Identification and validation of a novel angiogenesis-related gene signature for predicting prognosis in gastric adenocarcinoma

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.

Methods

The expression profiles of angiogenesis-related mRNA and lncRNA genes were collected from The Cancer Genome Atlas (TCGA). Then, the "limma" package was used to identify differentially expressed genes (DEGs). The expression profiles of angiogenesis-related genes were clustered by consumusclusterplus. The Pearson correlation coefficient was further used to identify lncRNAs coexpressed with angiogenesis-related clustere genes. We used Lasso Cox regression analysis to construct the angiogenesis-related lncRNAs signature. Furthermore, the diagnostic accuracy of the prognostic risk signature were validated by the TCGA training set, internal test sets and external test set. We used multifactor Cox analysis to determine that the risk score is an independent prognostic factor different from clinical characteristics. Nomogram has been used to quantitatively determine personal risk in a clinical environment. The ssGSEA method or GSE176307 data were used to evaluate the infiltration state of immune cells or predictive ability for the benefit of immunotherapy by angiogenesis-related lncRNAs signature. Finally, the expression and function of these signature genes were explored by RT-PCR and colony formation assays.

Results

Among angiogenesis-related genes clusters, the stable number of clusters was 2. A total of 289 DEGs were identified and 116 lncRNAs were screened to have a significant coexpression relationship with angiogenic DEGs (P value<0.001 and |R| >0.5). A six-gene signature comprising LINC01579, LINC01094, RP11.497E19.1, AC093850.2, RP11.613D13.8, and RP11.384P7.7 was constructed by Lasso Cox regression analysis. The multifactor Cox analysis and Nomogram results showed that our angiogenesis-related lncRNAs signature has good predictive ability for some different clinical factors. For immune, angiogenesis-related lncRNAs signature had the ability to efficiently predict infiltration state of 23 immune cells and immunotherapy. The qPCR analysis showed that the expression levels of the six lncRNA signature genes were all higher in gastric adenocarcinoma tissues than in adjacent tissues. The functional experiment results indicated that downregulation of the expression of these six lncRNA signature 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 provide potential therapeutic targets for STAD patients.