Lung Master Protocol (Lung-MAP)-A Biomarker-Driven Protocol for Accelerating Development of Therapies for Squamous Cell Lung Cancer: SWOG S1400

Lung-MAP Next-Generation Sequencing Analysis of Advanced Squamous Cell Lung Cancers (SWOG S1400)

INTRODUCTION

Squamous cell cancer (SqCC) is a lung cancer subtype with few targeted therapy options. Molecular characterization, that is, by next-generation sequencing (NGS), is needed to identify potential targets. Lung Cancer Master Protocol Southwest Oncology Group S1400 enrolled patients with previously treated stage IV or recurrent SqCC to assess NGS biomarkers for therapeutic sub-studies.

METHODS

Tumors underwent NGS using Foundation Medicine's FoundationOne research platform, which sequenced the exons and/or introns of 313 cancer-related genes. Mutually exclusive gene set analysis and Selected Events Linked by Evolutionary Conditions across Human Tumors were performed to identify mutually exclusive and co-occurring gene alterations. Comparisons were performed with data on 495 lung SqCC downloaded from The Cancer Genome Atlas. Cox proportional hazards models were used to assess associations between genetic variants and survival.

RESULTS

NGS data are reported for 1672 patients enrolled on S1400 between 2014 and 2019. Mutually exclusive gene set analysis identified two non-overlapping sets of mutually exclusive alterations with a false discovery rate of less than 15%: NFE2L2, KEAP1, and PARP4; and CDKN2A and RB1. PARP4, a relatively uncharacterized gene, showed three frequent mutations suggesting functional significance: 3116T>C (I1039T), 3176A>G (Q1059R), and 3509C>T (T1170I). When taken together, NFE2L2 and KEAP1 alterations were associated with poorer survival.

CONCLUSIONS

As the largest dataset to date of lung SqCC profiled on a clinical trial, the S1400 NGS dataset establishes a rich resource for biomarker discovery. Mutual exclusivity of PARP4 and NFE2L2 or KEAP1 alterations suggests that PARP4 may have an uncharacterized role in a key pathway known to impact oxidative stress response and treatment resistance.

Leveraging machine learning: Covariate-adjusted Bayesian adaptive randomization and subgroup discovery in multi-arm survival trials

Clinical trials evaluate the safety and efficacy of treatments for specific diseases. Ensuring these studies are well-powered is crucial for identifying superior treatments. With the rise of personalized medicine, treatment efficacy may vary based on biomarker profiles. However, researchers often lack prior knowledge about which biomarkers are linked to varied treatment effects. Fixed or response-adaptive designs may not sufficiently account for heterogeneous patient characteristics, such as genetic diversity, potentially reducing the chance of selecting the optimal treatment for individuals. Recent advances in Bayesian nonparametric modeling pave the way for innovative trial designs that not only maintain robust power but also offer the flexibility to identify subgroups deriving greater benefits from specific treatments. Building on this inspiration, we introduce a Bayesian adaptive design for multi-arm trials focusing on time-to-event endpoints. We introduce a covariate-adjusted response adaptive randomization, updating treatment allocation probabilities grounded on causal effect estimates using a random intercept accelerated failure time BART model. After the trial concludes, we suggest employing a multi-response decision tree to pinpoint subgroups with varying treatment impacts. The performance of our design is then assessed via comprehensive simulations.

A process to reanalyze clinical DNA sequencing data for biomarker matching in the Lung-MAP Master Protocol

For cancer clinical trials that require central confirmation of tumor genomic profiling, exhaustion of tissue from standard-of-care testing may prevent enrollment. For Lung-MAP, a master protocol that requires results from a defined centralized clinical trial assay to assign patients to a therapeutic substudy, we developed a process to repurpose existing commercial vendor raw genomic data for eligibility: genomic data reanalysis (GDR). Molecular results for substudy assignment were successfully generated for 369 of the first 374 patients (98.7%) using GDR for Lung-MAP, with a median time from request to result of 9 days. During the same period, 691 of 791 (87.4%) tissue samples received successfully yielded results, in a median of 14 days beyond sample acquisition. GDR is a scalable bioinformatic pipeline that expedites reanalysis of existing data for clinical trials in which validated integral biomarker testing is required for participation.

Advancing randomized controlled trial methodologies: The place of innovative trial design in eating disorders research

Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.

Cost-effectiveness of immunotherapies for advanced squamous non-small cell lung cancer: a systematic review

BACKGROUND

There are differences in the pharmacoeconomics of Immune checkpoint blocking (ICB) therapies for the treatment of lung squamous cell carcinoma (LSCC). However, no corresponding review studies have fully discussed the cost-effectiveness of ICBs in treating LSCC. The aim of this paper is to systematically review and evaluate all available pharmacoeconomic studies of ICBs for LSCC.

METHOD

The inclusion criteria were based on the population, intervention, comparator, outcomes, and study designs. An electronic search was conducted by June 2023, and the following databases were used: PubMed, EMBASE, Cochrane Library, and Web of Science. Search keywords included 'Carcinoma', Non-Small-Cell Lung', 'Immunotherapy', and 'Economics, Medical'. The primary outcome was the cost-effectiveness analysis of ICB therapy in LSCC patients. Drummond Checklist was used to assess quality problems and possible bias in the study design of included pharmacoeconomic studies.

RESULTS

This review searched 15 articles on the economic evaluation of ICB treatment for LSCC. After a qualitative review of 15 studies, we concluded that nivolumab is more cost-effective as a monotherapy than chemotherapy alone. In the combination regimen, pembrolizumab combined with chemotherapy appears to be the most cost-effective option at present, but for Chinese payers with LSCC, locally developed treatments such as sintilimab or toripalimab in combination with chemotherapy are more cost-effective.

DISCUSSION

The inclusion of economic evaluation has heterogeneity in research design and outcomes, which can only support qualitative synthesis. Therefore, The results of this paper need to be treated with caution. For the Chinese market, instead of imported drugs, the possible cost-effectiveness of locally developed ICB therapies should be the focus of future research.

New clinical trial design in precision medicine: discovery, development and direction

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

Novel Approach to Accelerate Lung Cancer Research: Lung-MAP and the Potential of Public-Private Partnerships

The National Cancer Institute recently found that death rates for non-small cell lung cancer (NSCLC) have been reduced by over 6% overall in recent years. This reduction in mortality has been accompanied by an average increase in overall survival and largely credited to the therapeutic advancements for the effective treatment of NSCLC. Numerous molecular alterations have been identified in NSCLC that have enabled the development of new drugs capable of targeting these changes and efficiently kill cancerous cells. New treatments to modulate patients' immune systems have been shown to be effective in stimulating natural immune cells to have an improved anti-cancer effect. While these types of approaches to treat cancer are providing new options for patients, leadership from the Food and Drug Administration (FDA) recognized that the expansion of targeted therapy in NSCLC presented significant promise, but evaluation of the safety and efficacy of these new drugs would be slowed if new models for conducting clinical studies were not identified. Specifically, the FDA recommended that a comprehensive approach be implemented to identify the patients that are the best candidates for these, and other new treatments based upon the molecular characteristics of their tumors, and more efficiently conduct the clinical studies necessary to evaluate the safety and efficacy of new drugs. To address this growing challenge, leading lung cancer experts and stakeholders across academia, government, industry, and patient advocacy came together to design a clinical research approach that could serve as a sustainable infrastructure for new lung cancer treatments called the Lung Cancer Master Protocol.

Representativeness of Patients Enrolled in the Lung Cancer Master Protocol (Lung-MAP)

PURPOSE

Lung Cancer Master Protocol (Lung-MAP), a public-private partnership, established infrastructure for conducting a biomarker-driven master protocol in molecularly targeted therapies. We compared characteristics of patients enrolled in Lung-MAP with those of patients in advanced non-small-cell lung cancer (NSCLC) trials to examine if master protocols improve trial access.

METHODS

We examined patients enrolled in Lung-MAP (2014-2020) according to sociodemographic characteristics. Proportions for characteristics were compared with those for a set of advanced NSCLC trials (2001-2020) and the US advanced NSCLC population using SEER registry data (2014-2018). Characteristics of patients enrolled in Lung-MAP treatment substudies were examined in subgroup analysis. Two-sided tests of proportions at an alpha of .01 were used for all comparisons.

