Copper Metabolism and Cuproptosis:Molecular Mechanisms and Therapeutic Perspectives in Neurodegenerative Diseases

Copper is an essential trace element,and plays a vital role in numerous physiological processes within the human body.During normal metabolism,the human body maintains copper homeostasis.Copper deficiency or excess can adversely affect cellular function.Therefore,copper homeostasis is stringently regulated.Recent studies suggest that copper can trigger a specific form of cell death,namely,cuproptosis,which is triggered by excessive levels of intracellular copper.Cuproptosis induces the aggregation of mitochondrial lipoylated proteins,and the loss of iron-sulfur cluster proteins.In neurodegenerative diseases,the pathogenesis and progression of neurological disorders are linked to copper homeostasis.This review summarizes the advances in copper homeostasis and cuproptosis in the nervous system and neurodegenerative diseases.This offers research perspectives that provide new insights into the targeted treatment of neurodegenerative diseases based on cuproptosis.

Detection of Al, Mg, Ca, and Zn in copper slag by LIBS combined with calibration curve and PLSR methods

The precise measurement of Al, Mg, Ca, and Zn composition in copper slag is crucial for effective process control of copper pyrometallurgy. In this study, a remote laser-induced breakdown spectroscopy(LIBS) system was utilized for the spectral analysis of copper slag samples at a distance of 2.5 m. The composition of copper slag was then analyzed using both the calibration curve(CC) method and the partial least squares regression(PLSR) analysis method based on the characteristic spectral intensity ratio. The performance of the two analysis methods was gauged through the determination coefficient(R^(2)), average relative error(ARE), root mean square error of calibration(RMSEC), and root mean square error of prediction(RMSEP). The results demonstrate that the PLSR method significantly improved both R^(2) for the calibration and test sets while reducing ARE, RMSEC, and RMSEP by 50% compared to the CC method. The results suggest that the combination of LIBS and PLSR is a viable approach for effectively detecting the elemental concentration in copper slag and holds potential for online detection of the elemental composition of high-temperature molten copper slag.

Copper slag assisted coke reduction of phosphogypsum for sulphur dioxide preparation

The reduction of phosphogypsum(PG)to lime slag and SO_(2)using coke can effectively alleviate the environmental problems caused by PG.However,the PG decomposition temperature remains high and the product yield remains poor.By adding additives,the decomposition temperature can be further reduced and PG decomposition rate and product yield can be improved.However,the use of current additives such as Fe_(2)O_(3)and SiO_(2)brings the problem of increasing economic cost.Therefore,it is proposed to use solid waste copper slag(CS)as a new additive to reduce PG to prepare SO2,which can reduce the cost and meet the environmental benefits at the same time.The effects of proportion,temperature and thermostatic time on PG decomposition are investigated by experimental and kinetic analysis combined with FactSage thermodynamic calculations to optimize the roasting conditions.Finally,the reaction mechanism is proposed.It is found that adding CS to the coke and PG system can increase the rate of PG decomposition and SO_(2)yield while lowering the PG decomposition temperature.For example,when the CS/PG mass ratio increases from 0 to 1,PG decomposition rate increases from 83.38%to 99.35%,SO_(2)yield increases from 78.62%to 96.81%,and PG decomposition temperature decreases from 992.4℃to 949.6℃.The optimal reaction parameters are CS/PG mass ratio of 1,Coke/PG mass ratio of 0.06 at 1100℃for 20 min with 99.35%PG decomposition rate and 96.81%SO_(2) yield.The process proceeds according to the following reactions:2CaSO_(4)+ 0.7C + 0.8Fe_(2)SiO_(4)→0.8Ca_(2)SiO_(4)+ 0.2Ca_(2)Fe_(2)O_(5)+ 0.4Fe_(3)O_(4)+2SO_(2)+ 0.7CO_(2)Finally,a process for decomposing PG with coke and CS is proposed.

Role of copper chelating agents: between old applications and new perspectives in neuroscience

The role of copper element has been an increasingly relevant topic in recent years in the fields of human and animal health, for both the study of new drugs and innovative food and feed supplements. This metal plays an important role in the central nervous system, where it is associated with glutamatergic signaling, and it is widely involved in inflammatory processes. Thus, diseases involving copper(Ⅱ) dyshomeostasis often have neurological symptoms, as exemplified by Alzheimer's and other diseases(such as Parkinson's and Wilson's diseases). Moreover, imbalanced copper ion concentrations have also been associated with diabetes and certain types of cancer, including glioma. In this paper, we propose a comprehensive overview of recent results that show the importance of these metal ions in several pathologies, mainly Alzheimer's disease, through the lens of the development and use of copper chelators as research compounds and potential therapeutics if included in multi-target hybrid drugs. Seeing how copper homeostasis is important for the well-being of animals as well as humans, we shortly describe the state of the art regarding the effects of copper and its chelators in agriculture, livestock rearing, and aquaculture, as ingredients for the formulation of feed supplements as well as to prevent the effects of pollution on animal productions.

Role of copper in central nervous system physiology and pathology

Copper is a transition metal and an essential element for the organism,as alterations in its homeostasis leading to metal accumulation or deficiency have pathological effects in several organs,including the central nervous system.Central copper dysregulations have been evidenced in two genetic disorders characterized by mutations in the copper-ATPases ATP7A and ATP7B,Menkes disease and Wilson’s disease,respectively,and also in multifactorial neurological disorders such as Alzheimer’s disease,Parkinson’s disease,amyotrophic lateral sclerosis,and multiple sclerosis.This review summarizes current knowledge about the role of copper in central nervous system physiology and pathology,reports about unbalances in copper levels and/or distribution under disease,describes relevant animal models for human disorders where copper metabolism genes are dysregulated,and discusses relevant therapeutic approaches modulating copper availability.Overall,alterations in copper metabolism may contribute to the etiology of central nervous system disorders and represent relevant therapeutic targets to restore tissue homeostasis.

OsMYB84,a transcriptional regulator of OsCOPT2 and OsHMA5,modulates copper uptake and transport and yield production in rice

Transcription factors regulating crop uptake and translocation of the micronutrient Cu have not been identified.We isolated a novel R2R3-MYB transcription factor,OsMYB84,and showed that it was a positive regulator involved in uptake and transport of Cu via activation of OsCOPT2 and OsHMA expression.OsMYB84 was highly expressed in roots and anthers and induced by Cu.Overexpression of OsMYB84 promoted uptake and root-to-shoot translocation of Cu in rice,facilitated Cu distribution into grain and increased grain yield.In contrast,mutation of OsMYB84 reduced Cu concentration in xylem sap.OsMYB84 bound to the promoter region of OsCOPT2 and OsHMA5 and upregulated their expression.OsCOPT2 mutants showed reduced uptake of Cu and OsHMA5 overexpression lines showed increased root-to-shoot translocation of Cu.

Removal of rubidium from brine by an integrated film of sulfonated polysulfone/graphene/potassium copper ferricyanide

A novel integrated film of sulfonated polysulfone/graphene/potassium copper ferricyanide(KCuFC/SPSG)was used for selectively extracting rubidium ion(Rb^(+))from brine.To form KCuFC/SPSG,the precursor film of sulfonated polysulfone/graphene(SPSG)was synthesized by phase conversion process,which was alternately immersed in 0.1 mol·L^(-1)CuSO_(4)/K_(4)[Fe(CN)_(6)]by in-situ adsorption coupled co-precipitation method.Various data such as nuclear magnetic resonance spectrometer,Fourier transform infrared spectroscope,X-ray photoelectron spectroscope,X-ray diffraction,scanning electron microscope,and energy dispersive spectroscopy all verified that abundant KCuFC were uniformly located on the film.The resulting KCuFC/SPSG was used in film separation system.As the solution was fed into the system,the Rb^(+)could be selectively adsorption by KCuFC/SPSG.After the saturation adsorption,0.5 mol·L^(-1)NH_(4)Cl/HCl was fed into the film cell,Rb^(+)could be quickly desorbed by ion-exchange between Rb^(+)and NH_(4)^(+)in the lattice of KCuFC.The purpose of separating and recovering Rb^(+)from the brine can be achieved after the repeated operation.The effects of pH,adsorption time,and interferential ions on the adsorption capacity of Rb^(+)were investigated by batch experiments.The adsorption behavior fits the pseudo-second order kinetic process,while KCuFC has a higher adsorption capacity(Langmuir maximum sorption 165.4 mg·g^(-1)).In addition,KCuFC/SPSG shows excellent selectivity for Rb^(+)even in complex brine systems.KCuFC/SPSG could maintain 93.5%extraction efficiency after five adsorption/desorption cycles.

