Molecular profiling and targeted therapy for advanced thoracic malignancies: a biomarker-derived, multiarm, multihistology phase II basket trial

Differential prioritization of therapies to subtypes of triple negative breast cancer using a systems medicine method

Triple negative breast cancer (TNBC) is a group of cancers whose heterogeneity and shortage of effective drug therapies has prompted efforts to divide these cancers into molecular subtypes. Our computational platform, entitled GenEx-TNBC, applies concepts in systems biology and polypharmacology to prioritize thousands of approved and experimental drugs for therapeutic potential against each molecular subtype of TNBC. Using patient-based and cell line-based gene expression data, we constructed networks to describe the biological perturbation associated with each TNBC subtype at multiple levels of biological action. These networks were analyzed for statistical coincidence with drug action networks stemming from known drug-protein targets, while accounting for the direction of disease modulation for coinciding entities. GenEx-TNBC successfully designated drugs, and drug classes, that were previously shown to be broadly effective or subtype-specific against TNBC, as well as novel agents. We further performed biological validation of the platform by testing the relative sensitivities of three cell lines, representing three distinct TNBC subtypes, to several small molecules according to the degree of predicted biological coincidence with each subtype. GenEx-TNBC is the first computational platform to associate drugs to diseases based on inverse relationships with multi-scale disease mechanisms mapped from global gene expression of a disease. This method may be useful for directing current efforts in preclinical drug development surrounding TNBC, and may offer insights into the targetable mechanisms of each TNBC subtype.

Functional precision cancer medicine-moving beyond pure genomics

The essential job of precision medicine is to match the right drugs to the right patients. In cancer, precision medicine has been nearly synonymous with genomics. However, sobering recent studies have generally shown that most patients with cancer who receive genomic testing do not benefit from a genomic precision medicine strategy. Although some call the entire project of precision cancer medicine into question, I suggest instead that the tools employed must be broadened. Instead of relying exclusively on big data measurements of initial conditions, we should also acquire highly actionable functional information by perturbing-for example, with cancer therapies-viable primary tumor cells from patients with cancer.

Precision Oncology: The Road Ahead

Current efforts in precision oncology largely focus on the benefit of genomics-guided therapy. Yet, advances in sequencing techniques provide an unprecedented view of the complex genetic and nongenetic heterogeneity within individual tumors. Herein, we outline the benefits of integrating genomic and transcriptomic analyses for advanced precision oncology. We summarize relevant computational approaches to detect novel drivers and genetic vulnerabilities, suitable for therapeutic exploration. Clinically relevant platforms to functionally test predicted drugs/drug combinations for individual patients are reviewed. Finally, we highlight the technological advances in single cell analysis of tumor specimens. These may ultimately lead to the development of next-generation cancer drugs, capable of tackling the hurdles imposed by genetic and phenotypic heterogeneity on current anticancer therapies.

Resources for Interpreting Variants in Precision Genomic Oncology Applications

Precision genomic oncology-applying high throughput sequencing (HTS) at the point-of-care to inform clinical decisions-is a developing precision medicine paradigm that is seeing increasing adoption. Simultaneously, new developments in targeted agents and immunotherapy, when informed by rich genomic characterization, offer potential benefit to a growing subset of patients. Multiple previous studies have commented on methods for identifying both germline and somatic variants. However, interpreting individual variants remains a significant challenge, relying in large part on the integration of observed variants with biological knowledge. A number of data and software resources have been developed to assist in interpreting observed variants, determining their potential clinical actionability, and augmenting them with ancillary information that can inform clinical decisions and even generate new hypotheses for exploration in the laboratory. Here, we review available variant catalogs, variant and functional annotation software and tools, and databases of clinically actionable variants that can be used in an ad hoc approach with research samples or incorporated into a data platform for interpreting and formally reporting clinical results.

Fighting tubulin-targeting anticancer drug toxicity and resistance

Tubulin-targeting drugs, like taxanes and vinca alkaloids, are among the most effective anticancer therapeutics used in the clinic today. Specifically, anti-microtubule cancer drugs (AMCDs) have proven to be effective in the treatment of castration-resistant prostate cancer and triple-negative breast cancer. AMCDs, however, have limiting toxicities that include neutropenia and neurotoxicity, and, in addition, tumor cells can become resistant to the drugs after long-term use. Co-targeting mitotic progression/slippage with inhibition of the protein kinases WEE1 and MYT1 that regulate CDK1 kinase activity may improve AMCD efficacy, reducing the acquisition of resistance by the tumor and side effects from the drug and/or its vehicle. Other possible treatments that improve outcomes in the clinic for these two drug-resistant cancers, including new formulations of the AMCDs and pursuing different molecular targets, will be discussed.

The Molecular Pathology of Lung Cancer

Advances in lung cancer genomics have revolutionized the diagnosis and treatment of this heterogeneous and clinically significant group of tumors. This article provides a broad overview of the most clinically relevant oncogenic alterations in common and rare lung tumors, with an emphasis on the pathologic correlates of the major oncogenic drivers, including EGFR, KRAS, ALK, and MET. Illustrations emphasize the morphologic diversity of lung adenocarcinoma, including genotype-phenotype correlations of genomic evolution in tumorigenesis. Molecular diagnostic approaches, including PCR-based testing, massively parallel sequencing, fluorescence in situ hybridization, and immunohistochemistry are reviewed.

Radiogenomics and radiotherapy response modeling

Advances in patient-specific information and biotechnology have contributed to a new era of computational medicine. Radiogenomics has emerged as a new field that investigates the role of genetics in treatment response to radiation therapy. Radiation oncology is currently attempting to embrace these recent advances and add to its rich history by maintaining its prominent role as a quantitative leader in oncologic response modeling. Here, we provide an overview of radiogenomics starting with genotyping, data aggregation, and application of different modeling approaches based on modifying traditional radiobiological methods or application of advanced machine learning techniques. We highlight the current status and potential for this new field to reshape the landscape of outcome modeling in radiotherapy and drive future advances in computational oncology.

Implementation of a Precision Pathology Program Focused on Oncology-Based Prognostic and Predictive Outcomes

Personalized or precision medicine as a diagnostic and therapeutic paradigm was introduced some 10-15 years ago, with the advent of biomarker discovery as a mechanism for identifying prognostic and predictive attributes associated with treatment indication and outcome. While the concept is not new, the successful development and implementation of novel 'companion diagnostics', especially in oncology, continues to represent a significant challenge and is currently at the forefront of smart trial design and therapeutic choice. The ability to determine patient selection for a specific therapy has broad implications including better chances for a positive outcome, limited exposure to potentially toxic drugs and improved health economics. Importantly, a significant step in this paradigm is the role of predictive pathology or the accurate assessment of morphology at the microscopic level. In breast cancer, this has been most useful where histologic attributes such as the classification of tubular and cribriform carcinoma dictates surgery while neoadjuvant studies suggest that patients with lobular carcinoma are not likely to benefit from chemotherapy. The next level of 'personalized pathology' at the tissue-cellular level is the use of 'protein biomarker panels' to classify the disease process and ultimately drive tumor characterization and treatment. The following review article will focus on the evolution of predictive pathology from a subjective, 'opinion-based' approach to a quantitative science. In addition, we will discuss the individual components of the precise pathology platform including advanced image analysis, biomarker quantitation with mathematical modeling and the integration with fluid-based (i.e. blood, urine) analytics as drivers of next generation precise patient phenotyping.

Liquid biopsies in lung cancer-time to implement research technologies in routine care?

Lung cancer is the leading cause of cancer mortality. A substantial progress in the understanding of lung cancer biology has resulted in several promising targeted therapies for advanced disease. Druggable targets today include point mutations such as EGFR, BRAF and re-arrangements in genes such as ALK and ROS1. Liquid biopsies collecting e.g., circulating tumor DNA (ctDNA) reflects overall tumor information and is not biased by analyzing of only a small fraction of the tumor and is always accessible in contrast to the lung cancer tissue. Technological advances in detection of low frequency mutation variants in ctDNA have made it the dominating liquid biopsy platform in terms of utility and sensitivity. Circulating DNA or RNA may possible be used to define populations with higher risk of developing lung cancer, thus reducing screening cohorts and increasing the positive predictive value of screening. Blood based-tests may also aid to identify genetic alterations several weeks prior to radiologically verified recurrence and may be of great value in the follow-up of lung cancer patients. Besides being an alternative to invasive biopsies in selected cases, liquid biopsies offer a unique possibility to monitor treatment response following medical treatment as well as treatment response and resistance development after targeted therapy, giving a possibility to modify the treatment after the genetic profile of the tumor. Ideally, genetic alterations found in ctDNA could be tracked in real-time discriminating between fast-growing life-threatening tumors from more indolent slow growing tumors or premalignant growth that are of no concern for the wellbeing of the patient. This review focuses on future perspectives of liquid biopsies in lung cancer care for different clinical settings and present current technological platforms for further discussion of possible strategies for implementation of liquid biopsies in lung cancer.

Precision oncology based on omics data: The NCT Heidelberg experience

Precision oncology implies the ability to predict which patients will likely respond to specific cancer therapies based on increasingly accurate, high-resolution molecular diagnostics as well as the functional and mechanistic understanding of individual tumors. While molecular stratification of patients can be achieved through different means, a promising approach is next-generation sequencing of tumor DNA and RNA, which can reveal genomic alterations that have immediate clinical implications. Furthermore, certain genetic alterations are shared across multiple histologic entities, raising the fundamental question of whether tumors should be treated by molecular profile and not tissue of origin. We here describe MASTER (Molecularly Aided Stratification for Tumor Eradication Research), a clinically applicable platform for prospective, biology-driven stratification of younger adults with advanced-stage cancer across all histologies and patients with rare tumors. We illustrate how a standardized workflow for selection and consenting of patients, sample processing, whole-exome/genome and RNA sequencing, bioinformatic analysis, rigorous validation of potentially actionable findings, and data evaluation by a dedicated molecular tumor board enables categorization of patients into different intervention baskets and formulation of evidence-based recommendations for clinical management. Critical next steps will be to increase the number of patients that can be offered comprehensive molecular analysis through collaborations and partnering, to explore ways in which additional technologies can aid in patient stratification and individualization of treatment, to stimulate clinically guided exploratory research projects, and to gradually move away from assessing the therapeutic activity of targeted interventions on a case-by-case basis toward controlled clinical trials of genomics-guided treatments.

[Prospective: How will renal, prostatic and urothelial tumours be treated in 10 years?]

Forward thinking does not seek to predict the future, to unveil it as if it were already in existence, rather, its aim is to help us to construct it. Although today's epidemiological and therapeutic situations for urogenital tumours can evolve over the next 10 years, diagnostic and therapeutic methods, as well as the treatment and implementation of innovations, are already rapidly changing. Rather than reducing our prospective thinking to the therapeutic treatment of cancer only, we will aim at proposing a global sanitary vision that includes diagnosis, therapies, prevention, routine utilisation of technomedicine, genomics and even nanomedicine. This journey into the near future of tomorrow's cancerology holds the promise of being better adapted to the evolution of the medical thinking process. Imagining the way we will be treating renal, prostatic and urothelial tumours in 10 years' time is as much an introspection into our present day treatment system as a projection into its hoped for future evolution.

