FDX1 can Impact the Prognosis and Mediate the Metabolism of Lung Adenocarcinoma

Cuproptosis associated cytoskeletal destruction contributes to podocyte injury in chronic kidney disease

The podocyte cytoskeleton determines the stability of podocyte structure and function, and their imbalance plays a pathogenic role in podocyte diseases. However, the underlying mechanism of podocyte cytoskeleton damage is not fully understood. Here, we investigate the specific role of cuproptosis in inducing podocyte cytoskeleton injury. In in vitro and in vivo studies, exposure to high levels of copper and adriamycin (ADR) caused significant increases in copper concentration in intracellular and renal tissue. Moreover, excessive accumulation of copper induced cuproptosis, resulting in the destruction of the podocyte cytoskeleton. However, inhibition of copper accumulation to reduce cuproptosis also significantly alleviated the damage of podocyte cytoskeleton. In addition, inhibition of cuproptosis mitigated ADR-induced mitochondrial damage as well as the production of reactive oxygen species and depolarization of mitochondrial membrane potential, and restored adenosine triphosphate (ATP) synthesis. Among the transcriptome sequencing data, the difference of CXCL5 (C-X-C motif chemokine ligand 5) was the most significant. Both high copper and ADR exposure can cause upregulation of CXCL5, and CXCL5 deletion inhibits the occurrence of cuproptosis, thereby alleviating the podocyte cytoskeleton damage. This suggests that CXCL5 may act upstream of cuproptosis that mediates podocyte cytoskeleton damage. In conclusion, cuproptosis induced by excessive copper accumulation may induce podocyte cytoskeleton damage by promoting mitochondrial dysfunction, thereby causing podocyte injury. This indicates that cuproptosis plays an important role in the pathogenesis of podocyte injury and provides a basis for seeking potential targets for the treatment of chronic kidney disease.NEW & NOTEWORTHY Cuproptosis induced by excessive copper accumulation leads to podocyte cytoskeleton damage by promoting mitochondrial dysfunction, and CXCL5 acts as an upstream signal mediating the occurrence of cuproptosis.

Cuproptosis in cancer: biological implications and therapeutic opportunities

Cuproptosis, a newly identified copper (Cu)-dependent form of cell death, stands out due to its distinct mechanism that sets it apart from other known cell death pathways. The molecular underpinnings of cuproptosis involve the binding of Cu to lipoylated enzymes in the tricarboxylic acid cycle. This interaction triggers enzyme aggregation and proteotoxic stress, culminating in cell death. The specific mechanism of cuproptosis has yet to be fully elucidated. This newly recognized form of cell death has sparked numerous investigations into its role in tumorigenesis and cancer therapy. In this review, we summarized the current knowledge on Cu metabolism and its link to cancer. Furthermore, we delineated the molecular mechanisms of cuproptosis and summarized the roles of cuproptosis-related genes in cancer. Finally, we offered a comprehensive discussion of the most recent advancements in Cu ionophores and nanoparticle delivery systems that utilize cuproptosis as a cutting-edge strategy for cancer treatment.

GLS and GLS2 Glutaminase Isoenzymes in the Antioxidant System of Cancer Cells

A pathway frequently altered in cancer is glutaminolysis, whereby glutaminase (GA) catalyzes the main step as follows: the deamidation of glutamine to form glutamate and ammonium. There are two types of GA isozymes, named GLS and GLS2, which differ considerably in their expression patterns and can even perform opposing roles in cancer. GLS correlates with tumor growth and proliferation, while GLS2 can function as a context-dependent tumor suppressor. However, both isoenzymes have been described as essential molecules handling oxidant stress because of their involvement in glutathione production. We reviewed the literature to highlight the critical roles of GLS and GLS2 in restraining ROS and regulating both cellular signaling and metabolic stress due to their function as indirect antioxidant enzymes, as well as by modulating both reductive carboxylation and ferroptosis. Blocking GA activity appears to be a potential strategy in the dual activation of ferroptosis and inhibition of cancer cell growth in a ROS-mediated mechanism.

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.

Clinical features and molecular landscape of cuproptosis signature-related molecular subtype in gastric cancer

Recent studies have highlighted the biological significance of cuproptosis in disease occurrence and development. However, it remains unclear whether cuproptosis signaling also has potential impacts on tumor initiation and prognosis of gastric cancer (GC). In this study, 16 cuproptosis-related genes (CRGs) transcriptional profiles were harnessed to perform the regularized latent variable model-based clustering in GC. A cuproptosis signature risk scoring (CSRS) scheme, based on a weighted sum of principle components of the CRGs, was used to evaluate the prognosis and risk of individual tumors of GC. Four distinct cuproptosis signature-based clusters, characterized by differential expression patterns of CRGs, were identified among 1136 GC samples across three independent databases. The four clusters were also associated with different clinical outcomes and tumor immune contexture. Based on the CSRS, GC patients can be divided into CSRS-High and CSRS-Low subtypes. We found that DBT, MTF1, and ATP7A were significantly elevated in the CSRS-High subtype, while SLC31A1, GCSH, LIAS, DLAT, FDX1, DLD, and PDHA1 were increased in the CSRS-Low subtype. Patients with CSRS-Low score were characterized by prolonged survival time. Further analysis indicated that CSRS-Low score also correlated with greater tumor mutation burden (TMB) and higher mutation rates of significantly mutated genes (SMG) in GC. In addition, the CSRS-High subtype harbored more significantly amplified focal regions related to tumorigenesis (3q27.1, 12p12.1, 11q13.3, etc.) than the CSRS-Low tumors. Drug sensitivity analyses revealed the potential compounds for the treatment of gastric cancer with CSRS-High score, which were experimentally validated using GC cells. This study highlights that cuproptosis signature-based subtyping is significantly associated with different clinical features and molecular landscape of GC. Quantitative evaluation of the CSRS of individual tumors will strengthen our understanding of the occurrence and development of cuproptosis and the treatment progress of GC.

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.

Ferredoxin 1: a gatekeeper in halting lung adenocarcinoma progression through activation of the GPRIN2 signaling pathway

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly lethal form of lung cancer. Despite advancements in treatments, managing LUAD is still challenging due to its aggressive behavior. Recent studies indicate that various molecular pathways, including the dysregulation of ferredoxin 1 (FDX1), play roles in LUAD progression. FDX1, a crucial protein in cellular redox reactions and energy metabolism, has been linked to several cancers. However, its exact role in the development of LUAD is not yet fully understood.

METHODS

We investigated the role of ferredoxin 1 (FDX1) in LUAD progression through analysis of its expression in LUAD tissues and its impact on patient survival. Functional assays were performed to assess the effects of FDX1 overexpression on LUAD cell proliferation, migration, and invasion. A xenograft model was employed to evaluate the tumorigenesis potential of LUAD cells with FDX1 overexpression. Mechanistic insights into FDX1 regulation were gained through depletion experiments targeting the G protein-regulated inducer of neurite outgrowth 2 (GPRIN2)/PI3K signaling pathway.

RESULTS

FDX1 expression was down-regulated in LUAD tissues, correlating with shorter patient survival. Overexpression of FDX1 suppressed LUAD cell proliferation, migration, and invasion in vitro, and inhibited tumorigenesis in vivo. Mechanistically, the GPRIN2/PI3K signaling pathway was implicated in FDX1 regulation, as depletion of GPRIN2 reversed the effects of FDX1 overexpression on cellular functions.

CONCLUSIONS

Our findings highlight FDX1 as a potential tumor suppressor in LUAD, acting through modulation of the GPRIN2/PI3K signaling pathway. These results suggest FDX1 as a promising therapeutic target for LUAD treatment, warranting further investigation into its clinical relevance.

A cuproptosis-based prognostic model for predicting survival in low-grade glioma

BACKGROUND

It is unknown what variables contribute to the formation and multiplication of low-grade gliomas (LGG). An emerging process of cell death is called cuproptosis. Our research aims to increase therapeutic options and gain a better understanding of the role that cuproptosis-related genes play in the physical characteristics of low-grade gliomas.

METHODS

The TCGA database was utilized to find cuproptosis genes that may be used to develop LGG risk model. Cox analysis in three different formats: univariate, multivariate, and LASSO. The gene signature's independent predictive ability was assessed using ROC curves and Cox regression analysis based on overall survival. Use of CGGA data and nomogram model for external validation Immunohistochemistry, gene mutation, and functional enrichment analysis are also employed to clarify risk models' involvement. Next, we analyzed changes in the immunological microenvironment in the risk model and forecasted possible chemotherapeutic drugs to target each group. Finally, we validated the protein expression levels of cuproptosis-related genes using LGG and adjacent normal tissues in a small self-case-control study.

RESULTS

This study developed a glioma predictive model based on five cuproptosis-associated genes. Compared to the high-risk group, the low-risk group's OS was significantly longer. The ROC curves showed high genetic signature performance in both groups. The signature-based categorisation was also linked to clinical characteristics and molecular subgroups. The prognosis of individuals with grade 2 or 3 glioma is also influenced by our risk model. Immunological testing revealed that the high-risk group had more immune cells and immunological function. The risk model also predicted immunotherapy and chemotherapy medication results. Also, this study confirmed that the expression of cuproptosis-related genes by Western blot.

CONCLUSION

We developed a prediction model for LGG patients using genes associated with cuproptosis. With acceptable prediction performance, this risk model may effectively stratify the prognosis of glioma patients.

Cuproptosis in glioblastoma: unveiling a novel prognostic model and therapeutic potential

Glioblastoma, a notably aggressive brain tumor, is characterized by a brief survival period and resistance to conventional therapeutic approaches. With the recent identification of "Cuproptosis," a copper-dependent apoptosis mechanism, this study aimed to explore its role in glioblastoma prognosis and potential therapeutic implications. A comprehensive methodology was employed, starting with the identification and analysis of 65 cuproptosis-related genes. These genes were subjected to differential expression analyses between glioblastoma tissues and normal counterparts. A novel metric, the "CP-score," was devised to quantify the cuproptosis response in glioblastoma patients. Building on this, a prognostic model, the CP-model, was developed using Cox regression techniques, designed to operate on both bulk and single-cell data. The differential expression analysis revealed 31 genes with distinct expression patterns in glioblastoma. The CP-score was markedly elevated in glioblastoma patients, suggesting an intensified cuproptosis response. The CP-model adeptly stratified patients into distinct risk categories, unveiling intricate associations between glioblastoma prognosis, immune response pathways, and the tumor's immunological environment. Further analyses indicated that high-risk patients, as per the CP-model, exhibited heightened expression of certain immune checkpoints, suggesting potential therapeutic targets. Additionally, the model hinted at the possibility of personalized therapeutic strategies, with certain drugs showing increased efficacy in high-risk patients. The CP-model offers a promising tool for glioblastoma prognosis and therapeutic strategy development, emphasizing the potential of Cuproptosis in cancer treatment.

[Correlation of serum ferredoxin 1 and lipoic acid levels with severity of coronary artery disease]

OBJECTIVE

To analyze the correlation of copper death inducer ferredoxin 1 (FDX1) and lipoic acid (LA) with the occurrence and severity of coronary atherosclerosis and explore their roles in coronary heart disease (CHD).

METHODS

We analyzed the data of 226 patients undergoing coronary artery angiography (CAG) in our hospital between October, 2021 and October, 2022, including 47 patients with normal CAG findings (control group) and 179 patients with mild, moderate or severe coronary artery stenosis (CHD group). Serum FDX1 and LA levels were determined with ELISA for all the patients. We also examined pathological changes in the aorta of normal and ApoE-/- mice using HE staining and observed collagen fiber deposition with Sirius red staining. Immunohistochemistry was used to detect the expression and distribution of FDX1 and LA in the aorta, and RT-PCR was performed to detect the expressions of FDX1, LIAS and ACO2 mRNAs in the myocardial tissues.

RESULTS

Compared with the control patients, CHD patients had significantly lower serum FDX1 and LA levels, which decreased progressively as coronary artery stenosis worsened (P < 0.01) and as the number of involved coronary artery branches increased (P < 0.05). Serum FDX1 and LA levels were positively correlated (r=0.451, P < 0.01) and they both negatively correlated with the Gensini score (r=-0.241 and -0.273, respectively; P < 0.01). Compared with normal mice, ApoE-/- mice showed significantly increased lipid levels (P < 0.01) and atherosclerosis index, obvious thickening, lipid aggregation, and collagen fiber hyperplasia in the aorta, and significantly reduced expressions of FDX1, LA, LIAS, and ACO2 (P < 0.05).

CONCLUSION

Serum FDX1 and LA levels decrease with worsening of coronary artery lesions, and theirs expressions are correlated with coronary artery lesions induced by hyperlipidemia.

Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer

Background: Ground-glass opacity (GGO)-associated cancers are increasingly prevalent, exhibiting unique clinical and molecular features that suggest the need for a distinct treatment strategy. However, the metabolic characteristics and vulnerabilities of GGO-associated lung cancers remain unexplored. Methods: We conducted metabolomic and transcriptomic analyses on 40 pairs of GGO-associated lung cancer tissues and adjacent normal tissues. By integrating data from TCGA database and single-cell RNA sequencing, we aimed to identify aberrant metabolic pathways, establish a metabolite-associated gene signature, and pinpoint key metabolic genes. The physiological effect of key genes was detected in vitro and vivo assays. Results: We identified a 30-gene metabolite-associated signature and discovered aberrant metabolic pathways for GGO-associated lung cancer at both metabolic and transcriptional levels. Patients with this signature displayed specific prognostic and molecular features. Cox regression analysis, based on the Cancer Genome Atlas Program (TCGA) data, further narrowed down the metabolite-related gene signature, resulting in a 5-gene signature. Confirmed by single-cell RNA sequencing (GSE203360), the 5-gene signature was mainly expressed in cancer cells of GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential expression of these genes between GGO and adjacent normal tissue obtained from pulmonary surgery. Finally, our integrative analysis unveiled aberrant histidine metabolism at both the multi-omics and single-cell levels. Moreover, we identified MAOB as a key metabolic gene, demonstrating its ability to suppress cell proliferation, migration, and invasion in LUAD cell lines, both in vitro and in vivo. Conclusions: We identified a specific metabolite-associated gene signature and identified aberrant histidine metabolism in GGO-associated lung cancer from multiple perspectives. Notably, MAOB, a crucial component in histidine metabolism, demonstrated a significant inhibitory effect on the proliferation and metastasis of LUAD, indicating its potential significance in pathogenesis and therapeutic interventions.

Cuprotosis clusters predict prognosis and immunotherapy response in low-grade glioma

Cuprotosis, an emerging mode of cell death, has recently caught the attention of researchers worldwide. However, its impact on low-grade glioma (LGG) patients has not been fully explored. To gain a deeper insight into the relationship between cuprotosis and LGG patients' prognosis, we conducted this study in which LGG patients were divided into two clusters based on the expression of 18 cuprotosis-related genes. We found that LGG patients in cluster A had better prognosis than those in cluster B. The two clusters also differed in terms of immune cell infiltration and biological functions. Moreover, we identified differentially expressed genes (DEGs) between the two clusters and developed a cuprotosis-related prognostic signature through the least absolute shrinkage and selection operator (LASSO) analysis in the TCGA training cohort. This signature divided LGG patients into high- and low-risk groups, with the high-risk group having significantly shorter overall survival (OS) time than the low-risk group. Its predictive reliability for prognosis in LGG patients was confirmed by the TCGA internal validation cohort, CGGA325 cohort and CGGA693 cohort. Additionally, a nomogram was used to predict the 1-, 3-, and 5-year OS rates of each patient. The analysis of immune checkpoints and tumor mutation burden (TMB) has revealed that individuals belonging to high-risk groups have a greater chance of benefiting from immunotherapy. Functional experiments confirmed that interfering with the signature gene TNFRSF11B inhibited LGG cell proliferation and migration. Overall, this study shed light on the importance of cuprotosis in LGG patient prognosis. The cuprotosis-related prognostic signature is a reliable predictor for patient outcomes and immunotherapeutic response and can help to develop new therapies for LGG.

Cuproptosis-related gene-located DNA methylation in lower-grade glioma: Prognosis and tumor microenvironment

Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients.

The Cross-Communication of Cuproptosis and Regulated Cell Death in Human Pathophysiology

Copper (Cu) plays a crucial and diverse function in biological systems, acting as a cofactor at numerous sites of enzymatic activity and participating in various physiological processes, including oxidative stress regulation, lipid metabolism, and energy metabolism. Similar to other micronutrients, the body regulates Cu levels to ensure homeostasis; any disruption in Cu homeostasis may result in various illnesses. Cuproptosis causes proteotoxic stress and ultimately results in cell death by the binding of Cu ions to lipid-acylated proteins during the tricarboxylic acid cycle of mitochondrial respiration. Cu is not only involved in regulatory cell death (RCD), but also in exogenous factors that induce cellular responses and toxic outcomes. Cu imbalances also affect the transmission of several RCD messages. Therefore, this article presents a thorough examination of the mechanisms involved in Cu-induced RCD as well as the role of Cu complexes in its pathophysiology.

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.

A prognostic signature for lung adenocarcinoma by five genes associated with chemotherapy in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common subtypes of lung cancer. Finding prognostic biomarkers is helpful in stratifying LUAD patients with different prognosis.

METHODS

We explored the correlation of LUAD prognosis and genes associated with chemotherapy in LUAD and obtained data of LUAD patients from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Drug sensitivity data were acquired from the Genomics of Drug Sensitivity in Cancer (GDSC) database. Differential and enrichment analyses were used to screen the target genes utilizing limma and "clusterProfiler" packages. Then univariate and LASSO Cox analyses were used to select the prognosis-related genes. Survival analysis was used to estimate the overall survival (OS) of different groups.

RESULTS

Twenty-three differentially expressed genes (DEGs) were screened between LUAD samples and healthy samples, and BTK, FGFR2, PIM2, CHEK1, and CDK1 were selected to construct a prognostic signature. The OS of patients in the high-risk group (risk score higher than 0.69) was worse than that in the low-risk group (risk score lower than 0.69).

CONCLUSION

The risk score model constructed by five genes is a potential prognostic biomarker for LUAD patients.

Pan-cancer analysis of cuproptosis-promoting gene signature from multiple perspectives

Cuproptosis is a newly discovered cell death form with a unique mechanism. Seven genes have been identified to facilitate the process. To explore the roles of cuproptosis in different cancers, we first used Gene Expression Profiling, Interactive Analysis, version 2, and cBioPortal to analyze expression, prognosis and mutation conditions in different cancers from The Cancer Genome Atlas (TCGA). Then, we conducted single sample gene set enrichment analysis to combine the signature of the cuproptosis-promoting genes for all TCGA cancers. Moreover, we performed a survival analysis to explore if cuproptosis-score could independently influence clinical outcomes. Next, we compared pathway enrichment, immune infiltration, gene set activity and gene mutation between different cuproptosis-score groups. Finally, based on the intersected genes from difference analysis and weighted gene co-expression network analysis, consensus clustering and Least Absolute Shrinkage and Selection Operator Cox regression were performed and nomograms were constructed. Cuproptosis-score was associated with a favorable prognosis in eight TCGA cancers. Cancer-associated fibroblasts, B cells, neutrophils and mast cells were generally less abundant, and ferroptosis activity was higher in high cuproptosis-score groups. The novel classifications could differentiate patients' overall survival, and the risk models could effectively predict patients' outcomes in kidney, renal clear cell carcinoma, liver hepatocellular carcinoma, mesothelioma and stomach adenocarcinoma. Cuproptosis activity was closely related to the prognosis of several cancers. Its effects on the immune microenvironment and its relationship with other cell death modes, especially ferroptosis, may become the focus of further research.

Lactylation of METTL16 promotes cuproptosis via m6A-modification on FDX1 mRNA in gastric cancer

Cuproptosis, caused by excessively high copper concentrations, is urgently exploited as a potential cancer therapeutic. However, the mechanisms underlying the initiation, propagation, and ultimate execution of cuproptosis in tumors remain unknown. Here, we show that copper content is significantly elevated in gastric cancer (GC), especially in malignant tumors. Screening reveals that METTL16, an atypical methyltransferase, is a critical mediator of cuproptosis through the m6A modification on FDX1 mRNA. Furthermore, copper stress promotes METTL16 lactylation at site K229 followed by cuproptosis. The process of METTL16 lactylation is inhibited by SIRT2. Elevated METTL16 lactylation significantly improves the therapeutic efficacy of the copper ionophore- elesclomol. Combining elesclomol with AGK2, a SIRT2-specific inhibitor, induce cuproptosis in gastric tumors in vitro and in vivo. These results reveal the significance of non-histone protein METTL16 lactylation on cuproptosis in tumors. Given the high copper and lactate concentrations in GC, cuproptosis induction becomes a promising therapeutic strategy for GC.

Progress in the research of cuproptosis and possible targets for cancer therapy

Developing novel cancer therapies that exploit programmed cell death pathways holds promise for advancing cancer treatment. According to a recently published study in Science, copper death (cuproptosis) occurs when intracellular copper is overloaded, triggering aggregation of lipidated mitochondrial proteins and Fe-S cluster proteins. This intriguing phenomenon is triggered by the instability of copper ions. Understanding the molecular mechanisms behind cuproptosis and its associated genes, as identified by Tsvetkov, including ferredoxin 1, lipoic acid synthase, lipoyltransferase 1, dihydrolipid amide dehydrogenase, dihydrolipoamide transacetylase, pyruvate dehydrogenase α1, pyruvate dehydrogenase β, metallothionein, glutaminase, and cyclin-dependent kinase inhibitor 2A, may open new avenues for cancer therapy. Here, we provide a new understanding of the role of copper death and related genes in cancer.

Identification of cuproptosis-related subtypes, characterization of immune microenvironment infiltration, and development of a prognosis model for osteoarthritis

Background

Osteoarthritis (OA) is a prevalent chronic joint disease with an obscure underlying molecular signature. Cuproptosis plays a crucial role in various biological processes. However, the association between cuproptosis-mediated immune infifiltration and OA progression remains unexplored. Therefore, this study elucidates the pathological process and potential mechanisms underlying cuproptosis in OA by constructing a columnar line graph model and performing consensus clustering analysis.

Methods

Gene expression profifile datasets GSE12021, GSE32317, GSE55235, and GSE55457 of OA were obtained from the comprehensive gene expression database. Cuproptosis signature genes were screened by random forest (RF) and support vector machine (SVM). A nomogram was developed based on cuproptosis signature genes. A consensus clustering was used to distinguish OA patients into different cuproptosis patterns. To quantify the cuproptosis pattern, a principal component analysis was developed to generate the cuproptosis score for each sample. Single-sample gene set enrichment analysis (ssGSEA) was used to provide the abundance of immune cells in each sample and the relationship between these significant cuproptosis signature genes and immune cells.To quantify the cuproptosis pattern, a principal component analysis technique was developed to generate the cuproptosis score for each sample. Cuproptosis-related genes were extracted and subjected to differential expression analysis to construct a disease prediction model and confifirmed by RT-qPCR.

Results

Seven cuproptosis signature genes were screened (DBT, LIPT1, GLS, PDHB, FDX1, DLAT, and PDHA1) to predict the risk of OA disease. A column line graph model was developed based on these seven cuproptosis signature genes, which may assist patients based on decision curve analysis. A consensus clustering method was used to distinguish patients with disorder into two cuproptosis patterns (clusters A and B). To quantify the cuproptosis pattern, a principal component analysis technique was developed to generate the cuproptosis score for each sample. Furthermore, the OA characteristics of patients in cluster A were associated with the inflflammatory factors IL-1b, IL-17, IL-21, and IL-22, suggesting that the cuproptosis signature genes play a vital role in the development of OA.

Discussion

In this study, a risk prediction model based on cuproptosis signature genes was established for the fifirst time, and accurately predicted OA risk. In addition, patients with OA were classifified into two cuproptosis molecule subtypes (clusters A and B); cluster A was highly associated with Th17 immune responses, with higher IL-1b, IL-17, and IL-21 IL-22 expression levels, while cluster B had a higher correlation with cuproptosis. Our analysis will help facilitate future research related cuproptosis-associated OA immunotherapy. However, the specifific mechanisms remain to be elucidated.

Elucidating Cuproptosis-Associated Genes in the Progression from Nash to HCC Using Bulk and Single-Cell RNA Sequencing Analyses and Experimental Validation

Background and Objectives: Non-alcoholic steatohepatitis (NASH) is a significant risk factor for hepatocellular carcinoma (HCC) development. Timely treatment during the NASH stage is essential to minimize the possibility of disease progression to HCC. Cuproptosis is a newly identified form of cellular death that could impact the progression of various diseases and cancers. Materials and Methods: Transcriptome and single-cell sequencing datasets were utilized to investigate the role of cuproptosis-related genes (CRGs) in NASH progression to HCC. FDX1, LIPT1, and PDHP were identified as CRGs in NASH patients, and FDX1, DBT, GCSH, SLC31A1, and DLAT were identified as CRGs in patients with NASH progressing to HCC. FDX1 was found to play a significant role in both NASH patients and patients with NASH progressing to HCC. This study constructed cuproptosis-related clusters (CRCs) using the Nonnegative Matrix Factorization algorithm, and they were linked to fatty acid metabolism and the PPAR signaling pathway in both NASH CRCs and HCC CRCs. The Weighted Correlation Network Analysis algorithm identified CRP, CRC, TAT, CXCL10, and ACTA1 as highly relevant genes in NASH CRCs and HCC CRCs. The expression of FDX1 was validated in both mouse models and human NASH samples. Results: The investigation highlights FDX1 as a pivotal CRG in both NASH and NASH progression to HCC. The comprehensive characterization of CRGs sheds light on their potential biofunctional importance in the context of NASH and HCC. Our experimental results show that FDX1 expression was significantly increased in NASH patients. Conclusions: The present study identified key CRGs, revealing their potential impact on NASH and HCC. Meanwhile, targeting FDX1 may prevent the progression of NASH to HCC.

Novel Molecular Subtyping Scheme Based on In Silico Analysis of Cuproptosis Regulator Gene Patterns Optimizes Survival Prediction and Treatment of Hepatocellular Carcinoma

BACKGROUND

The liver plays an important role in maintaining copper homeostasis. Copper ion accumulation was elevated in HCC tissue samples. Copper homeostasis is implicated in cancer cell proliferation and angiogenesis. The potential of copper homeostasis as a new theranostic biomarker for molecular imaging and the targeted therapy of HCC has been demonstrated. Recent studies have reported a novel copper-dependent nonapoptotic form of cell death called cuproptosis, strikingly different from other known forms of cell death. The correlation between cuproptosis and hepatocellular carcinoma (HCC) is not fully understood.

MATERIALS AND METHODS

The transcriptomic data of patients with HCC were retrieved from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and were used as a discovery cohort to construct the prognosis model. The gene expression data of patients with HCC retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases were used as the validation cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to construct the prognosis model. A principal component analysis (PCA) was used to evaluate the overall characteristics of cuproptosis regulator genes and obtain the PC1 and PC2 scores. Unsupervised clustering was performed using the ConsensusClusterPlus R package to identify the molecular subtypes of HCC. Cox regression analysis was performed to identify cuproptosis regulator genes that could predict the prognosis of patients with HCC. The receiver operating characteristics curve and Kaplan-Meier survival analysis were used to understand the role of hub genes in predicting the diagnosis and prognosis of patients, as well as the prognosis risk model. A weighted gene co-expression network analysis (WGCNA) was used for screening the cuproptosis subtype-related hub genes. The functional enrichment analysis was performed using Metascape. The 'glmnet' R package was used to perform the LASSO regression analysis, and the randomForest algorithm was performed using the 'randomForest' R package. The 'pRRophetic' R package was used to estimate the anticancer drug sensitivity based on the data retrieved from the Genomics of Drug Sensitivity in Cancer database. The nomogram was constructed using the 'rms' R package. Pearson's correlation analysis was used to analyze the correlations.

RESULTS

We constructed a six-gene signature prognosis model and a nomogram to predict the prognosis of patients with HCC. The Kaplan-Meier survival analysis revealed that patients with a high-risk score, which was predicted by the six-gene signature model, had poor prognoses (log-rank test p < 0.001; HR = 1.83). The patients with HCC were grouped into three distinct cuproptosis subtypes (Cu-clusters A, B, and C) based on the expression pattern of cuproptosis regulator genes. The patients in Cu-cluster B had poor prognosis (log-rank test p < 0.001), high genomic instability, and were not sensitive to conventional chemotherapeutic treatment compared to the patients in the other subtypes. Cancer cells in Cu-cluster B exhibited a higher degree of the senescence-associated secretory phenotype (SASP), a marker of cellular senescence. Three representative genes, CDCA8, MCM6, and NCAPG2, were identified in patients in Cu-cluster B using WGCNA and the "randomForest" algorithm. A nomogram was constructed to screen patients in the Cu-cluster B subtype based on three genes: CDCA8, MCM6, and NCAPG2.

CONCLUSION

Publicly available databases and various bioinformatics tools were used to study the heterogeneity of cuproptosis in patients with HCC. Three HCC subtypes were identified, with differences in the survival outcomes, genomic instability, senescence environment, and response to anticancer drugs. Further, three cuproptosis-related genes were identified, which could be used to design personalized therapeutic strategies for HCC.

FDX1 inhibits thyroid cancer malignant progression by inducing cuprotosis

Cuprotosis is a recently identified cell death form that caused by intracellular copper accumulation and regulated by FDX1. This work aimed to explore the role of cuprotosis and the pivotal regulatory gene FDX1 in thyroid cancer development. We observed that expression of FDX1 in tumor section was notably lower than that in non-tumor sections in clinical samples. Induction of cuprotosis by elesclomol (ES) significantly repressed the in vitro and in vivo growth of thyroid cancer cells, simultaneously elevated Cu level and expression of FDX1, whereas depletion of FDX1 abolished these effects. Knockdown of FDX1 decreased the lipoylation level of DLAT and DLST in thyroid cancer cells, alleviated cuprotosis-induced cell death, simultaneously upregulated the levels of PA and α-KG. These findings demonstrated that FDX1 promotes the cuprotosis of thyroid cancer cells via regulating the lipoylation of DLAT.

Exploration of cuprotosis-related genes for predicting prognosis and immunological characteristics in acute myeloid leukaemia based on genome and transcriptome

BACKGROUND

Acute myeloid leukemia (AML) is a common hematologic malignancy with a generally unfavorable prognosis. Cuprotosis as a new form of programmed cell death has been shown to play an important role in tumorigenesis and progression; However, the relationship between cuprotosis and the prognosis of AML patients remains unclear.

METHODS

Transcriptomic and genomics data, along with clinical information, were obtained from the TCGA and GEO databases. Especially, unsupervised clustering and machining learning were used to identify molecular subtypes and cuprotosis-related risk scores respectively. Kaplan-Meier analysis, univariate and multivariate Cox regression, and Receiver Operator Characteristic curve (ROC) were performed to assess the prognosis based on cuprotosis-related genes (CRGs). Moreover, multiple algorithms were used to evaluate immunological heterogeneity among patients with different risk scores. For in vitro analysis, the expression of genes involved in CRGs was detected by Quantitative Reverse Transcription Polymerase (qRT-PCR) in AML patients.

RESULTS

Transcriptomic and genome data indicated the immense heterogeneity in the CRGs landscape of normal and tumor samples. Cuprotosis subtype A and cuprotosis regulatory subtype B in the genomics map and biological characteristics were significantly different from the other groups. Furthermore, these two subtypes had lower risk scores and longer survival times compared to other groups. Cox analyses indicated that risk score was an independent prognostic factor for AML patients. In addition, our risk score could be an indicator of survival outcomes in immunotherapy datasets.

CONCLUSIONS

Our study demonstrates the potential of CRGs in guiding the prognosis, treatment, and immunological characteristics of AML patients.

Confirmation of the predictive function of cuproptosis-related gene FDX1 in clear cell renal carcinoma using qRT-PCR and western blotting

BACKGROUND

Cuproptosis is a novel cell death mechanism, and FDX1 is a key gene associated with cuproptosis. However, it is unclear whether FDX1 has prognostic and immunotherapeutic value for clear cell renal carcinoma (ccRCC).

METHODS

Data on FDX1 expression in ccRCC were extracted from various databases and validated using qRT-PCR and western blotting. Moreover, the survival prognosis, clinical features, methylation, and biological functions of FDX1 were evaluated, and the tumor immune dysfunction and exclusion (TIDE) score was used to explore the immunotherapy response to FDX1 in ccRCC.

RESULTS

The expression of FDX1 in ccRCC tissues was significantly lower than that in normal tissues, as validated by qRT-PCR and western blotting of patient samples (P < 0.01). Moreover, low FDX1 expression was related to shorter survival time and high immune activation, as indicated by alterations in the tumor mutational burden and tumor microenvironment, stronger immune cell infiltration and immunosuppression point expression, and a higher TIDE score.

CONCLUSIONS

FDX1 could serve as a novel and accessible biomarker for predicting survival prognosis, tumor immune landscape, and immune responses in ccRCC.

A novel cuproptosis-related lncRNAs signature predicts prognosis in bladder cancer

This study constructed a novel cuproptosis-related lncRNAs signature to predict the prognosis of BLCA patients. The Cancer Genome Atlas (TCGA) database was used to retrieve the RNA-seq data together with the relevant clinical information. The cuproptosis-related genes were first discovered. The cuproptosis-related lncRNAs were then acquired by univariate, the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to create a predictive signature. An eight cuproptosis-related lncRNAs (AC005261.1, AC008074.2, AC021321.1, AL024508.2, AL354919.2, ARHGAP5-AS1, LINC01106, LINC02446) predictive signature was created. Compared with the low-risk group, the prognosis was poorer for the high-risk group. The signature served as an independent overall survival (OS) predictor. Receiver operating characteristic (ROC) curve indicated that the signature demonstrated superior predictive ability, as evidenced by the area under the curve (AUC) of 0.782 than the clinicopathological variables. When we performed a subgroup analysis of the different variables, the high-risk group's OS for BLCA patients was lower than that of the low-risk group's patients. Gene Set Enrichment Analysis (GSEA) showed that high-risk groups were clearly enriched in many immune-related biological processes and tumor-related signaling pathways. Single sample gene set enrichment analysis (ssGSEA) revealed that the immune infiltration level was different between the two groups. Finally, quantitative RT-PCR showed that AC005261.1, AC021321.1, AL024508.2, LINC02446 and LINC01106 were lowly expressed in tumor cells, while ARHGAP5-AS1 showed the opposite trend. In summary, the predictive signature can independently predict the prognosis and provide clinical treatment guidance for BLCA patients.

Construction and validation of a novel cuproptosis-mitochondrion prognostic model related with tumor immunity in osteosarcoma

BACKGROUND

The purpose of this study was to develop a new prognostic model for osteosarcoma based on cuproptosis-mitochondrion genes.

MATERIALS AND METHODS

The data of osteosarcoma were obtained from TARGET database. By using Cox regression and LASSO regression analysis, a novel risk score was constructed based on cuproptosis-mitochondrion genes. Kaplan-Meier, ROC curve and independent prognostic analyses were performed to validate the risk score in GSE21257 dataset. Then, a predictive nomogram was constructed and further validated by calibration plot, C-index and ROC curve. Based on the risk score, all patients were divided into high-risk and low-risk group. GO and KEGG enrichment, immune correlation and drug sensitivity analyses were performed between groups. Real-time quantitative PCR verified the expression of cuproptosis-mitochondrion prognostic model genes in osteosarcoma. And we explored the function of FDX1 in osteosarcoma by western blotting, CCK8, colony formation assay, wound healing assay and transwell assays.

RESULTS

A total of six cuproptosis-mitochondrion genes (FDX1, COX11, MFN2, TOMM20, NDUFB9 and ATP6V1E1) were identified. A novel risk score and associated prognostic nomogram were constructed with high clinical application value. Strong differences in function enrichment and tumor immune microenvironment were shown between groups. Besides, the correlation of cuproptosis-mitochondrion genes and drug sensitivity were revealed to search for potential therapeutic target. The expression of FDX1, COX11, MFN2, TOMM20 and NDUFB9 at mRNA level was elevated in osteosarcoma cells compared with normal osteoblast hFOB1.19. The mRNA expression level of ATP6V1E1 was decreased in osteosarcoma. Compared with hFOB1.19, western blotting revealed that the expression of FDX1 was significantly elevated in osteosarcoma cells. Functional experiments indicated that FDX1 mainly promoted the migration of osteosarcoma rather than proliferation.

CONCLUSIONS

We developed a novel prognostic model of osteosarcoma based on cuproptosis-mitochondrion genes, which provided great guidance in survival prediction and individualized treatment decision making for patients with osteosarcoma.

FDX1 serves as a prognostic biomarker and promotes glioma progression by regulating the immune response

The present study investigates the prognostic value of the FDX1 gene and its association with immune infiltration in gliomas. Gene expression profiles and corresponding clinical parameters of glioma patients were obtained from the Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. In vitro experiments were also performed to validate its impact on malignant phenotypes of glioma cells. Kaplan-Meier analysis demonstrated that high FDX1 expression was associated with poor prognosis in glioma. Function and pathway enrichment for FDX1 predominantly demonstrated immunomodulatory function. In addition, the high-FDX1 expression group had higher Estimation of Stromal and Immune cells in malignant tumor tissues using Expression data, stromal, and immune scores (p<0.001). On evaluation of immunotherapy response, TIDE and dysfunction scores were higher in the low-FDX1 group, while the exclusion score demonstrated an opposite trend. In vitro tests showed that FDX1 silencing-induced inhibition of cell invasion and migration inactivated the nucleotide oligomerization domain (NOD)-like receptor signaling pathway by regulating PD-L1 expression. Notably, NOD1 expression was reversed in FDX1-knockdown cells after treatment with NOD1 agonists. In conclusion, FDX1 may play an important role in the diagnosis and treatment of gliomas. Regulating its expression may therefore help improve immunotherapy for these tumors.

Tumor cuproptosis and immune infiltration improve survival of patients with hepatocellular carcinoma with a high expression of ferredoxin 1

Background

Cuproptosis is a novel cell death pathway dependent on cellular copper ions and ferredoxin 1 (FDX1). Hepatocellular carcinoma (HCC) is derived from healthy liver as a central organ for copper metabolism. It remains no conclusive evidence whether cuproptosis is involved in survival improvement of patients with HCC.

Method

A 365-liver hepatocellular carcinoma (LIHC) cohort with RNA sequencing data and paired clinical and survival information was obtained from the The Cancer Genome Atlas (TCGA) dataset. A retrospective cohort of 57 patients with HCC with stages I/II/III was collected by Zhuhai People's Hospital from August 2016 to January 2022. Low- or high-FDX1 groups were divided according to the median value of FDX1 expression. Cibersort, single-sample gene set enrichment analysis, and multiplex immunohistochemistry analyzed immune infiltration in LIHC and HCC cohorts. Cell proliferation and migration of HCC tissues and hepatic cancer cell lines were evaluated using the Cell Counting Kit-8. Quantitative real-time PCR and RNA interference measured and downregulated FDX1 expression. Statistical analysis was conducted by R and GraphPad Prism software.

Results

High FDX1 expression significantly enhanced survival of patients with LIHC from the TCGA dataset, which was also demonstrated through a retrospective cohort with 57 HCC cases. Immune infiltration was different between the low- and high-FDX1 expression groups. Natural killer cells, macrophages, and B cells were significantly enhanced, and PD-1 expression was low in the high-FDX1 tumor tissues. Meanwhile, we found that a high expression of FDX1 decreased cell viability in HCC samples. HepG2 cells with FDX1 expression are sensitive to Cu²⁺, and interference of FDX1 promoted proliferation and migration of tumor cells. The consistent results were also demonstrated in Hep3B cells.

Conclusion

This study reveals that cuproptosis and tumor immune microenvironment were together involved in improvement of survival in patients with HCC with a high expression of FDX1.

A Novel Oncogenic Role of FDX1 in Human Melanoma Related to PD-L1 Immune Checkpoint

The aim of this study was to evaluate the association between Ferredoxin 1 (FDX1) expression and the prognostic survival of tumor patients and predict the efficacy of immunotherapy response to antitumor drug sensitivity. FDX1 plays an oncogenic role in thirty-three types of tumors, based on TCGA and GEO databases, and further experimental validation in vitro was provided through multiple cell lines. FDX1 was expressed highly in multiple types of cancer and differently linked to the survival prognosis of tumorous patients. A high phosphorylation level was correlated with the FDX1 site of S177 in lung cancer. FDX1 exhibited a significant association with infiltrated cancer-associated fibroblasts and CD8⁺ T cells. Moreover, FDX1 demonstrated correlations with immune and molecular subtypes, as well as functional enrichments in GO/KEGG pathways. Additionally, FDX1 displayed relationships with the tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and RNA and DNA synthesis (RNAss/DNAss) within the tumor microenvironment. Notably, FDX1 exhibited a strong connection with immune checkpoint genes in the co-expression network. The validity of these findings was further confirmed through Western blotting, RT-qPCR, and flow cytometry experiments conducted on WM115 and A375 tumor cells. Elevated FDX1 expression has been linked to the enhanced effectiveness of PD-L1 blockade immunotherapy in melanoma, as observed in the GSE22155 and GSE172320 cohorts. Autodocking simulations have suggested that FDX1 may influence drug resistance by affecting the binding sites of antitumor drugs. Collectively, these findings propose that FDX1 could serve as a novel and valuable biomarker and represent an immunotherapeutic target for augmenting immune responses in various human cancers when used in combination with immune checkpoint inhibitors.

A Deep Learning Approach for Prognostic Evaluation of Lung Adenocarcinoma Based on Cuproptosis-Related Genes

Lung adenocarcinoma represents a significant global health challenge. Despite advances in diagnosis and treatment, the prognosis remains poor for many patients. In this study, we aimed to identify cuproptosis-related genes and to develop a deep neural network model to predict the prognosis of lung adenocarcinoma. We screened differentially expressed genes from The Cancer Genome Atlas data through differential analysis of cuproptosis-related genes. We then used this information to establish a prognostic model using a deep neural network, which we validated using data from the Gene Expression Omnibus. Our deep neural network model incorporated nine cuproptosis-related genes and achieved an area under the curve of 0.732 in the training set and 0.646 in the validation set. The model effectively distinguished between distinct risk groups, as evidenced by significant differences in survival curves (p < 0.001), and demonstrated significant independence as a standalone prognostic predictor (p < 0.001). Functional analysis revealed differences in cellular pathways, the immune microenvironment, and tumor mutation burden between the risk groups. Furthermore, our model provided personalized survival probability predictions with a concordance index of 0.795 and identified the drug candidate BMS-754807 as a potentially sensitive treatment option for lung adenocarcinoma. In summary, we presented a deep neural network prognostic model for lung adenocarcinoma, based on nine cuproptosis-related genes, which offers independent prognostic capabilities. This model can be used for personalized predictions of patient survival and the identification of potential therapeutic agents for lung adenocarcinoma, which may ultimately improve patient outcomes.

Prognostic and immunological role of FDX1 in pan-cancer: an in-silico analysis

Previous research has demonstrated that ferredoxin 1 (FDX1) contributes to the accumulation of toxic lipoylated dihydrolipoamide S-acetyltransferase (DLAT) and results in cuproptotic cell death. However, the role that FDX1 plays in human cancer prognosis and immunology is still not well understood. The original data was obtained from TCGA and GEO databases and integrated using R 4.1.0. The TIMER2.0, GEPIA, and BioGPS databases were used to explore FDX1 expression. The impact of FDX1 on prognosis was analyzed using the GEPIA and Kaplan-Meier Plotter databases. External validation will be performed using the PrognoScan database. FDX1 expression in different immune and molecular subtypes of human cancers was evaluated using the TISIDB database. The correlation between FDX1 expression and immune checkpoints (ICP), microsatellite instability (MSI), and tumor mutational burden (TMB) in human cancers was analyzed using R 4.1.0. The TIMER2.0 and GEPIA databases were used to study the relationship between FDX1 expression and tumor-infiltrating immune cells. With the c-BioPortal database, we investigated the genomic alterations of FDX1. Pathway analysis and assessment of the sensitivity potential of FDX1-related drugs were also performed. Using the UALCAN database, we analyzed the differential expression of FDX1 in KIRC (kidney renal clear cell carcinoma) with different clinical features. Coexpression networks of FDX1 were analyzed using LinkedOmics. In general, FDX1 was expressed differently in different types of cancer in humans. Expression of FDX1 was strongly correlated with patient prognosis, ICP, MSI, and TMB. FDX1 was also participated in immune regulation and the tumor microenvironment. Coexpression networks of FDX1 were primarily involved in oxidative phosphorylation regulation. Pathway analysis revealed that the expression of FDX1 was correlated to cancer-related and immune-related pathways. FDX1 has the potential to serve as a biomarker for pan-cancer prognosis and immunology, as well as a novel target for tumor therapy.

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.

Ferredoxin 1 regulates granulosa cell apoptosis and autophagy in polycystic ovary syndrome

Polycystic ovary syndrome (PCOS), a common reproductive endocrine disorder in women of reproductive age, causes anovulatory infertility. Increased apoptosis of granulosa cells has been identified as one of the key factors contributing to abnormal follicular development. Ferredoxin 1 (FDX1) encodes a small ferredoxin that is involved in the reduction in mitochondrial cytochromes and the synthesis of various steroid hormones and has the potential to influence the function of granulosa cells. In the present study, we aimed to determine the relationship between FDX1 and follicular granulosa cell function. To this end, we investigated the difference between FDX1 expression in the granulosa cells of 50 patients with PCOS and that of the controls. Furthermore, we sought to elucidate the role and mechanism of FDX1 in PCOS granulosa cells by establishing a mouse PCOS model with dehydroepiandrosterone and KGN (a steroidogenic human granulosa cell-like tumor cell line). The results indicated significant up-regulation of FDX1 in the granulosa cells after androgen stimulation. Knockdown of FDX1 promoted the proliferation of KGN and inhibited apoptosis. Moreover, FDX1 could regulate autophagy by influencing the autophagy proteins ATG3 and ATG7. Our results demonstrated that FDX1 plays a critical role in female folliculogenesis by mediating apoptosis, autophagy, and proliferation. Therefore, FDX1 may be a potential prognostic factor for female infertility.

Identification of cuproptosis-based molecular subtypes, construction of prognostic signature and characterization of immune landscape in colon cancer

Background

Cuproptosis is a newly discovered form of cell death induced by targeting lipoacylated proteins involved in the tricarboxylic acid cycle. However, the roles of cuproptosis-related genes (CRGs) in the clinical outcomes and immune landscape of colon cancer remain unknown.

Methods

We performed bioinformatics analysis of the expression data of 13 CRGs identified from a previous study and clinical information of patients with colon cancer obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Colon cancer cases were divided into two CRG clusters and prognosis-related differentially expressed genes. Patient data were separated into three corresponding distinct gene clusters, and the relationships between the risk score, patient prognosis, and immune landscape were analyzed. The identified molecular subtypes correlated with patient survival, immune cells, and immune functions. A prognostic signature based on five genes was identified, and the patients were divided into high- and low-risk groups based on the calculated risk score. A nomogram model for predicting patient survival was developed based on the risk score and other clinical features.

Results

The high-risk group showed a worse prognosis, and the risk score was related to immune cell abundance, microsatellite instability, cancer stem cell index, checkpoint expression, immune escape, and response to chemotherapeutic drugs and immunotherapy. Findings related to the risk score were validated in the imvigor210 cohort of patients with metastatic urothelial cancer treated with anti-programmed cell death ligand 1.

Conclusion

We demonstrated the potential of cuproptosis-based molecular subtypes and prognostic signatures for predicting patient survival and the tumor microenvironment in colon cancer. Our findings may improve the understanding of the role of cuproptosis in colon cancer and lead to the development of more effective treatment strategies.

A novel cuproptosis-related gene signature to predict prognosis in Glioma

Glioma is primary brain tumour with a poor prognosis. Metabolic reprogramming is a hallmark of glioma, and is critical in the development of antiglioma agents and glioma therapy. Cuproptosis is a novel form of cell death mediated by protein lipidation and highly associated with mitochondrial metabolism. However, the clinical impact of cuproptosis-related genes (CRGs) in glioma remains largely unknown. The purpose of this study is to create a new CRGs signature that can be used to predict survival and immunotherapy in glioma patients. LASSO regression analysis was applied to establish prognostic gene signatures. Furthermore, a CRGs signature-based nomogram was developed and demonstrated good predictive potential. We also analyzed the relationship of CRGs and immune infiltration and the correlation with the pathological grade of glioma. Finally, we explored the miRNA that may regulate cuproptosis-related gene FDX1. We found that miR-606 was markedly downregulated in GBM, overexpression of miR-606 can significantly inhibit aerobic glycolysis and proliferation of GBM cells. FDX1 was upregulated in GBM, knockdown of FDX1 significantly inhibit aerobic glycolysis and proliferation of GBM cells. And luciferase assay was used to verified that miR-606 binds to and regulates FDX1 mRNA. These results provide a basis for further exploring the biological mechanisms of cuproptosis. This study may provide new potential therapeutic perspectives for patients with glioma.

Ferroptosis, necroptosis and cuproptosis: Novel forms of regulated cell death in diabetic cardiomyopathy

Diabetes is a common chronic metabolic disease, and its incidence continues to increase year after year. Diabetic patients mainly die from various complications, with the most common being diabetic cardiomyopathy. However, the detection rate of diabetic cardiomyopathy is low in clinical practice, and targeted treatment is lacking. Recently, a large number of studies have confirmed that myocardial cell death in diabetic cardiomyopathy involves pyroptosis, apoptosis, necrosis, ferroptosis, necroptosis, cuproptosis, cellular burial, and other processes. Most importantly, numerous animal studies have shown that the onset and progression of diabetic cardiomyopathy can be mitigated by inhibiting these regulatory cell death processes, such as by utilizing inhibitors, chelators, or genetic manipulation. Therefore, we review the role of ferroptosis, necroptosis, and cuproptosis, three novel forms of cell death in diabetic cardiomyopathy, searching for possible targets, and analyzing the corresponding therapeutic approaches to these targets.

Novel Cuproptosis-Related Gene Signature for Precise Identification of High-Risk Populations in Low-Grade Gliomas

Background

Patients with low-grade glioma (LGG) have wildly varying average lifespans. However, no effective way exists for identifying LGG patients at high risk. Cuproptosis is a recently described form of cell death associated with the abnormal aggregation of lipid acylated proteins. Few investigations have been conducted on cuproptosis-associated genes and LGG thus far. The purpose of this research is to establish a predictive model for cuproptosis-related genes in order to recognise LGG populations at high risk.

Methods

We analyzed 926 LGGs from 2 public datasets, all of which were RNA sequencing datasets. On the basis of immune scores, the LGG population was split into different risk categories with X-tile. LASSO and Cox regressions were employed to filter cuproptosis-associated genes and construct prediction models. The accuracy of the predictive models was measured by using TCGA internal validation set and the CGGA external validation set. In addition, LGG immune cell infiltration was viewed using CIBERSORT and ssGSEA algorithms and correlation analysis was done with cuproptosis-related genes. Finally, immune escape capacity in LGG low- and high-risk groups was evaluated using the TIDE method.

Results

The prediction model constructed by four cuproptosis-related genes was used to identify high-risk populations in LGG. It performed well in training and all validation sets (AUC values: 0.915, 0.894, and 0.774). Meanwhile, we found that FDX1 and ATP7A in the four cuproptosis-related genes were positively correlated with immune response, while GCSH and ATP7B were opposite. In addition, the high immune score group had a lower TIDE score, indicating that their immune escape capacity was weak.

Conclusion

High-risk individuals in LGG can be reliably identified by the model based on cuproptosis-related genes. Furthermore, cuproptosis is closely related to tumor immune microenvironment, which gives a novel approach to treating LGG.

An integrative analysis revealing cuproptosis-related lncRNAs signature as a novel prognostic biomarker in hepatocellular carcinoma

Background: Cuproptosis is a newly defined form of cell death, whether cuproptosis involved in hepatocellular carcinoma (HCC) remains elusive. Method: We obtained patients' RNA expression data and follow-up information from University of California Santa Cruz (UCSC) and The Cancer Genome Atlas (TCGA). We analyzed the mRNA level of Cuproptosis-related genes (CRGs) and performed univariate Cox analysis. Liver hepatocellular carcinoma (LIHC) was chosen for further investigation. Real-Time quantitative PCR (RT-qPCR), Western blotting (WB), Immunohistochemical (IHC), and Transwell assays were used to determine expression patterns and functions of CRGs in LIHC. Next, we identified CRGs-related lncRNAs (CRLs) and differentially expressed CRLs between HCC and normal cases. Univariate Cox analysis, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to construct the prognostic model. Univariate and multivariate Cox analysis was used to assess whether the risk model can act as an independent risk factor of overall survival duration. Different risk groups performed immune correlation analysis, tumor mutation burden (TMB), and Gene Set Enrichment Analysis (GSEA) analysis were performed in different risk groups. Finally, we assessed the performance of the predictive model in drug sensitivity. Results: CRGs expression levels have significant differences between tumor and normal tissues. High expression of Dihydrolipoamide S-Acetyltransferase (DLAT) correlated to metastasis of HCC cells and indicated poor prognosis for HCC patients. Our prognostic model consisted of four cuproptosis-related lncRNA (AC011476.3, AC026412.3, NRAV, MKLN1-AS). The prognostic model performed well in predicting survival rates. The results from Cox regression analysis suggested that risk score can serve as an independent prognostic element for survival durations. Survival analysis revealed that low risk patients have extended survival periods compared with those with high risk. The results of the immune analysis indicated that risk score has a positive correlation with B cell and CD4⁺ T cell Th2, while has a negative relationship with endothelial cell and hematopoietic cells. Besides, immune checkpoint genes have higher expression folds in the high-risk set than in the low-risk set. The high-risk group had higher rates of genetic mutation than the low-risk set while having a shorter survival time. GSEA revealed the signaling pathways enriched in the high-risk group were mostly immune-related, while metabolic-related pathways were enriched in the low-risk group. Drugs sensitivity analysis indicated that our model has the ability to predict the efficacy of clinical treatment. Conclusion: The Cuproptosis-related lncRNAs prognostic formula is a novel predictor of HCC patients' prognosis and drug sensitivity.

