Mitochondria-related chemoradiotherapy resistance genes-based machine learning model associated with immune cell infiltration on the prognosis of esophageal cancer and its value in pan-cancer.

ABSTRACT: Esophageal cancer, known for its high incidence and low five-year survival rate, poses significant treatment challenges. A key aspect of this challenge is the close link between mitochondria and resistance to chemoradiotherapy (CRT). Currently, there is a scarcity of biomarkers for predicting CRT response and prognosis in esophageal cancer. Our study addresses this gap by developing a prognostic model that incorporates mitochondria-related CRT resistance (MRCRTR) genes, including CTSL, TBL1X, CLN8, MMP1, PDPN, and MRPL37. Survival analysis using Kaplan-Meier curves reveals that patients with high MRCRTR scores have lower survival rates than those with low scores. Utilizing a nomogram, we successfully predict the one-, two-, and three-year overall survival rates for esophageal cancer patien

SUBMITTER: Liu Z 

PROVIDER: S-EPMC10851222 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature