Development and validation of a novel artificial intelligence algorithm for precise prediction the postoperative prognosis of esophageal squamous cell carcinoma.

ABSTRACT:

Background

Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy, and current postoperative prognostic assessment methods remain unsatisfactory, underlining the urgent to develop a reliable approach for precision medicine. Given the similarities with gametogenesis, cancer/testis genes (CTGs) are acknowledged for regulation unrestrained multiplication and immune microenvironment during oncogenic processes. These processes are associated with advanced disease and poorer prognosis, indicating that CTGs could serve as ideal prognostic biomarkers in ESCC. The purpose of this study is to develop a novel clinically prognostic prediction system to facilitate the individualized postoperative care.

Methods

We conducted LASSO regression analysis of protein-coding

SUBMITTER: Wang Z 

PROVIDER: S-EPMC11756118 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature