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PubMed2025

The molecular mechanism of cuproptosis and research progress in pancreatic diseases.

PURPOSE: Cuproptosis has been proven to be a novel mode of cell death, distinct from other types of cell death such as necrosis, ferroptosis, pyroptosis, and apoptosis. This study aims to systematically review the molecular mechanisms of cuproptosis in recent years and its research progress in pancreatic diseases. METHODS: By searching PubMed and Web of Science databases, 113 key literatures were included for thematic analysis, covering the molecular mechanism of cuproptosis and its role in the occurrence and development of pancreatic cancer, acute and chronic pancreatitis, diabetes, pancreatic cyst, pancreatic injury and pancreatic neuroendocrine tumor. RESULTS: Cuproptosis refers to the accumulation of copper ions in cells, which leads to instability of ferritin and aggregation of acylated proteins, resulting in oxidative stress-related cell death. Recent studies have shown that cuproptosis plays an important role in the occurrence and development of various pancreatic diseases, such as pancreatic cancer, acute and chronic pancreatitis, diabetes, pancreatic cysts, pancreatic injuries and pancreatic neuroendocrine tumor. The inducers of cuproptosis, such as disulfiram, chloroquinolones, and perilla phenols, alleviate pancreatic cancer by promoting cell cuproptosis. Copper chelators such as tetraethylenepentamine and tetrathiomolybdate promote the recovery of pancreatic injury by inhibiting cell cuproptosis. CONCLUSIONS: Cuproptosis plays a crucial role in the pathogenesis of pancreatic diseases. Further research on the cuproptosis pathway may become a potential target for the treatment of pancreatic diseases.

Animals↗

PubMed2026

A cuproptosis-related lncRNAs-based risk signature for predicting prognosis and immune status in glioma.

BACKGROUND: Glioma is one of the most prevalent primary malignant brain tumors, characterized by poor prognosis and limited treatment options. Recent studies have identified cuproptosis, a novel copper-dependent form of regulated cell death, as a critical mechanism involved in tumor progression. However, the role of cuproptosis-related long non-coding RNAs (lncRNAs) in glioma remains not fully clarified. This study aimed to develop and validate a prognostic model based on cuproptosis-associated lncRNAs to predict patient outcomes and guide individualizing therapeutic strategies. METHODS: Transcriptomic profiles and clinical data were obtained from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), and the Chinese Glioma Genome Atlas (CGGA) databases. Cuproptosis -related prognostic lncRNAs were filtered via univariate and multivariate Cox and Least absolute shrinkage and selection operator (LASSO) regression analyses, which were selected to establish a prognostic model for glioma. Samples were divided into high- and low-risk groups, and the predictive performance of the prognostic model was evaluated based on receiver operating characteristic (ROC) curves, Kaplan-Meier (K-M) survival curves, and a nomogram. In addition, immune cell infiltration, tumor mutational burden (TMB), immunophenoscore (IPS), Tumor Immune Dysfunction and Exclusion (TIDE) and drug sensitivity were analyzed. Expression levels of selected lncRNAs and proteins were validated using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting. RESULTS: An 11-lncRNA signature associated with cuproptosis was established, and the risk score derived from this model was identified as an independent prognostic factor for glioma. The model exhibited excellent predictive ability, with area under the curve (AUC) values of 0.880, 0.913, and 0.866 for 1-, 3-, and 5-year survival, respectively. Higher TMB, immune checkpoint expression, and IPS were observed in the high-risk group and no significant difference was observed in TIDE between risk groups. Drug sensitivity analysis identified TPCA-1, KIN001-135, and ispinesib mesylate as potential therapeutic agents. Expression validation in glioma cells further supported the biological relevance of the selected lncRNAs. CONCLUSIONS: This cuproptosis-related lncRNA-based signature demonstrates strong prognostic value and may serve as a promising tool for glioma risk stratification and personalized treatment selection.

Glioma↗

PubMed2024

Systematic analysis of cuproptosis abnormalities and functional significance in cancer.

BACKGROUND: Cuproptosis is a recently discovered type of cell death, but the role and behavior of cuproptosis-related genes (CuRGs) in cancers remain unclear. This paper aims to address these issues by analyzing the multi-omics characteristics of cancer-related genes (CuRGs) across various types of cancer. METHOD: To investigate the impact of somatic copy number alterations (SCNA) and DNA methylation on CRG expression, we will analyze the correlation between these factors. We developed a cuproptosis index (CPI) model to measure the level of cuproptosis and investigate its functional roles. Using this model, we assessed the clinical prognosis of colorectal cancer patients and analyzed genetic changes and immune infiltration features in different CPI levels. RESULTS: The study's findings indicate that the majority of cancer-related genes (CuRGs) were suppressed in tumors and had a positive correlation with somatic copy number alterations (SCNA), while having a negative correlation with DNA methylation. This suggests that both SCNA and DNA methylation have an impact on the expression of CuRGs. The CPI model is a reliable predictor of survival outcomes in patients with colorectal cancer and can serve as an independent prognostic factor. Patients with a higher CPI have a worse prognosis. We conducted a deeper analysis of the genetic alterations and immune infiltration patterns in both CPI positive and negative groups. Our findings revealed significant differences, indicating that CuRGs may play a crucial role in tumor immunity mechanisms. Additionally, we have noticed a positive correlation between CuRGs and various crucial pathways that are linked to the occurrence, progression, and metastasis of tumors. CONCLUSIONS: Overall, our study systematically analyzes cuproptosis and its regulatory genes, emphasizing the potential of using cuproptosis as a basis for cancer therapy.

Humans↗

PubMed2026

UBE2D4 Upregulation Promotes Cuproptosis Sensitivity in Colorectal Cancer.

BACKGROUND: Cuproptosis, a copper-dependent form of regulated cell death, represents a potential therapeutic vulnerability in colorectal cancer (CRC). However, the regulatory mechanisms governing cuproptosis in CRC remain largely unknown. METHODS: UBE2D4 expression was analyzed in the TCGA-COAD cohort and validated in CRC cell lines (HCT116, HT29) and normal colon epithelial cells (FHC) by qRT-PCR and western blot. Paired CRC and adjacent normal tissues (n = 5) were also examined by western blot. UBE2D4-knockdown HT29 cells were generated by transient siRNA transfection to assess cell viability (CCK-8), migration (wound healing assay), and expression of cuproptosis-related genes (DLAT, HSP70, LIAS) under copper overload conditions (elesclomol+CuSO4). RESULTS: UBE2D4 was significantly upregulated in CRC tissues and cell lines compared to normal controls. In paired clinical samples, western blot confirmed that UBE2D4 protein expression was elevated in tumor tissues, accompanied by increased DLAT, HSP70 and LIAS. Copper overload induced typical cuproptotic mitochondrial morphology and triggered a marked upregulation of UBE2D4, DLAT, and HSP70, alongside downregulation of LIAS. UBE2D4 silencing had no effect on baseline cell viability or migration but significantly rescued cells from copper-induced cytotoxicity. Genetically, UBE2D4 knockdown specifically attenuated the copper-induced elevation of DLAT, while restoring HSP70 and LIAS to near-baseline levels. CONCLUSION: These findings identify UBE2D4 as a genetically upregulated and functionally significant gene in colorectal cancer. Its upregulation correlates with altered expression of cuproptosis-related genes, particularly DLAT, suggesting that UBE2D4 expression status may represent a genetic determinant of cuproptosis sensitivity in CRC. This study provides a genetic basis for stratifying CRC patients who might benefit from copper-based therapeutic strategies.

Humans↗

PubMed2026

Glutathione reductase deficiency potentiates the immunogenicity of ferroptosis and cuproptosis via amplified reactive oxygen species accumulation and cGAS-STING pathway activation.

