No abstract

Antibody targeting of the immune checkpoint receptor PD1 produces therapeutic activity in a variety of solid tumors, but most patients exhibit partial or complete resistance to treatment for reasons that are unclear. In this study, we evaluated tumor specimens from 65 patients with melanoma, lung nonsquamous, squamous cell lung or head and neck cancers who were treated with the approved PD1-targeting antibodies pembrolizumab or nivolumab. Tumor RNA before anti-PD1 therapy was analyzed on the nCounter system using the PanCancer 730-Immune Panel, and we identified 23 immune-related genes or signatures linked to response and progression-free survival (PFS). In addition, we evaluated intra- and interbiopsy variability of PD1, PD-L1, CD8A, and CD4 mRNAs and their relationship with tumor-infiltrating lymphocytes (TIL) and PD-L1 IHC expression. Among the biomarkers examined, PD1 gene expression along with 12 signatures tracking CD8 and CD4 T-cell activation, natural killer cells, and IFN activation associated significantly with nonprogressive disease and PFS. These associations were independent of sample timing, drug used, or cancer type. TIL correlated moderately (∼0.50) with PD1 and CD8A mRNA levels and weakly (∼0.35) with CD4 and PD-L1. IHC expression of PD-L1 correlated strongly with PD-L1 (0.90), moderately with CD4 and CD8A, and weakly with PD1. Reproducibility of gene expression in intra- and interbiopsy specimens was very high (total SD <3%). Overall, our results support the hypothesis that identification of a preexisting and stable adaptive immune response as defined by mRNA expression pattern is reproducible and sufficient to predict clinical outcome, regardless of the type of cancer or the PD1 therapeutic antibody administered to patients. .

Assessment of ERCC1 mRNA expression in patient tumor tissue is feasible in the clinical setting and predicts response to docetaxel and cisplatin. Additional studies are warranted to optimize methodologies for ERCC1 analysis in small tumor samples and to refine a multibiomarker profile predictive of patient outcome.