Value-based genomics

Molecular classification of endometrial cancers (EC) and association with relapse-free survival (RFS) and overall survival (OS) outcomes: Ancillary analysis of GOG-0258

PURPOSE

Determine if molecular classification using mismatch repair (MMR) and p53 protein expression predicts recurrence-free survival (RFS) and overall survival (OS) in endometrial cancer (EC) patients treated with chemotherapy and radiation (CRT) versus chemotherapy (CT).

METHODS

GOG-0258, a phase III randomized trial (NCT00942357), compared CRT to CT. Immunohistochemistry assessed MMR and p53 status. Kaplan-Meier curves and adjusted Cox models analyzed survival outcomes by molecular subtype.

RESULTS

ECs classified as deficient MMR (dMMR) (27 %), p53 abnormal (p53abn) (24 %), and p53 wild type (p53wt) (49 %). p53abn were more frequent in patients that were older, Black, and had serous histology (p < 0.001). Median follow up was 113 months. Five-year RFS and OS were worse with p53abn (29 % [Hazard Ratio (HR) = 3.39 (95 % Confidence Interval (CI): 2.34-4.91)] and 39 % [HR = 4.64 (95 % CI: 3.16-6.79)] compared to those with p53wt (referent) (p < 0.001). The five-year RFS and OS for dMMR cancers were (58 % [HR = 1.30 (95 % CI: 0.85-1.97)] and 77 % [HR = 1.53 (95 % CI: 0.99-2.36)] compared to those with p53wt (69 % and 85 %). After adjusting for age, gross residual disease, and treatment, p53wt improved RFS with CRT compared to CT in an exploratory analysis (77 % vs 60 %; HR = 0.54 (95 % CI: 0.32-0.94). The 5-year and 10-year OS rates were similar in CRT compared to CT in all subgroups.

CONCLUSION

Molecular classification appears to be predictive and prognostic, with worse survival in those with p53abn tumors. In an exploratory analysis, p53wt appears to predict improved RFS, favoring CRT over CT. There was no difference in treatment efficacy based on molecular subtype for OS.

Physiological markers for immunotherapeutics: a review

Immunotherapy has been advanced through multiple approaches, including immunogenic cytokines, monoclonal antibodies, therapeutic vaccinations, adoptive cell transfer, stem cell transplantation, and oncolytic viruses. This review analyses various strategies in genomics, transcriptomics, single-cell techniques, computational analysis, big data, and imaging technologies for the identification of tumour microbiota and microenvironments. Immunotherapy is becoming acknowledged as a feasible cancer treatment method, facilitating innovative cancer medicines and personalized medicine techniques.

Development of a microcosting protocol to determine the economic cost of diagnostic genomic testing for rare diseases in Australia

INTRODUCTION

Genomic testing is a relatively new, disruptive and complex health technology with multiple clinical applications in rare diseases, cancer and infection control. Genomic testing is increasingly being implemented into clinical practice, following regulatory approval, funding and adoption in models of care, particularly in the area of rare disease diagnosis. A significant barrier to the adoption and implementation of genomic testing is funding. What remains unclear is what the cost of genomic testing is, what the underlying drivers of cost are and whether policy differences contribute to cost variance in different jurisdictions, such as the requirement to have staff with a medical license involved in testing. This costing study will be useful in future economic evaluations and health technology assessments to inform optimal levels of reimbursement and to support comprehensive and comparable assessment of healthcare resource utilisation in the delivery of genomic testing globally.

METHODS

A framework is presented that focuses on uncovering the process of genomic testing for any given laboratory, evaluating its utilisation and unit costs, and modelling the cost drivers and overall expenses associated with delivering genomic testing. The goal is to aid in refining and implementing policies regarding both the regulation and funding of genomic testing. A process-focused (activity-based) methodology is outlined, which encompasses resources, assesses individual cost components through a combination of bottom-up and top-down microcosting techniques and allows disaggregation of resource type and process step.

ETHICS AND DISSEMINATION

The outputs of the study will be reported at relevant regional genetics and health economics conferences, as well as submitted to a peer-reviewed journal focusing on genomics. Human research ethics committee approval is not required for this microcosting study. This study does not involve research on human subjects, and all data used in the analysis are either publicly available.

Analytic validation of NeXT Dx™, a comprehensive genomic profiling assay

We describe the analytic validation of NeXT Dx, a comprehensive genomic profiling assay to aid therapy and clinical trial selection for patients diagnosed with solid tumor cancers. Proprietary methods were utilized to perform whole exome and whole transcriptome sequencing for detection of single nucleotide variants (SNVs), insertions/deletions (indels), copy number alterations (CNAs), and gene fusions, and determination of tumor mutation burden and microsatellite instability. Variant calling is enhanced by sequencing a patient-specific normal sample from, for example, a blood specimen. This provides highly accurate somatic variant calls as well as the incidental reporting of pathogenic and likely pathogenic germline alterations. Fusion detection via RNA sequencing provides more extensive and accurate fusion calling compared to DNA-based tests. NeXT Dx features the proprietary Accuracy and Content Enhanced technology, developed to optimize sequencing and provide more uniform coverage across the exome. The exome was validated at a median sequencing depth of >500x. While variants from 401 cancer-associated genes are currently reported from the assay, the exome/transcriptome assay is broadly validated to enable reporting of additional variants as they become clinically relevant. NeXT Dx demonstrated analytic sensitivities as follows: SNVs (99.4%), indels (98.2%), CNAs (98.0%), and fusions (95.8%). The overall analytic specificity was >99.0%.

A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma

BACKGROUND

Although sentinel lymph node biopsy (SLNB) status is a strong prognostic indicator for cutaneous melanoma, unnecessary SLNBs have substantial cost and morbidity burden.

OBJECTIVE

This study was designed to develop, validate, and present a personalized, clinical, decision-making tool using nationally representative data with clinically actionable probability thresholds (Expected Lymphatic Metastasis Outcome [ELMO]).

METHODS

Data from the Surveillance, Epidemiology, and End Results (SEER) Registry from 2000 to 2017 and the National Cancer Database (NCDB) from 2004 to 2015 were used to develop and internally validate a logistic ridge regression predictive model for SLNB positivity. External validation was done with 1568 patients at a large tertiary referral center.

RESULTS

The development cohort included 134,809 patients, and the internal validation cohort included 38,518 patients. ELMO (AUC 0.85) resulted in a 29.54% SLNB reduction rate and greater sensitivity in predicting SLNB status for T1b, T2a, and T2b tumors than previous models. In external validation, ELMO had an accuracy of 0.7586 and AUC of 0.7218. Limitations of this study are potential miscoding, unaccounted confounders, and effect modification.

CONCLUSIONS

ELMO ( https://melanoma-sentinel.herokuapp.com/ ) has been developed and validated (internally and externally) by using the largest publicly available dataset of melanoma patients and was found to have high accuracy compared with other published models and gene expression tests. Individualized risk estimates for SLNB positivity are critical in facilitating thorough decision-making for healthcare providers and patients with melanoma.

Pyramidal Decision Support Framework Leverages Subspecialty Expertise across Enterprise to Achieve Superior Cancer Outcomes and Personalized, Precision Care Plans

The complexity of cancer care requires integrated and continuous support to deliver appropriate care. An expert network with complementary expertise and the capability of multidisciplinary care is an integral part of contemporary oncology care. Appropriate infrastructure is necessary to empower this network to deliver personalized precision care to their patients. Providing decision support as cancer care becomes exponentially more complex with new diagnostic and therapeutic choices remains challenging. City of Hope has developed a Pyramidal Decision Support Framework to address these challenges, which were exacerbated by the COVID pandemic, health plan restrictions, and growing geographic site diversity. Optimizing efficient and targeted decision support backed by multidisciplinary cancer expertise can improve individual patient treatment plans to achieve improved care and survival wherever patients are treated.

Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean

Metabolome is the end point of the genome-environment interplay, and enables an important holistic overview of individual adaptability and host responses to environmental, ecological, as well as endogenous changes such as disease. Pharmacometabolomics is the application of metabolome knowledge to decipher the mechanisms of interindividual and intraindividual variations in drug efficacy and safety. Pharmacometabolomics also contributes to prediction of drug treatment outcomes on the basis of baseline (predose) and postdose metabotypes through mathematical modeling. Thus, pharmacometabolomics is a strong asset for a diverse community of stakeholders interested in theory and practice of evidence-based and precision/personalized medicine: academic researchers, public health scholars, health professionals, pharmaceutical, diagnostics, and biotechnology industries, among others. In this expert review, we discuss pharmacometabolomics in four contexts: (1) an interdisciplinary omics tool and field to map the mechanisms and scale of interindividual variability in drug effects, (2) discovery and development of translational biomarkers, (3) advance digital biomarkers, and (4) empower drug repurposing, a field that is increasingly proving useful in the current era of Covid-19. As the applications of pharmacometabolomics are growing rapidly in the current postgenome era, next-generation proteomics and metabolomics follow the example of next-generation sequencing analyses. Pharmacometabolomics can also empower data reliability and reproducibility through multiomics integration strategies, which use each data layer to correct, connect with, and inform each other. Finally, we underscore here that contextual data remain crucial for precision medicine and drug development that stand the test of time and clinical relevance.

Utilisation of semiconductor sequencing for detection of actionable fusions in solid tumours

Oncogenic fusions represent compelling druggable targets in solid tumours highlighted by the recent site agnostic FDA approval of larotrectinib for NTRK rearrangements. However screening for fusions in routinely processed tissue samples is constrained due to degradation of nucleic acid as a result of formalin fixation., To investigate the clinical utility of semiconductor sequencing optimised for detection of actionable fusion transcripts in formalin fixed samples, we have undertaken an analysis of test trending data generated by a clinically validated next generation sequencing platform designed to capture 867 of the most clinically relevant druggable driver-partner oncogenic fusions. Here we show across a real-life cohort of 1112 patients with solid tumours that actionable fusions occur at high frequency (7.4%) with linkage to a wide range of targeted therapy protocols including seven fusion-drug matches with FDA/EMA approval and/or NCCN/ESMO recommendations and 80 clinical trials. The more prevalent actionable fusions identified were independent of tumour type in keeping with signalling via evolutionary conserved RAS/RAF/MEK/ERK, PI3K/AKT/MTOR, PLCy/PKC and JAK/STAT pathways. Taken together our data indicates that semiconductor sequencing for detection of actionable fusions can be integrated into routine diagnostic pathology workflows enabling the identification of personalised treatment options that have potential to improve clinical cancer management across many tumour types.

Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers

The utility of cancer whole genome and transcriptome sequencing (cWGTS) in oncology is increasingly recognized. However, implementation of cWGTS is challenged by the need to deliver results within clinically relevant timeframes, concerns about assay sensitivity, reporting and prioritization of findings. In a prospective research study we develop a workflow that reports comprehensive cWGTS results in 9 days. Comparison of cWGTS to diagnostic panel assays demonstrates the potential of cWGTS to capture all clinically reported mutations with comparable sensitivity in a single workflow. Benchmarking identifies a minimum of 80× as optimal depth for clinical WGS sequencing. Integration of germline, somatic DNA and RNA-seq data enable data-driven variant prioritization and reporting, with oncogenic findings reported in 54% more patients than standard of care. These results establish key technical considerations for the implementation of cWGTS as an integrated test in clinical oncology.

Cancer whole-genome and transcriptome sequencing (cWGTS) has been challenging to implement in clinical settings. Here, the authors develop a workflow to deliver robust cWGTS analyses and reports within clinically-relevant timeframes for paediatric, adolescent and young adult solid tumour patients.

Cost-effectiveness analysis of tumor molecular classification in high-risk early-stage endometrial cancer

PURPOSE

Tumor molecular analyses in endometrial cancer (EC) includes 4 distinct subtypes: (1) POLE-mutated, (2) mismatch repair protein (MMR) deficient, (3) p53 mutant, and (4) no specific molecular profile. Recently, a sub-analysis of PORTEC-3 demonstrated notable differences in treatment response between molecular classification (MC) groups. Cost of testing is one barrier to widespread adoption of MC. Therefore, we sought to determine the cost-effectiveness of MC in patients with stage I and II high-risk EC.

METHODS

A Markov decision model was developed to compare tumor molecular classification (TMC) vs. no testing (NT). A healthcare payor's perspective and 5-year time horizon were used. Base case data were abstracted from PORTEC-3 and the molecular sub-analysis. Cost and utility data were derived from public databases, peer-reviewed literature, and expert input. Strategies were compared using the incremental cost-effectiveness ratio (ICER) with effectiveness in quality-adjusted life years (QALYs) and evaluated with a willingness-to-pay threshold of $100,000 per QALY gained. Sensitivity analyses were performed to test model robustness.

RESULTS

When compared to NT, TMC was cost effective with an ICER of $25,578 per QALY gained; incremental cost was $1780 and incremental effectiveness was 0.070 QALYs. In one-way sensitivity analyses, results were most sensitive to the cost of POLE testing, but TMC remained cost-effective over all parameter ranges.

CONCLUSIONS

TMC in early-stage high-risk EC is cost-effective, and the model results were robust over a range of parameters. Given that MC can be used to guide adjuvant treatment decisions, these findings support adoption of TMC into routine practice.

Clinical Utility of Olaparib in the Treatment of Metastatic Castration-Resistant Prostate Cancer: A Review of Current Evidence and Patient Selection

Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive and fatal disease with a median survival of 36 months. With the advent of genetic sequencing to identify individual genomic profiles and acquired tumor-specific pathways, targeted therapies have revolutionized cancer treatment, including the treatment strategy in mCRPC. Poly(adenosine 5'-diphosphate) ribose polymerase inhibitors (PARPi) are oral drugs that target mutations in the homologous recombination repair (HRR) pathway, which are found in approximately 27% of prostate cancer patients. In May 2020, the first PARP inhibitor, olaparib, was approved by the US Food and Drug Administration for men with mCRPC with HHR gene mutations based on the findings of the Phase III PROfound trial that showed improved overall survival in men with mCRPC who received olaparib and whose disease had progressed on a novel hormonal agent. This review summarizes the current evidence and clinical utility of olaparib as treatment in men with mCRPC. We describe the mechanism of action of PARPi, key clinical trials of olaparib in men with mCRPC, and ongoing Phase II and III clinical trials investigating olaparib in combination therapy and as front-line therapy in mCRPC.

Whole genome sequencing in oncology: using scenario drafting to explore future developments

Background

In oncology, Whole Genome Sequencing (WGS) is not yet widely implemented due to uncertainties such as the required infrastructure and expertise, costs and reimbursements, and unknown pan-cancer clinical utility. Therefore, this study aimed to investigate possible future developments facilitating or impeding the use of WGS as a molecular diagnostic in oncology through scenario drafting.

Methods

A four-step process was adopted for scenario drafting. First, the literature was searched for barriers and facilitators related to the implementation of WGS. Second, they were prioritized by international experts, and third, combined into coherent scenarios. Fourth, the scenarios were implemented in an online survey and their likelihood of taking place within 5 years was elicited from another group of experts. Based on the minimum, maximum, and most likely (mode) parameters, individual Program Evaluation and Review Technique (PERT) probability density functions were determined. Subsequently, individual opinions were aggregated by performing unweighted linear pooling, from which summary statistics were extracted and reported.

Results

Sixty-two unique barriers and facilitators were extracted from 70 articles. Price, clinical utility, and turnaround time of WGS were ranked as the most important aspects. Nine scenarios were developed and scored on likelihood by 18 experts. The scenario about introducing WGS as a clinical diagnostic with a lower price, shorter turnaround time, and improved degree of actionability, scored the highest likelihood (median: 68.3%). Scenarios with low likelihoods and strong consensus were about better treatment responses to more actionable targets (26.1%), and the effect of centralizing WGS (24.1%).

Conclusions

Based on current expert opinions, the implementation of WGS as a clinical diagnostic in oncology is heavily dependent on the price, clinical utility (both in terms of identifying actionable targets as in adding sufficient value in subsequent treatment), and turnaround time. These aspects and the optimal way of service provision are the main drivers for the implementation of WGS and should be focused on in further research. More knowledge regarding these factors is needed to inform strategic decision making regarding the implementation of WGS, which warrants support from all relevant stakeholders.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08214-8.

Analytic validation and clinical utilization of the comprehensive genomic profiling test, GEM ExTra®

We developed and analytically validated a comprehensive genomic profiling (CGP) assay, GEM ExTra, for patients with advanced solid tumors that uses Next Generation Sequencing (NGS) to characterize whole exomes employing a paired tumor-normal subtraction methodology. The assay detects single nucleotide variants (SNV), indels, focal copy number alterations (CNA), TERT promoter region, as well as tumor mutation burden (TMB) and microsatellite instability (MSI) status. Additionally, the assay incorporates whole transcriptome sequencing of the tumor sample that allows for the detection of gene fusions and select special transcripts, including AR-V7, EGFR vIII, EGFRvIV, and MET exon 14 skipping events. The assay has a mean target coverage of 180X for the normal (germline) and 400X for tumor DNA including enhanced probe design to facilitate the sequencing of difficult regions. Proprietary bioinformatics, paired with comprehensive clinical curation results in reporting that defines clinically actionable, FDA-approved, and clinical trial drug options for the management of the patient's cancer. GEM ExTra demonstrated analytic specificity (PPV) of > 99.9% and analytic sensitivity of 98.8%. Application of GEM ExTra to 1,435 patient samples revealed clinically actionable alterations in 83.9% of reports, including 31 (2.5%) where therapeutic recommendations were based on RNA fusion findings only.

Cost-Effectiveness of Genomic Test-Directed Olaparib for Metastatic Castration-Resistant Prostate Cancer

Purpose: The effectiveness of poly (adenosine diphosphate–ribose) polymerase (PARP) inhibitor olaparib for metastatic castration-resistant prostate cancer (MCRPC) with multiple loss-of-function alterations in genes that are involved in DNA repair has been demonstrated. We aimed to evaluate the cost-effectiveness of genomic test-directed olaparib on MCRPC from the US payer perspective.

Methods: A partitioned survival model was adopted to project the disease course of MCRPC had at least one gene alteration in BRCA1, BRCA2 and ATM (Scenario A) and has alterations in any of all 15 prespecified genes (Scenario B) after next-generation sequencing test. The efficacy and toxicity data were gathered from the PROfound trial. Clinical probabilities related to survival were estimated from the reported survival probabilities in each PROfound group. Cost and health preference data were derived from the literature. The incremental cost-effectiveness ratio (ICER) was measured. Subgroup analysis and sensitivity analysis were performed for exploring the model uncertainties.

Results: Olaparib yielded an additional 0.063 and 0.068 of quality-adjusted life year (QALY) with the augmented cost of $7,382 and saved the cost of $ 1,980 compared to standard care in scenario A and B, respectively, which yielded an ICER of $116,903/QALY and a cost-saving option. The lower weekly cost related to olaparib treatment led to the dominant findings in scenario B. The varied results between scenario A and B could be partly explained by different the number need to screen for identifying eligible patients who could be administered with olaparib, which sharply augmented the costs of the olaparib arm in scenario A. Subgroup analysis and sensitivity analysis revealed the results were generally robust in both of two scenarios.

Conclusion: The genomic test-directed olaparib is a preferred option compared with standard care strategy for men with MCRPC who had any of all 15 prespecified genes.

Biomarker Discovery and Outcomes for Comprehensive Cell-Free Circulating Tumor DNA Versus Standard-of-Care Tissue Testing in Advanced Non–Small-Cell Lung Cancer

Purpose

Treatment guidelines for advanced non–small-cell lung cancer (aNSCLC) recommend broad molecular profiling for targeted therapy selection. This study prospectively assessed comprehensive next-generation sequencing (NGS) of cell-free circulating tumor DNA (cfDNA) compared with standard-of-care (SOC) tissue-based testing to identify guideline-recommended alterations in aNSCLC.

PATIENTS AND METHODS

Patients with treatment-naïve aNSCLC were tested using a well-validated NGS cfDNA panel, and results were compared with SOC tissue testing. The primary objective was noninferiority of cfDNA vs. tissue analysis for the detection of two guideline-recommended biomarkers ( EGFR and ALK) and an additional six actionable biomarkers. Secondary analyses included tissue versus cfDNA biomarker discovery, overall response rate (ORR), progression-free survival (PFS) to targeted therapy, and positive predictive value (PPV) of cfDNA.

RESULTS

The primary objective was met with cfDNA identifying actionable mutations in 46 patients versus 48 by tissue ( P < .05). In total, 0/186 patients were genotyped for all eight biomarkers with tissue, compared with 90.8% using cfDNA. Targetable alterations or KRAS were identified in 80.7% when cfDNA was used first versus 57.1% when tissue was used first. PPV for cfDNA-detected EGFR was 100.0% (25/25). ORR and PFS in patients receiving targeted therapy based on tissue or cfDNA were similar to those previously reported.

Conclusion

This prospective study confirms a previous report that comprehensive cfDNA testing is noninferior to SOC tissue testing in detecting aNSCLC-recommended biomarkers. Furthermore, cfDNA-based first-line therapy produced outcomes similar to tissue-based testing, demonstrating the clinical utility of comprehensive cfDNA genotyping as the initial genotyping modality in patients with treatment-naïve aNSCLC when tissue is insufficient or when all actionable biomarkers cannot be rapidly assessed.

Budget impact of capmatinib for adults with metastatic non-small cell lung cancer harboring a MET exon 14 skipping mutation in the United States

AIMS

To estimate the budget impact of adding capmatinib, the first FDA approved MET inhibitor, to a US commercial or Medicare health plan for patients with metastatic non-small cell lung cancer (mNSCLC) whose tumors have a mutation that leads to MET exon 14 (METex14) skipping.

METHODS

Target population size was estimated using published epidemiology data. Clinical data were obtained from the GEOMETRY mono-1 capmatinib trial and published trials. Treatments in the market mix included crizotinib, pembrolizumab, ramucirumab, and chemotherapy. Uptake of capmatinib and testing rates were based on market research. All costs (drug acquisition and administration, pre-progression, progression, terminal care, adverse event, and testing) were estimated based on public sources (2020 USD).

RESULTS

The number of patients eligible for capmatinib in the first three years was estimated to be 2-3 in a hypothetical 1 million member commercial plan and 34-44 in a hypothetical 1 million member Medicare plan each year. The estimated total budget impact ranged from $9,695 to $67,725 for a commercial plan and $141,350 to $985,695 for Medicare. With capmatinib included, a marginal per member per month budget impact was estimated (commercial: $0.0008 to $0.0056; Medicare: $0.0118 to $0.0821). Capmatinib inclusion resulted in lower medical costs (commercial: -$0.0003 to -$0.0007; Medicare: -$0.0037 to -$0.0106), partially offsetting increased drug costs ($0.0011 to $0.0064; $0.0154 to $0.0928, respectively), and were primarily driven by reductions in progression and terminal care costs (-$0.0003 to -$0.0009; -$0.0037 to -$0.0125, respectively). The results were most sensitive to capmatinib market share, capmatinib price, and treatment duration.

LIMITATIONS

Certain assumptions were applied to the model to account for inputs with limited evidence.

CONCLUSIONS

The estimated budget impact of including capmatinib for mNSCLC with a METex14 skipping mutation is minimal, and the increased drug costs were partially offset by savings in AEs, and progression-related and terminal care costs.

The future of genomics in Ireland - focus on genomics for health

Genomics is revolutionizing biomedical research, medicine and healthcare globally in academic, public and industry sectors alike. Concrete examples around the world show that huge benefits for patients, society and economy can be accrued through effective and responsible genomic research and clinical applications. Unfortunately, Ireland has fallen behind and needs to act now in order to catch up. Here, we identify key issues that have resulted in Ireland lagging behind, describe how genomics can benefit Ireland and its people and outline the measures needed to make genomics work for Ireland and Irish patients. There is now an urgent need for a national genomics strategy that enables an effective, collaborative, responsible, well-regulated, and patient centred environment where genome research and clinical genomics can thrive.  We present eight recommendations that could be the pillars of a national genomics health strategy.

Evaluation of Omics-Based Strategies for the Management of Advanced Lung Cancer

PURPOSE

Omic-informed therapy is being used more frequently for patients with non-small-cell lung cancer (NSCLC) being treated on the basis of evidence-based decision-making. However, there is a lack of a standardized framework to evaluate those decisions and understand the association between omics-based management strategies and survival among patients. Therefore, we compared outcomes between patients with lung adenocarcinoma who received omics-driven targeted therapy versus patients who received standard therapeutic options.

PATIENTS AND METHODS

This was a retrospective study of patients with advanced NSCLC adenocarcinoma (N = 798) at City of Hope who received genomic sequencing at the behest of their treating oncologists. A thoracic oncology registry was used as a clinicogenomic database to track patient outcomes.

RESULTS

Of 798 individuals with advanced NSCLC (median age, 65 years [range, 22-99 years]; 60% white; 50% with a history of smoking), 662 patients (83%) had molecular testing and 439 (55%) received targeted therapy on the basis of the omic-data. A fast-and-frugal decision tree (FFT) model was developed to evaluate the impact of omics-based strategy on decision-making, progression-free survival (PFS), and overall survival (OS). We calculated that the overall positive predictive value of the entire FFT strategy for predicting decisions regarding the use of tyrosine kinase inhibitor-based targeted therapy was 88% and the negative predictive value was 96%. In an adjusted Cox regression analysis, there was a significant correlation with survival benefit with the FFT omics-driven therapeutic strategy for both PFS (hazard ratio [HR], 0.56; 95% CI, 0.42 to 0.74; P < .001) and OS (HR, 0.51; 95% CI, 0.36 to 0.71; P < .001) as compared with standard therapeutic options.

CONCLUSION

Among patients with advanced NSCLC who received care in the academic oncology setting, omics-driven therapy decisions directly informed treatment in patients and was correlated with better OS and PFS.

Non-Small Cell Lung Cancer from Genomics to Therapeutics: A Framework for Community Practice Integration to Arrive at Personalized Therapy Strategies

Non-small cell lung cancer (NSCLC) is a heterogeneous disease, and therapeutic management has advanced with the identification of various key oncogenic mutations that promote lung cancer tumorigenesis. Subsequent studies have developed targeted therapies against these oncogenes in the hope of personalizing therapy based on the molecular genomics of the tumor. This review presents approved treatments against actionable mutations in NSCLC as well as promising targets and therapies. We also discuss the current status of molecular testing practices in community oncology sites that would help to direct oncologists in lung cancer decision-making. We propose a collaborative framework between community practice and academic sites that can help improve the utilization of personalized strategies in the community, through incorporation of increased testing rates, virtual molecular tumor boards, vendor-based oncology clinical pathways, and an academic-type singular electronic health record system.

Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small-Cell Lung Cancer

Introduction

Tumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment.

Objective

Here we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase III clinical trial.

Methods

In the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small-cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne^® CDx assay.

Results

TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90).

Conclusions

Parameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.

TMB: a promising immune-response biomarker, and potential spearhead in advancing targeted therapy trials

Immune checkpoint inhibition (ICI) has revolutionized cancer treatment, and produced durable responses in many cancer types. However, there remains a subset of patients that do not respond despite their tumors exhibiting PD-L1 expression, which highlights the need for additional biomarkers relevant to response. Here, we review checkpoint inhibitor signal pathways, resistance and sensitivity mechanisms, as well as response rates. We also investigate the correlation and response to ICI with BRCA1/2 mutation status and homologous recombination deficient tumors. Collectively we show that the use of tumor mutational burden may be effective as an emerging biomarker.

Homologous Recombination Repair Truncations Predict Hypermutation in Microsatellite Stable Colorectal and Endometrial Tumors

INTRODUCTION

Somatic mutations in BRCA1/2 and other homologous recombination repair (HRR) genes have been associated with sensitivity to PARP inhibitors and/or platinum agents in several cancers, whereas hypermutant tumors caused by alterations in POLE or mismatch repair genes have demonstrated robust responses to immunotherapy. We investigated the relationship between somatic truncations in HRR genes and hypermutation in colorectal cancer (CRC) and endometrial cancer (EC).

METHODS

We analyzed the mutational spectra associated with somatic BRCA1/2 truncations in multiple genomic cohorts (N = 2,335). From these results, we devised a classifier incorporating HRR genes to predict hypermutator status among microsatellite stable (MSS) tumors. Using additional genomic cohorts (N = 1,439) and functional in vivo assays, we tested the classifier to disambiguate POLE variants of unknown significance and identify MSS hypermutators without somatic POLE exonuclease domain mutations.

RESULTS

Hypermutator phenotypes were prevalent among CRCs with somatic BRCA1/2 truncations (50/62, 80.6%) and ECs with such mutations (44/47, 93.6%). The classifier predicted MSS hypermutators with a cumulative true-positive rate of 100% in CRC and 98.0% in EC and a false-positive rate of 0.07% and 0.63%. Validated by signature analyses of tumor exomes and in vivo assays, the classifier accurately reassigned multiple POLE variants of unknown significance as pathogenic and identified MSS hypermutant samples without POLE exonuclease domain mutations.

DISCUSSION

Somatic truncations in HRR can accurately fingerprint MSS hypermutators with or without known pathogenic exonuclease domain mutations in POLE and may serve as a low-cost biomarker for immunotherapy decisions in MSS CRC and EC.

The efficacy of DNA mismatch repair enzyme immunohistochemistry as a screening test for hypermutated gliomas

A subset of gliomas has DNA repair defects that lead to hypermutated genomes. While such tumors are resistant to alkylating chemotherapies, they may also express more mutant neoantigens on their cell surfaces, and thus be more responsive to immunotherapies. A fast, inexpensive method of screening for hypermutated gliomas would therefore be of great clinical value. Since immunohistochemistry (IHC) for the DNA mismatch repair (MMR) proteins Msh2, Msh6, Mlh1, and Pms2 is already used to screen for hypermutated colorectal cancers, we sought to determine whether that panel might have similar utility in gliomas. MMR IHC was scored in 100 WHO grade I-IV gliomas (from 96 patients) with known tumor mutation burden (TMB), while blinded to TMB data. Cases included 70 grade IV GBMs, 13 grade III astrocytomas, 4 grade II astrocytomas (3 diffuse astrocytomas and 1 pleomorphic xanthoastrocytoma), 1 grade I pilocytic astrocytoma, 2 grade III oligodendrogliomas, 7 grade II oligodendrogliomas, and 3 grade I glioneuronal tumors. Eight of 100 tumors showed loss of one or more MMR proteins by IHC, and all 8 were hypermutated. Among the remaining 92 gliomas with intact MMR IHC, only one was hypermutated; that tumor had an inactivating mutation in another DNA repair gene, ATM. Overall accuracy, sensitivity, and specificity for DNA MMR IHC compared to the gold standard of TMB were 99, 89, and 100%, respectively. The strongest correlates with hypermutation were prior TMZ treatment, MGMT promoter methylation, and IDH1 mutation. Among the 8 MMR-deficient hypermutated gliomas, 4 (50%) contained both MMR-lost and MMR-retained tumor cells. Together, these data suggest that MMR IHC could be a viable front-line screening test for gliomas in which immunotherapy is being considered. They also suggest that not all cells in a hypermutated glioma may actually be MMR-deficient, a finding that might need to be considered when treating such tumors with immunotherapies.

Precision medicine and actionable alterations in lung cancer: A single institution experience

OBJECTIVES

Oncology has become more reliant on new testing methods and a greater use of electronic medical records, which provide a plethora of information available to physicians and researchers. However, to take advantage of vital clinical and research data for precision medicine, we must initially make an effort to create an infrastructure for the collection, storage, and utilization of this information with uniquely designed disease-specific registries that could support the collection of a large number of patients.

MATERIALS AND METHODS

In this study, we perform an in-depth analysis of a series of lung adenocarcinoma patients (n = 415) with genomic and clinical data in a recently created thoracic patient registry.

RESULTS

Of the 415 patients with lung adenocarcinoma, 59% (n = 245) were female; the median age was 64 (range, 22-92) years with a median OS of 33.29 months (95% CI, 29.77-39.48). The most common actionable alterations were identified in EGFR (n = 177/415 [42.7%]), ALK (n = 28/377 [7.4%]), and BRAF V600E (n = 7/288 [2.4%]). There was also a discernible difference in survival for 222 patients, who had an actionable alteration, with a median OS of 39.8 months as compared to 193 wild-type patients with a median OS of 26.0 months (P<0.001). We identified an unprecedented number of actionable alterations [53.5% (222/415)], including distinct individual alteration rates, as compared with 15.0% and 22.3% in TCGA and GENIE respectively.

CONCLUSION

The use of patient registries, focused genomic panels and the appropriate use of clinical guidelines in community and academic settings may influence cohort selection for clinical trials and improve survival outcomes.

Assessment of Tumor Mutational Burden in Pediatric Tumors by Real-Life Whole-Exome Sequencing and In Silico Simulation of Targeted Gene Panels: How the Choice of Method Could Affect the Clinical Decision?

