Market Opportunity for Molecular Diagnostics in Personalized Cancer ...

Chapter 14

Market Opportunity for Molecular Diagnostics in Personalized Cancer Therapy Elemer Piros, PhD,a Istvan Petak, MD, PhD,b Attila Erdos, MD,c John Hautman, JD,a and Julianna Lisziewicz, PhDa aeMMUNITY

Inc., Bethesda, Maryland, USA Medicine Group, Budapest, Hungary cCaVax Kft., Szeged, Hungary bOncompass

Keywords: targeted drugs, immunotherapy, vaccine, cancer, genetic biomarker, predictive biomarker, prognostic biomarker, companion diagnostics, companion treatments, personalized medicine, personalized treatments, molecular diagnostics, market opportunity, comprehensive tumor profiling, targeted immunotherapy, nanomedicine

14.1 Introduction According to a survey conducted in 2001, 75% of cancer patients did not respond to treatment, indicating that a “one size fits all” approach is less than ideal [1]. The heterogeneity of the molecular profile of individual tumors coupled with the differential ability of individuals to process drugs is the main factor explaining the variability in responses to current cancer treatments. Handbook of Clinical Nanomedicine: Law, Business, Regulation, Safety, and Risk Edited by Raj Bawa, Gerald F. Audette, and Brian E. Reese Copyright © 2016 Pan Stanford Publishing Pte. Ltd. ISBN 978-981-4669-22-1 (Hardcover), 978-981-4669-23-8 (eBook) www.panstanford.com

Market Opportunity for Molecular Diagnostics in Personalized Cancer Therapy

Over the past two decades, there have been significant advances in our understanding of some of the common molecular aspects of cancer, facilitating targeted drug development for patients sharing features that are identified from their tumor. The introduction of trastuzumab in 1998 ushered in the era of personalized medicine in oncology. Trastuzumab is indicated for HER2+ breast cancer patients identified by the companion diagnostic HercepTest. For patients who do not overexpress HER2 (75–80% of the total), trastuzumab would not be beneficial at all. In a hypothetical “all comers” clinical trial, trastuzumab probably would have required many more patients to prove a statistically significant benefit. The actual registration trial of trastuzumab included only 470 patients screened by the HercepTest and took only 1.6 years to complete. Based on the response rate and frequency of HER2 amplification, it was calculated that without the pre-selection of patients, the minimum number of patients needed for the trial would have been 2200 and the trial would have taken 10 years. The “targeted” trial saved $35 million and the faster market entry led to $1.7 billion of additional revenue [2, 3]. Personalized treatment (for a definition see Fig. 14.1) is obviously more attractive for patients and payers. However, drug developers have been reluctant to embrace the concept because of the reduced size of the treatable patient population. The commercial success of trastuzumab itself ($6.6 billion sales in 2013) may have led to the realization of a significant market and full insurance reimbursement opportunity, even for subpopulationtargeted drugs. “Recent biomedical research breakthroughs, including the sequencing of the human genome and a deeper understanding of the molecular underpinnings of disease, have the potential to transform the treatment of disease and the practice of medicine. One of the most profound changes to medicine is the movement toward tailored therapeutics, or personalized medicine. As defined by the President’s Council of Advisors on Science and Technology, personalized medicine is the tailoring of medical treatments to the individual characteristics of each patient, and the ability to classify individuals into subpopulations based on their susceptibility to a particular disease or their responses to a specific treatment.”

Figure 14.1 Definition of personalized medicine (Source: FDA Innovation Report, 2011).

Introduction

Fast forward to 2012, where one-third of all approved drugs contained genomic biomarker information in the original data submission, of which some were relevant to patient selection, efficacy/activity or dosing parameters [4]. The Personalized Medicine Coalition found that 30% of surveyed biopharma companies require the inclusion of biomarkers for all of their experimental drugs and in 50% of all clinical trials DNA is collected for potential biomarker development [5]. While there were no new treatment options for malignant melanoma approved between 1990 and 2010, during the last four years, four new drugs were approved in the US. Three of these drugs (vemurafenib, dabrafenib, and trametinib) are targeting a specific mutation in the BRAF gene—present in ~50% of melanoma patients. Companion diagnostics to detect the mutation were also approved simultaneously. The fourth drug, ipilimumab, an immunotherapy, was approved without a biomarker that could identify the estimated 11% responsive patient population. Whereas the incidence of melanoma is relatively low in the US (76,000 new cases annually [6]), prior to the approval of targeted drugs, there was no market for melanoma biomarker tests. An accidental finding led to the rapid development and approval of a targeted drug (crizotinib) by pharmaceutical giant, Pfizer (New York, NY), for a very small population of non-small cell lung cancer patients. Four years prior to the approval of crizotinib in 2011, the anaplastic lymphoma kinase (ALK) was identified as a potential therapeutic target for lung cancer [7]. Pfizer happened to have a kinase inhibitor in development with known activity against ALK. Since only 5% of lung cancer patients actually harbor the ALK genetic defect, for every treated patient, 20 genetic tests will have to be performed. Still, Pfizer decided to conduct a Phase 1/2 trial including only preselected patients for ALK translocation. Due to the extremely high response rate in this population, FDA granted an ultrafast marketing approval without further randomized studies. Crizotinib costs almost $10,000 per month and is reimbursed by payers since patients identified by the ALK biomarker are responding to therapy for almost a year [8]. Sequential treatment with alternative pathway inhibitors and combination approaches are being pursued to address tumor escape. In addition, in an era when all the genetic alterations can be identified at a relatively low cost by next generation sequencing,


single-gene based companion diagnostics will offer limited clinical and commercial value. On the other hand, a single test that delineates the comprehensive molecular profile of a tumor and organizes the matching treatment options for the patient will revolutionize the field of oncology. In this context, the term companion therapeutics describes the paradigm of one genetic diagnostic test identifying multiple treatment options.

14.2 Targeted Drug Revolution

Currently, there are more than 30 targeted therapies in clinical use and more than 200 in clinical development. Moreover, hundreds of such compounds are in preclinical development. Thus, a “tsunami” of targeted drugs could arrive to the market in the next years. The wave was initiated in 2003 by the Human Genome Project [9] and amplified by the Cancer Genome Atlas Project during the past 10 years [10]. The simple idea to target the molecular cause of cancer, similarly to targeting bacteria in infectious disease, has proven to be to be a winning strategy; therefore many pharmaceutical companies are developing therapies for these “driver” genes. Presently, only 10–20% of cancers can be treated with “driver-hitting” drugs in clinical use; however, a patient could receive immediate benefit if referred to a clinical trial where a targeted compound is being tested against a “driver” gene present in the patient’s tumor. It has been proven that patients participating in molecular matching trials benefit significantly more from the experimental treatments than from the registered chemotherapy protocol they received before entering the trial [11].

14.3 The $1000 Genome Is Here

In his 2010 book, Kevin Davies writes, “The $1,000 genome has long been considered the tipping point that would open the floodgates to this [personalized genomic medicine] revolution” [12]. On January 14, 2014, Illumina (San Diego, CA) announced that with their HiSeqTM Ten sequencing system the $1000 genome goal has been achieved [13]. The floodgates are indeed open. However, today we are confronted with another floodgate: molecular informatics.

The $1000 Genome Is Here

14.3.1 Mapping the Cancer Genome Even before this momentous milestone announcement by Illumina in 2006, the National Cancer Institute (NCI) had initiated The Cancer Genome Atlas project to sequence 500 tumor samples for 20 different cancer types (10,000 samples) [10]. While researchers are still analyzing the data, at least two noteworthy findings have already emerged from this sequencing effort [14]. First, within a tumor type—for example lung, liver, or brain—the molecular signature indicates the existence of multiple subtypes. Accordingly, tumor classification, based on tissue origin alone, would have to be re-examined. Second, genetic aberrations in the same molecular pathways were observed across tumor samples from different tissues. These two findings suggest that a molecular signaturespecific description and diagnosis of a tumor, independent of tumor location, may lead to more optimized, personalized patient care. Cancer is now viewed as a large collection of rare diseases. The Catalogue of Somatic Mutations of Cancer (COSMIC) database at Sanger Institute contains 1.5 million mutations [15]. Although some of these are not true “driver” mutations, but are simply neutral “passenger” mutations, the complexity seems enormous. However, based on statistical methods, mutations of a limited number of genes, 138 “driver” genes, appear to be main causes of cancer. Each human tumor contains 2–8 of these “driver” cancer genes in different combinations [15]. Although some of the gene mutations are more frequent than others, it is obvious that most molecular subtypes will occur with a frequency of around 1%. These rare molecular subtypes may be associated with better or worse prognosis, or sensitivity or resistance to therapy. Therefore, larger scale studies are required to better understand the consequences of mutations with rare frequency.

14.3.2 Lung Cancer Master Protocol

An unprecedented collaboration between academia, government, and industry, the so-called Lung Cancer Master Protocol (LungMAP) trial, got under way in June 2014 [16]. The trial, conducted


by NCI’s newly formed National Clinical Trials Network, will focus on finding treatments for a subtype of lung cancer, squamous cell carcinoma (~25% all lung cancer). Every patient’s tumor sample will be analyzed by next generation sequencing (NGS) by commercial company, Foundation Medicine. Amgen (Thousand Oaks, CA), Genentech (South San Francisco, CA), Pfizer, AstraZeneca (London, UK), and Medimmune (Gaithersburg, MD) will test four different targeted drugs and a single anti-PD-L1 immunotherapy in five different arms of the Lung-MAP trial, stratified by tumor genetic signature. Drugs from five different sponsors have never before been tested in the same clinical trial. Based on a demonstration of early clinical benefit, each drug can be advanced to registration-track trials. The study, which was designed in close collaboration with the FDA, could yield multiple winners (i.e., approved drugs) from a single “master” protocol. The Lung-MAP trial is the first large, prospectively designed study, where the clinical utility of molecular profiling by NGS will be validated.

14.3.3 Exceptional Responders Initiative

Some drugs, which have failed in clinical trials, have nonetheless been proven effective in a very small subset of patients, who were actually “exceptional” or “super responders.” In some cases, the positive response was linked to the genetic background of the tumor. The NCI will explore 100–200 such patients in a trial with dozens of drugs that were not approved for a particular cancer type, because of low (1–10%) response rates [17]. Potential linkage to genomic alterations will be investigated by sequencing 200– 300 genes from tumor samples. In the past, such an analysis led to the first very effective targeted therapy of lung cancer. Gefitinib, developed by AstraZeneca, failed in a randomized Phase 3 trial, but some exceptional good responders were identified (5–10% of patients). Subsequent biomarker studies have led to the discovery of EGFR mutations, which identify this subpopulation of responders. Today, there are three targeted drugs registered for this small subset of patients whose life expectancy, due to these treatments, has become almost three times longer than with the previous standard of care [18].

Molecular Diagnostics for Targeted Drugs

14.3.4 Companion Therapeutics Squamous cell carcinoma, like all other cancer types, is characterized by a host of genomic alterations. A single diagnostic test, interrogating aberrations in a single gene, is not adequate to capture the complexity of individual tumors. Commenting on the LungMAP trial, Richard Pazdur, head of the FDA’s oncology division stated [19]: “The paradigm of each drug with its own companion diagnostic will not be a coherent drug development pattern as we go forward in oncology.”

While the FDA is in the process of finalizing guidance for the development of companion diagnostics, the agency will most likely have to factor in the complexity of cancer. Indeed, the FDA has already acknowledged the impact of cancer complexity. In the trade journal, BioCentury, Elizabeth Mansfield, the Director of the Personalized Medicine Staff at the Office of In Vitro Diagnostics and Radiological Health in the FDA’s Center for Devices and Radiological Health, was quoted as saying [19]: “The companion diagnostic paradigm is changing. With next-gen sequencing, you can get all the information you need with one test. We recognize that next-gen sequencing tests that can measure many things at one time may change that paradigm in a short time. FDA hopes to be able to tell manufacturers how to move forward with panels that measure many things.”

14.4 Molecular Diagnostics for Targeted Drugs It is envisaged that within five years every single tumor sample will be profiled by NGS. The prerequisites to achieve this goal include proving analytical validity and clinical utility and having reimbursement in place. Panelists at a recent discussion organized by the National Comprehensive Cancer Network (NCCN) were asked the following question: “By 2020 will we have a system in place that all patients receive tumor genome sequencing and research, regulation, and reimbursement are aligned and capable of handling all the information?”


The answer was a unanimous “yes”, except for the timing, which was thought to be optimistic [20]. According to the American Cancer Society, there are 1.6 million newly diagnosed cancer patients in the United States every year [21]. In addition, a portion of the 12 million patients living with cancer in the United States could also benefit from a comprehensive molecular diagnostic test. The European market size is comparable to the US market [22].

14.4.1 Commercial Opportunity for the First Movers

Several companies have begun to offer services to characterize the molecular signature of tumor samples. For example, Foundation Medicine (Cambridge, MA) currently provides a service assessing ~250 biologically relevant tumor genes by NGS. The goal is to detect aberrations in pathways for which marketed or investigational drugs can be identified for the patient. In a prospective study, it was demonstrated that in a cohort of 98 patients, the originally recommended therapy was modified for 28% of the patients based on the NGS test results [23]. As more and more targeted therapies enter clinical testing and eventually the market, it is anticipated that a much higher number of treatment decisions will be based on molecular profiling. Over the last two years, Foundation Medicine has analyzed more than 22,000 tumor specimens [24] and anticipates to test between 22,000 and 25,000 samples in 2014 [25]. Recently, large diagnostic companies, such as LabCorp (Burlington, NC), Qiagen (Venlo, the Netherlands), Thermo Fisher Scientific (Waltham, MA) and Quest Diagnostics (Madison, NJ), have also launched oncology sequencing test panels comprised of 30–400 actionable genes [26–29]. European diagnostic company KPS Life Sciences (Budapest, Hungary) lists 58 genes for their standard NGS oncology panel [30]. KPS Life Sciences incorporates the pre-screening of the clinical trials for patients based on their clinical history and molecular profile to provide relevant treatment options to the physician. On average, KPS finds ongoing clinical trials, which are positively associated with a patient’s tumor profile, for 87% of the cancer patients referred to KPS for testing [30].

Molecular Diagnostics for Targeted Drugs

Memorial Sloan Kettering Cancer Center (MSKCC) in New York City is the pre-eminent academic institution in comprehensive tumor profiling. MSKCC physicians led a pioneering study to match lung cancer patients with targeted therapies [31]. Oncogenic drivers were identified in 64% of the 733 patients tested. Clinicians were able to recommend targeted drugs to 28% of these patients. Encouragingly, the median survival of those treated with targeted drugs was 3.5 years vs. 2.4 years for those receiving conventional treatment. MSKCC has developed an oncogenic test panel (MSK-IMPACTTM) to reliably and accurately screen for mutations in 341 genes. Leveraging its expertise in clinical annotation of test results, MSKCC established collaboration with Quest Diagnostics to extend molecular testing across the US [32]. The two parties will share patient data to enable rapid translation of discoveries into clinically actionable information to optimize patient care. MSKCC also recently received a $100 million gift to establish a Center for Molecular Oncology, which will build out NGS capabilities to eventually analyze every single cancer patient entering the MSKCC facility [33]. MSKCC expects to sequence more than 10,000 tumor samples annually.

14.4.2 Interpretation of NGS DATA—Need Help!

The field of molecular oncology is advancing at an incredible pace. To stay up to date, it is estimated a physician would have to spend 160 hours reading medical publications every single week [34]. According to a recent study, only 20% of the knowledge derived from available trial-based evidence is used by oncologists when diagnosing and treating patients [35]. Twenty-two percent of 160 physicians from an NCI-designated comprehensive cancer center from Boston had low confidence about their knowledge of genomics and 26% doubted they could make treatment recommendations from genomics data [36]. Reports on the molecular profile of tumors and corresponding treatment options provided by Foundation Medicine and others somewhat alleviate the burden on the oncologist. However, the list of available treatment options provided in the reports does not factor in the patient’s medical history and most importantly the

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reports do not rank order drugs or experimental therapies identified in the reports as treatment options. Which one is the best option? What if every oncologist could rely on the expertise and experience of the entire clinical staff of MSKCC and MD Anderson? Soon they might. Both MSKCC [37] and MD Anderson [38] are teaching IBM’s supercomputer Watson to become an oncology “consultant.” In 2012 IBM and MSKCC, in collaboration with private insurer WellPoint, began “feeding” Watson 600,000 pieces of medical evidence, two million pages from medical journals and the ability to search through 1.5 million patient records. MD Anderson contributes its Oncology Expert Advisor database, containing hundreds of thousands of patient records, including treatment outcomes. IBM plans to make Watson’s capabilities available to any institution or individual physician through a cloud-based service. Would Watson replace the oncologist? Probably not, but it could assist in providing the best, evidence-based, personalized treatment for the patient. Flatiron Health takes a different approach [39]. Rather than turning to academic centers, they collect anonymized patient data from 1000s of community-based cancer specialists. The data, including patient outcomes to various therapies, including targeted drugs, is made accessible via cloud servers to physicians to provide evidence-based treatment options. In the future, health information technology will empower every oncologist to treat patients based on state of art scientific knowledge.

14.4.3 Who Will Pay for Molecular Profiling?

Foundation Medicine’s solid tumor test and hematological malignancy test have a list price of $5800 and $7200, respectively [40]. A representative from insurer WellPoint claimed at the aforementioned NCCN-organized panel discussion that for its insured cancer population, the cost of sequencing would be $350 million/year, necessitating an increase in premiums of $10/year/member [41]. At this point, NGS tumor profiling is considered by insurers to be experimental. WellPoint, Medicare and other insurers do not yet have coverage in place for this type of service. However, Foundation Medicine and other private and public stakeholders are investing in prospectively designed clinical

Molecular Diagnostics for Targeted Immunotherapy

studies to establish the clinical utility of the molecular profiling of every tumor. Providing molecular profiling each year of the tumors of a million cancer patients (of the 1.6 million newly diagnosed in the United States) would cost $6–7 billion for the healthcare system. The biggest value provided in exchange for this expenditure of healthcare dollars is the avoidance of treating a patient with therapies that would not be effective for that patient, as molecular profiling also includes information on mutations that the patient does not have. As we will make a case below, where an oncologist could identify the ipilimumab-responding patient prior to the commencement of treatment via a biomarker, the annual savings to the healthcare system would be ~$750 million. This represents the amount saved by avoiding unmatched, useless treatment. Analysts following Foundation Medicine estimate that the addressable US market for NGS in oncology is one million patients per year [42], but their opinion as to the value for the market leader ranges from $1.8 billion [43] and $4–7 billion [44].

14.5 Molecular Diagnostics for Targeted Immunotherapy

Immunotherapy has emerged as a new treatment paradigm exploiting a patient’s own immune system to fight cancer immune system to fight cancer [45]. Cancer cells are present in every person, but in most they are recognized as foreign to the body and killed by the person’s immune system responses. Immunotherapies boost a cancer patient’s immune system to eliminate cancer cells. Two immunotherapeutic approaches are of particular interest: (i) immune checkpoint inhibition, which aims to counteract the physiologic mechanisms of immune tolerance co-opted by some tumors, and (ii) vaccine therapy, which enables enhanced exposure to tumor antigen. Immune checkpoint inhibition therapies include the monoclonal antibody blockade of the cytotoxic T-lymphocyte antigen-4 (CTLA-4) with ipilimumab, as well as antibody blockade of the programmed cell death-1 (PD-1) receptor and the PD-1 ligand. Vaccines include antigen specific therapies, which induce specific antitumor immunity against relevant tumor-associated

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antigens, such as melanoma-associated antigen-A3 (MAGE-A3) and membrane-associated glycoprotein (MUC-1). With immunotherapy, cancer could become a chronically manageable and perhaps preventable disease.

14.5.1 Gold Rush for Immunotherapies

Encouraged by initial successes, the pharmaceutical industry began to invest heavily to develop immunotherapies. There are over 1000 clinical trials being conducted to test new immunotherapies, vaccines and cell therapies [46, 47]. Several large pharmaceutical companies have entered the field, including Bristol-Myers Squibb (New York, NY), Merck (Whitehouse Station, NJ), Roche (Basel, Switzerland) and AstraZeneca. These companies have committed an estimated $1.3B to evaluate their immunotherapy drugs in 78 clinical trials enrolling 19,000 patients [48]. Analysts project that the immunotherapy market will reach $35 billion in value by 2023, based on the currently visible drug pipeline [49]. If realized, cancer immunotherapy would represent the largest ever pharmaceutical opportunity, exceeding previous mega-blockbuster classes, such statins for cholesterol management.

14.5.2 Large Benefit for a Small Subgroup

Immunotherapies have been shown to provide a very significant clinical benefit, albeit to a small segment of the patient population. Some melanoma patients, who were expected to live for six months, are alive up to 10 years following treatment with the socalled checkpoint inhibitor, ipilimumab [50]. Unfortunately, 89% of patients do not respond at all and many of these non-responders may experience substantial toxicity [51]. Another checkpoint inhibitor, nivolumab (different target from ipilimumab), produced a higher, 32% response rate in a 107-patient advanced melanoma trial [52]. When ipilimumab was combined with nivolumab, the response rate rose to 42% [53]. While response rates improved, toxicity also increased: 53% of treated patients experienced grade 3–4 adverse events [53]. Data from another promising checkpoint inhibitor, pembrolizumab (same target as nivolumab), were reported at the 2014 ASCO conference. Response rates were 40%


for patients with no prior history of ipilimumab treatment and 28% for those who had been exposed to ipilimumab previously [54]. These data demonstrated that checkpoint inhibitors cause serous toxicity for some patients even in the absence of any benefit. MAGE-A3 is present in numerous tumors including melanoma and lung cancer and is absent in normal adult tissue, with the exception of the testis and placenta. For this reason, MAGE-A3 is a selective target for tumor-specific immunotherapy. MAGE-A3 vaccinations blocked the relapse of cancer in many lung cancer patients, albeit the improvement in disease free survival was not statistically significant when compared to placebo [55]. The results demonstrated low response rates and the need of a biomarker to enrich likely responders to cancer vaccines. Consequently, an 84-gene expression signature biomarker was developed for the MAGE-A3 antigen expressing cancers [56]. Despite the initial promising results, this gene expression biomarker did not enrich the responding patient population. MAGE-A3 vaccination was found not to be superior against control, when tested in large clinical trials in non-small cell lung cancer and separately in melanoma patients [5]. These disappointing clinical results were achieved even though in earlier trials, ~30% of patients had exhibited immune responses against the vaccine. MUC-1, another tumor-associated antigen, is normally expressed in epithelial cells. MUC-1 expression is greatly increased in cancer cells, including non-small cell lung cancer (NSCLC), breast, colorectal, prostate, and multiple myeloma. A MUC-1 peptide vaccine also missed the primary endpoint in a large Phase 3 trial in NSCLC. In the trial, which randomized 1239 patients, median over survival was 25.6 months in the vaccine arm vs. 22.3 months in the placebo arm [58]. However, in a large predefined subset of patients (n = 806), who were treated with chemotherapy concurrently with the vaccine, a 10-month survival benefit was observed, prompting the sponsor to re-initiate development [59]. Because of the favorable safety profile of vaccines, they represent excellent opportunities, either as a single agent or in combination studies, if responder populations can be identified prior to treatment. IMA901 renal cell cancer vaccine consists of nine tumorassociated peptides (TUMAPs) confirmed to be naturally presented

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in human cancer tissue. A clinical trial conducted in 64 human leukocyte antigen A (HLA-A)*02+ subjects with advanced cancer showed that only 26% of the treated renal cell carcinoma patients responded to more than one of the nine peptides. Coincidentally, these so-called multi-peptide responders experienced a significant survival benefit in the Phase 2 trial [60]. A Phase 3 program is under way in order to confirm the benefit observed previously. Not all nine tumor antigen peptides selected by Walter and co-workers in the IMA901 trial [60] may actually be present in a particular patient’s tumor. In addition, even if present, the patient’s immune system may not be able to process these peptides due to immunogenetic incompatibility, as illustrated by the observation that 74% of the patients either did not responded to the vaccine, or responded to one out of nine peptides [60]. There are research efforts under way to “ultra-personalize” peptide vaccines [60, 61]. According to this paradigm, the individual’s tumor sample would be screened for antigens that are unique to the tumor, as emerged in the process of tumorigenesis (neo-antigens). The peptides identified would be further tested for the patient’s ability to process them for immune recognition. A specific, individualized peptide cocktail would be manufactured for every single patient.

14.5.3 Payers Demand Biomarkers for Immunotherapies

What is the difference between a responder and a nonresponder patient to immunotherapy? We do not have an answer. Immunotherapies, such as vaccines (peptide, protein or DNA) or checkpoint inhibitors, either activate or reactivate T cell responses against specific tumor antigens [62]. These specific T cells can recognize and kill tumor cells. T cell responses depend on the individual’s ability to process vaccine or tumor antigens by the MHC/HLA molecules of the immune system. The genes encoding MHC/HLA proteins are amongst the most polymorphic in the entire genome [63]. Consequently, every patient generates different T cell responses. Indeed, when first rejecting reimbursement for ipilimumab, the National Institute for Health and Care Excellence (NICE) in the UK alluded to the possibility of HLA diversity (subtype) as a potential predictor of responder status [64]:


“NICE has concluded that a lack of appropriate biomarker (e.g. HLA subtype) to predict patients who are likely to benefit is a major deficiency in the current Yervoy [ipilimumab] submission.”

In the pivotal ipilimumab trial, only patients with HLA-A*0201 type were enrolled [65]. The study did not test the hypothesis of a potential correlation between responders and HLA status. HLA restriction was included because in a control arm, ipilimumab was combined with a peptide vaccine gp100, which binds to HLAA*0201, a common allele, with high affinity [66]. In addition, trials with dozens of peptide vaccines, which were designed for binding to other common HLA alleles (A1, A2, A3), have also failed to increase response rates even when given only to individuals with these haplotypes (Table 14.1). It is not surprising that a correlation between responders and HLA status was not found, when singling out only one specific allele of the thousands identified to date. Table 14.1

HLA biomarker does not select likely responders to immunotherapy

Indication Treatment

HLA restriction Sponsor Response rate

Renal cell IMA-901 carcinoma peptide mix

HLA-A02

Breast cancer

NeuVax peptide vaccine

Prostatic Neoplasm

Prostavac DNA vaccine

HLA-A2 or HLA-A3

Melanoma Gene-engineered HLA-A 0201 lymphocytes Anti-p53 TCR-Gene

Transduced lymphocytes

Melanoma Peptide vaccine

Melanoma Helper and multi-epitope peptide vaccine

HLA-A2

HLA-A 0201

HLA-A*0201 HLA-A1,-A2, or -A3

Immatics 26% [60] NCI

20–50% [67]

NCI

40% [69]

NCI NCI NCI NCI

25% (partial) [68] 8% [70]

10% [71]

5–47% [72]

14.5.4 Impact of Personalizing Immunotherapy The discovery of immunogenetic biomarkers to select or enrich likely responders to immunotherapies would represent a major advance in the treatment of cancer.

