Determinants of gastric cancer immune escape identified from non-coding immune-landscape quantitative trait loci

Only a portion of cancer patients respond favorably to immunotherapy, indicating the need for new biomarkers and targets. Here, we identify common somatic and germline 3´ untranslated region (3´UTR) variants across the human transcriptome from 375 gastric cancer patients from The Cancer Genome Atlas (39.5% somatic). By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3´UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration. To distinguish between causal and correlative effects of 3´UTR eQTLs in immune-related genes, we perform a massively parallel reporter assay. Our approach identifies numerous 3´UTR eQTLs and ilQTLs (e.g. in ADAR1), providing a unique resource for the identification of immunotherapeutic targets and biomarkers. Our prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer. To assess the effect of 3'UTR variants on gene expression we performed a massively parallel reporter assay (MPRA) in two stomach cancer cell lines (AGS, SNU719) in triplicate.