Unraveling tumor microenvironment heterogeneity in malignant pleural mesothelioma identifies biologically distinct immune subtypes enabling prognosis determination.

ABSTRACT:

Background

Malignant pleural mesothelioma (MPM) is a rare and intractable disease exhibiting a remarkable intratumoral heterogeneity and dismal prognosis. Although immunotherapy has reshaped the therapeutic strategies for MPM, patients react with discrepant responsiveness.

Methods

Herein, we recruited 333 MPM patients from 5 various cohorts and developed an in-silico classification system using unsupervised Non-negative Matrix Factorization and Nearest Template Prediction algorithms. The genomic alterations, immune signatures, and patient outcomes were systemically analyzed across the external TCGA-MESO samples. Machine learning-based integrated methodology was applied to identify a gene classifier for clinical application.

Results

The gene expression profiling

SUBMITTER: Yang K 

PROVIDER: S-EPMC9552848 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature