Zhao Tingting, Xu Jinyuan, Liu Ling, Bai Jing, Xu Chaohan, Xiao Yun, Li Xia, Zhang Liming
Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, China.
Mol Biosyst. 2015 Jan;11(1):126-36. doi: 10.1039/c4mb00478g. Epub 2014 Oct 30.
LncRNAs have become rising stars in biology and medicine, due to their versatile functions in a wide range of important biological processes and active roles in various human cancers. Here, we developed a computational method based on the naïve Bayesian classifier method to identify cancer-related lncRNAs by integrating genome, regulome and transcriptome data, and identified 707 potential cancer-related lncRNAs. We demonstrated the performance of the method by ten-fold cross-validation, and found that integration of multi-omic data was necessary to identify cancer-related lncRNAs. We identified 707 potential cancer-related lncRNAs and our results showed that these lncRNAs tend to exhibit significant differential expression and differential DNA methylation in multiple cancer types, and prognosis effects in prostate cancer. We also found that these lncRNAs were more likely to be direct targets of TP53 family members than others. Moreover, based on 147 lncRNA knockdown data in mice, we validated that four of six mouse orthologous lncRNAs were significantly involved in many cancer-related processes, such as cell differentiation and the Wnt signaling pathway. Notably, one lncRNA, lnc-SNURF-1, which was found to be associated with TNF-mediated signaling pathways, was up-regulated in prostate cancer and the protein-coding genes affected by knockdown of the lncRNA were also significantly aberrant in prostate cancer patients, suggesting its probable importance in tumorigenesis. Taken together, our method underlines the power of integrating multi-omic data to uncover cancer-related lncRNAs.
长链非编码RNA（lncRNAs）已成为生物学和医学领域的后起之秀，这是由于它们在广泛的重要生物学过程中具有多种功能，并且在各种人类癌症中发挥着积极作用。在此，我们基于朴素贝叶斯分类器方法开发了一种计算方法，通过整合基因组、调控组和转录组数据来识别与癌症相关的lncRNAs，并鉴定出707个潜在的与癌症相关的lncRNAs。我们通过十折交叉验证展示了该方法的性能，发现整合多组学数据对于识别与癌症相关的lncRNAs是必要的。我们鉴定出707个潜在的与癌症相关的lncRNAs，我们的结果表明，这些lncRNAs在多种癌症类型中往往表现出显著的差异表达和DNA甲基化差异，以及在前列腺癌中的预后影响。我们还发现，这些lncRNAs比其他lncRNAs更有可能是TP53家族成员的直接靶点。此外，基于小鼠中147个lncRNA敲低数据，我们验证了六个小鼠直系同源lncRNAs中的四个显著参与了许多与癌症相关的过程，如细胞分化和Wnt信号通路。值得注意的是，一个名为lnc-SNURF-1的lncRNA被发现与TNF介导的信号通路相关，在前列腺癌中上调，并且该lncRNA敲低所影响的蛋白质编码基因在前列腺癌患者中也显著异常，这表明它在肿瘤发生中可能具有重要作用。综上所述，我们的方法强调了整合多组学数据以揭示与癌症相关的lncRNAs的能力。