Pan-cancer integrated bioinformatics analysis reveals cuproptosis related gene FDX1 is a potential prognostic and immunotherapeutic biomarker for lower-grade gliomas

FDX1 participates in cuproptosis, a copper-dependent cell death mode, which might influence tumor progressions like ferroptosis and pyroptosis. However, the role of FDX1 in tumors remains to be explored. This study investigated FDX1 expression features, and correlations to prognosis, tumor stages, immune microenvironment, and cuproptosis from a pan-cancer perspective based on integrated bioinformatics. FDX1 mRNA and clinical data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Broad Institute Cancer Cell Line Encyclopedia (CCLE) databases. Differential expression of FDX1 in tumor stages was performed on GEPIA2.0. Cox proportional hazard regression and survival curve were used to analyze the prognostic value of FDX1. The relationships between FDX1 expression and immune infiltration, immune cells, immune checkpoints, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methyltransferase (DNMT) were explored. GSEA was utilized to find the biological function of FDX1 in LGG. Results showed that FDX1 was abnormally expressed in multiple tumor types and demonstrated variability in various tumor stages. Survival analysis revealed FDX1 predicted poor prognosis in glioma (GBMLGG), brain lower-grade glioma (LGG), and good prognosis in the pan-kidney cohort (KIPAN), and kidney renal clear cell carcinoma (KIRC). Immune correlation analysis suggested FDX1 showed positive correlations to StromalScore, ImmuneScore, ESTIMATEScore in LGG and negative correlation in KIRC. Additionally, positive correlations were observed between FDX1 and immune cells infiltration, immune checkpoints, tumor stemness, homologous recombination deficiency (HRD), and TMB in LGG in the pan-cancer analysis. Validation with CGGA suggested prognostic value and immune correlation of FDX1 in LGG. Specifically, high expression of FDX1 was accompanied by high expression of immune checkpoints such as CD276 (B7-H3), CD274 (PD-L1), PDCD1LG2 (PD-L2), CTLA4, and HAVCR2. These findings illustrated that FDX1 might be considered a potential poor prognosis biomarker and immunotherapy predictor in LGG.

Pan-cancer analyses reveal molecular and clinical characteristics of cuproptosis regulators

Imbalance in copper homeostasis can be lethal. A recent study found that excess copper induces cell death in a way that has never been characterized before, which is dependent on mitochondrial stress and is referred to as "cuproptosis." The role of cuproptosis in tumors has not yet been elucidated. In this study, we revealed the complex and important roles of cuproptosis regulators and cuproptosis activity in tumors via a comprehensive analysis of multiomics data from more than 10,000 samples of 33 tumor types. We found that the cyclin-dependent kinase inhibitor 2A is the most frequently altered cuproptosis regulator, and the cuproptosis regulator expression is dysregulated in various tumors. Additionally, we developed a cuproptosis activity score to reflect the overall cuproptosis level. On the basis of the expression levels of cuproptosis regulators, tumors can be divided into two clusters with different cuproptosis activities and survival outcomes. Importantly, cuproptosis activity was found to be associated with the prognosis of multiple tumors and multiple tumor-related pathways, including fatty acid metabolism and remodeling of the tumor microenvironment. Furthermore, cuproptosis increased the sensitivity to multiple drugs and exhibited potential to predict the outcome of immunotherapy. We also comprehensively identified cuproptosis-related microRNAs, long noncoding RNAs, and transcription factors. We provided the code corresponding to the results of this study in GitHub (https://github.com/Changwuuu/Cuproptosis-pancancer.git) for reference. In summary, this study reveals important molecular and clinical characteristics of cuproptosis regulators and cuproptosis activity in tumors, and suggests the use of cuproptosis as a promising tumor therapeutic approach. This study provides an important reference point for future cuproptosis-related research.

A Novel Cuprotosis-Related lncRNA Signature Effectively Predicts Prognosis in Glioma Patients

Cuprotosis is a novel and different cell death mechanism from the existing known ones that can be used to explore new approaches to treating cancer. Just like ferroptosis and pyroptosis, cuprotosis-related genes regulate various types of tumorigenesis, invasion, and metastasis. However, the relationship between cuprotosis-related long non-coding RNA (cuprotosis-related lncRNA) in glioma development and prognosis has not been investigated. We obtained relevant data from the Genotype-Tissue Expression (GTEx), Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and published articles. First, we identified 365 cuprotosis-related lncRNAs based on 10 cuprotosis-related differential genes (|R²|> 0.4, p < 0.001). Then using Lasso and Cox regression analysis methods, 12 prognostic cuprotosis-related lncRNAs were obtained and constructed the CuLncSigi risk score formula. Our next step was to divide the tumor gliomas into two groups (high risk and low risk) based on the median risk score, and we found that patients in the high-risk group had a significantly worse prognosis. We used internal and external validation methods to simultaneously analyze and validate that the risk score model has good predictive power for patients with glioma. Next, we also performed enrichment analyses such as GSEA and aaGSEA and evaluated the relationship between immune-related drugs and tumor treatment. In conclusion, we successfully constructed a formula of cuprotosis-related lncRNAs with a powerful predictive function. More importantly, our study paves the way for exploring cuprotosis mechanisms in glioma occurrence and development and helps to find new relevant biomarkers for glioma early identification and diagnosis and to investigate new therapeutic approaches.

Guiding Drug Repositioning for Cancers Based on Drug Similarity Networks

Drug repositioning aims to discover novel clinical benefits of existing drugs, is an effective way to develop drugs for complex diseases such as cancer and may facilitate the process of traditional drug development. Meanwhile, network-based computational biology approaches, which allow the integration of information from different aspects to understand the relationships between biomolecules, has been successfully applied to drug repurposing. In this work, we developed a new strategy for network-based drug repositioning against cancer. Combining the mechanism of action and clinical efficacy of the drugs, a cancer-related drug similarity network was constructed, and the correlation score of each drug with a specific cancer was quantified. The top 5% of scoring drugs were reviewed for stability and druggable potential to identify potential repositionable drugs. Of the 11 potentially repurposable drugs for non-small cell lung cancer (NSCLC), 10 were confirmed by clinical trial articles and databases. The targets of these drugs were significantly enriched in cancer-related pathways and significantly associated with the prognosis of NSCLC. In light of the successful application of our approach to colorectal cancer as well, it provides an effective clue and valuable perspective for drug repurposing in cancer.

Cuproptosis-related gene FDX1 as a prognostic biomarker for kidney renal clear cell carcinoma correlates with immune checkpoints and immune cell infiltration

Background: Kidney renal clear cell carcinoma (KIRC) is not sensitive to radiotherapy and chemotherapy, and only some KIRC patients can benefit from immunotherapy and targeted therapy. Cuproptosis is a new mechanism of cell death, which is closely related to tumor progression, prognosis and immunity. The identification of prognostic markers related to cuproptosis in KIRC may provide targets for treatment and improve the prognosis of KIRC patients. Methods: Ten cuproptosis-related genes were analyzed for differential expression in KIRC-TCGA and a prognostic model was constructed. Nomogram diagnostic model was used to screen independent prognostic molecules. The screened molecules were verified in multiple datasets (GSE36895 and GSE53757), and in KIRC tumor tissues by RT-PCR and immunohistochemistry (IHC). Clinical correlation of cuproptosis-related independent prognostic molecules was analyzed. According to the molecular expression, the two groups were divided into high and low expression groups, and the differences of immune checkpoint and tumor infiltrating lymphocytes (TILs) between the two groups were compared by EPIC algorithm. The potential Immune checkpoint blocking (ICB) response of high and low expression groups was predicted by the "TIDE" algorithm. Results: FDX1 and DLAT were protective factors, while CDKN2A was a risk factor. FDX1 was an independent prognostic molecule by Nomogram, and low expressed in tumor tissues compared with adjacent tissues (p < 0.05). FDX1 was positively correlated with CD274, HAVCR2, PDCD1LG2, and negatively correlated with CTLA4, LAG3, and PDCD1. The TIDE score of low-FDX1 group was higher than that of high-FDX1 group. The abundance of CD4⁺ T cells, CD8⁺ T cells and Endothelial cells in FDX1-low group was lower than that in FDX1-high group (p < 0.05). Conclusion: FDX1, as a key cuproptosis-related gene, was also an independent prognostic molecule of KIRC. FDX1 might become an interesting biomarker and potential therapeutic target for KIRC.

Copper Death Inducer, FDX1, as a Prognostic Biomarker Reshaping Tumor Immunity in Clear Cell Renal Cell Carcinoma

BACKGROUND

Progress in the diagnosis and treatment of clear cell renal cell carcinoma (ccRCC) has significantly prolonged patient survival. However, ccRCC displays an extreme heterogenous characteristic and metastatic tendency, which limit the benefit of targeted or immune therapy. Thus, identifying novel biomarkers and therapeutic targets for ccRCC is of great importance.

METHOD

Pan cancer datasets, including the expression profile, DNA methylation, copy number variation, and single nucleic variation, were introduced to decode the aberrance of copper death regulators (CDRs). Then, FDX1 was systematically analyzed in ccRCC to evaluate its impact on clinical characteristics, prognosis, biological function, immune infiltration, and therapy response. Finally, in vivo experiments were utilized to decipher FDX1 in ccRCC malignancy and its role in tumor immunity.

RESULT

Copper death regulators were identified at the pancancer level, especially in ccRCC. FDX1 played a protective role in ccRCC, and its expression level was significantly decreased in tumor tissues, which might be regulated via CNV events. At the molecular mechanism level, FDX1 positively regulated fatty acid metabolism and oxidative phosphorylation. In addition, FDX1 overexpression restrained ccRCC cell line malignancy and enhanced tumor immunity by increasing the secretion levels of IL2 and TNFγ.

CONCLUSIONS

Our research illustrated the role of FDX1 in ccRCC patients' clinical outcomes and its impact on tumor immunity, which could be treated as a promising target for ccRCC patients.

Cuproptosis regulatory genes greatly contribute to clinical assessments of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common abdominal cancer with dissatisfactory therapeutic effects. The discovery of cuproptosis lights on new approach for cancer treatment and assessment. So far, there is extremely limited research investigating the roles of cuproptosis-related (CR) genes in cancers.

METHODS

A novel CR risk signature was constructed using the Lasso regression analysis. Its prognostic value was assessed via a series of survival analyses and validated in three GEO cohorts. The effects of CR risk signature on tumor immune microenvironment (TIM) were explored through CIBERSORT, ESTIMATE, and ssGSEA algorithms. Using GESA, we investigated its impacts on various metabolism process. The somatic mutation features of CR signature genes were also explored via cBioPortal database. Using tumor mutation burden, expressions of immune checkpoints, TIDE score, IMvigor 210 cohort, and GSE109211 dataset, we explored the potential associations of CR risk score with the efficacy of immune checkpoint inhibitors (ICIs) and sorafenib. Finally, the biofunctions of DLAT in HCC cells were ascertained through qPCR, immunohistochemistry, colony formation, and Transwell assays.

RESULTS

FDX1, DLAT, CDKN2A and GLS constituted the CR risk signature. CR risk signature possessed high prognostic value and was also applicable to three validation cohorts. Meanwhile, it could improve the accuracy and clinical making-decision benefit of traditional prognostic model. Moreover, high CR risk was indicative of unfavorable anti-tumor immune response and active metabolisms of glycolysis and nucleotide. As for therapeutic correlation, CR risk score was a potential biomarker for predicting the efficacy of ICIs and sorafenib. Through qPCR and immunohistochemistry detection in clinical samples, we reconfirmed DLAT was significantly upregulated in HCC samples. Overexpression of DLAT could promote the proliferation, migration, and invasion of HepG2 and HuH-7 cells.

CONCLUSIONS

The novel CR risk signature greatly contributed to the clinical assessment of HCC. Cuproptosis regulatory gene DLAT possessed cancer-promoting capacities and was expected to be a promising therapeutic target for HCC.

High expression of cuproptosis-related gene FDX1 in relation to good prognosis and immune cells infiltration in colon adenocarcinoma (COAD)

BACKGROUND

Cuproptosis induced by FDX1 is a newly discovered mechanism regulating cell death. However, the role of FDX1 in the pathogenesis of colon adenocarcinoma (COAD) remains to be studied.

METHODS

FDX1 expression was analyzed with The Cancer Genome Atlas (TCGA) database and Human Protein Atlas (HPA) database. Association between FDX1 expression and COAD prognosis was investigated via the Kaplan-Meier (KM) survival curve. The differentially expressed genes (DEGs) of FDX1 were screened with R packages and the PPI were constructed via STRING database. Cytoscape software was used to detect the most profound modules in the PPIs network. CancerSEA database was used to analyze the effect of FDX1 expression levels on different functional status of COAD cells. The relationship between FDX1 expression and immune infiltration of COAD was analyzed by TIMER2.0 database. The COAD patients with high expression of FDX1 by Western blot, and the levels of immune infiltration were measured by flow cytometry.

RESULTS

FDX1 was low expressed in most cancers, such as BRCA, KICH, and COAD. The overall survival (OS) and disease-specific survival (DSS) of COAD with high FDX1 expression were better than that of the low expression group. GO-KEGG enrichment analysis revealed that FDX1 and its co-expressed genes played an important role in the pathogenesis of COAD. Moreover, FDX1 expression in COAD were positively associated with "quiescence" and "inflammation" but negatively correlated with "invasion". FDX1 expression was positively correlated with infiltration levels of CD8⁺ T cells, NK cells, and neutrophils. Oppositely, FDX1 expression was negatively correlated with that of CD4⁺ T cells and cancer-associated fibroblasts (CAFs). Finally, 6 COAD patients with high expression of FDX1 were screened, and the proportion of CD8⁺ T cells in cancer tissues of these patients was significantly higher than that in paracancerous, while the CD4⁺ T cells presented the opposite pattern.

CONCLUSION

FDX1 plays a role in inducing cuproptosis and modulating tumor immunity, which could be considered as potential therapeutic targets in COAD.

The implications and prospect of cuproptosis-related genes and copper transporters in cancer progression

Currently, cancer has become one of the major public health problems worldwide. Apoptosis is an important anti-cancer defense mechanism, which is used in the development of targeted drugs. Because cancer cells have endogenous resistance to apoptosis,the clinical efficacy of related drugs is not ideal. Therefore, non-apoptotic regulatory cell death may bring new therapeutic strategies for cancer treatment. Cuproptosis is a novel form of regulatory cell death which is copper-dependent, regulated and distinct from other known cell death regulatory mechanisms. FDX1,LIAS,and DLAT named cuproptosis-related genes play an essential role in regulating cuproptosis. Meanwhile, abnormal accumulation of copper can be observed in various malignant tumors. The correlation has been established between elevated copper levels in serum and tissues and the progression of several cancers. Copper transporters, CTR1 and Copper-transporting ATPases(ATP7A and ATP7B), are mainly involved in regulating the dynamic balance of copper concentration to maintain copper homeostasis. Thus,cuproptosis-related genes and copper transporters will be the focus of cancer research in future. This review elaborated the basic functions of cuproptosis-related genes and copper transporters by retrievalling PubMed. And then we analyzed their potential relationship with cancer aiming to provide theoretical support and reference in cancer progression, diagnosis and treatment for future study.

Consensus Clustering and Survival-Related Genes of Cuproptosis in Cutaneous Melanoma

As a highly malignant tumor, the morbidity and mortality of cutaneous melanoma (CM) are increasing year by year. A novel type of cell death connected to mitochondrial metabolism is called cuproptosis. Cuproptosis regulates tumor biological behavior. Thus, genes controlling cuproptosis could be a promising candidate bioindicator for cancer therapy. Datasets of CM patients were obtained from the public database that includes clinical information and RNA-seq data. We divided CM patients into three different subgroups by unsupervised clustering method and explored the differences in functional pathways among the three subgroups by GSVA to prove the possible potential mechanism of copper death-related genes in the formation and development of CM. Secondly, we used differential analysis and Cox regression analysis to find the differential genes related to prognosis, constructed the CRG score, found the critical score for dividing high and low CRG score groups, and then analyzed the prognosis and immune infiltration of high and low CRG score groups. The results show a great correlation between OS and CRG scores. Compared with patients with high CRG scores, patients with low CRG scores have a significantly higher survival rate. In a word, copper sagging plays a certain role in the progress of CM.

Cuproptosis-Related MiR-21-5p/FDX1 Axis in Clear Cell Renal Cell Carcinoma and Its Potential Impact on Tumor Microenvironment

As a newly identified type of programmed cell death, cuproptosis may have an impact on cancer development, including clear cell renal cell carcinoma (ccRCC). Herein, we first noticed that the expression levels of cuproptosis regulators exhibited a tight correlation with the clinicopathological characteristics of ccRCC. The cuproptosis-sensitive sub-type (CSS), classified via consensus clustering analysis, harbored a higher overall survival rate compared to the cuproptosis-resistant sub-type (CRS), which may have resulted from the differential infiltration of immune cells. FDX1, the cuproptosis master regulator, was experimentally determined as a tumor suppressor in ccRCC cells by suppressing the cell growth and cell invasion of ACHN and OSRC-2 cells in a cuproptosis-dependent and -independent manner. The results from IHC staining also demonstrated that FDX1 expression was negatively correlated with ccRCC tumor initiation and progression. Furthermore, we identified the miR-21-5p/FDX1 axis in ccRCC and experimentally verified that miR-21-5p directly binds the 3'-UTR of FDX1 to mediate its degradation. Consequently, a miR-21-5p inhibitor suppressed the cell growth and cell invasion of ACHN and OSRC-2 cells, which could be compensated by FDX1 knockdown, reinforcing the functional linkage between miR-21-5p and FDX1 in ccRCC. Finally, we evaluated the ccRCC tumor microenvironment under the miR-21-5p/FDX1 axis and noted that this axis was strongly associated with the infiltration of immune cells such as CD4⁺ T cells, Treg cells, and macrophages, suggesting that this signaling axis may alter microenvironmental components to drive ccRCC progression. Overall, this study constructed the miR-21-5p/FDX1 axis in ccRCC and analyzed its potential impact on the tumor microenvironment, providing valuable insights to improve current ccRCC management.