Identification of the Prognostic Value of Tumor Microenvironment-Related Genes in Esophageal Squamous Cell Carcinoma.

ABSTRACT: Background: Esophageal squamous cell carcinoma (ESCC) is the most prevalent histological type of esophageal cancer, but there is a lack of definite prognostic markers for this cancer. Methods: We used the ESTIMATE algorithm to access the tumor microenvironment (TME) of ESCC cases deposited in the TCGA database, and identified TME-related prognostic genes using Cox regression analysis. A least absolute shrinkage and selector operation or LASSO algorithm was used to identify key prognostic genes. Risk scores were calculated, and a clinical predictive model was constructed to evaluate the prognostic value of TME-related genes. Results: We found that high immune and stromal scores were significantly associated with poor overall survival (p < 0.05). We identified a t

SUBMITTER: Zhang D 

PROVIDER: S-EPMC7767869 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature