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BACKGROUND: In the phase III KEYNOTE-061 trial (NCT02370498), pembrolizumab did not significantly improve overall survival versus paclitaxel as second-line therapy for gastric/gastroesophageal junction (GEJ) adenocarcinoma with programmed death-ligand 1 (PD-L1) combined positive score (CPS) ≥1 tumors. The association of tissue tumor mutational burden (tTMB) status and clinical outcomes was determined, including the relationship with CPS and microsatellite instability-high (MSI-H) status. PATIENTS AND METHODS: In patients with whole exome sequencing (WES) data [420/592 (71%); pembrolizumab, 218; paclitaxel, 202], the association of tTMB with objective response rate (ORR; logistic regression), progression-free survival (PFS; Cox proportional hazards regression), and overall survival (OS; Cox proportional hazards regression) were measured using one-sided (pembrolizumab) and two-sided [paclitaxel] P values. tTMB was also evaluated using FoundationOne®CDx [205/592 (35%)]. Prespecified equivalent cut-offs of 175 mut/exome for WES and 10 mut/Mb for FoundationOne®CDx were used. RESULTS: WES-tTMB was significantly associated with ORR, PFS, and OS in pembrolizumab-treated (all P < 0.001) but not paclitaxel-treated patients (all P > 0.6) in univariate analysis. The area under the receiver operating characteristics curve for WES-tTMB and response was 0.68 [95% confidence interval (CI) 0.56-0.81] for pembrolizumab and 0.51 (95% CI 0.39-0.63) for paclitaxel in univariate analysis. There was low correlation between WES-tTMB and CPS in both treatment groups (r ≤ 0.16). WES-tTMB remained significantly associated with all clinical endpoints with pembrolizumab after adjusting for CPS and with PFS and OS after excluding known MSI-H tumors (n = 26). FoundationOne®CDx-tTMB demonstrated a positive association with ORR, PFS, and OS in pembrolizumab-treated patients (all P ≤ 0.003) but not PFS or OS in paclitaxel-treated patients (P > 0.1). CONCLUSION: This exploratory analysis from KEYNOTE-061 is the first to demonstrate a strong association between tTMB and efficacy with pembrolizumab but not paclitaxel in patients with gastric/GEJ adenocarcinoma in a randomized setting. Data further suggest tTMB is a significant and independent predictor beyond PD-L1 status. ispartof: ANNALS OF ONCOLOGY vol:32 issue:9 pages:1127-1136 ispartof: location:England status: published

Background: In the phase 2 KEYNOTE-086 study (NCT02447003), pembrolizumab monotherapy had durable antitumor activity in a subset of patients with previously treated mTNBC (cohort A; n = 170) and in patients with previously untreated PD-L1-positive mTNBC (cohort B; n = 84). In this exploratory analysis of KEYNOTE-086, we evaluated the association between several biomarkers and response to pembrolizumab. Methods: Cohort A enrolled patients regardless of PD-L1 expression who had documented disease progression following ≥1 systemic therapy for metastatic disease. Cohort B enrolled patients with PD-L1-positive (combined positive score [CPS] ≥1) tumors who had not received prior systemic therapy for metastatic disease. Immunohistochemistry was used to measure PD-L1 CPS and CD8 density; H&E staining for percentage of stromal tumor infiltrating lymphocytes (sTILs); RNA-sequencing for 18-gene T-cell-inflamed gene expression profile (GEP), angiogenesis, and glycolysis signatures; and whole exome sequencing (paired tumor and germline) for TMB (TMB-H defined as ≥175 mut/exome), HRD-LOH (DNA damage), Signature 3, and APOBEC. Biomarkers were analyzed as continuous variables in cohorts A and B combined and individually. Area under the receiver operating characteristic curve was estimated between each biomarker and overall response rate (ORR). Wald test P-values were calculated using logistic regression adjusted for cohort and Eastern Cooperative Oncology Group performance status. Germline and somatic BRCA1/2 mutations were pooled; one-sided P-value was calculated using Fisher’s exact test. Spearman’s correlation was used for correlations. Results: Biomarker data were available in the following number of patients: 253 (99.6%; PD-L1), 204 (80.3%; CD8), 187 (73.6%; GEP), 171 (67.3%; TMB/HRD), 228 (89.8%; sTILs), 163 (64.2%; Signature 3/APOBEC), and 132 (52.0%; angiogenesis/glycolysis). When data from cohorts A and B were combined, PD-L1 CPS (median 2; IQR 0-10), CD8 (median 159; IQR 62-319), GEP (median -0.34; IQR -0.57 to -0.11), TMB (median 82 mut/exome; IQR 50-139), and sTILs (median 5; IQR 2-20) were significantly associated with ORR (Table). There were moderate correlations between PD-L1 and GEP (r = 0.532), PD-L1 and sTILs (r = 0.451), and GEP and sTILs (r = 0.490). No correlation was observed between TMB and PD-L1 (r = 0.038), GEP (r = -0.035), and sTILs (r = -0.031). When cohorts were combined, TMB was significantly associated with ORR, PFS, and OS after adjustment for PD-L1, GEP, CD8, or sTILs. HRD-LOH score, Signature 3, and APOBEC were not significantly associated with ORR (Table); P for BRCA1/2 was 0.2385. The angiogenesis signature was associated with lack of response while the glycolysis signature was associated with response to pembrolizumab (Table). Conclusions: In this exploratory biomarker analysis from KEYNOTE-086, higher levels of PD-L1, GEP, TMB, CD8 IHC, sTILs, and the glycolysis signature were associated with increased response to pembrolizumab monotherapy. These findings may help identify patients with mTNBC who are most likely to respond to pembrolizumab. Table. Association of Biomarkers as Continuous Variables With Pembrolizumab Objective ResponseBiomarkerCombined Cohorts AUCCombined Cohorts P*Combined Cohorts Multitest corrected PCohort A AUCCohort B AUCPD-L10.6740.040-0.5440.654GEP0.7480.003-0.8370.561TMB0.6270.007-0.5480.710CD8 IHC0.760.000020.000120.850.68sTILs0.6710.012-0.6320.641HRD0.3940.874-0.5220.316Signature 30.6830.072-0.6970.736APOBEC0.5280.537-0.6740.623Angiogenesis0.6770.0090.0450.6610.731Glycolysis0.6120.0090.0360.8590.459AUC, area under the curve.*One-sided P-values are shown for all biomarkers except for Signature 3 and APOBEC, for which 2-sided P-values are shown. Citation Format: Sherene Loi, Peter Schmid, Javier Cortes, David W. Cescon, Eric P. Winer, Deborah L. Toppmeyer, Hope S. Rugo, Michelino De Laurentiis, Rita Nanda, Hiroji Iwata, Ahmad Awada, Antoinette R. Tan, Roberto Salgado, Vassiliki Karantza, Petar Jelinic, Anran Wang, Lingkang Huang, Razvan Cristescu, Lakshman Annamalai, Jennifer Yearley, Jennifer Yearley, Sylvia Adams. Association between biomarkers and response to pembrolizumab in patients with metastatic triple-negative breast cancer (mTNBC): Exploratory analysis from KEYNOTE-086 [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD14-07.

The MC38 (derived from carcinogen-induced colon adenocarcinoma) tumor model is sensitive to anti-programmed cell death-1 (anti-PD-1) treatment. However, there is no comprehensive description of the T and B cell receptor (TCR, BCR) repertoires of the MC38 tumor model following anti-PD-1 treatment, an improved understanding of which is highly important in the development of anti-PD-1 immunotherapy. The present study analyzed the TCR and BCR repertoires of three types of tissue, including tumor, spleen and tumor draining lymph node (DLN) from 20 MC38 syngeneic mice receiving murine anti-PD-1 (mDX400) treatment or mouse immunoglobulin G1 (mIgG1) control treatment. To obtain enough tissues for high-throughput sequencing, samples were collected on day 8 after the start of initial treatment. The usage frequencies of seven TCR β chain (TRB) V genes and one TRBJ gene were significantly different between mDX400- and mIgG1-group tumors. TCR repertoire diversity was significantly lower in mDX400-group tumors compared with mIgG1-group tumors, with the top 10 most frequent TCR clonotypes notably expanded in mDX400-group tumors. In addition, the proportion of high-frequency TCR clonotypes from mDX400-group tumors that were also present both in the DLN and spleen was significantly higher than that in mIgG1-group tumors. Among the highly expanded TCR clonotypes, one TCR clonotype was consistently expanded in >50% of the mDX400-group tumors compared with mIgG1-group tumors. Similarly, one BCR clonal family was highly expanded in >50% of mDX400-group tumor samples. The consistently expanded TCR and BCR clones were co-expanded in 29% of mDX400-group tumors. Moreover, mutation rates of immunoglobulin heavy chain sequences in the spleen within complementarity determining region 2 and framework region 3 were significantly higher in the mDX400 group than in the mIgG1 group. The findings of this study may contribute to an improved understanding of the molecular mechanisms of anti-PD-1 treatment.

BackgroundPembrolizumab is a standard-of-care first-line treatment for advanced/metastatic NSCLC, either as monotherapy (for patients with PD-L1 tumor proportion score [TPS] ≥1%) or combined with platinum chemotherapy. An improved OS benefit has been demonstrated for both pembrolizumab monotherapy and pembrolizumab plus chemotherapy in patients with higher tumor PD-L1 expression, and for pembrolizumab monotherapy in patients with higher tissue tumor mutation burden (tTMB). Mutations in KRAS occur relatively frequently in patients with nonsquamous NSCLC but infrequently in those with squamous NSCLC; most mutations are in codon 12. Notably, the pembrolizumab OS treatment effect was not diminished in patients with KRAS G12C mutations in phase 3 studies evaluating pembrolizumab monotherapy and pembrolizumab in combination with chemotherapy.1 2 Herein we describe prevalence of KRAS mutations among patients with advanced nonsquamous NSCLC from two phase 3 clinical studies evaluating first-line pembrolizumab (KEYNOTE-042 and KEYNOTE-189) and the relationship of such mutations with select patient characteristics.MethodsKEYNOTE-042 (NCT02220894) evaluated pembrolizumab versus platinum-based chemotherapy for advanced PD-L1–positive NSCLC (any histology) without EGFR/ALK alterations. KEYNOTE-189 (NCT02578680) evaluated pembrolizumab plus platinum-based chemotherapy versus platinum-based chemotherapy alone for metastatic nonsquamous NSCLC without EGFR/ALK alterations irrespective of tumor PD-L1 expression. Whole-exome sequencing of tumor tissue and matched normal DNA (blood) was performed for patients with nonsquamous histology. PD-L1 TPS was evaluated using the PD-L1 IHC 22C3 pharmDx assay (Agilent Technologies, Carpinteria, CA, USA). Prevalence of KRAS mutations and their relationships with TMB, PD-L1 TPS, and smoking status were analyzed descriptively.Results590 patients with nonsquamous NSCLC were included in these analyses (KEYNOTE-042, n=301; KEYNOTE-189, n=289). Overall, 42.9% of patients had tTMB ≥175 mut/exome, 81.4% were current/former smokers and, 40.3%, 42.7%, and 16.9% had PD-L1 TPS ≥50%, 1–49% and KRAS G12C, G12D, and G12V mutations occurred in 11.0%, 4.1%, and 5.4% of patients, respectively. Prevalence of KRAS mutations by patient characteristics is summarized in the table (table 1). KRAS G12C mutations occurred almost exclusively in current/former smokers. KRAS G12C was enriched in tumors with tTMB ≥175 mut/exome and tumors with PD-L1 TPS ≥50%. Prevalence was highest in tumors with both tTMB ≥175 mut/exome and PD-L1 TPS ≥50%.Abstract 364 Table 1KRAS Mutation PrevalenceConclusionsKRAS G12C mutations occurred with moderate frequency in patients with nonsquamous NSCLC, with most occurring in current/former smokers. KRAS G12C mutations occurred at higher frequency in patient subgroups defined by higher tTMB and PD-L1 TPS.AcknowledgementsMedical writing assistance was provided by Christabel Wilson, MSc, of ICON plc (North Wales, PA, USA), funded by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA.Trial RegistrationKEYNOTE-042, ClinicalTrials.gov, NCT02220894; KEYNOTE-189, ClinicalTrials.gov, NCT02578680ReferencesGadgeel S, Rodriguez-Abreu D, Felip E, et al. KRAS mutational status and efficacy in KEYNOTE-189: pembrolizumab (pembro) plus chemotherapy (chemo) vs placebo plus chemo as first-line therapy for metastatic non-squamous NSCLC. Ann Oncol 2019;30(suppl 11):xi64-xi5.Herbst RS, Lopes G, Kowalski DM, et al. Association of KRAS mutational status with response to pembrolizumab monotherapy given as first-line therapy for PD-L1-positive advanced non-squamous NSCLC in KEYNOTE-042. Ann Oncol 2019;30(suppl 11):xi63-xi4.Ethics ApprovalFor both trials, the protocol and all amendments were approved by the appropriate ethics committee at each center, the study was conducted in accordance with the standards of Good Clinical Practice. Patients provided written informed consent before enrollment.

BackgroundT-cell–inflamed gene expression profile (TcellinfGEP) and tumor mutational burden (TMB) are clinically validated biomarkers that independently predict pembrolizumab response. This study investigated prospective TcellinfGEP and TMB assessment in evaluating first-line pembrolizumab-based combination therapies; the different treatment combinations evaluated may provide insight into the unique biology of each biomarker subgroup.MethodsKEYNOTE-495/KeyImPaCT is a group-sequential, adaptively randomized, multisite, open-label, phase 2 study investigating first-line pembrolizumab plus the VEGF/FGFR inhibitor lenvatinib, CTLA-4 inhibitor quavonlimab (MK-1308), or LAG-3 inhibitor favezelimab (MK-4280) in patients with advanced NSCLC. DNA and RNA were extracted from tumor tissue to determine TcellinfGEP and TMB; patients were assigned to one of four biomarker-defined subgroups (TcellinfGEPlowTMBlow, TcellinfGEPlowTMBhigh, TcellinfGEPhighTMBlow, TcellinfGEPhighTMBhigh) and randomly assigned 1:1:1 to receive pembrolizumab (200mg IV Q3W)+lenvatinib (20mg oral QD), pembrolizumab+quavonlimab (75mg IV Q6W), or pembrolizumab+favezelimab (200mg [n=30] or 800mg [n=34] Q3W; the initial prespecified dose was 200mg but changed to 800mg based on emerging data). The primary end point was investigator-assessed ORR per RECIST v1.1. Multiple interim analyses will be performed until the prespecified clinical signal is observed. The first interim analysis for each combination therapy occurred after ≥10 patients had ≥12 weeks of follow-up.ResultsAt the data cutoff (January 11, 2021), 208 patients were treated (pembrolizumab+lenvatinib, n=72; pembrolizumab+quavonlimab, n=72; pembrolizumab+favezelimab 200mg, n=30; pembrolizumab+favezelimab 800mg, n=34). The overall assay success rate for testing and determining TcellinfGEP and TMB was 94%. In patients treated with pembrolizumab+lenvatinib, pembrolizumab+quavonlimab, or pembrolizumab+favezelimab, ORRs were generally highest in the TcellinfGEPhighTMBhigh subgroup (table 1); response rates were similar across combinations within this subgroup. ORR was low across combinations within the TcellinfGEPlowTMBlow subgroup. Treatment-related adverse events (TRAEs) occurred in 88%, 65%, 57%, and 59% of patients in the pembrolizumab+lenvatinib, pembrolizumab+quavonlimab, pembrolizumab+favezelimab 200mg and pembrolizumab+favezelimab 800mg arms, respectively. Consistent with the known TRAEs of these agents, most TRAEs were grade 1 or 2 in severity except in the pembrolizumab+lenvatinib arm (grade 3–5, 63%). Three deaths from TRAEs occurred (pembrolizumab+lenvatinib [n=2], brain hemorrhage and myocardial infarction; pembrolizumab+favezelimab 800 mg [n=1], pneumonitis).Abstract 457 Table 1Confirmed ORR by Therapy and Biomarker StatusConclusionsThese data demonstrate the feasibility and clinical usefulness of prospective TcellinfGEP and TMB assessment to study the clinical activity of three first-line pembrolizumab-based combination therapies in patients with advanced NSCLC. Although sample sizes were small, the TcellinfGEPhighTMBhigh subgroup demonstrated the best response among the biomarker subgroups for all three combination therapies; further validation is needed to determine additional signals and may be addressed as more mature data become available.AcknowledgementsJeanne Fahey, PhD, of Merck & Co., Inc., Kenilworth, New Jersey, USA, provided critical review of the abstract. Elisha Dettman PhD, Mark Ayers MS, and Andrey Loboda PhD of Merck & Co., Inc., Kenilworth, New Jersey, USA, provided critical review of study translational data. Medical writing and/or editorial assistance was provided by Shane Walton, PhD, and Lei Bai, PhD, of ApotheCom (Yardley, PA, USA). This assistance was funded by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA.Trial RegistrationClinicalTrials.gov, NCT03516981Ethics ApprovalThe study protocol and all amendments were approved by the relevant institutional review board or ethics committee at each study site. All patients provided written informed consent to participate in the clinical trial.

Current therapeutic interventions to eradicate latent HIV (“reservoir”) and restore immune function in ART-treated HIV infection have yet to show efficacy. To explore mechanisms of HIV persistence, we apply an integrated systems biology approach and identify a distinct group of individuals with poor CD4 T-cell reconstitution (Immunologic non-responders, “INRs”) and high frequencies of cells with inducible HIV. Contrary to the prevailing notion that immune activation drives HIV persistence and immune dysfunction, peripheral blood leukocytes from these subjects have enhanced expression of a network of genes regulated by cellular senescence. In these subjects, increased frequencies of regulatory T cells and expression of the TGF-β signaling cascade are concomitant with the downregulation of cell cycle and metabolism in CD4 central memory T (TCM) cells. These cascades, downstream of TGF-β, lead to the accumulation of PD-1 expressing CD4 TCM and are associated with an increase in frequencies of cells with inducible HIV ex vivo. In vitro validation confirmed that this cellular profile was driven by a β-hydroxybutyrates/bile acid rich metabolic milieu and resulted in TGF-β associated latency establishment. Our findings identify targets for PD-1 or TGF-β specific interventions that can overcome cellular senescence; these therapeutic approaches have shown safety and efficacy in cancer, and may prove to be crucial for HIV eradication.

Purpose:Molecular profiling of large databases of human tumor gene expression profiles offers novel opportunities for informing decisions in clinical development programs.Experimental Design:Gene expression profile of programmed death ligand 1 (PD-L1) was explored in a dataset of 16,000 samples, including approximately 4,000 metastatic tumors, across >25 tumor types prevalent in the United States, looking for new indications for the programmed death 1 (PD-1) inhibitor pembrolizumab. PD-L1 expression was highly concordant with several genomic signatures indicative of immune-inflamed tumor microenvironment. Prevalence of activated immune-inflamed tumors across all tumor types was explored and used to rank tumor types for potential response to pembrolizumab monotherapy.Results:The analysis yielded 3 tiers of indications in which high levels of PD-L1 and immune-inflamed signatures were found in up to 40% to 60%, 20% to 40%, and 0% to 20% of tumors. Tier 1 contained novel indications known at the time of analysis to be responsive to PD-1 checkpoint blockade in the clinic (such as melanoma and non–small cell lung cancer), as well as indications not studied in the clinic previously, including microsatellite instability–high colorectal, head and neck, bladder, and triple-negative breast cancers. Complementary analysis of an Asian/Pacific cancer dataset (gastric cancer) revealed high prevalence of immune-inflamed tumors in gastric cancer. These data contributed to prioritization of these indications for clinical development of pembrolizumab as monotherapy.Conclusions:Data highlight the value of molecular profiling in identifying populations with high unmet needs with potentially favorable response characteristics and accelerating development of novel therapies for these patients.See related commentary by Mansfield and Jen, p. 1443

PURPOSE Biomarkers that can predict response to anti–programmed cell death 1 (PD-1) therapy across multiple tumor types include a T-cell–inflamed gene-expression profile (GEP), programmed death ligand 1 (PD-L1) expression, and tumor mutational burden (TMB). Associations between these biomarkers and the clinical efficacy of pembrolizumab were evaluated in a clinical trial that encompassed 20 cohorts of patients with advanced solid tumors. METHODS KEYNOTE-028 ( ClinicalTrials.gov identifier: NCT02054806) is a nonrandomized, phase Ib trial that enrolled 475 patients with PD-L1–positive advanced solid tumors who were treated with pembrolizumab 10 mg/kg every 2 weeks for 2 years or until confirmed disease progression or unacceptable toxicity occurred. The primary end point was objective response rate (ORR; by RECIST v1.1, investigator review). Secondary end points included safety, progression-free survival (PFS), and overall survival (OS). Relationships between T-cell–inflamed GEP, PD-L1 expression, and TMB and antitumor activity were exploratory end points. RESULTS ORRs (with 95% CIs) ranged from 0% (0.0% to 14.2%) in pancreatic cancer to 33% (15.6% to 55.3%) in small-cell lung cancer. Across cohorts, median (95% CI) PFS ranged from 1.7 months (1.5 to 2.9 months) to 6.8 months (1.9 to 14.1 months) in pancreatic and thyroid cancers, respectively, and median OS from 3.9 months (2.8 to 5.5 months) to 21.1 months (9.1 to 22.4 months) in vulvar and carcinoid tumors, respectively. Higher response rates and longer PFS were demonstrated in tumors with higher T-cell–inflamed GEP, PD-L1 expression, and/or TMB. Correlations of TMB with GEP and PD-L1 were low. Response patterns indicate that patients with tumors that had high levels of both TMB and inflammatory markers (GEP or PD-L1) represent a population with the highest likelihood of response. Safety was similar and consistent with prior pembrolizumab reports. CONCLUSION A T-cell–-inflamed GEP, PD-L1 expression, and TMB predicted response to pembrolizumab in multiple tumor types. These biomarkers (alone/in combination) may help identify patients who have a higher likelihood of response to anti–PD-1 therapies across a broad spectrum of cancers.

Veglia et al. characterize the heterogeneity of polymorphonuclear neutrophils (PMNs) in the tumor microenvironment, spleen, and peripheral blood. The identification of neutrophil populations with potent immune suppressive activity opens selective targeting opportunities., In this study, using single-cell RNA-seq, cell mass spectrometry, flow cytometry, and functional analysis, we characterized the heterogeneity of polymorphonuclear neutrophils (PMNs) in cancer. We describe three populations of PMNs in tumor-bearing mice: classical PMNs, polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), and activated PMN-MDSCs with potent immune suppressive activity. In spleens of mice, PMN-MDSCs gradually replaced PMNs during tumor progression. Activated PMN-MDSCs were found only in tumors, where they were present at the very early stages of the disease. These populations of PMNs in mice could be separated based on the expression of CD14. In peripheral blood of cancer patients, we identified two distinct populations of PMNs with characteristics of classical PMNs and PMN-MDSCs. The gene signature of tumor PMN-MDSCs was similar to that in mouse activated PMN-MDSCs and was closely associated with negative clinical outcome in cancer patients. Thus, we provide evidence that PMN-MDSCs are a distinct population of PMNs with unique features and potential for selective targeting opportunities.

Introduction/Background Various biomarkers have been investigated to identify patients likely to respond to PARP inhibition. PARP inhibitor olaparib plus bevacizumab is approved by the US FDA as maintenance therapy for homologous recombination deficiency (HRD)–positive advanced ovarian cancer; the FDA contemporaneously approved a commercial assay as a companion diagnostic for HRD assessment that includes a genomic instability biomarker. Other genomic platforms measuring HRD are available or in development, including single-nucleotide polymorphism (SNP) genotyping arrays designed to measure tumour-related copy number changes. We evaluated the performance of OncoScan™ (ThermoFisher) and Infinium CytoSNP-850K (CytoSNP; Illumina) for assessing HRD genomic instability. Methodology DNA extracted from pretreatment archival tumour samples (N=126 across 20 indications) was evaluated with Oncoscan™, CytoSNP and an FDA-approved HRD test. ASCAT (v2.5.1), using log R ratio and B-allele frequency of autosomal markers with GC wave correction, was used to evaluate copy number variation (CNV) and loss of heterozygosity (LOH). The genomic metrics were further generated with default parameters using previously reported algorithms1 for LOH,2 number of telomeric-allelic imbalance (NTAI)3 and large-scale state transition (LST)4; the aggregate HRD metric was the sum of the three components. The association between genomic metrics (with BRCA deleterious alterations) and an FDA-approved HRD test metric (dichotomised at clinical cutoff) was calculated using AUROC. Correlations among continuous metrics were assessed using Spearman rank correlation coefficients. Results CNV segmentation and genomic metrics were successfully calculated for 120 (Oncoscan™), 106 (CytoSNP) and 126 (FDA-approved test) samples. Assessed by SNP genotyping arrays, the genomic metric as a continuous variable demonstrated good association with deleterious BRCA alterations (AUROC of HRD: Oncoscan™, 0.87; CytoSNP, 0.75) (table 1) and the FDA-approved test at cutoff 42 (AUROC of HRD: Oncoscan™, 0.92; CytoSNP, 0.91) (table 2). The genomic metric as a continuous variable showed good correlation with the FDA-approved HRD test metric (Spearman correlation of HRD: Oncoscan™, 0.82; CytoSNP, 0.81). The Spearman correlation of genomic metrics with the FDA-approved HRD test metric was 0.68 (LOH), 0.76 (TAI), 0.78 (LST) and 0.82 (HRD) for Oncoscan™ and 0.59 (LOH), 0.77 (TAI), 0.82 (LST) and 0.81 (HRD) for CytoSNP. Conclusion HRD as a continuous variable assessed by SNP genotyping arrays showed good correlation with an FDA-approved HRD test metric; SNP assays may potentially be able to identify most HRD-positive tumours if appropriate clinically relevant cutoffs can be determined. Disclosures This study was sponsored by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Razvan Cristescu is an employee of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA, and has stock ownership interests in Merck & Co., Inc., Kenilworth, NJ, USA. Xiao Qiao Liu is an employee of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Gladys Arreaza is an employee of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA, and has stock ownership interests in Merck & Co., Inc., Kenilworth, NJ, USA. Cai Chen is an employee of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Andrew Albright is an employee of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA, and has stock ownership interests in Merck & Co., Inc., Kenilworth, NJ, USA. Ping Qiu is an employee of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA, and has stock ownership interests in Merck & Co., Inc., Kenilworth, NJ, USA. Matthew Marton is an employee of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA, and has stock ownership interests in Merck & Co., Inc., Kenilworth, NJ, USA.

Background Various biomarkers have been investigated for their ability to identify patients more likely to respond to immunotherapy. Recently, the PD-1 inhibitor pembrolizumab was approved by the FDA for treating patients with unresectable or metastatic solid tumors with high TMB (TMB-H) who have no satisfactory alternative treatment options following progression on prior treatment. The FDA contemporaneously approved the FoundationOne®CDx (F1CDx; Foundation Medicine) as the companion diagnostic for TMB assessment for pembrolizumab. However, multiple comprehensive genomic profiling panels that can measure TMB are currently available or in development. We evaluated the performance of TruSight™ Oncology 500 (TSO500; Illumina) for assessing TMB and its clinical utility using F1CDx and whole exome sequencing (WES) as reference methods. Methods Pretreatment archival tumor samples from patients enrolled in 8 clinical trials of pembrolizumab monotherapy were evaluated for TMB by TSO500, F1CDx QSR pipeline v3.2.0, and WES. Correlation was assessed using Spearman’s rank correlation coefficient (ρ). The F1CDx and WES TMB cutpoints were 10 mut/Mb and 175 mut/exome, respectively. The TSO500 cutpoint was selected using the Youden index criterion. Concordance was assessed by calculating area under the receiver-operating curve (AUROC), positive percentage agreement (PPA), and negative percentage agreement (NPA). Statistical significance of the association of TMB measured by TSO500 with ORR was assessed using logistic regression adjusted for ECOG performance status and cancer type. Clinical utility of the selected TSO500 TMB cutpoint for discriminating responders and nonresponders was assessed by calculating sensitivity, specificity, positive predictive value, negative predictive value, ORR enrichment, and prevalence. Results TMB scores were valid for 294/294 patients assessed by TSO500, 269/270 assessed by F1CDx, and 293/294 assessed by WES. TMB assessed by TSO500 had good correlation with TMB assessed by F1CDx (ρ=0.76) and WES (ρ=0.74). Using Youden index criterion, 10 mut/Mb was the TSO500 cutpoint that corresponded with both the F1CDx and WES cutpoints. TSO500 reliably predicted TMB-H and non–TMB-H status as determined by the F1CDx (AUROC=0.99, PPA=97.4%, NPA=93.0%) and WES (AUROC=0.95, PPA=76.2%, NPA=96.1%) cutpoints. TMB measured by TSO500 was significantly associated with ORR (one-sided P Conclusions TMB assessed by TSO500 is highly correlated and concordant with TMB assessed by F1CDx and WES. Similar to the validated and approved F1CDx TMB cutpoint of 10 mut/Mb, the TSO500 TMB cutpoint of 10 mut/Mb is predictive of response to pembrolizumab monotherapy. Acknowledgements This analysis and all included studies were sponsored by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Trial Registration NA Ethics Approval The protocols and all amendments for the studies included in this analysis were approved by the appropriate ethics committee at each participating institution. Consent NA References NA

Clinical studies support the efficacy of programmed cell death 1 (PD-1) targeted therapy in a subset of patients with metastatic gastric cancer (mGC). With the goal of identifying determinants of response, we performed molecular characterization of tissues and circulating tumor DNA (ctDNA) from 61 patients with mGC who were treated with pembrolizumab as salvage treatment in a prospective phase 2 clinical trial. In patients with microsatellite instability-high and Epstein–Barr virus-positive tumors, which are mutually exclusive, dramatic responses to pembrolizumab were observed (overall response rate (ORR) 85.7% in microsatellite instability-high mGC and ORR 100% in Epstein–Barr virus-positive mGC). For the 55 patients for whom programmed death-ligand 1 (PD-L1) combined positive score positivity was available (combined positive score cut-off value ≥1%), ORR was significantly higher in PD-L1(+) gastric cancer when compared to PD-L1(−) tumors (50.0% versus 0.0%, P value

Background: Poly-ADP-ribose polymerase (PARP) inhibition plus PD-(L)1 blockade has shown encouraging antitumor activity in patients (pts) with recurrent ovarian or breast cancer with BRCAm and in pts with recurrent ovarian cancer regardless of BRCAm or HRD status. We present initial results of the ongoing KEYLYNK-007 (NCT04123366) study of antitumor activity and safety of olaparib + pembrolizumab in pts with previously treated, advanced, HRRm and/or HRD positive solid tumors. Methods: This phase 2, nonrandomized, multicenter, open-label study enrolled adult pts with histologically/cytologically confirmed, previously treated, advanced solid tumors with centrally-confirmed HRRm and/or HRD positive per Lynparza HRR-HRD assay, and ECOG PS of 0−1, and without prior PARP or PD-(L)1 inhibitor therapy or progression on or ≤4 wks after platinum therapy. Pts received olaparib 300 mg BID and pembrolizumab 200 mg Q3W for 35 cycles or until PD, unacceptable AEs, intercurrent illness, or investigator decision. The primary endpoint was ORR. Results: As of 25 Sep 2020, 168 pts were enrolled (BRCAm, n = 40; HRRm without BRCAm, n = 64; HRD positive without HRRm, n = 64). Median (range) time from first dose to data cutoff was 4.5 (0.1−8.4), 4.5 (0.1−7.5), and 5.3 (0.3−7.9) mo, respectively. Efficacy outcomes in pts with ≥4 mo follow-up are shown in the Table. Grade 3−4 treatment-related AEs occurred in 60 pts (35.7%); 4 pts (2.4%) discontinued treatment due to treatment-related AE; there were no grade 5 treatment-related AEs. Common (≥15%) treatment-related AEs were nausea (39.3%), anemia (30.4%), and fatigue (15.5%), comparable with monotherapy. Conclusions: Olaparib + pembrolizumab showed promising antitumor activity with manageable safety in pts with a range of advanced HRRm and/or HRD positive solid tumors, especially BRCAm. Enrollment is ongoing. Table. Efficacy OutcomesOlaparib Plus PembrolizumabEfficacy Outcomesa, bBRCAmc (n = 21)HRRmd Without BRCAmc (n = 32)HRD Positivee Without HRRmd (n = 47)HRRmd (n = 53)HRD Positivee (n = 76)ORR,f-h (95% CI)28.6 (11.3 to 52.2)6.3 (0.8 to 20.8)19.1 (9.1 to 33.3)15.1 (6.8 to 27.6)21.1 (12.5 to 31.9)- Tumor types with confirmed responsesCervical, endometrial, prostate, duodenalOvarian and neuroendocrineiOvarian (3), breast, peritoneum, NSCLC, cervicalCervical, endometrial, prostate, duodenal, ovarian, neuroendocrineCervical (2), endometrial, prostate, duodenal, ovarian (4), breast, peritoneum, NSCLC- Tumor types with unconfirmed responsesNSCLC, neuroendocrineNoneNSCLC (2)NSCLC, neuroendocrineNSCLC (3), neuroendocrineDOR,f,j median (range), moNR (0.0+ to 2.6+)4.2 (4.1+ to 4.2)NR (0.0+ to 4.2+)4.2(0.0+ to 4.2)NR (0.0+ to 4.2+)PFS,j median (95% CI), moNR (2.3 to NR)3.3 (2.0 to 4.6)4.1 (2.2 to NR)3.9(2.2 to 6.1)4.1(2.3 to NR)Estimated PFS rate at 3 mo,j %66.250.058.456.059.5NR, not reached.“+” indicates no PD by the time of last disease assessment.aTumor imaging assessed by blinded independent central review per RECIST version 1.1 or Prostate Cancer Working Group-modified RECIST version 1.1bIn pts enrolled ≥4 mo before the data cutoff date (25 September 2020).cDeleterious or suspected deleterious mutations in the BRCA1 and/or BRCA2 genes from the tumor tissue-based Lynparza HRR-HRD assay.dDeleterious or suspected deleterious mutations in at least 1 of 15 prespecified HRR genes (BRCA1, BRCA2, ATM, BARD1, BRIP1, CDK12, CHEK1, CHEK2, FANCL, PALB2, PPP2R2A, RAD51B, RAD51C, RAD51D, and RAD54L) from the tumor tissue-based Lynparza HRR-HRD assay.eDeleterious or suspected deleterious mutation in BRCA1 or BRCA2, or loss of heterozygosity score ≥16 from the tumor tissue-based Lynparza HRR-HRD assay.fIncludes confirmed and unconfirmed responses.gORR (95% CI) in pts with confirmed responses (primary endpoint): BRCAm, 19.0% (5.4%-41.9%); HRRm without BRCAm, 6.3% (0.8%-20.8%); HRD positive without HRRm, 14.9% (6.2%-28.3%); HRRm, 11.3% (4.3%-23.0%); HRD positive, 15.8% (8.4%-26.0%).hNumber of patients with responses: BRCAm, 4 confirmed + 2 unconfirmed; HRRm without BRCAm, 2 confirmed; HRD positive without HRRm, 7 confirmed + 2 unconfirmed; HRRm, 6 confirmed + 2 unconfirmed; HRD positive, 12 confirmed + 4 unconfirmed.iBoth pts had ATM mutation.jFrom Kaplan-Meier method for censored data. Citation Format: Michele Maio, Ronnie Shapira-Frommer, Timothy A. Yap, Tudor Ciuleanu, Henry Gomez, Andrew Hill, Iwona Lugowska, Ozgur Ozyilkan, Karina Vera, Seock-Ah Im, Anna Kryzhanivska, Serhii Lysenko, Michael Schenker, Salomon M. Stemmer, Sanatan Saraf, Razvan Cristescu, PhD, Fan Jin, Alexander Gozman, Miguel Quintela-Fandino. Olaparib plus pembrolizumab in patients with previously treated advanced solid tumors with homologous recombination repair mutation (HRRm) and/or homologous recombination deficiency (HRD): Initial results of the phase 2 KEYLYNK-007 study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT178.

// Jeeyun Lee 1, * , Razvan Cristescu 2, * , Kyoung-Mee Kim 3, * , Kyung Kim 1 , Seung Tae Kim 1 , Se Hoon Park 1 and Won Ki Kang 1 1 Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea 2 Department of Genetics and Pharmacogenomics (GpGx), Merck Research Laboratories, Merck Sharpe & Dohme, Boston, MA, USA 3 Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea * These authors have contributed equally to this work Correspondence to: Se Hoon Park, email: hematoma@skku.edu Keywords: stomach neoplasm, genomics, gene signature, subtypes, mesenchymal Received: March 07, 2017 Accepted: July 18, 2017 Published: August 07, 2017 ABSTRACT Previously, in the Asian Cancer Research Group (ACRG) project, we defined four distinct molecular subtypes in gastric cancer (GC). Mesenchymal (microsatellite stable with epithelial-to-mesenchymal transition phenotype, MSS/EMT) tumors showed the worst prognosis among all the subtypes. To develop a gene signature for predicting mesenchymal subtype GC, we conducted gene expression profiling using a NanoString assay in 70 ACRG specimens. The gene signature was validated in an independent set obtained from the prospective Adjuvant chemoRadioTherapy In Stomach Tumor (ARTIST) trial. The association between the mesenchymal subtype and survival was investigated. After cross-platform concordance test performed in 70 ACRG specimens, a 71-gene MSS/EMT signature was obtained. In the validation set, the gene signature predicted that 20 of 73 (27%) patients had mesenchymal tumors. Patients with mesenchymal subtype had diffuse GC, poorly-differentiated or signet ring cell carcinoma, and were microsatellite stable. The estimated hazard ratio for survival in patients with mesenchymal GC compared to those with non-mesenchymal tumors was 2.262 (95% confidence interval, 1.410 to 3.636; P=0.001). The survival difference remained significant when the subtypes were analyzed according to clinical prognostic parameters. This study suggested that the NanoString-based 71-gene signature for mesenchymal subtype is a strong predictor of the outcome in patients with GC.

Background Somatic KRAS mutations are detected in approximately 15%-30% of lung adenocarcinomas, with regional variation, and are associated with poor prognosis. We explored the prevalence of KRAS mutations and their association with efficacy in participants (pts) with non-squamous NSCLC enrolled in the KEYNOTE-042 study of pembrolizumab monotherapy vs platinum-based chemotherapy as first-line therapy for advanced PD-L1-positive (TPS ≥1%) NSCLC (NCT02220894). Methods KRAS mutational status and tumor mutational burden (TMB) were assessed by whole-exome sequencing (WES) in pts with who had available tumor and matched-normal tissue. This exploratory analysis included descriptive analyses of the correlation between KRAS mutational status and shifts in distributions of TMB and PD-L1 expression and the association of KRAS and KRAS G12C status with efficacy. Results Of the 782 pts with non-squamous histology, 301 (38%) were evaluable by WES and had matched tumor and normal DNA. KRAS mutations were identified in 69 (23%) pts, including 29 (10%) G12C carriers. Pts with vs without KRAS mutation tended to have higher PD-L1 TPS (median [IQR] 60% [10-95] vs 35% [10-80]) and TMB (median [IQR] 191 [129-288] vs 105 [56-226] mut/exome). Outcomes of pembrolizumab and of chemotherapy for pts with and without KRAS mutation and for KRAS G12C carriers are in the table. Of note, CIs were wide given the modest frequency of KRAS mutation and low frequency of KRAS G12C.TableLBA4TableWith Any KRAS MutationWith KRAS G12C MutationWithout Any KRAS MutationPembro Mono-therapy (N = 30)Chemo-therapy (N = 39)Pembro Mono-therapy (N = 12)Chemo-therapy (N = 17)Pembro Mono-therapy (N = 127)Chemo-therapy (N = 105)ORR, % (95% CI)56.7 (37.4-74.5)18.0 (7.5-33.5)66.7 (34.9-90.1)23.5 (6.8-49.9)29.1 (21.4-37.9)21.0 (13.6-30.0)PFS, median, mo (95% CI)12 (8-NR)6 (4-9)15 (10-NR)6 (4-8)6 (4-7)6 (6-8)PFS, HR (95% CI)0.51 (0.29-0.87)0.27 (0.10-0.71)1.00 (0.75-1.34)OS, median, mo (95% CI)28 (23-NR)11 (7-25)NR (23-NR)8 (5-NR)15 (12-24)12 (11-18)OS, HR (95% CI)0.42 (0.22-0.81)0.28 (0.09-0.86)0.86 (0.63-1.18) Conclusion Findings of this descriptive exploratory analysis suggest that pembrolizumab monotherapy should be considered as a standard first-line treatment option for PD-L1-positive advanced non-squamous NSCLC regardless of KRAS mutational status. These findings also suggest that a pembrolizumab-containing regimen is a clinically relevant comparator for studies of KRAS -targeted therapy given as first-line treatment of NSCLC. Clinical trial identification KEYNOTE-042; NCT02220894. Editorial acknowledgement Joanne Tomassini and Melanie Leiby, both of Merck & Co., Inc., Kenilworth, NJ, for writing support. Legal entity responsible for the study Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Funding Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Disclosure R.S. Herbst: Advisory / Consultancy: Abbvie Pharmaceuticals; Advisory / Consultancy: ARMO Biosciences; Advisory / Consultancy, Research grant / Funding (self): AstraZeneca; Advisory / Consultancy: Biodesix; Advisory / Consultancy: Bristol-Myers Squibb; Advisory / Consultancy, Research grant / Funding (self): Eli Lilly and Company; Advisory / Consultancy: EMD Serrano; Advisory / Consultancy: Genentech/Roche; Advisory / Consultancy: Genmab; Advisory / Consultancy: Halozyme; Advisory / Consultancy: Heat Biologics; Advisory / Consultancy: Infinity Pharmaceuticals; Advisory / Consultancy: Loxo Oncology; Advisory / Consultancy, Research grant / Funding (self): Merck & Co., Inc., Kenilworth, NJ, USA; Advisory / Consultancy: Nektar; Advisory / Consultancy: Neon Therapeutics; Advisory / Consultancy: NextCure; Advisory / Consultancy: Novartis; Advisory / Consultancy: Pfizer; Advisory / Consultancy: Sanofi; Advisory / Consultancy: Seattle Genetics; Advisory / Consultancy: Shire PLC; Advisory / Consultancy: Spectrum Pharmaceuticals; Advisory / Consultancy: Symphogen; Advisory / Consultancy: Tesaro; Advisory / Consultancy: Tocagen; Officer / Board of Directors: Junshi Pharmaceuticals. G. Lopes: Research grant / Funding (institution): AstraZeneca; Research grant / Funding (institution): EMD Serono; Research grant / Funding (institution): Merck & Co., Inc.. D.M. Kowalski: Advisory / Consultancy, Research grant / Funding (institution): MSD; Advisory / Consultancy: Boehringer-Ingelheim; Advisory / Consultancy: Roche; Advisory / Consultancy: Pfizer; Advisory / Consultancy: BMS. K. Kasahara: Research grant / Funding (institution): MSD. Y-L. Wu: Advisory / Consultancy, Research grant / Funding (institution): Boehringer-Ingelheim; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Roche; Advisory / Consultancy, Research grant / Funding (institution): MSD; Honoraria (self), Advisory / Consultancy: AstraZeneca; Honoraria (self): Eli Lilly; Honoraria (self): Pierre Fabre; Honoraria (self): Pfizer; Honoraria (self): Sanofi. G. De Castro Jr.: Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Roche; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: AstraZeneca; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution), Travel / Accommodation / Expenses: MSD; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: BMS; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Pfizer; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Merck Serono; Honoraria (self), Honoraria (institution), Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Boehringer-Ingelheim; Honoraria (self), Honoraria (institution): Novartis; Honoraria (institution): Amgen; Honoraria (institution): Astellas. B.C. Cho: Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution): AstraZeneca; Honoraria (self), Advisory / Consultancy: Boehringer Ingelheim; Honoraria (self), Advisory / Consultancy: Roche; Speaker Bureau / Expert testimony: Bristol Myers Squibb; Speaker Bureau / Expert testimony, Research grant / Funding (institution): MSD; Speaker Bureau / Expert testimony, Research grant / Funding (institution): Novartis; Research grant / Funding (institution): Bayer; Research grant / Funding (institution): Yuhan. H.Z. Turna: Research grant / Funding (institution): MSD. R. Cristescu: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. D. Aurora-Garg: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. J. Lunceford: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. J. Kobie: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. M. Ayers: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. M.C. Pietanza: Shareholder / Stockholder / Stock options, Non-remunerated activity/ies: Merck Sharp & Dohme. B. Piperdi: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. T.S.K. Mok: Honoraria (self), Advisory / Consultancy, Leadership role, Research grant / Funding (institution): AstraZeneca; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Boehringer Ingelheim; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): BMS; Advisory / Consultancy, Research grant / Funding (institution): Clovis Oncology; Research grant / Funding (institution): Eisai; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): MSD; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Novartis; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): Pfizer; Research grant / Funding (institution): Roche; Advisory / Consultancy, Research grant / Funding (institution): SFJ Pharmaceuticals; Research grant / Funding (institution): Taiho; Research grant / Funding (institution): Xcovery; Honoraria (self), Advisory / Consultancy: Roche/Genentech; Honoraria (self), Leadership role, Shareholder / Stockholder / Stock options: Hutchinson MedPharma; Honoraria (self): Janssen; Honoraria (self): Takeda; Honoraria (self): Fishawack Facilitate Ltd; Advisory / Consultancy: Eli Lilly; Advisory / Consultancy: Merck Serono; Advisory / Consultancy: ACEA Biosciences Inc.; Advisory / Consultancy: Celgene, Vertex, geneDecode, OncoGenex, Ignyta; Leadership role, Shareholder / Stockholder / Stock options: Sanomics Ltd; Advisory / Consultancy, Shareholder / Stockholder / Stock options: Cirina; Non-remunerated activity/ies, ASCO board of directors: ASCO; Non-remunerated activity/ies, track chair for ESMO 2019: ESMO.

