Background: Bladder cancer (BC) has high mortality due to distant metastasis. Previous works suggested that microRNA (miRNA)-340 is a critical regulator for the development and progression of various cancers. The specific biological function of miR-340 in BC is little known. Methods: In the present study, RT-qPCR was performed to measure the expression of miR-340 in paired BC tissues and adjacent non-tumor tissues. Next, the target gene of miR-340 was identified using dual-luciferase reporter assay and its level was also tested in tissues. Moreover, cell proliferation and apoptosis were analyzed by CCK-8 and flow cytometry. Finally, the expression of PCNA, Bax was detected by RT-qPCR and western blotting, as well as PI3K/AKT signaling measured by western blotting. Result: The results demonstrated that miR-340 expression was downregulated and its target Glut-1 level was upregulated in BC tissues. Functionally, overexpression of miR-340 suppressed the proliferation and induced apoptosis in BC cells, while Glut-1 reversed the suppression of proliferation or induction of apoptosis induced by miR-340. Additionally, miR-340 repressed PCNA, p-PI3K and p-AKT levels but enhanced Bax level, while Glut-1 rescued the effects. Conclusion: In conclusion, miR-340 functions as a tumor suppressor of BC, which inhibited proliferation and induced apoptosis by targeting Glut-1 partly through regulating PCNA, Bax expression and PI3K/AKT pathway. This study suggested that miR-340 is a potential target for the treatment of BC.

Increasing evidence has confirmed the vital role of Notch signaling in the tumorigenesis of clear cell renal cell carcinoma (ccRCC). The underlying function of long non-coding RNA (lncRNA) related to Notch signaling in ccRCC remains unclear. In present study, the prognostic value and therapeutic strategy of Notch signaling-related lncRNA are comprehensively explored in ccRCC. In total, we acquired 1422 NSRlncRNAs, of which 41 lncRNAs were identified the key NSRlncRNAs associated with the occurrence of ccRCC. The prognostic signature containing five NSRlncRNAs (AC092611.2, NNT-AS1, AGAP2-AS1, AC147651.3, and AC007406.3) was established and validated, and the ccRCC patients were clustered into the high- and low-risk groups. The overall survival of patients in the low-risk group were much more favorable than those in the high-risk group. Multivariate Cox regression analysis indicated that the risk score was an independent prognostic biomarker. Based on the risk score and clinical variables, a nomogram for predicting prognosis of ccRCC patients was constructed, and the calibration curves and DCA curves showed the superior predictive ability of nomogram. The risk score was correlated with immune cell infiltration, targeted therapy or chemotherapy sensitivity, and multiple oncogenic pathways. Additionally, consensus clustering analysis stratified the ccRCC patients into four clusters with obvious different outcomes, immune microenvironments, and expression of immune checkpoints. The constructed NSRlncRNA-based signature might serve as a potential biomarker for predicting prognosis and response to immunotherapy or targeted therapy in patients with ccRCC.

Background: Reactive Oxygen Species (ROS), a hallmark of cancer, is related to prognosis, tumor progression, and treatment response. Nevertheless, the correlation of ROS-based molecular signature with clinical outcome and immune cell infiltration has not been thoroughly studied in bladder cancer (BLCA). Accordingly, we aimed to thoroughly examine the role and prognostic value of ROS-related genes in BLCA.Methods: We obtained RNA sequencing and clinical data from The Cancer Genome Atlas (TCGA) for bladder cancer (BLCA) patients and identified ROS-associated genes using the GeneCards and Molecular Signatures Database (MSigDB). We then analyzed differential gene expression between BLCA and normal tissues and explored the functions of these ROS-related genes through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) analysis. Prognostic ROS-related genes were identified using Univariate Cox regression (UCR) and LASSO analyses, which were further refined in a Multivariate Cox Regression (MCR) analysis to develop a Prognostic Signature (PS). This PS was validated in the GSE13507 cohort, assessing its predictive power with Kaplan-Meier survival and time-dependent ROC curves. To forecast BLCA outcomes, we constructed a nomogram integrating the PS with clinical variables. We also investigated the signature’s molecular characteristics through Gene Set Enrichment Analysis (GSEA), Immune Cell Infiltration (ICI), and Tumor Mutational Burden (TMB) analyses. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict chemotherapy responses based on the PS. Additionally, we screened for Small-Molecule Drugs (SMDs) targeting ROS-related genes using the CMAP database. Finally, we validated our findings by checking protein levels of the signature genes in the Human Protein Atlas (HPA) and confirmed the role of Aldo–keto reductase family 1 member B1 (AKR1B1) through in vitro experiments.Results: The constructed and validated PS that comprised 17 ROS-related genes exhibited good performance in predicting overall survival (OS), constituting an independent prognostic biomarker in BLCA patients. Additionally, we successfully established a nomogram with superior predictive capacity, as indicated by the calibration plots. The bioinformatics analysis findings showcased the implication of PS in several oncogenic pathways besides tumor ICI regulation. The PS was negatively associated with the TMB. The high-risk group patients had greater chemotherapy sensitivity in comparison to low-risk group patients. Further, 11 candidate SMDs were identified for treating BLCA. The majority of gene expression exhibited a correlation with the protein expression. In addition, the expression of most genes was consistent with protein expression. Furthermore, to test the gene reliability we constructed, AKR1B1, one of the seventeen genes identified, was used for in-depth validation. In vitro experiments indicate that siRNA-mediated AKR1B1 silencing impeded BLCA cell viability, migration, and proliferation.Conclusions: We identified a PS based on 17 ROS-related genes that represented independent OS prognostic factors and 11 candidate SMDs for BLCA treatment, which may contribute to the development of effective individualized therapies for BLCA.

Background Bladder cancer (BC), characterized by epithelial heterogeneity, remains a challenging malignancy with limited tissue biomarkers for anticipating neoadjuvant chemotherapy efficacy. Tumor progression, orchestrated by cancer cells, intricately involves the modulation of apoptosis-related pathways. Given their pivotal role in this cascade, apoptosis-related genes emerge as potential determinants of tumor development. Concurrently, the formidable challenge of drug resistance significantly impedes the success of cancer treatments, where a patient's susceptibility to chemotherapy profoundly influences therapeutic outcomes. Consequently, our objective is to develop a prognostic risk model rooted in apoptosis and chemotherapy related gene. This comprehensive approach aims to enhance our ability to predict the prognosis of BC patients and optimize treatment strategies. Methods We extracted 412 BC patients and 19 healthy humans RNA-seq samples from the TCGA database and loaded 1416 apoptosis and chemotherapy related genes from the GeneCards website. Subsequently, we established four risk score models for apoptosis and chemotherapy related genes through single-factor, multi-factor, and LASSO regression analysis. Additionally, we conducted analyses on the risk model using methods such as Kaplan–Meier log-rank test, principal component analysis, time-dependent ROC curve analysis, uni-variate analysis, and multivariate Cox regression analysis. We discussed the relationship of this model with the immune status and its predictive capability for drug sensitivity. Finally, we validated the correlation of these four genes with BC drug resistance by establishing drug-resistant cell lines and conducting in vitro drug resistance-related experiments. Results This study’s findings demonstrate that apoptosis and chemotherapy related genes can impact the progression of BC. We obtained a prognostic risk model composed of four apoptosis and chemotherapy related genes (FASN, GLI2, VHL, and PDGFRA). Among them, FASN, GLI2, and PDGFRA were identified as risk factors, with high expression in the high-risk group, while VHL exhibited high expression in the low-risk group. A nomogram was constructed based on these features to assess patient survival and prognosis. In addition, in vitro drug resistance experiments showed that FASN was associated with BC resistance. Conclusion These four apoptosis-related genes may serve as valuable factors for predicting the prognosis of BC, providing insights into the pathogenic mechanisms of apoptosis-related genes in BC. It provides a new research path to overcome drug resistance in BC. They offer more precise references and guidance for the treatment of high-risk BC patients.

Background: In this study, we aimed to screen methylation signatures associated with the prognosis of patients with clear cell renal cell carcinoma (ccRCC).Methods: Gene expression and methylation profiles of ccRCC patients were downloaded from publicly available databases, and differentially expressed genes (DEGs)‐differentially methylated genes (DMGs) were obtained. Subsequently, gene set enrichment and transcription factor (TF) regulatory network analyses were performed. In addition, a prognostic model was constructed and the relationship between disease progression and immunity was analyzed.Results: A total of 23 common DEGs‐DMGs were analyzed, among which 14 DEGs‐DMGs were obtained with a cutoff value of PCC < 0 and p < 0.05. The enrichment analysis showed that the 14 DEGs‐DMGs were enriched in three GO terms and three KEGG pathways. In addition, a total of six TFs were shown to be associated with the 14 DEGs‐DMGs, including RP58, SOX9, NF‐κB65, ATF6, OCT, and IK2. A prognostic model using five optimized DEGs‐DMGs which efficiently predicted survival was constructed and validated using the GSE105288 dataset. Additionally, four types of immune cells (NK cells, macrophages, neutrophils, and cancer‐associated fibroblasts), as well as ESTIMATE, immune, and stromal scores were found to be significantly correlated with ccRCC progression (normal, primary, and metastasis) in addition to the five optimized DEGs‐DMGs.Conclusion: A five‐gene methylation signature with the predictive ability for ccRCC prognosis was investigated in this study, consisting of CCNB2, CDKN1C, CTSH, E2F2, and ERMP1. In addition, potential targets for methylation‐mediated immunotherapy were highlighted.