A 21 ‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer.

A 21‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer. Mol Med Rep. 2019 Nov 21;: Authors: Jiang H, Gu J, Du J, Qi X, Qian C, Fei B Abstract Gastric cancer (GC) ranks fifth in terms of incidence and third in terms of tumor mortality worldwide. The present study was designed to construct a Support Vector Machine (SVM) classifier and risk score system for GC. The GSE62254 (training set) and GSE26253 (validation set 2) datasets were downloaded from the Gene Expression Omnibus database. Furthermore, the gene expression profile of GC (validation set 1) was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) between recurrent and non‑recurrent samples were determined using the limma package. The feature genes were selected using the Caret package, and an SVM classifier was built using the e1071 package. Using the penalized package, the optimal predictive genes for constructing a risk score system were screened. Finally, stratification analysis of clinical factors and pathway enrichment analysis were performed using Gene Set Enrichment Analysis. A total of 239 DEGs were identified in GSE62254, among which 114 DEGs were significantly associated with both recurrence‑free survival and overall survival. Subsequently, 21 feature genes were screened from the 114 DEGs, and an SVM classifier was built. A risk score system for survival predic...
Source: Molecular Medicine Reports - Category: Molecular Biology Tags: Mol Med Rep Source Type: research