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Background: Gliomas are common aggressive brain tumors with poor prognosis. Dephosphorylation-related biomarkers are in a void in gliomas. This study aims to construct a validated prognostic risk model for dephosphorylation, which will provide new directions for clinical treatment, prognostic assessment, and temozolomide (TMZ) resistance in glioma patients. Methods: Screening dephosphorylation-related genes (DRGs) and transcriptome expression data from The Cancer Genome Atlas (TCGA), Molecular signatures database (MSigDB) and constructing risk scoring models. Kaplan-Meier (K-M), nomogram and ROC curve were used to assess the predictive efficacy of the model. Gene set enrichment analysis (GSEA), immune cell infiltration, immunotherapy response and chemotherapeutic drug sensitivity analysis were performed in this study. The correlation between chemotherapeutic drugs and the half maximal inhibitory concentration (IC50) values of 12 DRGs was analyzed. Cell division cycle 25A (CDC25A) and TMZ were screened and verified by experiments. Quantitative Real-Time PCR (qRT-PCR) detection of mRNA expression of 12 genes in human normal glial cells and two glioma cell lines. Transfection techniques overexpressed and knocked down CDC25A. qRT-PCR and Western Blot (WB) were used to detect the mRNA and protein expression levels of CDC25A. Subsequently, verify the effect of CDC25A on TMZ resistance in glioma cells. Results: The model established in this study was able to accurately predict the prognosis of glioma patients. Besides, there were significant differences in GSEA, immune cell infiltration, immunotherapeutic response and chemotherapeutic drug sensitivity analysis between glioma patients in the high and low risk groups. The results of CCK8 experiments showed that overexpression of CDC25A increased the susceptibility of U251 and LN229 cells to TMZ, and knockdown of CDC25A attenuated the susceptibility of U251 and LN229 cells to TMZ. [ABSTRACT FROM AUTHOR]

Background: Mitochondrial fusion is vital for cellular function and has been increasingly linked to cancer development. Kidney renal papillary cell carcinoma (KIRP), the second most common renal cell carcinoma, presents diverse prognostic outcomes. Identifying novel biomarkers is critical for improving prognosis and treatment response in KIRP. Objective: This study aims to explore the gene expression associated with mitochondrial fusion and establish a novel gene signature model to predict KIRP prognosis and cisplatin sensitivity. Methods: We analyzed RNA sequencing data and clinical records of 285 KIRP patients from The Cancer Genome Atlas (TCGA). LASSO regression identified four key mitochondrial fusion-related genes (BNIP3, GDAP1, MIEF2, PRKN). Multivariate Cox regression evaluated their association with overall survival. Risk stratification was developed based on gene expression. We assessed immunotherapy responses using checkpoint inhibitor scores, tumor mutation burden, TIDE scores, and tumor microenvironment characteristics. Cisplatin sensitivity was evaluated via correlation analysis of gene expression levels and half-maximal inhibitory concentration (IC50). In vitro loss- and gain-of-function experiments in KIRP cell lines (Caki-2, ACHN) assessed MIEF2's role in cisplatin sensitivity. Results: The gene signature successfully stratified patients into high- and low-risk groups, with significant survival differences. The area under the ROC curve (AUC) for the risk model was 0.782. MIEF2 was notably associated with cisplatin sensitivity, confirmed through functional experiments. Patients in the high-risk group exhibited lower MIEF2 expression and increased cisplatin sensitivity. [ABSTRACT FROM AUTHOR]

Numerous studies have revealed a correlation between the risk of developing diabetic nephropathy (DN) and the gut microbiota (GM) composition. However, it remains uncertain whether the GM composition causes DN. We aimed to explore any potential causal links between the GM composition and the risk of developing DN. A meta-analysis conducted by the MiBioGen consortium of the largest genome-wide association study (GWAS) provided aggregated data on the GM. DN data were obtained from the IEU database. The inverse-variance weighting (IVW) method was employed as the primary analytical approach. The IVW analysis indicated that genus Dialister (OR = 0.51, 95% CI: 0.34–0.77, p = 0.00118) was protective against DN. In addition, class Gammaproteobacteria (OR = 0.47, 95% CI: 0.27–0.83, p = 0.0096), class Lentisphaeria (OR =0.76, 95% CI: 0.68–0.99, p = 0.04), order Victivallales (OR = 0.76, 95% CI: 0.58–0.99, p = 0.04), and phylum Proteobacteria (OR = 0.53, 95% CI: 0.33–0.85, p = 0.00872) were negatively associated with the risk of developing DN. Genus LachnospiraceaeUCG008 (OR =1.45, 95% CI: 1.08–1.95, p = 0.01), order Bacteroidales (OR = 1.59, 95% CI: 1.02–2.49, p = 0.04), and genus Terrisporobacter (OR = 1.98, 95% CI: 1.14–3.45, p = 0.015) were positively associated with the risk of developing DN. In this study, we established a causal relationship between the genus Dialister and the risk of developing DN. Further trials are required to confirm the protective effects of probiotics on DN and to elucidate the precise protective mechanisms involving genus Dialister and DN. [ABSTRACT FROM AUTHOR]

NLRP3 inflammasome was introduced as a double-edged sword in tumorigenesis and influenced immunotherapy response by modulating host immunity. However, a systematic assessment of the NLRP3-inflammasome-related genes across human cancers is lacking, and the predictive role of NLRP3 inflammasome in cancer immunotherapy (CIT) response remains unexplored. Thus, in this study, we performed a pan-cancer analysis of NLRP3-inflammasome-related genes across 24 human cancers. Out of these 24 cancers, 15 cancers had significantly different expression of NLRP3-inflammasome-related genes between normal and tumor samples. Meanwhile, Cox regression analysis showed that the NLRP3 inflammasome score could be served as an independent prognostic factor in skin cutaneous melanoma. Further analysis indicated that NLRP3 inflammasome may influence tumor immunity mainly by mediating tumor-infiltrating lymphocytes and macrophages, and the effect of NLRP3 inflammasome on immunity is diverse across tumor types in tumor microenvironment. We also found that the NLRP3 inflammasome score could be a stronger predictor for immune signatures compared with tumor mutation burden (TMB) and glycolytic activity, which have been reported as immune predictors. Furthermore, analysis of the association between NLRP3 inflammasome and CIT response using six CIT response datasets revealed the predictive value of NLRP3 inflammasome for immunotherapy response of patients in diverse cancers. Our study illustrates the characterization of NLRP3 inflammasome in multiple cancer types and highlights its potential value as a predictive biomarker of CIT response, which can pave the way for further investigation of the prognostic and therapeutic potentials of NLRP3 inflammasome. [ABSTRACT FROM AUTHOR]

Accumulating evidence has proven that N6-methyladenosine (m6A) RNA methylation plays an essential role in tumorigenesis. However, the significance of m6A RNA methylation modulators in the malignant progression of papillary renal cell carcinoma (PRCC) and their impact on prognosis has not been fully analyzed. The present research set out to explore the roles of 17 m6A RNA methylation regulators in tumor microenvironment (TME) of PRCC and identify the prognostic values of m6A RNA methylation regulators in patients afflicted by PRCC. We investigated the different expression patterns of the m6A RNA methylation regulators between PRCC tumor samples and normal tissues, and systematically explored the association of the expression patterns of these genes with TME cell-infiltrating characteristics. Additionally, we used LASSO regression to construct a risk signature based upon the m6A RNA methylation modulators. Two-gene prognostic risk model including IGF2BP3 and HNRNPC was constructed and could predict overall survival (OS) of PRCC patients from the Cancer Genome Atlas (TCGA) dataset. The prognostic signature-based risk score was identified as an independent prognostic indicator in Cox regression analysis. Moreover, we predicted the three most significant small molecule drugs that potentially inhibit PRCC. Taken together, our study revealed that m6A RNA methylation regulators might play a significant role in the initiation and progression of PRCC. The results might provide novel insight into exploration of m6A RNA modification in PRCC and provide essential guidance for therapeutic strategies. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD) is one of the most malignant tumor types worldwide. Our objective was to identify a genetic signature that could predict the prognosis of patients with LUAD. We extracted gene data sets from The Cancer Genome Atlas and obtained differentially expressed genes that were highly expressed at every stage. These genes were analyzed using gene set enrichment analysis to obtain four biological processes associated with LUAD. Subsequently, Cox univariate and multivariate analyses were performed to generate four optimized models (G2M checkpoint, E2F targets, mitotic spindle, and glycolysis). We identified a mitotic spindle‐related signature (KIF15, BUB1, CCNB2, CDK1, KIF4A, DLGAP5, ECT2, and ANLN), which could be an independent prognostic indicator, to predict the prognosis of patients with LUAD. This new discovery should offer opportunities to explore the pathogenesis of LUAD and prove clinically useful in predicting LUAD patient prognosis. [ABSTRACT FROM AUTHOR]