College of Pharmaceutical Sciences & College of Computer Science and Technology, Zhejiang University, China.
MOE Key Laboratory of Contemporary Anthropology, Human Phenome Institute, School of Life Sciences, Fudan University, China.
Brief Bioinform. 2021 Sep 2;22(5). doi: 10.1093/bib/bbab131.
Current cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored. Due to the over-excess mutations unrelated to cancer, the great challenge is to identify somatic mutations that are cancer-driven. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model: while the ground component corresponds to passenger mutations, the rapidly evolving component corresponds to driver mutations. Then, we implemented an empirical Bayesian procedure to calculate the posterior probability of a site being cancer-driven. Based on these, we developed a software CanDriS (Cancer Driver Sites) to profile the potential cancer-driving sites for thousands of tumor samples from the Cancer Genome Atlas and International Cancer Genome Consortium across tumor types and pan-cancer level. As a result, we identified that approximately 1% of the sites have posterior probabilities larger than 0.90 and listed potential cancer-wide and cancer-specific driver mutations. By comprehensively profiling all potential cancer-driving sites, CanDriS greatly enhances our ability to refine our knowledge of the genetic basis of cancer and might guide clinical medication in the upcoming era of precision medicine. The results were displayed in a database CandrisDB (http://biopharm.zju.edu.cn/candrisdb/).
当前的癌症基因组学数据库已经积累了数以百万计的体细胞突变，这些突变有待进一步探索。由于与癌症无关的过度突变，巨大的挑战是识别出癌症驱动的体细胞突变。基于致癌作用是体细胞进化的一种形式的观点，我们开发了一个由两部分组成的混合模型：地面组件对应于乘客突变，快速进化组件对应于驱动突变。然后，我们实施了一种经验贝叶斯程序来计算一个位点被癌症驱动的后验概率。基于这些，我们开发了一个名为 CanDriS（癌症驱动位点）的软件，用于分析癌症基因组图谱和国际癌症基因组联盟中数千个肿瘤样本中潜在的癌症驱动位点，涉及多种肿瘤类型和泛癌症水平。结果表明，大约 1%的位点的后验概率大于 0.90，并列出了潜在的癌症广泛性和癌症特异性驱动突变。通过全面分析所有潜在的癌症驱动位点，CanDriS 极大地提高了我们完善对癌症遗传基础的认识的能力，并可能指导精准医学时代的临床用药。结果显示在数据库 CandrisDB（http://biopharm.zju.edu.cn/candrisdb/）中。
