Machine learning-based identification of exosome-related biomarkers and drugs prediction in nasopharyngeal carcinoma.

ABSTRACT:

Purpose

Exosomes are recognized as essential mediators in the intercellular communication between tumor cells, serving a pivotal function in tumor development. Nevertheless, the patterns of expression and medical relevance of exosome-related genes (ERGs) in nasopharyngeal carcinoma (NPC) remain insufficiently characterized.

Methods

Datasets retrieved from the Gene Expression Omnibus database were consolidated into a comprehensive gene dataset, which was then employed to ascertain differentially expressed genes (DEGs) by comparing NPC samples with controls. ERGs were intersected with the DEGs, yielding the detection of exosome-related DEGs. These identified genes underwent functional annotation and pathway enrichment evaluation. The least absolute shrinkage and selection oper

SUBMITTER: Wei Z 

PROVIDER: S-EPMC12174038 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature