Unraveling anoikis in glioblastoma: insights from single-cell sequencing and prognostic modeling.

ABSTRACT:

Background

Despite advances, Glioblastoma (GBM) treatment remains challenging due to its rapid progression and resistance to therapies.

Objectives

This study aimed to investigate the role of anoikis-a mechanism by which cells evade programmed cell death upon detachment from the extracellular matrix-in GBM progression and prognosis.

Methods

Utilizing single-cell sequencing and bulk-transcriptome sequencing data from TCGA, GEO, and CGGA databases, we performed comprehensive bioinformatics analyses. We identified anoikis-related genes, constructed a prognostic model using 101 machine learning algorithms, and validated its clinical utility across multiple cohorts.Finally, we also verified the expression of model genes and the function of key gene in clinical samples and c

SUBMITTER: Tang Q 

PROVIDER: S-EPMC11948803 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature