Establishment of an endoplasmic reticulum stress-related signature predicting outcomes of gastric adenocarcinoma patients - Gong, Meiyuan; Wang, Jingtao; Gao, Wenfang; Liu, Qian; Chen, Jiaxing; Wang, Guojun; Zhang, Qi (Frontiers in Genetics, 2022)
Background Gastric adenocarcinoma (GAC) is a common clinical malignancy with a poor prognosis. Endoplasmic reticulum stress (ER stress) plays important role in the progression, immune filtration, and chemoresistance of cancers. However, current knowledge about whether ER stress-related gene signatures can predict the prognosis of gastric adenocarcinoma patients is still unknown. Methods With the GAC patients’ RNA-seq data downloaded from The Cancer Genome Atlas (TCGA) and gastric cancer patients’ microarray data from Gene Expression Omnibus (GEO) datasets, LASSO regression was used to construct an ER stress-related signature. Survival analysis, time-dependent receiving operator characteristic (ROC) curves, and COX regression analysis were used to verify the signature’s efficacy. Immune infiltration, somatic mutation, immune checkpoints analysis, and copy number variation (CNV) analysis were utilized to explore the potential biological significance of the signature. Results In the present study, 8 ER stress-related genes signature were constructed. Survival analysis showed the patients in the high-risk group had a significantly worse prognosis. The area under time-dependent receiving operator characteristic (ROC) curves reached 0.65, 0.70, 0.63 at 1-, 3-, 5- years in the training cohort. COX regression analysis showed the signature was an independent prognostic factor. To predict GAC patients’ prognosis meeting individual needs, a nomogram was constructed with good accuracy. In addition, GSEA and immune filtration analysis showed that the ER stress-related signature is associated with cancer-related pathway activation and the immunosuppressive tumor microenvironment in GAC. Conclusions In the current study, we established an ER stress-related signature. This prognostic signature has good predictive power and can provide novel strategies for clinical treatment.