Abstract
Molecular profiling of large databases of human tumor gene expression profiles offers novel opportunities for informing decisions in clinical development programs. 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. 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. 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.
Highlights
Programmed death 1 (PD-1) is an immune checkpoint molecule that allows tumors to evade immune surveillance [1, 2]
Tier 1 contained novel indications known at the time of analysis to be responsive to PD-1 checkpoint blockade in the clinic, as well as indications not studied in the clinic previously, including microsatellite instability–high colorectal, head and neck, bladder, and triple-negative breast cancers
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
Summary
PD-L1 expression profile and its coexpression signature were assessed in Merck–Moffitt (N $12,000 primary and N $4,000 metastatic) and TCGA (N $10,000 primary) datasets. For each profiled sample or indication, the PD-L1 expression cut-off point for positivity was defined as the pan-cancer 75th percentile of PD-L1 expression in the Merck–Moffitt dataset This pan-cancer cutoff was selected to be consistent with the point at which the distribution of PD-L1 expression in the Merck–Moffitt dataset deviates from a normal distribution (Supplementary Fig. S2), and the cutoff led the percentage of PD-L1–positive tumors to roughly align with response rates reported at the time of the analysis in melanoma, NSCLC, and renal cell carcinoma (RCC). Ranking of primary tumors using PD-L1 expression level In Fig. 3A, the differences in PD-L1 expression are shown across the various tumor types for primary tumor samples included in the Merck–Moffitt dataset; this is reported as the percentage of tumors with PD-L1 positivity above the cutoff, as described in the Results. Trials being actively pursued in other tier 3 indications include metastatic, castration-resistant prostate cancer (as monotherapy in KEYNOTE-199, NCT02787005; in combination therapies in KEYNOTE-365, NCT02861573), advanced hepatocellular carcinoma (KEYNOTE-224, NCT02702414), previously treated metastatic colorectal cancer (KEYNOTE-164, NCT02460198), and recurrent or metastatic gastric or gastroesophageal junction adenocarcinoma (KEYNOTE-059, NCT02335411)
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