RESULTS

A total of 3,556 patients enrolled in Lung-MAP were compared with 2,215 patients enrolled in other NSCLC studies. Patients enrolled in Lung-MAP were more likely to be 65 years and older (57.2% v 46.3%; P < .0001), from rural areas (17.3% v 14.4%; P = .004), and from socioeconomically deprived neighborhoods (42.2% v 36.7%, P < .0001), but less likely to be female (38.6% v 47.2%; P < .0001), Asian (2.8% v 5.1%; P < .0001), or Hispanic (2.4% v 3.8%; P = .003). Among patients younger than 65 years, Lung-MAP enrolled more patients using Medicaid/no insurance (27.6% v 17.8%; P < .0001). Compared with the US advanced NSCLC population, Lung-MAP under represented patients 65 years and older (57.2% v 69.8%; P < .0001), females (38.6% v 46.0%; P < .0001), and racial or ethnic minorities (14.8% v 21.5%; P < .0001).

CONCLUSION

Master protocols may improve access to trials using novel therapeutics for older patients and socioeconomically vulnerable patients compared with conventional trials, but specific patient exclusion criteria influenced demographic composition. Further research examining participation barriers for under represented racial or ethnic minorities in precision medicine clinical trials is warranted.

The use of RNA-based treatments in the field of cancer immunotherapy

Over the past several decades, mRNA vaccines have evolved from a theoretical concept to a clinical reality. These vaccines offer several advantages over traditional vaccine techniques, including their high potency, rapid development, low-cost manufacturing, and safe administration. However, until recently, concerns over the instability and inefficient distribution of mRNA in vivo have limited their utility. Fortunately, recent technological advancements have mostly resolved these concerns, resulting in the development of numerous mRNA vaccination platforms for infectious diseases and various types of cancer. These platforms have shown promising outcomes in both animal models and humans. This study highlights the potential of mRNA vaccines as a promising alternative approach to conventional vaccine techniques and cancer treatment. This review article aims to provide a thorough and detailed examination of mRNA vaccines, including their mechanisms of action and potential applications in cancer immunotherapy. Additionally, the article will analyze the current state of mRNA vaccine technology and highlight future directions for the development and implementation of this promising vaccine platform as a mainstream therapeutic option. The review will also discuss potential challenges and limitations of mRNA vaccines, such as their stability and in vivo distribution, and suggest ways to overcome these issues. By providing a comprehensive overview and critical analysis of mRNA vaccines, this review aims to contribute to the advancement of this innovative approach to cancer treatment.

Progress in genome-inspired treatment decisions for multifocal lung adenocarcinoma

INTRODUCTION

Multifocal lung adenocarcinoma (MFLA) is becoming increasingly recognized as a distinct subset of lung cancer, with unique biology, disease course, and treatment outcomes. While definitions remain controversial, MFLA is characterized by the development and concurrent presence of multiple independent (non-metastatic) lesions on the lung adenocarcinoma spectrum. Disease progression typically follows an indolent course measured in years, with a lower propensity for nodal and distant metastases than other more common forms of non-small cell lung cancer.

AREAS COVERED

Traditional imaging and histopathological analyses of tumor biopsies are frequently unable to fully characterize the disease, prompting interest in molecular diagnosis. We highlight some of the key questions in the field, including accurate definitions to identify and stage MLFA, molecular tests to stratify patients and treatment decisions, and the lack of clinical trial data to delineate best management for this poorly understood subset of lung cancer patients. We review the existing literature and progress toward a genomic diagnosis for this unique disease entity.

EXPERT OPINION

Multifocal lung adenocarcinoma behaves differently than other forms of non-small cell lung cancer. Progress in molecular diagnosis may enhance potential for accurate definition, diagnosis, and optimizing treatment approach.

Unlocking multidimensional cancer therapeutics using geometric data science

Personalised approaches to cancer therapeutics primarily involve identification of patient sub-populations most likely to benefit from targeted drugs. Such a stratification has led to plethora of designs of clinical trials that are often too complex due to the need for incorporating biomarkers and tissue types. Many statistical methods have been developed to address these issues; however, by the time such methodology is available research in cancer has moved on to new challenges and therefore in order to avoid playing catch-up it is necessary to develop new analytic tools alongside. One of the challenges facing cancer therapy is to effectively and appropriately target multiple therapies for sensitive patient population based on a panel of biomarkers across multiple cancer types, and matched future trial designs. We present novel geometric methods (mathematical theory of hypersurfaces) to visualise complex cancer therapeutics data as multidimensional, as well as geometric representation of oncology trial design space in higher dimensions. The hypersurfaces are used to describe master protocols, with application to a specific example of a basket trial design for melanoma, and thus setup a framework for further incorporating multi-omics data as multidimensional therapeutics.

Assessing patient-level knowledge of precision medicine in a community health center setting

As precision medicine approaches are implemented, cancer treatment decisions have come to require comprehension of genetic tests and their role in risk stratification and treatment options. Acceptance and implementation of precision medicine requires patient understanding of numeracy, genetic literacy, health literacy, and medical trust. Implementing precision medicine in a US federally qualified community health center (FQCHC) setting has received little attention. Using a mixed-methods approach, we sought to identify patient-level factors influencing the understanding of cancer risk and precision medicine among FQCHC patients. We enrolled 26 English-speaking adults aged 40-79 years. Participants enrolled in focus groups and completed surveys to assess patient-level understanding of precision medicine, numeracy, and health literacy. The majority of participants were female (77%) and self-identified as African American (89%). Approximately one-third reported having a high school degree or less. While health literacy was generally high, 42% felt that genes or genetics had little impact on health and most (69%) reported little familiarity with precision medicine. Many participants reported that trust in their providers was extremely or very important when receiving genetic tests. Numeracy levels were moderate, with nearly half reporting some discomfort working with fractions and 38% finding numerical information only occasionally useful. Findings suggest that patients may lack familiarity with precision medicine concepts relevant for understanding cancer treatment decisions. Future educational efforts may help bridge the gap in patient understanding and facilitate equitable opportunities for precision medicine for all patients, including those seeking care from community health centers.

Rare molecular subtypes of lung cancer

Oncogenes that occur in ≤5% of non-small-cell lung cancers have been defined as 'rare'; nonetheless, this frequency can correspond to a substantial number of patients diagnosed annually. Within rare oncogenes, less commonly identified alterations (such as HRAS, NRAS, RIT1, ARAF, RAF1 and MAP2K1 mutations, or ERBB family, LTK and RASGRF1 fusions) can share certain structural or oncogenic features with more commonly recognized alterations (such as KRAS, BRAF, MET and ERBB family mutations, or ALK, RET and ROS1 fusions). Over the past 5 years, a surge in the identification of rare-oncogene-driven lung cancers has challenged the boundaries of traditional clinical grade diagnostic assays and profiling algorithms. In tandem, the number of approved targeted therapies for patients with rare molecular subtypes of lung cancer has risen dramatically. Rational drug design has iteratively improved the quality of small-molecule therapeutic agents and introduced a wave of antibody-based therapeutics, expanding the list of actionable de novo and resistance alterations in lung cancer. Getting additional molecularly tailored therapeutics approved for rare-oncogene-driven lung cancers in a larger range of countries will require ongoing stakeholder cooperation. Patient advocates, health-care agencies, investigators and companies with an interest in diagnostics, therapeutics and real-world evidence have already taken steps to surmount the challenges associated with research into low-frequency drivers.

A transcriptomics approach to expand therapeutic options and optimize clinical trials in oncology

Background

The current model of clinical drug development in oncology displays major limitations due to a high attrition rate in patient enrollment in early phase trials and a high failure rate of drugs in phase III studies.

Objective

Integrating transcriptomics for selection of patients has the potential to achieve enhanced speed and efficacy of precision oncology trials for any targeted therapies or immunotherapies.

Methods

Relative gene expression level in the metastasis and normal organ-matched tissues from the WINTHER database was used to estimate in silico the potential clinical benefit of specific treatments in a variety of metastatic solid tumors.

Results

As example, high mRNA expression in tumor tissue compared to analogous normal tissue of c-MET and its ligand HGF correlated in silico with shorter overall survival (OS; p < 0.0001) and may constitute an independent prognostic marker for outcome of patients with metastatic solid tumors, suggesting a strategy to identify patients most likely to benefit from MET-targeted treatments. The prognostic value of gene expression of several immune therapy targets (PD-L1, CTLA4, TIM3, TIGIT, LAG3, TLR4) was investigated in non-small-cell lung cancers and colorectal cancers (CRCs) and may be useful to optimize the development of their inhibitors, and opening new avenues such as use of anti-TLR4 in treatment of patients with metastatic CRC.

Conclusion

This in silico approach is expected to dramatically decrease the attrition of patient enrollment and to simultaneously increase the speed and detection of early signs of efficacy. The model may significantly contribute to lower toxicities. Altogether, our model aims to overcome the limits of current approaches.

Platform trials to overcome major shortcomings of traditional clinical trials in non-alcoholic steatohepatitis? Pros and cons

Non-alcoholic fatty liver disease is a condition that affects 25% of the population. Non-alcoholic steatohepatitis (NASH) is a progressive form of the disease that can lead to severe complications such as cirrhosis and hepatocellular carcinoma. Despite its high prevalence, no drugs are currently approved for the treatment of NASH. The drug development pipeline in NASH is very active, yet most assets do not progress to phase III trials and those that do reach phase III often fail to achieve the endpoints necessary for approval by regulatory agencies. Amongst other reasons, the methodological and operational features of traditional clinical trials in NASH might impede optimal drug development. In this regard, platform trials might be an attractive complement or alternative to conventional clinical trials. Platform trials use a master protocol which enables evaluation of multiple investigational medicinal products concurrently or sequentially with a single, shared control arm. Through Bayesian interim analyses, these trials allow for early exit of drugs from the trial based on success or futility, while providing participants better chances of receiving active compounds through adaptive randomisation. Overall, platform trials represent an alternative for patients, pharmaceutical companies, and clinicians in the quest to accelerate the approval of pharmacologic treatments for NASH.

Combi-TED: a new trial testing Tedopi® with docetaxel or nivolumab in metastatic non-small-cell lung cancer progressing after first line

Despite the positive results obtained by first-line chemoimmunotherapy in patients with metastatic non-small-cell lung cancer (NSCLC), only a few second-line options are available after disease progression. Combi-TED is a phase II international study that will assess the efficacy of Tedopi®, a cancer vaccine, combined with either docetaxel or nivolumab and compared with docetaxel monotherapy in patients with metastatic NSCLC after chemoimmunotherapy. The study, currently in the recruitment phase, will assess 1-year overall survival (primary end point), patient's progression-free survival and overall response rate, as well as the correlation of efficacy with several tumor or blood biomarkers. The results will hopefully provide more information on Tedopi combinational treatment compared with current standard of care in NSCLC patients who fail first-line chemoimmunotherapy. Clinical Trial Registration: NCT04884282 (ClinicalTrials.gov).

Design and analysis of umbrella trials: Where do we stand?

Background

The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted in their consideration in non-oncology settings. Umbrella trials are one class of master protocol design that evaluates multiple targeted therapies in a single disease setting. Despite the existence of several reviews of master protocols, the statistical considerations of umbrella trials have received more limited attention.

Methods

We conduct a systematic review of the literature on umbrella trials, examining both the statistical methods that are available for their design and analysis, and also their use in practice. We pay particular attention to considerations for umbrella designs applied outside of oncology.

Findings

We identified 38 umbrella trials. To date, most umbrella trials have been conducted in early phase settings (73.7%, 28/38) and in oncology (92.1%, 35/38). The quality of statistical information available about conducted umbrella trials to date is poor; for example, it was impossible to ascertain how sample size was determined in the majority of trials (55.3%, 21/38). The literature on statistical methods for umbrella trials is currently sparse.

Conclusions

Umbrella trials have potentially great utility to expedite drug development, including outside of oncology. However, to enable lessons to be effectively learned from early use of such designs, there is a need for higher-quality reporting of umbrella trials. Furthermore, if the potential of umbrella trials is to be realized, further methodological research is required.

Novel Clinical Trial Designs in Neuro-Oncology

Scientific and technologic advances have led to a boon of candidate therapeutics for patients with malignancies of the central nervous system. The path from drug development to clinical use has generally followed a regimented order of sequential clinical trial phases. The recent increase in novel therapies, however, has strained the regulatory process and unearthed limitations of the current system, including significant cost, prolonged development time, and difficulties in testing therapies for rarer tumors. Novel clinical trial designs have emerged to increase efficiencies in clinical trial conduct to better evaluate and bring impactful drugs to patients in a timely manner. In order to better capture meaningful benefits for brain tumor patients, new endpoints to complement or replace traditional endpoints are also an increasingly important consideration. This review will explore the current challenges in the current clinical trial landscape and discuss novel clinical trial concepts, including consideration of limitations and risks of novel trial designs, within the context of neuro-oncology.

Optimizing a Bayesian hierarchical adaptive platform trial design for stroke patients

BACKGROUND

Platform trials are well-known for their ability to investigate multiple arms on heterogeneous patient populations and their flexibility to add/drop treatment arms due to efficacy/lack of efficacy. Because of their complexity, it is important to develop highly optimized, transparent, and rigorous designs that are cost-efficient, offer high statistical power, maximize patient benefit, and are robust to changes over time.

METHODS

To address these needs, we present a Bayesian platform trial design based on a beta-binomial model for binary outcomes that uses three key strategies: (1) hierarchical modeling of subgroups within treatment arms that allows for borrowing of information across subgroups, (2) utilization of response-adaptive randomization (RAR) schemes that seek a tradeoff between statistical power and patient benefit, and (3) adjustment for potential drift over time. Motivated by a proposed clinical trial that aims to find the appropriate treatment for different subgroup populations of ischemic stroke patients, extensive simulation studies were performed to validate the approach, compare different allocation rules, and study the model operating characteristics.

RESULTS AND CONCLUSIONS

Our proposed approach achieved high statistical power and good patient benefit and was also robust against population drift over time. Our design provided a good balance between the strengths of both the traditional RAR scheme and fixed 1:1 allocation and may be a promising choice for dichotomous outcomes trials investigating multiple subgroups.

New Drug Development and Clinical Trial Design by Applying Genomic Information Management

Depending on the patients’ genotype, the same drug may have different efficacies or side effects. With the cost of genomic analysis decreasing and reliability of analysis methods improving, vast amount of genomic information has been made available. Several studies in pharmacology have been based on genomic information to select the optimal drug, determine the dose, predict efficacy, and prevent side effects. This paper reviews the tissue specificity and genomic information of cancer. If the tissue specificity of cancer is low, cancer is induced in various organs based on a single gene mutation. Basket trials can be performed for carcinomas with low tissue specificity, confirming the efficacy of one drug for a single gene mutation in various carcinomas. Conversely, if the tissue specificity of cancer is high, cancer is induced in only one organ based on a single gene mutation. An umbrella trial can be performed for carcinomas with a high tissue specificity. Some drugs are effective for patients with a specific genotype. A companion diagnostic strategy that prescribes a specific drug for patients selected with a specific genotype is also reviewed. Genomic information is used in pharmacometrics to identify the relationship among pharmacokinetics, pharmacodynamics, and biomarkers of disease treatment effects. Utilizing genomic information, sophisticated clinical trials can be designed that will be better suited to the patients of specific genotypes. Genomic information also provides prospects for innovative drug development. Through proper genomic information management, factors relating to drug response and effects can be determined by selecting the appropriate data for analysis and by understanding the structure of the data. Selecting pre-processing and appropriate machine-learning libraries for use as machine-learning input features is also necessary. Professional curation of the output result is also required. Personalized medicine can be realized using a genome-based customized clinical trial design.

Phase II Randomized Study of Ramucirumab and Pembrolizumab Versus Standard of Care in Advanced Non-Small-Cell Lung Cancer Previously Treated With Immunotherapy-Lung-MAP S1800A

PURPOSE

Resistance to immune checkpoint inhibition (ICI) in advanced non-small-cell lung cancer (NSCLC) represents a major unmet need. Combining ICI with vascular endothelial growth factor (VEGF)/VEGF receptor inhibition has yielded promising results in multiple tumor types.

METHODS

In this randomized phase II Lung-MAP nonmatch substudy (S1800A), patients ineligible for a biomarker-matched substudy with NSCLC previously treated with ICI and platinum-based chemotherapy and progressive disease at least 84 days after initiation of ICI were randomly assigned to receive ramucirumab plus pembrolizumab (RP) or investigator's choice standard of care (SOC: docetaxel/ramucirumab, docetaxel, gemcitabine, and pemetrexed). With a goal of 130 eligible patients, the primary objective was to compare overall survival (OS) using a one-sided 10% level using the better of a standard log-rank (SLR) and weighted log-rank (WLR; G[rho = 0, gamma = 1]) test. Secondary end points included objective response, duration of response, investigator-assessed progression-free survival, and toxicity.

RESULTS

Of 166 patients enrolled, 136 were eligible (69 RP; 67 SOC). OS was significantly improved with RP (hazard ratio [80% CI]: 0.69 [0.51 to 0.92]; SLR one-sided P = .05; WLR one-sided P = .15). The median (80% CI) OS was 14.5 (13.9 to 16.1) months for RP and 11.6 (9.9 to 13.0) months for SOC. OS benefit for RP was seen in most subgroups. Investigator-assessed progression-free survival (hazard ratio [80% CI]: 0.86 [0.66 to 1.14]; one-sided SLR, P = .25 and .14 for WLR) and response rates (22% RP v 28% SOC, one-sided P = .19) were similar between arms. Grade ≥ 3 treatment-related adverse events occurred in 42% of patients in the RP group and 60% on SOC.

CONCLUSION

This randomized phase II trial demonstrated significantly improved OS with RP compared with SOC in patients with advanced NSCLC previously treated with ICI and chemotherapy. The safety was consistent with known toxicities of both drugs. These data warrant further evaluation.

Landscape of coronavirus disease 2019 clinical trials: New frontiers and challenges

BACKGROUND/AIM

The number of coronavirus disease 2019 deaths and cases continues to increase globally. Novel therapies are urgently needed to treat patients with coronavirus disease 2019. We sought to provide a critical review of trials designed during the coronavirus disease 2019 pandemic. Our primary goal was to provide a critical review of the landscape of clinical trials designed to address the coronavirus disease 2019 pandemic. Specifically, we were interested in assessing the design of phase II/III and phase III interventional trials.

METHODS

We utilized the ClinicalTrials.gov database to include trials registered between 1 December 2019 and 11 April 2021 to survey the current landscape of clinical trials for coronavirus disease 2019. Variables extracted included: National Clinical Trial number, title, location, sponsor, study type, start date, completion date, gender group, age group, primary outcome, secondary outcome, overall status, and associated references.

RESULTS

About 57% of studies were interventional, 14.5% were phase III trials, and the majority of the therapeutic trials included hospitalized patients. There were 52 primary composite outcomes and 285 unique interventions spanning 10 drug classes. The outcomes, disease severity, and comparators varied substantially across trials, and the trials were often too small to be definitive.

CONCLUSION

These findings are relevant as we strongly advocate for global coordination of efforts through the use of common platforms that enable harmonizing of endpoints, collection of common key variables and clear definition of disease severity to have clinically meaningful results from clinical trials.

Patient Knowledge and Expectations About Return of Genomic Results in a Biomarker-Driven Master Protocol Trial (SWOG S1400GEN)

PURPOSE

Biomarker-driven master protocols represent a new paradigm in oncology clinical trials, but their complex designs and wide-ranging genomic results returned can be difficult to communicate to participants. The objective of this pilot study was to evaluate patient knowledge and expectations related to return of genomic results in the Lung Cancer Master Protocol (Lung-MAP).

METHODS

Eligible participants with previously treated advanced non-small-cell lung cancer were recruited from patients enrolled in Lung-MAP. Participants completed a 38-item telephone survey ≤ 30 days from Lung-MAP consent. The survey assessed understanding about the benefits and risks of Lung-MAP participation and knowledge of the potential uses of somatic testing results returned. Descriptive statistics and odds ratios for associations between demographic factors and correct responses to survey items were assessed.

RESULTS

From August 1, 2017, to June 30, 2019, we recruited 207 participants with a median age of 67, 57.3% male, and 94.2% White. Most participants "strongly/somewhat agreed" with statements that they "received enough information to understand" Lung-MAP benefits (82.6%) and risks (69.5%). In items asking about potential uses of Lung-MAP genomic results, 87.0% correctly indicated that the results help to select cancer treatment, but < 20% correctly indicated that the results are not used to confirm cancer diagnosis, would not reveal risk of developing diseases besides cancer, and would not indicate if family members had increased cancer risk. There were no associations between sociodemographic factors and proportions providing correct responses.

CONCLUSION

In a large National Clinical Trials Network biomarker-driven master protocol, most participants demonstrated incorrect knowledge and expectations about the uses of genomic results provided in the study despite most indicating that they had enough information to understand benefits and risks.

Streamlined Operational Approaches and Use of e-Technologies in Clinical Trials: Beat Acute Myeloid Leukemia Master Trial

Advances in genomic technologies and an increased understanding of the molecular pathogenesis of cancer have resulted in development of new effective, mutation-targeted therapies. In turn, these informed the development of Master Trial designs to test these therapies. The Beat Acute Myeloid Leukemia (BAML) Master Trial (Sponsor: The Leukemia & Lymphoma Society) tests several targeted therapies in patients aged ≥ 60 years with AML based on genomic profiling obtained within 7 days of study enrollment. We hypothesized that integrating operational strategies with new electronic technologies (e-technologies) might streamline the conduct and management of this Master Trial. BAML's 5 core operational strategies revolve around the guiding principle of "patients first." The e-technology platforms employed in BAML include: Clinical Oversight Platform: a central collaborative tool; e-Protocol/e-Source Upload/Electronic Data Capture Platform: digitizes the protocol, allows remote data monitoring, and collects/exports data in Study Data Tabulation Model format; and Data Review Platform: ingests data from different sources for clinical response and safety data reviews. The operational approaches, e-technologies and sponsor/contract research organization's (CRO) expertise together allow: the complexity and size of the BAML Master Trial to be better managed; near real-time study data oversight; better collaboration, communication and training; improved data collection, enhanced transmission and accessibility; data integration, review and generation of reports; while maintaining data privacy, and compliance. Initial e-technology challenges were overcome through training, learning, discipline and adjustment. In conclusion, to successfully manage Master Trials, significant time should be spent re-evaluating, improving and developing new operational approaches.Clinical Trial Registration: Clinical Trials.gov Identifier: NCT03013998. https://clinicaltrials.gov/ct2/show/NCT03013998 .

Nivolumab Plus Ipilimumab vs Nivolumab for Previously Treated Patients With Stage IV Squamous Cell Lung Cancer: The Lung-MAP S1400I Phase 3 Randomized Clinical Trial

IMPORTANCE

Nivolumab plus ipilimumab is superior to platinum-based chemotherapy in treatment-naive advanced non-small cell lung cancer (NSCLC). Nivolumab is superior to docetaxel in advanced pretreated NSCLC.

OBJECTIVE

To determine whether the addition of ipilimumab to nivolumab improves survival in patients with advanced, pretreated, immunotherapy-naive squamous (Sq) NSCLC.

DESIGN, SETTING, AND PARTICIPANTS

The Lung Cancer Master Protocol (Lung-MAP) S1400I phase 3, open-label randomized clinical trial was conducted from December 18, 2015, to April 23, 2018, randomizing patients in a 1:1 ratio to nivolumab alone or combined with ipilimumab. The median follow-up in surviving patients was 29.5 months. The trial was conducted through the National Clinical Trials Network and included patients with advanced immunotherapy-naive SqNSCLC and a Zubrod score of 0 (asymptomatic) to 1 (symptomatic but completely ambulatory) with disease progression after standard platinum-based chemotherapy. Randomization was stratified by sex and number of prior therapies (1 vs 2 or more). Data were analyzed from May 3, 2018, to February 1, 2021.

