Centre for Genomics and Personalized Health, School of Chemistry and Physics, Queensland University of Technology, Brisbane, QLD, Australia.
Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
J Cell Biochem. 2022 Aug;123(8):1394-1408. doi: 10.1002/jcb.30300. Epub 2022 Jun 27.
Competing endogenous RNAs (ceRNAs) have become an emerging topic in cancer research due to their role in gene regulatory networks. To date, traditional ceRNA bioinformatic studies have investigated microRNAs as the only factor regulating gene expression. Growing evidence suggests that genomic (e.g., copy number alteration [CNA]), transcriptomic (e.g., transcription factors [TFs]), and epigenomic (e.g., DNA methylation [DM]) factors can influence ceRNA regulatory networks. Herein, we used the Least absolute shrinkage and selection operator regression, a machine learning approach, to integrate DM, CNA, and TFs data with RNA expression to infer ceRNA networks in cancer risk. The gene-regulating factors-mediated ceRNA networks were identified in four hormone-dependent (HD) cancer types: prostate, breast, colorectal, and endometrial. The shared ceRNAs across HD cancer types were further investigated using survival analysis, functional enrichment analysis, and protein-protein interaction network analysis. We found two (BUB1 and EXO1) and one (RRM2) survival-significant ceRNA(s) shared across breast-colorectal-endometrial and prostate-colorectal-endometrial combinations, respectively. Both BUB1 and BUB1B genes were identified as shared ceRNAs across more than two HD cancers of interest. These genes play a critical role in cell division, spindle-assembly checkpoint signalling, and correct chromosome alignment. Furthermore, shared ceRNAs across multiple HD cancers have been involved in essential cancer pathways such as cell cycle, p53 signalling, and chromosome segregation. Identifying ceRNAs' roles across multiple related cancers will improve our understanding of their shared disease biology. Moreover, it contributes to the knowledge of RNA-mediated cancer pathogenesis.
竞争性内源 RNA（ceRNA）在基因调控网络中发挥作用，成为癌症研究中的一个新兴课题。迄今为止，传统的 ceRNA 生物信息学研究仅将 microRNA 作为唯一调节基因表达的因素进行了研究。越来越多的证据表明，基因组（例如，拷贝数改变[CNA]）、转录组（例如，转录因子[TFs]）和表观基因组（例如，DNA 甲基化[DM]）因素可以影响 ceRNA 调控网络。在此，我们使用最小绝对收缩和选择算子回归（一种机器学习方法），将 DM、CNA 和 TF 数据与 RNA 表达相结合，以推断癌症风险中的 ceRNA 网络。在四种激素依赖性（HD）癌症类型（前列腺癌、乳腺癌、结直肠癌和子宫内膜癌）中鉴定了基因调节因子介导的 ceRNA 网络。使用生存分析、功能富集分析和蛋白质-蛋白质相互作用网络分析进一步研究了 HD 癌症类型之间的共享 ceRNA。我们发现了两个（BUB1 和 EXO1）和一个（RRM2）在乳腺癌-结直肠癌-子宫内膜癌和前列腺癌-结直肠癌-子宫内膜癌组合中具有生存意义的共享 ceRNA。BUB1 和 BUB1B 基因均被鉴定为超过两种感兴趣的 HD 癌症的共享 ceRNA。这些基因在细胞分裂、纺锤体组装检查点信号和正确染色体排列中发挥着关键作用。此外，多个 HD 癌症中的共享 ceRNA 参与了细胞周期、p53 信号和染色体分离等重要癌症途径。确定多个相关癌症中 ceRNA 的作用将提高我们对其共享疾病生物学的理解。此外，它有助于了解 RNA 介导的癌症发病机制。
