Programmed death-1-directed (PD-1-directed) immune checkpoint blockade results in durable antitumor activity in many advanced malignancies. Recent studies suggest that IFN-γ is a critical driver of programmed death ligand-1 (PD-L1) expression in cancer and host cells, and baseline intratumoral T cell infiltration may improve response likelihood to anti-PD-1 therapies, including pembrolizumab. However, whether quantifying T cell-inflamed microenvironment is a useful pan-tumor determinant of PD-1-directed therapy response has not been rigorously evaluated. Here, we analyzed gene expression profiles (GEPs) using RNA from baseline tumor samples of pembrolizumab-treated patients. We identified immune-related signatures correlating with clinical benefit using a learn-and-confirm paradigm based on data from different clinical studies of pembrolizumab, starting with a small pilot of 19 melanoma patients and eventually defining a pan-tumor T cell-inflamed GEP in 220 patients with 9 cancers. Predictive value was independently confirmed and compared with that of PD-L1 immunohistochemistry in 96 patients with head and neck squamous cell carcinoma. The T cell-inflamed GEP contained IFN-γ-responsive genes related to antigen presentation, chemokine expression, cytotoxic activity, and adaptive immune resistance, and these features were necessary, but not always sufficient, for clinical benefit. The T cell-inflamed GEP has been developed into a clinical-grade assay that is currently being evaluated in ongoing pembrolizumab trials.

Purpose Expression of programmed death-ligand 1 (PD-L1) is a potential predictive marker for response and outcome after treatment with anti-programmed death 1 (PD-1). This study explored the relationship between anti-PD-1 activity and PD-L1 expression in patients with advanced melanoma who were treated with pembrolizumab in the phase Ib KEYNOTE-001 study (clinical trial information: NCT01295827). Patients and Methods Six hundred fifty-five patients received pembrolizumab10 mg/kg once every 2 weeks or once every 3 weeks, or 2 mg/kg once every 3 weeks. Tumor response was assessed every 12 weeks per Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 by independent central review. Primary outcome was objective response rate. Secondary outcomes included progression-free survival (PFS) and overall survival (OS). Membranous PD-L1 expression in tumor and tumor-associated immune cells was assessed by a clinical trial immunohistochemistry assay (22C3 antibody) and scored on a unique melanoma (MEL) scale of 0 to 5 by one of three pathologists who were blinded to clinical outcome; a score ≥ 2 (membranous staining in ≥ 1% of cells) was considered positive. Results Of 451 patients with evaluable PD-L1 expression, 344 (76%) had PD-L1-positive tumors. Demographic and staging variables were equally distributed among PD-L1-positive and -negative patients. An association between higher MEL score and higher response rate and longer PFS (hazard ratio, 0.76; 95% CI, 0.71 to 0.82) and OS (hazard ratio, 0.76; 95% CI, 0.69 to 0.83) was observed ( P < .001 for each). Objective response rate was 8%, 12%, 22%, 43%, 57%, and 53% for MEL 0, 1, 2, 3, 4, and 5, respectively. Conclusion PD-L1 expression in pretreatment tumor biopsy samples was correlated with response rate, PFS, and OS; however, patients with PD-L1-negative tumors may also achieve durable responses.

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 < 0.01). Kaplan-Meier curves at prespecified cutoffs generally showed PFS and OS separation in the anticipated direction for these biomarkers, except for OS and TMB. TMB did not correlate with PD-L1 or Tcellinf GEP (Spearman ρ = -0.03 and ρ = -0.13, respectively); PD-L1 and Tcellinf GEP were moderately correlated (Spearman ρ = 0.47). In multivariate models, TMB, PD-L1, and Tcellinf GEP were each independently predictive for ORR (p < 0.001). ORR was higher in patients with high versus low levels of biomarkers when dichotomized using prespecified cutoffs; patients with higher versus lower levels of TMB and PD-L1 or TMB and Tcellinf GEP had the highest ORRs. Within HPV subgroups, higher versus lower distributions of biomarkers (PD-L1, TMB, and Tcellinf GEP) were associated with response. HPV detection by p16-immunohistochemistry and WES showed good concordance (81%); results were generally similar by HPV status, regardless of the detection method. CONCLUSIONS: TMB and the inflammatory biomarkers PD-L1 and Tcellinf GEP, assessed alone or together, may be useful for characterizing clinical response to pembrolizumab in R/M HNSCC.

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.

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.

Purpose

To explore relationships between biological gene expression signatures and pembrolizumab response.

Experimental design

RNA-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.

Results

Covariance 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.

Conclusions

These 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.