Prognostic analysis of cuproptosis-related gene in triple-negative breast cancer

The molecular mechanism and therapeutic landscape of copper and cuproptosis in cancer

Copper, an essential micronutrient, plays significant roles in numerous biological functions. Recent studies have identified imbalances in copper homeostasis across various cancers, along with the emergence of cuproptosis, a novel copper-dependent form of cell death that is crucial for tumor suppression and therapeutic resistance. As a result, manipulating copper levels has garnered increasing interest as an innovative approach to cancer therapy. In this review, we first delineate copper homeostasis at both cellular and systemic levels, clarifying copper's protumorigenic and antitumorigenic functions in cancer. We then outline the key milestones and molecular mechanisms of cuproptosis, including both mitochondria-dependent and independent pathways. Next, we explore the roles of cuproptosis in cancer biology, as well as the interactions mediated by cuproptosis between cancer cells and the immune system. We also summarize emerging therapeutic opportunities targeting copper and discuss the clinical associations of cuproptosis-related genes. Finally, we examine potential biomarkers for cuproptosis and put forward the existing challenges and future prospects for leveraging cuproptosis in cancer therapy. Overall, this review enhances our understanding of the molecular mechanisms and therapeutic landscape of copper and cuproptosis in cancer, highlighting the potential of copper- or cuproptosis-based therapies for cancer treatment.

AKT1 Phosphorylates FDX1 to Promote Cuproptosis Resistance in Triple-Negative Breast Cancer

Cuproptosis, a recently defined copper-dependent cell death pathway, remains largely unexplored in tumor therapies, particularly in breast cancer. This study demonstrates that triple-negative breast cancer (TNBC) bears a relatively elevated copper levels and exhibits resistance to cuproptosis. Mechanistically, copper activates the AKT signaling pathway, which inhibits ferredoxin-1 (FDX1), a key regulator of cuproptosis. AKT1-mediated FDX1 phosphorylation not only abrogates FDX1-induced cuproptosis and aerobic respiration but also promotes glycolysis. Consequently, the combination of AKT1 inhibitors and the copper ionophores synergistically alleviate TNBC tumorigenesis both in vitro and in vivo. In summary, the findings reveal a crucial mechanism underlying TNBC resistance to cuproptosis and suggest a potential therapeutic approach for TNBC.

Construction of a novel five programmed cell death-related gene signature as a promising prognostic model for triple negative breast cancer

Background

Triple negative breast cancer (TNBC) is a more aggressive subtype of breast cancer that usually progresses rapidly, develops drug resistance, metastasis, and relapses, and remains a challenge for clinicians to treat. Programmed cell death (PCD), a conserved mechanism of cell suicide controlled by various pathways, contributed to carcinogenesis and cancer progression. Nevertheless, the prognostic significance of PCD-related genes in TNBC remains largely unclear, and more accurate prognostic models are urgently needed.

Methods

Gene expression profiles and clinical information of TNBC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to establish the PCD-related gene signature. Kaplan-Meier plotter, receiver operating characteristic curves, and nomogram were applied to validate the prognostic value of the gene signature. Gene set enrichment analysis was carried out to investigate the pathways and molecular functions.

Results

Five PCD-related genes including SEPTIN3, SCARB1, CHML, SYNM, and COL5A3 were identified to establish the PCD-related risk score for TNBC patients. Patients stratified into high-risk or low-risk group showed significantly different survival outcome, immune infiltration, and drug susceptibility. Kaplan-Meier and receiver operating characteristic curves showed a good performance for survival prediction in different cohorts. Gene set enrichment analysis revealed that the five-gene signature was associated with tumor metabolism, cancer cell proliferation, invasion and metastasis, and tumor microenvironment. Nomogram including the five-gene signature was established.

Conclusion

A novel five PCD-related gene signature and nomogram could be used for prognostic prediction in TNBC. The present work might offer useful insights in digging sensitive and effective biomarkers for TNBC prognosis prediction and establishing accurate prognostic model in clinical management.

Comprehensive analysis of prognosis and tumor immune microenvironment of cuproptosis-related gene CDKN2A in lung adenocarcinoma

BACKGROUND

Recent research has increasingly highlighted the significance of various forms of cell death in contributing to tumor heterogeneity and modulating anti-tumor immunity. However, the potential implications of cuproptosis-related genes (CRGs) in lung adenocarcinoma (LUAD) remains poorly explored.

METHODS

We conducted a comprehensive analysis of the expression profiles of 19 CRGs in LUAD based on The Cancer Genome Atlas (TCGA). Utilizing consensus clustering, we stratified the TCGA cohort into two distinct LUAD subtypes (Cluster 1 and Cluster 2). The expression of CDKN2A was further validated across multiple datasets, including TCGA, GEO, Cancer Cell Line Encyclopedia (CCLE), and the Human Protein Atlas (HPA). The prognostic value of the CDKN2A was evaluated through univariate, multivariate, and survival analyses. Gene set enrichment analysis (GSEA) was performed to elucidate the molecular mechanisms associated with the CDKN2A. Additionally, we assessed the levels of immune cell infiltration in LUAD using the CIBERSORT, ESTIMATE, and XCELL algorithms.

RESULTS

By systematically analyzing the genetic alterations of 19 CRGs in LUAD, we found 15 differentially expressed genes between LUAD and adjacent normal tissues. Subsequently, using the consensus clustering method, we classified LUAD patients into two molecular subtypes and cluster 2 had a poor prognosis. CDKN2A emerged as a key gene of interest, exhibiting elevated expression in LUAD and correlating with adverse patient outcomes. Moreover, immunoinfiltration analysis revealed differential levels of immune cell infiltration between the CDKN2A high and CDKN2A low expression groups.

CONCLUSIONS

Our findings indicate that CDKN2A may serve as an effective prognostic biomarker for LUAD and may offer valuable insights into potential immunotherapeutic strategies for these patients.

CLINICAL TRIAL NUMBER

Not applicable.

Unveiling the key mechanisms of FOLR2+ macrophage-mediated antitumor immunity in breast cancer using integrated single-cell RNA sequencing and bulk RNA sequencing

Breast cancer (BRCA) is a common malignant tumor, and its immune microenvironment plays a crucial role in disease progression. In this research, we utilized single-cell RNA sequencing and bulk RNA sequencing technologies, combined with in vivo and in vitro experiments, to thoroughly investigate the immunological functions and mechanisms of FOLR2+ macrophages in BRCA. Our findings demonstrate a significant enhancement in the interaction between FOLR2+ macrophages and CD8+ T cells within the tumor tissues of BRCA patients. FOLR2 is closely associated with T cell infiltration in the tumor microenvironment of BRCA patients, particularly with CD8+ T cells. By secreting CXCL9 and engaging with CXCR3, FOLR2+ macrophages can activate the functionality of CD8+ T cells, thereby promoting cancer cell apoptosis. Further animal experiments confirm that FOLR2+ macrophages activate CD8+ T cells through the CXCL9-CXCR3 axis, exhibiting an antitumor immunity effect in BRCA. FOLR2+ macrophages play a crucial role in antitumor immunity in BRCA through the CXCL9-CXCR3 axis.

Identification and characterization of cuproptosis related gene subtypes through multi-omics bioinformatics analysis in breast cancer

Cuproptosis, a newly suggested mechanism of controlled cellular demise, which has been extensively associated with aspects of occurrence and development in breast cancer. The aim of this study was to conduct a comprehensive multi-group bioinformatics analysis based on the expression of cuproptosis-related genes (CRGs) to identify novel breast cancer subtypes to guide clinical practice. We collected TCGA-BRCA and GSE42568 datasets to investigate the expression patterns of CRGs in breast cancer. Consensus cluster analysis was performed to identify distinct subtypes. Subsequently, an investigation was carried out to examine the disparities between CRGclusters through functional enrichment analysis. Finally, we examined microsatellite instability, tumor mutation burden, drug sensitivity, infiltration of immune cells and cancer cell stemness across different CRGclusters. We identified two subtypes, where CRGcluster S2 exhibits a poorer prognosis compared to CRGcluster S1. Moreover, CRGcluster S2 demonstrated lower immune infiltration scores, higher cancer cell stemness index, and increased tumor mutation burden relative to CRGcluster S1, with the most frequently mutated gene being ATP7A. Notably, breast cancer chemotherapy drugs such as docetaxel, doxorubicin, and paclitaxel exhibited reduced sensitivity towards CRGcluster S2 when compared to CRGcluster S1. We have identified two CRGclusters in breast cancer that could serve as potential therapeutic targets and warrant further investigation in clinical trial studies for breast cancer.

Cuproptosis: A new mechanism for anti-tumour therapy

As an indispensable trace metal element in the organism, copper acts as a key catalytic cofactor in a wide range of biological processes. Copper homeostasis disorders can be caused by either copper excess or deficiency, and copper homeostasis disorders will affect the normal physiological functions of cells and induce cell death through a variety of mechanisms, such as the emerging cuproptosis model. The imbalance of copper homeostasis will lead to the occurrence of cancer, and copper is a key factor in cell signalling, so copper is involved in the development of cancer by promoting cell proliferation, angiogenesis and metastasis, etc. The therapeutic role of Cuproptosis as a hotspot of research in cancer has also attracted much attention. Therefore, this paper comprehensively searches the literature to review the roles and mechanisms of Cuproptosis in the treatment of malignant tumours, aiming to provide new insights into the role and mechanism of Cuproptosis in anti-malignant tumour therapy and present novel ideas and methods.

Targeting the initiator to activate both ferroptosis and cuproptosis for breast cancer treatment: progress and possibility for clinical application

Breast cancer is the most commonly diagnosed cancer worldwide. Metal metabolism is pivotal for regulating cell fate and drug sensitivity in breast cancer. Iron and copper are essential metal ions critical for maintaining cellular function. The accumulation of iron and copper ions triggers distinct cell death pathways, known as ferroptosis and cuproptosis, respectively. Ferroptosis is characterized by iron-dependent lipid peroxidation, while cuproptosis involves copper-induced oxidative stress. They are increasingly recognized as promising targets for the development of anticancer drugs. Recently, compelling evidence demonstrated that the interplay between ferroptosis and cuproptosis plays a crucial role in regulating breast cancer progression. This review elucidates the converging pathways of ferroptosis and cuproptosis in breast cancer. Moreover, we examined the value of genes associated with ferroptosis and cuproptosis in the clinical diagnosis and treatment of breast cancer, mainly outlining the potential for a co-targeting approach. Lastly, we delve into the current challenges and limitations of this strategy. In general, this review offers an overview of the interaction between ferroptosis and cuproptosis in breast cancer, offering valuable perspectives for further research and clinical treatment.

Identification of cancer-associated fibroblast subtypes and prognostic model development in breast cancer: role of the RUNX1/SDC1 axis in promoting invasion and metastasis

In this study, we identified cancer-associated fibroblast (CAF) molecular subtypes and developed a CAF-based prognostic model for breast cancer (BRCA). The heterogeneity of cancer-associated fibroblasts (CAFs) and their significant involvement in the advancement of BRCA were discovered employing single-cell RNA sequencing. Notably, we discovered that the RUNX1/SDC1 axis enhances BRCA cell invasion and metastasis. RUNX1 transcriptionally upregulates SDC1, which facilitates extracellular matrix remodeling and promotes tumor cell migration. This finding highlights the vital contribution of CAFs to the tumor microenvironment and provides new potential targets for therapeutic intervention. The predictive model showcased remarkable precision in anticipating patient outcomes and could guide personalized treatment strategies.

Cuproptosis-related gene ATOX1 promotes MAPK signaling and diffuse large B-cell lymphoma proliferation via modulating copper transport

Diffuse Large B-cell lymphoma (DLBCL) is a common subtype of non-Hodgkin lymphoma, highlighting the importance of studying susceptibility genes to develop personalized treatment strategies. While cuproptosis, caused by high levels of copper ions induced by ionophores, has been shown to affect cancer survival, its specific role in lymphoma is not yet clear. To investigate the involvement of upregulation-related genes in DLBCL, we employed bioinformatics techniques. Specifically, we analyzed the differentially expressed genes (DEGs) in the GSE25638 dataset using Weighted Gene Co-expression Network Analysis (WGCNA) and performed functional enrichment analysis. By building a Protein-Protein Interaction (PPI) network, candidate genes were identified. Gene Set Enrichment Analysis (GSEA) and Receiver Operating Characteristic (ROC) curve analysis were used to confirm the clinical diagnostic use of these genes. The effects of Antioxidant 1 (ATOX1) knockdown, CuCl2, and DCAC50 treatments on DLBCL cells and the activation of the Mitogen-Activated Protein Kinase (MAPK) pathway were investigated by conducting in vitro experiments. Bioinformatics and in vitro experiments confirmed elevated expression of ATOX1 in DLBCL cells and tumor samples. ATOX1 knockdown led to decreased cell proliferation and G2 cell cycle arrest in vitro. Additionally, Phosphorylated Extracellular Signal-Regulated Kinases 1 and 2 (P-ERK1/2) protein levels within the MAPK pathway were reduced as a result of ATOX1 knockdown, but these levels were recovered by CuCl2. Treatment with DCAC50 showed a dose-dependent antiproliferative effect in DLBCL cells, which was strengthened by ATOX1 knockdown. Our study demonstrated that ATOX1 may be important in DLBCL via controlling the MAPK pathway through copper transport, providing new insights into potential therapeutic strategies for DLBCL.

Construction of a prognostic model based on cuproptosis-related genes and exploration of the value of DLAT and DLST in the metastasis for non-small cell lung cancer

BACKGROUND

To reveal the clinical value of cuproptosis-related genes on prognosis and metastasis in non-small cell lung cancer.

METHODS

Gene expression profiles and clinical information of non-small cell lung cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The data were grouped into training set, internal testing set, and external testing set. A risk prognostic model was constructed by Lasso-Cox regression analysis. Hub genes were identified and evaluated using immunohistochemistry and the transwell migration assay in 50 clinical patients.

RESULTS

A total of 17/19 cuproptosis-related genes were differentially expressed in tumors, 8 were significantly associated with prognosis, and 4 were markedly associated with metastasis. A risk model based on 2 cuproptosis-related genes was constructed and validated for predicting overall survival. The risk score was proven to be an independent risk factor for the prognosis of non-small cell lung cancer. Dihydrolipoamide S-acetyltransferase and dihydrolipoamide S-succinyltransferase, key genes in cuproptosis, were proven to be associated with non-small cell lung cancer prognosis and metastasis. Immunohistochemistry showed that their expression significantly predicted metastasis but failed to predict prognosis in non-small cell lung cancer patients. The transwell migration assay further increased the cellular reliability of our findings.

CONCLUSION

The cuproptosis-related genes prognostic model effectively predicted the prognosis of non-small cell lung cancer. Dihydrolipoamide S-acetyltransferase and dihydrolipoamide S-succinyltransferase may serve as predictive markers for metastasis in non-small cell lung cancer.

Bioinformatics analysis of the role of cuproptosis gene in acute myocardial infarction

BACKGROUND

Immune infiltration plays a vital role in the course of acute myocardial infarction (AMI). Cuproptosis is a new type of programmed cell death discovered recently. Currently, there is no study on the mechanism of cuproptosis gene regulating immune infiltration in AMI. Therefore, by integrating cuproptosis-related genes and GEO database-related microarray data, this study analyzed the association between cuproptosis genes and immune infiltration and built a risk model.

METHODS

The GSE59867 was used to extract cuproptosis gene expression profile. The R limma package was used to analyze the differentially expressed genes associated with AMI-Cuproptosis. The risk model was constructed according to AMI-cuproptosis differentially expressed genes. Prediction of AMI-cuproptosis-related gene drugs through Coremine Medical database. The upstream miRNAs were predicted using miRWalk, TargetScan, and miRDB libraries, and a miRNA-mRNA network was constructed.

RESULTS

Cuproptosis-related genes (DLST, LIAS, DBT, ATP7A, LIPT1, PDHB, GCSH, DLD, DLAT) were down-regulated in AMI patients. One (ATP7B) gene was up-regulated in AMI patients (P<0.05). These 10 Cuproptosis-related genes were significantly associated with immune cell infiltration. Based on these 10 differential genes, the AMI risk prediction model was constructed, and the AUC value was 0.825, among which the abnormal expression of DLST was a risk factor for AMI. Additionally, we also predicted DLAT upstream miRNAs and associated drug targets, finding that 9 miRNAs were upstream of DLST.

CONCLUSIONS

DLST is a potential cuproptosis gene associated with AMI, but its specific mechanism remains unclear and requires further investigation in future studies.

Rhomboid-like 2 correlated with TME infiltration inhibits cuproptosis-related genes and drives malignant phenotype in clear cell renal cell carcinoma

The crosstalk between cuproptosis and the tumor immune microenvironment (TIME) is vital during clear cell renal cell carcinoma (ccRCC) malignant progression. However, the underlying molecular mechanisms regulate this cross-talk remain elusive. Through tailored machine learning, we analyze clinical ccRCC data from The Cancer Genome Atlas (TCGA) to explore the critical factors that regulate the interaction among cuproptosis, TIME, and tumor progression. We found that rhomboid-like 2 (RHBDL2), critical gene affecting this process, might inhibit cuproptosis-related genes (CRGs) and promotes ccRCC progression through the Wnt/β-catenin pathway. Next, knocking down RHBDL2 expression increased the cuproptosis-related genes ferredoxin 1 (FDX1) and lipoic acid synthase (LIAS) levels but reduced forkhead box P3 (FOXP3) levels and tumor growth in vivo and in vitro models. By employing HLY78, Wnt/β-catenin pathway activator, we rescued the expression of CRGs and the malignant proliferation and metastasis capacity in ccRCC cells with RHBDL2 knockdown. Mechanistically, RHBDL2 inhibits cuproptosis and promotes malignant progression of ccRCC through the Wnt/β-catenin pathway. Abnormal RHBDL2 expression may cause the suppressive TIME formation by regulating Treg-cell infiltration, thus triggering immune escape. In summary, our results indicated that RHBDL2 is an oncogene that induces tumorigenesis and targeting RHBDL2 may be novel therapeutic direction for metastatic ccRCC.

The prognostic implications of cuproptosis-related gene signature and the potential of PPIC as a promising biomarker in cutaneous melanoma

Cutaneous melanoma is the most lethal of all skin tumors. Recently, cuproptosis, a novel form of cell death linked to oxidative phosphorylation, has emerged as an important factor. However, the precise role of cuproptosis in melanoma remains unclear. Our research explored the potential links between cuproptosis-related genes, prognosis, immune microenvironments, and melanoma treatments. Significantly, cuproptosis regulators showed remarkable differences between melanoma and normal tissues, establishing their relevance to melanoma. The newly developed cuproptosis-related gene signature (CGS) demonstrated a robust ability to predict overall survival (OS) in melanoma. We constructed a novel nomogram that combined clinical features with CGS to improve predictive accuracy. In addition, the study revealed correlations between CGS and immune cell populations, including CD8+T cells, Tfh cells, B cells, and myeloid-derived suppressor cells. Within the CGS, Peptidylprolyl isomerase C (PPIC) emerged as the most strongly associated with poor prognosis and drug resistance in melanoma. PPIC was identified as a promoter of melanoma progression, enhancing cell invasiveness while concurrently suppressing CD8+T cell activation. This comprehensive study not only elucidated the intricate connections between CGS, melanoma prognosis, immune microenvironment, and drug resistance but also provided compelling evidence supporting PPIC as a promising biomarker for predicting OS in melanoma treatment.

Construction of a prognostic model based on cuproptosis-related patterns for predicting survival, immune infiltration, and immunotherapy efficacy in breast cancer: Cuproptosis-based prognostic modeling in breast cancer

Breast cancer is the most common and lethal malignancy among women worldwide. Cuproptosis, a newly identified copper-dependent cell death, is closely associated with cancer development. However, its regulatory mechanisms in breast cancer are not well studied. This study aims to establish a prognostic model for breast cancer to improve risk stratification. The mRNA expression data was downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering identified patterns based on cuproptosis-related genes. Key genes were screened using Weighted Gene Co-Expression Network Analysis and differentially expressed gene analysis. A prognostic model was constructed using Cox regression and evaluated with time-dependent receiver operating characteristic and Kaplan-Meier analyses. Functional pathways, immune cell infiltration, and other tumor characteristics were also analyzed. Two distinct cuproptosis patterns were identified. The top 21 differentially expressed genes, significantly associated with survival, were used to construct the prognostic model. The risk score has a negative correlation with survival. Enrichment analysis showed immune-related pathways enriched in the low-risk group, which also had more immune cell infiltration, higher stromal component, lower tumor purity, and lower tumor heterogeneity. Finally, significant differences of half maximal inhibitory concentration were also observed between patients in high- and low-risk groups who received chemotherapy and targeted therapy drugs. These findings in our study may provide evidence for further research and individualized management of breast cancer.

Identification of a PANoptosis-related prognostic model in triple-negative breast cancer, from risk assessment, immunotherapy, to personalized treatment

Background

Triple-negative breast cancer is a breast cancer subtype characterized by its challenging prognosis, and establishing prognostic models aids its clinical treatment. PANoptosis, a recently identified type of programmed cell death, influences tumor growth and patient outcomes. Nonetheless, the precise impact of PANoptosis-related genes on the prognosis of triple-negative breast cancer has yet to be determined.

Methods

Clinical information for the triple-negative breast cancer samples was collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases, while 19 PANoptosis-related genes were sourced from previous studies. We first categorized PANoptosis-related subtypes and determined the differentially expressed genes between them. Subsequently, we developed and validated a PANoptosis-associated predictive model using LASSO and Cox multivariate regression analyses. Statistical evaluations were conducted using R software, and the mRNA expression levels of the genes were quantified using real-time PCR.

Results

Using consensus clustering analysis, we divided triple-negative breast cancer patients into two clusters based on PANoptosis-related genes and identified 1054 differentially expressed genes between these clusters. Prognostic-related genes were subsequently selected to re-cluster patients, validating their predictive ability. A prognostic model was then constructed based on four genes: BTN2A2, CACNA1H, PIGR, and S100B. The expression and enriched cell types of these genes were examined and the expression levels were validated in vitro. Furthermore, the model was validated, and a nomogram was created to enhance personalized risk assessment. The risk score, proven to be an independent prognostic indicator for triple-negative breast cancer, showed a positive correlation with both age and disease stage. Immune infiltration and drug sensitivity analyses suggested appropriate therapies for different risk groups. Mutation profiles and pathway enrichment were analyzed, providing insights into potential therapeutic targets.

Conclusion

A PANoptosis-related prognostic model was successfully developed for triple-negative breast cancer, offering a novel approach for predicting patient prognosis and guiding treatment strategies.

Copper homeostasis and cuproptosis in health and disease

Copper is a vital trace element in human physiology, essential for the synthesis of numerous crucial metabolic enzymes and facilitation of various biological processes. Regulation of copper levels within a narrow range is imperative for maintaining metabolic homeostasis. Numerous studies have demonstrated the significant roles of copper homeostasis and cuproptosis in health and disease pathogenesis. However, a comprehensive and up-to-date systematic review in this domain remains absent. This review aims to consolidate recent advancements in understanding the roles of cuproptosis and copper homeostasis in health and disease, focusing on the underlying mechanisms and potential therapeutic interventions. Dysregulation of copper homeostasis, manifesting as either copper excess or deficiency, is implicated in the etiology of various diseases. Cuproptosis, a recently identified form of cell death, is characterized by intracellular copper overload. This phenomenon mediates a diverse array of evolutionary processes in organisms, spanning from health to disease, and is implicated in genetic disorders, liver diseases, neurodegenerative disorders, and various cancers. This review provides a comprehensive summary of the pathogenic mechanisms underlying cuproptosis and copper homeostasis, along with associated targeted therapeutic agents. Furthermore, it explores future research directions with the potential to yield significant advancements in disease treatment, health management, and disease prevention.

lncRNAs as prognostic markers and therapeutic targets in cuproptosis-mediated cancer

Long non-coding RNAs (lncRNAs) have emerged as crucial regulators in various cellular processes, including cancer progression and stress response. Recent studies have demonstrated that copper accumulation induces a unique form of cell death known as cuproptosis, with lncRNAs playing a key role in regulating cuproptosis-associated pathways. These lncRNAs may trigger cell-specific responses to copper stress, presenting new opportunities as prognostic markers and therapeutic targets. This paper delves into the role of lncRNAs in cuproptosis-mediated cancer, underscoring their potential as biomarkers and targets for innovative therapeutic strategies. A thorough review of scientific literature was conducted, utilizing databases such as PubMed, Google Scholar, and ScienceDirect, with search terms like 'lncRNAs,' 'cuproptosis,' and 'cancer.' Studies were selected based on their relevance to lncRNA regulation of cuproptosis pathways and their implications for cancer prognosis and treatment. The review highlights the significant contribution of lncRNAs in regulating cuproptosis-related genes and pathways, impacting copper metabolism, mitochondrial stress responses, and apoptotic signaling. Specific lncRNAs are potential prognostic markers in breast, lung, liver, ovarian, pancreatic, and gastric cancers. The objective of this article is to explore the role of lncRNAs as potential prognostic markers and therapeutic targets in cancers mediated by cuproptosis.

Elucidating the evolving role of cuproptosis in breast cancer progression

Breast cancer (BC) persists as a highly prevalent malignancy in females, characterized by diverse molecular signatures and necessitating personalized therapeutic approaches. The equilibrium of copper within the organism is meticulously maintained through regulated absorption, distribution, and elimination, underpinning not only cellular equilibrium but also various essential biological functions. The process of cuproptosis is initiated by copper's interaction with lipoylases within the tricarboxylic acid (TCA) cycle, which triggers the conglomeration of lipoylated proteins and diminishes the integrity of Fe-S clusters, culminating in cell demise through proteotoxic stress. In BC, aberrations in cuproptosis are prominent and represent a crucial molecular incident that contributes to the disease progression. It influences BC cell metabolism and affects critical traits such as proliferation, invasiveness, and resistance to chemotherapy. Therapeutic strategies that target cuproptosis have shown promising antitumor efficacy. Moreover, a plethora of cuproptosis-centric genes, including cuproptosis-related genes (CRGs), CRG-associated non-coding RNAs (ncRNAs), and cuproptosis-associated regulators, have been identified, offering potential for the development of risk assessment models or diagnostic signatures. In this review, we provide a comprehensive exposition of the fundamental principles of cuproptosis, its influence on the malignant phenotypes of BC, the prognostic implications of cuproptosis-based markers, and the substantial prospects of exploiting cuproptosis for BC therapy, thereby laying a theoretical foundation for targeted interventions in this domain.

Cell Death: Mechanisms and Potential Targets in Breast Cancer Therapy

Breast cancer (BC) has become the most life-threatening cancer to women worldwide, with multiple subtypes, poor prognosis, and rising mortality. The molecular heterogeneity of BC limits the efficacy and represents challenges for existing therapies, mainly due to the unpredictable clinical response, the reason for which probably lies in the interactions and alterations of diverse cell death pathways. However, most studies and drugs have focused on a single type of cell death, while the therapeutic opportunities related to other cell death pathways are often neglected. Therefore, it is critical to identify the predominant type of cell death, the transition to different cell death patterns during treatment, and the underlying regulatory mechanisms in BC. In this review, we summarize the characteristics of various forms of cell death, including PANoptosis (pyroptosis, apoptosis, necroptosis), autophagy, ferroptosis, and cuproptosis, and discuss their triggers and signaling cascades in BC, which may provide a reference for future pathogenesis research and allow for the development of novel targeted therapeutics in BC.

Transcriptomic profiling and risk assessment in bladder cancer: Insights from copper death-related genes

BACKGROUND

The study aimed to investigate the role of copper death-related genes (CRGs) in bladder cancer (BC) for improved prognosis assessment.

METHODS

Multi-omics techniques were utilized to analyze CRG expression in BC tissues from TCGA and GEO databases. Consensus clustering categorized patients into molecular subtypes based on clinical characteristics and immune cell infiltration.

RESULTS

An innovative risk assessment model identified eight critical genes associated with BC risk. In vitro and in vivo experiments validated LIPT1's significant impact on copper-induced cell death, proliferation, migration, and invasion in BC.

CONCLUSION

This multi-omics analysis elucidates the pivotal role of CRGs in BC progression, suggesting enhanced risk assessment through molecular subtype categorization and identification of key genes like LIPT1. Insights into these mechanisms offer the potential for improved diagnosis and treatment strategies for BC patients.

Mechanisms of cuproptosis and its relevance to distinct diseases

Copper is a trace element required by the organism, but once the level of copper exceeds the threshold, it becomes toxic and even causes death. The underlying mechanisms of copper-induced death are inconclusive, with different studies showing different opinions on the mechanism of copper-induced death. Multiple investigations have shown that copper induces oxidative stress, endoplasmic reticulum stress, nucleolar stress, and proteasome inhibition, all of which can result in cell death. The latest research elucidates a copper-dependent death and denominates it as cuproptosis. Cuproptosis takes place through the combination of copper and lipoylated proteins of the tricarboxylic acid cycle, triggering agglomeration of lipoylated proteins and loss of iron-sulfur cluster proteins, leading to proteotoxic stress and ultimately death. Given the toxicity and necessity of copper, abnormal levels of copper lead to diseases such as neurological diseases and cancer. The development of cancer has a high demand for copper, neurological diseases involve the change of copper contents and the binding of copper to proteins. There is a close relationship between these two kinds of diseases and copper. Here, we summarize the mechanisms of copper-related death, and the association between copper and diseases, to better figure out the influence of copper in cell death and diseases, thus advancing the clinical remedy of these diseases.

Cuproptosis, the novel type of oxidation-induced cell death in thoracic cancers: can it enhance the success of immunotherapy?

Copper is an important metal micronutrient, required for the balanced growth and normal physiological functions of human organism. Copper-related toxicity and dysbalanced metabolism were associated with the disruption of intracellular respiration and the development of various diseases, including cancer. Notably, copper-induced cell death was defined as cuproptosis which was also observed in malignant cells, representing an attractive anti-cancer instrument. Excess of intracellular copper leads to the aggregation of lipoylation proteins and toxic stress, ultimately resulting in the activation of cell death. Differential expression of cuproptosis-related genes was detected in normal and malignant tissues. Cuproptosis-related genes were also linked to the regulation of oxidative stress, immune cell responses, and composition of tumor microenvironment. Activation of cuproptosis was associated with increased expression of redox-metabolism-regulating genes, such as ferredoxin 1 (FDX1), lipoic acid synthetase (LIAS), lipoyltransferase 1 (LIPT1), dihydrolipoamide dehydrogenase (DLD), drolipoamide S-acetyltransferase (DLAT), pyruvate dehydrogenase E1 subunit alpha 1 (PDHA1), and pyruvate dehydrogenase E1 subunit beta (PDHB)). Accordingly, copper-activated network was suggested as an attractive target in cancer therapy. Mechanisms of cuproptosis and regulation of cuproptosis-related genes in different cancers and tumor microenvironment are discussed in this study. The analysis of current findings indicates that therapeutic regulation of copper signaling, and activation of cuproptosis-related targets may provide an effective tool for the improvement of immunotherapy regimens.

PDE3B regulates KRT6B and increases the sensitivity of bladder cancer cells to copper ionophores

Cuproptosis is a new Cu-dependent programmed cell death manner that has shown regulatory functions in many tumor types, however, its mechanism in bladder cancer remains unclear. Here, we reveal that Phosphodiesterase 3B (PDE3B), a cuproptosis-associated gene, could reduce the invasion and migration of bladder cancer. PDE3B is downregulated in bladder cancer tissues, which is correlated with better prognosis. Conversely, overexpression of PDE3B in bladder cancer cell could significantly resist invasion and migration, which is consistent with the TCGA database results. Future study demonstrate the anti-cancer effect of PDE3B is mediated by Keratin 6B (KRT6B) which leads to the keratinization. Therefore, PDE3B can reduce KRT6B expression and inhibit the invasion and migration of bladder cancer. Meanwhile, increased expression of PDE3B was able to enhance the sensitivity of Cuproptosis drug thiram. This study show that PDE3B/KRT6B is a potential cancer therapeutic target and PDE3B activation is able to increase the sensitivity of bladder cancer cells to copper ionophores.

Cuproptosis in cancers: Function and implications from bench to bedside

Copper, an indispensable micronutrient, is implicated in numerous vital biological processes and is essential for all physiological activities. Recently, the discovery of a novel type of copper-dependent cell death, known as cuproptosis, has shed light on its role in cancer development. Extensive research is currently underway to unravel the mechanisms underlying cuproptosis and its correlation with various cancer types. In this review, we summarize the findings regarding the roles and mechanisms of cuproptosis in various cancer types, including colorectal cancer, lung cancer, gastric cancer, breast cancer, liver cancer and cutaneous melanoma. Furthermore, the effects of copper-related agents such as copper chelators and copper ionophores on cell proliferation, apoptosis, angiogenesis, tumor immunity, and chemotherapy resistance have been explored in cancer preclinical and clinical trials. These insights provide promising avenues for the development of prospective anticancer drugs aimed at inducing cuproptosis.

Bioinformatic analysis and experimental validation of six cuproptosis-associated genes as a prognostic signature of breast cancer

BACKGROUND

Breast carcinoma (BRCA) is a life-threatening malignancy in women and shows a poor prognosis. Cuproptosis is a novel mode of cell death but its relationship with BRCA is unclear. This study attempted to develop a cuproptosis-relevant prognostic gene signature for BRCA.

METHODS

Cuproptosis-relevant subtypes of BRCA were obtained by consensus clustering. Differential expression analysis was implemented using the 'limma' package. Univariate Cox and multivariate Cox analyses were performed to determine a cuproptosis-relevant prognostic gene signature. The signature was constructed and validated in distinct datasets. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were also conducted using the prognostic signature to uncover the underlying molecular mechanisms. ESTIMATE and CIBERSORT algorithms were applied to probe the linkage between the gene signature and tumor microenvironment (TME). Immunotherapy responsiveness was assessed using the Tumor Immune Dysfunction and Exclusion (TIDE) web tool. Real-time quantitative PCR (RT-qPCR) was performed to detect the expressions of cuproptosis-relevant prognostic genes in breast cancer cell lines.

RESULTS

Thirty-eight cuproptosis-associated differentially expressed genes (DEGs) in BRCA were mined by consensus clustering and differential expression analysis. Based on univariate Cox and multivariate Cox analyses, six cuproptosis-relevant prognostic genes, namely SAA1, KRT17, VAV3, IGHG1, TFF1, and CLEC3A, were mined to establish a corresponding signature. The signature was validated using external validation sets. GSVA and GSEA showed that multiple cell cycle-linked and immune-related pathways along with biological processes were associated with the signature. The results ESTIMATE and CIBERSORT analyses revealed significantly different TMEs between the two Cusig score subgroups. Finally, RT-qPCR analysis of cell lines further confirmed the expressional trends of SAA1, KRT17, IGHG1, and CLEC3A.

CONCLUSION

Taken together, we constructed a signature for projecting the overall survival of BRCA patients and our findings authenticated the cuproptosis-relevant prognostic genes, which are expected to provide a basis for developing prognostic molecular biomarkers and an in-depth understanding of the relationship between cuproptosis and BRCA.

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.

A Cuproptosis-Related LncRNA Risk Model for Predicting Prognosis and Immunotherapeutic Efficacy in Patients with Hepatocellular Carcinoma

Cuproptosis is a novel programmed cell death pathway that is initiated by direct binding of copper to lipoylated tricarboxylic acid (TCA) cycle proteins. Recent studies have demonstrated that cuproptosis-related genes regulate tumorigenesis. However, the potential role and clinical significance of cuproptosis-related long noncoding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) have not been established. We performed a bioinformatics analyses of RNA-sequencing data of HCC patients extracted from The Cancer Genome Atlas (TCGA) dataset to identify and validate a cuproptosis-related lncRNA prognostic signature. Furthermore, we analyzed the clinical significance of the prognostic signature of cuproptosis-related lncRNA in predicting the immunotherapeutic efficacy and the status of the tumor immune microenvironment. The RNA-sequencing data, genomic mutations, and clinical information were downloaded for 374 HCC samples and 50 normal liver samples from TCGA-Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. Co-expression analysis of Gene-lncRNA pairs with 49 known cuproptosis-related prognostic genes was used to define cuproptosis-related prognostic lncRNAs. We performed the LASSO algorithm and univariate and multivariate Cox regression analysis, respectively, to gradually identify the prognostic risk models of cuproptosis-related lncRNA based on the TCGA-LIHC dataset. Subsequently, the predictive performance of the model was evaluated using receiver operation characteristic (ROC) curves, Kaplan-Meier survival curves, and prognostic nomogram. The analysis of gene-lncRNA co-expression with 49 known cuproptosis-related genes identified 1359 cuproptosis-related lncRNAs in the TCGA-LIHC data set. A prognostic model was constructed with nine cuproptosis-related prognostic lncRNAs (AC007998.3, AC003086.1, AC009974.2, IQCH-AS1, LINC0256 1, AC105345.1, ZFPM2-AS1, AL353708.1 and WAC-AS1) using LASSO regression and Cox regression analyses. Risk scores were calculated for all HCC patient samples based on the four cuproptosis-related lncRNA prognostic models. All HCC patients were divided into high-risk and low-risk subgroups according to a 1:1 ratio column. The Kaplan-Meier survival curve analysis showed that the overall survival rate (OS) of the high-risk group patients was significantly lower than that of the low-risk group. The principal component analysis (PCA) confirmed that the prognostic lncRNA model accurately distinguished between high- and low-risk HCC patients. Furthermore, regression analysis as well as ROC curves confirmed the prognostic value of the risk score. A nomogram with risk scores and other clinicopathological characteristics was constructed. The nomogram accurately predicted the probability of 1-, 3-, and 5-year OS in HCC patients. Tumor mutation burden (TMB) scores were higher for high-risk patients than for low-risk patients. HCC patients in the low-risk group showed lower TIDE scores and greater sensitivity to antitumor drugs than those in the high-risk group. Tumor immune responses and tumor immune cell infiltration were significantly different between the high-risk and low-risk groups of patients with HCC. Our study identified a 9-cuproptosis-related lncRNA signature that accurately predicted prognosis, immunotherapeutic efficacy, and the status of the tumor immune microenvironment in HCC patients. Therefore, this cuproptosis-related lncRNA risk model is a potential prognostic biometric feature in HCC and shows high clinical value in identifying HCC patients who are potentially responsive to immunotherapy.

Micronutrient Status and Breast Cancer: A Narrative Review

Breast cancer is one of the most common cancers worldwide, at the same time being one of the most prevalent causes of women's death. Many factors such as alcohol, weight fluctuations, or hormonal replacement therapy can potentially contribute to breast cancer development and progression. Another important factor in breast cancer onset includes micronutrient status. In this narrative review, we analyzed 23 micronutrients and their possible influence on breast cancer onset and progression. Further, the aim of this study was to investigate the impact of micronutrient status on the prevention of breast cancer and its possible influence on various therapeutic pathways. We researched meta-analyses, systemic and narrative reviews, retrospective studies, as well as original studies on human and animal models. The results of these studies indicate a possible correlation between the different levels of micronutrients and a decreased risk of breast cancer as well as a better survival rate. However, further studies are necessary to establish adequate doses of supplementation of the chosen micronutrients and the exact mechanisms of micronutrient impact on breast cancer therapy.

Revolutionizing breast cancer treatment: Harnessing the related mechanisms and drugs for regulated cell death (Review)

Breast cancer arises from the malignant transformation of mammary epithelial cells under the influence of various carcinogenic factors, leading to a gradual increase in its prevalence. This disease has become the leading cause of mortality among female malignancies, posing a significant threat to the health of women. The timely identification of breast cancer remains challenging, often resulting in diagnosis at the advanced stages of the disease. Conventional therapeutic approaches, such as surgical excision, chemotherapy and radiotherapy, exhibit limited efficacy in controlling the progression and metastasis of the disease. Regulated cell death (RCD), a process essential for physiological tissue cell renewal, occurs within the body independently of external influences. In the context of cancer, research on RCD primarily focuses on cuproptosis, ferroptosis and pyroptosis. Mounting evidence suggests a marked association between these specific forms of RCD, and the onset and progression of breast cancer. For example, a cuproptosis vector can effectively bind copper ions to induce cuproptosis in breast cancer cells, thereby hindering their proliferation. Additionally, the expression of ferroptosis‑related genes can enhance the sensitivity of breast cancer cells to chemotherapy. Likewise, pyroptosis‑related proteins not only participate in pyroptosis, but also regulate the tumor microenvironment, ultimately leading to the death of breast cancer cells. The present review discusses the unique regulatory mechanisms of cuproptosis, ferroptosis and pyroptosis in breast cancer, and the mechanisms through which they are affected by conventional cancer drugs. Furthermore, it provides a comprehensive overview of the significance of these forms of RCD in modulating the efficacy of chemotherapy and highlights their shared characteristics. This knowledge may provide novel avenues for both clinical interventions and fundamental research in the context of breast cancer.

Identification of cuproptosis-related miRNAs in triple-negative breast cancer and analysis of the miRNA-mRNA regulatory network

Introduction

The close association between cuproptosis and tumor immunity in triple-negative breast cancer (TNBC) allows its monitoring for predicting the prognosis of patients with TNBC. Nevertheless, the biological function and prognostic value of cuproptosis-related miRNAs and their target genes have not been reported.

Purpose

To construct the miRNA and mRNA-based risk models associated with cuproptosis for patients with TNBC.

Methods

Comparison of expression levels for genes associated with cuproptosis was executed between patients in the normal individuals and the TCGA-TNBC cohort. Conducting differential analysis resulted in the identification of differentially expressed miRNA (DE-miRNAs) and differentially expressed genes (DEGs) between the TNBC and Control samples. Screening for prognostic miRNAs and biomarkers involved employing univariate Cox analysis and least absolute shrinkage and selection operator regression analyses. These methods were utilized to construct risk models aimed at predicting the survival of patients with TNBC. Based on the median value of risk scores, patients were then stratified into low- and high-risk groups. Functional enrichment analysis was employed to explore the potential function and pathways of prognostic genes. Additionally, independent prognostic analysis was performed through univariate and multivariate Cox regression. Immune infiltration analysis was performed to examine disparities in the infiltration of immune cells between the two risk groups. Finally, the prognostic gene expression was mined in key cell types of TNBC.

Results

We obtained 5213 DEGs and 204 DE-miRNAs related to cuproptosis between TNBC and Control samples. Five prognostic miRNAs (miR-203a-3p, miR-1277-3p, miR-135b-5p, miR-200c-3p, and miR-592) and three biomarkers (DENND5B, IGF1R, and MEF2C) were closely associated with TNBC. Significant differences in the functions of prognostic genes between the two risk groups were observed, encompassing adipogenesis, inflammatory response, and hormone metabolic process. The prognostic gene regulatory network revealed that miR200C-3p regulated ZFPM2 and CFL2, and miR-1277-3p regulated BMP2 and RORA. A nomogram was created based on riskScore, cancer status, and pathologic stage to predict 1/3/5-year survival of patients with TNBC. Immune infiltration analysis indicated that the immune microenvironment may be associated with the progression of TNBC. Interestingly, prognostic genes exhibited higher expression levels in T cells, fibroblasts, endothelial cells, and monocytes compared to other cells.

Conclusions

Five prognostic miRNA (miR-203a-3p, miR-1277-3p, miR-135b-5p, miR-200c-3p, and miR-592) and three biomarkers (DENND5B, IGF1R, and MEF2C) were significantly associated with TNBC, it provides new therapeutic targets for the treatment and prognosis of TNBC.

Analysis of cuproptosis-related genes in prognosis and immune infiltration in grade 4 diffuse gliomas

Background

Grade 4 diffuse gliomas are highly malignant tumours with poor prognosis. Cuproptosis is a novel form of cell death. Cuproptosis genes are associated with various tumours and affect the prognosis of patients with these tumours. However, the relationship between cuproptosis and grade 4 diffuse gliomas remains unclear.

Methods

Differentially expressed genes associated with cuproptosis in grade 4 diffuse gliomas were identified. Second, the prognostic model was established by univariate and multivariate COX regression analyses, and the genes (p < 0.05) were selected for subsequent analysis. The endpoint of the study was death. Single-gene analysis was performed in accordance with the expression levels of SLC31A1. Third, based on the expression levels of SLC31A1, gene function enrichment, drug sensitivity, and immune cell infiltration analyses were performed. Finally, the expression and biological functions of SLC31A1 in grade 4 diffuse gliomas were identified using immunohistochemical staining, qRT-PCR, and related biological experiments.

Results

We identified six coproptosis genes in the grade 4 diffuse gliomas dataset (SLC31A1, PDHA1, GLS, FDX1, LIPT1, and ATP7B). The six key cuproptosis genes of grade 4 diffuse gliomas were analysed using univariate COX analysis. Basic patient data, including age, race, year of diagnosis, sex, and treatment, were included in the univariate COX analysis. Then, multivariate COX analysis was performed for the factors with p < 0.2 in the univariate COX analysis. Age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 levels were found to be independent prognostic factors. A nomogram was constructed using these 5 factors. Through experiments, we found that SLC31A1 had a higher expression level in cancer tissue than that near cancer among the three genes, SLC31A1, PDHA1, and FDX1; therefore, we focused on SLC31A1. According on the expression level of SLC31A1, we performed gene function enrichment, drug sensitivity, and immune cell infiltration analyses. Navitoclax was the most sensitive drug. Differential gene function enrichment was observed for metalloendopeptidase activity. SLC31A1 is expressed in dendritic cells, macrophages, neutrophils, and CD8+T cells. SLC31A1 is highly expressed in grade 4 diffuse gliomas, whereas SLC31A1 knockdown significantly reduces cell proliferation and mobility.

Conclusions

Age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 expression were independent prognostic factors. A nomogram was constructed based on age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 levels. Through analysis and experimental verification, SLC31A1 was found to affect the prognosis and progression of patients with grade 4 diffuse gliomas and was associated with immune cell infiltration.

Cuproptosis-Related Genes MTF1 and LIPT1 as Novel Prognostic Biomarker in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a life-threatening hematologic malignant disease with high morbidity and mortality in both adults and children. Cuproptosis, a novel mode of cell death, plays an important role in tumor development, but the functional mechanisms of cuproptosis-related genes (CRGs) in AML are unclear. The differential expression of CRGs between tumors such as AML and normal tissues in UCSC XENA, TCGA and GTEx was verified using R (version: 3.6.3). Lasso regression, Cox regression and Nomogram were used to screen for prognostic biomarkers of AML and to construct corresponding prognostic models. Kaplan-Meier analysis, ROC analysis, clinical correlation analysis, immune infiltration analysis and enrichment analysis were used to further investigate the correlation and functional mechanisms of CRGs with AML. The ceRNA regulatory network was used to identify the mRNA-miRNA-lncRNA regulatory axis. Cuproptosis-related genes LIPT1, MTF1, GLS and CDKN2A were highly expressed in AML, while FDX1, LIAS, DLD, DLAT, PDHA1, SLC31A1 and ATP7B were lowly expressed in AML. Lasso regression, Cox regression, Nomogram and calibration curve finally identified MTF1 and LIPT1 as two novel prognostic biomarkers of AML and constructed the corresponding prognostic models. In addition, all 12 CRGs had predictive power for AML, with MTF1, LIAS, SLC31A1 and CDKN2A showing more reliable results. Further analysis showed that ATP7B was closely associated with mutation types such as FLT3, NPM1, RAS and IDH1 R140 in AML, while the expression of MTF1, LIAS and ATP7B in AML was closely associated with immune infiltration. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) revealed that biological functions such as metal ion transmembrane transporter activity, haptoglobin binding and oxygen carrier activity, pathways such as interferon alpha response, coagulation, UV response DN, apoptosis, hypoxia and heme metabolism all play a role in the development of AML. The ceRNA regulatory network revealed that 6 lncRNAs such as MALAT1, interfere with MTF1 expression through 6 miRNAs such as hsa-miR-32-5p, which in turn affect the development and progression of AML. In addition, APTO-253 has the potential to become an AML-targeted drug. The cuproptosis-related genes MTF1 and LIPT1 can be used as prognostic biomarkers in AML. A total of six lncRNAs, including MALAT1, are involved in the expression and regulation of MTF1 in AML through six miRNAs such as hsa-miR-32-5p.

Copper metabolism and cuproptosis in human malignancies: Unraveling the complex interplay for therapeutic insights

Copper, a vital trace element, orchestrates diverse cellular processes ranging from energy production to antioxidant defense and angiogenesis. Copper metabolism and cuproptosis are closely linked in the context of human diseases, with a particular focus on cancer. Cuproptosis refers to a specific type of copper-mediated cell death or copper toxicity triggered by disruptions in copper metabolism within the cells. This phenomenon encompasses a spectrum of mechanisms, such as oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, and perturbations in metal ion equilibrium. Mechanistically, cuproptosis is driven by copper binding to the lipoylated enzymes within the tricarboxylic acid (TCA) cycle. This interaction participates in protein aggregation and proteotoxic stress, ultimately culminating in cell death. Targeting copper metabolism and its associated pathways in cancer cells hold therapeutic potential by selectively targeting and eliminating cancerous cells. Strategies to modulate copper levels, enhance copper excretion, or interfere with cuproptotic pathways are being explored to identify novel therapeutic targets for cancer therapy and improve patient outcomes. Understanding the relationship between cuproptosis and copper metabolism in human malignancies remains an active area of research. This review provides a comprehensive overview of the association among copper metabolism, copper homeostasis, and carcinogenesis, explicitly emphasizing the cuproptosis mechanism and its implications for cancer pathogenesis. Additionally, we emphasize the therapeutic aspects of targeting copper and cuproptosis for cancer treatment.

Effective prognostic risk model with cuproptosis-related genes in laryngeal cancer

OBJECTIVE

Laryngeal cancer, characterized by high recurrence rates and a lack of effective biomarkers, has been associated with cuproptosis, a regulated cell death process linked to cancer progression. In this study, we aimed to explore the roles of cuproptosis-related genes in laryngeal cancer and their potential as prognostic markers and therapeutic targets.

METHODS

We collected comprehensive data from The Cancer Genome Atlas and Gene Expression Omnibus databases, including gene expression profiles and clinical data of laryngeal cancer patients. Using clustering and gene analysis, we identified cuproptosis-related genes with prognostic significance. A risk model was constructed based on these genes, categorizing patients into high- and low-risk groups for outcome comparison. Univariate and multivariate analyses were conducted to identify independent prognostic factors, which were then incorporated into a nomogram. Gene Set Enrichment Analysis was employed to explore pathways distinguishing high- and low-risk groups.

RESULTS

Our risk model, based on four genes, including transmembrane 2, dishevelled binding antagonist of β-catenin 1, stathmin 2, and G protein-coupled receptor 173, revealed significant differences in patient outcomes between high- and low-risk groups. Independent prognostic factors were identified and integrated into a nomogram, providing a valuable tool for prognostic prediction. Gene Set Enrichment Analysis uncovered up-regulated pathways specifically associated with high-risk patient samples.

CONCLUSION

This study highlights the potential of cuproptosis-related genes as valuable prognostic markers and promising therapeutic targets in the context of laryngeal cancer. This research sheds light on new avenues for understanding and managing this challenging disease.

LEVEL OF EVIDENCE

Level 4.

Integrated analysis identifies cuproptosis-related gene DLAT and its competing endogenous RNAs network to predict the prognosis of pancreatic adenocarcinoma patients

Pancreatic adenocarcinoma (PAAD) is a highly malignant tumor with poor prognosis. However, the relationship between cuproptosis-related genes (CRGs) and its competing endogenous RNA (ceRNA) network with the prognosis of PAAD patients remains unclear. To investigate this relationship, we calculated the difference in CRGs between PAAD tissues and normal tissues using the 'limma' R package. Additionally, we employed least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a prognostic signature for CRGs. Survival analysis of patients with PAAD was performed using Kaplan-Meier analysis. Furthermore, we used bioinformatics tools to screen for CRGs-related MicroRNA (miRNA) and lncRNAs. To validate these findings, we conducted real-time quantitative polymerase chain reaction (RT-qPCR), CCK-8, colony formation, and Transwell assays to assess the effect of DLAT in vitro. Our results revealed a cuproptosis-related prognostic signature consisting of 3 prognostic genes (DLAT, LIAS, and LIPT1). Notably, patients with a high-risk score for the CRGs signature exhibited poor prognosis in terms of overall survival (OS) (P < .05). The receiver operating characteristic (ROC) curve was used to evaluate the prognostic signature of CRGs. The results showed that the 1-year, 3-year, and 5-year area under the curve values for predicting OS were 0.62, 0.66, and 0.79, respectively. Additionally, the CRGs-related ceRNA network revealed the regulatory axis of LINC00857/has-miR-1179/DLAT in PAAD. In vitro experiments demonstrated that knockdown of LINC00857 and DLAT inhibited the growth and invasion of PAAD cells. This study identified a CRG-related prognostic signature consisting of 3 biomarkers (DLAT, LIAS, and LIPT1) for PAAD. Furthermore, ceRNA network analysis suggested the involvement of the LINC00857/has-miR-1179/DLAT axis in the development of PAAD. Overall, this study provides theoretical support for the investigation of diagnostic and prognostic biomarkers as well as potential therapeutic targets in PAAD.

Precision targeting of CuET overload to disrupt mitochondrial unfolded protein response by integrated liposome

Mitochondria in breast cancer play a critical role in survival and adaptation to dynamic environments. Thus, targeting mitochondria emerges as a promising therapeutic strategy for breast cancer. However, the adaptive unfolded protein response in mitochondria (UPRmt) due to mitochondrial unspecific distribution might contribute to diminished therapeutic outcomes. Herein, mitochondrial targeting liposome agents (CTPP-Lipid) are constructed and adopted for delivering the copper ion (CuET-DSF), which is especially sensitive for mitochondria-abundant breast tumors. In brief, the CTPP-Lipid@CuET achieves the goal of Cu2+ overloading by mitochondria targeting delivery. This rapidly increases ROS production, disrupts mitochondrial structure, and avoids the adaptive UPRmt formation, finally leading to apoptosis of breast cancer cells. In general, the Cu2+ overloading at mitochondria by CTPP-Lipid@CuET is a potential strategy for antitumor therapy, providing new insights into breast tumor therapy.

Multiple programmed cell death patterns and immune landscapes in bladder cancer: Evidence based on machine learning and multi-cohorts

BACKGROUND

Bladder cancer (BLCA) is the most prevalent malignant neoplasm of the urinary tract, and ranks seventh as the most frequent systemic neoplasm in males. Dysregulation of programmed cell death (PCD) has been implicated in various stages of cancer progression, including tumorigenesis, invasion, and metastasis. However, the correlation between multiple PCD modes and BLCA is lacking. Thus, a risk prediction model was built based on 12 models of PCD to predict prognosis and immunotherapy response in patients with BLCA.

METHODS

The RNA sequencing transcriptome data of BLCA were collected from the Cancer Genome Atlas Program (TCGA) and GEO datasets. Univariate Cox and LASSO regression analyzes were performed to identify PCD-related genes (PCDRGs) significant for prognosis. Multivariate Cox regression analysis was used to develop a prognostic model for PCD. Survival analysis and chi-squared test were employed to analyze the survival variations between different risk groups. Univariate and multivariate Cox analyses were performed to evaluate the model as an independent prognostic predictor. A nomogram was formulated using both clinical data and the model to predict the survival rates of BLCA patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were performed to analyze and elucidate the molecular mechanisms and pathways operating within different risk score groups. Furthermore, the immune landscape was investigated and the efficacy of various anti-tumor drugs was evaluated for BLCA. Finally, consensus clustering analysis was adopted to explore the association between different PCD clusters and clinical characteristics.

RESULTS

Assessment of the public datasets and multivariate Cox analysis yielded 1254 PCDRGs, of which 10 PCDRGs for BLCA were identified. Based on the PCDRGs, a prognostic model was built for BLCA patient prognosis. Compared with the low-risk group, the high-risk group had a poorer prognosis. The model predicted area under the curve (AUC) values of 0.751, 0.753, and 0.763, respectively, for 1-, 3-, and 5-year survival of BLCA patients. The nomogram further demonstrated the credibility of the prognosis model. The low-risk group patients exhibited lower TIDE scores and higher TMB scores, implying better response of the low-risk group to immunotherapy. The consensus clustering analysis indicated that compared with PCD cluster A, PCD cluster B was significantly more expressed in PCDRGs, suggesting a closer relation of PCD cluster B to PCDRGs. Patients in PCD cluster B had lower risk scores.

CONCLUSION

To summarize, the effects of 12 PCD patterns on BLCA were synthesized and the correlation between PCD and BLCA was explored. These findings provide new and convincing evidence for individualized treatment of BLCA, and help guide the treatment strategy and improve the prognosis of BLCA patients.

Cuproptosis-related ceRNA axis triggers cell proliferation and cell cycle through CBX2 in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) has high morbidity and mortality. Despite substantial advances in treatment, the prognosis of patients with LUAD remains unfavorable. The ceRNA axis has been reported to play an important role in the pathogenesis of LUAD. In addition, cuproptosis is considered an important factor in tumorigenesis. The expression of CBX2 has been associated with the development of multiple tumors, including LUAD. However, the precise molecular mechanisms through which the cuproptosis-related ceRNA network regulates CBX2 remain unclear.

METHODS

The DEGs between tumor and normal samples of LUAD were identified in TCGA database. The "ConsensusClusterPlus" R package was used to perform consensus clustering based on the mRNA expression matrix and cuproptosis-related gene expression profile. Then, LASSO-COX regression analysis was performed to identify potential prognostic biomarkers associated with cuproptosis, and the ceRNA network was constructed. Finally, the mechanisms of ceRNA in LUAD was studied by cell experiments.

RESULTS

In this study, the AC144450.1/miR-424-5p axis was found to promote the progression of LUAD by acting on CBX2. The expression of AC144450.1 and miR-424-5p can be altered to regulate CBX2 and is correlated with cell proliferation and cell cycle of LUAD. Mechanistically, AC144450.1 affects the expression of CBX2 by acting as the ceRNA of miR-424-5p. In addition, a cuproptosis-related model were constructed in this study to predict the prognosis of LUAD.

CONCLUSIONS

This study is the first to demonstrate that the AC144450.1/miR-424-5p/CBX2 axis is involved in LUAD progression and may serve as a novel target for its diagnosis and treatment.

A cuproptosis score model and prognostic score model can evaluate clinical characteristics and immune microenvironment in NSCLC

BACKGROUND

Cuproptosis-related genes (CRGs) are associated with lung adenocarcinoma. However, the links between CRGs and non-small-cell lung cancer (NSCLC) are not clear. In this study, we aimed to develop two cuproptosis models and investigate their correlation with NSCLC in terms of clinical features and tumor microenvironment.

METHODS

CRG expression profiles and clinical data from NSCLC and normal tissues was obtained from GEO (GSE42127) and TCGA datasets. Molecular clusters were classified into three patterns based on CRGs and cuproptosis cluster-related specific differentially expressed genes (CRDEGs). Then, two clinical models were established. First, a prognostic score model based on CRDEGs was established using univariate/multivariate Cox analysis. Then, through principal component analysis, a cuproptosis score model was established based on prognosis-related genes acquired via univariate analysis of CRDEGs. NSCLC patients were divided into high/low risk groups.

RESULTS

Eighteen CRGs were acquired, all upregulated in tumor tissues, 15 of which significantly (P < 0.05). Among the three CRG clusters, cluster B had the best prognosis. In the CRDEG clusters, cluster C had the best survival. In the prognostic score model, the high-risk group had worse prognosis, higher tumor mutation load, and lower immune infiltration while in the cuproptosis score model, a high score represented better survival, lower tumor mutation load, and high-level immune infiltration.

CONCLUSIONS

The cuproptosis score model and prognostic score model may be associated with NSCLC prognosis and immune microenvironment. These novel findings on the progression and immune landscape of NSCLC may facilitate the provision of more personalized immunotherapy interventions for NSCLC patients.

Cuproptosis-related genes predict prognosis and trastuzumab therapeutic response in HER2-positive breast cancer

Breast cancer is the most common diagnosed cancer, the HER2-positive subtype account for 15% of all breast cancer. HER2-targeted therapy is the mainstay treatment for HER2-positive breast cancer. Cuproptosis is a novel form of programmed cell death, and is caused by mitochondrial lipoylation and destabilization of iron-sulfur proteins triggered by copper, which was considered as a key player in various biological processes. However, the roles of cuproptosis-related genes in HER2-positive breast cancer remain largely unknown. In the present study, we constructed a prognostic prediction model of HER2-positive breast cancer patients using TCGA database. Dysregulated genes for cells resistant to HER2-targeted therapy were analyzed in the GEO dataset. KEGG pathway, GO enrichment and GSEA was performed respectively. The immune landscape of DLAT was analyzed by CIBERSORT algorithm and TIDE algorithm. HER2-positive breast cancer patients with high CRGs risk score showed shorter OS. DLAT was downregulated and correlated with better survival of HER2-positive breast cancer patients (HR = 3.30, p = 0.022). High expressed DLAT was associated with resistant to HER2-targeted therapy. Knocking down DLAT with siRNA increased sensitivity of breast cancer to trastuzumab. KEGG pathway and GO enrichment of DEGs indicated that DLAT participates in various pathways correlated with organelle fission, chromosome segregation, nuclear division, hormone-mediated signaling pathway, regulation of intracellular estrogen receptor signaling pathway, condensed chromosome and PPAR signaling pathway. There was a negative correlation between TIDE and DLAT expression (r = - 0.292, p < 0.001), which means high DLAT expression is an indicator of sensitivity to immunotherapy. In conclusion, our study constructed a four CRGs signature prognostic prediction model and identified DLAT as an independent prognostic factor and associated with resistant to HER2-targeted therapy for HER2-positive breast cancer patients.

Identification of a new gene signature for prognostic evaluation in cervical cancer: based on cuproptosis-associated angiogenesis and multi-omics analysis

Patients with recurrent or metastatic cervical cancer are in urgent need of novel prognosis assessment or treatment approaches. In this study, a novel prognostic gene signature was discovered by utilizing cuproptosis-related angiogenesis (CuRA) gene scores obtained through weighted gene co-expression network analysis (WGCNA) of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. To enhance its reliability, the gene signature was refined by integrating supplementary clinical variables and subjected to cross-validation. Meanwhile, the activation of the VEGF pathway was inferred from an analysis of cell-to-cell communication, based on the expression of ligands and receptors in cell transcriptomic datasets. High-CuRA patients had less infiltration of CD8 + T cells and reduced expression of most of immune checkpoint genes, which indicated greater difficulty in immunotherapy. Lower IC50 values of imatinib, pazopanib, and sorafenib in the high-CuRA group revealed the potential value of these drugs. Finally, we verified an independent prognostic gene SFT2D1 was highly expressed in cervical cancer and positively correlated with the microvascular density. Knockdown of SFT2D1 significantly inhibited ability of the proliferation, migration, and invasive in cervical cancer cells. CuRA gene signature provided valuable insights into the prediction of prognosis and immune microenvironment of cervical cancer, which could help develop new strategies for individualized precision therapy for cervical cancer patients.

Identification of prognostic biomarkers for cervical cancer based on programmed cell death-related genes and assessment of their immune profile and response to drug therapy

BACKGROUND

Programmed cell death (PCD) has been widely investigated in various human diseases. The present study aimed to identify a novel PCD-related genetic signature in cervical squamous cell carcinoma (CESC) to provide clues for survival, immunotherapy and drug sensitization prediction.

METHODS

Single-sample gene set enrichment analysis (ssGSEA) was used to quantify the PCD score and assess the distribution of PCD in clinicopathological characteristics in The Cancer Genome Atlas (TCGA)-CESC samples. Then, the ConsensusClusterPlus method was used to identify molecular subtypes in the TCGA-CESC database. Genomic mutation analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment, as well as tumor microenvironment (TME) infiltration analysis, were performed for each molecular subtype group. Finally, a prognostic model by Uni-Cox and least absolute shrinkage and selection operator-Cox analysis was established based on differentially expressed genes from molecular subtypes. ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) and ssGSEA were performed to assess the correlation between the model and TME. Drug sensitization prediction was carried out with the oncoPredict package.

RESULTS

Preliminary analysis indicated that PCD had a potential association clinical characteristics of the TCGA-CESC cohort, and PCD-related genes mutated in 289 (70.59%) CESC patients. Next, four groups of CESC molecular typing were clustered based on 63 significantly prognostic PCD-related genes. Among four subtypes, C1 group displayed the worst prognosis combined with over expressed PCD genes and enriched cell cycle-related pathways. C4 group exhibited the best prognosis accompanied with high degree of immune infiltration. Finally, a five-gene (SERPINE1, TNF, CA9, CX3CL1 and JAK3) prognostic model was constructed. Patients in the high-risk group displayed unfavorable survival. Immune infiltration analysis found that the low-risk group had significantly higher levels of immune cell infiltration such as T cells, Macrophages_M1, relative to the high-risk group, and were significantly enriched in apoptosis-associated pathways, which predicted a higher level of immunity. Drug sensitivity correlation analysis revealed that the high-risk group was resistant to conventional chemotherapeutic drugs and sensitive to the Food and Drug Administration-approved drugs BI.2536_1086 and SCH772984_1564.

CONCLUSIONS

In the present study, we first found that PCD-related gene expression patterns were correlated with clinical features of CESC patients, which predicts the feasibility of subsequent mining of prognostic features based on these genes. The five-PCD-associated-gene prognostic model showed good assessment ability in predicting patient prognosis, immune response and drug-sensitive response, and provided guidance for the elucidation of the mechanism by which PCD affects CESC, as well as for the clinical targeting of drugs.

Cuproptosis gene-related, neural network-based prognosis prediction and drug-target prediction for KIRC

BACKGROUND

Kidney renal clear cell carcinoma (KIRC), as a common case in renal cell carcinoma (RCC), has the risk of postoperative recurrence, thus its prognosis is poor and its prognostic markers are usually based on imaging methods, which have the problem of low specificity. In addition, cuproptosis, as a novel mode of cell death, has been used as a biomarker to predict disease in many cancers in recent years, which also provides an important basis for prognostic prediction in KIRC. For postoperative patients with KIRC, an important means of preventing disease recurrence is pharmacological treatment, and thus matching the appropriate drug to the specific patient's target is also particularly important. With the development of neural networks, their predictive performance in the field of medical big data has surpassed that of traditional methods, and this also applies to the field of prognosis prediction and drug-target prediction.

OBJECTIVE

The purpose of this study is to screen for cuproptosis genes related to the prognosis of KIRC and to establish a deep neural network (DNN) model for patient risk prediction, while also developing a personalized nomogram model for predicting patient survival. In addition, sensitivity drugs for KIRC were screened, and a graph neural network (GNN) model was established to predict the targets of the drugs, in order to discover potential drug action sites and provide new treatment ideas for KIRC.

METHODS

We used the Cancer Genome Atlas (TCGA) database, International Cancer Genome Consortium (ICGC) database, and DrugBank database for our study. Differentially expressed genes (DEGs) were screened using TCGA data, and then a DNN-based risk prediction model was built and validated using ICGC data. Subsequently, the differences between high- and low-risk groups were analyzed and KIRC-sensitive drugs were screened, and finally a GNN model was trained using DrugBank data to predict the relevant targets of these drugs.

RESULTS

A prognostic model was built by screening 10 significantly different cuproptosis-related genes, the model had an AUC of 0.739 on the training set (TCGA data) and an AUC of 0.707 on the validation set (ICGC data), which demonstrated a good predictive performance. Based on the prognostic model in this paper, patients were also classified into high- and low-risk groups, and functional analyses were performed. In addition, 251 drugs were screened for sensitivity, and four drugs were ultimately found to have high sensitivity, with 5-Fluorouracil having the best inhibitory effect, and subsequently their corresponding targets were also predicted by GraphSAGE, with the most prominent targets including Cytochrome P450 2D6, UDP-glucuronosyltransferase 1A, and Proto-oncogene tyrosine-protein kinase receptor Ret. Notably, the average accuracy of GraphSAGE was 0.817 ± 0.013, which was higher than that of GAT and GTN.

CONCLUSION

Our KIRC risk prediction model, constructed using 10 cuproptosis-related genes, had good independent prognostic ability. In addition, we screened four highly sensitive drugs and predicted relevant targets for these four drugs that might treat KIRC. Finally, literature research revealed that four drug-target interactions have been demonstrated in previous studies and the remaining targets are potential sites of drug action for future research.

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.

Identification of a 5-Gene Cuproptosis Signature Predicting the Prognosis for Colon Adenocarcinoma Based on WGCNA

Background: Colorectal cancer is a highly aggressive malignant tumor that primarily affects the digestive system. It is frequently diagnosed at an advanced stage. Cuproptosis is a copper-dependent form cell death mechanism, distinct from all other known pathways underlying cell death, tumor progression, prognosis, and immune response. Although the role of cuproptosis in colorectal cancer has been investigated over time, there is still an urgent need to explore new methods and insights to understand its potential function. Methods: The Gene Expression Omnibus and The Cancer Genome Atlas gene expression data were systematically explored to investigate the role of cuproptosis in colon adenocarcinoma. The weighted gene coexpression network analysis was used to construct a gene coexpression network and identify the critical module and cuproptosis-related genes correlated with colon adenocarcinoma prognosis. A cuproptosis-related genes prognostic signature for colon adenocarcinoma was identified and validated. To validate the identified gene signature, quantitative reverse transcription-polymerase chain reaction was performed. Cell proliferation assays were analyzed by CCK8 and cell cycle detection. In addition, reactive oxygen species assay was also analyzed. Results: Five hub cuproptosis-related genes (Dihydrolipoamide S-acetyltransferase, Cyclin-dependent kinase inhibitor 2A, ATOX1, VEGFA, and ULK1) were screened and a prognostic risk model for predicting overall survival was established based on these genes. The model was successfully tested in the validation cohort and the GEPIA database. Colon adenocarcinoma patients were categorized into high-risk and low-risk groups based on risk scores. The study revealed that patients with higher risk scores were more likely to have a poor prognosis. Moreover, Dihydrolipoamide S-acetyltransferase was a tumor suppressor gene that can induce cell death and affected the redox reactions in the colon cancer cell line. Conclusions: These findings suggest that the newly identified 5-gene signature may serve as a more reliable prognostic factor than clinical factors such as age and stage of disease. These findings offer a theoretical foundation for further investigation into potential cuproptosis-related biomarkers for predicting colon adenocarcinoma prognosis in the future.

Copper homeostasis and cuproptosis in mitochondria

Mitochondria serve as sites for energy production and are essential for regulating various forms of cell death induced by metal metabolism, targeted anticancer drugs, radiotherapy and immunotherapy. Cuproptosis is an autonomous form of cell death that depends on copper (Cu) and mitochondrial metabolism. Although the recent discovery of cuproptosis highlights the significance of Cu and mitochondria, there is still a lack of biological evidence and experimental verification for the underlying mechanism. We provide an overview of how Cu and cuproptosis affect mitochondrial morphology and function. Through comparison with ferroptosis, similarities and differences in mitochondrial metabolism between cuproptosis and ferroptosis have been identified. These findings provide implications for further exploration of cuproptotic mechanisms. Furthermore, we explore the correlation between cuproptosis and immunotherapy or radiosensitivity. Ultimately, we emphasize the therapeutic potential of targeting cuproptosis as a novel approach for disease treatment.

NAA20 recruits Rin2 and promotes triple-negative breast cancer progression by regulating Rab5A-mediated activation of EGFR signaling

Triple-negative breast cancer (TNBC) is the most aggressive subtype with poor prognosis and high mortality. To improve the prognosis and survival of TNBC patients, it is necessary to explore new targets and signaling pathways to develop novel therapies for TNBC treatment. N-α-acetyltransferase 20 (NAA20) is one of the catalytic subunits of N-terminal acetyltransferase (NatB). It has been reported that NAA20 played a critical role in cancer progression. In this study, we found that NAA20 expression was markedly higher in TNBC tissues than in paracancerous normal tissues using The Cancer Genome Atlas (TCGA) analysis. This result was further confirmed by qRT-PCR and immunohistochemistry (IHC). Knockdown of NAA20 significantly inhibited TNBC cell viability by CCK8 and colony formation assays and cell migration and invasion by Transwell assays. Additionally, NAA20 knockdown decreased the expression of EGFR in TNBC cells. Upon stimulation with EGF and knockdown of NAA20, EGFR internalization and degradation were observed by confocal microscopy. The western blot results showed that NAA20 knockdown down-regulated PI3K, AKT, and mTOR phosphorylation. Next, we further explored the underlying molecular mechanisms of NAA20 by co-immunoprecipitation (Co-IP). The results suggested that there was an interacting relationship between NAA20 and Rab5A. Over-expression of NAA20 could potentiate the expression of Rab5A. Furthermore, the knockdown of Rab5A inhibited EGFR expression and the phosphorylation of downstream signaling targets. NAA20 over-expression offset the knockdown effect of Rab5A and activated EGFR signaling. Finally, we constructed a xenograft mouse model transfected TNBC cells to investigate the role of NAA20 in vivo. NAA20 knockdown markedly suppressed tumor growth and decreased tumor volume and weight. In conclusion, our study demonstrated that NAA20, a novel target of TNBC, could promote TNBC progression by regulating Rab5A-mediated activation of EGFR signaling.

Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in breast cancer

Introduction

Breast cancer (BC) is now the most common type of cancer in women. Disulfidptosis is a new regulation of cell death (RCD). RCD dysregulation is causally linked to cancer. However, the comprehensive relationship between disulfidptosis and BC remains unknown. This study aimed to explore the predictive value of disulfidptosis-related genes (DRGs) in BC and their relationship with the TME.

Methods

This study obtained 11 disulfidptosis genes (DGs) from previous research by Gan et al. RNA sequencing data of BC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO) databases. First, we examined the effect of DG gene mutations and copy number changes on the overall survival of breast cancer samples. We then used the expression profile data of 11 DGs and survival data for consensus clustering, and BC patients were divided into two clusters. Survival analysis, gene set variation analysis (GSVA) and ss GSEA were used to compare the differences between them. Subsequently, DRGs were identified between the clusters used to perform Cox regression and least absolute shrinkage and selection operator regression (LASSO) analyses to construct a prognosis model. Finally, the immune cell infiltration pattern, immunotherapy response, and drug sensitivity of the two subtypes were analyzed. CCK-8 and a colony assay obtained by knocking down genes and gene sequencing were used to validate the model.

Result

Two DG clusters were identified based on the expression of 11DGs. Then, 225 DRGs were identified between them. RS, composed of six genes, showed a significant relationship with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-RS shows a better prognosis and higher immunotherapy response than high-RS. A nomogram with perfect stability constructed using signature and clinical characteristics can predict the survival of each patient. CCK-8 and colony assay obtained by knocking down genes have demonstrated that the knockdown of high-risk genes in the RS model significantly inhibited cell proliferation.

Discussion

This study elucidates the potential relationship between disulfidptosis-related genes and breast cancer and provides new guidance for treating breast cancer.