A prognosis model for predicting immunotherapy response of esophageal cancer based on oxidative stress-related signatures.

ABSTRACT: Oxidative stress (OS) is intimately associated with tumorigenesis and has been considered a potential therapeutic strategy. However, the OS-associated therapeutic target for esophageal squamous cell carcinoma (ESCC) remains unconfirmed. In our study, gene expression data of ESCC and clinical information from public databases were downloaded. Through LASSO-Cox regression analysis, a risk score (RS) signature map of prognosis was constructed and performed external verification with the GSE53625 cohort. The ESTIMATE, xCell, CIBERSORT, TIMER, and ImmuCellAI algorithms were employed to analyze infiltrating immune cells and generate an immune microenvironment (IM). Afterward, functional enrichment analysis clarified the underlying mechanism of the model. Nomogram was utilized for forecasting the

SUBMITTER: Guo J 

PROVIDER: S-EPMC10774069 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature