The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China.
Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou, China.
J Cell Mol Med. 2020 Apr;24(8):4804-4818. doi: 10.1111/jcmm.15159. Epub 2020 Mar 12.
Differential expression analysis has led to the identification of important biomarkers in oesophageal squamous cell carcinoma (ESCC). Despite enormous contributions, it has not harnessed the full potential of gene expression data, such as interactions among genes. Differential co-expression analysis has emerged as an effective tool that complements differential expression analysis to provide better insight of dysregulated mechanisms and indicate key driver genes. Here, we analysed the differential co-expression of lncRNAs and protein-coding genes (PCGs) between normal oesophageal tissue and ESCC tissues, and constructed a lncRNA-PCG differential co-expression network (DCN). DCN was characterized as a scale-free, small-world network with modular organization. Focusing on lncRNAs, a total of 107 differential lncRNA-PCG subnetworks were identified from the DCN by integrating both differential expression and differential co-expression. These differential subnetworks provide a valuable source for revealing lncRNA functions and the associated dysfunctional regulatory networks in ESCC. Their consistent discrimination suggests that they may have important roles in ESCC and could serve as robust subnetwork biomarkers. In addition, two tumour suppressor genes (AL121899.1 and ELMO2), identified in the core modules, were validated by functional experiments. The proposed method can be easily used to investigate differential subnetworks of other molecules in other cancers.
差异表达分析已导致食管鳞状细胞癌（ESCC）中重要生物标志物的鉴定。尽管做出了巨大贡献，但它并未充分利用基因表达数据的全部潜力，例如基因之间的相互作用。差异共表达分析已成为一种有效的工具，可以补充差异表达分析，提供对失调机制的更好理解，并指示关键驱动基因。在这里，我们分析了正常食管组织和 ESCC 组织之间 lncRNA 和蛋白质编码基因（PCG）之间的差异共表达，并构建了 lncRNA-PCG 差异共表达网络（DCN）。DCN 具有无标度、小世界网络的特点，具有模块化组织。关注 lncRNA，通过整合差异表达和差异共表达，从 DCN 中总共鉴定出 107 个差异 lncRNA-PCG 子网络。这些差异子网络为揭示 lncRNA 功能和 ESCC 中相关功能失调的调控网络提供了有价值的来源。它们的一致性区分表明它们可能在 ESCC 中具有重要作用，并可能作为稳健的子网标志物。此外，核心模块中鉴定出的两个肿瘤抑制基因（AL121899.1 和 ELMO2）通过功能实验得到了验证。所提出的方法可以很容易地用于研究其他癌症中其他分子的差异子网。