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According to IMS Health, the worldwide drug spending on oncology treatment is approaching $100 billion [73]. The US bears the largest burden with an estimated 41% of the total drug expenditures [73]. Should a good portion of the current crop of immunotherapies succeed in gaining approval, the burden could become even more substantial in the absence of responder selection biomarker. Combination or sequential administration to all comers of $100,000+ immunotherapies, many of which are already being tested in the clinic, could strain the healthcare system towards a tipping point. The current “bill” for US payers for the first immunotherapy drug, ipilimumab, is estimated to be a relatively modest ~$1 billion (Fig. 14.2). Should, as envisaged, “immunotherapy will likely form the backbone of 60% of all developed world cancer management regimes” the bill could rise to a staggering $35 billion [49]. If a suitable biomarker for ipilimumab were to be discovered, the savings, due to prescribing only to likely responders, could be $3.8 billion over a five-year period for ipilimumab alone (Fig. 14.2). IPILIMUMAB CASE STUDY

• Approved for melanoma in 2011 in the US • Response rate: 11% • Median survival benefit: + 4 months; responder survival is up to 10 years • Cost: $120,000 • 2013 sales: $960MM • Number of patients treated: ~8000 • Number of patients benefited: ~880 (11%) • Ipilimumab is widely reimbursed (in US)—total bill for payors: $960MM • Total Rx bill, if responders were pre-identified: $132MM • • • •

Total Dx bill for all 8000 patients: $10,000 × 8000 = $80MM Total Dx + Rx bill for 8000 patients: $212MM Total savings to payors: ~$750MM for ipilimumab in 1 year Total savings for ipilimumab over 5 years: $3.8B

Figure 14.2 Pharmacoeconomic benefit of a biomarker test.

Should a universal biomarker be discovered applicable for the entire class of immunotherapies and assuming a 30% overall


response rate, theoretically, 70% of the projected $35 billion (i.e. $25 billion) could be saved by the healthcare system every year. Offsetting the savings would be the potential eligibility of the patient to an alternative therapy within or outside of the immunotherapy class. Assuming a $100,000 price/treatment figure, the $35 billion revenue estimate implies 350,000 patients treated. With a universal biomarker, seventy percent, or 245,000 patients, would not have to be needlessly exposed to a potentially toxic therapy that is prospectively determined NOT to provide any benefit. Patients, physicians, and payers would adopt and demand such a biomarker test that could personalize immunotherapy.

14.5.5 A Glimpse at the Future: Nanomedicine

By virtue of their design, the class of protein and monoclonal antibody checkpoint inhibitors and T cell activators cannot be easily modified to target non-responsive populations. When combining these therapies to broaden efficacy, toxicity is also enhanced. Off-target toxicity is a consequence of the systemic delivery and the lack of cancer tissue specificity of these therapies. However, cancer vaccines are well tolerated and the targeted delivery of antigens expressed only by the tumors to the lymph nodes greatly improves their immunogenicity [74]. Targeted delivery of DNA-encoded protein antigens is achieved by nanoparticle formulation mimicking infectious organisms. Targeting specific cells of the immune system, such as the dendritic cells, could maximize effectiveness by stimulating cytotoxic T cell populations to eliminate cancer [75]. “When a particular cancer vaccine belongs to a class of agents that has been previously administered to humans, a body of safety and activity data may already exist. In such situations, depending on the relevance of the available clinical data, additional preclinical studies may not be needed to support the starting dose and dosing schedule. The sponsor should provide comprehensive information in the IND, including existing clinical data regarding the activity and safety profile, to support the safety of the cancer vaccine in the proposed trial”

Figure 14.3 FDA guidance on cancer vaccines.

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Nucleic acid-based, nanoparticle formulated targeted vaccines hold a great promise because of their safety and versatility. These vaccines offer a cost-effective opportunity not only to treat cancer patients but also prevent cancer in individuals with high risk. Once the therapeutic index of a prototypical vaccine is established, additional vaccines, addressing different populations, could be developed in a straightforward fashion. While the antigens encoded by DNA or RNA might be different, the delivery system (vector and formulation) remains the same; therefore, the toxicity profile of various members of a family of vaccines is anticipated to be similarly benign. The FDA recognizes the reduced necessity of additional preclinical testing, once the prototypical vaccine has been evaluated in human subjects [76] (Fig. 14.3).

14.6 Conclusions

Targeted drugs, vaccines, and immunotherapies are gaining ground every month. So what does it take for a company to capitalize on the biggest pharmaceutical business opportunity of the 21st century? First and foremost, a new medicinal product must be susceptible to “personalization” by a biomarker. It is envisioned that cost-effective personalization of targeted therapies may be accomplished with platform technology that supports the development of a “family” of medicinal products. Genetic biomarkers for cancer medicine will be identified based on the molecular profile of the tumor and the genetic background of the patient. Molecular profiling of every tumor will lead to a comprehensive molecular diagnosis suitable to select the best matching targeted medicine for every single patient. Payers will reimburse molecular diagnostic services as they reimburse any blood test that helps physicians to select treatment for their patients. We expect that in five years every patient will benefit from such cancer molecular diagnosis and targeted medicine. This “personalization” of the practice of medicine as described above will have profound and long lasting positive effects on a multitude of fronts. From the individual perspective, a patient seeking therapies for cancer will receive better care since any therapy prescribed by the doctor will have a high likelihood of being effective. This means the patient will have to endure potential

Conclusions

side effects from a prescribed therapy only in cases where the prescribed therapy is predicted to provide the patient clinical benefit. In addition, there will be a substantial business opportunity for diagnostic companies with health information technology to access, organize, analyze, and interpret “Big Data” generated from widespread NGS-based tumor profiling. Molecular diagnostic companies could inform oncologists about the best matching treatment protocols and play a pivotal role in advising payers on the likely efficacy of therapies to reimburse (Fig. 14.4).

Figure 14.4 Molecular diagnostic-guided, personalized cancer treatment. Present cancer treatment is based on clinical experience. Selection of the best physician has a significant impact on outcome. In the future, every physician will use molecular diagnosis and health information technology and every patient will obtain the best treatment available for her/his disease.

From a macroeconomic perspective, “personalization” has the potential to salvage on a worldwide basis a healthcare system, which is not presently sustainable based on the current therapeutic models. “Personalization” will eliminate or at least substantially reduce the prescribing of a costly therapy for a patient where molecular diagnostic testing and biomarkers demonstrate that the therapy will not be effective for that patient, thereby saving the healthcare system billions of dollars. Thus, with the

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personalization of cancer treatment with molecular diagnostics, the healthcare system will finally be able to start reversing a decades old downward spiral since payers will only reimburse therapies that are likely to be effective and safe for patients. As with the personal computer revolution three decades ago, there will be both winners and losers among the companies attempting to ride the personalized medicine wave. Microsoft (Redmond, WA) became one of the winners in the personal computer revolution by deploying an operating system which became the de facto industry standard and then developing a family of applications integrated with that operating system. Similarly, the winners in the personalized medicine revolution will be those companies that develop widely applicable molecular diagnostic tests and biomarkers with companion medicine offerings designed to treat cancer, regardless of physical location, based on the genetics of both the patient and the patient’s cancer.

