Highlights d Tumor immune infiltration impacts response to immunotherapy d GWAS identifies inherited genetic variants associated with immune infiltration d Aggregating variants into genes and networks increases power to find associations d Germline associations may offer insight into predictors of response to immunotherapy

24Given the clinical success of immune checkpoint blockade (ICB) across a diverse set of solid 25 tumors, and the emerging role for different immune infiltrates in contributing to response to ICB, 26 a comprehensive assessment of the properties that dictate immune infiltrations may reveal new 27 biological insights and inform the development of new effective therapies. Multiple studies have 28 examined somatic and functional immune properties associated with different tumor infiltrates; 29 however, germline features that associate with specific immune infiltrates in cancers have been 30 incompletely characterized. Here, we analyzed over 7 million autosomal germline variants in 31 the TCGA cohort (5788 European-ancestry samples across 30 cancer types) and tested for pan-32 cancer association with established immune-related phenotypes that describe the tumor immune 33 microenvironment. We identified: one SNP associated with the fraction of follicular helper T 34 cells in bulk tumor; 77 unique candidate genes, some of which are involved in cytokine-mediated 35 signaling (e.g. CNTF and TRIM34 ) and cancer pathogenesis (e.g. ATR and AKAP9 ); and 36 subnetworks with genes that are part of DNA repair (RAD51 and XPC ) and transcription 37 2 elongation (CCNT2 ) pathways. We found a positive association between polygenic risk for 38 rheumatoid arthritis and absolute fraction of infiltrating CD8 T cells. Overall, we identified 39 multiple germline genetic features associated with specific tumor-immune phenotypes across 40 cancer, and developed a framework for probing inherited features that contribute to variation 41 in immune infiltration.42

Since 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from European ancestry individuals apply heterogeneously in non-European ancestry individuals. Here, we argue that enrichment analyses which aggregate SNP-level association statistics at multiple genomic scales—to genes and pathways—have been overlooked and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the insights generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven self-identified human ancestries in the UK Biobank and the Biobank Japan, as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African-American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. By testing for statistical associations at multiple genomic scales, enrichment analyses also illustrate the importance of reconciling contrasting results from association tests, heritability estimation, and prediction models in order to make personalized medicine a reality for all.