ArticleFrontiers in endocrinology2023
Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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60 citing papers in PubMed, 76 citations in OpenAlex.
- [The Role of Cuproptosis Related Key Genes in Ovarian Cancer and the Construction of a Prognostic Model].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Article
- Dynamic assessment of the allocation of copper to cytochrome c oxidase using size-exclusion chromatography (SEC) combined with inductively coupled plasma mass spectrometry (ICP-MS).The Journal of biological chemistry · 2026Article
- Artificial neural network-based immune biomarker signature predicts pathological complete response to neoadjuvant chemotherapy in HER2-negative breast cancer.Frontiers in oncology · 2026Article
- DUSP5 contributes to platinum resistance in ovarian cancer: single-cell discovery and functional validation.Frontiers in pharmacology · 2026Article
- Development and validation of a nomogram model of lung metastasis in breast cancer based on machine learning algorithm and cytokines.BMC cancer · 2025Article
- Downregulated STAT3 and STAT5B are prognostic biomarkers for colorectal cancer and are associated with immune infiltration.Discover oncology · 2025Article
- Review
- Integrative multi-omics and experimental analyses implicate PTK2 as a lorazepam-associated biomarker and potential therapeutic target in ovarian cancer.Frontiers in pharmacology · 2025Article
- Metabolic reprogramming in hepatocellular carcinoma: mechanisms of immune evasion and therapeutic implications.Frontiers in immunology · 2025Review
- Metabolic reprogramming and immune microenvironment characteristics in laryngeal carcinoma: advances in immunotherapy.Frontiers in immunology · 2025Review
- Integrated Multiomics Unravels Hedgehog (HH) Signaling Characteristics in Pancreatic Cancer (PC) and DCBLD2 Regulates HH Signaling to Drive PC Progression.Human mutation · 2025Article
- Integrated bulk and single-cell profiling characterize sphingolipid metabolism in pancreatic cancer.BMC cancer · 2024Article
- Multi‑omics identification of a signature based on malignant cell-associated ligand-receptor genes for lung adenocarcinoma.BMC cancer · 2024Article
- Cuproptosis-related gene DLAT is a biomarker of the prognosis and immune microenvironment of gastric cancer and affects the invasion and migration of cells.Cancer medicine · 2024Article
- Identification of a novel monocyte/macrophage-related gene signature for predicting survival and immune response in acute myeloid leukemia.Scientific reports · 2024Article
- Identification of the biological functions and chemo-therapeutic responses of ITGB superfamily in ovarian cancer.Discover oncology · 2024Article
- Cuproptosis: unveiling a new frontier in cancer biology and therapeutics.Cell communication and signaling : CCS · 2024Review
- Prognostic and immunotherapeutic potential of regulatory T cell-associated signature in ovarian cancer.Journal of cellular and molecular medicine · 2024Article
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Ovarian cancer (OC) is one of the most common and most malignant gynecological malignancies in gynecology. On the other hand, dysregulation of copper metabolism (CM) is closely associated with tumourigenesis and progression. Here, we investigated the impact of genes associated with copper metabolism (CMRGs) on the prognosis of OC, discovered various CM clusters, and built a risk model to evaluate patient prognosis, immunological features, and therapy response. Methods: 15 CMRGs affecting the prognosis of OC patients were identified in The Cancer Genome Atlas (TCGA). Consensus Clustering was used to identify two CM clusters. lasso-cox methods were used to establish the copper metabolism-related gene prognostic signature (CMRGPS) based on differentially expressed genes in the two clusters. The GSE63885 cohort was used as an external validation cohort. Expression of CM risk score-associated genes was verified by single-cell sequencing and quantitative real-time PCR (qRT-PCR). Nomograms were used to visually depict the clinical value of CMRGPS. Differences in clinical traits, immune cell infiltration, and tumor mutational load (TMB) between risk groups were also extensively examined. Tumour Immune Dysfunction and Rejection (TIDE) and Immune Phenotype Score (IPS) were used to validate whether CMRGPS could predict response to immunotherapy in OC patients. Results: In the TCGA and GSE63885 cohorts, we identified two CM clusters that differed significantly in terms of overall survival (OS) and tumor microenvironment. We then created a CMRGPS containing 11 genes to predict overall survival and confirmed its reliable predictive power for OC patients. The expression of CM risk score-related genes was validated by qRT-PCR. Patients with OC were divided into low-risk (LR) and high-risk (HR) groups based on the median CM risk score, with better survival in the LR group. The 5-year AUC value reached 0.74. Enrichment analysis showed that the LR group was associated with tumor immune-related pathways. The results of TIDE and IPS showed a better response to immunotherapy in the LR group. Conclusion: Our study, therefore, provides a valuable tool to further guide clinical management and tailor the treatment of patients with OC, offering new insights into individualized treatment.
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