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Exploring the correlation of glycolysis-related chondroitin polymerizing factor (CHPF) with clinical characteristics, immune infiltration, and cuproptosis in bladder cancer.

ABSTRACT: Bladder cancer (BLCA) is a common malignant neoplasm of the urinary system. Glycolysis is an essential metabolic pathway regulated by various genes with implications for tumor progression and immune escape. Scoring the glycolysis for each sample in the TCGA-BLCA dataset was done using the ssGSEA algorithm for quantification. The results showed that the score in BLCA tissues was markedly greater than those in adjacent tissues. Additionally, the score was found to be correlated with metastasis and high pathological stage. Functional enrichment analyses of the glycolysis-related genes showed they were related to roles associated with tumor metastasis, glucose metabolism, cuproptosis, and tumor immunotherapy in BLCA. Using 3 different machine learning algorithms, we identified chondroitin polymerizing factor (CHPF) as a central glycolytic gene with high expression in BLCA. In addition, we showed CHPF is a valuable diagnostic marker of BLCA with an area under the ROC (AUC) of 0.81. Sequencing BLCA 5637 cells after siRNA-mediated CHPF silencing and bioinformatics revealed that CHPF positively correlated with the markers of epithelial-to-mesenchymal transformation (EMT), glycometabolism-related enzymes, and immune cell infiltration. In addition, CHPF silencing inhibited the infiltration of multiple immune cells in BLCA. Genes that promote cuproptosis negatively correlated with CHPF expression and were up-regulated after CHPF silencing. High CHPF expression was a risk factor for overall and progression-free survival of patients who received immunotherapy for BLCA. Finally, using immunohistochemistry, we demonstrated that the CHPF protein had high expression in BLCA, increasing in high-grade tumors and those with muscle invasion. The CHPF expression levels were also positively associated with ¹⁸F-fluorodeoxyglucose uptake in PET/CT images. We conclude that the glycolysis-related gene CHPF is an effective diagnostic and treatment target for BLCA.

SUBMITTER: Zhong Q

PROVIDER: S-EPMC10326591 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Exploring the correlation of glycolysis-related chondroitin polymerizing factor (<i>CHPF</i>) with clinical characteristics, immune infiltration, and cuproptosis in bladder cancer.

Zhong Quliang Q Jiang Kehua K Zhang Facai F Tian Yuan Y Gu Jiang J Li Tao T Chen Xulong X Yang Jianjun J Sun Fa F

American journal of cancer research 20230615 6

Bladder cancer (BLCA) is a common malignant neoplasm of the urinary system. Glycolysis is an essential metabolic pathway regulated by various genes with implications for tumor progression and immune escape. Scoring the glycolysis for each sample in the TCGA-BLCA dataset was done using the ssGSEA algorithm for quantification. The results showed that the score in BLCA tissues was markedly greater than those in adjacent tissues. Additionally, the score was found to be correlated with metastasis and ...[more]

PMID: 37424829

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Project description:BackgroundCuproptosis is a newly identified form of cell death that is dependent on copper (Cu) ions, termed Cu-dependent cytotoxicity. This process is distinct from other forms of cell death such as apoptosis, necrosis, and ferroptosis. The accumulation of copper is known to play a significant role in various biological processes, including angiogenesis (the formation of new blood vessels) and metastasis (the spread of cancer cells to different parts of the body). These processes are crucial for tumor growth and progression, indicating that copper and the cuproptosis-related genes (CPRGs) might be indispensable in the context of cancer development and progression. Given this background, we aimed to explore the relationship between CPRGs and both prognostic predictions and tumor microenvironment (TME) infiltration in bladder cancer (BLCA).MethodsFor this study, we utilized data from The Cancer Genome Atlas (TCGA) to identify CPRGs and subsequently divided BLCA patients into three distinct molecular clusters based on these genes. To assess the proportions of various immune cell types within the TME, we employed single-sample gene set enrichment analysis (ssGSEA) and the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) method. These computational techniques allowed us to quantify the infiltration of different immune cells, providing insights into the immune landscape of the tumors. Furthermore, we developed a risk score model using CPRGs to predict the survival prospects of BLCA patients.ResultsOur analysis identified three molecular clusters of BLCA patients, each exhibiting unique clinical features and patterns of TME infiltration. Among these clusters, cluster 1 was associated with a poor prognosis. Interestingly, this cluster also showed significant infiltration of activated CD4+ (ssGSEA P<0.001) and CD8+ T (ssGSEA P<0.05) cells, which are crucial components of the immune response against tumors. This finding suggests a complex interaction between the immune system and the tumor, where a high presence of T cells does not necessarily correlate with better outcomes. Additionally, our risk score model revealed that the high-risk group, characterized by a specific expression pattern of CPRGs, also had enhanced infiltration of CD4+ and CD8+ T cells. This indicates that the cuproptosis-based risk model has a robust ability to predict patient prognosis and can guide immunotherapy decisions.ConclusionsOur study sheds light on the biological functions of CPRGs within the TME of BLCA and their correlations with clinical parameters and patient prognosis. The identification of distinct molecular clusters with varying prognoses and immune cell infiltrations highlights the heterogeneity of BLCA and underscores the potential of CPRGs as biomarkers for prognosis and therapeutic targets. These findings offer new perspectives for the development of immunotherapeutic strategies in the treatment of BLCA patients, potentially leading to more personalized and effective cancer therapies.

Project description:BackgroundA novel form of cell death termed cuproptosis was proposed recently. miRNAs play important roles in colorectal cancer (CRC). However, their relationships have not been reported.MethodsmiRNAs that negatively regulate 16 cuproptosis regulators were predicted using Targetscan database. The univariate Cox, LASSO, and multivariate Cox regression analyses were performed to select cuproptosis-related miRNAs. GSEA and ssGSEA analysis was carried out for functional enrichment analysis. The immune cell proportion score (IPS) and the efficiencies of multiple chemotherapy drugs were compared between different risk groups. The CCK8, cell colony, edu, and flow cytometry assays were performed to validate the roles of miRNA. Luciferase reporter assay confirmed the regulatory mechanism of miRNA on cuproptosis.ResultsSix cuproptosis-related miRNAs (hsa-miR-653, hsa-miR-216a, hsa-miR-3684, hsa-miR-4437, hsa-miR-641, and hsa-miR-552) were screened out for model construction. The risk score could act as an independent prognostic indicator in CRC (p < 0.001, 95% HR = 1.243 (1.129-1.369)). The nomogram could efficiently predict the overall survival rate (AUC = 0.836). Then, the level of immunosuppressive pathways, immunosuppressive cells, stromal-activated genes, and stromal score was higher in the high-risk group. The IPS analysis showed a better response to immunotherapy in the low-risk group. Also, the risk score was closely correlated with efficiencies of multiple chemotherapy drugs. Furthermore, miR-653 was highly expressed in CRC tissues (p < 0.001), closely correlated with T stage (p < 0.001), metastasis (p < 0.001), and tumor stage (p < 0.001). High expression of miR-653 predicted a shorter overall survival (p = 0.0282) and disease-free survival (p = 0.0056). In addition, miR-653 promoted cell proliferation, inhibited apoptosis, and negatively regulated the expression of DLD through directly binding to the 3'-UTR of DLD mRNA.ConclusionWe constructed a cuproptosis-related miRNA signature for the prediction of CRC patient survival and immunotherapy sensitivity. miR-653 was highly expressed in CRC tissues, promoted cell proliferation, and inhibited apoptosis by negatively regulating the expression of DLD.

Project description:Introduction Periodontitis is an inflammatory disease and its molecular mechanisms is not clear. A recently discovered cell death pathway called cuproptosis, may related to the disease. Methods The datasets GSE10334 of human periodontitis and control were retrieved from the Gene Expression Omnibus database (GEO) for analysis.Following the use of two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature removal (SVM-RFE) were used to find CRG-based signature. Then the Receiver operating characteristic (ROC) curves was used to evaluate the gene signature's discriminatory ability. The CIBERSORT deconvolution algorithm was used to study the link between hub genes and distinct types of immune cells. Next, the association of the CRGs with immune cells in periodontitis and relevant clusters of cuproptosis were found. The link between various clusters was ascertained by the GSVA and CIBERSORT deconvolution algorithm. Finally, An external dataset (GSE16134) was used to confirm the diagnosis capacity of the identified biomarkers. In addition, clinical samples were examined using qRT-PCR and immunohistochemistry to verifiy the expression of genes related to cuprotosis in periodontitis and the signature may better predict the periodontitis. Results 15 periodontitis-related DE-CRGs were found,then 11-CRG-based signature was found by using of LASSO and SVM-RFE. ROC curves also supported the value of signature. CIBERSORT results of immune cell signature in periodontitis showed that signature genes is a crucial component of the immune response.The relevant clusters of cuproptosis found that the NFE2L2, SLC31A1, FDX1,LIAS, DLD, DLAT, and DBT showed a highest expression levels in Cluster2 ,while the NLRP3, MTF1, and DLST displayed the lowest level in Cluster 2 but the highest level in Cluster1. The GSVA results also showed that the 11 cuproptosis diagnostic gene may regulate the periodontitis by affecting immune cells. The external dataset (GSE16134) confirm the diagnosis capacity of the identified biomarkers, and clinical samples examined by qRT-PCR and immunohistochemistry also verified that these cuprotosis related signiture genes in periodontitis may better predict the periodontitis. Conclusion These findings have important implications for the cuproptosis and periodontitis, and highlight further research is needed to better understand the mechanisms underlying this relationship between the cuproptosis and periodontitis.

Project description:Objectives: Bladder cancer (BLCA) is the most common malignant tumor in the urinary system, while the prognosis of muscle-invasive bladder cancer (MIBC) is poor. Cuproptosis might be a promising therapeutic approach to trigger tumor cell death. This study aimed to figure out the role of cuproptosis in BLCA and constructed a new cuproptosis scoring system to guide clinical diagnosis and individualize treatments. Methods: Consensus clustering was used to classify 490 patients with BLCA from TCGA and GEO cohorts. Survival outcomes and functional enrichment analyses were performed between the different subtypes. The cuproptosis scoring system was constructed by LASSO-Cox analysis. ESTIMATE, CIBERSORT, and ssGSEA were used to investigate the tumor microenvironment (TME). Drug sensitivity was evaluated with pRRophetic. An immunotherapy cohort was used to investigate the treatment response. The cuproptosis scoring system was verified in our own cohort with quantitative real-time PCR. Results: An overview of 12 cuproptosis genes (CuGs) in the TCGA database was depicted. Based on the mRNA expression profiles of CuGs, patients were classified into two cuproptosis molecular patterns. Based on the differential genes between the two cuproptosis patterns, the patients were classified into two cuproptosis gene clusters. There were distinct survival outcomes, signaling pathways, and TME between the two subtypes. A 7-gene cuproptosis scoring system was constructed. Patients with high cuproptosis scores showed worse OS and more immunosuppressing TME than those with low cuproptosis scores. The two cuproptosis score groups had distinct mutation profiles. Patients with high cuproptosis scores tended to be sensitive to chemotherapy drugs, but insensitive to immune checkpoint inhibitors (ICIs) treatment. Conclusion: This study depicted the landscape of cuproptosis in BLCA. We constructed a cuproptosis scoring system to predict the prognosis of BLCA patients. There were significant differences in survival outcomes, TME, mutation profiles, and drug sensitivities in high and low cuproptosis score patients. The cuproptosis scoring system could help oncologists comprehensively understand the tumor characteristic of BLCA and make individualized treatment strategies.

Dataset Information

Exploring the correlation of glycolysis-related chondroitin polymerizing factor (CHPF) with clinical characteristics, immune infiltration, and cuproptosis in bladder cancer.

Publications

Exploring the correlation of glycolysis-related chondroitin polymerizing factor (<i>CHPF</i>) with clinical characteristics, immune infiltration, and cuproptosis in bladder cancer.

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