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BACKGROUND: In the randomized, controlled, phase III KEYNOTE-061 trial, second-line pembrolizumab did not significantly prolong overall survival (OS) versus paclitaxel in patients with PD-L1-positive (combined positive score ≥1) advanced gastric/gastroesophageal junction (G/GEJ) cancer but did elicit a longer duration of response and offered a favorable safety profile. This prespecified exploratory analysis was conducted to evaluate associations between tumor gene expression signatures and clinical outcomes in the phase III KEYNOTE-061 trial. METHODS: Using RNA sequencing data obtained from formalin-fixed, paraffin-embedded baseline tumor tissue samples, we evaluated the 18-gene T-cell-inflamed gene expression profile (TcellinfGEP) and 10 non-TcellinfGEP signatures (angiogenesis, glycolysis, granulocytic myeloid-derived suppressor cell (gMDSC), hypoxia, monocytic MDSC (mMDSC), MYC, proliferation, RAS, stroma/epithelial-to-mesenchymal transition/transforming growth factor-β, WNT). The association between each signature on a continuous scale and outcomes was analyzed using logistic (objective response rate (ORR)) and Cox proportional hazards regression (progression-free survival (PFS) and OS). One-sided (pembrolizumab) and two-sided (paclitaxel) p values were calculated for TcellinfGEP (prespecified α=0.05) and the 10 non-TcellinfGEP signatures (multiplicity-adjusted; prespecified α=0.10). RESULTS: RNA sequencing data were available for 137 patients in each treatment group. TcellinfGEP was positively associated with ORR (p=0.041) and PFS (p=0.026) for pembrolizumab but not paclitaxel (p>0.05). The TcellinfGEP-adjusted mMDSC signature was negatively associated with ORR (p=0.077), PFS (p=0.057), and OS (p=0.033) for pembrolizumab, while the TcellinfGEP-adjusted glycolysis (p=0.018), MYC (p=0.057), and proliferation (p=0.002) signatures were negatively associated with OS for paclitaxel. CONCLUSIONS: This exploratory analysis of tumor TcellinfGEP showed associations with ORR and PFS for pembrolizumab but not for paclitaxel. TcellinfGEP-adjusted mMDSC signature was negatively associated with ORR, PFS, and OS for pembrolizumab but not paclitaxel. These data suggest myeloid-driven suppression may play a role in resistance to PD-1 inhibition in G/GEJ cancer and support a strategy of considering immunotherapy combinations which target this myeloid axis. TRIAL REGISTRATION NUMBER: NCT02370498.

BACKGROUND: We performed an integrated biomarker evaluation in pembrolizumab-treated patients with R/M HNSCC enrolled in KEYNOTE-012 or KEYNOTE-055. The relationship between biomarkers and HPV status was explored. METHODS: We evaluated PD-L1 (combined positive score [CPS]), TMB, T-cell-inflamed gene expression profile (Tcellinf GEP), and HPV status. Associations between biomarkers were evaluated by logistic regression (ORR) and Cox regression (PFS, OS). RESULTS: Two hundred and fifty-seven patients (KEYNOTE-012, n = 106; KEYNOTE-055, n = 151) had TMB data available; of these, 254 had PD-L1 and 236 had Tcellinf GEP. TMB, PD-L1, and Tcellinf GEP were each significantly associated with ORR (p

PurposeTo explore relationships between biological gene expression signatures and pembrolizumab response.Experimental designRNA-sequencing data on baseline tumor tissue from 1,188 patients across seven tumor types treated with pembrolizumab monotherapy in nine clinical trials were used. A total of 11 prespecified gene expression signatures [18-gene T-cell-inflamed gene expression profile (TcellinfGEP), angiogenesis, hypoxia, glycolysis, proliferation, MYC, RAS, granulocytic myeloid-derived suppressor cell (gMDSC), monocytic myeloid-derived suppressor cell (mMDSC), stroma/epithelial-to-mesenchymal transition (EMT)/TGFβ, and WNT] were evaluated for their relationship to objective response rate (per RECIST, version 1.1). Logistic regression analysis of response for consensus signatures was adjusted for tumor type, Eastern Cooperative Oncology Group performance status, and TcellinfGEP, an approach equivalent to evaluating the association between response and the residuals of consensus signatures after detrending them for their relationship with the TcellinfGEP (previously identified as a determinant of pembrolizumab response) and tumor type. Testing of the 10 prespecified non-TcellinfGEP consensus signatures for negative association [except proliferation (hypothesized positive association)] with response was adjusted for multiplicity.ResultsCovariance patterns of the 11 signatures (including TcellinfGEP) identified in Merck-Moffitt and The Cancer Genome Atlas datasets showed highly concordant coexpression patterns in the RNA-sequencing data from pembrolizumab trials. TcellinfGEP was positively associated with response; signatures for angiogenesis, mMDSC, and stroma/EMT/TGFβ were negatively associated with response to pembrolizumab monotherapy.ConclusionsThese findings suggest that features beyond IFNγ-related T-cell inflammation may be relevant to anti-programmed death 1 monotherapy response and may define other axes of tumor biology as candidates for pembrolizumab combinations. See related commentary by Cho et al., p. 1479.

To characterize genomic determinants of response to pembrolizumab in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) in the KEYNOTE-012 study. Associations between biomarkers (tumor mutational burden (TMB), neoantigen load (NL), 18-gene T-cell-inflamed gene expression profile (TcellinfGEP), and PD-L1 combined positive score (CPS)) and clinical outcomes with pembrolizumab were assessed in patients with R/M HNSCC (n=192). Tumor human papillomavirus (HPV) status was also evaluated with the use of p16 immunohistochemistry and whole exome sequencing (WES; HPV+, mapping >20 HPV reads) in pretreatment tumor samples (n=106). TMB, clonality-weighted TMB, and TcellinfGEP were significantly associated with objective response (p=0.0276, p=0.0201, and p=0.006, respectively), and a positive trend was observed between NL and PD-L1 CPS and clinical response (p=0.0550 and p=0.0682, respectively). No correlation was observed between TMB and TcellinfGEP (Spearman ρ=-0.026) or TMB and PD-L1 (Spearman ρ=0.009); a correlation was observed between TcellinfGEP and PD-L1 (Spearman ρ=0.511). HPV status by WES and p16 immunohistochemistry showed concordance (84% ҡ=0.573) among patients whose HPV results were available using both methods. TMB and inflammatory biomarkers (TcellinfGEP and PD-L1) may represent distinct and complementary biomarkers predicting response to anti-programmed death 1 therapies in HNSCC; further study of these relationships in randomized clinical trials is needed. NCT01848834.