Waldenstrom macroglobulinemia cells devoid of BTKC481S or CXCR4WHIM-like mutations acquire resistance to ibrutinib through upregulation of Bcl-2 and AKT resulting in vulnerability towards venetoclax or MK2206 treatment

Although ibrutinib is highly effective in Waldenstrom macroglobulinemia (WM), no complete remissions in WM patients treated with ibrutinib have been reported to date. Moreover, ibrutinib-resistant disease is being steadily reported and is associated with dismal clinical outcome (overall survival of 2.9–3.1 months). To understand mechanisms of ibrutinib resistance in WM, we established ibrutinib-resistant in vitro models using validated WM cell lines. Characterization of these models revealed the absence of BTK^C481S and CXCR4^WHIM-like mutations. BTK-mediated signaling was found to be highly attenuated accompanied by a shift in PI3K/AKT and apoptosis regulation-associated genes/proteins. Cytotoxicity studies using the AKT inhibitor, MK2206±ibrutinib, and the Bcl-2-specific inhibitor, venetoclax±ibrutinib, demonstrated synergistic loss of cell viability when either MK22016 or venetoclax were used in combination with ibrutinib. Our findings demonstrate that induction of ibrutinib resistance in WM cells can arise independent of BTK^C481S and CXCR4^WHIM-like mutations and sustained pressure from ibrutinib appears to activate compensatory AKT signaling as well as reshuffling of Bcl-2 family proteins for maintenance of cell survival. Combination treatment demonstrated greater (and synergistic) antitumor effect and provides rationale for development of therapeutic strategies encompassing venetoclax+ibrutinib or PI3K/AKT inhibitors+ibrutinib in ibrutinib-resistant WM.

CD52, CD22, CD26, EG5 and IGF-1R expression in thymic malignancies

BACKGROUND

Thymic epithelial tumours are rare cancers for which new treatment options are required. Identification of putative predictive markers is important for developing clinical trials. We studied the expression of five putative predictive biomarkers, potentially actionable by approved experimental drugs.

METHODS

CD52, CD22, CD26, EG5, and IGF-1R expression were investigated by immunohistochemistry in formalin-fixed surgical samples of thymic epithelial tumour patients. All samples containing 10% positive epithelial tumour cells, independent of tumour cell intensity, were considered as positive. Correlation with histological subtype was performed.

RESULTS

106 surgical samples (89 thymomas, 12 thymic carcinoma, and 5 thymic neuroendocrine tumours) were evaluated. Overall, CD52, CD22, CD26, EG5 and IGF-1R expression was observed in 7%, 42%, 25%, 42% and 77% of samples, respectively. CD52 expression was more frequent in B2 and B3 thymoma. All TET subtypes stained for CD22, mainly AB thymoma (68%). CD26 expression also correlated with AB thymoma (68%), and A thymoma (50%) subtype, while IGFR1 was the most common marker expressed by thymic carcinoma samples (92%), followed by EG5 (60%). Only EG5 expression was significantly higher in thymic carcinomas than in thymomas (75% vs. 38%, p=0.026).

CONCLUSIONS

Our data were consistent with a previous study of IGF-1R expression. Based on their expression, activity of agents targeting CD52, CD 22, CD26 and EG5 could be further explored in TET patients.

Clinical Trials in the Genomic Era

Personalization of therapy to target specific molecular pathways has been placed in the forefront of cancer research. Initial reports from clinical trials designed to select patients for appropriate treatment on the basis of tumor characteristics not only have generated considerable excitement but also have identified several challenges. These challenges include the overcoming of regulatory and logistic difficulties, identification of the best selection biomarkers and diagnostic platforms that can be applied in the clinical setting, definition of relevant outcomes in small preselected patient populations, and the design of methods that facilitate rapid enrollment and interpretation of clinical trials by aggregating data across histologically diverse malignancies with common genetic alterations. Furthermore, because our knowledge of the functional consequences of many genetic alterations lags, investigators and sponsors struggle with choosing between ideal clinical trial designs and more practical ones. These challenges are amplified when more than one biomarker is used to select patients for a combination of targeted agents. This review summarizes the current status and challenges of clinical trials in the genomic era and proposes ways to address these challenges.

Bayesian response-adaptive designs for basket trials

We develop a general class of response-adaptive Bayesian designs using hierarchical models, and provide open source software to implement them. Our work is motivated by recent master protocols in oncology, where several treatments are investigated simultaneously in one or multiple disease types, and treatment efficacy is expected to vary across biomarker-defined subpopulations. Adaptive trials such as I-SPY-2 (Barker et al., 2009) and BATTLE (Zhou et al., 2008) are special cases within our framework. We discuss the application of our adaptive scheme to two distinct research goals. The first is to identify a biomarker subpopulation for which a therapy shows evidence of treatment efficacy, and to exclude other subpopulations for which such evidence does not exist. This leads to a subpopulation-finding design. The second is to identify, within biomarker-defined subpopulations, a set of cancer types for which an experimental therapy is superior to the standard-of-care. This goal leads to a subpopulation-stratified design. Using simulations constructed to faithfully represent ongoing cancer sequencing projects, we quantify the potential gains of our proposed designs relative to conventional non-adaptive designs.

An efficient basket trial design

The landscape for early phase cancer clinical trials is changing dramatically because of the advent of targeted therapy. Increasingly, new drugs are designed to work against a target such as the presence of a specific tumor mutation. Because typically only a small proportion of cancer patients will possess the mutational target, but the mutation is present in many different cancers, a new class of basket trials is emerging, whereby the drug is tested simultaneously in different baskets, that is, subgroups of different tumor types. Investigators desire not only to test whether the drug works but also to determine which types of tumors are sensitive to the drug. A natural strategy is to conduct parallel trials, with the drug 's effectiveness being tested separately, using for example, the popular Simon two-stage design independently in each basket. The work presented is motivated by the premise that the efficiency of this strategy can be improved by assessing the homogeneity of the baskets ' response rates at an interim analysis and aggregating the baskets in the second stage if the results suggest the drug might be effective in all or most baskets. Via simulations, we assess the relative efficiencies of the two strategies. Because the operating characteristics depend on how many tumor types are sensitive to the drug, there is no uniformly efficient strategy. However, our investigation demonstrates that substantial efficiencies are possible if the drug works in most or all baskets, at the cost of modest losses of power if the drug works in only a single basket. Copyright © 2017 John Wiley & Sons, Ltd.

Innovations in Clinical Trial Design in the Era of Molecular Profiling

Historically, cancer has been studied, and therapeutic agents have been evaluated based on organ site, clinical staging, and histology. The science of molecular profiling has expanded our knowledge of cancer at the cellular and molecular level such that numerous subtypes are being described based on biomarker expression and genetic mutations rather than traditional classifications of the disease. Drug development has experienced a concomitant revolution in response to this knowledge with many new targeted therapeutic agents becoming available, and this has necessitated an evolution in clinical trial design. The traditional, large phase II and phase III adjuvant trial models need to be replaced with smaller, shorter, and more focused trials. These trials need to be more efficient and adaptive in order to quickly assess the efficacy of new agents and develop new companion diagnostics. We are now seeing a substantial shift from the traditional multiphase trial model to an increase in phase II adjuvant and neoadjuvant trials in earlier-stage disease incorporating surrogate endpoints for long-term survival to assess efficacy of therapeutic agents in shorter time frames. New trial designs have emerged with capabilities to assess more efficiently multiple disease types, multiple molecular subtypes, and multiple agents simultaneously, and regulatory agencies have responded by outlining new pathways for accelerated drug approval that can help bring effective targeted therapeutic agents to the clinic more quickly for patients in need.

Statistical controversies in clinical research: basket trials, umbrella trials, and other master protocols: a review and examples

In recent years, cancers once viewed as relatively homogeneous in terms of organ location and treatment strategy are now better understood to be increasingly heterogeneous across biomarker and genetically defined patient subgroups. This has produced a shift toward development of biomarker-targeted agents during a time when funding for cancer research has been limited; as a result, the need for improved operational efficiency in studying many agent-and-target combinations in parallel has emerged. Platform trials, basket trials, and umbrella trials are new approaches to clinical research driven by this need for enhanced efficiency in the modern era of increasingly specific cancer subpopulations and decreased resources to study treatments for individual cancer subtypes in a traditional way. In this review, we provide an overview of these new types of clinical trial designs, including discussions of motivation for their use, recommended terminology, examples, and challenges encountered in their application.

Clinical Genomic Profiling of a Diverse Array of Oncology Specimens at a Large Academic Cancer Center: Identification of Targetable Variants and Experience with Reimbursement

Large cancer panels are being increasingly used in the practice of precision medicine to generate genomic profiles of tumors with the goal of identifying targetable variants and guiding eligibility for clinical trials. To facilitate identification of mutations in a broad range of solid and hematological malignancies, a 467-gene oncology panel (Columbia Combined Cancer Panel) was developed in collaboration with pathologists and oncologists and is currently available and in use for clinical diagnostics. Herein, we share our experience with this testing in an academic medical center. Of 255 submitted specimens, which encompassed a diverse range of tumor types, we were able to successfully sequence 92%. The Columbia Combined Cancer Panel assay led to the detection of a targetable variant in 48.7% of cases. However, although we show good clinical performance and diagnostic yield, third-party reimbursement has been poor. Reimbursement from government and third-party payers using the 81455 Current Procedural Terminology code was at 19.4% of billed costs, and 55% of cases were rejected on first submission. Likely contributing factors to this low level of reimbursement are the delays in valuation of the 81455 Current Procedural Terminology code and in establishing national or local coverage determinations. In the absence of additional demonstrations of clinical utility and improved patient outcomes, we expect the reimbursement environment will continue to limit the availability of this testing more broadly.

Analysis of a panel of druggable gene mutations and of ALK and PD-L1 expression in a series of thymic epithelial tumors (TETs)

INTRODUCTION

Thymic epithelial tumors (TETs) are rare neoplasms with different prognosis lacking consistent molecular alterations possibly leading to targeted therapy. We collected a consecutive series of TETs aimed at investigating the mutational status of druggable genes (EGFR, c-KIT, KRAS, BRAF, PDGFR-alpha and -beta, HER2 and c-MET) and the expression of ALK and PD-L1.

PATIENTS AND METHODS

One hundred twelve consecutive cases of TETs and relative clinico-pathologic features were collected. Immunohistochemical expression of ALK (clone D5F3) and PD-L1 (clone E1L3N), molecular analysis of EGFR (exons 18-21), c-KIT (exons 9,11,13,14,17), KRAS (exon 2), BRAF (exon 15), PDGFR-alpha (exon 12) and -beta (exons 12, 14, 18), HER-2 (exons 19 and 20) and c-MET (exons 14, 17, 18, 19) mutations were performed. Immuno-molecular results were then statistically matched with clinico-pathologic characteristics.

RESULTS

Patients were male in 54% of cases, with a median age of 61 years (range 19-83) and affected mainly by thymoma (78%) in stage II (45%). At molecular analysis, there were 4 c-KIT mutations (occurring in exon 11 V559A, L576P, Y553N and exon 17 D820E) in thymic carcinomas (typeC), but not in other tumor types (p=0.003). No mutations were detected in other genes and none case was ALK positive. Twenty-nine (26%) cases were PD-L1 positive (65% of thymic carcinomas and 18% of thymomas). High PD-L1 expression was statistically associated with WHO classification stage type C (p<0.001) and Masaoka stage III-IV disease (p=0.007). In univariate analysis, WHO classification type C, advanced Masaoka stage and absence of myasthenia, but not PD-L1 expressions were correlated with worse survival; at multivariate analysis, only WHO type C confirmed its negative prognostic role.

CONCLUSION

A subset of TETs as thymic carcinomas can harbor c-KIT mutations and elevated PD-L1 expression that could represent targets of potential therapeutic use.

Integrating next-generation sequencing into clinical oncology: strategies, promises and pitfalls

We live in an era of genomic medicine. The past five years brought about many significant achievements in the field of cancer genetics, driven by rapidly evolving technologies and plummeting costs of next-generation sequencing (NGS). The official completion of the Cancer Genome Project in 2014 led many to envision the clinical implementation of cancer genomic data as the next logical step in cancer therapy. Stemming from this vision, the term 'precision oncology' was coined to illustrate the novelty of this individualised approach. The basic assumption of precision oncology is that molecular markers detected by NGS will predict response to targeted therapies independently from tumour histology. However, along with a ubiquitous availability of NGS, the complexity and heterogeneity at the individual patient level had to be acknowledged. Not only does the latter present challenges to clinical decision-making based on sequencing data, it is also an obstacle to the rational design of clinical trials. Novel tissue-agnostic trial designs were quickly developed to overcome these challenges. Results from some of these trials have recently demonstrated the feasibility and efficacy of this approach. On the other hand, there is an increasing amount of whole-exome and whole-genome NGS data which allows us to assess ever smaller differences between individual patients with cancer. In this review, we highlight different tumour sequencing strategies currently used for precision oncology, describe their individual strengths and weaknesses, and emphasise their feasibility in different clinical settings. Further, we evaluate the possibility of NGS implementation in current and future clinical trials, and point to the significance of NGS for translational research.

Institutional implementation of clinical tumor profiling on an unselected cancer population

BACKGROUND. Comprehensive genomic profiling of a patient's cancer can be used to diagnose, monitor, and recommend treatment. Clinical implementation of tumor profiling in an enterprise-wide, unselected cancer patient population has yet to be reported. METHODS. We deployed a hybrid-capture and massively parallel sequencing assay (OncoPanel) for all adult and pediatric patients at our combined cancer centers. Results were categorized by pathologists based on actionability. We report the results for the first 3,727 patients tested. RESULTS. Our cohort consists of cancer patients unrestricted by disease site or stage. Across all consented patients, half had sufficient and available (>20% tumor) material for profiling; once specimens were received in the laboratory for pathology review, 73% were scored as adequate for genomic testing. When sufficient DNA was obtained, OncoPanel yielded a result in 96% of cases. 73% of patients harbored an actionable or informative alteration; only 19% of these represented a current standard of care for therapeutic stratification. The findings recapitulate those of previous studies of common cancers but also identify alterations, including in AXL and EGFR, associated with response to targeted therapies. In rare cancers, potentially actionable alterations suggest the utility of a "cancer-agnostic" approach in genomic profiling. Retrospective analyses uncovered contextual genomic features that may inform therapeutic response and examples where diagnoses revised by genomic profiling markedly changed clinical management. CONCLUSIONS. Broad sequencing-based testing deployed across an unselected cancer cohort is feasible. Genomic results may alter management in diverse scenarios; however, additional barriers must be overcome to enable precision cancer medicine on a large scale. FUNDING. This work was supported by DFCI, BWH, and the National Cancer Institute (5R33CA155554 and 5K23CA157631).

Clinical Impact of Hybrid Capture-Based Next-Generation Sequencing on Changes in Treatment Decisions in Lung Cancer

INTRODUCTION

Targeted therapy significantly prolongs survival in lung adenocarcinoma. Current diagnostic guidelines include only EGFR and anaplastic lymphoma receptor tyrosine kinase gene (ALK) testing. Next-generation sequencing (NGS) reveals more actionable genomic alterations than do standard diagnostic methods. Data on the influence of hybrid capture (HC)-based NGS on treatment are limited, and we investigated its impact on treatment decisions and clinical outcomes.

METHODS

This retrospective study included patients with advanced lung cancer on whom HC-based NGS was performed between November 2011 and October 2015. Demographic and clinicopathologic characteristics, treatments, and outcome data were collected.

RESULTS

A total of 101 patients were included (median age 63 years [53% females, 45% never-smokers, and 85% with adenocarcinoma]). HC-based NGS was performed upfront and after EGFR/ALK testing yielded negative or inconclusive results in 15% and 85% of patients, respectively. In 51.5% of patients, HC-based NGS was performed before first-line therapy, and in 48.5%, it was performed after treatment failure. HC-based NGS identified clinically actionable genomic alterations in 50% of patients, most frequently in EGFR (18%), Ret proto-oncogene (RET) (9%), ALK (8%), Mesenchymal-epithelial transition factor (MET) receptor tyrosine kinase gene (6%), and erb-b2 receptor tyrosine kinase 2 gene (ERBB2) (5%). In 15 patients, it identified EGFR/ALK aberrations after negative results of prior standard testing. Treatment strategy was changed for 43 patients (42.6%). The overall response rate in these patients was 65% (complete response 14.7%, partial response 50%). Median survival was not reached. Immunotherapy was administered in 33 patients, mostly without an actionable driver, with a presenting disease control rate of 32%, and with an association with tumor mutation burden.

CONCLUSIONS

HC-based NGS influenced treatment decisions in close to half of the patients with lung adenocarcinoma and was associated with an overall response rate of 65%, which may translate into a survival benefit.

Next-Generation Sequencing and Result Interpretation in Clinical Oncology: Challenges of Personalized Cancer Therapy

The tools of next-generation sequencing (NGS) technology, such as targeted sequencing of candidate cancer genes and whole-exome and -genome sequencing, coupled with encouraging clinical results based on the use of targeted therapeutics and biomarker-guided clinical trials, are fueling further technological advancements of NGS technology. However, NGS data interpretation is associated with challenges that must be overcome to promote the techniques' effective integration into clinical oncology practice. Specifically, sequencing of a patient's tumor often yields 30-65 somatic variants, but most of these variants are "passenger" mutations that are phenotypically neutral and thus not targetable. Therefore, NGS data must be interpreted by multidisciplinary decision-support teams to determine mutation actionability and identify potential "drivers," so that the treating physician can prioritize what clinical decisions can be pursued in order to provide cancer therapy that is personalized to the patient and his or her unique genome.

Selumetinib in the treatment of non-small-cell lung cancer

The RAS-RAF-MEK-ERK pathway regulates processes involved in the proliferation and survival of cells. KRAS mutations, prevalent in approximately 30% of patients with non-small-cell lung cancer (NSCLC), result in constitutive activation of the pathway. Selumetinib (AZD6244, ARRY-142886) is a potent and selective inhibitor of MEK1/2 which has demonstrated significant efficacy in combination with docetaxel in patients with KRAS mutant pretreated advanced NSCLC. Several trials in combination with other chemotherapy and targeted therapy regimens in lung cancer are ongoing. We review the development of selumetinib in patients with NSCLC, summarize the pharmacodynamic, pharmacokinetic and tolerability characteristics, and the available clinical trial data to understand the role of selumetinib in the treatment of NSCLC.

Tracking Down Response and Resistance to TRK Inhibitors

Two recent studies validate the LMNA-NTRK1 fusion as an oncogenic driver and therapeutic target of TRK inhibitors. The LMNA-NTRK1 fusion occurs at low frequency across multiple tumor types. The studies highlight the increasing need to develop molecular biomarker-based clinical trials across cancer subtypes.

Small Cell Lung Cancer Screen of Oncology Drugs, Investigational Agents, and Gene and microRNA Expression

BACKGROUND

Small cell lung carcinoma (SCLC) is an aggressive, recalcitrant cancer, often metastatic at diagnosis and unresponsive to chemotherapy upon recurrence, thus it is challenging to treat.

METHODS

Sixty-three human SCLC lines and three NSCLC lines were screened for response to 103 US Food and Drug Administration-approved oncology agents and 423 investigational agents. The investigational agents library was a diverse set of small molecules that included multiple compounds targeting the same molecular entity. The compounds were screened in triplicate at nine concentrations with a 96-hour exposure time using an ATP Lite endpoint. Gene expression was assessed by exon array, and microRNA expression was derived by direct digital detection. Activity across the SCLC lines was associated with molecular characteristics using pair-wise Pearson correlations.

RESULTS

Results are presented for inhibitors of targets: BCL2, PARP1, mTOR, IGF1R, KSP/Eg5, PLK-1, AURK, and FGFR1. A relational map identified compounds with similar patterns of response. Unsupervised microRNA clustering resulted in three distinct SCLC subgroups. Associating drug response with micro-RNA expression indicated that lines most sensitive to etoposide and topotecan expressed high miR-200c-3p and low miR-140-5p and miR-9-5p. The BCL-2/BCL-XL inhibitors produced similar response patterns. Sensitivity to ABT-737 correlated with higher ASCL1 and BCL2. Several classes of compounds targeting nuclear proteins regulating mitosis produced a response pattern distinct from the etoposide response pattern.

CONCLUSIONS

Agents targeting nuclear kinases appear to be effective in SCLC lines. Confirmation of SCLC line findings in xenografts is needed. The drug and compound response, gene expression, and microRNA expression data are publicly available at http://sclccelllines.cancer.gov.

Mutant HRAS as novel target for MEK and mTOR inhibitors

HRAS is a frequently mutated oncogene in cancer. However, mutant HRAS as drug target has not been investigated so far. Here, we show that mutant HRAS hyperactivates the RAS and the mTOR pathway in various cancer cell lines including lung, bladder and esophageal cancer. HRAS mutation sensitized toward growth inhibition by the MEK inhibitors AZD6244, MEK162 and PD0325901. Further, we found that MEK inhibitors induce apoptosis in mutant HRAS cell lines but not in cell lines lacking RAS mutations. In addition, knockdown of HRAS by siRNA blocked cell growth in mutant HRAS cell lines. Inhibition of the PI3K pathway alone or in combination with MEK inhibitors did not alter signaling nor had an impact on viability. However, inhibition of mTOR or combined inhibition of MEK and mTOR reduced cell growth in a synergistic manner. Finally, Ba/F3 cells transformed with mutant HRAS isoforms Q61L, Q61R and G12V demonstrated equal sensitivity towards MEK and mTOR inhibition. Our results show that HRAS mutations in cancer activate the RAS and mTOR pathways which might serve as a therapeutic option for patients with HRAS mutant tumors.

The 2015 World Health Organization Classification of Tumors of the Thymus: Continuity and Changes

This overview of the 4th edition of the World Health Organization (WHO) Classification of thymic tumors has two aims. First, to comprehensively list the established and new tumor entities and variants that are described in the new WHO Classification of thymic epithelial tumors, germ cell tumors, lymphomas, dendritic cell and myeloid neoplasms, and soft-tissue tumors of the thymus and mediastinum; second, to highlight major differences in the new WHO Classification that result from the progress that has been made since the 3rd edition in 2004 at immunohistochemical, genetic and conceptual levels. Refined diagnostic criteria for type A, AB, B1-B3 thymomas and thymic squamous cell carcinoma are given, and it is hoped that these criteria will improve the reproducibility of the classification and its clinical relevance. The clinical perspective of the classification has been strengthened by involving experts from radiology, thoracic surgery, and oncology; by incorporating state-of-the-art positron emission tomography/computed tomography images; and by depicting prototypic cytological specimens. This makes the thymus section of the new WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart a valuable tool for pathologists, cytologists, and clinicians alike. The impact of the new WHO Classification on therapeutic decisions is exemplified in this overview for thymic epithelial tumors and mediastinal lymphomas, and future perspectives and challenges are discussed.

Challenges in molecular testing in non-small-cell lung cancer patients with advanced disease

Lung cancer diagnostics have progressed greatly in the previous decade. Development of molecular testing to identify an increasing number of potentially clinically actionable genetic variants, using smaller samples obtained via minimally invasive techniques, is a huge challenge. Tumour heterogeneity and cancer evolution in response to therapy means that repeat biopsies or circulating biomarkers are likely to be increasingly useful to adapt treatment as resistance develops. We highlight some of the current challenges faced in clinical practice for molecular testing of EGFR, ALK, and new biomarkers such as PDL1. Implementation of next generation sequencing platforms for molecular diagnostics in non-small-cell lung cancer is increasingly common, allowing testing of multiple genetic variants from a single sample. The use of next generation sequencing to recruit for molecularly stratified clinical trials is discussed in the context of the UK Stratified Medicine Programme and The UK National Lung Matrix Trial.

Live cumulative network meta-analysis: protocol for second-line treatments in advanced non-small-cell lung cancer with wild-type or unknown status for epidermal growth factor receptor

INTRODUCTION

Many second-line treatments for advanced non-small-cell lung cancer (NSCLC) have been assessed in randomised controlled trials, but which treatments work the best remains unclear. Novel treatments are being rapidly developed. We need a comprehensive up-to-date evidence synthesis of all these treatments. We present the protocol for a live cumulative network meta-analysis (NMA) to address this need.

METHODS AND ANALYSIS

We will consider trials of second-line treatments in patients with advanced NSCLC with wild-type or unknown epidermal growth factor receptor status. We will consider any single agent of cytotoxic chemotherapy, targeted therapy, combination of cytotoxic chemotherapy and targeted therapy and any combination of targeted therapies. The primary outcomes will be overall survival and progression-free survival. The live cumulative NMA will be initiated with a NMA and then iterations will be repeated at regular intervals to keep the NMA up-to-date over time. We have defined the update frequency as 4 months, based on an assessment of the pace of evidence production on this topic. Each iteration will consist of six methodological steps: adaptive search for treatments and trials, screening of reports and selection of trials, data extraction, assessment of risk of bias, update of the network of trials and synthesis, and dissemination. We will set up a research community in lung cancer, with different groups of contributors of different skills. We will distribute tasks through online crowdsourcing. This proof-of-concept study in second-line treatments of advanced NSCLC will allow one for assessing the feasibility of live cumulative NMA and opening the path for this new form of synthesis.

ETHICS AND DISSEMINATION

Ethical approval is not required because our study will not include confidential participant data and interventions. The description of all the steps and the results of this live cumulative NMA will be available online.

TRIAL REGISTRATION NUMBER

CRD42015017592.

Next-Generation Sequencing and Immunotherapy Biomarkers: A Medical Oncology Perspective

The two most important scientific developments of the past decade regarding therapies for patients with non-small cell lung cancer are the ability to exploit particular genetic mutations with targeted therapies and the discovery of drugs that can help the patient's own immune system attack the cancer. Despite these advances, many patients do not yet benefit from either approach. To maximize patient benefit, clinicians and pathologists will need to rationally apply the growing scientific knowledge to best characterize a patient's tumor and possible driver mutations. A growing understanding of host-tumor immune interactions will hopefully help expand our therapeutic options. Lastly, the still elusive identification of immunotherapy biomarkers will hopefully help identify patients most likely to derive a therapeutic response to immune checkpoint inhibitors, and promises to be an important field of study for years to come.

Targeting Signaling Transduction Pathways in Bladder Cancer

Systemic therapy for urothelial carcinoma (UC) of the bladder has largely revolved around cytotoxic chemotherapy regimens. However, several recent clinical trials have explored the roles of targeted therapies which specifically inhibit signal transduction pathways. Simultaneously, a rationale for such therapies has come to the forefront of management of this disease because an overabundance of signaling pathways are genetically deranged as a result of point mutation or copy number alteration (CNA) as identified by several recent next generation sequencing (NGS) studies. Importantly, these derangements are found in all stages of disease, and therefore targeted therapies hold promise as a next step in the evolution of the medical management of both localized and metastatic UCC. We review the rationale for and progress in studying inhibition of signal transduction as a means of treatment of UCC.

Precision oncology: origins, optimism, and potential

Imatinib, the first and arguably the best targeted therapy, became the springboard for developing drugs aimed at molecular targets deemed crucial to tumours. As this development unfolded, a revolution in the speed and cost of genetic sequencing occurred. The result--an armamentarium of drugs and an array of molecular targets--set the stage for precision oncology, a hypothesis that cancer treatment could be markedly improved if therapies were guided by a tumour's genomic alterations. Drawing lessons from the biological basis of cancer and recent empirical investigations, we take a more measured view of precision oncology's promise. Ultimately, the promise is not our concern, but the threshold at which we declare success. We review reports of precision oncology alongside those of precision diagnostics and novel radiotherapy approaches. Although confirmatory evidence is scarce, these interventions have been widely endorsed. We conclude that the current path will probably not be successful or, at a minimum, will have to undergo substantive adjustments before it can be successful. For the sake of patients with cancer, we hope one form of precision oncology will deliver on its promise. However, until confirmatory studies are completed, precision oncology remains unproven, and as such, a hypothesis in need of rigorous testing.

Molecular Triage Trials in Colorectal Cancer

Advances in the understanding of genomic alterations in cancer, and the various therapies targeted to these alterations have permitted the design of trials directed to bringing this science to the clinic, with the ultimate goal of tailoring therapy to the individual. There is a high need for advances in targeted therapy in colorectal cancer, a disease in which only 2 classes of targeted therapies are approved for use in colorectal cancer, despite the majority of colorectal cancers containing a potentially targetable mutation. Here we outline the key elements to the design of these clinical trials and summarize the current active molecular triage trials in colorectal cancer.

Precision Oncology Medicine: The Clinical Relevance of Patient-Specific Biomarkers Used to Optimize Cancer Treatment

Precision medicine in oncology is the result of an increasing awareness of patient-specific clinical features coupled with the development of genomic-based diagnostics and targeted therapeutics. Companion diagnostics designed for specific drug-target pairs were the first to widely utilize clinically applicable tumor biomarkers (eg, HER2, EGFR), directing treatment for patients whose tumors exhibit a mutation susceptible to an FDA-approved targeted therapy (eg, trastuzumab, erlotinib). Clinically relevant germline mutations in drug-metabolizing enzymes and transporters (eg, TPMT, DPYD) have been shown to impact drug response, providing a rationale for individualized dosing to optimize treatment. The use of multigene expression-based assays to analyze an array of prognostic biomarkers has been shown to help direct treatment decisions, especially in breast cancer (eg, Oncotype DX). More recently, the use of next-generation sequencing to detect many potential "actionable" cancer molecular alterations is further shifting the 1 gene-1 drug paradigm toward a more comprehensive, multigene approach. Currently, many clinical trials (eg, NCI-MATCH, NCI-MPACT) are assessing novel diagnostic tools with a combination of different targeted therapeutics while also examining tumor biomarkers that were previously unexplored in a variety of cancer histologies. Results from ongoing trials such as the NCI-MATCH will help determine the clinical utility and future development of the precision-medicine approach.

Evolving landscape of tumor molecular profiling for personalized cancer therapy: a comprehensive review

INTRODUCTION

Tumour molecular profiling has been at the crossroads of large-scale integrative genomic studies and major clinical trials over the past 5 years and has provided roadmaps for better disease stratification and therapeutic management.

AREAS COVERED

We review the landscape of precision oncology trials in Asia, Europe and the United States, and emerging insights gained from recently reported studies such as the SHIVA and CUSTOM trials. Changes in the molecular portraits of human cancers and the immune contexture of the tumor microenvironment during treatment may predict the course of tumor progression, including the development of treatment resistance. 'Liquid biopsy' approaches that harness circulating tumor cells, cell-free DNA and exosomes may provide a non-invasive means of monitoring the parent tumor in real-time. Several molecular signatures are being evaluated as biomarkers for emerging immunologic approaches, such as the mismatch-repair deficiency status and nonsynonymous mutation burden in anti-PD-1 immune checkpoint blockade. Finally, we review the current actionability and future clinical impact of multigene panel and next-generation sequencing (NGS)-based profiling.

EXPERT OPINION

In the future, molecular profiling may help to fulfill unmet needs for predictive biomarkers in novel immunotherapeutic approaches, while ongoing precision trials are laying the foundations for clinical uptake of NGS testing.

The Obama Administration's Cancer Moonshot: A Call for Proteomics

The Cancer Moonshot Program has been launched and represents a potentially paradigm-shifting initiative with the goal to implement a focused national effort to double the rate of progress against cancer. The placement of precision medicine, immunotherapy, genomics, and combination therapies was placed at the central nexus of this initiative. Although we are extremely enthusiastic about the goals of the program, it is time we meet this revolutionary project with equally bold and cutting-edge ideas: it is time we move firmly into the postgenome era and provide the necessary resources to propel and seize on innovative recent gains in the field of proteomics required for it to stand on equal footing in this narrative as a combined, synergistic engine for molecular profiling. After all, although the genome is the information archive, it is the proteins that actually do the work of the cell and represent the structural cellular machinery. It is the proteins that comprise most of the biomarkers that are measured to detect cancers, constitute the antigens that drive immune response and inter- and intracellular communications, and it is the proteins that are the drug targets for nearly every targeted therapy that is being evaluated in cancer trials today. We believe that a combined systems biology view of the tumor microenvironment that orients cancer studies back to the functional proteome, phosphoproteome, and biochemistry of the cell will be essential to deliver on the promise of the Cancer Moonshot Program. Clin Cancer Res; 22(18); 4556-8. ©2016 AACR.

Precision Medicine in Gastrointestinal Pathology

Context.—Precision medicine is the promise of individualized therapy and management of patients based on their personal biology. There are now multiple global initiatives to perform whole-genome sequencing on millions of individuals. In the United States, an early program was the Million Veteran Program, and a more recent proposal in 2015 by the president of the United States is the Precision Medicine Initiative. To implement precision medicine in routine oncology care, genetic variants present in tumors need to be matched with effective clinical therapeutics. When we focus on the current state of precision medicine for gastrointestinal malignancies, it becomes apparent that there is a mixed history of success and failure.

Objective.—To present the current state of precision medicine using gastrointestinal oncology as a model. We will present currently available targeted therapeutics, promising new findings in clinical genomic oncology, remaining quality issues in genomic testing, and emerging oncology clinical trial designs.

Data Sources.—Review of the literature including clinical genomic studies on gastrointestinal malignancies, clinical oncology trials on therapeutics targeted to molecular alterations, and emerging clinical oncology study designs.

Conclusions.—Translating our ability to sequence thousands of genes into meaningful improvements in patient survival will be the challenge for the next decade.