Background: Tumor mutational burden (TMB) is an emerging genomic biomarker in cancer that has been associated with improved response to immune checkpoint inhibitors (ICIs) in adult cancers. It was described that variability in TMB assessment is introduced by different laboratory techniques and various settings of bioinformatic pipelines. In pediatric oncology, no study has been published describing this variability so far. Methods: In our study, we performed whole exome sequencing (WES, both germline and somatic) and calculated TMB in 106 patients with high-risk/recurrent pediatric solid tumors of 28 distinct cancer types. Subsequently, we used WES data for TMB calculation using an in silico approach simulating two The Food and Drug Administration (FDA)-approved/authorized comprehensive genomic panels for cancer. Results: We describe a strong correlation between WES-based and panel-based TMBs; however, we show that this high correlation is significantly affected by inclusion of only a few hypermutated cases. In the series of nine cases, we determined TMB in two sequentially collected tumor tissue specimens and observed an increase in TMB along with tumor progression. Furthermore, we evaluated the extent to which potential ICI indication could be affected by variability in techniques and bioinformatic pipelines used for TMB assessment. We confirmed that this technological variability could significantly affect ICI indication in pediatric cancer patients; however, this significance decreases with the increasing cut-off values. Conclusions: For the first time in pediatric oncology, we assessed the reliability of TMB estimation across multiple pediatric cancer types using real-life WES and in silico analysis of two major targeted gene panels and confirmed a significant technological variability to be introduced by different laboratory techniques and various settings of bioinformatic pipelines.

Genomic Profiling for KRAS, NRAS, BRAF, Microsatellite Instability, and Mismatch Repair Deficiency Among Patients With Metastatic Colon Cancer

PURPOSE

Genomic testing is recognized in national guidelines as essential to guide appropriate therapy selection in metastatic colorectal cancer. Previous studies report adherence to testing guidelines is suboptimal, but current testing rates have not been assessed. This study reports testing rates in metastatic colon cancer (mCC) for guideline-recommended biomarkers in a US-based population.

MATERIALS AND METHODS

A retrospective review of data extracted from electronic medical records was performed to identify patients with pathologically confirmed mCC and describe patterns of guideline-aligned biomarker testing. Data were extracted from the electronic health records of 1,497 patients treated at 23 practices across the United States. Both community and academic centers were represented.

RESULTS

A total of 1,497 patients with mCC diagnosed between January 1, 2013 and December 31, 2017 were identified. Guideline-aligned biomarker testing rates for RAS, BRAF, and microsatellite instability/mismatch repair deficiency over this study period were 41%, 43%, and 51%, respectively. Patients were more likely to have guideline-aligned testing for RAS and BRAF if they were treated at an academic center, were diagnosed with de novo metastatic disease, and were female. In addition, patients < 65 years of age were more likely to have guideline-aligned RAS testing. Of the 177 patients (12% of cohort) who received anti-epidermal growth factor receptor therapy, only 50 (28%) had complete guideline-aligned biomarker testing.

CONCLUSION

Despite guideline recommendations and significant therapeutic implications, overall biomarker testing rates in mCC remain suboptimal. Adherence to guideline-recommended biomarker testing would potentially reduce exposure to expensive and ineffective therapies, resulting in improved patient outcomes.

Integrated genomic profiling expands clinical options for patients with cancer

Genomic analysis of paired tumor-normal samples and clinical data can be used to match patients to cancer therapies or clinical trials. We analyzed 500 patient samples across diverse tumor types using the Tempus xT platform by DNA-seq, RNA-seq and immunological biomarkers. The use of a tumor and germline dataset led to substantial improvements in mutation identification and a reduction in false-positive rates. RNA-seq enhanced gene fusion detection and cancer type classifications. With DNA-seq alone, 29.6% of patients matched to precision therapies supported by high levels of evidence or by well-powered studies. This proportion increased to 43.4% with the addition of RNA-seq and immunotherapy biomarker results. Combining these data with clinical criteria, 76.8% of patients were matched to at least one relevant clinical trial on the basis of biomarkers measured by the xT assay. These results indicate that extensive molecular profiling combined with clinical data identifies personalized therapies and clinical trials for a large proportion of patients with cancer and that paired tumor-normal plus transcriptome sequencing outperforms tumor-only DNA panel testing.

Emerging epigenomic landscapes of pancreatic cancer in the era of precision medicine

Genetic studies have advanced our understanding of pancreatic cancer at a mechanistic and translational level. Genetic concepts and tools are increasingly starting to be applied to clinical practice, in particular for precision medicine efforts. However, epigenomics is rapidly emerging as a promising conceptual and methodological paradigm for advancing the knowledge of this disease. More importantly, recent studies have uncovered potentially actionable pathways, which support the prediction that future trials for pancreatic cancer will involve the vigorous testing of epigenomic therapeutics. Thus, epigenomics promises to generate a significant amount of new knowledge of both biological and medical importance.

In pancreatic cancer, the epigenomic landscape can strongly impact the disease phenotype. Here, the authors discuss recent advances in our understanding of pancreatic cancer epigenomics, and how this knowledge can integrate with precision medicine approaches in this lethal disease.

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

Targeted Therapies in Non-small-Cell Lung Cancer

The treatment landscape for non-small-cell lung cancer (NSCLC) has dramatically shifted over the past two decades. Targeted or precision medicine has primarily been responsible for this shift. Older paradigms of treating metastatic NSCLC with cytotoxic chemotherapy, while still important, have given way to evaluating tumor tissues for specific driver mutations that can be treated with targeted agents. Patients treated with targeted agents frequently have improved progression-free survival and overall survival compared to patients without a targetable driver mutation, highlighting the clinical benefit of precision medicine. In this chapter, we explore the historic landmark trials, the current state of the field, and potential future targets under investigation, in this exciting, rapidly evolving discipline of precision medicine in lung cancer.

Next-generation sequencing in precision oncology: Patient understanding and expectations

BACKGROUND

Implementation of precision oncology interventions poses several challenges to informed consent and patient education. This study assessed cancer patients' understanding, expectations, and outcomes regarding participation in research examining the impact of matched tumor and germline sequencing on their clinical care.

METHODS

A total of 297 patients (mean age: 59 years; 50% female; 96% white) with refractory, metastatic cancer were surveyed, including 217 who completed surveys both before and after undergoing integrated whole exome and transcriptome sequencing as part of a larger clinical research study.

RESULTS

At baseline, the vast majority of patients expected to receive several potential direct benefits from study participation, including written reports of sequencing findings (88%), greater understanding of the causes of their cancer (74%), and participation in clinical trials for which sequencing results would make them eligible (84%). In most cases, these benefits were not realized by study completion. Despite explanations from study personnel to the contrary, most participants (67%-76%) presumed that incidental germline sequencing findings relevant to noncancerous health conditions (eg, diabetes) would automatically be disclosed to them. Patients reported low levels of concern about study risks at baseline and low levels of regret about study participation at follow-up.

CONCLUSIONS

Findings suggest that cancer patients participating in precision oncology intervention research have largely unfulfilled expectations of direct benefits related to their study participation. Increased focus on patient education to supplement the informed consent process may help manage patients' expectations regarding the extent and likelihood of benefits received as a result of undergoing genomic sequencing.

Genomics-Enabled Precision Medicine for Cancer

Genomic information is increasingly being incorporated into clinical cancer care. Large-scale sequencing efforts have deepened our understanding of the genomic landscape of cancer and contributed to the expanding catalog of alterations being leveraged to aid in cancer diagnosis, prognosis, and treatment. Genomic profiling can provide clinically relevant information regarding somatic point mutations, copy number alterations, translocations, and gene fusions. Genomic features, such as mutational burden, can also be measured by more comprehensive sequencing strategies and have shown value in informing potential treatment options. Ongoing clinical trials are evaluating the use of molecularly targeted agents in genomically defined subsets of cancers within and across tumor histologies. Continued advancements in clinical genomics promise to further expand the application of genomics-enabled medicine to a broader spectrum of oncology patients.

Methods of measurement for tumor mutational burden in tumor tissue

Immunotherapies based on immune checkpoint inhibitors are emerging as an innovative treatment for different types of advanced cancers. While the utility of immune checkpoint inhibitors has been clearly demonstrated, the response rate is highly variable across individuals. Due to the cost and toxicity of these immunotherapies, a critical challenge in this field is the identification of predictive biomarkers to discriminate which patients may respond to immunotherapy. Recently, a high tumor mutational burden (TMB) has been identified as a genetic signature that is associated with a favorable outcome for immune checkpoint inhibitor therapy. The TMB is defined as the total number of nonsynonymous mutations per coding area of a tumor genome. Initially, it was determined using whole exome sequencing, but due to the high costs and long turnaround time of this method, targeted panel sequencing is currently being explored to measure TMB. In the near future, TMB evaluation may play an important role in immuno-oncology, but its implementation in a routine setting involves robust analytical and clinical validation. Standardization is also needed in order to make informed decisions about patients. This review presents the methodologies employed for determining TMB and discusses the factors that may have an impact on its measurement.

Multiple Facets of Marine Invertebrate Conservation Genomics

Conservation genomics aims to preserve the viability of populations and the biodiversity of living organisms. Invertebrate organisms represent 95% of animal biodiversity; however, few genomic resources currently exist for the group. The subset of marine invertebrates includes the most ancient metazoan lineages and possesses codes for unique gene products and possible keys to adaptation. The benefits of supporting invertebrate conservation genomics research (e.g., likely discovery of novel genes, protein regulatory mechanisms, genomic innovations, and transposable elements) outweigh the various hurdles (rare, small, or polymorphic starting materials). Here we review best conservation genomics practices in the laboratory and in silico when applied to marine invertebrates and also showcase unique features in several case studies of acroporid corals, crown-of-thorns starfish, apple snails, and abalone. Marine conservation genomics should also address how diversity can lead to unique marine innovations, the impact of deleterious variation, and how genomic monitoring and profiling could positively affect broader conservation goals (e.g., value of baseline data for in situ/ex situ genomic stocks).

Heuristic value-based framework for lung cancer decision-making

Heuristics and the application of fast-and-frugal trees may play a role in establishing a clinical decision-making framework for value-based oncology. We determined whether clinical decision-making in oncology can be structured heuristically based on the timeline of the patient's treatment, clinical intuition, and evidence-based medicine. A group of 20 patients with advanced non-small cell lung cancer (NSCLC) were enrolled into the study for extensive treatment analysis and sequential decision-making. The extensive clinical and genomic data allowed us to evaluate the methodology and efficacy of fast-and-frugal trees as a way to quantify clinical decision-making. The results of the small cohort will be used to further advance the heuristic framework as a way of evaluating a large number of patients within registries. Among the cohort whose data was analyzed, substitution and amplification mutations occurred most frequently. The top five most prevalent genomic alterations were TP53 (45%), ALK (40%), LRP1B (30%), CDKN2A (25%), and MYC (25%). These 20 cases were analyzed by this clinical decision-making process and separated into two distinctions: 10 straightforward cases that represented a clearer decision-making path and 10 complex cases that represented a more intricate treatment pathway. The myriad of information from each case and their distinct pathways was applied to create the foundation of a framework for lung cancer decision-making as an aid for oncologists. In late-stage lung cancer patients, the fast-and-frugal heuristics can be utilized as a strategy of quantifying proper decision-making with limited information.