Bioinformatic analysis identifying Endoplasmic Reticulum Stress-Related genes as a new diagnostic and prognostic indicator in clear cell Renal Cell Carcinoma

Abstract

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancer types worldwide, and its incidence is increasing year by year. Endoplasmic reticulum stress (ERS) caused by protein misfolding has broad and profound effects on the progression and metastasis of various cancers. Accumulating evidence suggests that ERS-related genes are closely related to the occurrence and progression of ccRCC. This study aimed to identify ERS-related signature genes for evaluating the prognosis of ccRCC patients. Transcriptomic expression profiles of patients with ccRCC from public databases Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) and survival data and clinical phenotype data of patients in the TCGA database were used. Then the GeneCards database was used to identify the differentially expressed genes related to ERS. We obtained 11 signature genes, and then used the Lasso regression method to establish a diagnostic model, univariate and multivariate Cox analysis was used to analyze the correlation between the expression levels of the signature genes and the clinical characteristics, and finally 5 signature genes were associated with poor prognosis (TNFSF13B, APOL1, COL5A3, CDH5）. In summary, this study suggests that these genes may have potential as prognostic biomarkers in ccRCC and may provide new evidence to support targeted therapy in ccRCC.