Background. Aberrant lipid metabolism is an alteration common to many types of cancer. Dysregulation of lipid metabolism is considered a major risk factor for bladder cancer. Accordingly, we focused on genes related to lipid metabolism and screened novel markers for predicting the prognosis of bladder cancer. Methods. RNA‐seq data for bladder cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The nonnegative matrix factorization (NMF) algorithm was used to classify the molecular subtypes. Weighted correlation network analysis (WGCNA) was applied to identify coexpressed genes, and least absolute shrinkage and selection operator (LASSO) multivariate Cox analysis was used to construct a prognostic risk model. External validation data and in vitro experiments were used to verify the results from in silico analysis. Results. Bladder cancer samples were grouped into two clusters based on the NMF algorithm. A total of 1467 genes involved in coexpression modules were identified in WGCNA. We finally established a 5‐gene signature (TM4SF1, KCNK5, FASN, IMPDH1, and KCNJ15) that exhibited good stability across different datasets and was also an independent risk factor for prognosis. Furthermore, the predictive efficacy of our model was generally higher than the predictive efficacy of other published models. Distinct risk groups of patients also showed significantly different immune infiltration cell patterns and associations with clinical variables. Moreover, the 5 signature genes were verified in clinical samples by quantitative real‐time polymerase chain reaction (qRT‐PCR) and immunohistochemistry, which were in agreement with the in silico analysis. For in vitro experiments, knockdown of IMPDH1 markedly inhibited cell proliferation in bladder cancer. Conclusion. We established a 5‐gene prognosis signature based on lipid metabolism in bladder cancer, which could be an effective prognostic indicator.

Docetaxel is the preferred chemotherapeutic agent in patients with castrate‐resistant prostate cancer (CRPC). However, patients eventually develop docetaxel resistance and in the absence of effective treatment options. Consequently, it is essential to investigate the mechanisms generating docetaxel resistance and develop novel alternative therapeutic targets. RNA sequencing was undertaken on docetaxel‐sensitive and docetaxel‐resistant prostate cancer (PCa) cells. Subsequently, chemoresistance, cancer stemness, and lipid metabolism were investigated. To obtain insight into the precise activities and action mechanisms of NOTCH3 in docetaxel‐resistant PCa, immunoprecipitation, mass spectrometry, ChIP, luciferase reporter assay, cell metabolism, and animal experiments were performed. Through RNA sequencing analysis, we found that NOTCH3 expression was markedly higher in docetaxel‐resistant cells relative to parental cells, and that this trend was continued in docetaxel‐resistant PCa tissues. Experiments in vitro and in vivo revealed that NOTCH3 enhanced stemness, lipid metabolism, and docetaxel resistance in PCa. Mechanistically, NOTCH3 is bound to TUBB3 and activates the MAPK signaling pathway. Moreover, NOTCH3 was directly regulated by MEF2A in docetaxel‐resistant cells. Notably, targeting NOTCH3 and the MEF2A/TUBB3 signaling axis was related to docetaxel chemoresistance in PCa. Overall, these results demonstrated that NOTCH3 fostered stemness, lipid metabolism, and docetaxel resistance in PCa via the TUBB3 and MAPK signaling pathways. Therefore, NOTCH3 may be employed as a prognostic biomarker in PCa patients. NOTCH3 could be a therapeutic target for PCa patients, particularly those who have developed docetaxel resistance.

Cuproptosis, Copper Induced Cell Death, is a newly defined type of programmed cell death, involving in the regulation of tricarboxylic acid (TCA) cycle. Dysfunction of cuproptosis induces cytotoxicity and influences the proliferation of multiple tumors. However, the direct prognostic effect of cuproptosis related genes and corresponding regulating mechanisms amid prostate cancer remains unknown. A multi-omics analysis strategy was adopted to explore the role of ten cuproptosis related genes in The Cancer Genome Atlas- Prostate Adenocarcinoma (TCGA-PRAD). Firstly, mRNA expression, Copy Number Variance (CNV), mutation, DNA methylation and prognostic power of the ten genes were illustrated. Based on transcriptomic data, we developed a novel prognostic model named the Cuproptosis-related gene score (CRGScore), Their biological functions were then detected by enrichment analysis and unsupervised cluster analysis. Following that, their correlation with Tumor Immune Microenvironment (TIME), immunotherapy, Biochemical Recurrence (BCR) and chemotherapeutic resistance were elaborated by relevant bioinformatics algorithms. Ten cuproptosis related genes exhibited extensive alteration of CNV and DNA methylation and showed significant influence on the prognosis of prostate cancer patients. These genes mainly enriched in E2F and G2M targets and mitosis pathways, Samples with high CRGScore showed enhancement resulting in the increased infiltration of T cell, B cell, NK cells. They also demonstrated close correlations with the BCR status, expression of eight immune checkpoints and chemotherapeutic resistances in prostate cancer. Our comprehensive analysis of CRGScore revealed an extensive regulatory mechanism by which they affect the tumor-immune-stromal microenvironment, clinicopathological features, and prognosis. We also determined the therapeutic liability of CRGScore in targeted therapy and immunotherapy. These findings highlight the crucial clinical implications of CRGScore and provide new ideas for guiding personalized immunotherapy strategies for patients with Pca.

Prostate cancer (PCa) has emerged as a predominant cause of cancer-related mortality among men globally. The mechanisms of branched-chain amino acids (BCAAs) contributing to the development of PCa remain inadequately elucidated. The objective of this study was to examine the involvement of BCAAs and BCAT2 in tumorigenesis. BCAAs exhibited elevated expression levels in PCa tissues and cells. Among the critical enzymes involved in the BCAA metabolic pathway, only BCAT2 demonstrated significant expression in PCa and was closely associated with tumor progression and patient prognosis. RNA sequencing along with related functional experiments indicated that BCAT2 can inhibit autophagy, autophagy-related apoptosis, and ferroptosis in PCa. Furthermore, the results of co-immunoprecipitation, mass spectrometry, and other methodologies established that PCBP1, as a downstream protein interacting with BCAT2, co-regulates the PI3K/AKT pathway, thereby influencing progression of PCa. Moreover, BCAT2 interacted with PCBP1 at Leucine 239 to collaboratively regulate the PI3K/AKT signaling pathway, which is crucial for the initiation and progression of PCa. Targeting BCAT2 may represent a promising therapeutic strategy to prevent proliferation of PCa.

Despite advances in its treatment, patients diagnosed with clear cell renal cell carcinoma (ccRCC) have a poor prognosis. The mechanism of cuproptosis has been found to differ from other mechanisms that regulate cell death, including apoptosis, iron poisoning, pyrophosphate poisoning, and necrosis. Cuproptosis is an essential component in the regulation of a wide variety of biological processes, such as cell wall remodeling and oxidative stress responses. However, cuproptosis-related genes’ expression in ccRCC patients and their association with the patient’s prognosis remain ambiguous. Evaluation of The Cancer Genome Atlas (TCGA) identified 11 genes associated with cuproptosis that were differently expressed in ccRCC and nearby nontumor tissue. To construct a multigene prognostic model, the prognostic value of 11 genes was assessed and quantified. A signature was constructed by least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and this signature was used to separate ccRCC patients into different risk clusters, with low-risk patients having a much better prognosis. This five-gene signature, when combined with patients’ clinical characteristics, might serve as one independent predictor of overall survival (OS) in ccRCC patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that cuproptosis-related genes were enriched in patients with ccRCC. Then, quantitative real-time PCR (qPCR) was employed to verify these genes’ expression. Generally, research has indicated that cuproptosis-related genes are important in tumor immunity and can predict OS of ccRCC patients.

Background: Bladder cancer is the leading causes of cancer-associated mortality and seriously affects population health. Hypoxia plays a key role in tumor development and immune escape, which contributes to malignant behaviors. Methods: In this study, we analyzed the RNA-seq and clinical information of bladder cancer patients from The Cancer Genome Atlas (TCGA) database. To investigate the hypoxia-related prognostic and immune microenvironment in bladder cancer, we constructed a hypoxia-related risk model for overall survival (OS). The RNA-seq and clinical data of bladder cancer patients from the Gene Expression Omnibus (GEO) database were used as validation sets. Results: The hypoxia-related risk signature was significantly correlated with clinical outcomes and could independently predict OS outcomes. Furthermore, the hypoxia-related risk signature could effectively reflected the levels of immune cell type fractions and the expression of critical immune checkpoint genes were higher in the high-risk group compared to the low-risk group. We also validated the expression levels of the prognostic genes in bladder cancer and paracancerous tissue samples through qRT-PCR analysis. Conclusion: We established a 7 hypoxia-related gene (HRG) signature that can be used as an independent clinical predictor and provided a potential mechanism in bladder cancer immunotherapy.