Systems Biology Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr Aiguader 88, 08003, Barcelona, Spain.
Institut de Recerca Biomedica (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028, Barcelona, Spain.
Nat Commun. 2018 Jul 4;9(1):2601. doi: 10.1038/s41467-018-04900-7.
The genetic causes of cancer include both somatic mutations and inherited germline variants. Large-scale tumor sequencing has revolutionized the identification of somatic driver alterations but has had limited impact on the identification of cancer predisposition genes (CPGs). Here we present a statistical method, ALFRED, that tests Knudson's two-hit hypothesis to systematically identify CPGs from cancer genome data. Applied to ~10,000 tumor exomes the approach identifies known and putative CPGs - including the chromatin modifier NSD1 - that contribute to cancer through a combination of rare germline variants and somatic loss-of-heterozygosity (LOH). Rare germline variants in these genes contribute substantially to cancer risk, including to ~14% of ovarian carcinomas, ~7% of breast tumors, ~4% of uterine corpus endometrial carcinomas, and to a median of 2% of tumors across 17 cancer types.
癌症的遗传原因包括体细胞突变和遗传种系变异。大规模肿瘤测序彻底改变了对体细胞驱动突变的鉴定，但对鉴定癌症易感性基因（CPGs）的影响有限。在这里，我们提出了一种统计方法 ALFRED，该方法可通过测试 Knudson 的两次打击假说，从癌症基因组数据中系统地识别 CPGs。该方法应用于大约 10000 个肿瘤外显子，可识别已知和假定的 CPGs，包括染色质修饰物 NSD1，这些 CPGs通过罕见的种系变异和体细胞杂合性丢失（LOH）的组合导致癌症。这些基因中的罕见种系变异对癌症风险有很大贡献，包括约 14%的卵巢癌、约 7%的乳腺癌、约 4%的子宫体子宫内膜癌，以及 17 种癌症类型中肿瘤的中位数为 2%。
