapeutic drugs used for the treatment of MM. It has also been used to investigate the signaling networks involved with the disease, the results of which are expected to guide future studies of MM pathogenesis. Perhaps one of the greatest promises of mass spectrometry will be its use in helping direct therapy.13 “Since current ‘one size fits all’ therapy is complicated by serious toxicities and may be unnecessary in some good prognosis patients, it is critical to introduce risk-adapted therapy,” write Micallef and Dharsee in a 2010 Journal of Hematology & Oncology paper.13 This approach will require better prognostic markers, since current prognostic models are inadequate for predicting disease outcome in individual patients. Protein expression profiling by mass spectrometry holds promise in identifying biomarkers for improving the diagnosis and prognosis of MM. As such, this will also help advance understanding of the mechanisms of drug resistance, which will invariably aid in directing therapeutic strategies. Multiple myeloma is the second most prevalent hematological malignancy in the U.S. (after non-Hodgkin lymphoma).
  5. 5. 5 | www.quintiles.com Lymphomas Hodgkin and Non-Hodgkin Disease Lymphoma is actually a name covering a set of diseases associated with lymphocytes and may include acute, aggressive and indolent forms, each with its own set of problems. Non- Hodgkin lymphoma (NHL) is the most prevalent hematologic malignancy in the U.S. with an estimated incidence of 69,760 cases in 2013.14 Prediction of outcomes in patients with lymphoma is a major challenge for clinicians.15 Recently, gene-expression profiling has enabled identification of specific gene expression signatures that are associated with distinct genetic alterations and differing survival rates in various lymphomas. From these studies, signatures that included increased expression of MCL1, BCL6 and/or CFLAR demonstrated a decreased chance of achieving stable disease or better, while those gene profiles that experience decreased expression of CDKN1B correlated with lower progression survival16 in patients with relapsed/refractory NHL. The importance of the tumor microenvironment has been demonstrated in classical Hodgkin Lymphoma (cHL). Multiple reports now support the value of enumerating tumor- associated macrophages in pretreatment biopsies for outcome prediction in cHL. Kamper et al. used immunohistochemistry to investigate a large number (n = 288) of pretreatment biopsies from patients with cHL and found a significant correlation between tumor- associated macrophages and adverse treatment outcome. Furthermore, these investigators demonstrated a previously unrecognized association of CD68+ macrophages with latent Epstein-Barr virus (EBV) infection of the tumor cells.17 This study, together with others,18,19 strongly suggests that the number of CD68+ macrophages can be used as a reliable biomarker in cHL and NHL. Diffuse large B-cell lymphoma Significant progress was made in the mid-1990s when an international group set up the International Prognostic Index (IPI) for diffuse large B-cell lymphoma (DLBCL). DLBCL is the most common type of non-Hodgkin lymphoma among adults with an annual incidence of 7-8 cases per 100,000 people per year in the U.S. Many studies now suggest that cases of DLBCL can be separated into two groups on the basis of their gene expression profiles (GEP); these groups are known as germinal centre B-cell-like (GCB) and non-GCB or activated B-cell-like (ABC). Risk stratification for DLBCL is important since the GCB subtype has a better prognosis and more favorable response to current standard of care therapy with RCHOP compared to the ABC subtype.20 While GEP is recognized as the gold standard for the molecular classification of DLBCL subtypes, considerable progress has been made in developing less technically complex classification algorithms with immunostains such as the Choi algorithm. Using highly specific antibody-based immunostains of GCET1, CD10, BCL6, MUM1, and FOXP1 proteins, this new algorithm closely approximated the GEP classification of DLBCL into GCB and ABC subtypes with 93% concordance.21 These new immunostain based algorithms are being used increasingly in clinical trials of novel agents for risk stratification of DLBCL. Diffuse large B-cell lymphoma is the most common type of non- Hodgkin lymphoma among adults.
  6. 6. www.quintiles.com | 6 In addition, various genetic features, such as IRF4 translocations, gains in 1q21, 18q21, 7p22, and 7q21, as well as changes in 3q27, including gains and translocations affecting the BCL6 locus, are significantly associated with increased patient age and worsened prognosis in DLBCL.22 Clearly, an improved understanding of the biology of biomarkers such as these and their specific contribution to prognosis and outcome will be paramount. Another notable finding of recent gene expression studies is the importance of the cells and microscopic structures interspersed between the malignant B cells within the DLBCL tumor, an area commonly known as the tumor microenvironment. The presence of gene expression signatures commonly associated with macrophages, T cells, and remodelling of the extracellular matrix seems to be associated with an improved prognosis and better overall survival. In contrast, expression of genes coding for pro-angiogenic factors is correlated with poorer survival.23 The LLBC study concluded that variations in biologic features are largely overshadowed by the IPI for prognostic impact, and that biomarkers only allow subtle refinements of the IPI. Attempts to build an index using biomarkers alone, or the combination of biomarkers with IPI individual factors (instead of IPI categories) did not result in an improved model fit or discrimination, the authors note.15 The inability of biomarkers to further stratify outcomes “may reflect the importance of patient characteristics over biologic characteristics of tumor cells in this patient subset.” However, biomarkers may contribute to defining more homogeneous biologic subsets of DLBCL for which targeted therapies can be investigated. The study also concluded that attempts to validate immunohistochemical (IHC) biomarkers for prognostic stratification of patients “clearly require large cohorts and reproducible methodology that allows for the control of cofactor interactions. In this regard, stratification based on biomarkers for guiding treatment options should be viewed cautiously.” The authors conclude that the IPI remains the best available index in patients with DLBCL treated with rituximab and chemotherapy.15 Some progress may be possible with more reliable IHC, cytogenetic or molecular markers, but their assessment as prognostic factors will require careful evaluation before they can be routinely used in clinical practice. Other B cell Lymphomas Several lymphoma types, such as follicular lymphoma (FL), mantle cell lymphoma (MCL), and Burkitt lymphoma (BL), are linked with hallmark translocations due to errors when the physiologic mechanisms involved in generating immunologic diversity go awry.24 However, the associations are not absolute and none is completely diagnostically specific or sensitive, leading to the absence of clinically relevant biomarkers for these indications. In a 2011 Hematology paper, Bagg also writes that it is not necessary to perform any kind of genetic testing to render a diagnosis, but it is clear that genetic factors and/or cell-of-origin data are key determinants of prognosis as well as of specific subtypes. Nonetheless, in spite of a decade of investigation, none of the interesting data from gene expression profiling and other technologies has translated into routine clinical practice. “For now, unless a patient is not a candidate for aggressive therapy, it might be appropriate to consider screening all such lymphomas for not only MYC translocations, but also BCL2 and BCL6 translocations, as well,” concludes the author.
  7. 7. 7 | www.quintiles.com Chronic Lymphocytic Leukemia Chronic lymphocytic leukemia (CLL) is the most prevalent leukemia in the western world; it is estimated there will be 15,680 new cases and 4,580 deaths from CLL in the USA in 2013.25 The clinical course of this disease is remarkably heterogeneous. As such, some patients have relatively aggressive disease requiring early treatment, while others have highly indolent disease that does not require treatment for decades.26 Current staging systems have not been able to predict which patients in early or intermediate risk stages will undergo disease progression and which will undergo an indolent course. Universal treatment of all patients with early stage disease has been shown to be more harmful than beneficial. As such, early identification of patients who will have more aggressive disease soon after diagnosis has been a major goal in CLL research. However, several clinical parameters have been identified that are predictive of the clinical course. As mentioned below, there are a number of molecular biomarkers that have been identified and verified as providing prognostic information, most involving cytogenetics by FISH, immunoglobulin heavy chain (IgH) mutational status and expression of ZAP70. Regarding ZAP70, researchers have utilized quantitative DNA methylation analysis to discover a single CpG dinucleotide that plays an important role for ZAP70 expression, which has shown significant correlation with prognosis status in CLL, so much so that it is likely to be incorporated as part of the clinical staging of this disease going forward. A remaining challenge is to understand how to use this information in clinical practice, and whether to alter treatment based on the detection of “high-risk” features. Of note, recent investigations into B-cell activation via the PI3K signaling pathway in CLL have elucidated important biomarkers that have led to clinical advances with the investigational drug ibrutinib. A primary focus of ASH 2012, ibrutinib has received considerable attention given its ability to selectively inhibit Bruton’s tyrosine kinase (Btk), a key component to B-cell activation and further intracellular signaling. To this end, ibrutinib has been shown to decrease tumor cell chemotaxis towards chemokines, as well as inhibit cellular adhesion following B-cell receptor (BCR) activation.27, 28 Thus, ibrutinib’s purported mechanism of action is through the blockage of BCR signaling, resulting in cellular apoptosis. Ibrutinib is currently under development for CLL, but is also being actively investigated in mantle cell lymphoma, DLBCL, and MM. While ibrutinib has clearly shown the clinical importance of specifically targeting Btk in CLL, additional biomarkers in CLL are also under investigation and merit consideration here. CD38+,29 miRNAs,30 and BCL-231 have all been shown to have significant associations with clinical disease management and outcome in CLL. These studies also suggest, and as mentioned earlier, the definition of predictive medicine and predictive tests is now being expanded to include the risk-stratification of patients with early forms of a disease such as CLL using biomarkers. For example, the overproduction of CD38+ and ZAP70 proteins identifies those patients who will go on to develop the more aggressive form of the disease. Rather than waiting until such patients develop more aggressive disease and require treatment with both chemotherapy and monoclonal antibodies, treatment decisions can be made earlier and with more confidence given the context of greater information and how to more effectively target biomarkers such as these. Chronic lymphocytic leukemia is the most prevalent leukemia in the western world. Some patients have relatively aggressive disease requiring early treatment, while others have highly indolent disease that does not require treatment for decades.
  8. 8. www.quintiles.com | 8 Acute Myeloid Leukemia Acute myeloid leukemia (AML) is a disease in particular need of relevant biomarkers to improve decision-making. Like CLL, AML is a highly heterogeneous disease, lacking well- defined biomarkers for clinical staging. As with other hematologic malignancies, there is clear need for the ability to stratify patients with AML according to current disease status, as well as for assigning patients with certain subtypes of this disease to available molecular targeted therapies. Further complicating matters is the fact that many AML patients do not feature any known molecular markers and therefore cannot be stratified. Given this lack of information and knowledge on how best to treat, the clinical outcome for AML patients remains poor. At this time, approximately 12,000 adults are diagnosed with AML in the United States annually, the majority of whom die from their disease32 , with 5-year survival for less than 25%.33 Currently, the worldwide standard of care for initial treatment, cytosine arabinoside combined with an anthracycline, was developed approximately 40 years ago; further, as the epidemiology of AML is biased towards older patients, a large fraction of patients are really not candidates for this standard therapy. AML is a genetically heterogeneous disease, and many patients can be categorized into clinicopathologic subgroups based on the underlying molecular genetic defects. Greater specificity of diagnostic classification would be expected to lead to more effective application of targeted agents and an ability to create personalized treatment strategies. Roboz32 concludes that several strategies may accelerate the availability of new drugs or treatment regimens in the clinic: • Development of existing drugs in addition to searching for new ones – In pediatric acute lymphoblastic leukemia, major improvements in outcomes have been achieved by optimizing the combination, schedule, and duration of treatment using existing, potentially outdated drugs. • Increased accrual to clinical trials – Currently, fewer than 5% of adults with cancer in the United States participate in clinical trials, while 60% of pediatric cancer patients participate in trials.34 • Change the paradigm for drug development – For AML, there is growing realization that the traditional phase 1-3 drug development paradigm is ineffective. Phase 1 trials typically provide novel agents to patients with relapsed and refractory disease, a setting where non-cytotoxic, molecularly targeted agents have little chance of success, and where signals of their true biologic efficacy may be missed. Some of these agents should be considered instead for trials aimed at prolonging response duration and survival in AML patients who have already achieved remission. Phase 2 trials in AML are often small and may also give misleading efficacy signals. “Given the heterogeneity of the disease, subgroup analyses based at least on age, performance status, cytogenetics, and molecular features are essential, yet these are meaningless when the total cohort includes only 20-50 patients,” notes Roboz. “There is increasing support for randomized phase 2 trials, including adaptive randomization and ‘pick- the-winner’ strategies aimed at rapidly comparing new treatments with existing standards of care, using as few patients as possible and to continue only with those that meet predetermined efficacy benchmarks. Phase 3 trials in AML are described as being “often unbearably slow and expensive to complete and, unfortunately, for the Like chronic lymphocytic leukemia, acute myeloid leukemia is a highly heterogeneous disease, lacking well-defined biomarkers for clinical staging.
  9. 9. 9 | www.quintiles.com most part have resulted in only small improvements in outcome.” Also, as the number of molecularly and clinically defined subgroups increases, it is ever more challenging to determine a reasonable control arm for new Phase 3 trials. Roboz concludes: “It is hoped that further refinements in the molecular characterization of AML will allow the identification of more homogeneous treatment groups and tailored therapeutics.”32 In current clinical practice, a relatively small number of genetic abnormalities are used to predict outcome and to direct therapy in AML. These include CBF translocations and translocations associated with acute promyelocytic leukemia, which predict for favorable outcome with induction/consolidation and for sensitivity to all-trans retinoic acid and arsenic trioxide, respectively. Schlenk et al. have shown that mutational analysis of FLT3 in combination with NPM1 or CEBPA mutations can be used to predict outcome in cytogenetically normal AML and to identify patients who will benefit from allogeneic stem cell transplantation.35 However, a large number of AML patients lack any of these abnormalities, so there remains significant heterogeneity in clinical outcome within currently classified prognostic groups. These observations suggest there are additional biomarkers that can predict outcome in AML. Recently, genetic studies have identified an increasing number of recurrent somatic mutations in AML patients, including mutations in TET2,36,37 ASXL1,38,39 IDH140 and IDH2,41,42 DNMT3A43,44,45 and PHF6.46 In addition, several of these newly identified genetic abnormalities have been shown to have prognostic importance in AML.47 Haferlach48 notes that in AML, a diverse range of new compounds is under preclinical and clinical investigation. A goal is to develop targeted treatment concepts that are based on interference with molecular genetic or epigenetic mechanisms. The author writes that “future therapy in AML will hopefully be based more on genetic and epigenetic targets that will be individually defined for each patient.” Haferlach suggests that the search for new diagnostics and therapeutic targets “should be conceived as integral parts, as only their perfect interaction will be able to pave the way to targeted treatment for patients with AML.”48 Conclusion Recent advances in understanding the pathogenesis of hematopoietic malignancies and the advent of high-throughput technologies have the potential to facilitate rigorous translational research toward the discovery, development, and clinical validation of novel biomarkers for the early detection as well as for disease progression and recurrence.49 There is also a need for the development and improvement of specific technologies and methods for quantitative detection of novel biomarkers associated with these hematopoietic malignancies. Such biomarkers – for early stage detection or for identification and stratification of groups at risk for aggressive disease or for detection of minimal residual disease50 – may improve overall survival rates by reducing the high levels of morbidity and mortality associated with late stage diagnosis. To this end, careful clinical assessment of minimal residual disease enables detection of lingering leukemia burden following treatment with improved sensitivity compared to morphological analyses alone. Detection of residual burden following therapy supports the notion that there is a clinically relevant value to treatment decisions based on this type of analysis. Thus, the need for standardization of minimal technologies and their interpretations must be emphasized. In the future, the investment in biomarker discovery, elucidation and application will remain necessary, if not indispensable.
  10. 10. www.quintiles.com | 10 The challenges of patient stratification and treatment optimization through specific biomarkers are inherently grounded in understanding the biology of those markers and how to best utilize them in the clinic. Given the considerable complexity of the hematologic malignancies we are dealing with, the discovery of determinant biomarkers is a critical exercise. However, researchers will also have to effectively negotiate the full range of difficulties of prospective verification and clinical validation for the most promising factors. In the future, to make treatment of hematologic malignancies affordable and value-driven, the investment in biomarker discovery, elucidation and application will remain necessary, if not indispensable. In summary, if the application of the aforementioned techniques continues to progress genetic associations and profiles that can be either effectively drugged or targeted, then efficacious personalized medicine for numerous hematologic malignancies is potentially within reach.
  11. 11. 11 | www.quintiles.com References 1 http://grants.nih.gov/grants/guide/pa-files/PA-12-220.html 2 http://grants.nih.gov/grants/guide/pa-files/PA-12-220.html 3 Munshi NC. Investigative Tools for Diagnosis and Management. Hematology 2008;298-305 4 Larsen JT, Kumar SK, Dispenzieri A, Kyle RA, Katzmann JA, Rajkumar SV. Serum free light chain ratio as a biomarker for high-risk smoldering multiple myeloma.Leukemia, October 16, 2012. 5 Asher Chanan-Khan A, Giralt S. Importance of Achieving a Complete Response in Multiple Myeloma, and the Impact of Novel Agents. JCO May 20, 2010 vol. 28 no. 15 2612-2624. 6 Hoering A, Crowley C, Shaughnessy JD, Hollmig K, Alsayed Y, Szymonifka J, Waheed S, Nair B, van Rhee F, Anaissie E, Barlogie B. Complete remission in multiple myeloma examined as time-dependent variable in terms of both onset and duration in Total Therapy protocols. Blood, August 13, 2009 vol. 114 no. 7 1299-1305. 7 Sawyer JR. The prognostic significance of cytogenetics and molecular profiling in multiple myeloma. Cancer Genetics, Volume 204, Issue 1, January 2011, Pages 3–12. 8 Monaghan, S.A., Dai, L., Mapara, M.Y., Normolle, D.P., Gollin, S.M., and Lentzsch, S. Longitudinal bone marrow evaluations for myelodysplasia in patients with myeloma before and after treatment with lenalidomide. Posted online on January 28, 2013. (doi:10.3109/10428194.2012.755177). 9 Circulating endothelial progenitor cells as potential prognostic biomarker in multiple myeloma. Leukemia & Lymphoma. April 2012, Vol. 53, No. 4 , Pages 635-640 10 Jones CI, Zabolotskaya MV, King AJ, et al. British Journal of Cancer (2012) 107, 1987–1996. 11 Posted online on November 26, 2012, Leukemia & Lymphoma 12 Fragioudaki M, Tsirakis G, Pappa CA, et al. Leukemia Research, Volume 36, Issue 8, August 2012, Pages 1004–1008. 13 Micallef J, Dharsee M, Chen J, Ackloo S, Evans K, Qiu L, Chang H. Applying mass spectrometry based proteomic technology to advance the understanding of multiple myeloma. Journal of Hematology & Oncology 2010, 3:13. http://www.jhoonline.org/ content/3/1/13 14 National Cancer Institute web page, Non-Hodgkin Lymphoma. http://www.cancer.gov/ cancertopics/types/non-hodgkin 15 Salles G, de Jong D, Xie W, Rosenwald A, Chhanabhai M, Gaulard P, Klapper W, Calaminici M, Sander B, Thorns C, Campo E, Molina T, Lee A, PfreundschuhM, Horning S, Lister A, Sehn LH, Raemaekers J, Hagenbeek A, Gascoyne RD, Weller E. Prognostic significance of immunohistochemical biomarkers in diffuse large B-cell lymphoma: a study from the Lunenburg Lymphoma Biomarker Consortium. Blood (June 2011);117(26):7070-78. 16 British Journal of Haematology, July 2012, Volume 158, Issue 2, Pages 153–296.
  12. 12. www.quintiles.com | 12 17 Kamper P, Bendix K, Hamilton-Dutoit S, et al. Tumor-infiltrating macrophages correlate with adverse prognosis and Epstein-Barr virus status in classical Hodgkin’s lymphoma. Haematologica February 2011 96: 269-276. 18 Panico L, Ronconi F, Lepore M, Tenneriello V, Cantore N, Carmela Dell’Angelo A, Ferbo U, Ferrara F. Prognostic role of tumor-associated macrophages and angiogenesis in classical Hodgkin lymphoma. Leukemia & Lymphoma. (doi:10.3109/10428194.2013.7784 05) 19 Gaslain S, Stolbrink M, Jones M, Soilleux E. CD68+ cell numbers and dendritic cell numbers and phenotype fail to predict the presence of a MYC rearrangement in aggressive B-cell lymphomas. Journal of Hematopathology, December 2012, Volume 5, Issue 4, p. 291-296. 20 Lenz G, Wright G, Dave SS, Xiao W, Powell J, Zhao H, Xu W, Tan B et al. (2008).Stromal Gene Signatures in Large-B-Cell Lymphomas. New England Journal of Medicine 359 (22): 2313–2323. 21 Choi WW, Weisenburger DD, Griner TC, et al. Clin Cancer Res. 2009 Sep 1;15(17):5494- 5502 22 Klapper W, Kreuz M, Kohler CW, et al., Molecular Mechanisms in Malignant Lymphomas Network Project of the Deutsche Krebshilfe, Blood February 23, 2012 vol. 119 no. 8 1882- 1887. 23 Linderoth J, Edén P, Ehinger M, Valcich J, Jerkeman M, Bendahl PRO, Berglund M, Enblad G et al. (2008). Genes associated with the tumour microenvironment are differentially expressed in cured versus primary chemotherapy-refractory diffuse large B-cell lymphoma. British Journal of Haematology 141 (4): 423–432. 24 Bagg A. B Cells Behaving Badly: A Better Basis to Behold Belligerence in B-Cell Lymphomas. Hematology 2011; 330-35. 25 National Cancer Institute web site, General Information About Chronic Lymphocytic Leukemia. http://www.cancer.gov/cancertopics/pdq/treatment/CLL/healthprofessional/ page1/AllPages 26 Gribben JG. Molecular Profiling in CLL. Hematology 2008; 444-49. 27 Ponader S, Chen SS, Buggy JJ, Balakrishnan K, Gandhi V, Wierda WG, Keating MJ, O’Brien S, Chiorazzi N, Burger JA. (2012) The Bruton tyrosine kinase inhibitor PCI-32765 thwarts chronic lymphocytic leukemia cell survival and tissue homing in vitro and in vivo. Blood 119: 1182-1189. 28 de Rooij MF, Kuil A, Geest CR, Eldering E, Chang BY, Buggy JJ, Pals ST, Spaargaren M. (2012) The clinically active BTK inhibitor PCI-32765 targets B-cell receptor (BCR)- and chemokine-controlled adhesion and migration in chronic lymphocytic leukemia. Blood 119: 2590-2594. 29 Ann Oncol (2012) 23 (suppl 5): v12-v22. 30 Moussay E, Wang K, Cho JH, et al. Proc Natl Acad Sci US A. 2011 Apr 19; 108(16):6573-8. 31 Clin Oncol 30:488-496, 2011. 32 Roboz GJ. Novel Approaches to the Treatment of Acute Myeloid Leukemia. Hematology
  13. 13. 13 | www.quintiles.com 2011;43-50. 33 http://seer.cancer.gov/statfacts/html/amyl.html#survival 34 Transforming Clinical Research in the United States: Challenges and Opportunities: Workshop Summary. Institute of Medicine (US) Forum on Drug Discovery, Development, and Translation. Washington (DC): National Academies Press (US); 2010. 35 Schlenk RF, Dohner K, Krauter J, et al. Mutations and treatment outcomes in cytogenetically normal acute myeloid leukemia. N Engl J Med 2008; 358 (18): 1909-1918. 36 Delhommeau F, Dupont S, Della Valle V, et al. Mutation in TET2 in myeloid cancers. N Engl J Med. 2009;360(22):2289-2301. 37 Abdel-Wahab O, Mullally A, Hedvat C, et al. Genetic characterization of TET1, TET2, and TET3 alterations in myeloid malignancies. Blood. 2009;114(1):144-147. 38 Gelsi-Boyer V, Trouplin V, Adelaide J, et al. Mutations of polycomb-associated gene ASXL1 in myelodysplastic syndromes and chronic myelomonocytic leukaemia. Br J Haematol. 2009;145(6):788-800. 39 Abdel-Wahab O, Manshouri T, Patel J, et al. Genetic analysis of transforming events that convert chronic myeloproliferative neoplasms to leukemias. Cancer Res. 2010;70(2): 447- 452. 40 Mardis ER, Ding L, Dooling DJ, et al. Recurring mutations found by sequencing an acute myeloid leukemia genome. N Engl J Med. 2009;361(11):1058-1066. 41 Marcucci G, Maharry K, Wu YZ, et al. IDH1 and IDH2 gene mutations identify novel molecular subsets within de novo cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. J Clin Oncol. 2010;28(14):2348-2355. 42 Ward PS, Patel J, Wise DR, et al. The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha- ketoglutarate to 2-hydroxyglutarate. Cancer Cell. 2010;17(3):225-234. 43 Yamashita Y, Yuan J, Suetake I, et al. Array-based genomic resequencing of human leukemia. Oncogene. 2010;29:3723-3731. 44 Ley TJ, Ding L, Walter MJ, et al. DNMT3A mutations in acute myeloid leukemia. N Engl J Med. 2010;363(25):2424-2433. 45 Yan XJ, Xu J, Gu ZH, et al. Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia. Nat Genet. 2011;43(4):309-315. 46 Van Vlierberghe P, Patel J, Abdel-Wahab O, et al. PHF6 mutations in adult acute myeloid leukemia. Leukemia. 2011; 25(4):130-134. 47 Patel JP and Levine RL. How do novel molecular genetic markers influence treatment decisions in acute myeloid leukemia? Hematology 2012; 28-34. 48 Haferlach T. Molecular Genetic Pathways as Therapeutic Targets in Acute Myeloid Leukemia. Hematology 2008; 400-11. 49 http://grants.nih.gov/grants/guide/pa-files/PA-12-220.html 50 DiNardo CD, Luger SM. Beyond morphology: minimal residual disease detection in acute myeloid leukemia. Curr Opin Hematol. 2012 Mar;19(2):82-8.
  14. 14. 14 | www.quintiles.com Harish Dave, MD, MBA Vice President, Global Medical Strategy Head, Hematology and Oncology, Quintiles With fifteen years of academic hematology-oncology experience, Dr. Dave oversees a number of hematology and oncology studies at all phases of drug development, and provides strategy and guidance. His areas of therapeutic experience include cancers of lung, breast, colorectal, brain, sarcoma, pancreas, prostate, melanoma and liquid tumors. Dr. Dave has served as a P.I. on multiple studies, served as Chairman of an NIH Study Section and chaired the Research and Development Committee at a major academic medical institution. In the latter capacity, Dr. Dave oversaw all research and IRB-related activity, reviewing and managing over 170 protocols annually. He received his medical degree from the University of Sheffield Medical School, England and his residency training at Royal Medical Postgraduate Medical School System, University of London, England. He conducted basic research in gene regulation and gene therapy at the NIH. He is board certified in internal medicine, medical oncology and hematology and was previously Associate Professor of Medicine at George Washington University and Assistant Chief of Hematology and Chief of Laboratory of Molecular Hematology at the Veterans Affairs (VA) Medical Center in Washington, DC. Chris Learn, Ph.D, PMP Senior Clinical Project Manager, Oncology, Quintiles Chris Learn, Ph.D, PMP, is Senior Clinical Program Manager, Oncology, Quintiles. He has over 10 years of experience leading investigator led oncology trials in academic settings and in industry. His expertise includes the development of molecular immunotherapies for malignant glioma. Prior to joining Quintiles, he held senior positions in clinical research at Surgical Review Corporation, The Hamner Institutes for Health Sciences and Duke University Medical Center. About the Authors Ronald Lieberman, MD Senior Medical Director, Oncology, Quintiles Dr. Lieberman is a senior director in the medical and scientific services group in Quintiles’ Oncology therapeutic area. He is board certified in internal medicine, hematology/ oncology, clinical pharmacology and blood banking, and has served as the medical and scientific advisor on clinical trials in the following hematology-oncology indications: solid tumors (lung, prostate, breast, colon, bladder, gliomas, melanoma, kidney, ovary, head and neck, stomach, esophagus, and liver) and hematologic malignancies (leukemia, lymphoma, myeloma, and bone marrow/stem cell transplantation (GVHD). He has also served as a global and regional medical advisor supporting multiple registrational Phase 3 trials for drugs and biologics. Dr. Lieberman’s special interests include early phase clinical trials-translational oncology/biomarkers, PK and Bayesian guided clinical trial design, immunotherapy and clinical development of new anticancer drugs and biologics.
  15. 15. 15 | www.quintiles.com Prior to joining Quintiles, Dr. Lieberman has had an active career in clinical development with more than 30 years experience including leadership positions at the FDA (CDER); National Institutes of Health/National Cancer Institute (NIH/NCI) and Biopharma (MedImmune). At FDA, he served as a team leader in the Division of Oncology Drug Products and Assistant Director of Clinical Pharmacology Training. At NIH/NCI, he served as Program Director for Blood Diseases and Resources, Clinical Immunology, Acting Chief of the Prostate and Urologic Cancer Group and Attending Physician in the NCI Oncology Clinic. At MedImmune, he served as Medical Director for clinical development, translational oncology and business development/due diligence. He has authored/coauthored approximately 100 articles and serves on the Editorial Board/Expert Reviewer for several journals.
  16. 16. Copyright © 2013 Quintiles. 16.15.21-042013 Contact Us: US Toll Free: 1 866 267 4479 Direct: +1 973 850 7571 On the web: quintiles.com Email: clinical@quintiles.com

×