Su Xiaohui, Zhang Jianjun, Yang Wei, Liu Yanqing, Liu Yang, Shan Zexing, Wang Wentao
Department of Gastric Surgery, Cancer Hospital of China Medical University, Liaoning, China.
Front Genet. 2020 Feb 11;11:27. doi: 10.3389/fgene.2020.00027. eCollection 2020.
Gastric cancer is a common malignant tumor with high occurrence and recurrence and is the leading cause of death worldwide. However, the prognostic value of protein-coding and non-coding RNAs in stage III gastric cancer has not been systematically analyzed. In this study, using TCGA data, we identified 585 long noncoding RNAs (lncRNAs) and 927 protein-coding genes (PCGs) correlated with the overall survival rate of gastric cancer. Functional enrichment analysis revealed that the prognostic genes positively correlated with death rates were enriched in pathways, including gap junction, focal adhesion, cell adhesion molecules (CAMs), and neuroactive ligand-receptor interaction, that are involved in the tumor microenvironment and cell-cell communications, suggesting that their dysregulation may promote the tumor progression. To evaluate the performance of the prognostic genes in risk prediction, we built three multivariable Cox models based on prognostic genes selected from the prognostic PCGs and lncRNAs. The performance of the three models based on features from only PCGs or lncRNAs or from all prognostic genes were systematically compared, which revealed that the features selected from all the prognostic genes showed higher performance than the features selected only from lncRNAs or PCGs. Furthermore, the multivariable Cox regression analysis revealed that the stratification with the highest performance was an independent prognostic factor in stage III gastric cancer. In addition, we explored the underlying mechanism of the prognostic lncRNAs in the Cox model by predicting the lncRNA and protein interaction. Specifically, was predicted to interact with and , which could also interact with cancer-related proteins, including and , suggesting that CTD-2218G20.2 might participate in the cancer progression these cancer-related proteins. In summary, the systematic analysis of the prognostic lncRNAs and PCGs was of great importance to the understanding of the progression of stage III gastric cancer.
胃癌是一种常见的恶性肿瘤，发病率和复发率都很高，是全球主要的死亡原因。然而，蛋白质编码RNA和非编码RNA在III期胃癌中的预后价值尚未得到系统分析。在本研究中，我们利用TCGA数据，鉴定出585个与胃癌总生存率相关的长链非编码RNA（lncRNA）和927个蛋白质编码基因（PCG）。功能富集分析显示，与死亡率呈正相关的预后基因富集于包括缝隙连接、粘着斑、细胞粘附分子（CAM）和神经活性配体-受体相互作用等在内的通路中，这些通路参与肿瘤微环境和细胞间通讯，表明它们的失调可能促进肿瘤进展。为了评估预后基因在风险预测中的性能，我们基于从预后PCG和lncRNA中选择的预后基因构建了三个多变量Cox模型。系统比较了仅基于PCG或lncRNA或所有预后基因的特征构建的三个模型的性能，结果显示，从所有预后基因中选择的特征表现优于仅从lncRNA或PCG中选择的特征。此外，多变量Cox回归分析显示，性能最高的分层是III期胃癌的独立预后因素。此外，我们通过预测lncRNA与蛋白质的相互作用，探索了Cox模型中预后lncRNA的潜在机制。具体而言，预测CTD-2218G20.2与以及相互作用，而后者也可与包括和在内的癌症相关蛋白相互作用，这表明CTD-2218G20.2可能通过这些癌症相关蛋白参与癌症进展。总之，对预后lncRNA和PCG的系统分析对于理解III期胃癌的进展具有重要意义。