Background KRAS mutations are observed in ∼25% of lung adenocarcinomas, with some studies suggesting it is a prognostic factor in NSCLC. We assessed the prevalence of KRAS mutations and their association with efficacy in an exploratory analysis of the KEYNOTE-189 study of pembrolizumab plus pemetrexed and platinum chemotherapy vs placebo plus chemotherapy as first-line therapy for metastatic non-squamous NSCLC (NCT02578680). Methods Whole-exome sequencing (WES) was used to assess KRAS status and tumor mutational burden (TMB) in participants (pts) who had available tumor and matched-normal tissue. Descriptive analyses of the association of KRAS and KRAS G12C status with efficacy were included as part of this exploratory analysis, as was correlation between KRAS mutational status and shifts in TMB and PD-L1 expression distributions. Results 289 (47%) of 616 pts had evaluable WES data from both tumor and normal DNA. 89 (31%) of 289 pts had KRAS mutation, including 37 (13%) G12C carriers. Pts with vs without KRAS mutations tended to have higher PD-L1 TPS (median [IQR] 30% [1-71] vs 5% [0-60]) and higher TMB (median [IQR] 204 [137-276] vs 141 [85-252] mut/exome). Outcomes of pembrolizumab plus chemotherapy and of placebo plus chemotherapy in pts with and without KRAS mutation and in KRAS G12C carriers are summarized in the table. 95% CIs were wide given the modest frequency of KRAS mutation, particularly KRAS G12C, and the 2:1 randomization that resulted in small populations for placebo plus chemotherapy.TableLBA5TableWith Any KRAS MutationWith KRAS G12C MutationWithout Any KRAS MutationPembro + Chemo (N = 59)Placebo + Chemo (N = 30)Pembro + Chemo (N = 26)Placebo + Chemo (N = 11)Pembro + Chemo (N = 145)Placebo + Chemo (N = 55)ORR, % (95% CI)40.726.750.018.247.610.9(28.1-54.3)(12.3-45.9)(29.9-70.1)(2.3-51.8)(39.2-56.0)(4.1-22.3)PFS, median, mo (95% CI)9 (7-14)5 (5-9)11 (6-18)5 (5-NR)9 (7-14)5 (4-5)PFS, HR (95% CI)0.47 (0.29-0.77)0.48 (0.22-1.06)0.40 (0.29-0.57)OS, median, mo (95% CI)21 (16-NR)14 (8-NR)18 (11-NR)25 (8-NR)23 (19-NR)9 (7-17)OS, HR (95% CI)0.79 (0.45-1.38)1.14 (0.45-2.92)0.55 (0.37-0.81) Conclusion Based on this descriptive exploratory analysis, pembrolizumab plus pemetrexed and a platinum should be a standard first-line treatment for pts with metastatic non-squamous NSCLC regardless of KRAS mutation status. Clinical trial identification KEYNOTE-189, NCT02578680. Editorial acknowledgement Joanne Tomassini and Melanie Leiby, both of Merck & Co., Inc., Kenilworth, NJ, USA, for writing support. Legal entity responsible for the study Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Funding Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Disclosure S. Gadgeel: Advisory / Consultancy: Boehringer-Ingelheim; Advisory / Consultancy: Xcovery; Advisory / Consultancy: AstraZeneca; Advisory / Consultancy: Novocure; Advisory / Consultancy, Travel / Accommodation / Expenses: Genentech/Roche; Advisory / Consultancy: Takeda; Research grant / Funding (institution): Merck Sharp & Dohme; Advisory / Consultancy: Pharmamar. D. Rodriguez-Abreu: Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Roche; Honoraria (self), Speaker Bureau / Expert testimony: AstraZeneca; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: BMS; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Boehringer Ingelheim; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution), Travel / Accommodation / Expenses: MSD; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Eli Lilly; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Pfizer; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Novartis. E. Felip: Advisory / Consultancy: Boehringer Ingelheim; Advisory / Consultancy: Eli Lilly; Advisory / Consultancy: Pfizer; Advisory / Consultancy: Roche; Advisory / Consultancy, Research grant / Funding (institution): Merck Sharp & Dohme; Advisory / Consultancy: Abbvie; Honoraria (self), lecture fees: AstraZeneca; Honoraria (self), lecture fees: Bristol Myers Squibb; Honoraria (self), lecture fees: Novartis. E. Esteban: Travel / Accommodation / Expenses: Pfizer; Travel / Accommodation / Expenses: Roche; Travel / Accommodation / Expenses: AstraZeneca; Travel / Accommodation / Expenses: Novartis; Research grant / Funding (institution): MSD. G. Speranza: Research grant / Funding (institution): MSD. M. Reck: Honoraria (self), Advisory / Consultancy: Amgen; Honoraria (self), Advisory / Consultancy: AstraZeneca; Honoraria (self), Advisory / Consultancy: BMS; Honoraria (self), Advisory / Consultancy: Boehringer Ingelheim; Honoraria (self), Advisory / Consultancy: Celgene; Honoraria (self), Advisory / Consultancy: Merck ; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): MSD; Honoraria (self), Advisory / Consultancy: Eli LIlly; Honoraria (self), Advisory / Consultancy: Pfizer; Honoraria (self), Advisory / Consultancy: Abbvie; Honoraria (self), Advisory / Consultancy: Roche; Honoraria (self), Advisory / Consultancy: Novartis. R. Hui: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): MSD; Honoraria (self), Advisory / Consultancy: AstraZeneca; Advisory / Consultancy: BMS; Honoraria (self), Advisory / Consultancy: Novartis; Honoraria (self), Advisory / Consultancy: Roche; Advisory / Consultancy: Eli Lilly. M. Boyer: Honoraria (self), Honoraria (institution), Research grant / Funding (institution): AstraZeneca; Honoraria (institution), Research grant / Funding (institution): MSD; Honoraria (institution): Roche; Research grant / Funding (institution): Amgen; Research grant / Funding (institution): BMS; Research grant / Funding (institution): Novartis; Research grant / Funding (institution): Beigene; Research grant / Funding (institution): Ascentage Pharma; Research grant / Funding (institution): Pfizer; Research grant / Funding (institution): Roche/Genentech; Research grant / Funding (institution): Janssen. E.B. Garon: Honoraria (self): Dracen; Honoraria (self), Research grant / Funding (institution): EMD Serono; Honoraria (self), Research grant / Funding (institution): Novartis; Research grant / Funding (institution): AstraZeneca; Research grant / Funding (institution): BMS; Research grant / Funding (institution): Genentech; Research grant / Funding (institution): Eli Lilly; Research grant / Funding (institution): Dynavax; Research grant / Funding (institution): Iovance; Research grant / Funding (institution): Mirati; Research grant / Funding (institution): Neon; Research grant / Funding (institution): MSD. H. Horinouchi: Honoraria (self), Advisory / Consultancy: Eli LIlly; Honoraria (self), Research grant / Funding (institution): BMS; Honoraria (self), Research grant / Funding (institution): ONO; Honoraria (self), Advisory / Consultancy: AstraZeneca; Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): MSD; Honoraria (self): Kyowa-Kirin; Honoraria (self): Taiho; Research grant / Funding (institution): Daiichi-Sankyo; Research grant / Funding (institution): Abbvie; Research grant / Funding (institution): Chugai/Roche; Research grant / Funding (institution): Genomic Health. R. Cristescu: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. D. Aurora-Garg: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. J. Lunceford: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. J. Kobie: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. M. Ayers: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. B. Piperdi: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. M.C. Pietanza: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck Sharp & Dohme. M.C. Garassino: Advisory / Consultancy, Research grant / Funding (institution): MSD; Research grant / Funding (institution): Eli Lilly; Research grant / Funding (institution): Boehringer Ingelheim; Research grant / Funding (institution): Otsuka Pharma; Advisory / Consultancy, Research grant / Funding (institution): AstraZeneca; Research grant / Funding (institution): Novartis; Research grant / Funding (institution): BMS; Research grant / Funding (institution): Roche; Research grant / Funding (institution): Pfizer; Research grant / Funding (institution): Celgene; Advisory / Consultancy: Incyte; Advisory / Consultancy: Takeda; Advisory / Consultancy: Inivata; Advisory / Consultancy: Takeda; Research grant / Funding (institution): Tiziana Sciences; Research grant / Funding (institution): Clovis; Research grant / Funding (institution): Merck Serono; Research grant / Funding (institution): Bayer; Advisory / Consultancy, Research grant / Funding (institution): GSK; Advisory / Consultancy: Sanofi-Aventis; Research grant / Funding (institution): Spectrum Pharmaceuticals.

This study reports the establishment of a bone marrow mononuclear cell (BMMC) 3D culture model and the application of this model to define sensitivity and resistance biomarkers of acute myeloid leukaemia (AML) patient bone marrow samples in response to Cytarabine (Ara‐C) treatment. By mimicking physiological bone marrow microenvironment, the growth conditions were optimized by using frozen BMMCs derived from healthy donors. Healthy BMMCs are capable of differentiating into major hematopoietic lineages and various types of stromal cells in this platform. Cryopreserved BMMC samples from 49 AML patients were characterized for ex vivo growth and sensitivity to Ara‐C. RNA sequencing was performed for 3D and 2D cultures to determine differential gene expression patterns. Specific genetic mutations and/or gene expression signatures associated with the ability of the ex vivo expansion and response to Ara‐C were elucidated by whole‐exome and RNA sequencing. Data analysis identified unique gene expression signatures and novel genetic mutations associated with sensitivity to Ara‐C treatment of proliferating AML specimens and can be used as predictive therapeutic biomarkers to determine the optimal treatment regimens. Furthermore, these data demonstrate the translational value of this ex vivo platform which should be widely applicable to evaluate other therapies in AML.

INTRODUCTION: Immunotherapy targeting the programmed cell death protein–1 (PD-1) axis elicits durable antitumor responses in multiple cancer types. However, clinical responses vary, and biomarkers predictive of response may help to identify patients who will derive the greatest therapeutic benefit. Clinically validated biomarkers predictive of response to the anti–PD-1 monoclonal antibody pembrolizumab include PD-1 ligand 1 (PD-L1) expression in specific cancers and high microsatellite instability (MSI-H) regardless of tumor type. Tumor mutational burden (TMB) and T cell–inflamed gene expression profile (GEP) are emerging predictive biomarkers for pembrolizumab. Both PD-L1 and GEP are inflammatory biomarkers indicative of a T cell–inflamed tumor microenvironment (TME), whereas TMB and MSI-H are indirect measures of tumor antigenicity generated by somatic tumor mutations. However, the relationship between these two categories of biomarkers is not well characterized. RATIONALE: This study assessed the potential for TMB and a T cell–inflamed GEP to jointly predict clinical response to pembrolizumab in >300 patient samples with advanced solid tumors and melanoma across 22 tumor types from four KEYNOTE clinical trials. To assess the individual and joint clinical utility of TMB and GEP, patients were stratified in four biomarker–defined clinical response groups [GEP low and TMB low (GEP(lo) TMB(lo)), GEP low and TMB high (GEP(lo) TMB(hi)), GEP(hi) TMB(lo), and GEP(hi) TMB(hi)] based on predefined cutoffs for TMB and GEP. These patient–defined biomarker groups were further used to guide transcriptome and exome analyses of tumors in a large molecular database [The Cancer Genome Atlas (TCGA)] (n = 6384 tumors) to identify targetable patterns of biology that may modulate response and resistance. RESULTS: TMB and GEP exhibited only modest correlation and were independently predictive of response across the KEYNOTE clinical datasets. We found that objective response rates were strongest in patients with GEP(hi) TMB(hi) (37 to 57%), moderate in those with GEP(hi) TMB(lo) (12 to 35%) and GEP(lo) TMB(hi) (11 to 42%), and reduced or absent in those with GEP(lo) TMB(lo) (0 to 9%) (see the figure). Additionally, longer progression–free survival times were seen in patients with higher levels of both TMB and GEP. Findings were comparable when TMB and PD-L1 expression were jointly assessed. Within TCGA database, GEP and TMB again had a low correlation, demonstrating the potential to jointly stratify transcriptomic and genomic features across cancer types. Specific gene expression patterns reflective of TME biology showed significant associations with TMB, GEP, or both. In particular, gene set enrichment analysis identified proliferative and stromal, myeloid, and vascular biology corresponding to specific TMB-defined subgroups within GEP(hi) tumors. In TMB(hi) tumors, indication-dependent somatic DNA alterations in key cancer driver genes showed a strong negative association with GEP. CONCLUSION: This analysis shows that TMB and inflammatory biomarkers (T cell–inflamed GEP and PD-L1 expression) can jointly stratify human cancers into groups with different clinical responses to pembrolizumab monotherapy and identify patterns of underlying, targetable biology related to these groups. TMB and inflammatory biomarkers independently predict response and may capture distinct features of neoantigenicity and T cell activation, respectively. This approach may provide a precision medicine framework for rationally constructing and evaluating anti–PD-1– and/or –PD-L1–based combination therapy regimens.

155 Background: Metastatic castration resistant prostate cancer (mCRPC) is a heterogeneous disease in which molecular stratification is needed to improve clinical outcomes. Targeting programmed cell death protein 1 (PD-1) elicits durable antitumor responses in multiple cancer types. Putative biomarkers predictive of response to anti-PD-1 therapies include programmed death-ligand-1 (PD-L1), tumour mutational burden (TMB), T cell-inflamed 18-gene expression profile (GEP), and DNA repair defects. Objective: To study potential biomarkers of response in mCRPC to anti-PD-1 therapy (PD-L1, GEP, mismatch repair (MMR) protein), other biomarkers of interest including BRCA2, PALB2, CDK12, PTEN, TP53, SOX2, and to determine association with clinical outcomes. Methods: The study population included 100 men with mCRPC treated at the Royal Marsden Hospital with available fresh mCRPC biopsy tissue. All men had received at least one line of therapy with a next generation hormonal agent and one line of taxane-based chemotherapy. Clinical characteristics and outcomes were extracted from medical records. mCRPC biopsies were assayed by whole exome sequencing (WES), targeted next generation sequencing (NGS), RNA sequencing (RNAseq), GEP score (Nanostring), PD-L1 immunohistochemistry (IHC; DAKO 22C3 assay), SOX2 IHC, ATM IHC. Correlations among these biomarkers and clinical outcomes were assessed. Results: The median age of patients was 68.0 years; 46/84 (54.8%) had de novo metastatic disease at diagnosis and 24/100 (24.0%) patients had visceral disease. Median follow-up from mCRPC biopsy was 56.2 months. The prevalence of loss of protein expression by IHC and/or pathogenic mutation by NGS of MMR was 7/100 (7%). Loss of PTEN and ATM by IHC was 29/100 (29%) and 13/100 (13%) respectively. SOX2 expression (defined as expression in >5% of cells) was 27/100 (27%). The prevalence of TP53 mutation was 25/100 (25%); deleterious alterations of BRCA2 was 9/100 (9%), CDK12 3/100 (3%) and PALB2 1/100 (1%). PDL1 and GEP results were available for 70 and 93 samples respectively. PD-L1 was expressed (combined positive score ≥1) in 24 (33%) mCRPC biopsies; 23 (26%) had high GEP scores (> -0.318). PD-L1 and GEP expression were positively correlated (Phi 0.63). No other biomarkers showed strong correlations. Of 5 samples with MMR loss for which PD-L1 was available, 1 (20%) had PD-L1 ≥1; one of the CDK12 samples had PD-L1 ≥1 (33%). 0/6 BRCA2 mutated biopsies expressed PD-L1 (0%). Based on univariate analysis, PD-L1 expression [HR: 1.75 (1.00;3.06), p=0.045], high GEP score [HR: 2.00 (1.18;3.39), p=0.0083] and SOX2 expression [HR: 1.81 (1.12;2.94), p=0.015] were associated with worse overall survival (OS). No other biomarkers associated with OS. Conclusions: PD-L1 IHC expression was detected in 33% of mCRPC patients and associated with high GEP score. Higher PD-L1, GEP, and SOX2 expression were associated with poor prognosis.

