Multi-omics approach reveals the impact of prognosis model-related genes on the tumor microenvironment in medulloblastoma.

ABSTRACT:

Background

The tumor microenvironment (TME) significantly impacts the progression and prognosis of medulloblastoma (MB). This study aimed to develop a TME-associated risk score(TMErisk) model using RNA sequencing data to predict patient outcomes and elucidate biological mechanisms.

Methods

RNA sequencing data from 322 Tiantan and 763 GSE85217 MB samples were analyzed. Key gene modules related to immune and stromal components were identified using Weighted Gene Co-expression Network Analysis (WGCNA). Significant genes were screened using LASSO-COX and COX regression models. Single-cell RNA sequencing (scRNA-seq), single-cell ATAC sequencing (scATAC-seq), and spatial RNA analyses validated the findings.

Results

Differential expression analysis identified 731 upregulated

SUBMITTER: Han D 

PROVIDER: S-EPMC11913712 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature