ArticleAmerican journal of human genetics2026
Distinct mutational landscapes for germline and somatic cancer variants in forty tumor suppressor genes.
Article in American journal of human genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Germline and somatic cancer variants in tumor suppressor genes (TSGs) share loss-of-function mechanisms, but studies of a few genes (DICER1 and CEBPA) have demonstrated differences in variant consequence and location. To systematically assess whether TSGs display distinct mutational patterns, we leveraged large public genetic databases and compared 32,941 high-quality pathogenic/likely pathogenic (P/LP) germline variants in ClinVar, with 12,907 oncogenic/likely oncogenic (O/LO) somatic tumor variants from cBioPortal across 40 TSGs. Only 3,863 (9.2%) variants were shared. Eighteen TSGs showed significantly different distributions of variant occurrences by molecular 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 nine TSGs (e.g., RB1 and APC) contained excess somatic stop-gain events throughout the coding sequence. Analysis by tumor type revealed excess stop-gain events in tissues exposed to environmental mutagens with corresponding mutation signatures. For several TSGs (WT1), germline variants predispose to tumors (Wilms' tumor) distinct from the majority source of somatic data (myeloid leukemia). Germline and somatic events are also distributed unevenly across cDNA locations, with 103 regions of preferential clustering in 39 TSGs (78 somatic and 25 germline). Twenty somatic clusters contained 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. Altogether, germline and somatic variants of TSGs represent unique sets with substantially different patterns shaped by selection pressures from gene-specific and somatic mutational mechanisms. Characterizing these distinctions enables more accurate clinical interpretation of TSG variants.
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