Multidimensional comprehensive and integrated analysis of the potential function of TMEM25 in renal clear cell carcinoma with low expression status.

BACKGROUND: Transmembrane 25(TMEM25) stands out as a potential prognostic biomarker and therapeutic target in the realm of cancer, yet its precise mechanism of action within clear cell renal cell carcinoma (ccRCC) remains unclear. MATERIALS AND METHODS: Gene expression data and clinically relevant information extracted from The Cancer Genome Atlas (TCGA) and Gene expression omnibus (GEO) databases unveil the expression patterns of TMEM25 within renal clear cell carcinoma, which reveals its prognostic and diagnostic significance. The protein expression data is available via the Human Protein Atlas (HPA) database. Further, qPCR experiments conducted on cells and tissues provide strong evidence of the gene's expression status. Additionally, they explore the correlations between TMEM25 expression and DNA methylation, gene mutations, immune cell infiltration, and drug sensitivity within this specific tumor context. RESULTS: At both the RNA and protein levels, TMEM25 displays a noteworthy downregulation in expression, which is consistently linked to an unfavorable prognosis. Receiver Operating Characteristic (ROC) curve analysis, univariate and multivariate Cox regression analyses confirmed the ability of TMEM25 to diagnose and determine prognosis in ccRCC. Its expression related closely with various immune cell types, immune checkpoints, immune inhibitors, and MHC molecules. Within ccRCC tissues, TMEM25 DNA methylation levels are observed to be elevated, and this upregulation is observed across various conditions. TMEM25 mutations also have an impact on the prognosis of ccRCC patients and the results of drug sensitivity analyses are useful for clinical decision-making. CONCLUSIONS: TMEM25 in ccRCC could potentially function as a tumor suppressor gene, holding substantial promise as a novel biomarker for diagnosing, treating, and prognosticating ccRCC patients.

Astaxanthin alleviates chronic prostatitis/chronic pelvic pain syndrome by increasing colonization of Akkermansia muciniphila in the intestine.

BACKGROUND: Astaxanthin (AST) is a natural compound with anti-inflammatory/immunomodulatory properties that has been found to have probiotic properties. However, the role and mechanism of AST in chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) are still not fully understood. PURPOSE: The aim of this study was to evaluate the effect of AST on CP/CPPS and elucidate the mediating role of the gut microbiota. MATERIALS AND METHODS: An experimental autoimmune prostatitis (EAP) mouse model was utilized to test the potential role of AST on CP/CPPS. Antibiotic cocktail (ABX) treatment and fecal microbiota transplantation (FMT) were used to elucidate the gut microbiota-mediated effects on AST. In addition, 16S rRNA gene sequencing and qRT-PCR analyses were used to analyze changes in the gut microbiota of EAP mice and CP/CPPS patients. Finally, the mechanism by which AST exerts a protective effect on CP/CPPS was explored by untargeted metabolomics and gut barrier function assays. RESULTS: Oral administration of AST reduced prostate inflammation scores, alleviated tactile sensitization of the pelvic region in EAP mice, reduced CD4+ T cell and CD68+ macrophage infiltration in the prostatic interstitium, and inhibited the up-regulation of systemic and localized pain/pro-inflammatory mediators in the prostate. After ABX, the protective effect of AST against CP/CPPS was attenuated, whereas colonization with fecal bacteria from AST-treated EAP mice alleviated CP/CPPS. 16S rRNA gene sequencing and qRT-PCR analyses showed that Akkermansia muciniphila in the feces of EAP mice and CP/CPPS patients showed a trend toward a decrease, which was associated with poor progression of CP/CPPS. In contrast, oral administration of AST increased the relative abundance of A. muciniphila, and oral supplementation with A. muciniphila also alleviated inflammation and pain in EAP mice. Finally, we demonstrated that both AST and A. muciniphila interventions increased serum levels of SCFAs acetate, up-regulated expression of colonic tight junction markers, and decreased serum lipopolysaccharide levels in EAP mice. CONCLUSION: Our results showed that AST improved CP/CPPS by up-regulating A. muciniphila, which provides new potentially effective strategies and ideas for CP/CPPS management.

Systematic analysis of RNASET2 gene as a potential prognostic and immunological biomarker in clear cell renal cell carcinoma.

BACKGROUND: RNASET2 has been identified as an oncogene with anti-angiogenic and immunomodulatory effects in a variety of cancers, but its function in clear cell renal cell carcinoma (ccRCC) is still not well understood. METHODS: The RNASET2 expression matrix was extracted from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets and analyzed for diagnostic and prognostic value. RNASET2 mRNA expression was detected by quantitative polymerase chain reaction (qPCR) in ccRCC patients and renal cancer cell lines. Wound healing assay, transwell assay, western blotting, and tube formation assays were used to evaluate the function of RNASET2 in renal cancer in vitro. In addition, transcriptome sequencing was performed on knockdown RNASET2 kidney cancer cells to analyze their potential signaling pathways. Moreover, the immune microenvironment and mutational status were evaluated to predict the potential mechanisms of RNASET2 involvement in renal cancer progression. Sensitivity to common chemotherapeutic and targeted agents was assessed according to the Genomics of Drug Sensitivity in Cancer (GDSC) database. RESULTS: RNASET2 expression was significantly upregulated in ccRCC tissues and renal cancer cell lines, predicting poor prognosis for patients. In vitro experiments showed that silencing RNASET2 inhibited the migration and pro-angiogenic ability of renal cancer cells. Transcriptome sequencing suggested its possible involvement in the remodeling of the immune microenvironment in renal cell carcinoma. Furthermore, bioinformatics analysis and immunohistochemical staining showed that RNASET2 was positively correlated with the infiltration abundance of regulatory T cells. Finally, we mapped the mutational landscape of RNASET2 in ccRCC and found its predictive value for drug sensitivity. CONCLUSIONS: Our results suggest that RNASET2 is a promising biomarker and therapeutic target in ccRCC.

Upregulation of CENPM is associated with poor clinical outcome and suppression of immune profile in clear cell renal cell carcinoma.

BACKGROUND: The response of advanced clear cell renal cell carcinoma (ccRCC) to immunotherapy is still not durable, suggesting that the immune landscape of ccRCC still needs to be refined, especially as some molecules that have synergistic effects with immune checkpoint genes need to be explored. METHODS: The expression levels of CENPM and its relationship with clinicopathological features were explored using the ccRCC dataset from TCGA and GEO databases. Quantitative polymerase chain reaction (qPCR) analysis was performed to validate the expression of CENPM in renal cancer cell lines. Kaplan-Meier analysis, COX regression analysis and Nomogram construction were used to systematically evaluate the prognostic potential of CENPM in ccRCC. Besides, single gene correlation analysis, protein-protein interaction (PPI) network, genetic ontology (GO), kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) were used to predict the biological behaviour of CENPM and the possible signalling pathways involved. Finally, a comprehensive analysis of the crosstalk between CENPM and immune features in the tumor microenvironment was performed based on the ssGSEA algorithm, the tumor immune dysfunction and exclusion (TIDE) algorithm, the TIMER2.0 database and the TISIDB database. RESULTS: CENPM was significantly upregulated in ccRCC tissues and renal cancer cell lines and was closely associated with poor clinicopathological features and prognosis. Pathway enrichment analysis revealed that CENPM may be involved in the regulation of the cell cycle in ccRCC and may have some crosstalk with the immune microenvironment in tumors. The ssGSEA algorithm, CIBERSOPT algorithm suggests that CENPM is associated with suppressor immune cells in ccRCC such as regulatory T cells. The ssGSEA algorithm, CIBERSOPT algorithm suggests that CENPM is associated with suppressor immune cells in ccRCC such as regulatory T cells. Furthermore, the TISIDB database provides evidence that not only CENPM is positively associated with immune checkpoint genes such as CTLA4, PDCD1, LAG3, TIGIT, but also chemokines and receptors (such as CCL5, CXCL13, CXCR3, CXCR5) may be responsible for the malignant phenotype of CENPM in ccRCC. Meanwhile, predictions based on the TIDE algorithm support that patients with high CENPM expression have a worse response to immunotherapy. CONCLUSIONS: The upregulation of CENPM in ccRCC predicts a poor clinical outcome, and this malignant phenotype may be associated with its exacerbation of the immunosuppressive state in the tumor microenvironment.