Cuproptosis and cuproptosis-related genes in rheumatoid arthritis: Implication, prospects, and perspectives

Iron, copper, zinc and magnesium on rheumatoid arthritis: a two-sample Mendelian randomization study

This study aimed to elucidate the causal genetic relationships between iron, copper, zinc, magnesium, and rheumatoid arthritis (RA). A two-sample Mendelian randomization (MR) analysis was conducted using the "TwoSampleMR" and "MendelianRandomization" packages in R. The random-effects inverse variance-weighted (IVW) method was used as the primary approach. We performed sensitivity analyses to test the reliability of the results. The random-effects IVW analysis revealed that there was no genetic causal relationship between iron (P = 0.429, odds ratio [OR] 95% confidence interval [CI] = 0.919 [0.746-1.133]), copper (P = 0.313, OR 95% CI = 0.973 [0.921-1.027]), zinc (P = 0.633, OR 95% CI = 0.978 [0.891-1.073]), or magnesium (P = 0.218, OR 95% CI = 0.792 [0.546-1.148]) and RA. Sensitivity analysis verified the reliability of the results. Therefore, there is no evidence to support a causal relationship between iron, copper, zinc, and magnesium intake at the genetic level and the development of RA.

Identification and experimental validation of cuproptosis regulatory program in a sepsis immune microenvironment through a combination of single-cell and bulk RNA sequencing

Background

In spite of its high mortality rate and poor prognosis, the pathogenesis of sepsis is still incompletely understood. This study established a cuproptosis-based risk model to diagnose and predict the risk of sepsis. In addition, the cuproptosis-related genes were identified for targeted therapy.

Methods

Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model's accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis.

Results

ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype.

Conclusions

This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.

Unveiling the role of copper metabolism and STEAP2 in idiopathic pulmonary fibrosis molecular landscape

Idiopathic pulmonary fibrosis (IPF) is a debilitating interstitial lung disease characterized by progressive fibrosis and poor prognosis. Despite advancements in treatment, the pathophysiological mechanisms of IPF remain elusive. Herein, we conducted an integrated bioinformatics analysis combining clinical data and carried out experimental validations to unveil the intricate molecular mechanism of IPF. Leveraging three IPF datasets, we identified 817 upregulated and 560 downregulated differentially expressed genes (DEGs). Of these, 14 DEGs associated with copper metabolism were identified, shedding light on the potential involvement of disrupted copper metabolism in IPF progression. Immune infiltration analysis revealed dysregulated immune cell infiltration in IPF, with a notable correlation between copper metabolism-related genes and immune cells. Weighted gene co-expression network analysis (WGCNA) identified a central module correlated with IPF-associated genes, among which STEAP2 emerged as a key hub gene. Subsequent in vivo and in vitro studies confirmed the upregulation of STEAP2 in IPF model. Knockdown of STEAP2 using siRNA alleviated fibrosis in vitro, suggesting potential pathway related to copper metabolism in the pathophysiological progression of IPF. Our study established a novel link between immune cell infiltration and dysregulated copper metabolism. The revelation of intracellular copper overload and upregulated STEAP2 unravelled a potential therapeutic option. These findings offer valuable insights for future research and therapeutic interventions targeting STEAP2 and associated pathways in IPF.

Cuproptosis in lung cancer: mechanisms and therapeutic potential

Cuproptosis, a recently identified form of cell death that differs from other forms, is induced by the disruption of the binding of copper to mitochondrial respiratory acylation components. Inducing cell cuproptosis and targeting cell copper death pathways are considered potential directions for treating tumor diseases. We have provided a detailed introduction to the metabolic process of copper. In addition, this study attempts to clarify and summarize the relationships between cuproptosis and therapeutic targets and signaling pathways of lung cancer. This review aims to summarize the theoretical achievements for translating the results of lung cancer and cuproptosis experiments into clinical treatment.

Copper homeostasis dysregulation in respiratory diseases: a review of current knowledge

Cu is an essential micronutrient for various physiological processes in almost all human cell types. Given the critical role of Cu in a wide range of cellular processes, the local concentrations of Cu and the cellular distribution of Cu transporter proteins in the lung are essential for maintaining a steady-state internal environment. Dysfunctional Cu metabolism or regulatory pathways can lead to an imbalance in Cu homeostasis in the lungs, affecting both acute and chronic pathological processes. Recent studies have identified a new form of Cu-dependent cell death called cuproptosis, which has generated renewed interest in the role of Cu homeostasis in diseases. Cuproptosis differs from other known cell death pathways. This occurs through the direct binding of Cu ions to lipoylated components of the tricarboxylic acid cycle during mitochondrial respiration, leading to the aggregation of lipoylated proteins and the subsequent downregulation of Fe-S cluster proteins, which causes toxic stress to the proteins and ultimately leads to cell death. Here, we discuss the impact of dysregulated Cu homeostasis on the pathogenesis of various respiratory diseases, including asthma, chronic obstructive pulmonary disease, idiopathic interstitial fibrosis, and lung cancer. We also discuss the therapeutic potential of targeting Cu. This study highlights the intricate interplay between copper, cellular processes, and respiratory health. Copper, while essential, must be carefully regulated to maintain the delicate balance between necessity and toxicity in living organisms. This review highlights the need to further investigate the precise mechanisms of copper interactions with infections and immune inflammation in the context of respiratory diseases and explore the potential of therapeutic strategies for copper, cuproptosis, and other related effects.

Copper Chelation Therapy Attenuates Periodontitis Inflammation through the Cuproptosis/Autophagy/Lysosome Axis

Periodontitis development arises from the intricate interplay between bacterial biofilms and the host's immune response, where macrophages serve pivotal roles in defense and tissue homeostasis. Here, we uncover the mitigative effect of copper chelator Tetrathiomolybdate (TTM) on periodontitis through inhibiting cuproptosis, a newly identified form of cell death which is dependent on copper. Our study reveals concurrent cuproptosis and a macrophage marker within murine models. In response to lipopolysaccharide (LPS) stimulation, macrophages exhibit elevated cuproptosis-associated markers, which are mitigated by the administration of TTM. TTM treatment enhances autophagosome expression and mitophagy-related gene expression, countering the LPS-induced inhibition of autophagy flux. TTM also attenuates the LPS-induced fusion of autophagosomes and lysosomes, the degradation of lysosomal acidic environments, lysosomal membrane permeability increase, and cathepsin B secretion. In mice with periodontitis, TTM reduces cuproptosis, enhances autophagy flux, and decreases Ctsb levels. Our findings underscore the crucial role of copper-chelating agent TTM in regulating the cuproptosis/mitophagy/lysosome pathway during periodontitis inflammation, suggesting TTM as a promising approach to alleviate macrophage dysfunction. Modulating cuproptosis through TTM treatment holds potential for periodontitis intervention.