Abbreviations

HER2: human epidermal growth factor receptor 2 BRAF: human gene that encodes a protein called B-Raf ALK: anaplastic lymphoma kinase NCI: National Cancer Institute COSMIC: Catalogue of Somatic Mutations of Cancer NGS: next generation sequencing FDA: Food and Drug Administration EGFR: epidermal growth factor receptor NCCN: National Comprehensive Cancer Network MSKCC: Memorial Sloan-Kettering Cancer Center CTLA-4: cytotoxic T-lymphocyte antigen-4 PD-1: programmed cell death-1 receptor MAGE-A3: melanoma-associated antigen-encoding gene-A3 MUC-1: Mucin-1 ASCO: American Society of Clinical Oncology NSCLC: non-small cell lung cancer HLA: human leukocyte antigen MHC: major histocompatibility complex NICE: National Institute for Health and Care Excellence

About the Authors

Disclosures and Conflict of Interest Istvan Petak declares that he is a founder, scientific director, and shareholder of KPS Life Sciences, a company mentioned in this chapter. Dr. Lisziewicz, Dr. Piros, and Mr. Hautman declare that they are officers and shareholders of eMMUNITY, Inc., which is focusing on the personalization of immunotherapies against cancer and the development of a universal biomarker for immunotherapies. No writing assistance was utilized in the production of this chapter and the authors have received no payment for its preparation.

Corresponding Author

Dr. Julianna Lisziewicz President, eMMUNITY Inc. 4400 East West Highway Suite 1126, Bethesda, MD 20814, USA Email: [email protected]

About the Authors

Elemer Piros is the chairman of the board of eMMUNITY, Inc. Prior to joining eMMUNITY, he was a senior biotechnology analyst at Rodman & Renshaw, Burrill Securities and Spear, Leeds & Kellogg, a wholly owned subsidiary of Goldman Sachs. From 1990 to 2000, Dr. Piros conducted academic research in the field of neuroscience, focusing on understanding the molecular mechanism of communication in the nervous system. Istvan Petak is a co-founder and chief scientific officer of Oncompass Medicine Group. Dr. Petak is an expert of the molecular pathology and pharmacology of anti-cancer targeted therapies. He was a Fulbright Scholar at the Department of Molecular Pharmacology of St. Jude Children’s Research Hospital, Memphis, USA, where he

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conducted research on the molecular regulation of cell death in cancer cells induced by chemotherapy and targeted agents. In 2003, he and Dr. Richard Schwab founded KPS Life Sciences, which is now part of the Oncompass Medicine Group. They were among the first to treat EGFR mutant lung cancer patients based on the molecular evidence, which was published in the Journal of Clinical Oncology in 2005. Dr. Petak has published 60 articles in this field. He is an editor of Current Signal Transduction Therapy and invited author of Nature Reviews Drug Discovery. Attila Erdos is a medical doctor by training and received his MBA degree from INSEAD (France). After leaving practice, he worked in various senior level positions at SmithKline Beecham Pharmaceuticals and was leading the Central European Office of GE Healthcare. During the last 10 years, Dr. Erdos has been engaged in developing several biotechnology ventures and startups, including molecular laboratories and other diagnostic facilities.

John Hautman is the Chief Executive Officer of eMMUNITY, Inc. Prior to joining eMMUNITY, Inc. He was a senior partner and Head of the Intellectual Property practice of the Washington, DC-based law firm of Hogan & Hartson (now Hogan Lovells).

Julianna Lisziewicz is the president and chief scientific officer of eMMUNITY, based in Bethesda, Maryland, USA. In 2013, she co-founded eMMUNITY, Inc., a biotech company focusing on the development of genetic biomarkers for the personalization of immunotherapy against cancer. From 1998 to 2013, Dr. Lisziewicz was the president and chief executive officer of Genetic Immunity, where she had directed the translational research program on nanomedicine-based HIV-specific immunotherapy from discovery to successful phase II clinical trials. In 1994, she co-founded the non-profit Research Institute for Genetic and Human Therapy (RIGHT) and co-directed

References

the research, clinical, and business affairs in the USA and Italy. RIGHT was focusing on the treatment of HIV/AIDS from multiple perspectives: virology, molecular biology, immunology, and medicine. From 1990 to 1995, she was head of the Antiviral Unit in the Laboratory of Tumor Cell Biology at the NCI, NIH in Bethesda, Maryland, USA. While at NIH, she discovered and developed antisense oligonucleotide therapy and gene therapy for HIV/ AIDS. In 2005, she was awarded the Marie Curie Chair by the EU. She received her PhD in molecular biology from the Max-Planck Institute, Gottingen, Germany.

References

1. Spear, B. B., Heath-Chiozzi, M., Huff, J. (2001). Clinical application of pharmacogenetics. Trends Mol. Med., 7(5), 201–204. 2. Cook, J., Hunter, G., Vernon, J. (2009). The future costs, risks, and rewards of drug development. Pharmacoeconomics, 27, 355–363.

3. Press, M., Seelig, S. (2004). Lessons learned from the development of a diagnostic to predict response to herceptin: Targeted medicine— from concept to clinic. Thomson Financ. Street Events Conf. Rep. Target. Med., November 11, 10–11.

4. Janet Woodcock (FDA): “Coming of age” of personalized medicine. Available at: http://1.usa.gov/1qYNBsX (accessed on April 18, 2010). 5. The Case for Personalized Medicine. Available at: http://bit.ly/TiMYxY (accessed on April 18, 2015).

6. Melanoma Incidence Statistics, National Cancer Institute. Available at: http://www.cancer.gov/cancertopics/types/melanoma (accessed on April 18, 2015).

7. Soda, M., Choi, Y. L., Enomoto, M., Takada, S., Yamashita, Y., et al. (2007). Identification of the transforming EML4-ALK fusion gene in nonsmall cell lung cancer. Nature, 448, 561–566.

8. Crizotinib Prescription Information. Available at: http://bit.ly/ 1lIMBne (accessed on February 18, 2015).

9. All About the Human Genome Project. National Human Genome Research Institute. Available at: http://www.genome.gov/10001772 (accessed on February 18, 2015).

10. The Cancer Genome Atlas. Available at: http://1.usa.gov/1lIMEPZ (accessed on February 18, 2015).

23

24


11. Tsimberidou, A. M., Iskander, N. G., Hong, D. S., Wheler, J. J., Falchook, G. S., et al. (2012). Personalized medicine in a phase I clinical trials program: the MD Anderson Cancer Center Initiative. Clin. Cancer Res., 18(22), 6373–6383.

12. Davies, K. (2010). The $1,000 Genome. Free Press, New York, NY, p. 13.

13. Illumina press release. Available at: http://bit.ly/1eIsg1C (accessed on February 18, 2015). 14. Weinstein, J. N., Collisson E. A., Mills, G. B., Mills Shaw, K. R., Ozenberger, B. A., et al. (2013). The Cancer Genome Atlas Pan-Cancer Analysis Project. Nat. Gen., 45, 1113–1120. 15. Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A. Jr, Kinzler, K. W. (2013). Cancer genome landscapes. Science, 339 (6127), 1546–1558.

16. Lung-MAP Launches. NCI Press Release. Available at: http://1.usa. gov/1q4dRSg (accessed on February 18, 2015).

17. My Cancer Genome Feature: Table of Anti-cancer agents. Available at: http://www.mycancergenome.org/file/newsletters/2/My%20 Cancer%20Genome%20June%202013%20Newsletter.pdf (accessed on February 18, 2015). 18. Peták, I., Schwab, R., Orfi, L., Kopper, L., Kéri, G. (2010). Integrating molecular diagnostics into anticancer drug discovery. Nat. Rev. Drug Discov., 9(7), 523–535.

19. Usdin, S. (2013). Beyond companion diagnostics. BioCentury, 21(42), A13. 20. 2014 NCCN Summit. Available at: http://bit.ly/1zgw4Bb (accessed on February 18, 2015).

21. Cancer Facts and Statistics. American Cancer Society. Available at: http://www.cancer.org/research/cancerfactsstatistics/ (accessed on February 18, 2015).

22. GLOBOCAN 2012: Estimated Cancer Incidence Mortality and Prevalence Worldwide in 2012. Available at: http://globocan.iarc.fr/ Default.aspx (accessed on February 18, 2015).

23. Braiteh, F., Porter Sharman, J., Richards, D. A., Rama Skelton, M., Cheryl DeMarco, L., et al. (2014). Effect of clinical NGS-based cancer genomic profiling on physician treatment decisions in advanced solid tumors. American Society for Clinical Oncology Annual Meeting (Chicago, IL) abstract number 11109.

References

24. Foundation Medicine Securities and Exchange Commission filings. Available at: http://investors.foundationmedicine.com/sec.cfm (accessed on February 18, 2015). 25. Foundation Medicine Press Release. Available at: http://investors. foundationmedicine.com/releasedetail.cfm?ReleaseID=846185 (accessed on February 18, 2015).

26. IntelliGEN Oncology Therapeutic Panel (NGS). Integrated Oncology website. Available at: http://bit.ly/1nC6yxA (accessed on February 18, 2015).

27. Qiagen Introduces 14 new DNAseq V2 Gene Panels Targeting CancerRelated Genes/Gene Regions. Press release. Available at: http://www. pharmabiz.com/NewsDetails.aspx?aid=82977&sid=2 (accessed on February 18, 2015).

28. Ion AmpliSeqTM Comprehensive Cancer Panel. Life Technologies website. Available at: http://www.lifetechnologies.com/order/ catalog/product/4477685 (accessed on February 18, 2015).

29. Memorial Sloan Kettering Cancer Center and Quest Diagnostics Partner to Advance Precision Medicine in Cancer Diagnosis and Treatment. Press release. Available at: http://bit.ly/1ondPCT (accessed on February 18, 2015).

30. Oral presentation: Petak, I. (2014). “Driver” gene based targeted cancer treatment strategies in the post cancer genomics era. Oncology Days (Bled, Slovenia) April 24–25.

31. Kris, M. G., et al. (2014). Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. J. Am. Med. Assoc., 311(19), 1998–2006. 32. Memorial Sloan Kettering Cancer Center and Quest Diagnostics Partner to Advance Precision Medicine in Cancer Diagnosis and Treatment. Press release. Available at: http://bit.ly/1ondPCT (accessed on February 18, 2015).

33. Landmark gift to Memorial Sloan Kettering Cancer Center. Press release. Available at: http://bit.ly/1nj70Sz (accessed on February 18, 2015). 34. IBM’s Watson Could Diagnose Cancer Better Than Doctors. Qmed website. Available at: http://www.qmed.com/news/ibms-watsoncould-diagnose-cancer-better-doctors (accessed on February 18, 2015).

25

26


35. Gray, S. W., Hicks-Courant, K., Cronin, A., Rollins, B. J., Weeks, J. (2014). Physicians attitude about tumor genomic testing. J. Clin. Oncol., 32(13), 1317–1323.

36. IBM’s Watson is Better at Diagnosing Cancer than Human Doctors. Wired Magazine (UK). Available at: http://www.wired.co.uk/news/ archive/2013-02/11/ibm-watson-medical-doctor (accessed on February 18, 2015). 37. IBM’s Watson is Better at Diagnosing Cancer than Human Doctors. Wired Magazine (UK). Available at: http://www.wired.co.uk/news/ archive/2013-02/11/ibm-watson-medical-doctor (accessed on February 18, 2015).

38. MD Anderson Taps IBM Watson to Power “Moon Shots” Mission. Press release. Available at: http://www-03.ibm.com/press/us/en/ pressrelease/42214.wss (accessed on February 18, 2015). 39. Noyes, K. Flatiron Health’s Bold Proposition to Fight Cancer with Big Data. Fortune Magazine. Available at: http://fortune. com/2014/06/12/flatiron-healths-bold-proposition-to-fight-cancerwith-big-data/ (accessed on February 18, 2015).

40. Foundation Medicine Striving to use Next-Generation Gene sequencing to Enrich Diagnostic Value Offered to Physicians by Clinical Laboratories. Dark Daily Magazine. Available at: http://bit.ly/ VNJeGZ (accessed on February 18, 2015).

41. 2014 NCCN Policy Summit. Available at: http://bit.ly/1zgw4Bb (accessed on February 18, 2015). 42. Leerink Swann Starts Foundation Medicine at Outperform. Available at: http://bit.ly/VNJ2rg (accessed on February 18, 2015).

43. Wedbush Starts Foundation Medicine at Outperform. Available at: http://bit.ly/1mVuA5A (accessed on February 18, 2015).

44. Goldman Sachs Starts Foundation Medicine at Neutral. Available at: http://bit.ly/1qzgCfI (accessed on February 18, 2015).

45. Drake, C. G., Lipson, E. J., Brahmer, J. R. (2014). Breathing life into immunotherapy: Review of melanoma, lung and kidney cancer. Nat. Rev. Clin. Oncol., 11, 24–37. 46. ClinicalTrials.gov. Available at: (accessed on February 18, 2015).

http://www.clinicaltrials.gov/

47. International Clinical Trials Registry Platform. World Health Organization. Available at: http://apps.who.int/trialsearch/ (accessed on February 18, 2015).

References

48. Kresge, N., Langreth, R. Immune Therapy’s Cancer promise Creates Research Rush. Bloomberg. Available at: http://bloom.bg/1qY3SOS (accessed on February 18, 2015). 49. Baum, A. S. Immunotherapy—The Beginning of the End for Cancer. Available at: https://www.citivelocity.com/citigps/OpArticleDetail. action?recordId=209 (accessed on February 18, 2015).

50. Longest Follow-up of Largest Number of Melanoma Patients Treated with Ipilimumab Shows Some Survive up to Ten Years. The European Cancer Congress 2013. Available at: http://bit.ly/TVVMuo (accessed on February 18, 2015). 51. Ipilimumab Prescription Information. Available at: http://packageinserts.bms.com/pi/pi_yervoy.pdf (accessed on February 18, 2015). 52. Hodi, F. S., Sznol, M., Kluger, H. M., McDermott, D. F., Carvajal, R. D., et al. (2014). Long-term survival of ipilimumab-naïve patients with advanced melanoma treated with nivolumab in a phase 1 trials. J. Clin. Oncol., 32:5s (suppl; abstr LBA9002).

53. Sznol, M., Kluger, H. M., Callahan, M. K., Postow, M. A., Gordon, R. A., et al. (2014). Survival, response duration, and activity by BRAF mutation status of Nivolumab and ipilimumab concurrent therapy in advanced melanoma. J. Clin. Oncol., 32:5s (suppl; abstr LBA9003).

54. Ribas, A., Hodui, F. S., Kefford, R., Hamid, O., Daud, A., et al. (2014). Efficacy and Safety of the Anti-PD-1 Monoclonal Antibody MK-3475 in 411 Patients with Melanoma. J. Clin. Oncol., 32:5s (suppl; abstr LBA9000). 55. Vansteenkiste, J., Zielinski, M., Linder, A., Dahabreh, J., Gonzalez, E. E., et al. (2013). Adjuvant MAGE-A3 immunotherapy in resected nonsmall-cell lung cancer: Phase II randomized study results. J. Clin. Oncol., 31, 2396–2403.

56. Ulloa-Montoya, F., Louahed, J., Dizier, B., Gruselle, O., Spiessns, B., et al. (2013). Predictive gene signature in MAGE-A3 antigenspecific cancer immunotherapy. J. Clin. Oncol., 31, 2388–2395.

57. Carroll, J. GlaxoSmithKline’s Cancer Vaccine MAGE-A3 Suffers its Second PhIII Flop. FierceBiotech website. Available at: http://bit.ly/ 1owDniy (accessed on February 18, 2015). 58. Butts, C. A., Socinski, M. A., Mithchell, P., Thathcher, N., Havel, L., et al. (2013). START: A phase III study of L-BLP25 cancer immunotherapy for unresectable stage III non-small cell lung cancer. J. Clin. Oncol., 31: abstr 7500.

27

28


59. Merck KGaA press release. Available at: http://news.emdgroup.com/ N/0/F5D9C027EC5D1592C1257BF00050E92F/$File/Tecemotide EMD.pdf (accessed on February 18, 2015). 60. Walter, S., Weischenk, T., Stenzi, A., Zdrojowy, R., pluzanska, A., et al. (2012). Multipeptide immune response to cancer vaccine IMA901 after single-dose cyclophosphamide associates with longer patient survival. Nat. Med., 8(18), 1254–1261.

61. Hacohen, N., Fritsch, E. F., Carter, T. A., Lander, E. S., Wu, C. J. (2013). Getting personal with neoantigen-based therapeutic cancer vaccines. Cancer Immunol. Res., 1(1), 11–15.

62. Vasaturo, A., Di Blasio, S., Peeters, D. G. A., de Konig, C. C. H., de Vries, J. M., Figdor, C. G., Hato, S. V. (2013). Clinical implications of coinhibitory molecule expression in the tumor microenvironment for DC vaccination: A game of stop and go. Front. Immunol., 4, 1–14.

63. Trowsdale, J., Knight, J. C. (2013). Major histocompatibility complex genomics and human disease. Ann. Rev. Genomics Human Gen., 14, 301–323. 64. Kudrin, A. (2012). Reimbursement challenges with cancer immunotherapeutics. Hum. Vaccine Immunother., 8(9), 1326–1334.

65. Hodi, F. S., O’Day, S. J., McDermott, D. F., Weber, R. W., Sosman, J. A., et al. (2010). Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med., 19(363), 711–723.

66. Mullins, D. W., Bullock, T. N., Colella, T. A., Robila, V. V., Engelhard, V. H. (2001). Immune responses to the HLA-A*0201-restricted epitope of tyrosinase and glycoprotein 100 enable control of melanoma outgrowth in HLA-A*0201-transgenic mice. J. Immunol., 167(9), 4853– 4860. 67. Schneble, E. J., Berry, J. S., Trappey, F. A., Clifton, G. T., Ponniah, S., et al. (2014). The HER2 peptide nelipepimut-S (E75) vaccine (NeuVaxTM) in breast cancer patients at risk for recurrence: Correlation of immunologic data with clinical response. Immunotherapy, 6(5), 519–531.

68. Heemskerk, B., Liu, K., Dudley, M. E., Johnson, L. A., Kaiser, A., et al. (2008). Adoptive cell therapy for patients with melanoma, using tumor-infiltrating lymphocytes genetically engineered to secrete interleukin-2. Hum. Gene Ther., 19(5), 496–510.

69. Kantoff, P. W., Schuetz, T. J., Blumenstein, B. A., Glode, L. M., Bilhartz, D. L., et al. (2010). Overall survival analysis of a phase II randomized controlled trial of a poxviral-based PSA-targeted immunotherapy in metastatic castration-resistant prostate cancer. J. Clin. Oncol., 28, 1099–1105.

References

70. Cohen, C. J., Zheng, Z., Bray, R., Zhao, Y., Sherman, L. A., et al. (2005). Recognition of fresh human tumor by human peripheral blood lymphocytes transduced with a bicistronic retroviral vector encoding a murine anti-p53 TCR. J. Immunol., 175, 5799–5808. 71. Roberts, J. D., Niedzwiecki, D., Carson, W. E., Chapman, P. B., Gajewski, T. F., et al. (2006). Phase 2 study of the g209-2M melanoma peptide vaccine and low-dose interleukin-2 in advanced melanoma. J. Immunother., 29, 95–101.

72. Slingluff Jr, C. L., Petroni, G. R., Chianese-Bullock, K. A., Smolkin, M. E., Ross, M. I., et al. (2011). Randomized multicenter trial of the effects of melanoma-associated helper peptides and cyclophosphamide on the immunogenicity of a multipeptide melanoma vaccine. J. Clin. Oncol., 29(21), 2924–2932.

73. Innovation in Cancer Care and Implications for Health Systems. IMS Institute report. Available at: http://bit.ly/1rzo5Ny (accessed on February 18, 2015).

74. Singh, M. S., Bhaskar, S. (2014). Nanocarrier-based immunotherapy in cancer management and research. Immun. Targets Ther., 3, 121–134. 75. Toke, E. R., Lorincz, O., Csiszovszki, Z., Somogyi, E., Felfoldi, G., et al. (2014). Exploitation of langerhans cells for in vivo DNA vaccine delivery into the lymph nodes. Gene Ther., 1, 1–9.

76. Clinical Considerations for Therapeutic Cancer Vaccines. FDA guidance document. Available at: http://1.usa.gov/TKGxE3 (accessed on February 18, 2015). 1. Spear, B. B., Heath-Chiozzi, M., Huff, J. (2001). Clinical application of pharmacogenetics. Trends Mol. Med., 7(5), 201–204.

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