Identification of a telomere-related gene signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma by integrated analysis of machine learning and Mendelian randomization.

ABSTRACT: Telomere-related genes (TRGs) are vital in diverse tumor types. Nevertheless, there is a notable lack of in-depth research concerning their significance in head and neck squamous cell carcinoma (HNSCC). In this context, the present study aims to assess the predictive value of TRGs in HNSCC. Gene expression data and clinical data for HNSCC were sourced from The Cancer Genome Atlas and the Gene Expression Omnibus database. A new prognostic signature for TRGs was formulated through the application of machine learning techniques. Based on this signature, risk scores were computed for individual samples, effectively classifying individuals into low- and high-risk categories. The signature was evaluated in terms of its association with survival outcomes, tumor mutation burden, functional enrichm

SUBMITTER: Wei Z 

PROVIDER: S-EPMC12014034 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature