Identification of the Prognosis-Related lncRNAs and Genes in Gastric Cancer

Abstract

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, CTD-2218G20.2 was predicted to interact with PSG4, PSG5, and PSG7, which could also interact with cancer-related proteins, including KISS1, TIMP2, MMP11, IGFBP1, EGFR, and CDKN1C, suggesting that CTD-2218G20.2 might participate in the cancer progression via 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.

DNA Methylation Signatures Associated With Prognosis of Gastric Cancer

“…Gene set enrichment analysis revealed that gene body methylation could affect GC prognosis by regulating the neuroactive ligand-receptor interaction pathway, which has been also enriched for a number of long noncoding RNAs associated with OS of GC in a prior study 34 .…”

Screening and analysis of RNAs associated with activated memory CD4 and CD8 T cells in liver cancer

“…Wang et al found that abnormal expression of CD4 T cell subsets in peripheral blood of patients with ovarian cancer and an imbalance of Th1/Th2 and Treg/Th17 provide a basis for clinical immunotherapy of ovarian cancer [ 33 ]. In addition, Su et al identified lncRNAs and genes related to the prognosis of gastric cancer and showed that prognostic genes positively related to mortality were enriched in the CAM signaling pathway by performing a functional enrichment analysis [ 34 ]. Furthermore, Talia et al showed that GPER levels are related to metastasis and premigration genes belonging to the CAM signaling pathway in breast cancer [ 35 ], which further suggested that T cell-related genes may be related to the progression of liver cancer via Th1- and Th2-cell differentiation and CAM signaling pathways.…”

DNA methylation signatures associated with prognosis of gastric cancer

“…Gene set enrichment analysis revealed that gene body methylation could affect GC prognosis by regulating the neuroactive ligand-receptor interaction pathway [ 35 ], which has been also enriched for a number of long noncoding RNAs associated with OS of GC in a prior study [ 36 ]. Moreover, this pathway has also been enriched for differentially methylated genes between tumor and normal tissue of GC [ 37 ], indicating a significant role in both carcinogenesis and prognosis of GC.…”