基于癌症基因组图谱(TCGA)全基因组测序数据集的全面突变谱分析

Cancer arises from the progressive accumulation of genomic alterations. The Cancer Genome Atlas (TCGA), a landmark consortium project, has comprehensively characterized 33 cancer types through multi-omics profiling of over 11,000 tumor-normal pairs. However, most TCGA-based studies had relied on whole-exome sequencing (WES), which covers only ~1-2% of the genome, leaving the majority of the genomic landscape unexplored. To achieve a more comprehensive understanding of cancer genomes, the Broad Institute and Inocras collaboratively analyzed TCGA whole-genome sequencing (WGS) data encompassing over 8,000 tumors across more than 30 cancer types, which were initially analyzed by whole-exome sequencing. To fully leverage this resource, we applied CancerVision, an automated and streamlined bioinformatics pipeline developed by Inocras for clinical-grade WGS interpretation. CancerVision detects diverse genomic variants, including single-nucleotide variants (SNVs), insertions/deletions (indels), somatic copy number alterations (SCNAs), structural variants (SVs), and germline mutations, while also inferring homologous recombination deficiency (HRD) and mutational signatures. Using CancerVision, we performed a comprehensive, harmonized reanalysis of the TCGA WGS dataset and benchmarked our results against the bioinformatics pipelines from the Broad Institute and the official TCGA exome data. Across representative cohorts, ovarian cancer (CNV-driven), thyroid cancer (SNV-driven), and glioblastoma (mixed), CancerVision achieved high concordance, often uncovering additional high-confidence genomic alterations not captured in the existing TCGA resource. By integrating these results, we expand the known landscape of somatic variants, improve driver gene detection, and demonstrate the power of whole-genome-based analytics for actionable insights in precision oncology.