Comprehensive Gene Analysis Reveals Cuproptosis-Related Gene Signature Associated with M2 Macrophage in Staphylococcus aureus-Infected Osteomyelitis

Objective

Osteomyelitis is a challenging disease in the field of bone infections, with its immune and molecular regulatory mechanisms still poorly understood. The aim of this study is to explore the value and potential mechanisms of cuproptosis-related genes (CRGs) in Staphylococcus aureus (S. aureus)-infected osteomyelitis from an immunological perspective.

Methods

Initially, three transcriptomic datasets from public databases were integrated and analyzed, and consistent expression of CRGs in S. aureus-infected osteomyelitis was identified. Subsequently, immune infiltration analysis was performed, and M2 macrophage-related CRGs (M2R-CRGs) were further identified. Their potential molecular mechanisms were evaluated using Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA). Finally, distinct osteomyelitis subtypes and diagnostic models based on characteristic M2R-CRGs were constructed.

Results

Through correlation analysis with immune cell infiltration, three characteristic M2R-CRGs (SLC31A1, DLD, and MTF1) were identified. Further analysis using unsupervised clustering and immune microenvironment analysis indicated that cluster 1 might activate pro-inflammatory responses, while cluster 2 was shown to exhibit anti-inflammatory effects in osteomyelitis. Compared to Cluster A, Cluster B demonstrated higher levels and a greater diversity of immune cell infiltrations in CRG-related molecular patterns, suggesting a potential anti-inflammatory role in osteomyelitis. A diagnostic model for S. aureus-infected osteomyelitis, based on the three M2R-CRGs, was constructed, exhibiting excellent diagnostic performance and validated with an independent dataset. Significant upregulation in mRNA and protein expression levels of the three M2R-CRGs was observed in rat models of S. aureus-infected osteomyelitis, aligning with bioinformatic results.

Conclusion

The M2R-CRGs (SLC31A1, DLD, and MTF1) may be considered characteristic genes for early diagnosis and personalized immune therapy in patients with S. aureus-infected osteomyelitis.

Deciphering cuproptosis-related signatures in pediatric allergic asthma using integrated scRNA-seq and bulk RNA-seq analysis

OBJECTIVE

Allergic asthma (AA) is common in children. Excess copper is observed in AA patients. It is currently unclear whether copper imbalance can cause cuproptosis in pediatric AA.

METHODS

The datasets about pediatric AA (GSE40732 and GSE40888) were obtained from Gene Expression Omnibus (GEO) database. The expression of cuproptosis-related genes (CRGs) and immune cell infiltration in pediatric AA samples were analyzed. Single-cell RNA sequencing (scRNA-seq) data (GSE193816) were used to evaluate the expression patterns of CRGs in AA. The identification of differentially expressed genes within clusters was conducted using weighted gene co-expression network analysis. Subsequently, disease progression and cuproptosis-related models were screened using random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and general linear model (GLM) algorithms.

RESULTS

Four CRGs were notably increased in pediatric AA samples. CD4+ T cells, macrophages and mast cells exhibited a lower cuproptosis score in AA samples, indicating that these immune cells may be closely associated with cuproptosis in AA development. Co-expression network of CRGs in AA was constructed. AA samples were divided into two cuprotosis clusters. Following construction of four machine-learning models, SVM model exhibited the highest efficacy of prediction in the testing set (AUC = 0.952). SVM model containing five important variables can be used for prediction of AA.

CONCLUSION

This work provided a machine learning model containing five important variables, which may have good diagnostic efficiency for pediatric AA.

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.

Cuproptosis-Related lncRNAs Modulate the Prognosis of MIBC by Regulating the Expression Pattern of Immunosuppressive Molecules Within the Tumor Microenvironment

Background

Cuproptosis-related gene and long non-coding RNA (lncRNA) modulation of cancer regulation is well-established. This investigation aimed to elucidate the prognostic implications of cuproptosis-associated lncRNAs in muscle-invasive bladder cancer (MIBC).

Methods

Employing the Cancer Genome Atlas (TCGA) and IMvigor210 cohorts, bioinformatics and statistical analyses probed the prognostic relevance of cuproptosis-related lncRNAs.

Results

Co-expression analysis revealed tight associations between lncRNA expression and cuproptosis-linked genes, with 13 cuproptosis-related lncRNAs found to correlate with MIBC prognosis. Lasso regression identified a six-lncRNA prognostic signature, enabling patient stratification into high- and low-risk categories. Tissue validation substantiated differential expression of FAM13A-AS1, GHRLOS, LINC00456, OPA1-AS1, RAP2C-AS1, and UBE2Q1-AS1 between MIBC tumor and normal tissues. Comparative analyses of tumor microenvironments and immune profiles between risk groups disclosed elevated immunosuppressive molecule expression, including programmed cell death-1 (PD-L1) and T-cell immunoglobulin-3 (TIM-3), in high-risk individuals.

Conclusion

These findings suggest that cuproptosis-related lncRNAs may modulate the expression of immunosuppressive molecules, thereby influencing MIBC tumorigenesis and progression. Further exploration is warranted to unveil novel therapeutic targets for MIBC based on the expression patterns of cuproptosis-related lncRNAs and their impact on immune responses in the tumor microenvironment.

Systematic analysis based on the cuproptosis-related genes identifies ferredoxin 1 as an immune regulator and therapeutic target for glioblastoma

Glioblastoma multiforme (GBM) is recognized as the prevailing malignant and aggressive primary brain tumor, characterized by an exceedingly unfavorable prognosis. Cuproptosis, a recently identified form of programmed cell death, exhibits a strong association with cancer progression, therapeutic response, and prognostic outcomes. However, the specific impact of cuproptosis on GBM remains uncertain. To address this knowledge gap, we obtained transcriptional and clinical data pertaining to GBM tissues and their corresponding normal samples from various datasets, including TCGA, CGGA, GEO, and GTEx. R software was utilized for the analysis of various statistical techniques, including survival analysis, cluster analysis, Cox regression, Lasso regression, gene enrichment analysis, drug sensitivity analysis, and immune microenvironment analysis. Multiple assays were conducted to investigate the expression of genes related to cuproptosis and their impact on the proliferation, invasion, and migration of glioblastoma multiforme (GBM) cells. The datasets were obtained and prognostic risk score models were constructed and validated using differentially expressed genes (DEGs) associated with cuproptosis. To enhance the practicality of these models, a nomogram was developed.Patients with glioblastoma multiforme (GBM) who were classified as high risk exhibited a more unfavorable prognosis and shorter overall survival compared to those in the low risk group. Additionally, we specifically chose FDX1 from the differentially expressed genes (DEGs) within the high risk group to assess its expression, prognostic value, biological functionality, drug responsiveness, and immune cell infiltration. The findings demonstrated that FDX1 was significantly upregulated and associated with a poorer prognosis in GBM. Furthermore, its elevated expression appeared to be linked to various metabolic processes and the susceptibility to chemotherapy drugs. Moreover, FDX1 was found to be involved in immune cell infiltration and exhibited correlations with multiple immunosuppressive genes, including TGFBR1 and PDCD1LG2. The aforementioned studies offer substantial assistance in informing the chemotherapy and immunotherapy approaches for GBM. In summary, these findings contribute to a deeper comprehension of cuproptosis and offer novel perspectives on the involvement of cuproptosis-related genes in GBM, thereby presenting a promising therapeutic strategy for GBM patients.

Demethylation of CDKN2A in systemic lupus erythematosus and rheumatoid arthritis: a blood biomarker for diagnosis and assessment of disease activity

INTRODUCTION/OBJECTIVES

Considering the phenotypic and serological heterogeneity of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA), significant challenges may intervene with the precise diagnosis. In this regard, numerous studies have shown that changes in DNA methylation levels can be used to distinguish between healthy individuals and those with SLE and RA, as well as to predict disease activity and prognosis.

METHODS

In the current study, we evaluated quantitative methylation level of CDKN2A promoter in peripheral blood mononuclear cells (PBMCs) of SLE and RA patients, and healthy controls by methylation-quantification of endonuclease-resistant DNA (MethyQESD), a bisulfite conversion-independent method.

RESULTS

Our findings revealed an excessive hypomethylation of CDKN2A in SLE and RA patients compared to healthy individuals (P < 0.001). Besides, by determining efficient cutoff value, the specificity of CDKN2A for correct diagnosis of healthy subjects was measured to be 77.30% and the sensitivity for SLE and RA diagnosis were 81.33%, and 72%, respectively. Furthermore, CDKN2A methylation level was shown to be positively associated with C3 and C4 levels and negatively associated with anti‑dsDNA concentration (P < 0.001). Moreover, a statistically significant difference in the DNA methylation levels of CDKN2A promoter was identified between SLE cases with age of ≤ 18 and patients with > 18 years of age (P = 0.025).

CONCLUSION

Our findings demonstrated that CDKN2A methylation levels in PBMCs of SLE and RA patients could be used as a promising diagnostic biomarker. The significant association between hypomethylation of CDKN2A promoter and disease activity factors in SLE patients, is suggesting that CDKN2A hypomethylation could be used as an alternative biomarker for assessment of disease activity. Key Points • Several studies have reported increased expression of CDKN2A in SLE and RA suggesting that it may be involved in the pathogenesis of these disorders. • CDKN2A hypomethylation has been implicated in different autoimmune diseases. • Our findings demonstrated that CDKN2A methylation levels in PBMCs of SLE and RA patients could be used as a promising diagnostic and prognostic biomarker.

Copper and Diabetes: Current Research and Prospect

Copper is an essential trace metal for normal cellular functions; a lack of copper is reported to impair the function of important copper-binding enzymes, while excess copper could lead to cell death. Numerous studies have shown an association between dietary copper consumption or plasma copper levels and the incidence of diabetes/diabetes complications. And experimental studies have revealed multiple signaling pathways that are triggered by copper shortages or copper overload in diabetic conditions. Moreover, studies show that treated with copper chelators improve vascular function, maintain copper homeostasis, inhibit cuproptosis, and reduce cell toxicity, thereby alleviating diabetic neuropathy, retinopathy, nephropathy, and cardiomyopathy. However, the mechanisms reported in these studies are inconsistent or even contradictory. This review summarizes the precise and tight regulation of copper homeostasis processes, and discusses the latest progress in the association of diabetes and dietary copper/plasma copper. Further, the study pays close attention to the therapeutic potential of copper chelators and copper in diabetes and its complications, and hopes to provide new insight for the treatment of diabetes.

The function and immune role of cuproptosis associated hub gene in Barrett's esophagus and esophageal adenocarcinoma

Barrett's esophagus (BE) is a precancerous lesion of esophageal adenocarcinoma (EAC), with approximately 3-5% of patients developing EAC. Cuproptosis is a kind of programmed cell death phenomenon discovered in recent years, which is related to the occurrence and development of many diseases. However, its role in BE and EAC is not fully understood. We used single sample Gene Set Enrichment Analysis (ssGSEA) for differential analysis of BE in the database, followed by enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and GSEA, Protein-Protein Interaction (PPI), Weighted Gene Co-expression Network Analysis (WGCNA), Receiver Operating Characteristic Curve (ROC) and finally Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry (IHC) of clinical tissues. Two hub genes can be obtained by intersection of the results obtained from the cuproptosis signal analysis based on BE. The ROC curves of these two genes predicted EAC, and the Area Under the Curve (AUC) values could reach 0.950 and 0.946, respectively. The mRNA and protein levels of Centrosome associated protein E (CENPE) and Shc SH2 domain binding protein 1 (SHCBP1) were significantly increased in clinical EAC tissues. When they were grouped by protein expression levels, high expression of CENPE or SHCBP1 had a poor prognosis. The CENPE and SHCBP1 associated with cuproptosis may be a factor promoting the development of BE into EAC which associated with the regulation of NK cells and T cells.

Identification of immunological characterization and Anoikis-related molecular clusters in rheumatoid arthritis

Objective: To investigate the potential association between Anoikis-related genes, which are responsible for preventing abnormal cellular proliferation, and rheumatoid arthritis (RA). Methods: Datasets GSE89408, GSE198520, and GSE97165 were obtained from the GEO with 282 RA patients and 28 healthy controls. We performed differential analysis of all genes and HLA genes. We performed a protein-protein interaction network analysis and identified hub genes based on STRING and cytoscape. Consistent clustering was performed with subgrouping of the disease. SsGSEA were used to calculate immune cell infiltration. Spearman's correlation analysis was employed to identify correlations. Enrichment scores of the GO and KEGG were calculated with the ssGSEA algorithm. The WGCNA and the DGIdb database were used to mine hub genes' interactions with drugs. Results: There were 26 differentially expressed Anoikis-related genes (FDR = 0.05, log2FC = 1) and HLA genes exhibited differential expression (P < 0.05) between the disease and control groups. Protein-protein interaction was observed among differentially expressed genes, and the correlation between PIM2 and RAC2 was found to be the highest; There were significant differences in the degree of immune cell infiltration between most of the immune cell types in the disease group and normal controls (P < 0.05). Anoikis-related genes were highly correlated with HLA genes. Based on the expression of Anoikis-related genes, RA patients were divided into two disease subtypes (cluster1 and cluster2). There were 59 differentially expressed Anoikis-related genes found, which exhibited significant differences in functional enrichment, immune cell infiltration degree, and HLA gene expression (P < 0.05). Cluster2 had significantly higher levels in all aspects than cluster1 did. The co-expression network analysis showed that cluster1 had 51 hub differentially expressed genes and cluster2 had 72 hub differentially expressed genes. Among them, three hub genes of cluster1 were interconnected with 187 drugs, and five hub genes of cluster2 were interconnected with 57 drugs. Conclusion: Our study identified a link between Anoikis-related genes and RA, and two distinct subtypes of RA were determined based on Anoikis-related gene expression. Notably, cluster2 may represent a more severe state of RA.

Cuproptosis: emerging biomarkers and potential therapeutics in cancers

The sustenance of human life activities depends on copper, which also serves as a crucial factor for vital enzymes. Under typical circumstances, active homeostatic mechanisms keep the intracellular copper ion concentration low. Excess copper ions cause excessive cellular respiration, which causes cytotoxicity and cell death as levels steadily rise above a threshold. It is a novel cell death that depends on mitochondrial respiration, copper ions, and regulation. Cuproptosis is now understood to play a role in several pathogenic processes, including inflammation, oxidative stress, and apoptosis. Copper death is a type of regulatory cell death(RCD).Numerous diseases are correlated with the development of copper homeostasis imbalances. One of the most popular areas of study in the field of cancer is cuproptosis. It has been discovered that cancer angiogenesis, proliferation, growth, and metastasis are all correlated with accumulation of copper ions. Copper ion concentrations can serve as a crucial marker for cancer development. In order to serve as a reference for clinical research on the product, diagnosis, and treatment of cancer, this paper covers the function of copper ion homeostasis imbalance in malignant cancers and related molecular pathways.

Association between magnesium, copper, and potassium intakes with risk of rheumatoid arthritis: a cross-sectional study from National Health and Nutrition Examination Survey (NHANES)

BACKGROUND

The relationship between Mg (magnesium), Cu (copper), and K (potassium) intakes and the risk of rheumatoid arthritis (RA) remains limited. The aim of present study was to examine the associations between Mg, Cu and K intakes with RA.

METHODS

Using data from the National Health and Nutrition Examination Survey (NHANES) 2003-2018, we examined the association between Mg, Cu and K intakes and the risk of RA among US adults. After adjustment for age, sex, race, BMI, educational level, smoking history, alcohol consumption, family Poverty Income Ratio (PIR), diabetes and total daily energy intake, logistic regression models and smooth curve fitting were applied to examine the associations of Mg, Cu and K intakes with RA.

RESULTS

A total of 18,338 participants were included (1,008 participants with RA). The multivariate adjusted ORs (95% CI) of RA were [0.66 (0.51, 0.84)], [0.76 (0.60, 0.97)], and [0.75 (0.58, 0.97)] in the highest versus lowest quartile of magnesium intakes, respectively. A nonlinear association between Cu intakes and RA was found. When Cu intake (ln) was between 0.6-2.2 mg, the risk of RA reduced by 26% for every 1 mg increase of intake in Cu [0.74 (0.58, 0.96)].

CONCLUSIONS

Higher Mg, Cu and K intakes may be inversely associated with the risk of RA among US adults, and an inverse L-shaped association between dietary Cu and RA was found.

A novel defined risk signature of cuproptosis-related long non-coding RNA for predicting prognosis, immune infiltration, and immunotherapy response in lung adenocarcinoma

Background: Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor immunity formation and patient-tailored treatment optimization of lung adenocarcinoma (LUAD) is still unclear. Methods: RNA sequencing and survival data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database for model training. The patients with LUAD in GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081 were used for validation. The proofed cuproptosis-related genes were extracted from the previous studies. The Pearson correlation was applied to select cuproptosis-related lncRNAs. We chose differentially expressed cuproptosis-related lncRNAs in the tumor and normal tissues and allowed them to go to a Cox regression and a LASSO regression for a lncRNA signature that predicts the LUAD prognosis. Kaplan-Meier estimator, Cox model, ROC, tAUC, PCA, nomogram predictor, decision curve analysis, and real-time PCR were further deployed to confirm the model's accuracy. We examined this model's link to other regulated cell death forms. Applying TMB, immune-related signatures, and TIDE demonstrated the immunotherapeutic capabilities of signatures. We evaluated the relationship of our signature to anticancer drug sensitivity. GSEA, immune infiltration analysis, and function experiments further investigated the functional mechanisms of the signature and the role of immune cells in the prognostic power of the signature. Results: An eight-lncRNA signature (TSPOAP1-AS1, AC107464.3, AC006449.7, LINC00324, COLCA1, HAGLR, MIR4435-2HG, and NKILA) was built and demonstrated owning prognostic power by applied to the validation cohort. Each signature gene was confirmed differentially expressed in the real world by real-time PCR. The eight-lncRNA signature correlated with 2321/3681 (63.05%) apoptosis-related genes, 11/20 (55.00%) necroptosis-related genes, 34/50 (68.00%) pyroptosis-related genes, and 222/380 (58.42%) ferroptosis-related genes. Immunotherapy analysis suggested that our signature may have utility in predicting immunotherapy efficacy in patients with LUAD. Mast cells were identified as key players that support the predicting capacity of the eight-lncRNA signature through the immune infiltrating analysis. Conclusion: In this study, an eight-lncRNA signature linked to cuproptosis was identified, which may improve LUAD management strategies. This signature may possess the ability to predict the effect of LUAD immunotherapy. In addition, infiltrating mast cells may affect the signature's prognostic power.

The applications of functional materials-based nano-formulations in the prevention, diagnosis and treatment of chronic inflammation-related diseases

Chronic inflammation, in general, refers to systemic immune abnormalities most often caused by the environment or lifestyle, which is the basis for various skin diseases, autoimmune diseases, cardiovascular diseases, liver diseases, digestive diseases, cancer, and so on. Therapeutic strategies have focused on immunosuppression and anti-inflammation, but conventional approaches have been poor in enhancing the substantive therapeutic effect of drugs. Nanomaterials continue to attract attention for their high flexibility, durability and simplicity of preparation, as well as high profitability. Nanotechnology is used in various areas of clinical medicine, such as medical diagnosis, monitoring and treatment. However, some related problems cannot be ignored, including various cytotoxic and worsening inflammation caused by the nanomaterials themselves. This paper provides an overview of functional nanomaterial formulations for the prevention, diagnosis and treatment of chronic inflammation-related diseases, with the intention of providing some reference for the enhancement and optimization of existing therapeutic approaches.

Verification of cuproptosis-related diagnostic model associated with immune infiltration in rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is a chronic autoimmune disease closely related to inflammation. Cuproptosis is a newly discovered unique type of cell death, and it has been found that it may play an essential role in the occurrence and development of RA. Therefore, we intend to explore the potential association between cuproptosis-related genes (CRGs) and RA to provide a new biomarker for the treatment and prognosis of RA.

Methods

Download GSE93777 datasets from the GEO database. Variance analysis was performed on the CRGs that had been reported. Then, the random forest (RF) model and nomogram of differentially expressed CRGs were constructed, and the ROC curve was used to evaluate the accuracy of the diagnostic model. Next, RA patients were subtyped by consensus clustering, and immune infiltration was analyzed in each subgroup to confirm the correlation between CRGs and abundance of immune cells. The expression levels of CRGs were verified by qRT-PCR.

Results

Eight differentially expressed CRGs (DLST, DLD, PDHB, PDHA1, ATP7A, CDKN2A, LIAS, DLAT) were screened out by differential analysis to construct an RF model. The ROC curve proved that this model had good diagnostic accuracy. Based on the above eight significant CRGs, a nomogram was built to predict effective and high-precision results. The consensus clustering method identified two CRG patterns. Most of the immune cells were enriched in cluster A, indicating that cluster A may be related to the development of RA. Finally, qRT-PCR verified the expression of eight key genes, further confirming our findings.

Conclusion

The diagnosis model of RA based on the above eight CRGs has excellent diagnostic potential. Based on these, patients can be divided into two different molecular subtypes; it is expected to develop a new treatment strategy for RA.

Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis

BACKGROUND

Ulcerative colitis is one of the two main forms of inflammatory bowel disease. Cuproptosis is reported to be a novel mode of cell death.

METHODS

We examined clusters of cuproptosis related genes and immune cell infiltration molecules in 86 ulcerative colitis samples from the GSE179285 dataset. We identified the differentially expressed genes according to the clustering method, and the performance of the SVM model, the random forest model, the generalized linear model, and the limit gradient enhancement model were compared, and then the optimal machine model was selected. To assess the accuracy of the learning predictions, the nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis have been accurately predicted.

RESULTS

Significant cuproptosis-related genes and immune response cells were detected between the ulcerative colitis and control groups. Two cuproptosis-associated molecular clusters were identified. Immune infiltration analysis indicated that different clusters exhibited significant heterogeneity. The immune scores for Cluster2 were elevated. Both the residual error and root mean square error of the random forest machine model had clinical significance. There was a clear correlation between the differentially expressed genes in cluster 2 and the response of immune cells. The nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis had sufficient accuracy.

CONCLUSION

We examined the complex relationship between cuproptosis and ulcerative colitis in a systematic manner. To estimate the likelihood that each subtype of cuproptosis will occur in ulcerative colitis patients and their disease outcome, we developed a promising prediction model.

Cuproptosis engages in c-Myc-mediated breast cancer stemness

BACKGROUND

Intra-tumoral heterogeneity (ITH) is a distinguished hallmark of cancer, and cancer stem cells (CSCs) contribute to this malignant characteristic. Therefore, it is of great significance to investigate and even target the regulatory factors driving intra-tumoral stemness. c-Myc is a vital oncogene frequently overexpressed or amplified in various cancer types, including breast cancer. Our previous study indicated its potential association with breast cancer stem cell (BCSC) biomarkers.

METHODS

In this research, we performed immunohistochemical (IHC) staining on sixty breast cancer surgical specimens for c-Myc, CD44, CD24, CD133 and ALDH1A1. Then, we analyzed transcriptomic atlas of 1533 patients with breast cancer from public database.

RESULTS

IHC staining indicated the positive correlation between c-Myc and BCSC phenotype. Then, we used bioinformatic analysis to interrogate transcriptomics data of 1533 breast cancer specimens and identified an intriguing link among c-Myc, cancer stemness and copper-induced cell death (also known as "cuproptosis"). We screened out cuproptosis-related characteristics that predicts poor clinical outcomes and found that the pro-tumoral cuproptosis-based features were putatively enriched in MYC-targets and showed a significantly positive correlation with cancer stemness.

CONCLUSION

In addition to previous reports on its oncogenic roles, c-Myc showed significant correlation to stemness phenotype and copper-induced cell toxicity in breast cancer tissues. Moreover, transcriptomics data demonstrated that pro-tumoral cuproptosis biomarkers had putative positive association with cancer stemness. This research combined clinical samples with large-scale bioinformatic analysis, covered description and deduction, bridged classic oncogenic mechanisms to innovative opportunities, and inspired the development of copper-based nanomaterials in targeting highly heterogeneous tumors.

Integrated single-cell and bulk characterization of cuproptosis key regulator PDHB and association with tumor microenvironment infiltration in clear cell renal cell carcinoma

Background

Renal clear cell carcinoma (ccRCC) is one of the most prevalent cancers worldwide. Accumulating evidence revealed that copper-induced cell death played a vital role in various tumors. However, the underlying mechanism of cuproptosis with molecular heterogeneity and tumor microenvironment (TME) in ccRCC remains to be elucidated. The present study aimed to discover the biological function of cuproptosis regulators with the potential to guide clinical therapy.

Methods

Using Single-cell RNA-seq, bulk transcriptome and other multi-omics datasets, we identify essential cuproptosis-related hub gene PDHB for further study. The dysregulation of PDHB in ccRCC was characterized, together with survival outcomes, pathway enrichment and immune infiltration among tumor microenvironments. The functional significance and clinical association of PDHB was validated with loss of function experiments and surgical removal specimens.

Results

PDHB mRNA and protein expression level was significantly downregulated in ccRCC tissues compared with normal and paired normal tissues. Clinicopathological parameters and tissue microarray (TMA) indicated that PDHB was identified as a prognostic factor for survival outcomes among ccRCC patients. Additionally, low PDHB was negatively correlated with Treg cells, indicating an immunosuppressive microenvironment. Mechanistically, knockdown PDHB appeared to promote the RCC cells proliferation, migration, and invasion potentials. Subsequent studies showed that copper-induced cell death activation could overcome sunitinib resistance in RCC cells.

Conclusion

This research illustrated a cuproptosis-related hub gene PDHB which could serve as a potential prognostic marker and provide therapeutic benefits for clinical treatment of ccRCC patients.

A nomogram based on cuproptosis-related genes predicts 7-year relapse-free survival in patients with estrogen receptor-positive early breast cancer

Introduction

Excess copper induces cell death by binding to lipoylated components of the tricarboxylic acid cycle. Although a few studies have examined the relationship between cuproptosis-related genes (CRGs) and breast cancer prognosis, reports on estrogen receptor-positive (ER+) breast cancer are lacking. Herein, we aimed to analyze the relationship between CRGs and outcomes in patients with ER+ early breast cancer (EBC).

Methods

We conducted a case-control study among patients with ER+ EBC presenting poor and favorable invasive disease-free survival (iDFS) at West China Hospital. Logistic regression analysis was performed to establish the association between CRG expression and iDFS. A cohort study was performed using pooled data from three publicly available microarray datasets in the Gene Expression Omnibus database. Subsequently, we constructed a CRG score model and a nomogram to predict relapse-free survival (RFS). Finally, the prediction performance of the two models was verified using training and validation sets.

Results

In this case-control study, high expression of LIAS, LIPT1, and ATP7B and low CDKN2A expression were associated with favorable iDFS. In the cohort study, high expression of FDX1, LIAS, LIPT1, DLD, PDHB, and ATP7B and low CDKN2A expression were associated with favorable RFS. Using LASSO-Cox analysis, a CRG score was developed using the seven identified CRGs. Patients in the low CRG score group had a reduced risk of relapse in both training and validation sets. The nomogram included the CRG score, lymph node status, and age. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was significantly higher than the AUC of the CRG score at 7 years.

Conclusions

The CRG score, combined with other clinical features, could afford a practical long-term outcome predictor in patients with ER+ EBC.

Cuproptosis-related gene CDKN2A as a molecular target for IPF diagnosis and therapeutics

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a progressive chronic interstitial lung disease with limited therapeutic options. Cuproptosis is a recently proposed novel form of programmed cell death, which has been strongly implicated in the development of various human diseases. However, the prognostic and therapeutic value of cuproptosis-related genes (CRGs) in IPF remains to be elucidated.

METHODS

In the present study, weighted gene co-expression network analysis (WGCNA) was employed to identify the key CRGs associated with the development of IPF. The subsequent GSEA, immune cell correlation analysis, and single-cell RNA-Seq analysis were conducted to explore the potential role of the identified CRGs in IPF. In addition, ROC curves and survival analysis were used to assess the prognostic value of the key CRGs in IPF. Moreover, we explored the molecular mechanisms of participation of identified key CRGs in the development of pulmonary fibrogenesis through in vivo and in vitro experiments.

RESULTS

The expression level of cyclin-dependent kinase inhibitor 2A (CDKN2A) is upregulated in the lung tissues of IPF patients and associated with disease severity. Notably, CDKN2A was constitutively expressed by fibrosis-promoting M2 macrophages. Decreased CDKN2A expression sensitizes M2 macrophages to elesclomol-induced cuproptosis in vitro. Inhibition of CDKN2A decreases the number of viable macrophages and attenuates bleomycin-induced pulmonary fibrosis in mice.

CONCLUSION

These findings indicate that CDKN2A mediates the resistance of fibrosis-promoting M2 macrophages to cuproptosis and promotes pulmonary fibrosis in mice. Our work provides fresh insights into CRGs in IPF with potential value for research in the pathogenesis, diagnosis, and a new therapy strategy for IPF.

Role of cuproptosis in understanding diseases

Cell death is involved in a wide range of physiological and pathological processes. Recently, the term "cuproptosis" was coined to describe a novel type of cell death. This type of cell death, characterized by copper accumulation and proteotoxic stress, is a copper-dependent manner of death. Despite the progress achieved toward a better understanding of cuproptosis, mechanisms and related signaling pathways in physiology and pathology across various diseases remain to be proved. This mini review summarizes current research on cuproptosis and diseases, providing insights into prospective clinical therapies via targeting cuproptosis.

Cuproptosis-a potential target for the treatment of osteoporosis

Osteoporosis is an age-related disease of bone metabolism marked by reduced bone mineral density and impaired bone strength. The disease causes the bones to weaken and break more easily. Osteoclasts participate in bone resorption more than osteoblasts participate in bone formation, disrupting bone homeostasis and leading to osteoporosis. Currently, drug therapy for osteoporosis includes calcium supplements, vitamin D, parathyroid hormone, estrogen, calcitonin, bisphosphates, and other medications. These medications are effective in treating osteoporosis but have side effects. Copper is a necessary trace element in the human body, and studies have shown that it links to the development of osteoporosis. Cuproptosis is a recently proposed new type of cell death. Copper-induced cell death regulates by lipoylated components mediated via mitochondrial ferredoxin 1; that is, copper binds directly to the lipoylated components of the tricarboxylic acid cycle, resulting in lipoylated protein accumulation and subsequent loss of iron-sulfur cluster proteins, leading to proteotoxic stress and eventually cell death. Therapeutic options for tumor disorders include targeting the intracellular toxicity of copper and cuproptosis. The hypoxic environment in bone and the metabolic pathway of glycolysis to provide energy in cells can inhibit cuproptosis, which may promote the survival and proliferation of various cells, including osteoblasts, osteoclasts, effector T cells, and macrophages, thereby mediating the osteoporosis process. As a result, our group tried to explain the relationship between the role of cuproptosis and its essential regulatory genes, as well as the pathological mechanism of osteoporosis and its effects on various cells. This study intends to investigate a new treatment approach for the clinical treatment of osteoporosis that is beneficial to the treatment of osteoporosis.

Transcriptomic profiling identifies differentially expressed genes and related pathways associated with wound healing and cuproptosis-related genes in Ganxi goats

Introduction

Wound healing is very important for the maintenance of immune barrier integrity, which has attracted wide attention in past 10 years. However, no studies on the regulation of cuproptosis in wound healing have been reported.

Methods

In this study, the skin injury model was constructed in Gnxi goats, and the function, regulatory network and hub genes of the skin before and after the injury were comprehensively analyzed by transcriptomics.

Results

The results showed that there were 1,438 differentially expressed genes (DEGs), genes up-regulated by 545 and genes down-regulated by 893, which were detected by comparing day 0 and day 5 posttraumatic skin. Based on GO-KEGG analysis, DEGs that were up-regulated tended to be enriched in lysosome, phagosome, and leukocyte transendothelial migration pathways, while down-regulated DEGs were significantly enriched in adrenergic signaling in cardiomyocytes and calcium signaling pathway. There were 166 overlapped genes (DE-CUGs) between DEGs and cuproptosis-related genes, with 72 up-regulated DE-CUGs and 94 down-regulated DE-CUGs. GOKEGG analysis showed that up-regulated DE-CUGs were significantly enriched in ferroptosis, leukocyte transendothelial migration and lysosome pathways, while down-regulated DE-CUGs were significantly enriched in Apelin signaling pathway and tyrosine metabolism pathways. By constructing and analyzing of protein-protein interaction (PPI) networks of DEGs and DE-CUGs, 10 hub DEGs (ENSCHIG00000020079, PLK1, AURKA, ASPM, CENPE, KIF20A, CCNB2, KIF2C, PRC1 and KIF4A) and 10 hub DE-CUGs (MMP2, TIMP1, MMP9, MMP14, TIMP3, MMP1, EDN1, GCAT, SARDH, and DCT) were obtained, respectively.

Discussion

This study revealed the hub genes and important wound healing pathways in Ganxi goats, and identified the correlation between wound healing and cuproptosis for the first time, and found that MMP2, TIMP1, MMP9, and EDN1 were the core genes associated. This study enriched the transcriptome data of wound healing in Ganxi goats and expanded the research direction of cuproptosis.

Identification and validation of cuproptosis related genes and signature markers in bronchopulmonary dysplasia disease using bioinformatics analysis and machine learning

BACKGROUND

Bronchopulmonary Dysplasia (BPD) has a high incidence and affects the health of preterm infants. Cuproptosis is a novel form of cell death, but its mechanism of action in the disease is not yet clear. Machine learning, the latest tool for the analysis of biological samples, is still relatively rarely used for in-depth analysis and prediction of diseases.

METHODS AND RESULTS

First, the differential expression of cuproptosis-related genes (CRGs) in the GSE108754 dataset was extracted and the heat map showed that the expression of NFE2L2 gene was significantly higher in the control group whereas the expression of GLS gene was significantly higher in the treatment group. Chromosome location analysis showed that both the genes were positively correlated and associated with chromosome 2. The results of immune infiltration and immune cell differential analysis showed differences in the four immune cells, significantly in Monocytes cells. Five new pathways were analyzed through two subgroups based on consistent clustering of CRG expression. Weighted correlation network analysis (WGCNA) set the screening condition to the top 25% to obtain the disease signature genes. Four machine learning algorithms: Generalized Linear Models (GLM), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGB) were used to screen the disease signature genes, and the final five marker genes for disease prediction. The models constructed by GLM method were proved to be more accurate in the validation of two datasets, GSE190215 and GSE188944.

CONCLUSION

We eventually identified two copper death-associated genes, NFE2L2 and GLS. A machine learning model-GLM was constructed to predict the prevalence of BPD disease, and five disease signature genes NFATC3, ERMN, PLA2G4A, MTMR9LP and LOC440700 were identified. These genes that were bioinformatics analyzed could be potential targets for identifying BPD disease and treatment.

Identification of the cuproptosis-related hub genes and therapeutic agents for sarcopenia

Background: Along with acceleration of population aging, the increasing prevalence of sarcopenia has posed a heavy burden on families as well as society. In this context, it is of great significance to diagnose and intervene sarcopenia as early as possible. Recent evidence has indicated the role of cuproptosis in the development of sarcopenia. In this study, we aimed to seek the key cuproptosis-related genes that can be used for identification and intervention of sarcopenia.

Methods: The GSE111016 dataset was retrieved from GEO. The 31 cuproptosis-related genes (CRGs) were obtained from previous published studies. The differentially expressed genes (DEGs) and Weighed gene co-expression network analysis (WGCNA) were subsequently analyzed. The core hub genes were acquired by the intersection of DEGs, WGCNA and CRGs. Through logistic regression analysis, we established a diagnostic model of sarcopenia based on the selected biomarkers and was validated in muscle samples from GSE111006 and GSE167186. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis were performed on these genes. Furthermore, the gene set enrichment analysis (GSEA), and immune cell infiltration were also conducted on the identified core genes. Finally, we screened the potential drugs targeting the potential biomarkers of sarcopenia.

Results: A total of 902 DEGs and WGCNA containing 1,281 significant genes were preliminarily selected. Intersection of DEGs, WGCNA and CRGs yielded four core genes (PDHA1, DLAT, PDHB, and NDUFC1) as potential biomarkers for the prediction of sarcopenia. The predictive model was established and validated with high AUC values. KEGG pathway and Gene Ontology biological analysis indicated these core genes may play a crucial role in energy metabolism in mitochondria, oxidation process, and aging-related degenerative diseases. In addition, the immune cells may be involved in the development of sarcopenia through mitochondrial metabolism. Finally, metformin was identified as a promising strategy of sarcopenia treatment via targeting NDUFC1.

Conclusion: The four cuproptosis-related genes PDHA1, DLAT, PDHB and NDUFC1 may be the diagnostic biomarkers for sarcopenia, and metformin holds great potential to be developed as a therapy for sarcopenia. These outcomes provide new insights for better understanding of sarcopenia and innovative therapeutic approaches.

Understanding the function of the GABAergic system and its potential role in rheumatoid arthritis

Rheumatoid arthritis (RA) is a highly disabling chronic autoimmune disease. Multiple factors contribute to the complex pathological process of RA, in which an abnormal autoimmune response, high survival of inflammatory cells, and excessive release of inflammatory factors lead to a severe chronic inflammatory response. Clinical management of RA remains limited; therefore, exploring and discovering new mechanisms of action could enhance clinical benefits for patients with RA. Important bidirectional communication occurs between the brain and immune system in inflammatory diseases such as RA, and circulating immune complexes can cause neuroinflammatory responses in the brain. The gamma-aminobutyric acid (GABA)ergic system is a part of the nervous system that primarily comprises GABA, GABA-related receptors, and GABA transporter (GAT) systems. GABA is an inhibitory neurotransmitter that binds to GABA receptors in the presence of GATs to exert a variety of pathophysiological regulatory effects, with its predominant role being neural signaling. Nonetheless, the GABAergic system may also have immunomodulatory effects. GABA/GABA-A receptors may inhibit the progression of inflammation in RA and GATs may promote inflammation. GABA-B receptors may also act as susceptibility genes for RA, regulating the inflammatory response of RA via immune cells. Furthermore, the GABAergic system may modulate the abnormal pain response in RA patients. We also summarized the latest clinical applications of the GABAergic system and provided an outlook on its clinical application in RA. However, direct studies on the GABAergic system and RA are still lacking; therefore, we hope to provide potential therapeutic options and a theoretical basis for RA treatment by summarizing any potential associations.

Effect of regulatory cell death on the occurrence and development of head and neck squamous cell carcinoma

Head and neck cancer is a malignant tumour with a high mortality rate characterized by late diagnosis, high recurrence and metastasis rates, and poor prognosis. Head and neck squamous cell carcinoma (HNSCC) is the most common type of head and neck cancer. Various factors are involved in the occurrence and development of HNSCC, including external inflammatory stimuli and oncogenic viral infections. In recent years, studies on the regulation of cell death have provided new insights into the biology and therapeutic response of HNSCC, such as apoptosis, necroptosis, pyroptosis, autophagy, ferroptosis, and recently the newly discovered cuproptosis. We explored how various cell deaths act as a unique defence mechanism against cancer emergence and how they can be exploited to inhibit tumorigenesis and progression, thus introducing regulatory cell death (RCD) as a novel strategy for tumour therapy. In contrast to accidental cell death, RCD is controlled by specific signal transduction pathways, including TP53 signalling, KRAS signalling, NOTCH signalling, hypoxia signalling, and metabolic reprogramming. In this review, we describe the molecular mechanisms of nonapoptotic RCD and its relationship to HNSCC and discuss the crosstalk between relevant signalling pathways in HNSCC cells. We also highlight novel approaches to tumour elimination through RCD.

Development and validation of cuproptosis-related genes in synovitis during osteoarthritis progress

Osteoarthritis (OA) is one of the most common refractory degenerative joint diseases worldwide. Synovitis is believed to drive joint cartilage destruction during OA pathogenesis. Cuproptosis is a novel form of copper-induced cell death. However, few studies have examined the correlations between cuproptosis-related genes (CRGs), immune infiltration, and synovitis. Therefore, we analyzed CRGs in synovitis during OA. Microarray datasets (GSE55235, GSE55457, GSE12021, GSE82107 and GSE176308) were downloaded from the Gene Expression Omnibus database. Next, we conducted differential and subtype analyses of CRGs across synovitis. Immune infiltration and correlation analyses were performed to explore the association between CRGs and immune cell abundance in synovitis. Finally, single-cell RNA-seq profiling was performed using the GSE176308 dataset to investigate the expression of CRGs in the various cell clusters. We found that the expression of five CRGs (FDX1, LIPT1, PDHA1, PDHB, and CDKN2A) was significantly increased in the OA synovium. Moreover, abundant and various types of immune cells infiltrated the synovium during OA, which was correlated with the expression of CRGs. Additionally, single-cell RNA-seq profiling revealed that the cellular composition of the synovium was complex and that their proportions varied greatly as OA progressed. The expression of CRGs differed across various cell types in the OA synovium. The current study predicted that cuproptosis may be involved in the pathogenesis of synovitis. The five screened CRGs (FDX1, LIPT1, PDHA1, PDHB, and CDKN2A) could be explored as candidate biomarkers or therapeutic targets for OA synovitis.

Identification of copper death-associated molecular clusters and immunological profiles in rheumatoid arthritis

Objective

An analysis of the relationship between rheumatoid arthritis (RA) and copper death-related genes (CRG) was explored based on the GEO dataset.

Methods

Based on the differential gene expression profiles in the GSE93272 dataset, their relationship to CRG and immune signature were analysed. Using 232 RA samples, molecular clusters with CRG were delineated and analysed for expression and immune infiltration. Genes specific to the CRGcluster were identified by the WGCNA algorithm. Four machine learning models were then built and validated after selecting the optimal model to obtain the significant predicted genes, and validated by constructing RA rat models.

Results

The location of the 13 CRGs on the chromosome was determined and, except for GCSH. LIPT1, FDX1, DLD, DBT, LIAS and ATP7A were expressed at significantly higher levels in RA samples than in non-RA, and DLST was significantly lower. RA samples were significantly expressed in immune cells such as B cells memory and differentially expressed genes such as LIPT1 were also strongly associated with the presence of immune infiltration. Two copper death-related molecular clusters were identified in RA samples. A higher level of immune infiltration and expression of CRGcluster C2 was found in the RA population. There were 314 crossover genes between the 2 molecular clusters, which were further divided into two molecular clusters. A significant difference in immune infiltration and expression levels was found between the two. Based on the five genes obtained from the RF model (AUC = 0.843), the Nomogram model, calibration curve and DCA also demonstrated their accuracy in predicting RA subtypes. The expression levels of the five genes were significantly higher in RA samples than in non-RA, and the ROC curves demonstrated their better predictive effect. Identification of predictive genes by RA animal model experiments was also confirmed.

Conclusion

This study provides some insight into the correlation between rheumatoid arthritis and copper mortality, as well as a predictive model that is expected to support the development of targeted treatment options in the future.

Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer

Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients’ immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients’ overall survival, indicate immunocyte infiltration, and identify individualized treatment.