A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer

Abstract

PurposeThe exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC).MethodsThe mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.Results5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139–0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group.ConclusionWe construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.

Contrast-Enhanced Computed Tomography–Based Radiogenomics Analysis for Predicting Prognosis in Gastric Cancer

“…The AUC of this radiogenomic nomogram is 0.838 in the training cohort and 0.791 in the validation cohort, which is higher than the previously published genomic nomogram (AUC = 0.744) by Chen et al. ( 35 ) and radiomic nomogram (AUC = 0.771) by Wang et al. ( 36 ).…”

“…In the nomogram, RIS, tumor metastasis, lymph node positive detection rate, primary tumor, and age were kept after multivariate Cox analysis. The AUC of this radiogenomic nomogram is 0.838 in the training cohort and 0.791 in the validation cohort, which is higher than the previously published genomic nomogram (AUC = 0.744) by Chen et al (35) and radiomic nomogram (AUC = 0.771) by Wang et al (36). In addition, combining radiogenomic, clinical, and pathological information together produced this nomogram with better performance than using TNM staging information alone (Figure 4F).…”

DNA Repair and Replication-Related Gene Signature Based on Tumor Mutation Burden Reveals Prognostic and Immunotherapy Response in Gastric Cancer

“…Liu et al have identified GAMT as a biomarker of prognosis in patients with advanced GC treated with docetaxel, cisplatin, and S-1 (DCS) [50]. Chen et al also have demonstrated that high expression of GAMT, a gene driven by DNA methylation, was remarkably associated with poor prognosis [51].…”

A SERPINE1-Based Immune Gene Signature Predicts Prognosis and Immunotherapy Response in Gastric Cancer

“…GNAI1 (G protein subunit alpha i1) is a member of the Gαi family and functions to suppress adenylate cyclase activity. To date, only a handful of studies have shown that the high expression and low DNA hypermethylation of GNAI1 were significantly associated with poor prognosis in GC [33].…”