Purification of copper foils driven by single crystallization

High-purity copper(Cu) with excellent thermal and electrical conductivity, is crucial in modern technological applications, including heat exchangers, integrated circuits, and superconducting magnets. The current purification process is mainly based on the zone/electrolytic refining or anion exchange, however, which excessively relies on specific integrated equipment with ultra-high vacuum or chemical solution environment, and is also bothered by external contaminants and energy consumption. Here we report a simple approach to purify the Cu foils from 99.9%(3N) to 99.99%(4N) by a temperature-gradient thermal annealing technique, accompanied by the kinetic evolution of single crystallization of Cu.The success of purification mainly relies on(i) the segregation of elements with low effective distribution coefficient driven by grain-boundary movements and(ii) the high-temperature evaporation of elements with high saturated vapor pressure.The purified Cu foils display higher flexibility(elongation of 70%) and electrical conductivity(104% IACS) than that of the original commercial rolled Cu foils(elongation of 10%, electrical conductivity of ~ 100% IACS). Our results provide an effective strategy to optimize the as-produced metal medium, and therefore will facilitate the potential applications of Cu foils in precision electronic products and high-frequency printed circuit boards.

Efficient C-N coupling in electrocatalytic urea generation on copper carbonate hydroxide electrocatalysts

Urea generation through electrochemical CO_(2) and NO_(3)~-co-reduction reaction(CO_(2)NO_(3)RR)is still limited by either the low selectivity or yield rate of urea.Herein,we report copper carbonate hydroxide(Cu_2(OH)_2CO_(3))as an efficient CO_(2)NO_(3)RR electrocatalyst with an impressive urea Faradaic efficiency of45.2%±2.1%and a high yield rate of 1564.5±145.2μg h~(-1)mg_(cat)~(-1).More importantly,H_(2) evolution is fully inhibited on this electrocatalyst over a wide potential range between-0.3 and-0.8 V versus reversible hydrogen electrode.Our thermodynamic simulation reveals that the first C-N coupling follows a unique pathway on Cu_2(OH)_2CO_(3) by combining the two intermediates,~*COOH and~*NHO.This work demonstrates that high selectivity and yield rate of urea can be simultaneously achieved on simple Cu-based electrocatalysts in CO_(2)NO_(3)RR,and provide guidance for rational design of more advanced catalysts.

Breaking the Fe_(3)O_(4)-wrapped copper microstructure to enhance copper-slag separation

The precipitation of Fe_(3)O_(4)particles and the accompanied formation of Fe_(3)O_(4)-wrapped copper structure are the main obstacles to copper recovery from the molten slag during the pyrometallurgical smelting of copper concentrates.Herein,the commercial powdery pyrite or anthracite is replaced with pyrite-anthracite pellets as the reductants to remove a large amount of Fe_(3)O_(4)particles in the molten slag,resulting in a deep fracture in the Fe_(3)O_(4)-wrapped copper microstructure and the full exposure of the copper matte cores.When 1wt%composite pellet is used as the reductant,the copper matte droplets are enlarged greatly from 25μm to a size observable by the naked eye,with the copper content being enriched remarkably from 1.2wt%to 4.5wt%.Density functional theory calculation results imply that the formation of the Fe_(3)O_(4)-wrapped copper structure is due to the preferential adhesion of Cu_(2)S on the Fe_(3)O_(4)particles.X-ray photoelectron spectroscopy,Fourier transform infrared spectrometer(FTIR),and Raman spectroscopy results all reveal that the high-efficiency conver-sion of Fe_(3)O_(4)to FeO can decrease the volume fraction of the solid phase and promote the depolymerization of silicate network structure.As a consequence,the settling of copper matte droplets is enhanced due to the lowered slag viscosity,contributing to the high efficiency of copper-slag separation for copper recovery.The results provide new insights into the enhanced in-situ enrichment of copper from mol-ten slag.

A Multi-Stage Differential-Multifactorial Evolutionary Algorithm for Ingredient Optimization in the Copper Industry

Ingredient optimization plays a pivotal role in the copper industry,for which it is closely related to the concentrate utilization rate,stability of furnace conditions,and the quality of copper production.To acquire a practical ingredient plan,which should exhibit long duration time with sufficient utilization and feeding stability for real applications,an ingredient plan optimization model is proposed in this study to effectively guarantee continuous production and stable furnace conditions.To address the complex challenges posed by this integer programming model,including multiple coupling feeding stages,intricate constraints,and significant non-linearity,a multi-stage differential-multifactorial evolution algorithm is developed.In the proposed algorithm,the differential evolutionary(DE)algorithm is improved in three aspects to efficiently tackle challenges when optimizing the proposed model.First,unlike traditional time-consuming serial approaches,the multifactorial evolutionary algorithm is utilized to optimize multiple complex models contained in the population of evolutionary algorithm caused by the feeding stability in a parallel manner.Second,a repair algorithm is employed to adjust infeasible ingredient lists in a timely manner.In addition,a local search strategy taking feedback from the current optima and considering the different positions of global optimum is developed to avoiding premature convergence of the differential evolutionary algorithm.Finally,the simulation experiments considering different planning horizons using real data from the copper industry in China are conducted,which demonstrates the superiority of the proposed method on feeding duration and stability compared with other commonly deployed approaches.It is practically helpful for reducing material cost as well as increasing production profit for the copper industry.

Design of low-alloying and high-performance solid solution-strengthened copper alloys with element substitution for sustainable development

Solid solution-strengthened copper alloys have the advantages of a simple composition and manufacturing process,high mechanical and electrical comprehensive performances,and low cost;thus,they are widely used in high-speed rail contact wires,electronic component connectors,and other devices.Overcoming the contradiction between low alloying and high performance is an important challenge in the development of solid solution-strengthened copper alloys.Taking the typical solid solution-strengthened alloy Cu-4Zn-1Sn as the research object,we proposed using the element In to replace Zn and Sn to achieve low alloying in this work.Two new alloys,Cu-1.5Zn-1Sn-0.4In and Cu-1.5Zn-0.9Sn-0.6In,were designed and prepared.The total weight percentage content of alloying elements decreased by 43%and 41%,respectively,while the product of ultimate tensile strength(UTS)and electrical conductivity(EC)of the annealed state increased by 14%and 15%.After cold rolling with a 90%reduction,the UTS of the two new alloys reached 576 and 627MPa,respectively,the EC was 44.9%IACS and 42.0%IACS,and the product of UTS and EC(UTS×EC)was 97%and 99%higher than that of the annealed state alloy.The dislocations proliferated greatly in cold-rolled alloys,and the strengthening effects of dislocations reached 332 and 356 MPa,respectively,which is the main reason for the considerable improvement in mechanical properties.

ZNT1 Involves Cuproptosis through Regulating MTF1-conduced Expression of MT1X under Copper Overload

Industrial activities such as smelting emissions,mineral combustion and industrial wastewater discharge might lead to copper pollution in the environment.This kind of copper pollution has harmful effects on aquatic o rganisms,plants and animals through direct or indirect exposure.However,the current understanding of the toxicity of copper is rather limited.Copper overload can perturb intracellular homeostasis and induce oxidative stress and e ven cell death.Recently,cuproptosis has been identified as a copper-dependent form of cell death induced by o xidative stress in mitochondria.We uncover here that zinc transporter 1(ZNT1)is an important regulator involved in cuproptosis.Firstly,we established the copper overload-induced cell death model with the overexpression of copper importer SLC31A1 in HeLa cells.Using this model,we conducted unbiased genome-wide CRISPR-Cas9 screens in cells treated with copper.Our results revealed a significant enrichment of ZNT1 gene in both library A and library B plasmids.Knocking out of ZNT1 in HeLa cells notably prevented cuproptosis.Subsequent knockout of metal transcription factor 1(MTF1)in ZNT1-deficient cells nearly abolished their ability to resist copper-induced cell death.However,overexpression of metallothionein 1X(MT1X)in the double-knockout cells could p artially restored the resistance to cuproptosis by loss of MTF1.Mechanistically,knockout of ZNT1 could promote MT1X expression by activating MTF1.As a consequence,the interaction between MT1X and copper was e nhanced,reducing the flow of copper into mitochondria and eliminating mitochondria damage.Taken together,this study reveals the important role of ZNT1 in cuproptosis and shows MTF1-MT1X axis mediated resistance to c uproptosis.Moreover,our study will help to understand the regulatory mechanism of cellular and systemic copper homeostasis under copper overload,and present insights into novel treatments for damages caused by both genetic copper overload diseases and environmental copper contamination.

A Dual Closed-Loop Digital Twin Construction Method for Optimizing the Copper Disc Casting Process

The copper disc casting machine is core equipment for producing copper anode plates in the copper metallurgy industry.The copper disc casting machine casting package motion curve(CPMC) is significant for precise casting and efficient production.However,the lack of exact casting modeling and real-time simulation information severely restricts dynamic CPMC optimization.To this end,a liquid copper droplet model describes the casting package copper flow pattern in the casting process.Furthermore,a CPMC optimization model is proposed for the first time.On top of this,a digital twin dual closed-loop self-optimization application framework(DT-DCS) is constructed for optimizing the copper disc casting process to achieve self-optimization of the CPMC and closed-loop feedback of manufacturing information during the casting process.Finally,a case study is carried out based on the proposed methods in the industrial field.

Editorial Commentary:Copper Homeostasis in Neurodegenerative Diseases

Copper,as an essential trace nutrient,plays a crucial role in biological processes such as mitochondrial respiration,antioxidant stress response,and the synthesis of biomolecules.Typically,cellular copper concentrations are maintained at very low levels,a pattern also observed in cancer cells to prevent adverse consequences of copper overload,such as cuproptosis.This involves copper dependency,accumulation of lipidated proteins,and a reduction in Fe-S cluster proteins[1].Various neurodegenerative diseases are associated with imbalances in copper homeostasis.

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Potential-dependent insights into the origin of high ammonia yield rate on copper surface via nitrate reduction:A computational and experimental study

Focusing on revealing the origin of high ammonia yield rate on Cu via nitrate reduction(NO3RR),we herein applied constant potential method via grand-canonical density functional theory(GC-DFT)with implicit continuum solvation model to predict the reaction energetics of NO3RR on pure copper surface in alkaline media.The potential-dependent mechanism on the most prevailing Cu(111)and the minor(100)and(110)facets were established,in consideration of NO_(2)_(−),NO,NH_(3),NH_(2)OH,N_(2),and N_(2)O as the main products.The computational results show that the major Cu(111)is the ideal surface to produce ammonia with the highest onset potential at 0.06 V(until−0.37 V)and the highest optimal potential at−0.31 V for ammonia production without kinetic obstacles in activation energies at critical steps.For other minor facets,the secondary Cu(100)shows activity to ammonia from−0.03 to−0.54 V with the ideal potential at−0.50 V,which requires larger overpotential to overcome kinetic activation energy barriers.The least Cu(110)possesses the longest potential range for ammonia yield from−0.27 to−1.12 V due to the higher adsorption coverage of nitrate,but also with higher tendency to generate di-nitrogen species.Experimental evaluations on commercial Cu/C electrocatalyst validated the accuracy of our proposed mechanism.The most influential(111)surface with highest percentage in electrocatalyst determined the trend of ammonia production.In specific,the onset potential of ammonia production at 0.1 V and emergence of yield rate peak at−0.3 V in experiments precisely located in the predicted potentials on Cu(111).Four critical factors for the high ammonia yield and selectivity on Cu surface via NO3RR are summarized,including high NO3RR activity towards ammonia on the dominant Cu(111)facet,more possibilities to produce ammonia along different pathways on each facet,excellent ability for HER inhibition and suitable surface size to suppress di-nitrogen species formation at high nitrate coverage.Overall,our work provides comprehensive potential-dependent insights into the reaction details of NO3RR to ammonia,which can serve as references for the future development of NO3RR electrocatalysts,achieving higher activity and selectivity by maximizing these characteristics of copper-based materials.

Enhancing XRF sensor-based sorting of porphyritic copper ore using particle swarm optimization-support vector machine(PSO-SVM)algorithm

X-ray fluorescence(XRF)sensor-based ore sorting enables efficient beneficiation of heterogeneous ores,while intraparticle heterogeneity can cause significant grade detection errors,leading to misclassifications and hindering widespread technology adoption.Accurate classification models are crucial to determine if actual grade exceeds the sorting threshold using localized XRF signals.Previous studies mainly used linear regression(LR)algorithms including simple linear regression(SLR),multivariable linear regression(MLR),and multivariable linear regression with interaction(MLRI)but often fell short attaining satisfactory results.This study employed the particle swarm optimization support vector machine(PSO-SVM)algorithm for sorting porphyritic copper ore pebble.Lab-scale results showed PSO-SVM out-performed LR and raw data(RD)models and the significant interaction effects among input features was observed.Despite poor input data quality,PSO-SVM demonstrated exceptional capabilities.Lab-scale sorting achieved 93.0%accuracy,0.24%grade increase,84.94%recovery rate,57.02%discard rate,and a remarkable 39.62 yuan/t net smelter return(NSR)increase compared to no sorting.These improvements were achieved by the PSO-SVM model with optimized input combinations and highest data quality(T=10,T is XRF testing times).The unsuitability of LR methods for XRF sensor-based sorting of investigated sample is illustrated.Input element selection and mineral association analysis elucidate element importance and influence mechanisms.

One stone two birds:electrochemical and colorimetric dual-mode biosensor based on copper peroxide/covalent organic framework nanocomposite for ultrasensentive norovirus detection

Norovirus(NoV)is regarded as one of the most common causes of foodborne diarrhea in the world.It is urgent to identify the pathogenic microorganism of the diarrhea in short time.In this work,we developed an electrochemical and colorimetric dual-mode detection for NoV based on the excellent dual catalytic properties of copper peroxide/COF-NH_(2)nanocomposite(CuO_(2)@COF-NH_(2)).For the colorimetric detection,NoV can be directly detected by the naked eye based on CuO_(2)@COF-NH_(2)as a laccase-like nonazyme using“peptide-NoV-antibody”recognition mode.The colorimetric assay displayed a wide and quality linear detection range from 1 copy/mL to 5000 copies/mL of NoV with a low limit of detection(LOD)of 0.125 copy/mL.For the electrochemical detection of NoV,CuO_(2)@COF-NH_(2)showed an oxidation peak of copper ion from Cu^(+)to Cu^(2+)using“peptide-NoV-antibody”recognition mode.The electrochemical assay showed a linear detection range was 1-5000 copies/mL with a LOD of 0.152 copy/mL.It's worthy to note that this assay does not need other electrical signal molecule,which provide the stable and sensitive electrochemial detection for NoV.The electrochemical and colorimetric dual-mode detection was used to detect NoV in foods and faceal samples,which has the potential for improving food safety and diagnosing of NoV-infected diarrhea.

Prognostic characterization of copper death-related immune checkpoint genes and analysis of immunologic and pharmacologic therapy in bladder cancer

Objective:Copper death-induced tumor cell death and immune checkpoint blockade therapy are highly selective.Combining their advantages and understanding their characteristics in bladder cancer is very important for the development of new targeted therapy.The identification of bladder cancer by screening the characteristic genes of copper death-related immune checkpoints provide a theoretical basis for the selection of adjuvant treatment options and the application of new targets.Methods:The expression samples of normal bladder tissue and bladder cancer were obtained from TCGA and GEO databases,and 13 cop-per death genes and 79 immune checkpoint genes were extracted from previous studies.The mRNA expression of prognostic genes was verified by qPCR.The copper death-related immune checkpoint genes were screened by correlation analysis to construct a prognostic model,and the differences in the efficacy of immunotherapy and chemotherapy between the high-risk group and the low-risk group were evaluated.Results:A prognostic model consisting of BTNL9,CD160,TNFRSF14 and TNFRSF18 was constructed.Its reliable predictive ability was proved in both databases,and qPCR showed that the expression levels of the four genes were significantly different between the normal group and the cancer cell group.The effect of immunotherapy in the lowrisk group was better than that in the high-risk group.Patients in the high-risk group had better chemotherapy efficacy.Conclusion:The copper death-related immune checkpoint gene model can accurately predict the prognosis of patients.Drug and immune analysis provide a basis for clinical treatment,and the discovery of potential targets provides a new solution for clinical decision-making.