Prostate cancer is still a significant global health burden in the coming decade. Novel biomarkers for detection and prognosis are needed to improve the survival of distant and advanced stage prostate cancer patients. The tumor microenvironment is an important driving factor for tumor biological functions. To investigate RNA prognostic biomarkers for prostate cancer in the tumor microenvironment, we obtained relevant data from The Cancer Genome Atlas (TCGA) database. We used the bioinformatics tools Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm and weighted coexpression network analysis (WGCNA) to construct tumor microenvironment stromal-immune score-based competitive endogenous RNA (ceRNA) networks. Then, the Cox regression model was performed to screen RNAs associated with prostate cancer survival. The differentially expressed gene profile in tumor stroma was significantly enriched in microenvironment functions, like immune response, cancer-related pathways, and cell adhesion-related pathways. Based on these differentially expressed genes, we constructed three ceRNA networks with 152 RNAs associated with the prostate cancer tumor microenvironment. Cox regression analysis screened 31 RNAs as the potential prognostic biomarkers for prostate cancer. The most interesting 8 prognostic biomarkers for prostate cancer included lncRNA LINC01082, miRNA hsa-miR-133a-3p, and genes TTLL12, PTGDS, GAS6, CYP27A1, PKP3, and ZG16B. In this systematic study for ceRNA networks in the tumor environment, we screened out potential biomarkers to predict prognosis for prostate cancer. Our findings might apply a valuable tool to improve prostate cancer clinical management and the new target for mechanism study and therapy.
Purpose. To explore the active compounds of the Chinese medicine prescriptions of Bushen Hugu Decoction (BHD) and demonstrate its mechanisms against malignant tumor bone metastasis (BM) through network pharmacology and molecular docking analysis.Methods. The main components and targets of BHD were retrieved from the TCMSP database, and the targets were normalized by UniProt. The Herbs-Components-Targets network of BHD was established by Cytoscape. The main BM targets were obtained from GeneCards, TTD, DrugBank, and OMIM. STRING and Cytoscape were used to construct a PPI network and obtain hub genes. DAVID and Metascape were used for GO and KEGG enrichment analyses. According to the network topology parameters, the top 4 components were selected for molecular docking verification with the core targets. Results. Compound–target network of BHD mainly contained 51 compounds and 259 corresponding targets including 107 BHD-BM targets. PPI interaction network and subnetworks identified ten hub genes. GO enrichment analysis found 1970 terms ( p < 0.05 ), and 164 signaling pathways ( p < 0.05 ) were found in KEGG, including PI3K-Akt signaling pathway, proteoglycans in cancer, prostate cancer, MAPK signaling pathway, and IL-17 signaling pathway. Molecular docking analysis showed that the active components of BHD, quercetin, luteolin, kaempferol, and aureusidin have good binding activity to the core targets. Conclusion. The potential molecular target and signaling pathways were found for BHD major active components. It provides guidance for the future mechanism research of the BHD in malignant tumor bone metastasis. This study also established the foundation for the new strategy for the pharmacology study of Chinese medicine.
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