The composition of the tumor microbial microenvironment participates in the whole process of tumor disease. However, due to the limitations of the current technical level, the depth and breadth of the impact of microorganisms on tumors have not been fully recognized, especially in prostate cancer (PCa). Therefore, the purpose of this study is to explore the role and mechanism of the prostate microbiome in PCa based on bacterial lipopolysaccharide (LPS)-related genes by means of bioinformatics.
The Comparative Toxicogenomics Database (CTD) was used to find bacterial LPS- related genes. PCa expression profile data and clinical data were acquired from TCGA, GTEx, and GEO. The differentially expressed LPS-related hub genes (LRHG) were obtained by Venn diagram, and gene set enrichment analysis (GSEA) was used to investigate the putative molecular mechanism of LRHG. The immune infiltration score of malignancies was investigated using single-sample gene set enrichment analysis (ssGSEA). Using univariate and multivariate Cox regression analysis, a prognostic risk score model and nomogram were developed.
6 LRHG were screened. LRHG were involved in functional phenotypes such as tumor invasion, fat metabolism, sex hormone response, DNA repair, apoptosis, and immunoregulation. And it can regulate the immune microenvironment in the tumor by influencing the antigen presentation of immune cells in the tumor. And a prognostic risk score and the nomogram, which were based on LRHG, showed that the low-risk score has a protective effect on patients.
Microorganisms in the PCa microenvironment may use complex mechanism and networks to regulate the occurrence and development of PCa. Bacterial lipopolysaccharide-related genes can help build a reliable prognostic model and predict progression-free survival in patients with prostate cancer.