Cuproptosis-Related lncRNA Predict Prognosis and Immune Response of LUAD.

Background: Lung cancer is the leading cause of cancer deaths worldwide, primarily due to lung adenocarcinoma (LUAD). However, the heterogeneity of programmed cell death results in varied prognostic and predictive outcomes. This study aimed to develop an LUAD evaluation marker based on cuproptosis-related lncRNAs. Methods: First, transcriptome data and clinical data related to LUAD were downloaded from the Cancer Genome Atlas (TCGA), and cuproptosis-related genes were analyzed to identify cuproptosis-related lncRNAs. Univariate, LASSO, and multivariate Cox regression analyses were conducted to construct cuproptosis-associated lncRNA models. LUAD patients were categorized into high-risk and low-risk groups using prognostic risk values. Kaplan-Meier analysis, PCA, GSEA, and nomograms were employed to evaluate and validate the results. Results: 7 cuproptosis-related lncRNAs were identified, and a risk model was created. High-risk tumors exhibited cuproptosis-related gene alterations in 95.54% of cases, while low-risk tumors showed alterations in 85.65% of cases, mainly involving TP53. The risk value outperformed other clinical variables and tumor mutation burden as a predictor of 1-, 3-, and 5-year overall survival. The cuproptosis-related lncRNA-based risk model demonstrated high validity for LUAD evaluation, potentially influencing individualized treatment approaches. Expression analysis of four candidate cuproptosis-related lncRNAs (AL606834.1, AL161431.1, AC007613.1, and LINC02835) in LUAD tissues and adjacent normal tissues revealed significantly higher expression levels of AL606834.1 and AL161431.1 in LUAD tissues, positively correlating with tumor stage, lymph node metastasis, and histopathological grade. Conversely, AC007613.1 and LINC02835 exhibited lower expression levels, negatively correlating with these factors. High expression of AL606834.1 and AL161431.1 indicated poor prognosis, while low expression of AC007613.1 and LINC02835 was associated with unfavorable outcomes. Univariate and multivariate analyses confirmed these lncRNAs as independent risk factors for LUAD prognosis. Conclusion: The 4 cuproptosis-related (lncRNAsAL606834.1, AL161431.1, AC007613.1, and LINC02835) can accurately predict the prognosis of patients with LUAD and may provide new insights into clinical applications and immunotherapy.

Tumor microenvironment activation amplify oxidative stress promoting tumor energy remodeling for mild photothermal therapy and cuproptosis.

Tumor metabolic reprogramming requires high levels of adenosine triphosphate (ATP) to maintain treatment resistance, which poses major challenges to chemotherapy and photothermal therapy. Especially, high levels of ATP promote copper ion efflux for limiting the curative effect of cuproptosis. Here, an H2S-responsive mesoporous Cu2Cl(OH)3-loading chemotherapeutic cisplatin (CDDP) was synthesized, and the final nanoparticle, CDDP@Cu2Cl(OH)3-CDs (CDCuCDs), was encapsulated by electrostatic action with carbon dots (CDs). CDCuCDs reacted with overproduction H2S in colon tumor to produce photothermic copper sulfide for photothermal therapy. CDDP was released by lysis to achieve chemotherapeutic effects. Importantly, CDDP elevated H2O2 levels in cells through a cascade reaction and continuously transforms H2O2 into highly cytotoxic •OH through chemodynamic therapy between H2O2 and Cu+, which enables nanoparticles to generate •OH and improve the chemotherapeutic efficacy. Highly toxic •OH disrupts mitochondrial homeostasis, prohibiting it from performing normal energy-supplying functions. Down-regulated ATP inhibits heat shock protein expression, which promotes the therapeutic effect of mild photothermal therapy and reduces the efflux of intracellular copper ions, thus improving the therapeutic effect of cuproptosis. Our research provides a potential therapeutic strategy using overproduction H2S responses in tumors, allowing tumor microenvironment-activated •OH nanogenerators to promote tumor energy remodeling for cancer treatment.

The cuproptosis-related signature predicts the prognosis and immune microenvironments of primary diffuse gliomas: a comprehensive analysis.

