• Shu-Kun Lin, Chen-Ming Zhang, Bo Men, Zhong Hua, Si-Cheng Ma, and Fang Zhang.
• The Second Clinical Medical College of Henan University of Traditional Chinese Medicine, Zhengzhou, Henan, China.
• Medicine (Baltimore). 2024 Nov 15; 103 (46): e40570e40570.

AbstractBioinformatics analysis of genes and immune cells that influence prostate cancer (PCa) bone metastases. Using the gene expression omnibus database, we analyzed a PCa bone metastasis dataset. Differentially expressed genes were identified through the utilization of GEO2R and weighted gene co-expression network analysis. Gene set enrichment analysis software was used to identify important pathways. In addition to creating a network of protein-protein interactions, functional enrichment analyses were conducted using Kyoto encyclopedia of genes databases. To screen hub genes, Cytoscape software was used with the CytoHubba plug-in and performed mRNA and survival curve validation analysis of key genes using the cBioPortal website and GEPIA2 database. Immune infiltration analysis was performed using the CIBERSORTx website, and finally, immune cell correlation analysis was performed for key genes according to the TIMER database. A total of 197 PCa bone metastasis risk genes were screened, "G2M_CHECKPOINT" was significantly enriched in PCa bone metastasis samples according to genomic enrichment analysis. Based on the protein interactions network, we have identified 10 alternative hub genes, and 3 hub genes, CCNA2, NUSAP1, and PBK, were validated by the cBioPortal website and the GEPIA2 database. T cells regulatory and macrophages M0 may influence PCa to metastasize to bones, according to CIBERSORTx immune cell infiltration analysis. TIMER database analysis found different degrees of correlation between 3 key genes and major immune cells. PCa bone metastasis has been associated with CCNA2, NUSAP1, and PBK. T cells regulatory and macrophages (M0) may also be involved.Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.

18 keywords...

hide…