Mapping Inherited Genetic Variation with Opposite Effects on Autoimmune Disease and Four Cancer Types Identifies...

Background: Germline alleles near genes encoding certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer, but in opposite ways. This motivates a systematic search for additional germline alleles with this pattern with the aim of identifying potential cancer immunotherapeutic targets using human genetics. Methods: Pairwise fixed effect cross-disorder meta-analyses combining genome-wide association studies (GWAS) for breast, prostate, ovarian and endometrial cancers (240,540 cases/317,000 controls) and seven autoimmune/autoinflammatory diseases (112,631 cases/895,386 controls) coupled with in silico follow-up. Results: Meta-analyses followed by linkage disequilibrium clumping identified 312 unique, independent lead variants with p < 5 × 10^-8 associated with at least one of the cancer types at p < 10^-3 and one of the autoimmune/autoinflammatory diseases at p < 10^-3. At each lead variant, the allele that conferred autoimmune/autoinflammatory disease risk was protective for cancer. Mapping led variants to nearest genes as putative functional targets and focusing on immune-related genes implicated 32 genes. Tumor bulk RNA-Seq data highlighted that the tumor expression of 5/32 genes (IRF1, IKZF1, SPI1, SH2B3, LAT) was each strongly correlated (Spearman's ρ > 0.5) with at least one intra-tumor T/myeloid cell infiltration marker (CD4, CD8A, CD11B, CD45) in every one of the cancer types. Tumor single-cell RNA-Seq data from all cancer types showed that the five genes were more likely to be expressed in intra-tumor immune versus malignant cells. The five lead SNPs corresponding to these genes were linked to them via the expression of quantitative trait locus mechanisms and at least one additional line of functional evidence. Proteins encoded by the genes were predicted to be druggable. Conclusions: We provide population-scale germline genetic and functional genomic evidence to support further evaluation of the proteins encoded by IRF1, IKZF1, SPI1, SH2B3 and LAT as possible targets for cancer immunotherapy.