Chu Xin-Yi, Jiang Ling-Han, Zhou Xiong-Hui, Cui Ze-Jia, Zhang Hong-Yu
Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
Genes (Basel). 2017 Jul 14;8(7):182. doi: 10.3390/genes8070182.
The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information.
癌症返祖理论认为致癌作用是一个逆向进化过程。因此，探索癌症驱动基因的进化起源以及致癌作用背后的相关机制具有极大的研究价值。此外，癌症驱动基因的进化特征有助于从高通量数据中筛选癌症生物标志物。在本研究中，通过分析癌症内源性分子网络，我们发现源自真核生物的子网可以控制癌细胞的无限增殖，而源自真后生动物的子网可以概括癌症的其他特征。此外，基于多个数据集的研究表明，癌症驱动基因在源自真核生物、后鞭毛生物和真后生动物的基因中富集。这些结果对于通过基因年龄信息选择基因特征来增强癌症预后模型的稳健性具有重要意义。
