Landscape of Biomarkers in Non-small Cell Lung Cancer Using Comprehensive Genomic Profiling and PD-L1 Immunohistochemistry.

Comprehensive genomic profiling (CGP) and immunohistochemistry (IHC) are important biomarker tools used for patients with non-small cell lung cancer (NSCLC) given the expanding number of standard-of-care therapies that require companion diagnostic testing. We examined 9450 NSCLC real-world patient samples that underwent both CGP and programmed death-ligand 1 (PD-L1) IHC to understand the biomarker landscape in this patient cohort. By assessing National Comprehensive Cancer Network (NCCN)-recommended biomarkers including genomic alterations, tumor mutational burden (≥10 mutations/Mb cut-off), and PD-L1 expression (Tumor Proportion Score (TPS) ≥ 50% cut-off), we show that CGP + PD-L1 IHC yielded potentially actionable results for 70.5% of the 9,450 patients with NSCLC. Among the remaining 29.5% (2,789/9,450) of patients, 86.7% (2,419/2,789) were potentially eligible for another biomarker-associated therapy and/or clinical trial based on their genomic profile. In addition, in the PD-L1TPS≥50% disease subset, BRAF mutations, MET mutations, MET amplifications, and KRAS mutations were significantly enriched; and in the PD-L1TPS<50%, EGFR mutations, ERBB2 mutations, STK11 mutations, and KEAP1 mutations were enriched. These findings highlight the improved clinical utility of combining CGP with IHC to expand the biomarker-guided therapeutic options available for patients with NSCLC, relative to single biomarker testing alone.

Biomarkers in Breast Cancer: An Integrated Analysis of Comprehensive Genomic Profiling and PD-L1 Immunohistochemistry Biomarkers in 312 Patients with Breast Cancer.

BACKGROUND: We examined the current biomarker landscape in breast cancer when programmed death-ligand 1 (PD-L1) testing is integrated with comprehensive genomic profiling (CGP). MATERIAL AND METHODS: We analyzed data from samples of 312 consecutive patients with breast carcinoma tested with both CGP and PD-L1 (SP142) immunohistochemistry (IHC) during routine clinical care. These samples were stratified into hormone receptor positive (HR+)/human epidermal growth factor receptor negative (HER2-; n = 159), HER2-positive (n = 32), and triple-negative breast cancer (TNBC) cohorts (n = 121). RESULTS: We found that in the TNBC cohort, 43% (52/121) were immunocyte PD-L1-positive, and in the HR+/HER2- cohort, 30% (48/159) had PIK3CA companion diagnostics mutations, and hence were potentially eligible for atezolizumab plus nab-paclitaxel or alpelisib plus fulvestrant, respectively. Of the remaining 212 patients, 10.4% (22/212) had a BRCA1/2 mutation, which, if confirmed by germline testing, would allow olaparib plus talazoparib therapy. Of the remaining 190 patients, 169 (88.9%) were positive for another therapy-associated marker or a marker that would potentially qualify the patient for a clinical trial. In addition, we examined the relationship between immunocyte PD-L1 positivity and different tumor mutation burden (TMB) cutoffs and found that when a TMB cutoff of ≥9 mutations per Mb was applied (cutoff determined based on prior publication), 11.6% (14/121) patients were TMB ≥9 mutations/Mb and of these, TMB ≥9 mutations per Mb, 71.4% (10/14) were also positive for PD-L1 IHC. CONCLUSION: Our integrated PD-L1 and CGP methodology identified 32% of the tested patients as potentially eligible for at least one of the two new Food and Drug Administration approved therapies, atezolizumab or alpelisib, and an additional 61.2% (191/312) had other biomarker-guided potential therapeutic options. IMPLICATIONS FOR PRACTICE: This integrated programmed death-ligand 1 immunohistochemistry and comprehensive genomic profiling methodology identified 32% of the tested patients as eligible for at least one of the two new Food and Drug Administration-approved therapies, atezolizumab or alpelisib, and an additional 61.2% (191/312) had other biomarker-guided potential therapeutic options. These findings suggest new research opportunities to evaluate the predictive utility of other commonly seen PIK3CA mutations in hormone receptor-positive breast cancers and to standardize tumor mutation burden cutoffs to evaluate its potentially predictive role in triple-negative breast cancer.

Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence.

Treatment with immune checkpoint inhibitors (ICPIs) extends survival in a proportion of patients across multiple cancers. Tumor mutational burden (TMB)-the number of somatic mutations per DNA megabase (Mb)-has emerged as a proxy for neoantigen burden that is an independent biomarker associated with ICPI outcomes. Based on findings from recent studies, TMB can be reliably estimated using validated algorithms from next-generation sequencing assays that interrogate a sufficiently large subset of the exome as an alternative to whole-exome sequencing. Biological processes contributing to elevated TMB can result from exposure to cigarette smoke and ultraviolet radiation, from deleterious mutations in mismatch repair leading to microsatellite instability, or from mutations in the DNA repair machinery. A variety of clinical studies have shown that patients with higher TMB experience longer survival and greater response rates following treatment with ICPIs compared with those who have lower TMB levels; this includes a prospective randomized clinical trial that found a TMB threshold of ≥10 mutations per Mb to be predictive of longer progression-free survival in patients with non-small cell lung cancer. Multiple trials are underway to validate the predictive values of TMB across cancer types and in patients treated with other immunotherapies. Here we review the rationale, algorithm development methodology, and existing clinical data supporting the use of TMB as a predictive biomarker for treatment with ICPIs. We discuss emerging roles for TMB and its potential future value for stratifying patients according to their likelihood of ICPI treatment response. IMPLICATIONS FOR PRACTICE: Tumor mutational burden (TMB) is a newly established independent predictor of immune checkpoint inhibitor (ICPI) treatment outcome across multiple tumor types. Certain next-generation sequencing-based techniques allow TMB to be reliably estimated from a subset of the exome without the use of whole-exome sequencing, thus facilitating the adoption of TMB assessment in community oncology settings. Analyses of multiple clinical trials across several cancer types have demonstrated that TMB stratifies patients who are receiving ICPIs by response rate and survival. TMB, alongside other genomic biomarkers, may provide complementary information in selecting patients for ICPI-based therapies.

Effect of a Collaboration Between a Health Plan, Oncology Practice, and Comprehensive Genomic Profiling Company from the Payer Perspective.

BACKGROUND: Comprehensive genomic profiling (CGP) is a next-generation sequencing-based methodology that detects 4 classes of genomic alterations, as well as gene signature biomarkers such as microsatellite instability and tumor mutational burden. In the context of precision oncology, CGP can help to direct treatment to genomically matched therapies. OBJECTIVE: To describe the results of a 3-year observational analysis of patients undergoing testing with CGP assays (either FoundationOne or FoundationOne Heme) at a community oncology practice after a regional health plan implemented a medical policy that enabled coverage of CGP. METHODS: A retrospective analysis of medical records was completed at the oncology practice from November 2013 to January 2017; this date range was chosen to coincide with the regional health plan's medical policy implementation of CGP. The medical policy provided coverage of CGP for patients with advanced solid and hematologic cancers. A medical record review assessed all previous and current molecular test results, matched therapy or clinical trial enrollment, and clinical outcomes (clinical benefit or disease progression). The potential cost diversion, from payer to study sponsor, for patients who enrolled in clinical trials was explored. RESULTS: There were 96 patients in the community oncology practice who received CGP over the 3-year period, 86 of whom had clinically relevant genomic alterations. Of the 86, 15 patients were treated with genomically matched therapy, and 6 patients enrolled in clinical trials based on CGP results. In a subset of 32 patients who previously underwent conventional testing, most (84%) had clinically relevant genomic alterations detected by CGP that conventional testing did not identify, and a portion of these patients subsequently received treatment based on the CGP results. In the separate cost diversion analysis of 20 patients who enrolled in phase 1 clinical trials, an estimated $25,000 per-patient cost-benefit may have been accrued to the payer. CONCLUSIONS: This observational analysis characterized the use of CGP in a large community oncology practice among a group of patients insured by a regional health plan. Clinical trial enrollment was facilitated by CGP use in the community setting and may have contributed to cost diversion from the payer to study sponsors. DISCLOSURES: No separate study-related funding was provided by or to Priority Health, Foundation Medicine, and Cancer and Hematology Centers of West Michigan. Data analysis by Reitsma was conducted as part of an internship funded by Priority Health. Reitsma and Fox are employed by Priority Health. Anhorn, Vanden Borre, Cavanaugh, Chudnovsky, and Erlich are employed by Foundation Medicine.

Budget impact analysis of comprehensive genomic profiling in patients with advanced non-small cell lung cancer.

AIMS: Broad molecular profiling of patients with advanced non-small cell lung cancer (NSCLC) is strongly advised to optimize genomic matching with available targeted treatment options or investigational agents. Unlike conventional molecular diagnostic testing, or smaller hotspot panels, comprehensive genomic profiling (CGP) identifies genomic alterations across hundreds of clinically relevant cancer genes from a single tissue specimen. The present study sought to estimate the budget impact of increased use of CGP using a 324-gene panel (FoundationOne) vs non-CGP (represented by a mix of conventional molecular diagnostic testing and smaller NGS hotspot panels) and the number needed to test with CGP to gain 1 life year. MATERIALS AND METHODS: A decision analytic model was developed to assess the budget impact of increased CGP in advanced NSCLC from a US private payer perspective. Model inputs were based on published literature (epidemiology and treatment outcomes), real-world data (testing and rates, medical service costs), list prices for CGP and anti-cancer drugs, and assumptions for clinical trial participation. RESULTS: Among 2 million covered lives, 532 had advanced NSCLC; 266 underwent molecular diagnostic testing. An increase in CGP among those tested, from 2% to 10%, was associated with $0.02 per member per month budget impact, of which $0.013 was attributable to costs of prolonged drug treatment and survival and $0.005 to testing cost. Approximately 12 patients would need to be tested with CGP to add 1 life year. LIMITATIONS: The model incorporated certain assumptions to account for inputs with a limited evidence profile and simplify the possible post-CGP treatments. CONCLUSIONS: An increase in CGP utilization from 2% to 10% among patients with advanced NSCLC undergoing molecular diagnostic testing was associated with a modest budget impact, most of which was attributable to increased use of more effective treatments and prolonged survival.

Real-world utilization of molecular diagnostic testing and matched drug therapies in the treatment of metastatic cancers.

AIMS: To assess the frequency of biopsies and molecular diagnostic testing (human DNA/RNA analysis), anti-cancer drug use (genomically-matched targeted therapy [GMTT], unmatched targeted therapy [UTT], endocrine therapy [ET], and chemotherapy [CT]), and medical service costs among adults with metastatic cancer. METHODS: Adults diagnosed with metastatic breast, non-small cell lung (NSCLC), colorectal, head and neck, ovarian, and uterine cancer (2010Q1-2015Q1) were identified in the OptumHealth Care Solutions claims database and followed from first metastatic diagnosis for ≥1 month and until the end of data availability. Utilization was assessed for each cancer cohort (all and patients aged ≥65 years); per-patient-per-month (PPPM) medical service costs were assessed for all patients. Testing frequency estimates were applied to Surveillance, Epidemiology, and End Results Program data to estimate the number of untested patients (2010-2014). RESULTS: Patients with metastatic cancer (n = 8,193; breast [n = 3,414], NSCLC [n = 2,231], colorectal [n = 1,611], head and neck [n = 511], ovarian [n = 275], and uterine [n = 151]) were 63 years old (mean), with 11.1-22.2 months of observation. Biopsy and molecular diagnostic testing frequencies ranged from 7% (uterine) to 73% (ovarian), and from 34% (head and neck) to 52% (breast), respectively. Few were treated with GMTT (breast, 11%; NSCLC, 9%; colorectal, 6%). Treatment with UTT ranged from 0.7% (uterine) to 21% (colorectal). Biopsy, diagnostic testing, and anti-cancer drug therapy were less frequent for those ≥65 years. Medical service costs (PPPM, mean) ranged from $6,618 (head and neck) to $9,940 (ovarian). The estimated number of untested new patients with metastatic cancer was 636,369 (all) and 341,397 (≥65). LIMITATIONS: In addition to the limitations of claims analyses, diagnostic testing frequency may be under-estimated if patients underwent testing prior to study inclusion. CONCLUSIONS: The low frequency of molecular diagnostic testing suggests there are opportunities to better inform management of patients with advanced cancer, particularly decisions to treat with GMTT.