BACKGROUND: Evidence has revealed a connection between cuproptosis and the inhibition of tumor angiogenesis. While the efficacy of a model based on cuproptosis-related genes (CRGs) in predicting the prognosis of peripheral organ tumors has been demonstrated, the impact of CRGs on the prognosis and the immunological landscape of gliomas remains unexplored. METHODS: We screened CRGs to construct a novel scoring tool and developed a prognostic model for gliomas within the various cohorts. Afterward, a comprehensive exploration of the relationship between the CRG risk signature and the immunological landscape of gliomas was undertaken from multiple perspectives. RESULTS: Five genes (NLRP3, ATP7B, SLC31A1, FDX1, and GCSH) were identified to build a CRG scoring system. The nomogram, based on CRG risk and other signatures, demonstrated a superior predictive performance (AUC of 0.89, 0.92, and 0.93 at 1, 2, and 3 years, respectively) in the training cohort. Furthermore, the CRG score was closely associated with various aspects of the immune landscape in gliomas, including immune cell infiltration, tumor mutations, tumor immune dysfunction and exclusion, immune checkpoints, cytotoxic T lymphocyte and immune exhaustion-related markers, as well as cancer signaling pathway biomarkers and cytokines. CONCLUSION: The CRG risk signature may serve as a robust biomarker for predicting the prognosis and the potential viability of immunotherapy responses. Moreover, the key candidate CRGs might be promising targets to explore the underlying biological background and novel therapeutic interventions in gliomas.

A cuproptosis-related gene DLAT as a novel prognostic marker and its relevance to immune infiltration in low-grade gliomas.

DLAT has been recognized as a cuproptosis-related gene that is crucial for cuproptosis in earlier research. The study is to look at how DLAT affects individuals with low-grade glioma's prognosis and immune infiltration. The Genotype-Tissue Expression (GTEx) database and the TCGA database were used in this work to download RNAseq data in TPM format. DLAT was found to be overexpressed in LGG by comparing DLAT expression levels between LGG and normal brain tissue, and the expression of DLAT was verified by immunohistochemistry and semi-quantitative analysis. Then, the functional enrichment analysis revealed that the biological functional pathways and possible signal transduction pathways involved were primarily focused on extracellular matrix organization, transmembrane transporter complex, ion channel complex, channel activity, neuroactive ligand-receptor interaction, complement and coagulation cascades, and channel activity. The level of immune cell infiltration by plasmacytoid dendritic cells and CD8 T cells was subsequently evaluated using single-sample gene set enrichment analysis, which showed that high DLAT expression was inversely connected with that level of infiltration. The link between the methylation and mRNA transcription of DLAT was then further investigated via the MethSurv database, and the results showed that DLAT's hypomethylation status was linked to a poor outcome. Finally, by evaluating the prognostic value of DLAT using the Cox regression analysis and Kaplan-Meier technique, a column line graph was created to forecast the overall survival (OS) rate at 1, 3, and 5 years after LGG identification. The aforementioned results demonstrated that high DLAT expression significantly decreased OS and DSS, and that overexpression of DLAT in LGG was significantly linked with WHO grade, IDH status, primary therapy outcome, overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) events. DLAT was discovered as a separate predictive sign of OS in the end. DLAT might thus represent a brand-new predictive biomarker.

The crosstalk between copper-induced oxidative stress and cuproptosis: a novel potential anticancer paradigm.

Copper is a crucial trace element that plays a role in various pathophysiological processes in the human body. Copper also acts as a transition metal involved in redox reactions, contributing to the generation of reactive oxygen species (ROS). Under prolonged and increased ROS levels, oxidative stress occurs, which has been implicated in different types of regulated cell death. The recent discovery of cuproptosis, a copper-dependent regulated cell death pathway that is distinct from other known regulated cell death forms, has raised interest to researchers in the field of cancer therapy. Herein, the present work aims to outline the current understanding of cuproptosis, with an emphasis on its anticancer activities through the interplay with copper-induced oxidative stress, thereby providing new ideas for therapeutic approaches targeting modes of cell death in the future.

Identification of diagnostic signature and immune infiltration for ischemic cardiomyopathy based on cuproptosis-related genes through bioinformatics analysis and experimental validation.

BACKGROUND: Ischemic cardiomyopathy (IC) is primarily due to long-term ischemia/hypoxia of the coronary arteries, leading to impaired cardiac contractile or diastolic function. A new form of cell death induced by copper, called "cuproptosis" is related to the development and progression of multiple diseases. The cuproptosis-related gene (CuGs) plays an important role in acute myocardial infarction, while the specific mechanisms of CuGs in ischemic cardiomyopathy remain unclear. METHODS: The expressions of CuGs and their immune characteristics were analyzed with the IC datasets obtained from the Gene Expression Omnibus, namely GSE5406 and GSE57338, identifying core genes associated with IC development. By comparing RF, SVM, GLM and XGB models, the optimal machine learning model was selected. The expression of marker genes was validated based on the GSE57345, GSE48166 and GSE42955 datasets. Construct a CeRNA network based on core genes. Therapeutic chemiacals targeting core genes were acquired using the CTD database, and molecular docking was performed using Autodock vina software. By ligating the left anterior descending (LAD) coronary artery, an IC mouse model is established, and core genes were experimentally validated using Western blot (WB) and immunohistochemistry (IHC) methods. RESULTS: We identified 14 CuGs closely associated with the onset of IC. The SVM model exhibited superior discriminative power (AUC = 0.914), with core genes being DLST, ATP7B, FDX1, SLC31A1 and DLAT. Core genes were validated on the GSE42955, GSE48166 and GSE57345 datasets, showing excellent performance (AUC = 0.943, AUC = 0.800, and AUC = 0.932). The CeRNA network consists of 218 nodes and 264 lines, including 5 core diagnostic genes, 52 miRNAs, and 161 lncRNAs. Chemicals predictions indicated 8 chemicals have therapeutic effects on the core diagnostic genes, with benzo(a)pyrene molecular docking showing the highest affinity (-11.3 kcal/mol). Compared to the normal group, the IC group,which was established by LAD ligation, showed a significant decrease in LVEF as indicated by cardiac ultrasound, and increased fibrosis as shown by MASSON staining, WB results suggest increased expression of DLST and ATP7B, and decreased expression of FDX1, SLC31A1 and DLAT in the myocardial ischemic area (p < 0.05), which was also confirmed by IHC in tissue sections. CONCLUSION: In summary, this study comprehensively revealed that DLST, ATP7B, FDX1, SLC31A1 and DLAT could be identified as potential immunological biomarkers in IC, and validated through an IC mouse model, providing valuable insights for future research into the mechanisms of CuGs and its diagnostic value to IC.

Three Birds with One Stone: Copper Ions Assisted Synergistic Cuproptosis/Chemodynamic/Photothermal Therapy by a Three-Pronged Approach.

Copper is indispensable to organisms, while its homeostatic imbalance may interference normal cellular physiological processes and even induce cell death. Artificially regulating cellular copper content provides a viable strategy to activate antineoplastic effect. In light of this, a copper ions homeostasis perturbator (CuP-CL) with cinnamaldehyde (Cin) packaging and thermosensitive liposome coating is reported. Following laser exposure, the doping of Cu2+ in polydopamine initiates enhanced photothermal therapy (PTT) and unlocks the outer layer of liposome, leading to the release of copper ions and Cin in tumor microenvironment with mild acidity and high glutathione (GSH) levels. The liberative Cu2+ can evoke cuproptosis and chemodynamic therapy (CDT). Meanwhile, leveraging the merits of H2O2 supply and GSH consumption, Cin serves as a tumor microenvironment regulator to amplify Cu2+ mediated cuproptosis and CDT. Additionally, the positive feedback effects of "laser-triggered PTT, PTT accelerates reactive oxygen species (ROS) generation, ROS amplifies lipid peroxide (LPO) accumulation, LPO mediates heat shock proteins (HSPs) clearance, down-regulated HSPs promote PTT" entailed the overall benefit to therapeutic outcomes. Both in vitro and in vivo results corroborate the remarkable antineoplastic performance of CuP-CL by the synergy of cuproptosis/CDT/PTT. Collectively, based on the three-pronged approach, this work plots a viable multimodal regimen for cancer therapy.

Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.

Background: Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophen overdose may contribute to liver injury and even liver failure. Acetaminophen-induced liver injury (AILI) is closely related to mitochondrial oxidative stress and dysfunction, which play critical roles in cuproptosis. Here, we explored the potential role of cuproptosis-related genes (CRGs) in AILI. Methods: The gene expression profiles were obtained from the Gene Expression Omnibus database. The differential expression of CRGs was determined between the AILI and control samples. Protein protein interaction, correlation, and functional enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was evaluated. The AILI mouse model was established by intraperitoneal injection of APAP solution. Quantitative real-time PCR and western blotting were used to validate hub gene expression in the AILI mouse model. The copper content in the mouse liver samples and AML12 cells were quantified using a colorimetric assay kit. Ammonium tetrathiomolybdate (ATTM), was administered to mouse models and AML12 cells in order to investigate the effects of copper chelator on AILI. Results: The analysis identified 7,809 differentially expressed genes, 4,245 of which were downregulated and 3,564 of which were upregulated. Four optimal feature genes (OFGs; SDHB, PDHA1, NDUFB2, and NDUFB6) were identified through the intersection of two machine learning algorithms. Further nomogram, decision curve, and calibration curve analyses confirmed the diagnostic predictive efficacy of the four OFGs. Enrichment analysis indicated that the OFGs were involved in multiple pathways, such as IL-17 pathway and chemokine signaling pathway, that are related to AILI progression. Immune infiltration analysis revealed that macrophages were more abundant in AILI than in control samples, whereas eosinophils and endothelial cells were less abundant. Subsequently, the AILI mouse model was successfully established, and histopathological analysis using hematoxylin-eosin staining along with liver function tests revealed a significant induction of liver injury in the APAP group. Consistent with expectations, both mRNA and protein levels of the four OFGs exhibited a substantial decrease. The administration of ATTAM effectively mitigates copper elevation induced by APAP in both mouse model and AML12 cells. However, systemic administration of ATTM did not significantly alleviate AILI in the mouse model. Conclusion: This study first revealed the potential role of CRGs in the pathological process of AILI and offered novel insights into its underlying pathogenesis.

Copper-Based Composites Nanoparticles Improve Triple-Negative Breast Cancer Treatment with Induction of Apoptosis-Cuproptosis and Immune Activation.

The synergistic effect of apoptosis and cuproptosis, along with the activation of the immune system, presents a promising approach to enhance the efficacy against triple-negative breast cancer (TNBC). Here, two prodrugs are synthesized: a reactive oxygen species (ROS)-responsive prodrug PEG-TK-DOX and a glutathione (GSH)-responsive prodrug PEG-DTPA-SS-CPT. These prodrugs are self-assembled and chelated Cu2+ to prepare nanoparticle PCD@Cu that simultaneously loaded doxorubicin (DOX), camptothecin (CPT), and Cu2+. The elevated levels of ROS and GSH in TNBC cells disrupted the PCD@Cu structure, leading to the release of Cu+, DOX, and CPT and the depletion of GSH. DOX and CPT triggered apoptosis with immunogenic cell death (ICD) in TNBC cells. Simultaneously, PCD@Cu downregulated the expression of copper transporting ATPase 2 (ATP7B), causing a significant accumulation of copper ions in TNBC cells. This further induced the aggregation of lipoylated dihydrolipoamide S-acetyltransferase (DLAT) and downregulation of iron-sulfur (Fe-S) cluster proteins, ultimately leading to cuproptosis and ICD in TNBC. In vitro and in vivo experiments confirmed that PCD@Cu induced apoptosis and cuproptosis in TNBC and activated the immune system, demonstrating strong anti-tumor capabilities. Moreover, PCD@Cu exhibited an excellent biosafety profile. Overall, this study provides a promising strategy for effective TNBC therapy.

FDX1 as a novel biomarker and treatment target for stomach adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is one of the main reasons for cancer-related deaths worldwide. This investigation aimed to define the connection between STAD and Cuproptosis-related genes (CRGs). Cuproptosis is a newly identified form of mitochondrial cell death triggered by copper. AIM: To explore the identification of potential biomarkers for STAD disease based on cuproptosis. METHODS: A predictive model using Gene Ontology (GO), Least Absolute Shrinkage and Selection Operator (LASSO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Variation Analysis (GSVA), and Gene Set Enrichment Analysis analyzed gene interconnections, focusing on 3 copper-related genes and their expression in The Cancer Genome Atlas-STAD. Networks for mRNA-miRNA and mRNA-transcription factor interactions were constructed. The prognostic significance of CRG scores was evaluated using time-receiver operating characteristic, Kaplan-Meier curves, and COX regression analysis. Validation was conducted with datasets GSE26942, GSE54129, and GSE66229. Expression of copper-related differentially expressed genes was also analyzed in various human tissues and gastric cancer subpopulations using the human protein atlas. RESULTS: Three significant genes (FDX1, LIAS, MTF1) were identified and selected via LASSO analysis to predict and classify individuals with STAD into high and low CRG score subgroups. These genes were down-regulated in both risk categories. GO and KEGG analyses highlighted their involvement mainly in the electron transport chain. After validating their differential expression, FDX1 emerged as the most accurate diagnostic marker for gastric cancer. Additionally, the RCircos package localized FDX1 on chromosome 11. CONCLUSION: Our study revealed that FDX1 could be a potential biomarker and treatment target for gastric malignancy, providing new ideas for further scientific research.

Multi-omic validation of the cuproptosis-sphingolipid metabolism network: modulating the immune landscape in osteosarcoma.

Background: The current understanding of the mechanisms by which metal ion metabolism promotes the progression and drug resistance of osteosarcoma remains incomplete. This study aims to elucidate the key roles and mechanisms of genes involved in cuproptosis-related sphingolipid metabolism (cuproptosis-SPGs) in regulating the immune landscape, tumor metastasis, and drug resistance in osteosarcoma cells. Methods: This study employed multi-omics approaches to assess the impact of cuproptosis-SPGs on the prognosis of osteosarcoma patients. Lasso regression analysis was utilized to construct a prognostic model, while multivariate regression analysis was applied to identify key core genes and generate risk coefficients for these genes, thereby calculating a risk score for each osteosarcoma patient. Patients were then stratified into high-risk and low-risk groups based on their risk scores. The ESTIMATE and CIBERSORT algorithms were used to analyze the level of immune cell infiltration within these risk groups to construct the immune landscape. Single-cell analysis was conducted to provide a more precise depiction of the expression patterns of cuproptosis-SPGs among immune cell subtypes. Finally, experiments on osteosarcoma cells were performed to validate the role of the cuproptosis-sphingolipid signaling network in regulating cell migration and apoptosis. Results: In this study, seven cuproptosis-SPGs were identified and used to construct a prognostic model for osteosarcoma patients. In addition to predicting survival, the model also demonstrated reliability in forecasting the response to chemotherapy drugs. The results showed that a high cuproptosis-sphingolipid metabolism score was closely associated with reduced CD8 T cell infiltration and indicated poor prognosis in osteosarcoma patients. Cellular functional assays revealed that cuproptosis-SPGs regulated the LC3B/ERK signaling pathway, thereby triggering cell death and impairing migration capabilities in osteosarcoma cells. Conclusion: The impact of cuproptosis-related sphingolipid metabolism on the survival and migration of osteosarcoma cells, as well as on CD8 T cell infiltration, highlights the potential of targeting copper ion metabolism as a promising strategy for osteosarcoma patients.

Investigation of copper-induced intestinal damage and proteome alterations in Takifugu rubripes: Potential health risks and environmental toxicology detection.

Copper is one of the predominant water pollutants. Excessive exposure to copper can cause harm to animal health, affecting the central nervous system and causing blood abnormalities. Cuproptosis is a novel form of cell death that differs from previous programmed cell death methods. However, the impact of copper on the intestines remains unclear. Therefore, we investigated the effects of different concentrations of copper exposure on the intestinal proteome of Takifugu rubripes (T. rubripes). Relevant biomarkers were used to detect cuproptosis. We revealed the crosstalk relationship between cuproptosis and self-rescue at different concentrations, and discussed the feasibility of using potential cuproptosis indicators as anti-infection factors. We observed intestinal damage in the three copper exposure groups, especially in T. rubripes treated with 100 and 500 µg/L copper, with shedding and breakage of intestinal villus and fuzzy and loose structure of intestinal mucosa. The presence of copper stress not only causes cuproptosis but also oxidative damage caused by reactive oxygen species (ROS). The results of quantitative proteomics by TMT showed that compared to the 50 and 100 µg/L copper exposure groups, the expression of glutaminase, pyruvate kinase, and skin mucus lectin in the 500 µg/L group was significantly increased. The positive mediators COX5A and CTNNB1, as well as the negative mediators CD4 and FDXR, were found to be differentially expressed. Using the protein expression trends of cuproptosis indicator factors FDX1 and DLAT to indicate the concentration of copper ions in the environment. In addition, we found a new effect of promoting ferroptosis: providing additional copper ions can activate the phenomenon of ferroptosis. Our results expand our understanding of the potential health risks of copper in T. rubripes. At the same time, it is of great significance for the process of copper poisoning and the development of new environmental toxicology detection reagents.

S-Allyl-L-cysteine (SAC) inhibits copper-induced apoptosis and cuproptosis to alleviate cardiomyocyte injury.

Cardiomyocyte injury is closely related to various myocardial diseases, and S-Allyl-L-cysteine (SAC) has been found to have myocardial protective effects, but its mechanism is currently unclear. Meanwhile, copper also has various physiological functions, and this study found that copper inhibited cell viability in a concentration and time-dependent manner, and was associated with multiple modes of death. Elesclomol plus CuCl2 (ES + Cu) significantly inhibited cell viability, and this effect could only be blocked by copper chelator TTM, indicating that "ES + Cu" induced cuproptosis in cardiomyocytes. SAC reduced the inhibitory effects of high concentration copper and "ES + Cu" on cell viability in a concentration and time-dependent manner, indicating that SAC plays a cardioprotective role under stress. Further mechanism study showed that high concentration of copper significantly induced cardiomyocyte apoptosis and increased the levels of LDH, MDA and ROS, while SAC inhibited the apoptosis and injury of cardiomyocytes induced by copper. "ES + Cu" significantly increased intracellular copper levels and decreased the expression of FDX1, LIAS, Lip-DLST and Lip-DLAT; FDX1 siRNA did not affect the expression of LIAS, but further reduced the expression of Lip-DLST and Lip-DLAT; SAC did not affect the expression of these genes, but enhanced the effect of "ES + Cu" in down-regulating these gene expression and restored intracellular copper levels. In addition, "ES + Cu" reduced ATP production, weakened the activity of mitochondrial complex I and III, inhibited cell viability, and increased the contents of injury markers LDH, MDA, CK-MB and cTnI, while SAC significantly improved mitochondrial function injury and cardiomyocyte injury induced by "ES + Cu". Therefore, SAC can inhibit apoptosis and cuproptosis to play a cardioprotective role.

Cuproptosis and physical training: A review.

Copper is an essential element in the human body, involved in many physiological and metabolic functions, including coagulation, oxidative metabolism, and hormone production. The maintenance of copper homeostasis within cells is a complex procedure that is intrinsically controlled by a multitude of intricate mechanisms. Disorders of copper homeostasis encompass a wide range of pathological conditions, including degenerative neurological diseases, metabolic disorders, cardio-cerebrovascular diseases, and tumors. Cuproptosis, a recently identified non-apoptotic mode of cell death mode, is characterized by copper dependence and the regulation of mitochondrial respiration. Cuproptosis represents a novel form of cell death distinct from the previously described modes, including apoptosis, necrosis, pyroptosis, and ferroptosis. Excess copper has been shown to induce cuproptosis by stimulating protein toxic stress responses via copper-dependent abnormal oligomerization of lipoylation proteins within the tricarboxylic acid cycle and the subsequent reduction of iron-sulfur cluster protein levels. Ferredoxin1 facilitates the lipoacylation of dihydrolipoyl transacetylase, which in turn degrades iron-sulfur cluster proteins by reducing Cu2+ to Cu+, thereby inducing cell death. Furthermore, copper homeostasis is regulated by the copper transporter, and disturbances in this homeostasis result in cuproptosis. Current evidence suggests that cuproptosis plays an important role in the onset and development of several cardiovascular diseases. Copper-chelating agents, including ammonium tetrathiomolybdate (VI) and DL-penicillamine, have been shown to facilitate the alleviation of cardiovascular disease by inhibiting cuproptosis. It is hypothesized that oxidative phosphorylation inhibitors such as physical training may inhibit cuproptosis by inhibiting the protein stress response. In conclusion, the implementation of physical training may be a viable strategy to reducte the incidence of cuproptosis.

Cuproptosis-related gene DLAT is a biomarker of the prognosis and immune microenvironment of gastric cancer and affects the invasion and migration of cells.

OBJECTIVE: Cuproptosis is a novel cell death dependent on mitochondrial respiration and regulated by copper. This study aimed to investigate the cuproptosis-related gene DLAT potential value in gastric cancer (GC). METHODS: Bioinformatics was used to analyze DLAT expression. DLAT expression in GC cell lines was detected using qRT-PCR. Cell proliferation ability was assessed using CCK8 and cell cycle assay. Cell migration and invasion were assessed using wound healing and transwell assay. A prognostic assessment was performed through survival and Cox regression analysis. DLAT protein expression was analyzed through HPA immunohistochemistry. Biological functions and processes were analyzed through GO and KEGG enrichment analysis and PPI. Correlation with immune cell infiltration and immune checkpoint genes was analyzed for DLAT. RESULTS: DLAT expression was upregulated in GC tissues and cells and correlated with shorter survival for patients. Age, gender, histological typing, lymph node metastasis, and distant metastasis were identified as independent prognostic factors affecting OS in GC. DLAT protein was upregulated in GC. The biological functions and pathways enriched in DLAT were mainly linked to mitochondrial respiration and the TCA cycle. The expression of DLAT was found to be positively correlated with the infiltration of Th and Th2 immune cells and only positively correlated with the expression of the BTN2A1 immune checkpoint gene. CONCLUSION: DLAT has the potential to serve as a prognostic assessment factor in GC. The expression of DLAT was correlated with immune infiltration and tumor immune escape, providing a new target for immunotherapy of GC.

Quercetin Attenuates Acute Kidney Injury Caused by Cisplatin by Inhibiting Ferroptosis and Cuproptosis.

Ferroptosis, an iron- and ROS-dependent form of regulated cell death. Cuproptosis is a novel form of cellular demise mode. Quercetin, a natural flavonoid, has demonstrated a range of pharmacological activities, including anti-cancer, anti-inflammatory, and antioxidant properties. In this research, we investigated the quercetin effect on cisplatin-induced acute kidney and its mechanism associated ferroptosis and cuproptosis. The HK-2 cells were used in this research. Cell viability was evaluated using the CCK-8 assay. Acute kidney injury (AKI) models were established to perform in vivo experiments. Renal tissue homogenate was used to determine ROS, LPO, MDA, PA, etc., to assess ferroptosis and cuproptosis. To perform bioinformatic analysis, microarray data from the GEO database was utilized. Real-time PCR analysis and ELISA was explored the mechanism of ferroptosis and cuproptosis. We found that ferroptosis and cuproptosis in AKI were abnormally activated caused by cisplatin, and that quercetin attenuated AKI by inhibiting ferroptosis and cuproptosis. QCT suppressed ferroptosis by reducing malondialdehyde (MDA) and ROS levels and increasing glutathione (GSH) levels and alleviated cuproptosis by reducing copper ion, pyruvate (PA) and HSP70 levels. Moreover, bioinformatic analysis revealed that the ferroptosis-related gene SLC7A11 and the cuproptosis-related genes ATP7B and GLS were the differential expression genes. And QCT significantly increased the expression or activity of SLC7A11, GPX4, ATP7B, and GLS in Cis-AKI mice. Our findings highlight the clinical importance of quercetin, which guards against cisplatin-induced acute kidney injury by suppressing ferroptosis and cuproptosis.

A novel signature constructed by cuproptosis-related RNA methylation regulators suggesting downregulation of YTHDC2 may induce cuproptosis resistance in colorectal cancer.

BACKGROUND: A newly identified type of cell death due to intracellular copper accumulation is known as cuproptosis and RNA methylation is a post-transcriptional modification mechanism, both of which perform vital roles in the immune microenvironment of colorectal cancer (CRC), but the link between the two needs more research. METHODS: TCGA database provided RNA-seq data and details clinically of CRC samples. Cuproptosis-related RNA methylation regulators (CRRMRs) were identified by correlation analysis. We screened 6 CRRMRs for prognostic model construction by employing LASSO-Cox regression analysis and calculated risk scores by CRRMRs (CuMS). GSE39582 and GSE38832 cohort were used as external validation sets. This research concentrated on the connection between the prognostic model and somatic mutation, anti-cancer drug sensitivity, immune infiltration, immune checkpoint expression. In addition, we investigated the differential expression of YTHDC2 in epithelial cell subpopulations by single-cell analysis with GSE166555, calculated cuproptosis scores and performed pathway enrichment. In vitro experiments were performed to explore the consequences of knockdown of YTHDC2 on CRC cell proliferation and migration, as well as changes in CRC cell viability in response to elesclomol after knockdown of YTHDC2. In vivo experiments, we constructed the cell line-derived xenograft model to further validate the results of the in vitro experiments. RESULTS: The prognosis of CRC can be predicted by CuMS, which GSE39582 and GSE38832 confirmed. Two CuMS groups showed different tumor mutation burden (TMB) and immune infiltration. CuMS was connected to emerging immune checkpoints CD47 and PVR, therefore, it can be clinically complementary to TMB and microsatellite instability (MSI) status. In single-cell analysis, a subpopulation of epithelial cells with high YTHDC2 expression had a high cuproptosis score. In vitro experiments, knocking down YTHDC2 promoted cell proliferation and migration in CRC, and weaken the inhibitory effect of elesclomol and elesclomol-Cu on cell viability, which in vivo experiments validated. CONCLUSION: We developed a prognostic model constructed by 6 CRRMRs to assess overall survival and immune microenvironment of CRC patients. YTHDC2 might regulate cuproptosis in multiple ways.

Construction and validation of a prognostic and therapeutic cuproptosis- and immune-related gene signature in hepatocellular carcinoma.

Background: Abnormal accumulation of copper could induce cell death and tumor growth, and affect tumor immune escape by regulating programmed cell death ligand 1 (PD-L1) expression. This study aims to establish and verify a risk signature based on cuproptosis- and immune-related genes (CIRGs) for hepatocellular carcinoma (HCC) management. Methods: HCC RNA-seq and clinical data were obtained from open databases. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were utilized to screen CIRGs and develop a risk signature. The signature's value for clinical applications, functional enrichment, tumor mutation burden (TMB), and immune profile analyses were investigated systematically. Results: A risk signature was developed utilizing seven CIRGs, and it performed well in predicting the prognosis of HCC patients in both the training and external validation cohorts. The model's risk score was discovered to be related to important clinical features. Top 15 mutated genes in HCC were significantly different among different risk groups. High-risk patients showed higher TMB, and high TMB was closely identified with a poorer prognosis. Immune profile analyses showed that immune infiltration level was higher in low-risk patients than high-risk patients, and the level of immune checkpoint genes expression varied significantly between patients in two different risk groups. Low-risk patients responded well to immunotherapy treatment, whereas high-risk patients were more sensitive to sorafenib, doxorubicin, gemcitabine and AKT (also known as protein kinase B) inhibitors. Conclusions: The established risk signature based on CIRGs can not only well predict the prognosis of HCC patients but is also promising in evaluating TMB and treatment response to immunotherapy, targeted therapy and chemotherapy, which has the potential to assist in the clinical management of HCC.

Bioinformatics prediction and experimental verification identify a cuproptosis-related gene signature as prognosis biomarkers of hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) of which its prognostic prediction is still unclarified is a highly heterogeneous disease. Cuproptosis is a form of cell death that depends on copper regulation. Whether the cuproptosis-related genes can be the prognostic indicators of HCC is yet to be elucidated. The aim of this study is to investigate whether cuproptosis-related genes play a role in HCC and can be used as a diagnostic index to predict the occurrence of liver cancer. Methods: We downloaded HCC patients' gene expression profiles and their corresponding clinical data from a public database. To screen data, we used single factor Cox regression analysis, meanwhile, polymerase chain reaction (PCR) was used for the verification. After that, the risk score was calculated and the relationship between risk score and clinical factors was analyzed. Besides, a nomogram map was constructed for predicting the prognosis of HCC, and calibration map and decision curve analysis (DCA) map were used to test the model. Results: Compared to the high expression group of four cuproptosis-related genes, the low expression group showed better overall survival (OS) [hazard ratio (HR) =2.58; 95% confidence interval (CI): 1.72-3.89, P<0.01]. The expression of the four cuproptosis-relate genes increased in liver cancer cell lines compared to liver cell lines (P<0.05). Based on these four genes, we calculated the risk score and divided them into two groups as high-risk group and low-risk group. The risk factor map showed the high-risk group had shorter survival time and the four genes were highly expressed. The area under curve (AUC) of receiver operating characteristic (ROC) prediction curve for the first year was 0.726. Risk scores were closely related to clinical factors and immune cells. Finally, we constructed a nomogram for predicting the prognosis of HCC. Conclusions: The risk score for cuproptosis-related genes was established and involved in the construction of the nomogram, providing a new perspective on the prognosis and copper metabolism of HCC.

Multi-omics analysis of the prognostic and biological role of cuproptosis-related gene in gastric cancer.

Background: A considerable number of gastric cancer (GC) patients cannot receive benefits from current treatments. We aimed to identify possible biomarkers of cuproptosis-related genes (CRGs) in GC patients, which may help guide precision medicine-based decision-making. Methods: RNA sequencing data, copy number variations (CNVs) data, and single nucleotide variant (SNV) data were obtained from The Cancer Genome Atlas (TCGA) database and Gene Set Cancer Analysis (GSCA) database. Chi-squared test was adopted to screen differentially expressed CRGs (DE-CRGs) between samples from 14 kinds of carcinoma and adjacent tissue samples. Then, GC samples were divided into high- and low-expressed groups based on DE-CRGs for further survival analyses and the selection of biomarkers. Methylation sites related with biomarkers were acquired. The correlation between immune cells and biomarkers was verified. Finally, miRNA-mRNA, TFs-mRNA, and co-expression networks were established to detect factors with regulating effects on biomarkers. Results: Three CRGs including LIAS, GLS, and CDKN2A were identified as biomarkers in GC patients. Three methylation sites with a significant survival effect including cg13601799, 07562918, and 07253264 were acquired. Then, we found that B cells native was significantly correlated with CDKN2A, four immune cells such as T cells regulatory are significantly correlated with GLS, and two immune cells such as T cells CD4 memory activated were significantly correlated with LIAS. Moreover, 10 miRNAs in the miRNA-mRNA network and three transcription factors (TFs) in the TFs-mRNA network had a significant correlation with overall survival (OS). Finally, 20 enrichment functions were obtained on the basis of the co-expression network. Conclusions: Three biomarkers with a prognosis prediction value of GC were found, and multi-factor regulatory networks were constructed to screen out 13 factors with regulating influences of biomarkers.