BACKGROUND: Cancer remains a major therapeutic challenge due to drug resistance and metastasis, processes driven by oxidative stress and redox imbalance. Targeting this vulnerability through ferroptosis (iron-dependent lipid peroxidation) and cuproptosis (copper-driven mitochondrial dysfunction), two ROS-mediated cell death pathways, offers a promising therapeutic strategy. However, clinical translation is hindered by incomplete understanding of their redox regulation and limited immunogenicity. METHODS: A genome-wide CRISPR knockout screen was performed to identify key regulators of ferroptosis. Genetic depletion or pharmacological inhibition of candidate genes was evaluated across multiple cancer cell lines for sensitivity to ferroptosis inducer RSL3 and the cuproptosis inducer elesclomol (Es). Antitumor efficacy was assessed in xenograft, orthotopic, metastatic, and syngeneic mouse models, alone or combined with immune checkpoint inhibitors. Mechanistic studies also examined ROS production, mitochondrial stress, mitochondrial DNA release, cGAS-STING activation, and immune responses within the tumor microenvironment. RESULTS: Glutathione reductase (GSR), a central enzyme maintaining reduced glutathione (GSH) homeostasis, was identified as the top suppressor of ferroptosis. GSR knockout or pharmacological inhibition markedly sensitized diverse cancer cell lines to RSL3-induced ferroptosis, while GSR overexpression conferred resistance. Strikingly, GSR depletion also enhanced sensitivity to cuproptosis triggered by the copper ionophore Es. In multiple in vivo tumor models, GSR inhibition synergizes with RSL3 or Es to suppress tumor growth, inhibit lung metastasis, and prolong survival. Mechanistically, GSR deficiency amplified ROS production, induced mitochondrial stress, and triggered the cytosolic mitochondrial DNA release under ferroptotic or cuproptotic stress, activating the cGAS-STING pathway in vitro and in vivo. This increased inflammatory cytokine production, promoted immunogenic cell death, and enhanced the release of damage-associated molecular patterns (DAMPs), including HMGB1. Together, GSR inhibition combined with a ferroptosis or cuproptosis inducer transformed the tumor microenvironment into a highly immune stimulatory state, thereby enhancing the efficacy of immune checkpoint blockade through increased dendritic cell activation and T-cell infiltration and activation. CONCLUSIONS: GSR represents a key molecular node connecting and modulating ferroptosis and cuproptosis through redox regulation. Targeting GSR amplifies ROS-mediated immunogenic cell death, triggers cGAS-STING activation in cancer cells, and enhances the efficacy of cancer immunotherapy, providing a promising redox-based therapeutic strategy.

Ferroptosis↗

PubMed2026

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2024

Identification of cuproptosis-realated key genes and pathways in Parkinson's disease via bioinformatics analysis.

INTRODUCTION: Parkinson's disease (PD) is the second most common worldwide age-related neurodegenerative disorder without effective treatments. Cuproptosis is a newly proposed conception of cell death extensively studied in oncological diseases. Currently, whether cuproptosis contributes to PD remains largely unclear. METHODS: The dataset GSE22491 was studied as the training dataset, and GSE100054 was the validation dataset. According to the expression levels of cuproptosis-related genes (CRGs) and differentially expressed genes (DEGs) between PD patients and normal samples, we obtained the differentially expressed CRGs. The protein-protein interaction (PPI) network was achieved through the Search Tool for the Retrieval of Interacting Genes. Meanwhile, the disease-associated module genes were screened from the weighted gene co-expression network analysis (WGCNA). Afterward, the intersection genes of WGCNA and PPI were obtained and enriched using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, the key genes were identified from the datasets. The receiver operating characteristic curves were plotted and a PPI network was constructed, and the PD-related miRNAs and key genes-related miRNAs were intersected and enriched. Finally, the 2 hub genes were verified via qRT-PCR in the cell model of the PD and the control group. RESULTS: 525 DEGs in the dataset GSE22491 were identified, including 128 upregulated genes and 397 downregulated genes. Based on the PPI network, 41 genes were obtained. Additionally, the dataset was integrated into 34 modules by WGCNA. 36 intersection genes found from WGCNA and PPI were significantly abundant in 7 pathways. The expression levels of the genes were validated, and 2 key genes were obtained, namely peptidase inhibitor 3 (PI3) and neuroserpin family I member 1 (SERPINI1). PD-related miRNAs and key genes-related miRNAs were intersected into 29 miRNAs including hsa-miR-30c-2-3p. At last, the qRT-PCR results of 2 hub genes showed that the expressions of mRNA were up-regulated in PD. CONCLUSION: Taken together, this study demonstrates the coordination of cuproptosis in PD. The key genes and miRNAs offer novel perspectives in the pathogenesis and molecular targeting treatment for PD.

Humans↗

PubMed2026

Metabolic-cell-death gene trio predicts survival and cuproptosis sensitivity in colorectal cancer.

BACKGROUND: Metabolic cell death (MCD) modulates colorectal cancer (CRC) progression, yet its prognostic value remains unexplored. We aimed to build an MCD-centred gene signature for outcome prediction and precision therapy. METHODS: Transcriptomes of 1,174 CRC patients were integrated. Weighted gene co-expression network analysis, differential expressions and least absolute shrinkage and selection operator (LASSO) + random survival forest were successively applied to derive a three-gene (CDKN2A/MPC1/AHCY) risk model. Functional, immune-infiltration, drug-sensitivity and genomic analyses were performed, followed by validation in fresh clinical specimens and cell lines. RESULTS: Integrative metabolic-death transcriptomics identified CDKN2A, MPC1 and AHCY as the hub drivers of CRC. Their three-gene signature robustly stratified patients into high- and low-risk subsets [3-year area under the curve (AUC) 0.83-0.85, P<0.001]. High-risk tumors were enriched for extracellular matrix (ECM)-receptor-interaction pathways, displayed abundant myeloid-derived suppressor cell (MDSC) infiltration and were more vulnerable to AZD8186, AZ960 and JAK inhibitors. Guided by these in-silico findings, we functionally confirmed that CDKN2A silencing markedly repressed proliferation, invasion and migration of SW480/HCT116 cells and potentiated cuproptosis via up-regulation of lipoylated DLAT/DLST and CTR1. CONCLUSIONS: We report the first MCD-derived prognostic platform for CRC that simultaneously predicts survival and therapeutic response. Targeting CDKN2A-enhanced cuproptosis represents a promising metabolic-precision strategy for high-risk patients.

Colorectal cancer (CRC)↗

PubMed2025

CYFIP1 coordinate with RNMT to induce osteosarcoma cuproptosis via AURKAIP1 m7G modification.

Osteosarcoma (OS) presents challenges due to its genomic instability and complexity, necessitating investigation into its oncogenesis and progression mechanisms. Recent studies have implicated m7G, a post-transcriptional modification, in the development of various cancers. However, research on m7G modification in OS remains limited. This study aimed to explore the impact of m7G modification in OS, focusing on the role and mechanism of CYFIP1, a member of m7G cap binding complexes. Our findings demonstrated prominent anti-OS effects of CYFIP1 in vitro and vivo. Mechanistically, CYFIP1 collaborated with RNMT to induce the m7G methylation of AURKAIP1 mRNA, which resulted in the stability and the increasing translation of AURKAIP1 mRNA. AURKAIP1, a kind of mitochondrial small ribosomal subunit protein, exhibited increased expression, leading to the dysregulation of mitochondrial translation. This, in turn, caused an increase in the expression of FDX1, eventually triggering cuproptosis in OS cells and repressing OS occurrence and progression. In summary, our study identified the CYFIP1/RNMT/AURKAIP1/FDX1 axis as a potential therapeutic target for OS. These insights contribute to OS research and may guide the development of novel treatments for this challenging disease.

Humans↗

PubMed2026

A TIGIT nanotrapping-guided STING-activatable immunometabolic strategy overcomes innate immune silence and T cell exhaustion in breast cancer.

Breast cancer exhibits a profoundly immunosuppressive tumor microenvironment (TME), where innate immune silence prevents antigen sensing and persistent T cell exhaustion limits effector responses, rendering most immunotherapies ineffective. Clinical profiling of 1093 The Cancer Genome Atlas (TCGA) cases identified a glucose-fueled glutathione (GSH)-glutathione peroxidase 4 (GPX4)-dihydrolipoamide S-acetyltransferase (DLAT) axis as a dominant metabolic shield that suppresses oxidative stress, and thereby enforces both stimulator of interferon genes (STING) silence and CD8+ T cell exclusion. To dismantle this barrier, we developed an immunometabolic nanotherapy, GOx/ES-CO-LDH@TIGIT-Nanotrap (TNT). In acidic tumors, proton-driven layered double hydroxide (LDH) disassembly releases glucose oxidase (GOx) and extremely small cuprous oxide (ES-CO). GOx depletes glucose and nicotinamide adenine dinucleotide phosphate (NADPH) to induce disulfidptosis, while ES-CO releases cuprous ions (Cu+) that trigger cuproptosis via binding to lipoylated mitochondrial proteins. Their mutual biochemical amplification produces a cycloacclerated disulfidptosis-cuproptosis cascade that collapses the GSH-GPX4-DLAT axis and restores STING activation. Meanwhile, the macrophage-derived T cell immunoreceptor with Ig and ITIM domains (TIGIT) Nanotrap sequesters CD155 to prevent T cell suppression. Together, this coordinated innate reactivation and adaptive rescue converts immune-cold tumors into STING-inflamed and T cell responsive lesions.

Female↗

PubMed2026

scRNA-seq and bulk RNA-seq reveal the characteristics of macrophage copper metabolism and establish a risk signature in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent malignancy with an urgent need for improved prognostic stratification and treatment-response prediction. This study aimed to explore a macrophage copper metabolism-associated prognostic model and to investigate the relationship between this risk model and the tumor immune microenvironment. METHODS: The FindClusters function was used to analyze cell clusters, and CellChat and CellPhoneDB/LIANA were employed for cell-cell communication analysis. Copper metabolism-related genes were sourced from the MSigDB database. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis, and a nomogram was constructed by integrating the prognostic model with clinicopathological factors. Additional analyses were performed to map the seven model genes in single-cell data, assess model uncertainty and robustness, evaluate macrophage/copper/cuproptosis-related transcriptional programs, and examine the correlations between risk score, immune infiltration and predicted drug sensitivity. RESULTS: Using single-cell RNA sequencing (scRNA-seq) data, we identified four macrophage subpopulations. Macrophages with high SPP1 expression showed close interaction with T cell populations and were associated with copper ion metabolism. By incorporating 141 copper metabolism-related genes and using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a seven-gene risk prediction model. Additional single-cell mapping showed that the model genes were detectable in the HCC single-cell dataset and showed a macrophage-associated expression pattern. The model showed moderate prognostic discrimination in TCGA-LIHC, whereas its external performance was heterogeneous and remained evaluable across external cohorts, with performance varying among datasets. Immune and mechanism-related analyses suggested that the risk signature was associated with macrophage-related infiltration, copper metabolism and cuproptosis-related transcriptional programs. Drug sensitivity analysis nominated Daporinad as a computationally predicted candidate compound, supporting Daporinad as a pharmacogenomic candidate for follow-up investigation. CONCLUSIONS: By integrating scRNA-seq and bulk RNA sequencing (RNA-seq) data, we constructed a macrophage copper metabolism-associated prognostic signature for HCC. The risk score was associated with survival, immune microenvironment features and predicted drug response, providing a transcriptomic framework for risk stratification and therapeutic hypothesis generation.

Hepatocellular carcinoma (HCC)↗