INTERVENTIONS

Nivolumab, 3 mg/kg intravenously every 2 weeks, with or without ipilimumab, 1 mg/kg intravenously every 6 weeks, until disease progression or intolerable toxic effects.

MAIN OUTCOMES AND MEASURES

The primary end point was overall survival (OS). Secondary end points included investigator-assessed progression-free survival (IA-PFS) and response per Response Evaluation Criteria in Solid Tumors (RECIST) guidelines, version 1.1.

RESULTS

Of 275 enrolled patients, 252 (mean age, 67.5 years [range 41.8-90.3 years]; 169 men [67%]; 206 White patients [82%]) were deemed eligible (125 randomized to nivolumab/ipilimumab and 127 to nivolumab). The study was closed for futility at a planned interim analysis. Overall survival was not significantly different between the groups (hazard ratio [HR], 0.87; 95% CI, 0.66-1.16; P = .34). Median survival was 10 months (95% CI, 8.0-14.4 months) in the nivolumab/ipilimumab group and 11 months (95% CI, 8.6-13.7 months) in the nivolumab group. The IA-PFS HR was 0.80 (95% CI, 0.61-1.03; P = .09); median IA-PFS was 3.8 months (95% CI, 2.7-4.4 months) in the nivolumab/ipilimumab group and 2.9 months (95% CI, 1.8-4.0 months) in the nivolumab alone group. Response rates were 18% (95% CI, 12%-25%) with nivolumab/ipilimumab and 17% (95% CI, 10%-23%) with nivolumab. Median response duration was 28.4 months (95% CI, 4.9 months to not reached) with nivolumab/ipilimumab and 9.7 months with nivolumab (95% CI, 4.2-23.1 months). Grade 3 or higher treatment-related adverse events occurred in 49 of 124 patients (39.5%) who received nivolumab/ipilimumab and in 41 of 123 (33.3%) who received nivolumab alone. Toxic effects led to discontinuation in 31 of 124 patients (25%) on nivolumab/ipilimumab and in 19 of 123 (15%) on nivolumab.

CONCLUSIONS AND RELEVANCE

In this phase 3 randomized clinical trial, ipilimumab added to nivolumab did not improve outcomes in patients with advanced, pretreated, immune checkpoint inhibitor-naive SqNSCLC.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02785952.

Toward personalized treatment approaches for non-small-cell lung cancer

Worldwide, lung cancer is the most common cause of cancer-related deaths. Molecular targeted therapies and immunotherapies for non-small-cell lung cancer (NSCLC) have improved outcomes markedly over the past two decades. However, the vast majority of advanced NSCLCs become resistant to current treatments and eventually progress. In this Perspective, we discuss some of the recent breakthrough therapies developed for NSCLC, focusing on immunotherapies and targeted therapies. We highlight our current understanding of mechanisms of resistance and the importance of incorporating genomic analyses into clinical studies to decipher these further. We underscore the future role of neoadjuvant and maintenance combination therapy approaches to potentially cure early disease. A major challenge to successful development of rational combination therapies will be the application of robust predictive biomarkers for clear-cut patient stratification, and we provide our views on clinical research areas that could influence how NSCLC will be managed over the coming decade.

Phase II study of durvalumab plus tremelimumab as therapy for patients with previously treated anti-PD-1/PD-L1 resistant stage IV squamous cell lung cancer (Lung-MAP substudy S1400F, NCT03373760)

INTRODUCTION

S1400F is a non-match substudy of Lung Cancer Master Protocol (Lung-MAP) evaluating the immunotherapy combination of durvalumab and tremelimumab to overcome resistance to anti-programmed death ligand 1 (PD-(L)1) therapy in patients with advanced squamous lung carcinoma (sq non-small-cell lung cancer (NSCLC)).

METHODS

Patients with previously treated sqNSCLC with disease progression after anti-PD-(L)1 monotherapy, who did not qualify for any active molecularly targeted Lung-MAP substudies, were eligible. Patients received tremelimumab 75 mg plus durvalumab 1500 mg once every 28 days for four cycles then durvalumab alone every 28 days until disease progression. The primary endpoint was the objective response rate (RECIST V.1.1). Primary and acquired resistance cohorts, defined as disease progression within 24 weeks versus ≥24 weeks of starting prior anti-PD-(L)1 therapy, were analyzed separately and an interim analysis for futility was planned after 20 patients in each cohort were evaluable for response.

RESULTS

A total of 58 eligible patients received drug, 28 with primary resistance and 30 with acquired resistance to anti-PD-(L)1 monotherapy. Grade ≥3 adverse events at least possibly related to treatment were seen in 20 (34%) patients. The response rate in the primary resistance cohort was 7% (95% CI 0% to 17%), with one complete and one partial response. No responses were seen in the acquired resistance cohort. In the primary and resistance cohorts the median progression-free survival was 2.0 months (95% CI 1.6 to 3.0) and 2.1 months (95% CI 1.6 to 3.2), respectively, and overall survival was 7.7 months (95% CI 4.0 to 12.0) and 7.6 months (95% CI 5.3 to 10.2), respectively.

CONCLUSION

Durvalumab plus tremelimumab had minimal activity in patients with advanced sqNSCLC progressing on prior anti-PD-1 therapy.Trial registration numberNCT03373760.

What can heart failure trialists learn from oncology trialists?

Globally, there has been little change in mortality rates from cardiovascular (CV) diseases or cancers over the past two decades (1997-2018). This is especially true for heart failure (HF) where 5-year mortality rates remain as high as 45-55%. In the same timeframe, the proportion of drug revenue, and regulatory drug approvals for cancer drugs, far out paces those for CV drugs. In 2018, while cancer drugs made 27% of Food and Drug Administration drug approvals, only 1% of drug approvals was for a CV drug, and over this entire 20 year span, only four drugs were approved for HF in the USA. Cardiovascular trialists need to reassess the design, execution, and purpose of CV clinical trials. In the area of oncology research, trials are much smaller, follow-up is shorter, and targeted therapies are common. Cardiovascular diseases and cancer are the two most common causes of death globally, and although they differ substantially, this review evaluates whether some elements of oncology research may be applicable in the CV arena. As one of the most underserved CV diseases, the review focuses on aspects of cancer research that may be applicable to HF research with the aim of streamlining the clinical trial process and decreasing the time and cost required to bring safe, effective, treatments to patients who need them. The paper is based on discussions among clinical trialists, industry representatives, regulatory authorities, and patients, which took place at the Cardiovascular Clinical Trialists Workshop in Washington, DC, on 8 December 2019 (https://www.globalcvctforum.com/2019 (14 September 2020)).

Phase 2 Study of Talazoparib in Patients With Homologous Recombination Repair-Deficient Squamous Cell Lung Cancer: Lung-MAP Substudy S1400G

PURPOSE

This signal finding study (S1400G) was designed to evaluate the efficacy of talazoparib in advanced stage squamous cell lung cancer harboring homologous recombination repair deficiency.

PATIENTS AND METHODS

The full eligible population (FEP) had tumors with a deleterious mutation in any of the study-defined homologous recombination repair genes and without prior exposure to a PARP inhibitor. The primary analysis population (PAP) is a subset of FEP with alteration in ATM, ATR, BRCA1, BRCA2, or PALB2. Treatment consisted of talazoparib 1 mg daily continuously in 21-day cycles. A 2-stage design with exact 93% power and 1-sided 0.07 type I error required enrollment of 40 patients in the PAP in order to rule out an overall response rate (ORR) of 15% or less if the true ORR is ≥ 35%.

RESULTS

The study enrolled 47 patients in the FEP, of whom 24 were in the PAP. The median age for the FEP was 66.7 years; 83% were male and 85% white. ORR in the PAP was 4% (95% confidence interval [CI], 0, 21) with disease control rate of 54% (95% CI, 33, 74). Median progression-free survival and overall survival were 2.4 months (95% CI, 1.5-2.8) and 5.2 months (95% CI, 4.0-10), respectively. In the FEP, ORR was 11% (95% CI, 3.6, 23), the disease control rate was 51% (95% CI, 36, 66), and the median duration of response was 1.8 months (95% CI, 1.3, 4.2). Median progression-free and overall survival were 2.5 months and 5.7 months, respectively.

CONCLUSIONS

S1400G failed to show sufficient level of efficacy for single agent talazoparib in a biomarker defined subset of squamous lung cancer with homologous recombination repair deficiency.

A Phase II Study of Telisotuzumab Vedotin in Patients With c-MET-positive Stage IV or Recurrent Squamous Cell Lung Cancer (LUNG-MAP Sub-study S1400K, NCT03574753)

INTRODUCTION

Lung-MAP S1400K was designed to evaluate the response to telisotuzumab vedotin, an antibody-drug conjugate targeting c-MET, in patients with c-MET-positive squamous cell carcinoma (SCC).

PATIENTS AND METHODS

Patients with previously treated SCC with c-MET-positive tumors (H score ≥ 150, Ventana SP44 assay) were enrolled into 2 cohorts: Cohort 1 (immune checkpoint inhibitor-naive) and Cohort 2 (immune checkpoint inhibitor refractory). Telisotuzumab vedotin 2.7 mg/kg was administered intravenously every 3 weeks until disease progression or unacceptable toxicity. Response assessments were performed every 6 weeks. The primary endpoint was response by Response Evaluation Criteria in Solid Tumors (RECIST) v1.1. Secondary endpoints included progression-free survival, overall survival, response within cohort, duration of response, and toxicities. Interim analysis was planned after 20 evaluable patients, with ≥ 3 responses needed to continue enrollment.

RESULTS

Forty-nine patients (14% of screened patients) were assigned to S1400K, 28 patients enrolled (15 in Cohort 1 and 13 in Cohort 2), and 23 were eligible. S1400K closed on December 21, 2018 owing to lack of efficacy. Two responses (response rate of 9%; 95% confidence interval, 0%-20%) were reported in cohort 1 (1 complete and 1 unconfirmed partial response), whereas 10 patients had stable disease, with a disease control rate of 52%. The median overall and progression-free survival was 5.6 and 2.4 months, respectively. There were 3 grade 5 events (2 pneumonitis, in Cohort 2, and 1 bronchopulmonary hemorrhage, in Cohort 1).

CONCLUSION

Telisotuzumab vedotin failed to meet the pre-specified response needed to justify continuing enrollment to S1400K. Pneumonitis was an unanticipated toxicity observed in patients with SCC.

Treatment allocation strategies for umbrella trials in the presence of multiple biomarkers: A comparison of methods

Umbrella trials are an innovative trial design where different treatments are matched with subtypes of a disease, with the matching typically based on a set of biomarkers. Consequently, when patients can be positive for more than one biomarker, they may be eligible for multiple treatment arms. In practice, different approaches could be applied to allocate patients who are positive for multiple biomarkers to treatments. However, to date there has been little exploration of how these approaches compare statistically. We conduct a simulation study to compare five approaches to handling treatment allocation in the presence of multiple biomarkers – equal randomisation; randomisation with fixed probability of allocation to control; Bayesian adaptive randomisation (BAR); constrained randomisation; and hierarchy of biomarkers. We evaluate these approaches under different scenarios in the context of a hypothetical phase II biomarker-guided umbrella trial. We define the pairings representing the pre-trial expectations on efficacy as linked pairs, and the other biomarker-treatment pairings as unlinked. The hierarchy and BAR approaches have the highest power to detect a treatment-biomarker linked interaction. However, the hierarchy procedure performs poorly if the pre-specified treatment-biomarker pairings are incorrect. The BAR method allocates a higher proportion of patients who are positive for multiple biomarkers to promising treatments when an unlinked interaction is present. In most scenarios, the constrained randomisation approach best balances allocation to all treatment arms. Pre-specification of an approach to deal with treatment allocation in the presence of multiple biomarkers is important, especially when overlapping subgroups are likely.

On the design and the analysis of stratified biomarker trials in the presence of measurement error

A major emphasis in precision medicine is to optimally treat subgroups of patients who may benefit from certain therapeutic agents. And as such, enormous resources and innovative clinical trials designs in oncology are devoted to identifying predictive biomarkers. Predictive biomarkers are ones that will identify patients that are more likely to respond to specific therapies and they are usually discovered through retrospective analysis from large randomized phase II or phase III trials. One important design to consider is the stratified biomarker design, where patients will have their specimens obtained at baseline and the biomarker status will be assessed prior to random assignment. Regardless of their biomarker status, patients will be randomized to either an experimental arm or the standard of care arm. The stratified biomarker design can be used to test for a treatment-biomarker interaction in predicting a time-to event outcome. Many biomarkers, however, are derived from tissues from patients, and their levels may be heterogeneous. As a result, biomarker levels may be measured with error and this would have an adverse impact on the power of a stratified biomarker clinical trial. We present a trial design and an analysis framework for the stratified biomarker design. We show that the naïve test is biased and provide bias-corrected estimators for computing the sample size and the 95% confidence interval when testing for a treatment-biomarker interaction in predicting a time to event outcome. We propose a sample size formula that adjusts for misclassification and apply it in the design of a phase III clinical trial in renal cancer.

Molecular characterization of lung squamous cell carcinoma tumors reveals therapeutically relevant alterations

INTRODUCTION

Unlike lung adenocarcinoma patients, there is no FDA-approved targeted-therapy likely to benefit lung squamous cell carcinoma patients.

MATERIALS AND METHODS

We performed survival analyses of lung squamous cell carcinoma patients harboring therapeutically relevant alterations identified by whole exome sequencing and mass spectrometry-based validation across 430 lung squamous tumors.

RESULTS

We report a mean of 11.6 mutations/Mb with a characteristic smoking signature along with mutations in TP53 (65%), CDKN2A (20%), NFE2L2 (20%), FAT1 (15%), KMT2C (15%), LRP1B (15%), FGFR1 (14%), PTEN (10%) and PREX2 (5%) among lung squamous cell carcinoma patients of Indian descent. In addition, therapeutically relevant EGFR mutations occur in 5.8% patients, significantly higher than as reported among Caucasians. In overall, our data suggests 13.5% lung squamous patients harboring druggable mutations have lower median overall survival, and 19% patients with a mutation in at least one gene, known to be associated with cancer, result in significantly shorter median overall survival compared to those without mutations.

CONCLUSIONS

We present the first comprehensive landscape of genetic alterations underlying Indian lung squamous cell carcinoma patients and identify EGFR, PIK3CA, KRAS and FGFR1 as potentially important therapeutic and prognostic target.

Novel Study Designs in Precision Medicine - Basket, Umbrella and Platform Trials

The concept of 'one size fits all' - one treatment for patients with a particular disease, seems to be outdated. The advent of precision medicine has prompted profound changes in clinical research and it allows researchers to predict, more accurately, the prevention and treatment strategies for a specific disease population. Novel study designs are, therefore, essential to establish safe and effective personalized medicine. Basket, umbrella and platform trial designs (collectively referred to as master protocols) are biomarker enrichment designs that allow for testing more than one hypothesis within a protocol, thus accelerating drug development. These trial designs tailor intervention strategies based on patient's risk factor(s) that can help predict whether they will respond to a specific treatment. Basket trials evaluate therapy for various diseases that share a common molecular alteration while umbrella trials evaluate multiple targeted therapies for a single disease that is stratified into subgroups based on different molecular alterations/ risk factors. These designs are complex and their major limitations stem from the fact that it would be inappropriate to completely replace histological typing with molecular profiling alone. However, in the upcoming decades, these trial designs are likely to gain popularity and improve the efficiency of clinical research. This article briefly overviews the characteristics of master protocol designs with examples of completed and ongoing clinical trials utilizing these study designs.

Recent advances in preclinical models for lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) represents a major subtype of non-small cell lung cancer with limited treatment options. Previous studies have elucidated the complex genetic landscape of LUSC and revealed multiple altered genes and pathways. However, in stark contrast to lung adenocarcinoma, few targetable driver mutations have been established so far and targeted therapies for LUSC remain unsuccessful. Immunotherapy has revolutionized LUSC treatment and is currently approved as the new standard of care. To gain a better understanding of the LUSC biology, improved modeling systems are urgently needed. Preclinical models, particularly those mimicking human disease with an intact tumor immune microenvironment, are an invaluable tool to study cancer development and evaluate new therapeutic targets. Here, we discuss recent advances in LUSC preclinical models, with a focus on genetically engineered mouse models (GEMMs) and organoids, in the context of evolving precision medicine and immunotherapy.

Molecular Profiling-Based Assignment of Cancer Therapy (NCI-MPACT): A Randomized Multicenter Phase II Trial

This trial assessed the utility of applying tumor DNA sequencing to treatment selection for patients with advanced, refractory cancer and somatic mutations in one of four signaling pathways by comparing the efficacy of four study regimens that were either matched to the patient's aberrant pathway (experimental arm) or not matched to that pathway (control arm).

MATERIALS AND METHODS

Adult patients with an actionable mutation of interest were randomly assigned 2:1 to receive either (1) a study regimen identified to target the aberrant pathway found in their tumor (veliparib with temozolomide or adavosertib with carboplatin [DNA repair pathway], everolimus [PI3K pathway], or trametinib [RAS/RAF/MEK pathway]), or (2) one of the same four regimens, but chosen from among those not targeting that pathway.

RESULTS

Among 49 patients treated in the experimental arm, the objective response rate was 2% (95% CI, 0% to 10.9%). One of 20 patients (5%) in the experimental trametinib cohort had a partial response. There were no responses in the other cohorts. Although patients and physicians were blinded to the sequencing and random assignment results, a higher pretreatment dropout rate was observed in the control arm (22%) compared with the experimental arm (6%; P = .038), suggesting that some patients may have had prior tumor mutation profiling performed that led to a lack of participation in the control arm.

CONCLUSION

Further investigation, better annotation of predictive biomarkers, and the development of more effective agents are necessary to inform treatment decisions in an era of precision cancer medicine. Increasing prevalence of tumor mutation profiling and preference for targeted therapy make it difficult to use a randomized phase II design to evaluate targeted therapy efficacy in an advanced disease setting.

Next Generation Sequencing in Non-Small Cell Lung Cancer: Pitfalls and Opportunities

Lung cancer remains the first cause of cancer-related deaths worldwide. Thanks to the improvement in the knowledge of the biology of non-small cell lung cancer (NSCLC), patients' survival has significantly improved. A growing number of targetable molecular alterations have been identified. Next-generation sequencing (NGS) has become one of the methodologies entered in clinical practice and was recently recommended by the European society for medical oncology (ESMO) to perform a comprehensive molecular characterization in patients with cancer. The current review provides an overview of the clinical trials that have explored the impact of NGS in patients with cancer, its limits, and advantages.

Methods and resources to access mutation-dependent effects on cancer drug treatment

In clinical cancer treatment, genomic alterations would often affect the response of patients to anticancer drugs. Studies have shown that molecular features of tumors could be biomarkers predictive of sensitivity or resistance to anticancer agents, but the identification of actionable mutations are often constrained by the incomplete understanding of cancer genomes. Recent progresses of next-generation sequencing technology greatly facilitate the extensive molecular characterization of tumors and promote precision medicine in cancers. More and more clinical studies, cancer cell lines studies, CRISPR screening studies as well as patient-derived model studies were performed to identify potential actionable mutations predictive of drug response, which provide rich resources of molecularly and pharmacologically profiled cancer samples at different levels. Such abundance of data also enables the development of various computational models and algorithms to solve the problem of drug sensitivity prediction, biomarker identification and in silico drug prioritization by the integration of multiomics data. Here, we review the recent development of methods and resources that identifies mutation-dependent effects for cancer treatment in clinical studies, functional genomics studies and computational studies and discuss the remaining gaps and future directions in this area.

Biomarker-driven therapies for previously treated squamous non-small-cell lung cancer (Lung-MAP SWOG S1400): a biomarker-driven master protocol

BACKGROUND

The Lung Cancer Master Protocol (Lung-MAP; S1400) is a completed biomarker-driven master protocol designed to address an unmet need for better therapies for squamous non-small-cell lung cancer. Lung-MAP (S1400) was created to establish an infrastructure for biomarker screening and rapid regulatory intent evaluation of targeted therapies and was the first biomarker-driven master protocol initiated with the US National Cancer Institute (NCI).

METHODS

Lung-MAP (S1400) was done within the National Clinical Trials Network of the NCI using a public-private partnership. Eligible patients were aged 18 years or older, had stage IV or recurrent squamous non-small-cell lung cancer, had previously been treated with platinum-based chemotherapy, and had an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2. The study included a screening component using the FoundationOne assay (Foundation Medicine, Cambridge, MA, USA) for next-generation sequencing, and a clinical trial component with biomarker-driven substudies and non-match substudies for patients who were ineligible for biomarker-driven substudies. Patients were pre-screened and received their substudy assignment upon progression, or they were screened at progression and received their substudy assignment upon completion of testing. Patients could enrol onto additional substudies after progression on a substudy. The study is registered with ClinicalTrials.gov, NCT02154490, and all research related to Lung-MAP (S1400) is completed.

FINDINGS

Between June 16, 2014, and Jan 28, 2019, 1864 patients enrolled and 1841 (98·9%) submitted tissue. 1674 (90·9%) of 1841 patients had biomarker results, and 1404 (83·9%) of 1674 patients received a substudy assignment. Of the assigned patients, 655 (46·7%) registered to a substudy. The biomarker-driven substudies evaluated taselisib (targeting PIK3CA alterations), palbociclib (cell cycle gene alterations), AZD4547 (FGFR alteration), rilotumumab plus erlotinib (MET), talazoparib (homologous recombination repair deficiency), and telisotuzumab vedotin (MET). The non-match substudies evaluated durvalumab, and nivolumab plus ipilimumab for anti-PD-1 or anti-PD-L1-naive disease, and durvalumab plus tremelimumab for anti-PD-1 or anti-PD-L1 relapsed disease. Combining data from the substudies, ten (7·0%) of 143 patients responded to targeted therapy, 53 (16·8%) of 315 patients responded to anti-PD-1 or anti-PD-L1 therapy for immunotherapy-naive disease, and three (5·4%) of 56 responded to docetaxel in the second line of therapy. Median overall survival was 5·9 months (95% CI 4·8-7·8) for the targeted therapy groups, 7·7 months (6·7-9·2) for the docetaxel groups, and 10·8 months (9·4-12·3) for the anti-PD-1 or anti-PD-L1-containing groups. Median progression-free survival was 2·5 months (95% CI 1·7-2·8) for the targeted therapy groups, 2·7 months (1·9-2·9) for the docetaxel groups, and 3·0 months (2·7-3·9) for the anti-PD-1 or anti-PD-L1-containing groups.

INTERPRETATION

Lung-MAP (S1400) met its goal to quickly address biomarker-driven therapy questions in squamous non-small-cell lung cancer. In early 2019, a new screening protocol was implemented expanding to all histological types of non-small-cell lung cancer and to add focus on immunotherapy combinations for anti-PD-1 and anti-PD-L1 therapy-relapsed disease. With these changes, Lung-MAP continues to meet its goal to focus on unmet needs in the treatment of advanced lung cancers.

FUNDING

US National Institutes of Health, and AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Genentech, and Pfizer through the Foundation for the National Institutes of Health.

