Resveratrol induces apoptosis of benign prostatic hyperplasia epithelial cell line (BPH-1) through p38 MAPK-FOXO3a pathway.

BACKGROUND: Resveratrol is reported to inhibit the growth of prostate, which is characteristic of benign prostatic hyperplasia (BPH) condition. However, the mechanism remains unclear. This study aimed to identify the effects and probable mechanism of resveratrol on BPH. METHODS: We used the BPH epithelial cell line BPH-1 to investigate the effect of resveratrol. Cells were treated with various concentrations of resveratrol, and its effects on cells viability, apoptosis, ROS accumulation, and cell cycle were assessed. Western blot was used to examine activation of p38 MAPK and protein levels of FOXO3a, Bcl2, Bcl-XL, and caspase3. Cells were also co-treated with the p38 MAPK inhibitor SB203580 or ROS scavenger N-Acetyl-L-cysteine (NAC) to further investigate the mechanism. RESULTS: Resveratrol treatment inhibited the growth of BPH-1 and increased apoptosis of cells. In addition, levels of phosphorylated p38 MAPK level was elevated and FOXO3a repression was observed. Concomitantly, ROS was accumulated. All of these resveratrol-mediated effects were suppressed by additional treatment with SB203580 or NAC. Resveratrol was also found to induce cell cycle arrest at S phase. CONCLUSIONS: Resveratrol can activate p38 MAPK and repress FOXO3a, thereby causing repression of SOD2, catalase, and increase of ROS accumulation, leading to apoptosis in BPH-1 cells.

Identification of a Novel Immune-Related Prognostic Biomarker and Small-Molecule Drugs in Clear Cell Renal Cell Carcinoma (ccRCC) by a Merged Microarray-Acquired Dataset and TCGA Database.

Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal cancer, with a poor prognosis. Our study aimed to identify a biomarker that is significantly associated with ccRCC prognosis and novel immunotherapeutic targets, as well as some novel molecular drugs for ccRCC. Based on the overlap of The Cancer Genome Atlas (TCGA)-Kidney Renal Clear Cell Carcinoma (KIRC) data and the ImmPort database, we obtained 1,292 immune-related genes (IRGs) and constructed a weighed co-expression network based on the IRGs. A total of 39 hub genes were screened out in three modules. CTLA4, which had the highest connectivity degree among the screened genes in a protein-protein interaction network (degree = 24), was selected. Internal validation based on the GEPIA database revealed that patients with a higher expression of CTLA4 had a significantly shorter overall survival time and disease-free survival time. Expression of CTLA4 was also closely correlated with local recurrence, pathologic stage, and immune infiltration level. External validation based on the Oncomine database and merged microarray-acquired dataset validated the mRNA expression level of hub genes. Gene-set enrichment analysis revealed that six KEGG signaling pathways, which were significantly associated with CTLA4, were enriched on immune-related pathways. Further analysis according to the TIMER database demonstrated that CTLA4 expression was positively related to dendritic cells (cor = 0.446, P = 1.32E-23) and negatively associated with tumor purity (cor = -0.267, P = 5.51E-09). Finally, we screened out 293 differentially expressed genes by integrating six datasets from the GEO database. The Connectivity Map (CMap) analysis revealed the strong potential of three small molecule drugs (monensin, quercetin, and fenbufen) for ccRCC treatment. In conclusion, CTLA4 was identified and validated in prognosis of ccRCC. CTLA4 may be a new prognostic biomarker and immunotherapeutic target for ccRCC. Monensin, quercetin, and fenbufen may be novel choices for ccRCC treatment.

Complement C7 (C7), a Potential Tumor Suppressor, Is an Immune-Related Prognostic Biomarker in Prostate Cancer (PC).

Objectives: Prostate cancer (PC) is the second most frequent tumor in men, which has a high recurrence rate and poor prognosis. Therefore, this study aimed to identify novel prognostic biomarkers and therapeutic targets for immunotherapy and small molecule drugs for PC treatment. Materials and Methods: The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to calculate immune scores and stromal scores of TCGA-PRAD data. Differentially expressed genes (DEGs) were identified using R package "limma." GO, KEGG, and DO analyses were performed to analyze DEGs. Overall survival and disease-free survival analyses were conducted for hub gene identification. To validate the hub gene at the mRNA and protein expression levels, genetic alterations were measured, and CCLE and Cox regression analyses were performed. Connectivity map (CMap) analysis and GSEA were performed for drug exploration and function analysis, respectively. Results: Immune scores ranged from -1795.98 to 2339.39, and stomal scores ranged from -1877.60 to 1659.96. In total, 45 tumor microenvironment (TME)-related DEGs were identified, of which Complement C7 (C7) was selected and validated as a hub gene. CMap analysis identified six small molecule drugs as potential agents for PC treatment. Further analysis demonstrated that C7 expression was significantly correlated with clinical T, pathological N, and immune infiltration level. Conclusions: In conclusion, of the 45 TME-related DEGs, C7 was shown to correlate with PC prognosis in patients, indicating it as a novel prognostic biomarker and immunotherapy target in PC. Additionally, six small molecule drugs showed strong therapeutic potential for PC treatment.