Distinct mutational landscapes when comparing germline and somatic cancer variants in forty tumor suppressor genes

Abstract Germline and somatic cancer variants in tumor suppressor genes (TSGs) share loss of function mechanisms with studies of a few genes ( DICER1 , CEBPA ) highlighting differences in variant consequence and location. To systematically assess whether TSGs display distinct mutational patterns we leveraged large public genetic databases and compared high-quality pathogenic/likely pathogenic (P/LP) germline variants in ClinVar, with oncogenic/likely oncogenic (O/LO) somatic tumor variants from cBioPortal across 40 TSGs. We obtained 32,941 P/LP germline and 12,907 O/LO somatic variants. Only 3,863 (9.2%) variants were shared. Eighteen TSGs showed significant differences in distributions of variant occurrences by consequence replicated with non-overlapping somatic data from the COSMIC database (chi-squared tests, false discovery rate=5%). DICER1 , TP53 , and SMAD4 displayed excess somatic missense events, while 9 TSGs (e.g., RB1 , APC ) contained excess somatic stop-gains throughout the coding sequence. Analysis of tumor type revealed excess stop-gains in tissues exposed to environmental mutagens with corresponding mutation signatures. Germline and somatic events also distributed unevenly across cDNA location with 103 regions of preferential clustering in 39 TSGs (78 somatic, 25 germline). Twenty somatic clusters overlapped recurring frameshifts in homopolymer runs, many in tumors with microsatellite instability. Germline clusters contain more germline-exclusive variants, some driving non-cancer phenotypes reflecting genetic pleiotropy. In some TSGs ( WT1 ), germline variants predispose to tumors representing a minority of somatic data. Altogether, germline and somatic variants of TSGs represent unique sets with substantially different patterns shaped by selection pressures including environmental, phenotypic, and functional mechanisms. Characterizing these distinctions enables more accurate clinical interpretation of cancer variants.