癌症基因组图谱（TCGA）全基因组测序数据集中的种系易感性

The goal of The Cancer Genome Atlas (TCGA) has been to continually characterize the genomic and transcriptomic landscapes across diverse malignancies. In this analysis, we assess matched tumor-normal Whole-Genome Sequencing (WGS) data from a previously sequenced set of adult cancer patients to identify germline pathogenic variations. These latest TCGA data consist of cancer patients from varied ancestral backgrounds with solid tumors and lymphoid cancers and patient-matched normal samples, consisting of blood or tissue. We have now obtained high-quality tumor and normal WGS data from over 8,000 samples, including normal samples derived mainly from the patient-matched blood samples. To discover novel links between genetics and cancer predisposition, we are analyzing germline variants-including single-nucleotide variants (SNVs) and structural variants (SVs)-in known cancer genes, as well as in genes with recurrent mutations that may have been missed or previously could not be assessed using exome or low-coverage genome studies.We have conducted a preliminary analysis focused on identifying Pathogenic or Likely Pathogenic (P/LP) variants, classified according to American College of Medical Genetics and Genomics guidelines, in cancer predisposition genes. This initial pass on a majority of samples confirmed the presence of P/LP variants across the cohort in canonical cancer predisposition genes, including BRCA1 , BRCA2 , ATM , and other genes integral to the mismatch and DNA repair pathways. Across cohorts, we identified known P/LP germline variants in established cancer predisposition genes in less than 10% of all cases, with the largest number of variants identified in BRCA1/2 , aligning with previous published work. The prevalence of P/LP variants was not uniform across cancer types, with some showing an enrichment, including breast cancer, while other cancer types, like low-grade gliomas, demonstrated a lower prevalence than the average. These findings underscore the highly variable, tumor-specific landscape of germline predisposition.We continue to leverage this comprehensive WGS dataset as a key resource for ongoing analyses of germline-somatic interactions. We are actively investigating how these germline P/LP variants shape the tumor's somatic mutational landscape and contribute to oncogenesis. We are also investigating whether haplotype-specific copy number alterations contribute to the pathogenicity of identified germline cancer risk alleles. Further work includes characterizing both structural and complex non-coding pathogenic variants that were previously inaccessible in exome or low-coverage WGS studies.