Integrated Multiomics Analysis Reveals a Migrasome-Related Signature for Prognosis and Immunotherapy Response in Lung Adenocarcinoma.

ABSTRACT:

Background

Migrasomes, a newly identified subtype of extracellular vesicles generated during cell migration, play crucial roles in tumor microenvironment modulation. However, their systematic characterization in lung adenocarcinoma (LUAD) remains unexplored. This study is aimed at deciphering migrasome-related molecular features and their clinical significance through multiomics integration.

Methods

We integrated bulk transcriptomes (541 LUAD samples from TCGA/GEO) with single-cell RNA-seq (GSE156632). Migrasome-related genes (MIGgenes) were identified through WGCNA and differential expression analysis. A machine learning framework incorporating 10 algorithms generated 101 combinatorial models, with the optimal prognostic signature (MIGsig) selected via 10-fold cross-validat

SUBMITTER: Zhou J 

PROVIDER: S-EPMC12781864 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature