June 2012, Vol 1, No 2
Implementing the Promise of Personalized Cancer CareUncategorized
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Until recently, cancer treatment relied solely on histologic diagnosis for determining systemic therapy. Aside from considerations related to a patient’s underlying comorbidities and performance status, there was minimal deviation from an organ-of-origin–based treatment strategy. This relatively primitive understanding of malignancy failed to exploit biological and molecular differences within each cancer type to allow for selection of a more rational therapy focused on individual patient and tumor characteristics. However, exciting strides are currently being made in the field of cancer research and treatment, both with solid tumors and hematologic malignancies. As our understanding of cancer initiation, progression, and response to treatment has advanced, and technical achievements in bioinformatics and genome/proteome analysis have been made, the opportunities to tailor therapies to individual patients have markedly expanded. Indeed, an expanding pool of predictive biomarkers has now ushered in the era of personalized medicine for cancer patients. Several of these markers have transformed patient care, and testing for these markers has become mandatory prior to initiation of therapy. As a result, targeted therapeutics that rely on the molecular characteristics of a malignancy offer hope for personalized care in cancer with improved patient outcomes.
However, because a rapidly increasing number of molecular biomarkers are now becoming clinically available, a significant need exists for healthcare pro fessionals who manage patients with cancer to keep abreast of the latest information on tumor biomarkers and how to appropriately use them to optimize therapy for their patients. In this regard, the Global Biomarkers Consortium (GBC) was developed. The GBC is a community of worldrenowned healthcare professionals coming together to provide a forum for the improved understanding of the clinical application of prognostic and predictive molecular biomarkers toward optimal personalized care for patients with cancer. The inaugural conference of the GBC was held on March 9-11, 2012, in Orlando, Florida. This monograph will highlight the key findings from that meeting.
Biomarkers Today – the Link to Therapeutics
The ultimate goals in individualized or personalized cancer therapy are to:
- Understand the biology of each tumor with respect to risk of recurrence, pathways that drive growth and resistance, and potential targets for therapy
- Identify patients who need treatment due to adverse tumor biology characteristics (in addition to traditional tumor characteristics)
- Identify benefits of a specific therapy or type of therapy
- Avoid ineffective therapies
Our current tools allow for an assessment of risk and of the overall benefit of chemotherapy, but in order to achieve true, personalized cancer therapy, tools are needed to predict benefit from a specific therapy and take into account patient preferences. In early-stage breast cancer, we learned from a retrospective analysis by the Early Breast Cancer Trialists’ Collaborative Group that estrogen receptor (ER) status could predict the grade of disease, extent of proliferation, likelihood of a response to chemotherapy or hormone therapy, and overall survival. 1 Similarly, in prospective trials of patients with node-positive early breast cancer, ER status was shown to predict response to enhanced chemotherapy regimens, including doxorubicin/cyclophosphamide plus pac litaxel, where only patients with ER-negative tumors derived benefit from these enhanced regimens with respect to disease recurrence and overall survival.2 Subsequently, multigene assays were developed (MammaPrint and Oncotype) that provided prognostic information but were not sufficient by themselves to predict chemotherapy benefit, merely complementing clinicalpathological factors.3-5 Unfortunately, breast cancer research has not moved forward from this point. At present, while we can look broadly at the benefit from chemotherapy, hormone therapy, and HER2-directed therapy, we are not yet able to predict which patient will benefit most from a specific therapy.
However, there is a great deal of research ongoing in this area. For example, in patients with HER2-positive metastatic breast cancer, the combined blockade of the HER2 receptor with trastuzumab and pertuzumab resulted in the longest progression-free survival (PFS) in the first-line setting of any subset of breast cancer other than ER-positive disease (Table 1).6-10 Thus, when a treatable target is identified (in this case, HER2), specific agents can be developed that result in improved clinical outcomes and that can overcome drug resistance.
Table 1. Targeting the HER2 Receptor: The First Druggable Target Since Estrogen Receptor6,8-10
Taking these results a step further, 3 prospective clinical trials (NeoSphere, Neo-ALLTO, and GeparQuinto), in which patients with HER2-overexpressing breast cancer were treated with trastuzumab plus pertuzumab or trastuzumab plus lapatinib, included serial sampling of tumor tissue. Subsequent biomarker analysis of the tissue samples taken during the NeoSphere trial revealed that while HER2 overexpression was associated with sensitivity to pertuzumab, there was no predictive value in the biomarkers tested for patients with specific treatment regimens.11 The challenge is in identifying the appropriate set of biomarkers that can be clearly related to benefit from a specific therapy. Failure to do so up to this point may have contributed to the withdrawal of approval for bevacizumab for HER2-negative disease, simply because of the lack of a reliable biomarker to identify the subset of breast cancer patients who would benefit from this drug.
The area where we have had the greatest success is in the use of inhibitors of the mammalian target of rapamycin (mTOR). As tumors become increasingly resistant to hormone therapy, they up-regulate signal – ing through the phosphoinositide 3-kinase (PI3K)/Akt pathway, and a recent study investigated biomarkers that could help identify patients who would benefit from blocking that pathway. In the BOLERO-2 trial, patients with hormone receptor (HR)-positive breast cancer that had become resistant to hormonal therapy were randomized to treatment with everolimus (an mTOR inhibitor) plus exemestane versus placebo plus exemestane. As shown in Table 2, median PFS was significantly improved in patients treated with everolimus plus exemestane compared with those treated with placebo plus exemestane, suggesting that adding an inhibitor of the mTOR pathway can overcome resistance to hormone therapy.12
Table 2. Everolimus in Hormone Receptor–Positive Advanced Breast Cancer12
There are a number of pathways for more effective breast cancer therapy that will require rethinking on how drug candidates are tested in clinical trials and what molecular targets should be pursued. Efforts are being made in these directions – in the I-SPY 2 trial, in which promising agents are being screened in combination with standard chemotherapy in the neoadjuvant setting to accelerate the process of identifying drugs that are effective for specific breast cancer subtypes; in attempts to design agents that target deregulated pathways; and by development of clinically and molecularly appropriate treatment protocols based on multidisciplinary input from clinical oncologists, surgeons, radiation oncologists, molecular biologists, geneticists, pathologists, and patient advocates.
Comprehending the Next Generation of Oncology Care
A technological revolution is driving the expectation that we are on the verge of a transformation of approaches to cancer management with an attendant improvement in patient outcomes.13 In this regard, there are an unprecedented number of targeted therapies in clinical trials – about 500 targeted therapies investigating about 140 genomic alterations, with approximately 40 potential genomic targets that will require clinical testing in the near future. In lung cancer, the recognition that EGFR mutations are correlated with clinical response to gefitinib and erlotinib therapy is well known.14-16 However, this was not an isolated example – subsequent work showed that approximately 7% of patients with non–small cell lung cancer (NSCLC) expressed a transforming EML4-ALK fusion gene that was distinct from the EGFR mutations.17 This led to the dramatic finding that 57% of NSCLC patients with the ALK rearrangement responded to treatment with crizotinib, a small-molecule oral inhibitor of ALK tyrosine kinase (Figure 1),18 which recently led to the drug’s approval for ALK-positive NSCLC.
Figure 1. Tumor Responses to Crizotinib in Patients with ALK-Positive Non-Small Cell Lung Cancer18
However, this is an evolving process, as shown by the recent identification of the ROS1 rearrangement that defines a molecular subset of NSCLC (~2% of patients) with distinct clinical characteristics and impressive clinical sensitivity to crizotinib,19 as well as the KIF5B-RET transformation in colorectal cancer and NSCLC cells that are sensitive to multikinase inhibitors that inhibit RET.20
Our ability to characterize the majority of aberrations in actionable cancer genes has made it possible to rapidly test potential biomarkers based on targeting the patients most likely to benefit in a trial. However, implementation of molecular testing into patient care requires that all tests be performed in a Clinical Laboratory Improvement Amendments–certified laboratory with a high degree of quality control and an understanding of the accuracy of the results. As our ability to characterize the genome of tumors from specific patients improves, the number of aberrations discovered and the challenge to determine their relevance to response to targeted therapies will increase, demanding the development of bioinformatic approaches to determine which aberrations are the drivers of effective therapy, and novel, critically experimental approaches designed to test the predictive value of the molecular aberrations.
The future of cancer care also relies on the techniques that we are able to develop to uncover actionable cancer genes. The techniques should be used in a complementary effort and include both old and new methodologies: cytomorphology, cytogenetics, immunophenotyping, gene expression profiling, nextgeneration sequencing, histology, fluorescence in situ hybridization (FISH), and molecular genetics.
Incorporating Personalized Medicine Into Practice: A Natural Evolution of Evidence-Based and Translational Medicine to Personalized Medicine
Over the past several years, there has been an increase in our understanding of cancer pathogenesis at the molecular level, along with an appreciation of numerous pathways that have been implicated in cancer development and growth. This knowledge has led to the concept that we should be conducting biomarker enrichment trials to improve the efficiency of new therapeutic development for personalized medicine. In conducting biomarker enrichment trials, there are 2 major considerations:
- Does a therapeutic agent benefit “biomarker-positive” and/or “biomarker-negative” patients?
- Was this the right biomarker to test, ie, what is the right marker, what are the appropriate materials or specimens to test, and do we have a good biomarker assay available?
There are several possible trial designs in a biomarker enrichment trial. A retrospective validation in which periodic tissue and serum specimens are collected from patients enrolled in a trial in which they are followed for several years. Biomarkers are then retrospectively evaluated and correlated to the pathophysiology and clinical outcomes for each patient. A prospective validation can be carried out in several different ways:
- Biomarker testing is performed on all patients, but randomization is not based on the results from biomarker testing
- Biomarker testing is performed on all patients prior to randomization, and randomization is based on the biomarker-positive or biomarker-negative status of each patient. Each biomarker-randomized patient is then rerandomized or stratified to an experimental arm or a control. This design is especially interesting in the setting of VEGF inhibitors in breast cancer
- The most complex strategy involves a biomarkerguided randomization in parallel with a markerblinded randomization. The biomarker-positive group is placed into the experimental arm, the biomarker- negative group into the control group, and the biomarker-blinded group is rerandomized to an experimental arm or control. The challenge in this design is in getting the physician and patient to agree to follow a therapeutic approach based on biomarker analysis, ie, some patients may actually be resistant to the concept of personalized medicine! This type of biomarker enrichment trial typically required a larger number of enrolled patients
Table 3 outlines several of the most important issues to consider in designing biomarker enrichment trials. The reproducibility and validity of the biomarker assay is especially important since this is the basis for the concept of personalized medicine. Unfortunately, in breast cancer, for example, the discordance rate among different laboratories is ~10% for HR and progesterone receptor and ~15% for HER2; variability among immunohistochemistry experts is ~8% for FISH testing, although this could be reduced to 3% to 4% if the pathologists examined the specimens together (Perez E. Written communication from the experience at Mayo Clinic).
Table 3. Important Issues to Consider in Designing Biomarker Enrichment Clinical Trials
These types of trials are already prompting a rethinking of how personalized cancer treatment can be accomplished. For example, in breast cancer, early detection of metastasis-prone tumors and characterization of residual metastatic cancers are important in efforts to improve patient management. Applications of genomescale molecular analysis technologies are making these complementary approaches possible by revealing molecular features uniquely associated with metastatic disease. Assays that reveal these molecular features will facilitate detection prior to metastatic spread, and knowledge of these features will guide development of therapeutic strategies that can be applied when metastatic disease burden is low, thereby increasing the probability of a curative response.21 This so-called “Omic Approach” is complementary to the traditional anatomic and histologic analyses of breast cancer. However, the genomic approach to the treatment of breast cancer is complex and must take into account gene expression profiles, RNA structure, genomic rearrangements, and gene sequence mutations in order to integrate these features into a model that predicts tumor behavior. Figure 2 outlines the schema used at the Mayo Clinic in accomplishing this goal – DNA and RNA are collected, whole genome sequencing is performed, and a multidisciplinary bioinformatics team is convened to make decisions on applying the data to research and clinical practice.
Figure 2. Mayo Clinic Integrated Approach to Defining the Genomic Landscape of Breast Tumors for Research and Practice
While incorporation of translational medicine into practice is essential for the future of personalized medicine in oncology, we must not lose sight of the fact that incorporating evidence-based guidelines and pathways into clinical practice is also important in improving patient outcomes.
There are 2 types of evidence-based guidelines:
- A process map of integrated interventions over time (eg, the National Comprehensive Cancer Network [NCCN] guidelines) that addresses the coordination of care and specifically illuminates the continuum of care
- Individual guidelines in which the scope is more restricted, and there may be as many as 1000 decision points posing an enormous challenge in terms of a comprehensive review and analysis of the literature
How do guidelines fit into decisions about treatments? They should follow clinical decision-making pathways that offer a range of appropriate treatments for specific situations that are included in the guidelines, with the goal of reducing variability in care.22
Reimbursement Challenges and Strategies for Personalized Medicine in Oncology – Perspectives for Providers and Patients
To achieve the reality of personalized medicine in oncology, we need to understand how payers review molecular biomarker data for coverage and how these coverage decisions impact providers and patients. Molecular biomarkers are not a special category of test from a payer perspective, and payers evaluate and pay for biomarker testing in the same way they manage all other diagnostic tests (Pezalla E. Written communication of the regulations from Aetna Pharmacy Management). In general, diagnostic tests are always covered under the medical benefit even if they are being used to determine if the patient should receive a specific pharmaceutical, but they are not covered under the pharmacy benefit. Molecular biomarker testing may even be required in some instances by payers before approving a specific therapy; in those cases, the testing will always be covered. However, providers and patients should be aware of channel management by some payers, ie, a requirement to use a particular source for the diagnostic test. This is not merely a cost control issue, it also ensures access to the highest quality laboratories available.
Most payers review all testing, pharmaceuticals, and procedures based on the supporting clinical evidence, primarily in the form of published literature, national professional guidelines (eg, NCCN), FDA findings, and information from developers or manufacturers (Pezalla E. Personal communication of the regulations from Aetna Pharmacy Management). The results of these reviews are typically published in clinical policy bulletins, which are available online for providers and patients. These bulletins classify tests as experimental or clinically necessary, cite the conditions under which the diagnostic test is deemed necessary, provide a review of the literature to support the stated policy, and list payment and diagnostic codes. These are invaluable for providers in managing their patients with cancer. The major criteria for coverage of a molecular biomarker test are that the test accomplishes what it purports to do in terms of accuracy, reliability, and reproducibility, and that the test has a measurable impact on medical decision making and patient outcomes.
The inaugural conference of the Global Biomarkers Consortium represented a unique opportunity for a diverse, world-renowned faculty to convene to discuss the current state of the art in tumor biomarkers from the perspective of providers, payers, and patients. The meeting focused on the use of molecular biomarkers in an effort to fully realize the promise of personalized medicine in oncology.
Because of the wide range of topics discussed, this overview has captured only a small portion of the topics discussed and has avoided discussion of the development of molecular biomarkers for each specific solid tumor and hematologic malignancy discussed at the meeting. These topics will be reviewed in future editions of Personalized Medicine in Oncology.
- Early Breast Cancer Trialists’ Collaborative Group (EBCTG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365:1687-1717.
- Berry DA, Cirrincione C, Henderson IC, et al. Estrogen-receptor status and outcomes of modern chemotherapy for patients with node-positive breast cancer. JAMA. 2006;295:1658-1667.
- Sotriou C, Pusztai L. Gene-expression signatures in breast cancer. N Engl J Med. 2009;360:790-800.
- Albain KS, Paik S, van’t Veer L. Prediction of adjuvant chemotherapy benefit in endocrine responsive, early breast cancer using multigene assays. Breast. 2009;18(suppl 3):141-145.
- Knauer M, Mook S, Rutgers EJ, et al. The predictive value of the 70- gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat. 2010;120:655-661.
- Slamon DJ, Leyland-Jones B, Shak S, et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. 2001;344:783-792.
- Mass RD, Press MF, Anderson S, et al. Evaluation of clinical outcomes according to HER2 detection by fluorescence in situ hybridization in women with metastatic breast cancer treated with trastuzumab. Clin Breast Cancer. 2005;6:240-246.
- Marty M, Cognetti F, Maraninchi D, et al. Randomized phase II trial of the efficacy and safety of trastuzumab combined with docetaxel in patients with human epidermal growth factor receptor 2-positive metastatic breast cancer administered as first-line treatment: the M77001 study group. J Clin Oncol. 2005;23:4265-4274.
- Baselga J, Cortés J, Kim SB, et al; CLEOPATRA Study Group. Pertuzumab plus trastuzumab plus docetaxel for metastatic breast cancer. N Engl J Med. 2012;366:109-119.
- Gianni L, Romieu G, Lichinitser M, et al. First results of AVEREL, a randomized phase III trial to evaluate bevacizumab (BEV) in combination with trastuzumab (H) + docetaxel (DOC) as first-line therapy for HER2- positive locally recurrent/metastatic breast cancer (LR/mBC). Presented at the CTRC-AACR San Antonio Breast Cancer Symposium, December 6-11, 2011, San Antonio, TX. Abstract S4-8.
- Gianni L, Bianchini G, Kiermaier A, et al. Neoadjuvant pertuzumab (P) and trastuzumab (H): biomarker analyses of a 4-arm randomized phase II study (NeoSphere) in patients (pts) with HER2-positive breast cancer (BC). Presented at the CTRC-AACR San Antonio Breast Cancer Symposium, December 6-11, 2011, San Antonio, TX. Abstract S5-1.
- Baselga J, Campone M, Piccart M, et al. Everolimus in postmenopausal hormone-receptor-positive advanced breast cancer. N Engl J Med. 2012;366:520-529.
- Mills GB. An emerging toolkit for targeted cancer therapies. Genome Res. 2012;22:177-182.
- Paez JG, Janne PA, Lee JC, et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science. 2004;304:1497-1500.
- Lynch TJ, Bell DW, Sordella R, et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med. 2004;350:2129-2139.
- Pao W, Miller V, Zakowski M, et al. EGF receptor gene mutations are common in lung cancers from “never smokers” and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci U S A. 2004;101:13306-13311.
- Soda M, Choi YL, Enomoto M, et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature. 2007; 448:561-566.
- Kwak EL, Bang YJ, Camidge DR, et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med. 2010;363:1693-1703.
- Bergethon K, Shaw AT, Ou SH, et al. ROS1 rearrangements define a unique molecular class of lung cancers. J Clin Oncol. 2012;30:863-870.
- Lipson D, Capelletti M, Yelensky R, et al. Identification of new ALK and RET gene fusions from colorectal and lung cancer biopsies. Nat Med. 2012;18:382-384.
- Griffith OL, Gray JW. ‘Omic approaches to preventing or managing metastatic breast cancer. Breast Cancer Res. 2011;13:230.
- National Comprehensive Cancer Network; NCCN Guidelines. www.nccn.org.
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Commercial Support Acknowledgment
This activity is supported by educational grants from Abbott Laboratories, Daiichi Sankyo, Genentech, and Millennium: The Takeda Oncology Company.
This activity was developed for medical oncologists and hematologists, pathologists, geneticists, advanced practice oncology nurses, research nurses, clinical oncology pharmacists, and genetic counselors involved in the management of patients with solid tumors or hematologic malignancies, and interested in the use of molecular tumor biomarkers to help optimize patient care.
After completing this activity, the participants should be better able to:
- Assess emerging data and recent advances in the discovery of tumor biomarkers, their impact on the treatment of patients with solid tumors and hematologic malignancies, and how to integrate key findings into clinical practice.
- Discuss the role of tumor biomarkers in designing personalized therapy for patients with cancer, including management of treatmentrelated adverse events.
Before the activity, all faculty and anyone who is in a position to have control over the content of this activity and their spouse/life partner will disclose the existence of any financial interest and/or relationship(s) they might have with any commercial interest producing healthcare goods/services to be discussed during their presentation(s): honoraria, expenses, grants, consulting roles, speakers bureau membership, stock ownership, or other special relationships. Presenters will inform participants of any off-label discussions. All identified conflicts of interest are thoroughly vetted by University of Cincinnati and Medical Learning Institute, Inc. for fair balance, scientific objectivity of studies mentioned in the materials or used as the basis for content, and appropriateness of patient care recommendations.
Planners and Managers Disclosures
Rick Ricer, MD, UC CME Content Reviewer, has nothing to disclose.
Lorrie McSherry, RN, BSN, OCN, MLI Peer Reviewer, is on the advisory board for Onyx.
Patricia Woster, PharmD, MLI Peer Reviewer, is a former employee of Eisai and has stock in Pfizer.
Rüdiger Hehlmann, MD, PhD, has nothing to disclose.
*Hope S. Rugo, MD, is a researcher for Genentech/Roche, GlaxoSmithKline, ImClone, Merck, Novartis, and Sanofi/BiPar, and is on the speakers bureau for Bayer, Intellikine, and Genomic Health. *Content will include non–FDA-approved uses.
The associates of University of Cincinnati, Medical Learning Institute, Inc., the accredited providers for this activity, Center of Excellence Media, LLC, and Core Principle Solutions, LLC, do not have any financial relationships to products or devices with any commercial interest related to the content of this CME/CE activity for any amount during the past 12 months.
The information provided at this CME/CE activity is for continuing education purposes only and is not meant to substitute for the independent medical judgment of a healthcare provider relative to diagnostic and treatment options of a specific patient’s medical condition. Recommendations for the use of particular therapeutic agents are based on the best available scientific evidence and current clinical guidelines. No bias toward or promotion for any agent discussed in this program should be inferred.
Estimated time to complete this activity: 1.0 hour
Initial Release Date: June 15, 2012
Expiration Date: June 15, 2013
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