Targeting surface receptors overexpressed on cancer cells is one way to specifically treat cancer versus normal cells. Vintafolide (EC145), which consists of folate linked to a cytotoxic small molecule, desacetylvinblastine hydrazide (DAVLBH), takes advantage of the overexpression of folate receptor (FR) on cancer cells. Once bound to FR, vintafolide enters the cell by endocytosis, and the reducing environment of the endosome cleaves the linker, releasing DAVLBH to destabilize microtubules. Vintafolide has shown efficacy and improved tolerability compared with DAVLBH in FR-positive preclinical models. As the first FR-targeting drug to reach the clinic, vintafolide has achieved favorable responses in phase II clinical trials in FR-positive ovarian and lung cancer. However, some FR-positive patients in these clinical trials do not respond to vintafolide. We sought to identify potential biomarkers of resistance to aid in the future development of this and other FR-targeting drugs. Here, we confirm that high P-glycoprotein (P-gp) expression was the strongest predictor of resistance to DAVLBH in a panel of 359 cancer cell lines. Furthermore, targeted delivery of DAVLBH via the FR, as in vintafolide, fails to overcome P-gp–mediated efflux of DAVLBH in both in vitro and in vivo preclinical models. Therefore, we suggest that patients whose tumors express high levels of P-gp be excluded from future clinical trials for vintafolide as well as other FR-targeted therapeutics bearing a P-gp substrate. Mol Cancer Ther; 15(8); 1998–2008. ©2016 AACR.

Gene expression profiling from glioblastoma (GBM) patients enables characterization of cancer into subtypes that can be predictive of response to therapy. An integrative analysis of imaging and gene expression data can potentially be used to obtain novel biomarkers that are closely associated with the genetic subtype and gene signatures and thus provide a noninvasive approach to stratify GBM patients. In this retrospective study, we analyzed the expression of 12,042 genes for 558 patients from The Cancer Genome Atlas (TCGA). Among these patients, 50 patients had magnetic resonance imaging (MRI) studies including diffusion weighted (DW) MRI in The Cancer Imaging Archive (TCIA). We identified the contrast enhancing region of the tumors using the pre- and post-contrast T1-weighted MRI images and computed the apparent diffusion coefficient (ADC) histograms from the DW-MRI images. Using the gene expression data, we classified patients into four molecular subtypes, determined the number and composition of genes modules using the gap statistic, and computed gene signature scores. We used logistic regression to find significant predictors of GBM subtypes. We compared the predictors for different subtypes using Mann–Whitney U tests. We assessed detection power using area under the receiver operating characteristic (ROC) analysis. We computed Spearman correlations to determine the associations between ADC and each of the gene signatures. We performed gene enrichment analysis using Ingenuity Pathway Analysis (IPA). We adjusted all p values using the Benjamini and Hochberg method. The mean ADC was a significant predictor for the neural subtype. Neural tumors had a significantly lower mean ADC compared to non-neural tumors (\(p=0.005\)), with mean ADC of \(1.07\pm 0.16 \times 10^{-3}\) and \(1.23\pm 0.16\times 10^{-3}\; \mathrm{{mm^2/s}}\) for neural and non-neural tumors, respectively. Mean ADC showed an area under the ROC of 0.75 for detecting neural tumors. We found eight gene modules in the GBM cohort. The mean ADC was significantly correlated with the gene signature related with dendritic cell maturation (\(\rho =-0.51\), \(p=0.001\)). Mean ADC could be used as a biomarker of a gene signature associated with dendritic cell maturation and to assist in identifying patients with neural GBMs, known to be resistant to aggressive standard of care.

Background: STK11 (also known as LKB1) and KEAP1 mutations have been associated with chemoresistance and poor outcomes and shown to be more frequent in PD-L1-negative tumors with high tumor mutational burden (TMB). We performed an exploratory analysis of KEYNOTE-042 (NCT02220894) to assess the prevalence of STK11 and KEAP1 mutations and their association with efficacy. Methods: STK11 and KEAP1 status and TMB were assessed by whole-exome sequencing (WES) in tumor tissue and matched-normal DNA. PD-L1 was assessed with the PD-L1 IHC 22C3 pharmDx assay. Descriptive analyses were performed to assess the correlation of STK11 and KEAP1 status with TMB and PD-L1 expression distributions and the association between STK11 and KEAP1 status and efficacy. Results: 429/1274 pts (34%) had evaluable WES data from tumor and normal DNA. STK11 and KEAP1 mutations were seen in 33 (8%) and 64 (15%) pts, respectively; 12 pts (3%) had both mutations. Pts with STK11 mutation tended to have a lower PD-L1 TPS than pts without (median [IQR] 15% [3-50] vs 40% [10-80]); TPS tended to be similar in pts with vs without KEAP1 mutation (40% [10-81] vs 40% [10-80]). TMB score tended to be higher in pts with vs without STK11 (median [IQR] 191 [104-272] vs 146 [72-253]) or KEAP1 (183 [114-283] vs 142 [68-252]) mutation. ORR, PFS, and OS with pembrolizumab were similar in pts with vs without STK11 or KEAP1 mutation; chemotherapy efficacy was lower in pts with vs without STK11 mutation (Table). Pembrolizumab was associated with better outcomes than chemotherapy regardless of STK11 or KEAP1 status (Table). 95% CIs were wide given the modest frequency of STK11 and KEAP1 mutations. Conclusions: The findings of this exploratory analysis suggest pembrolizumab monotherapy should be considered a standard first-line treatment option for advanced PD-L1-positive NSCLC regardless of STK11 or KEAP1 status. STK11KEAP1With MutationWithout MutationWith MutationWith MutationPembroChemoPembroChemoPembroChemoPembroChemo(n = 16)(n = 17)(n = 214)(n = 182)(n = 31)(n = 33)(n = 199)(n = 166)ORR, % (95% CI)31 (11-59)6 ( Citation Format: Byoung Chul Cho, Gilberto Lopes, Dariusz M. Kowalski, Kazuo Kasahara, Yi-Long Wu, Gilberto Castro, Hande Z. Turna, Razvan Cristescu, Deepti Aurora-Garg, Andrey Loboda, Jared Lunceford, Julie Kobie, Mark Ayers, M. Catherine Pietanza, Bilal Piperdi, Tony S. Mok. Relationship between STK11 and KEAP1 mutational status and efficacy in KEYNOTE-042: pembrolizumab monotherapy versus platinum-based chemotherapy as first-line therapy for PD-L1-positive advanced NSCLC [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT084.

Introduction: KEYNOTE-001 (NCT01295827) was a phase 1 study of pembro in pts with locally advanced or metastatic melanoma (parts B and D). KEYNOTE-006 (NCT01866319) was a randomized phase 3 study of pembro vs ipilimumab in pts with advanced melanoma. We explored potential relationships between key tumor microenvironment canonical signatures beyond T cell-inflamed gene expression profile (GEP) and response/resistance to pembro monotherapy in pts with melanoma. Methods: In pembro-treated, ipilimumab-naive pts from KEYNOTE-001 and KEYNOTE-006 with available RNA-sequencing and clinical data (n = 476), we analyzed association of 9 non-T cell-inflamed GEP canonical signatures (angiogenesis, gMDSC, glycolysis, hypoxia, Myc, proliferation, RAS, stromal/EMT/TGFβ, WNT) with clinical outcomes. Signatures were defined with TCGA and Moffitt databases (independent of any pembro trial) using a correlation algorithm to select individual genes for membership in the canonical signature based on correlation with reference signatures identified in literature or internal work. Relationships between RNA signatures and clinical outcomes were assessed using 2 models: 1 adjusted for ECOG PS and batch effect and 1 adjusted for T cell-inflamed GEP to understand the additional explanatory value of a non-T cell-inflamed GEP signature for clinical outcomes. P values were adjusted for multiplicity; significance was predefined at α = 0.05. Database cutoffs for clinical data: 11/27/2017 (KEYNOTE-001), 12/4/2017 (KEYNOTE-006). Results: T cell-inflamed GEP was statistically significantly associated with response to pembro (P < 0.0001). No canonical signatures showed statistically significant association with response/resistance to pembro after multiplicity adjustment when adjusting for T cell-inflamed GEP, ECOG PS, and batch effect. Without adjusting for T cell-inflamed GEP, Myc signature was the only signature identified as statistically significantly associated with response to pembro in the postulated direction of negative association. Prolonged OS, but not PFS, was observed in pts with a lower Myc signature. Myc signature did not show independent predictive value beyond T cell-inflamed GEP, indicating that interferon γ-related T-cell inflammation has a more dominant impact on immunotherapy efficacy than the Myc signature and other gene sets in immune-suppressive axes. Conclusions: In this exploratory analysis, no canonical signatures showed statistical significance after adjusting for T cell-inflamed GEP. Although observed only without adjusting for T cell-inflamed GEP, Myc signature was negatively associated with response in ipilimumab-naive pts with melanoma receiving pembro monotherapy. Citation Format: Adil Daud, Matteo S. Carlino, Antoni Ribas, Ana Arance, Jean-Jacques Grob, James Larkin, Georgina V. Long, Jacob Schachter, Andrea L. Webber, Clemens Krepler, Chunsheng Zhang, Jared Lunceford, Razvan Cristescu, Qing Zhao, Junshui Ma, Caroline Robert. Evaluation of RNA-sequencing signatures with response to pembrolizumab (pembro) monotherapy in ipilimumab-naive patients (pts) with melanoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2009.

Background: We retrospectively assessed the relationship between TMB and outcomes in patients (pts) with previously treated advanced solid tumors enrolled in 12 trials that evaluated pembro monotherapy. Methods: WES was performed on DNA extracted from pretreatment tumor samples and matched normal DNA from pts in KEYNOTE-001, 002, 010, 012, 028, 045, 055, 059, 061, 086, 100, and 199 who received ≥1 prior therapy and ≥1 dose of study therapy. ORR, DOR, PFS, and OS were assessed for pts with TMB ≥175 mut/exome and 10 pts, in a pooled set of tumor types with ≤10 pts, and regardless of PD-L1 expression assessed by IHC. In the randomized studies, pembro improved outcomes vs chemo in pts with TMB ≥175 mut/exome (Table). TMB was consistently associated with ORR (P ≤ 0.016), PFS (P ≤ 0.005), and OS (P ≤ 0.029) for pembro but not for chemo (P ≥ 0.340, ≥0.643, and ≥0.174, respectively). Conclusions: TMB ≥175 mut/exome assessed by WES was associated with clinically meaningful improvement in efficacy of pembro monotherapy and improved outcomes for pembro vs chemo in pts with previously treated advanced solid tumors. TMB was associated with outcomes of pembro but not of chemo. These data suggest TMB may predict efficacy of pembro monotherapy, regardless of tumor type. Table.Efficacy by TMB ScoreTMB ≥175 mut/exomeTMB Citation Format: Razvan Cristescu, Deepti Aurora-Garg, Andrew Albright, Lei Xu, Xiao Qiao Liu, Andrey Loboda, Lixin Lang, Fan Jin, Alexandra Snyder, Jared Lunceford. Association between tumor mutational burden (TMB) assessed by whole-exome sequencing (WES) and outcomes of pembrolizumab (pembro) monotherapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-261.

Background: Mutations in the tumor suppressor genes STK11 (also known as LKB1) and KEAP1 have been associated with poorer clinical outcomes in patients (pts) with NSCLC. In an exploratory analysis, we assessed the prevalence of STK11 and KEAP1 mutations and their association with efficacy in KEYNOTE-189 (NCT02578680). Methods: STK11 and KEAP1 status and tumor mutational burden (TMB) were assessed by whole-exome sequencing (WES) in pts who had available tumor and matched-normal tissue. PD-L1 was assessed by the PD-L1 IHC 22C3 pharmDx assay. The association of STK11 and KEAP1 status with efficacy and their correlation with TMB and PD-L1 expression distributions were evaluated descriptively. Results: WES data from both tumor and normal DNA were evaluable for 289 (47%) of 616 pts, of whom 54 (19%) had an STK11 mutation and 68 (24%) had a KEAP1 mutation; 29 (10%) had both STK11 and KEAP1 mutations. PD-L1 TPS tended to be lower in pts with vs without STK11 mutation (median [IQR] 0% [0-16] vs 15% [0-75]), whereas TMB score tended to be higher in pts with mutation (209 [132-265] vs 146 [89-264]). Similar patterns were seen for pts with vs without KEAP1 mutation (PD-L1 TPS: 1% [0-13] vs 20% [0-75]; TMB: 173 [124-267] vs 147 [89-263]). Although ORR of pembrolizumab plus chemotherapy was lower and PFS and OS shorter in pts with vs without STK11 and KEAP1 mutation, pembrolizumab plus chemotherapy was associated with numerically better outcomes than placebo plus chemotherapy regardless of mutation status (Table). 95% CIs were wide given the modest mutation frequency and the 2:1 randomization in favor of pembrolizumab plus chemotherapy. Conclusions: Data from this exploratory analysis support use of pembrolizumab plus pemetrexed and platinum as standard first-line therapy for pts with metastatic nonsquamous NSCLC regardless of STK11 or KEAP1 status. STK11KEAP1With MutationWithout MutationWith MutationWithout MutationPembro + ChemoPlacebo + ChemoPembro + ChemoPlacebo + ChemoPembro + ChemoPlacebo + ChemoPembro + ChemoPlacebo + Chemo(n = 36)(n = 18)(n = 168)(n = 67)(n = 45)(n = 23)(n = 159)(n = 62)ORR, % (95% CI)31 (16-48)17 (4-41)49 (41-57)16 (8-27)36 (22-51)17 (5-39)48 (40-56)16 (8-28)PFS, median, mo (95% CI)6 (4-9)5 (5-9)10 (8-14)5 (5-5)5 (4-11)5 (5-9)10 (8-14)5 (5-5)PFS, HR (95% CI)0.81 (0.44-1.47)0.38 (0.27-0.52)0.65 (0.38-1.12)0.38 (0.28-0.53)OS, median, mo (95% CI)17 (5-NR)8 (7-NR)23 (20-NR)12 (8-25)13 (7-NR)9 (7-NR)24 (20-NR)12 (8-NR)OS, HR (95% CI)0.75 (0.37-1.50)0.59 (0.41-0.85)0.81 (0.44-1.49)0.57 (0.39-0.84) Citation Format: Shirish M. Gadgeel, Delvys Rodriguez-Abreu, Enriqueta Felip, Emilio Esteban, Giovanna Speranza, Martin Reck, Rina Hui, Michael Boyer, Edward B. Garon, Hidehito Horinouchi, Razvan Cristescu, Deepti Aurora-Garg, Andrey Loboda, Jared Lunceford, Julie Kobie, Mark Ayers, Bilal Piperdi, M. Catherine Pietanza, Marina C. Garassino. Pembrolizumab plus pemetrexed and platinum vs placebo plus pemetrexed and platinum as first-line therapy for metastatic nonsquamous NSCLC: analysis of KEYNOTE-189 by STK11 and KEAP1 status [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-397.

1013 Background: In the randomized, open-label, phase 3 KEYNOTE-119 study (NCT02555657) , OS was not significantly different with pembro monotherapy versus chemo in second- or third-line settings for mTNBC; however, the pembro treatment effect increased with increasing PD-L1 enrichment. We evaluated the association of TMB with efficacy of pembro monotherapy versus chemo in patients with previously treated mTNBC. Methods: Patients with centrally confirmed TNBC and 1 or 2 prior systemic treatments for metastatic disease were enrolled. Patients were randomly assigned 1:1 to pembro 200 mg Q3W or single-agent chemo per investigator’s choice of capecitabine, eribulin, gemcitabine, or vinorelbine. Association of TMB, as measured by FoundationOne CDx (Foundation Medicine), with response was an exploratory objective evaluated using receiver operator characteristic (ROC) analysis, logistic regression (ORR), and Cox regression (OS; PFS) within treatment arms; estimates of efficacy based on TMB cutpoint used a prespecified cutpoint of 10 mut/Mb. Results: TMB data were available for 253/601 (42.1%) treated patients (pembro, n = 132; chemo, n = 121); baseline characteristics were similar to that of the overall study population. One-sided P values for the association of TMB and clinical outcomes in pembro-treated patients were 0.154 for ORR, 0.014 for PFS, and 0.018 for OS; the area under the ROC curve ([AUROC] 95% CI) for predicting ORR was 0.58 (0.43-0.73). Two-sided P values for the association of TMB and clinical outcomes in chemo-treated patients were 0.114 for ORR, 0.478 for PFS, and 0.906 for OS; AUROC (95% CI) was 0.43 (0.27-0.59). Twenty-six patients had TMB ≥10 mut/Mb. Thus, the prevalence of TMB ≥10 mut/Mb was ~10%. Outcomes based on TMB cutpoint are reported in the Table. Conclusions: Data from this exploratory analysis from KEYNOTE-119 suggest a potential positive association between TMB and clinical benefit with pembro but not chemo in patients with mTNBC. Although precision is limited by sample size and the number of patients with TMB ≥10 mut/Mb, ORR and HRs for OS suggested a trend towards increased benefit with pembro versus chemo in patients with TMB ≥10 mut/Mb. Clinical trial information: NCT02555657 . [Table: see text]

5526 Background: In the phase II KEYNOTE-199 study (NCT02787005), pembrolizumab monotherapy demonstrated antitumor activity in pts with docetaxel-refractory mCRPC (n = 258). Here we evaluated the association between prespecified molecular biomarkers and clinical outcomes. Methods: Cohorts 1 (C1) and 2 (C2) enrolled pts with RECIST-measurable PD-L1–positive (combined positive score [CPS] ≥1 using immunohistochemistry) and PD-L1–negative (CPS

9521 Background: In a previous analysis of KEYNOTE-189 (NCT02578680), we showed that tissue TMB (tTMB) assessed by whole-exome sequencing was not significantly associated with efficacy in either arm and that pembro + chemo improved outcomes vs placebo + chemo in both the tTMB ≥175 and tTMB < 175 mut/exome subgroups. Here, we explored the association of bTMB with efficacy in KEYNOTE-189. Methods: 616 patients (pts) were randomized 2:1 to pembro + chemo or placebo + chemo. bTMB was assessed in cfDNA using the Guardant Health Omni assay. Association of bTMB (continuous square root transformed) with outcomes in each arm was assessed using Cox proportional hazards models (OS, PFS) and logistic regression (ORR) adjusted for ECOG PS; statistical significance was determined at the 0.05 level without multiplicity adjustment. The clinical utility of bTMB on outcomes was assessed using the cutoff that most closely approximated the 175 mut/exome tTMB cutoff as determined by AUROC analysis. Data cutoff was 21 Sep 2018. Results: 235 (38%) treated pts had evaluable tTMB and bTMB: 160 in the pembro + chemo arm and 75 in the placebo + chemo arm. bTMB as a continuous variable was not significantly associated with OS or ORR for pembro + chemo (one-sided P = .229 and .051) or placebo + chemo (two-sided P = .641 and .069); bTMB was significantly associated with PFS in the pembro + chemo arm (one-sided P = .015) but not the placebo + chemo arm (two-sided P = .058). bTMB and tTMB scores were moderately correlated (r = .61). The bTMB cutoff that most closely approximated tTMB 175 mut/exome was 15 mut/Mb (AUROC 0.81, 95% CI 0.75-0.86). 178 (76%) pts had concordant bTMB and tTMB results—101 low and 77 high by both—whereas 57 (24%) had discordant results—21 high bTMB but low tTMB, 36 low bTMB but high tTMB. Pembro + chemo improved OS, PFS, and ORR vs placebo + chemo for bTMB ≥15 and < 15 mut/exome (Table). Conclusions: Similar to previous findings based on tTMB, bTMB has limited clinical utility in the setting of pembro with pemetrexed and platinum given as first-line therapy for metastatic nonsquamous NSCLC. Clinical trial information: NCT02578680 . [Table: see text]

5024 Background: We assessed the association of baseline RNA-sequencing–based gene expression signatures and DNA alterations with response or resistance to pembrolizumab in patients with advanced renal cell carcinoma in cohorts A (clear cell; n = 110) and B (non-clear cell; n = 165) of the phase 2 KEYNOTE-427 study (NCT02853344). Methods: Using RNA-sequencing, we analyzed the association of gene expression signatures (18-gene T-cell–inflamed gene expression profile [GEP]; 10 non–T-cell–inflamed GEP canonical signatures [angiogenesis, gMDSC, glycolysis, hypoxia, mMDSC, MYC, proliferation, RAS, stromal/EMT/TGFβ, WNT]) quantifying tumor microenvironment elements (TME) with objective response rate (ORR) and progression-free survival (PFS). Canonical signatures were derived from 2 databases (TCGA, Moffit) using an algorithm that included genes based on their correlation to reference signatures in the literature. Signature definitions were finalized before linking to the clinical data, and significance was prespecified at 0.10 given the potential for limited power. Canonical signatures were analyzed through regression testing of response for association with consensus signatures after adjusting for T-cell–inflamed GEP and International Metastatic RCC Database Consortium scores in the model. P values were adjusted for multiplicity. Using whole exome sequencing, we also summarized the association of renal cell carcinoma driver gene mutations with ORR. Clinical data cutoff: Jan 30, 2019. Results: Patient characteristics for this analysis were comparable to the overall population. In cohort A, T-cell–inflamed GEP (n = 78) was statistically significantly associated with a better ORR ( P = 0.021; AUROC = 0.65) but not PFS ( P = 0.116). No other TME canonical signatures showed a correlation with ORR or PFS. ORR was estimated for mutations (Table). Conclusions: RNA-sequencing–based, T-cell–inflamed GEP was associated with ORR in patients with clear cell renal cell carcinoma receiving first-line pembrolizumab. Precision was limited by sample size for estimating ORR by specific gene mutation status. Evaluation of tissue-based biomarkers in larger studies are planned. Biomarker analyses from patients in cohort B will also be presented. Clinical trial information: NCT02853344 . [Table: see text]

4512 Background: KEYNOTE-061 (NCT02370498) was a randomized, open-label, phase 3 study of pembrolizumab vs paclitaxel in patients with advanced gastric or gastroesophageal junction adenocarcinoma with tumor progression after first-line therapy (N =592). We explored the association of tissue tumor mutational burden (tTMB) status and clinical outcomes in patients with GC enrolled in KEYNOTE-061, including the relationship with PD-L1 combined positive score (CPS) and microsatellite instability-high (MSI-H) status. Methods: In patients from KEYNOTE-061 with evaluable tumor and matched normal whole exome sequencing (WES) data (N = 420; pembrolizumab, 218; paclitaxel, 202), the association of tTMB (continuous log10 scale) with confirmed ORR and PFS by blinded central radiology review per RECIST v1.1, and OS was evaluated within each treatment arm using logistic regression (ORR) and Cox proportional hazards regression (PFS; OS). The clinical utility of tTMB was assessed using the prespecified cutoff of 175 mut/exome. Clinical data cutoff: October 26, 2017. Results: tTMB was significantly associated (α=0.05) with ORR, PFS, and OS in patients treated with pembrolizumab (one-sided P0.600). The area under the receiver operating characteristics curve for tTMB and response (pembrolizumab vs paclitaxel) was 0.68 (95% CI, 0.56-0.81) vs 0.51 (95% CI, 0.39-0.63). Patient outcomes by tTMB cutoff are reported in Table. There was low correlation between tTMB and PD-L1 CPS in both treatment arms (r

The programmed death receptor ligand 1 (PD-L1) immunohistochemistry (IHC) 22C3 pharmDx assay is a widely used selection method for pembrolizumab treatment in gastric cancer (GC) patients, especially in the U.S. The present study investigated the relationship between PD-L1 expression and the clinical features, molecular markers, and molecular subtypes of GC.PD-L1 expression was assessed based on combined positive score (CPS) using PD-L1 IHC 22C3 pharmDx in the Asian Cancer Research Group (ACRG) GC cohort (N = 300), which has been previously genomically profiled. PD-L1 positivity was defined as PD-L1 CPS ≥ 1. The association between PD-L1 expression and clinical features, tumor burden, and molecular subtypes (ACRG and The Cancer Genome Atlas [TCGA]) was analyzed.Of the 300 tumors, 178 (59.3 %) had PD-L1 CPS ≥ 1 and 122 (40.7 %) had PD-L1 CPS1. PD-L1 CPS ≥ 1 was significantly associated with stage I tumor (P = 0.022), high microsatellite instability (MSI-H) (P0.001), Epstein-Barr virus (EBV) positivity (P = 0.008), and positive Helicobacter pylori status (P = 0.001). PD-L1 CPS ≥ 1 was observed in 96/193 (49.7 %) EBV-negative/microsatellite stable (MSS) tumors. In gene expression profiling, PD-L1 CPS was highly correlated with mutational load (P0.001) as well as EBV (P0.001) and MSI subtypes (P0.001); 27/300 (9%) GC patients had a very high PD-L1 (≥ 20) score (MSI-H, n = 10; EBV, n = 6; and non-EBV/MSS, n = 11). OS was longer in patients with PD-L1 CPS ≥ 1 tumors than in those with PD-L1 CPS1 tumors (median OS not reached vs. 40 months; P = 0.008; log-rank test).PD-L1 is expressed in 59.3 % of GC patients and is associated with MSI and EBV positivity. These results provide a basis for identifying GC patients who may benefit from anti-PD-1/PD-L1 therapy.

Mining immunotherapy clinical trials Clinical trial data can provide a wealth of information about how drugs work. Yet such information often belongs to pharmaceutical companies and is rarely accessible to the scientific community at large. Cristescu et al. provide exploratory analysis of a cancer genomics dataset, collected from four separate clinical trials of Merck's PD-1 immunotherapy drug, pembrolizumab. This informative public resource examines more than 300 patient samples representing 22 different tumor types. Two widely used signatures that currently predict immunotherapy response are tumor mutational burden and a “hot” T cell–inflamed microenvironment. The study analyzed these two proposed biomarkers in combination to see what predictive clinical utility they may hold. Science , this issue p. eaar3593

PURPOSE Limited treatment options exist for patients with thymic epithelial tumor (TET) whose disease progresses after platinum-based chemotherapy. We conducted a phase II study of pembrolizumab in patients with TET to evaluate its efficacy and safety. METHODS Patients with histologically confirmed TET whose disease progressed after at least one line of platinum-based chemotherapy were eligible for the study. Patients were excluded if they had an active autoimmune disease requiring systemic treatment within the past year or documented history of clinically severe autoimmune disease. Patients received 200 mg of pembrolizumab intravenously every 3 weeks until tumor progression or unacceptable toxicity. The primary objective of response rate was assessed every 9 weeks by investigators. RESULTS Of 33 patients enrolled, 26 had thymic carcinoma and seven had thymoma. Of seven thymoma, two (28.6%; 95% CI, 8.2% to 64.1%) had partial response, and five (71.6%) had stable disease. Of 26 thymic carcinoma, five (19.2%; 95% CI, 8.5% to 37.9%) had partial response and 14 (53.8%) had stable disease. The median progression-free survival was 6.1 months for both groups. The most common adverse events of any grade included dyspnea (11; 33.3%), chest wall pain (10; 30.3%), anorexia (seven; 21.2%), and fatigue (seven; 21.2%). Five (71.4%) of seven patients with thymoma and four (15.4%) of 26 patients with thymic carcinoma reported grade ≥ 3 immune-related adverse events, including hepatitis (four; 12.1%), myocarditis (three; 9.1%), myasthenia gravis (two; 6.1%), thyroiditis (one; 3.0%), antineutrophil cytoplasmic antibody–associated rapidly progressive glomerulonephritis (one; 3.0%), colitis (one; 3.0%), and subacute myoclonus (one; 3.0%). CONCLUSIONS Pembrolizumab showed encouraging antitumor activity in patients with advanced TET. Given the high incidence of autoimmunity, additional studies are needed to identify those who can benefit from pembrolizumab without immune-related adverse events.

The paper presents the case of a 57-year-old male patient who complained of slow progressive loss of visual acuity. Anamnesis revealed he was a heavy drinker and he was previously diagnosed with a pancreatic cancer, observed on the MRI. The clinical examination revealed ocular features that made the diagnosis difficult. Initially, it seemed to be a case of narrow angle glaucoma but further ocular examinations revealed macular thinning.

This study explored the clinical implications of tumor mutational burden (TMB) in a well-defined HER2-positive metastatic breast cancer (MBC) patient population who had been previously treated but had subsequent disease progression. Whole exome sequencing was performed on formalin-fixed paraffin-embedded tumor samples and matched normal tissue. Among the 46 patients, 13 (28.3%) were estrogen receptor-positive and nine (19.6%) were progesterone receptor-positive by immunohistochemistry analysis. Twenty patients (43.5%) had recurrent MBC compared with de novo MBC (n = 26, 56.5%). Sixteen patients (34.6%) demonstrated more than 100 somatic non-synonymous SNV mutations, which was predefined as a high TMB. The median follow-up duration was 57.5 months. The median overall survival (mOS) differed significantly between low and high TMB status (44.9 months vs. 85.8 months, respectively, p = 0.016). In a multivariate Cox regression analysis, TMB was the only independent prognostic factor for good metastatic overall survival after adjusting for age and recurrence (Hazard ratio [HR] = 0.32, 95% confidence interval [CI], 0.103–0.998, p = 0.049). These data suggest that high TMB may be a prognostic marker for predicting good overall survival for patients undergoing conventional HER2-directed treatments and chemotherapy. Further, future clinical trials harnessing TMB may benefit by identifying an appropriate population who may have a favorable response to immunotherapy after recurrence following HER2-directed treatments.

Background Pembro + chemo improves efficacy as 1L therapy for metastatic squamous and nonsquamous NSCLC, regardless of PD-L1 TPS. We explored the relationship between tTMB and efficacy in KEYNOTE-021 C and G (nonsquamous; NCT02039674), 189 (nonsquamous; NCT02578680), and 407 (squamous; NCT02775435). Methods tTMB was determined by whole-exome sequencing of tumor and matched normal DNA. For each study, the association of tTMB (continuous log10 transformed) with outcomes for pembro + chemo and for chemo was assessed in pts with evaluable tTMB using Cox proportional hazards models (OS, PFS) and logistic regression (ORR); statistical significance was determined at the 0.05 level (no multiplicity adjustment). Clinical utility of tTMB on outcomes was assessed using a prespecified cutpoint of 175 mut/exome. Primary study endpoints were OS and PFS in KEYNOTE-189 and 407 and ORR in 021. Results tTMB was evaluable in 48% of treated pts in KEYNOTE-021 C and G, 48% in 189, and 56% in 407. Baseline characteristics and efficacy were similar in the tTMB-evaluable and total populations. tTMB (continuous log10) was not significantly associated with efficacy of pembro + chemo or chemo (minimum P values across studies: 1-sided .072 for ORR, .052 for PFS, and .081 for OS for pembro + chemo; 2-sided .086, .055, and .475, respectively, for chemo). Pembro + chemo improved OS and PFS for tTMB ≥175 and Conclusions In this exploratory analysis, tTMB was not significantly associated with efficacy of pembro + platinum-based chemo or of chemo alone as 1L therapy for metastatic NSCLC, regardless of histology. Pembro + chemo showed survival benefit in the tTMB-high and low subgroups for both squamous and nonsquamous NSCLC.TableLBA80TabletTMB ≥175 mut/exomeatTMB Clinical trial identification KEYNOTE-021: NCT02039674, originally posted January 17, 2014; KEYNOTE-189: NCT02578680, originally posted October 19, 2015; KEYNOTE-407: NCT02775435, originally posted May 17, 2016. Editorial acknowledgement Melanie Leiby of Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Legal entity responsible for the study Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Funding Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA Disclosure L. Paz-Ares: Officer / Board of Directors: Genomica; Honoraria (self): Roche ; Honoraria (self), Research grant / Funding (institution): MSD; Honoraria (self): Lilly; Honoraria (self): Novartis; Honoraria (self): Boehringer Ingelheim; Honoraria (self), Research grant / Funding (institution): AstraZeneca; Honoraria (self): Amgen; Honoraria (self): Sanofi; Honoraria (self): Pharamar; Honoraria (self), Research grant / Funding (institution): Pfizer; Honoraria (self), Research grant / Funding (institution): Bristol-Myers Squibb; Honoraria (self): Merck; Honoraria (self): Takeda; Honoraria (self): Celgene; Honoraria (self): Servier; Honoraria (self): Sysmex; Honoraria (self): Incyte; Honoraria (self): Ipsen; Honoraria (self): Adacap; Honoraria (self): Bayer; Honoraria (self): Blueprint; Leadership role: Altum Sequencing. C.J. Langer: Advisory / Consultancy, Research grant / Funding (institution): Merck & Co., Inc.; Advisory / Consultancy: AbbVie; Advisory / Consultancy: AstraZeneca; Advisory / Consultancy: Celgene; Advisory / Consultancy: Lilly; Advisory / Consultancy: Pfizer; Advisory / Consultancy: Roche/Genentech; Advisory / Consultancy: Takeda; Advisory / Consultancy: Bristol-Myers Squibb. S. Novello: Speaker Bureau / Expert testimony: AstraZeneca; Speaker Bureau / Expert testimony: Boehringer Ingelheim; Speaker Bureau / Expert testimony: Bristol-Myers Squibb; Speaker Bureau / Expert testimony: Bayer; Speaker Bureau / Expert testimony, Research grant / Funding (institution): MSD; Speaker Bureau / Expert testimony: Roche; Speaker Bureau / Expert testimony: Takeda; Speaker Bureau / Expert testimony: Pfizer; Speaker Bureau / Expert testimony: Eli Lilly. B. Halmos: Advisory / Consultancy, Research grant / Funding (institution): Merck & Co., Inc.; Advisory / Consultancy, Research grant / Funding (institution): Boehringer Ingelheim; Advisory / Consultancy, Research grant / Funding (institution): AstraZeneca; Advisory / Consultancy, Research grant / Funding (institution): Novartis; Advisory / Consultancy, Research grant / Funding (institution): Pfizer; Advisory / Consultancy, Research grant / Funding (institution): Guardant Health; Advisory / Consultancy: Spectrum; Advisory / Consultancy, Research grant / Funding (institution): Bristol-Myers Squibb; Advisory / Consultancy: Genentech; Research grant / Funding (institution): Eli Lilly; Research grant / Funding (institution): GlaxoSmithKline; Research grant / Funding (institution): AbbVie; Research grant / Funding (institution): Mirati; Research grant / Funding (institution): Takeda. Y. Cheng: Research grant / Funding (institution): MSD. S.M. Gadgeel: Advisory / Consultancy: Boehringer Ingelheim; Advisory / Consultancy: Xcovery; Advisory / Consultancy: AstraZeneca; Advisory / Consultancy: Novocure; Advisory / Consultancy: Bristol-Myers Squibb; Advisory / Consultancy: Genentech/Roche; Advisory / Consultancy: Takeda; Research grant / Funding (institution): MSD. R. Hui: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): MSD; Honoraria (self), Advisory / Consultancy: AstraZeneca; Honoraria (self), Advisory / Consultancy: Roche; Honoraria (self), Advisory / Consultancy: Novartis; Honoraria (self), Advisory / Consultancy: Bristol-Myers Squibb; Honoraria (self), Advisory / Consultancy: Eli Lilly. S. 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Borghaei: Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Amgen; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Pfizer; Advisory / Consultancy, Travel / Accommodation / Expenses: Bristol-Myers Squibb; Advisory / Consultancy, Travel / Accommodation / Expenses: Genentech; Advisory / Consultancy, Travel / Accommodation / Expenses: Celgene; Advisory / Consultancy, Research grant / Funding (institution), Travel / Accommodation / Expenses: Merck ; Advisory / Consultancy, Travel / Accommodation / Expenses: EMD-Serono; Advisory / Consultancy: Boehringer Ingelheim; Advisory / Consultancy, Travel / Accommodation / Expenses: AstraZeneca; Advisory / Consultancy, Travel / Accommodation / Expenses: Novartis; Advisory / Consultancy, Travel / Accommodation / Expenses: Genmab; Advisory / Consultancy: Regeneron; Advisory / Consultancy: BioNTech; Advisory / Consultancy: Cantargia AB; Advisory / Consultancy: AbbVie; Advisory / Consultancy: Axiom; Advisory / Consultancy: PharmaMar; Advisory / Consultancy: Takeda; Advisory / Consultancy: Huya Bio; Research grant / Funding (institution): Milennium; Research grant / Funding (institution): Merck/Celgene; Research grant / Funding (institution): BMS/Lilly; Full / Part-time employment: Fox Chase Cancer Center; Advisory / Consultancy, Travel / Accommodation / Expenses: Lilly. R. Cristescu: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. D. Aurora-Garg: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. A. Albright: Full / Part-time employment: Merck & Co., Inc.. A. Loboda: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. J. Kobie: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. J. Lunceford: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. M. Ayers: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. G.M. Lubiniecki: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. M.C. Pietanza: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. B. Piperdi: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. M.C. Garassino: Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution): AstraZeneca; Speaker Bureau / Expert testimony: Takeda; Advisory / Consultancy, Research grant / Funding (institution): Bristol-Myers Squibb; Advisory / Consultancy, Research grant / Funding (institution): MSD; Advisory / Consultancy: Lilly; Advisory / Consultancy: Roche; Advisory / Consultancy: Boehringer Ingelheim; Advisory / Consultancy: Novartis; Research grant / Funding (institution): Roche/Genentech; Research grant / Funding (institution): MedImmune.