Advanced Squamous Cell Carcinoma of the Lung: Current Treatment Approaches and the Role of Afatinib

Options for the treatment of squamous cell lung carcinoma expanded in recent years with the introduction of the immune checkpoint inhibitors into routine clinical practice in both the first- and second-line settings but are still limited. As a result, pembrolizumab, given either alone or in combination with platinum-based chemotherapy, is now a standard first-line treatment for squamous cell lung cancer. However, few options exist once patients have progressed on immune checkpoint inhibitors and chemotherapy. In this setting, the irreversible ErbB family blocker, afatinib, has a potential role as second or subsequent therapy for some patients. The Phase III LUX-Lung 8 study demonstrated that afatinib significantly prolonged progression-free and overall survival compared with erlotinib in patients with squamous cell lung carcinoma. Notably, retrospective, ad-hoc biomarker analyses of a subset of patients from LUX-Lung 8 suggested that patients with ErbB family mutations derived particular benefit from afatinib, especially those with ErbB2 (HER2) mutations. Afatinib has a manageable and predictable safety profile, and adverse events can be managed with the use of a tolerability-guided dose modification protocol. Until more data are available, afatinib could be considered as a potential second-line treatment option for patients who have progressed on combined pembrolizumab and platinum-based chemotherapy and are ineligible for more established second-line options, or as a third-line option in patients who have received first-line immunotherapy, and second-line chemotherapy or chemotherapy and antiangiogenesis therapy. However, further data are required to support the use of afatinib following immunotherapy. Given that treatment options are limited in both of these settings, investigating an agent with an entirely new mechanism of action is warranted. If available, molecular analysis to identify ErbB family mutations or the use of proteomic profiling could help to further isolate patients who are likely to derive the most benefit from afatinib.

Transcriptomics and solid tumors: The next frontier in precision cancer medicine

Transcriptomics, which encompasses assessments of alternative splicing and alternative polyadenylation, identification of fusion transcripts, explorations of noncoding RNAs, transcript annotation, and discovery of novel transcripts, is a valuable tool for understanding cancer mechanisms and identifying biomarkers. Recent advances in high-throughput technologies have enabled large-scale gene expression profiling. Importantly, RNA expression profiling of tumor tissue has been successfully used to determine clinically actionable molecular alterations. The WINTHER precision medicine clinical trial was the first prospective trial in diverse solid malignancies that assessed both genomics and transcriptomics to match treatments to specific molecular alterations. The use of transcriptome analysis in WINTHER and other trials increased the number of targetable -omic changes compared to genomic profiling alone. Other applications of transcriptomics involve the evaluation of tumor and circulating noncoding RNAs as predictive and prognostic biomarkers, the improvement of risk stratification by the use of prognostic and predictive multigene assays, the identification of fusion transcripts that drive tumors, and an improved understanding of the impact of DNA changes as some genomic alterations are silenced at the RNA level. Finally, RNA sequencing and gene expression analysis have been incorporated into clinical trials to identify markers predicting response to immunotherapy. Many issues regarding the complexity of the analysis, its reproducibility and variability, and the interpretation of the results still need to be addressed. The integration of transcriptomics with genomics, proteomics, epigenetics, and tumor immune profiling will improve biomarker discovery and our understanding of disease mechanisms and, thereby, accelerate the implementation of precision oncology.

Evaluation of Traditional Chinese Medicine Herbs in Oncology Clinical Trials

Despite wide empirical use and demand for traditional Chinese medicine (TCM) herbs worldwide, high-quality clinical trials of TCM herbs in oncology are limited. We developed recommendations for rigorous clinical trials to evaluate their safety and efficacy for oncology patients. To accomplish this goal, the TCM & Cancer Research Committee of the Chinese Pharmaceutical Association convened a working group of oncologists, TCM experts, clinical researchers, biostatisticians, and industry/government representatives to develop principles and approaches for TCM cancer drug clinical trials. They identified 2 categories of herbal drugs based on therapeutic intent: survival improvement and symptom management. The working group also emphasized the need to adopt international standards when appropriate for TCM herbal drug approval and to develop methodology to standardize diagnostic criteria, treatment approaches, and outcome measures according to defining TCM characteristics. These recommendations aim to improve study design and methods to inform rigorous investigation of TCM herbs in patients with cancer.

From the Broad Phase II Trial to Precision Oncology: A Perspective on the Origins of Basket and Umbrella Clinical Trial Designs in Cancer Drug Development

Oncologic phase II trials that evaluate the activity of new therapeutic agents have evolved dramatically over the past 50 years. The standard approach beginning in the late 1960s focused on individual studies that evaluated new anticancer agents against a wide range of both solid and hematopoietic malignancies often in a single "broad phase II trial" that included hundreds of patients; such studies efficiently established the landscape for subsequent development of a specific drug with respect to likely disease focus, toxicity, dose, and schedule. In the 1980s and 1990s, emphasis on histological context drove an explosion in the number of individual phase II trials conducted; despite this increase in trial activity, investigations based on histology per se failed to improve the success rate of new agents brought to the clinic. Over the past 20 years, evolution toward a molecular drug development paradigm has demonstrably improved our ability to select patients more likely to benefit from systemic treatment; simultaneously, technological advances have permitted initial attempts at the rapid assignment of therapy based on predefined molecular characteristics of tumor or germline in broad-based master protocols that are inclusive of many diseases and molecularly characterized disease subsets, akin to but much more sophisticated scientifically than the broad phase II platforms of the past.

Biostatistical and Logistical Considerations in the Development of Basket and Umbrella Clinical Trials

Oncology clinical trials are undergoing transformation to evaluate targeted therapies addressing a wider variety of biologically defined cancer subgroups. Multiarm basket and umbrella trials conducted under master protocols have become more prominent mechanisms for the clinical evaluation of promising new biologically driven anticancer therapies that are integral to precision oncology medicine. These new trial designs permit efficient clinical evaluation of multiple therapies in a variety of histologically and biologically defined cancers. These complex trials require extensive planning and attention to many factors, including choice of biomarker assay platform, mechanism for processing clinicopathologic and biomarker data to assign patients to substudies, and statistical design, monitoring, and analysis of substudies. Trial teams have expanded to include expertise in the interface between biology, clinical oncology, bioinformatics, and statistics. Strategies for the design, conduct, and analysis of these complex trials will continue to evolve to meet new challenges and opportunities in precision oncology medicine.

Molecular subtyping and genomic profiling expand precision medicine in refractory metastatic triple-negative breast cancer: the FUTURE trial

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease, and molecular subtyping may result in improved diagnostic precision and targeted therapies. Our previous study classified TNBCs into four subtypes with putative therapeutic targets. Here, we conducted the FUTURE trial (ClinicalTrials.gov identifier: NCT03805399), a phase Ib/II subtyping-based and genomic biomarker-guided umbrella trial, to evaluate the efficacy of these targets. Patients with refractory metastatic TNBC were enrolled and stratified by TNBC subtypes and genomic biomarkers, and assigned to one of these seven arms: (A) pyrotinib with capecitabine, (B) androgen receptor inhibitor with CDK4/6 inhibitor, (C) anti PD-1 with nab-paclitaxel, (D) PARP inhibitor included, (E) and (F) anti-VEGFR included, or (G) mTOR inhibitor with nab-paclitaxel. The primary end point was the objective response rate (ORR). We enrolled 69 refractory metastatic TNBC patients with a median of three previous lines of therapy (range, 1–8). Objective response was achieved in 20 (29.0%, 95% confidence interval (CI): 18.7%–41.2%) of the 69 intention-to-treat (ITT) patients. Our results showed that immunotherapy (arm C), in particular, achieved the highest ORR (52.6%, 95% CI: 28.9%–75.6%) in the ITT population. Arm E demonstrated favorable ORR (26.1%, 95% CI: 10.2%–48.4% in the ITT population) but with more high grade (≥ 3) adverse events. Somatic mutations of TOP2A and CD8 immunohistochemical score may have the potential to predict immunotherapy response in the immunomodulatory subtype of TNBC. In conclusion, the phase Ib/II FUTURE trial suggested a new concept for TNBC treatment, demonstrating the clinical benefit of subtyping-based targeted therapy for refractory metastatic TNBC.

Future Approaches to Precision Oncology-Based Clinical Trials

The last 2 decades have seen a rapid advance of the precision oncology paradigm-from its early singular successes to becoming the prevailing model of cancer therapy. As the treatment of cancer moves away from traditional chemotherapy, so too will oncology clinical trials have to move away from the traditional model of phase I to phase III progression of drug development. Achieving this goal of individualized care will involve a concerted effort by the entire cancer care community to fundamentally change the design and implementation of oncology clinical trials. We envision that the next 2 decades will be a period of evolution in precision oncology clinical trials through scientific and technologic advances, transformation of clinical trial infrastructure, and changes in the kind of evidence required for regulatory approval.