Identification and validation of a novel angiogenesis-related gene signature for predicting prognosis in gastric adenocarcinoma - Xu, Peipei; Liu, Sailiang; Song, Shu; yao, Xiang; Li, Xuechuan; Zhang, Jie; Liu, Yinbing; Zheng, Ye; Gao, Ganglong; Xu, Jingjing (Frontiers in Oncology, 2023)
Background: Angiogenesis is a major promotor of tumor progression and metastasis in gastric adenocarcinoma (STAD). We aimed to develop a novel lncRNA gene signature by identifying angiogenesis-related genes to better predict prognosis in STAD patients. Metheds: The expression profiles of lncRNA genes were collected from The Cancer Genome Atlas (TCGA all set, 350 patients). Then, the “limma” package was used to identify differentially expressed genes (DEGs) between different subtypes. Based on these DEGs, Cox regression and Kaplan–Meier (KM) survival analysis were used to establish a novel gene signature. Furthermore, the TCGA training set was divided into two internal test sets for validation, while the TCGA test set was used as an external test set. The enriched angiogenesis-related genes were determined by single-sample gene set enrichment analysis (ssGSEA) with the “GSVA” R package. A risk scoring model was constructed by using multivariate Cox and least absolute shrinkage and selection operator (LASSO). Finally, the expression and function of these signature genes were explored by RT–PCR and colony formation assays. Results: A six-gene signature comprising LINC01579, LINC01094, RP11.497E19.1, AC093850.2, RP11.613D13.8, and RP11.384P7.7 was constructed. The expression status of the six-gene signature is correlated with the prognosis of STAD patients. The risk scoring model has great advantages in predicting the prognosis of STAD patients. The expression levels of the six-gene signature were all higher in gastric adenocarcinoma tissues than in adjacent tissues. Downregulation of the expression of these six genes suppressed the proliferation of ASG and MKN45 cells. Conclusion: Six angiogenesis-related genes were identified and integrated into a novel risk signature that can effectively assess prognosis and guide the treatment of STAD patients.