Abstract 492: Uncovering therapeutically targetable mutations from The Cancer Genome Atlas (TCGA) whole-genome datasets.

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Abstract The systematic identification of therapeutically actionable genomic alterations across tumor types is essential to advance precision oncology. Using the CancerVisionTM whole-genome analysis platform, we analyzed >8,000 whole-genome sequencing (WGS) samples spanning more than 30 cancer types to characterize clinically actionable mutations. Actionability was defined according to the Cancer Knowledgebase evidence levels, where Level A denotes biomarkers linked to FDA-approved on-label therapies. Overall, 2903 patients (∼32%) harbored at least one Level A actionable alteration encompassing ∼20,100 events (median 2 per sample). Level A on-label targets were detected in more than half of THCA (thyroid cancer), KIRC (kidney clear-cell), SKCM (skin cutaneous melanoma), BRCA (breast cancer), and COAD (colon adenocarcinoma), underscoring their clinical relevance. The ten most frequent Level A targets were PIK3CA, KRAS, BRAF, VHL, PTEN, ERBB2, BRCA1/2, NRAS, and EGFR, showing variable frequencies among cancer types. Among KRAS alterations, p.G12C was the predominant actionable hotspot, mainly in lung adenocarcinoma with a few cases in colorectal and rectal cancers. A total of 950 fusion targets were identified across the cohort. BRCA exhibited the highest frequency (45 cases; 2.5%), including 40 ESR1-CCDC170 fusions, followed by THCA (55 cases; 9.7%), dominated by CCDC6-RET (25 cases). NRG1 fusions were found in 145 samples (1.7%), markedly higher than the historical pan-cancer frequency (∼0.2%). Other recurrent targetable fusions included NTRK (0.7%; 60 samples), RET (0.7%), ALK (0.7%), BRAF (0.6%), and FGFR (2.5%; 210 samples), the latter largely involving FGFR2 (∼180 cases). Across all fusion classes, >80% retained the kinase domain, supporting oncogenic potential. Clinical-trial-matched targets were most commonly TP53, PIK3CA, and CDKN2A, reflecting their broad inclusion in precision-medicine studies. This comprehensive pan-cancer analysis defines the most extensive WGS-based landscape to date of actionable mutations and druggable fusions. The whole-genome approach enabled high-resolution detection of rare structural variants that are often missed by targeted sequencing panels, highlighting the potential of whole-genome profiling to uncover therapeutically relevant but under-recognized targets, supporting the integration of WGS into future tumor-agnostic clinical trial design. Citation Format: Ryul Kim, Chunyang Bao, Hansol Park, Gang-Hee Lee, Won-Chul Lee, Jonghoon Lee, Yoonsuh Lee, Beomki Lee, David Lehotzky, Ron Solan, Antonia Kowalewski, Xavi Loinaz, Vasuki Narasimha Swamy, David I. Heiman, Samantha Van Seters, Saveliy Belkin, Sam Wiseman, Andrew D. Cherniack, Luis Antonio Corchete Sanchez, Brian P Danysh, Zachary Everton, Chip Stewart, Haruna Tomono, Gengchao Wang, Esther Rheinbay, Gad Getz, Young Seok Ju. Uncovering therapeutically targetable mutations from The Cancer Genome Atlas (TCGA) whole-genome datasets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 492.

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