Aim: To determine the prevalence of deleterious mutations in BRCA1 and BRCA2 and in 13 genes involved in homologous recombination repair (HRR), the prevalence of genomic loss of heterozygosity and the allelic and hereditary status of BRCA1, BRCA2 and other HRR gene mutations in multiple solid tumor types. Patients & methods: This was a retrospective observational study of patients with an advanced/metastatic diagnosis in one of 15 solid tumor types, who were identified in a real-world clinico-genomic database. Results: Tumor tissue samples from 9457 patients were analyzed, among which 4.7% had known or suspected deleterious BRCA1/2 mutations. The prevalence (range) of mutations in HRR genes was 13.6% (2.4%–26.0%) and genomic loss of heterozygosity ≥16% was 20.6% (2.6–34.4%) across all tumor types. Conclusion: The prevalence of mutations varied significantly depending on the type of tumor. Plain Language Summary The integrity of the human genome is maintained via multiple pathways of DNA repair, one of the most important of which is homologous recombination repair (HRR), which uses a sister chromatid as a template for high-fidelity restoration of altered DNA sequences. This study aimed to determine the prevalence of deleterious mutations, i.e., changes in the genetic code that interfere with proper cellular function, in the breast cancer genes BRCA1 and BRCA2 and in 13 other genes involved in HRR in various types of solid tumors in patients with advanced or metastatic cancer. The researchers found that 4.7% of tumor samples had BRCA1/2 mutations, 13.6% had mutations in any of the HRR genes and 20.6% had genomic loss of heterozygosity (gLOH) of at least 16% i.e., loss of sections of chromosomes affecting 16% or more of the genome. BRCA1/2 mutations were most common in ovarian cancer (13.1%), prostate cancer (9.3%), breast cancer (8.2%) and pancreatic cancer (4.9%). Prevalence for mutations in HRR genes ranges from 2.4 to 26.0% and gLOH ≥16% ranged from 2.6 to 34.4% depending on the tumor type. In conclusion, the prevalence of mutations in the BRCA1/2 genes, HRR genes and gLOH ≥16% varied widely across 15 tumor types. Tweetable Abstract Among 9457 patients across 15 solid tumor types, we found that 4.7% had BRCA1/2 mutations, 13.6% had mutations in homologous recombination repair genes and 20.6% had gLOH ≥16%. The prevalence of mutations varied by tumor type. The prevalence of mutations in homologous recombination repair (HRR) genes and of genomic loss of heterozygosity (gLOH) and the allelic and hereditary status of these mutations across solid tumor types are not well described. This study reports the prevalence of mutations in BRCA1/2 and in 13 other HRR genes and of gLOH across 15 tumor types, including tumor types beyond those more commonly associated with these biomarkers. Almost 5% of tumor samples had BRCA1/2 mutations, 14% had mutations in any of the HRR genes and 21% had a high prevalence of gLOH (gLOH ≥16%). The highest prevalences of were BRCA1/2 mutations in ovarian (13.1%), prostate (9.3%), breast (8.2%) and pancreatic (4.9%) cancers. The prevalence of BRCA1/2 mutations in mesothelioma, bladder cancer, endometrial cancer and gastric cancer were not negligible. Among tumors where biallelic status was determined, the biallelic proportions of BRCA1/2 mutations were 95% in prostate, 86% in ovarian, 83% in breast, 77% in pancreatic cancer and from 23% (gastric cancer) to 38% (bladder cancer) in other tumor types. Among tumors where heritable status was determined, germline BRCA1/2 mutations predominated in pancreatic and breast cancers, whereas somatic mutations were the majority in ovarian and most of the other tumor types. Across all tumor types, the proportion of gLOH ≥16% was highest in those with biallelic mutations of BRCA1, BRCA2 and PALB2. The prevalence of mutations in HRR genes varied considerably across tumor types. Evaluation of HRR gene alterations and gLOH may enable identification of tumors that are susceptible to drugs that act by causing double-strand DNA breaks. [ABSTRACT FROM AUTHOR]

Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab. TMB and GEP were independently predictive of response and demonstrated low correlation, suggesting that they capture distinct features of neoantigenicity and T cell activation. Analysis of The Cancer Genome Atlas database showed TMB and GEP to have a low correlation, and analysis by joint stratification revealed biomarker-defined patterns of targetable-resistance biology. These biomarkers may have utility in clinical trial design by guiding rational selection of anti-PD-1 monotherapy and combination immunotherapy regimens.

We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds while minimizing the energy consumed for communication. We assume that the nodes use joint entropy coding based on explicit communication between sensor nodes, and consider both maximum and average distortion bounds. The optimization is complex since it involves an interplay between the spaces of possible transmission structures given radio reachability limitations, and feasible placements satisfying distortion bounds.We address this problem by first looking at the simplified problem of optimal placement in the one-dimensional case. An analytical solution is derived for the case when there is a simple aggregation scheme, and numerical results are provided for the cases when joint entropy encoding is used. We use the insight from our 1-D analysis to extend our results to the 2-D case, and show that our algorithm for two-dimensional placement and transmission structure provides significant power benefit over a commonly used combination of uniformly random placement and shortest path trees.