Screening of potential pain genes in pancreatic ductal adenocarcinoma (PDAC) based on bioinformatics methods.

ABSTRACT:

Background

We aimed to identify cancer pain genes in pancreatic ductal adenocarcinoma (PDAC) using bioinformatic tools to provide evidence for pain treatment in PDAC patients.

Methods

The GSE50570 data were obtained from the high-throughput Gene Expression Omnibus (GEO) database and subsequently analyzed. A volcano map, principal component analysis (PCA) map, box plot, and heat map were drawn, and a Venn diagram was constructed by comparison with human secreted histone genes. The differentially expressed secreted histone genes in PDAC were obtained. Then, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, followed by protein-protein interaction (PPI) network analysis and key genetic screening.

Results

I

SUBMITTER: Xu Q 

PROVIDER: S-EPMC10007930 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature