Dataset Information

A novel cuproptosis-related gene signature for predicting prognosis in cervical cancer.

ABSTRACT: Purpose: Cuproptosis, a form of copper-induced cell death, can be a promising therapeutic target for refractory cancers. Hence, we conducted this research to explore the association between cuproptosis and prognosis in cervical cancer (CC). Methods: For constructing a prognostic signature based on cuproptosis-related genes from TCGA database, the least absolute shrinkage and selection operator Cox regression was utilized. The GSE44001 cohort was utilized for validation. Results: A total of nine cuproptosis-related genes showed distinct expression in CC and normal samples in TCGA-GTEx cohort. Two risk groups were identified based on a seven-gene signature. A significant decrease in overall survival was observed in the high-risk group (p < 0.001). The risk score (HR = 2.77, 95% CI = 1.58-4.86) was an autocephalous predictor with a better predictive ability than the clinical stage. Functional analysis indicated that immune activities were suppressed more in the high-risk group than in the low-risk group. A total of 11 candidate compounds targeting the signature were identified. Conclusion: A total of seven cuproptosis-related gene signatures were constructed to predict prognosis and propose a new therapeutic target for patients with CC.

SUBMITTER: Lei L

PROVIDER: S-EPMC9453033 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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A novel cuproptosis-related gene signature for predicting prognosis in cervical cancer.

Lei Lei L Tan Liao L Sui Long L

Frontiers in genetics 20220825

Purpose: Cuproptosis, a form of copper-induced cell death, can be a promising therapeutic target for refractory cancers. Hence, we conducted this research to explore the association between cuproptosis and prognosis in cervical cancer (CC). Methods: For constructing a prognostic signature based on cuproptosis-related genes from TCGA database, the least absolute shrinkage and selection operator Cox regression was utilized. The GSE44001 cohort was utilized for validation. Results: ...[more]

PMID: 36092887

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Project description:BackgroundGastric cancer (GC) is one of the most common malignancies. Cuproptosis is a newly discovered type of cell death caused by protein toxicity stress, with copper having considerable importance in GC development.MethodsFirst, differentially expressed (DE) cuproptosis-related genes (CRGs) were screened in GC. The tumor mutation burden (TMB) of CRGs was analyzed. We then performed enrichment analyses of DE-CRGs. Next, we constructed a GC cuproptosis-related (CR) signature (CRs) using Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. The predictive efficacy was assessed using receiver operating characteristic (ROC) curves. Furthermore, we performed gene set enrichment analysis (GSEA). Different methods were used to assess tumor immunity of the CRs, and the Wilcoxon test was used to examine the expressions of m6A-, m7G-, and ferroptosis-related genes. The "pRRophetic" R package (The R Foundation for Statistical Computing) was used to predict the half maximal inhibitory concentration IC50 of common chemotherapeutic agents. Finally, the expression of CRGs in different clusters was analyzed using single-cell RNA sequencing (scRNA-seq).ResultsWe identified 8 DE-CRGs in GC. There were 9 CRGs with TMB values >1%. We constructed gene expression networks and CRs for GC. The DE-CRGs were involved in important mitochondrial metabolic pathways, and the CRs was a valuable independent prognosis factor. The GSEA revealed that angiogenesis and metabolic-related pathways were enriched in the high-risk group, whereas the low-risk group showed enrichment in DNA replication mismatch and repair pathways. The expressions of immunological checkpoints, ferroptosis-, m6A-, and m7G-related genes, type II interferon (INF) response, major histocompatibility complex (MHC class-I), and the IC50 of the copper-based carrier drug elesclomol were significantly different between the 2 groups of the CRs. Furthermore, the scRNA-seq analysis showed that most CRGs were mainly upregulated in endothelial cells.ConclusionsThe novel CRs could predict the prognosis of GC.

Project description:Patients diagnosed with advanced cervical cancer (CC) have poor prognosis after primary treatment, and there is a lack of biomarkers for predicting patients with an increased risk of recurrence of CC. Cuproptosis is reported to play a role in tumorigenesis and progression. However, the clinical impacts of cuproptosis-related lncRNAs (CRLs) in CC remain largely unclear. Our study attempted to identify new potential biomarkers to predict prognosis and response to immunotherapy with the aim of improving this situation. The transcriptome data, MAF files, and clinical information for CC cases were obtained from the cancer genome atlas, and Pearson correlation analysis was utilized to identify CRLs. In total, 304 eligible patients with CC were randomly assigned to training and test groups. LASSO regression and multivariate Cox regression were performed to construct a cervical cancer prognostic signature based on cuproptosis-related lncRNAs. Afterwards, we generated Kaplan-Meier curves, receiver operating characteristic curves and nomograms to verify the ability to predict prognosis of patients with CC. Genes for assessing differential expression among risk subgroups were also evaluated by functional enrichment analysis. Immune cell infiltration and the tumour mutation burden were analysed to explore the underlying mechanisms of the signature. Furthermore, the potential value of the prognostic signature to predict response to immunotherapy and sensitivity to chemotherapy drugs was examined. In our study, a risk signature containing eight cuproptosis-related lncRNAs (AL441992.1, SOX21-AS1, AC011468.3, AC012306.2, FZD4-DT, AP001922.5, RUSC1-AS1, AP001453.2) to predict the survival outcome of CC patients was developed, and the reliability of the risk signature was appraised. Cox regression analyses indicated that the comprehensive risk score is an independent prognostic factor. Moreover, significant differences were found in progression-free survival, immune cell infiltration, therapeutic response to immune checkpoint inhibitors, and IC50 for chemotherapeutic agents between risk subgroups, suggesting that our model can be well employed to assess the clinical efficacy of immunotherapy and chemotherapy. Based on our 8-CRLs risk signature, we were able to independently assess the outcome and response to immunotherapy of CC patients, and this signature might benefit clinical decision-making for individualized treatment.

Project description:Background: Cuproptosis and necroptosis represent two distinct programmed cell death modalities implicated in neoplastic progression; however, the role of combining cuproptosis and necroptosis in hepatocellular carcinoma (HCC) remains to be elucidated. Methods: A total of 29 cuproptosis-related necroptosis genes (CRNGs) were identified, followed by an extensive analysis of their mutational characteristics, expression patterns, prognostic implications, and associations with the tumor microenvironment (TME). Subsequently, a CRNG subtype-related signature was developed, and its value of prognostic prediction, TME, and therapeutic responses in HCC were thoroughly investigated. Last, quantitative real-time PCR and Western blotting were employed for investigating the signature gene expression in 15 paired clinical tissue samples. Results: Two distinct CRNG subtypes were discerned, demonstrating associations between CRNG expression patterns, clinicopathological attributes, prognosis, and the TME. A CRNG subtype-related prognostic signature, subjected to external validation, was constructed, serving as an independent prognostic factor for HCC patients, indicating poor prognosis for high-risk individuals. Concurrently, the signature's correlations with an immune-suppressive TME, mutational features, stemness properties, immune checkpoint genes, chemoresistance-associated genes, and drug sensitivity were observed, signifying its utility in predicting treatment responses. Subsequently, highly accurate and clinically convenient nomograms were developed, and the signature genes were validated via quantitative real-time PCR and Western blotting, further substantiating the stability and dependability of the CRNG subtype-related prognostic signature. Conclusion: Overall, this investigation presented an extensive panorama of CRNGs and developed the CRNG subtype-related prognostic signature, which holds potential for implementation in personalized treatment strategies and prognostic forecasting for HCC patients.

Project description:Background: Given the high incidence and high mortality of cervical cancer (CC) among women in developing countries, identifying reliable biomarkers for the prediction of prognosis and therapeutic response is crucial. We constructed a prognostic signature of cuproptosis-related long non-coding RNAs (lncRNAs) as a reference for individualized clinical treatment. Methods: A total of seven cuproptosis-related lncRNAs closely related to the prognosis of patients with CC were identified and used to construct a prognostic signature via least absolute shrinkage and selection operator regression analysis in the training set. The predictive performance of the signature was evaluated by Kaplan-Meier (K-M) analysis, receiver operating characteristic (ROC) analysis, and univariate and multivariate Cox analyses. Functional enrichment analysis and single-sample gene set enrichment analysis were conducted to explore the potential mechanisms of the prognostic signature, and a lncRNA-microRNA-mRNA network was created to investigate the underlying regulatory relationships between lncRNAs and cuproptosis in CC. The associations between the prognostic signature and response to immunotherapy and targeted therapy were also assessed. Finally, the prognostic value of the signature was validated using the CC tissues with clinical information in my own center. Results: A prognostic signature was developed based on seven cuproptosis-related lncRNAs, including five protective factors (AL441992.1, LINC01305, AL354833.2, CNNM3-DT, and SCAT2) and two risk factors (AL354733.3 and AC009902.2). The ROC curves confirmed the superior predictive performance of the signature compared with conventional clinicopathological characteristics in CC. The ion transport-related molecular function and various immune-related biological processes differed significantly between the two risk groups according to functional enrichment analysis. Furthermore, we discovered that individuals in the high-risk group were more likely to respond to immunotherapy and targeted therapies including trametinib and cetuximab than those in the low-risk group. Finally, CC tissues with clinical data from my own center further verify the robustness of the seven-lncRNA risk signature. Conclusion: We generated a cuproptosis-related lncRNA risk signature that could be used to predict prognosis of CC patients. Moreover, the signature could be used to predict response to immunotherapy and chemotherapy and thus could assist clinicians in making personalized treatment plans for CC patients.

Dataset Information

A novel cuproptosis-related gene signature for predicting prognosis in cervical cancer.

Publications

A novel cuproptosis-related gene signature for predicting prognosis in cervical cancer.

Similar Datasets

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