Delivering Precision Oncology in a Community Cancer Program: Results From a Prospective Observational Study.

INTRODUCTION: Precision oncology (PO) is a growing treatment approach in the era of next-generation sequencing (NGS) and matched therapies. Effective delivery of PO in the community has not been extensively studied. Our program developed a virtual molecular tumor board (MTB) strategy to help guide PO care. MATERIALS AND METHODS: Over 18 months, eligible adult patients with advanced, incurable solid tumor malignancies were enrolled in a molecular profiling (MP) study using the Foundation Medicine NGS panel. Results were reviewed through a weekly, videoconferenced MTB conducted across our largely rural integrated health system. Recommendations from the MTB were used to identify actionable alterations (AAs). Feasibility of PO care delivery was assessed as the primary outcome. Secondary outcomes included the frequency of AAs, genomic matched treatments, genomic matched clinical trial enrollment, and clinical outcomes. RESULTS: A total of 120 participants with a variety of advanced tumor types were enrolled. Of these, 109 (90.8%) had successful MP. Treatment on the basis of an AA was recommended by the MTB in 58% of patients (63 of 109) who had a successful MP result. For those completing MP, treatments included enrollment in a genomic matched clinical trial (n = 16; 14.6%) and genomic matched treatment with a Food and Drug Administration-approved agent (n = 23; 21.1%). Response and survival data were similar regardless of the matched treatment option chosen. CONCLUSION: A video-conferenced MTB-facilitated NGS testing and treatment delivery system was implemented in our integrated community oncology program. Continued use of this model aims to increase understanding of the impact of PO in this setting.

Estimated Cost of Anticancer Therapy Directed by Comprehensive Genomic Profiling in a Single-Center Study.

PURPOSE: Comprehensive genomic profiling (CGP) detects several classes of genomic alterations across numerous genes simultaneously and can match more patients with genomically targeted therapies than conventional molecular profiling. The current study estimated the costs of anticancer drugs and overall survival (OS) for patients who were treated with matched and unmatched therapy. METHODS: Costs were estimated for patients with complete data (188 of 500 patients) from a prospective, nonrandomized study of patients with diverse refractory cancers who underwent CGP and were treated with matched or unmatched therapy. We assessed mean time to treatment failure (TTF) and mean observed OS. Patient-specific drug and administration costs were imputed for the first regimen after CGP on the basis of drug classes, unit costs, and time on treatment. RESULTS: Patients on matched (n = 122) versus unmatched (n = 66) therapy had longer mean TTF (+1.5 months) and observed OS (+2.4 months) and higher drug costs (+$38,065; all P < .01). Increased drug costs were largely attributable to the longer duration of therapy associated with extended TTF (66.3%) rather than higher monthly drug costs (33.7%). Incremental increases in TTF (+1.9 months v +1.2 months) and observed OS (+2.5 months v +2.1 months) between matched and unmatched therapies were larger for those who underwent CGP in earlier- versus later-line therapy. Incremental increases in drug costs between matched and unmatched therapies were lower for earlier- compared with later-line therapy (+$27,000 v +$43,000, respectively). CONCLUSION: Matched therapy was associated with longer TTF, increased OS, and manageable incremental cost increases compared with unmatched therapy. Most of these increased costs were a result of the longer duration of therapy rather than higher monthly drug costs. The benefits of matching were numerically greater in earlier versus later lines of therapy, which is consistent with the value of early use of CGP.