Pan-cancer PCR-free whole-genome sequencing refines the somatic driver landscape beyond exome sequencing alone

Background: The initial TCGA exome sequencing project established a foundational catalog of somatic mutations. However, capture biases and limited coverage in GC-rich and repetitive regions may have obscured bona fide driver events and introduced systematic “blind spots” in the landscape of protein-coding genes. Leveraging high-depth, PCR-free whole-genome sequencing (WGS), we revisited the somatic mutation landscape in multiple tumor types to enhance driver discovery by improving sensitivity in GC-rich regions and reducing artifact-driven false positives. Methods: We analyzed matched tumor-normal PCR-free WGS data from >8,000 TCGA cases across several cancer types with existing previously published somatic mutation calls from whole exome sequencing (WES) data, applying a unified best-practice pipeline for SNV/indel detection and stringent post-calling filters. We focused on (i) concordance between WGS and exome across coding regions, (ii) coverage, allele fraction, and local sequence context (GC content, segmental duplications) of discordant sites, and (iii) recurrence and positional clustering of variants in established cancer genes. Results: PCR-free WGS identified substantially more high-confidence coding mutations than WES, with the greatest gains in GC-rich exons and difficult-to-capture loci. This increased sensitivity uncovered additional pathogenic or likely pathogenic variants in canonical drivers, including TP53 and FOXA1 in breast cancer, EGFR in glioblastoma, and BAP1 in uveal melanoma (UVM), thereby strengthening known genotype-phenotype associations. In UVM, we observed an indel in the BAP1 5′UTR/promoter region that was systematically missed by WES but supported by robust read evidence in WGS data, nominating an expanded spectrum of BAP1-disrupting events with potential regulatory and clinical relevance. Conversely, we found a subset of WES-only calls localized to segmental duplications or low-support sites, consistent with technical artifacts. Integrated re-annotation of discordant calls thus both eliminates spurious events and reveals underappreciated driver mutations and mechanisms. Conclusions: Our systematic comparison demonstrates that PCR-free WGS can refine the somatic mutation and driver landscape beyond exome-based catalogs, particularly in GC-rich and regulatory regions. These results advocate for re-interrogation of previously profiled tumor types with contemporary WGS to achieve a more complete and accurate map of cancer-driving alterations.