Comprehensive analysis of single-cell and bulk RNA sequencing data unveils antigen-presenting and processing fibroblasts and establishes a predictive model in gastric cancer.

ABSTRACT:

Background

Antigen-presenting and processing fibroblasts (APPFs) have emerged as pivotal regulators of antitumor immunity. However, the predictive value of APPF-related genes (APPFRGs) in the prognosis and tumor immune status of gastric cancer (GC) remains largely unexplored.

Methods

Bioinformatics analysis was conducted using single-cell and bulk RNA sequencing datasets of GC retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The APPFs were identified using AUCell algorithm based on APP-associated genes obtained from the InnateDB database. CellChat algorithm was utilized to evaluate interactions between cells. The non-negative matrix factorization (NMF) clustering analysis was performed to identify APPF-related subgroups based on

SUBMITTER: Zhang C 

PROVIDER: S-EPMC12182674 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature