Comprehensive analyses of PDHA1 that serves as a predictive biomarker for immunotherapy response in cancer

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.

Glutamine metabolism-related genes predict the prognostic risk of acute myeloid leukemia and stratify patients by subtype analysis

BACKGROUND

Acute myeloid leukemia (AML) is a genetically heterogeneous disease in which glutamine (Gln) contributes to AML progression. Therefore, this study aimed to identify potential prognostic biomarkers for AML based on Gln metabolism-related genes.

METHODS

Gln-related genes that were differentially expressed between Cancer Genome Atlas-based AML and normal samples were analyzed using the limma package. Univariate, least absolute shrinkage, selection operators, and stepwise Cox regression analyses were used to identify prognostic signatures. Risk score-based prognostic and nomogram models were constructed to predict the prognostic risk of AML. Subsequently, consistent cluster analysis was performed to stratify patients into different subtypes, and subtype-related module genes were screened using weighted gene co-expression network analysis.

RESULTS

Through a series of regression analyses, HGF, ANGPTL3, MB, F2, CALR, EIF4EBP1, EPHX1, and PDHA1 were identified as potential prognostic biomarkers of AML. Prognostic and nomogram models constructed based on these genes could significantly differentiate between high- and low-risk AML with high predictive accuracy. The eight-signature also stratified patients with AML into two subtypes, among which Cluster 2 was prone to a high risk of AML prognosis. These two clusters exhibited different immune profiles. Of the subtype-related module genes, the HOXA and HOXB family genes may be genetic features of AML subtypes.

CONCLUSION

Eight Gln metabolism-related genes were identified as potential biomarkers of AML to predict prognostic risk. The molecular subtypes clustered by these genes enabled prognostic risk stratification.

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.

A pan-cancer cuproptosis signature predicting immunotherapy response and prognosis

Background

Cuproptosis may represent a potential biomarker for predicting prognosis and immunotherapy response, but the available evidence is insufficient.

Methods

The multiple single-cell RNA sequencing (scRNA-seq) datasets were analyzed to investigate the specific occurrence of cuproptosis in distinct cell populations. Utilizing 28 scRNA-seq datasets, TCGA pan-cancer cohort, and 10 immunotherapy cohorts, we developed a cuproptosis signature (Cup.Sig). This signature was used to construct prediction models for immunotherapy response and identify potential prognostic biomarkers for pan-cancer using 11 different machine learning algorithms.

Results

Malignant cells demonstrate the higher cuproptosis scores in comparison to other cell types across diverse cancer types. The Cup.Sig exhibits significant associations with cancer hallmarks and immune cell response in multiple cancer types. Leveraging the Cup.Sig, the robust pan-cancer immunotherapy prediction model and prognostic biomarker have been established and validated using diverse datasets from various platforms.

Conclusions

We developed a pan-cancer cuproptosis signature for predicting survival and immunotherapy response.

A comparative cross-platform analysis of cuproptosis-related genes in human nonobstructive azoospermia: An observational study

This study aimed to identify novel biomarkers associated with cuproptosis in human nonobstructive azoospermia (NOA). We obtained 4 NOA microarray datasets (GSE145467, GSE9210, GSE108886, and GSE45885) from the NCBI Gene Expression Omnibus database and merged them into training set. Another NOA dataset (GSE45887) was used as validation set. Differentially expressed cuproptosis-related genes were identified from training set. Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted. Least absolute shrinkage and selection operator regression and support vector machine-recursive feature elimination were used to identify hub cuproptosis-related genes. We calculated the expression of the hub cuproptosis-related genes in both validation set and patients with NOA. Gene set variation analysis was used to explore their potential biological functions. The risk prediction model was built by logistic regression analysis and was evaluated in the validation set. Finally, we constructed a competing endogenous RNA network. The training set included 29 patents in the control group and 92 in the NOA group, and 10 cuproptosis-related differentially expressed genes were identified. Subsequently, we screened 6 hub cuproptosis-related genes (DBT, GCSH, NFE2L2, NLRP3, PDHA1, and SLC31A1) by least absolute shrinkage and selection operator regression and support vector machine-recursive feature elimination. GCSH, NFE2L2, NLRP3, and SLC31A1 expressed higher in NOA group than in control group (P < .05) in the validation set (4 patients in control and 16 in NOA groups), while the expression levels of GCSH, NFE2L2, NLRP3, PDHA1, and SLC31A1 were higher in NOA group than in control group (P < .05) in our patients (3 patients in control and 4 in NOA groups). The model based on the 6-gene signature showed superior performance with an AUC value of 0.970 in training set, while 1.0 in validation set. Gene set variation analysis revealed a higher enrichment score of "homologous recombination" in the high expression groups of the 6 hub genes. Finally, we constructed a competing endogenous RNA network and found hsa-miR-335-3p and hsa-miR-1-3p were the most frequently related to the 6 hub genes. DBT, GCSH, NFE2L2, NLRP3, PDHA1, and SLC31A1 may serve as predictors of cuproptosis and play important roles in the NOA pathogenesis.

A systematic overview of single-cell transcriptomics databases, their use cases, and limitations

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of transcriptomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Such platforms can help bridge the gap between computational and wet lab scientists through user-friendly web-based interfaces needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

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.

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

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

Cuproptosis in lung cancer: mechanisms and therapeutic potential

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

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

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

A Systematic Overview of Single-Cell Transcriptomics Databases, their Use cases, and Limitations

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of genomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Furthermore, we propose that bridging the gap between computational and wet lab scientists through user-friendly web-based platforms is needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

Cuproptosis-Related Gene Signature Contributes to Prognostic Prediction and Immunosuppression in Multiple Myeloma

Cuproptosis is a type of programmed cell death triggered by accumulation of intracellular copper which was considered closely related to tumor progression. The study of cuproptosis in multiple myeloma (MM) is however limited. To determine the prognostic significance of cuproptosis-related gene signature in MM, we interrogated gene expression and overall survival with other available clinical variables from public datasets. Four cuproptosis-related genes were included to establish a prognostic survival model by least absolute shrinkage and selection operator (LASSO) Cox regression analysis, which showed a good performance on prognosis prediction in both training and validation cohorts. Patients with higher cuproptosis-related risk score (CRRS) exhibited worse prognosis compared with lower risk score. Survival prediction capacity and clinical benefit were elevated after integrating CRRS to existing prognostic stratification system (International Staging System, ISS or Revised International Staging System, RISS) both on 3-year and 5-year survival. Based on CRRS groups, functional enrichment analysis and immune infiltration in bone marrow microenvironment revealed correlation between CRRS and immunosuppression. In conclusion, our study found that cuproptosis-related gene signature is an independent poor prognostic factor and functions negatively on immune microenvironment, which provides another perspective on prognosis assessment and immunotherapy strategy in MM.

Identification of cuproptosis-related diagnostic biomarkers in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with clinical and pathological heterogeneity. Recent studies have identified cuproptosis as a novel cell death mechanism. However, the role of cuproptosis-related genes in the pathogenesis of IPF is still unclear. Two IPF datasets of the Gene Expression Omnibus database were studied. Mann-Whitney U test, correlation analysis, functional enrichment analyses, single-sample gene set enrichment analysis, CIBERSORT, unsupervised clustering, weighted gene co-expression network analysis, and receiver operating characteristic curve analysis were used to conduct our research. The dysregulated cuproptosis-related genes and immune responses were identified between IPF patients and controls. Two cuproptosis-related molecular clusters were established in IPF, the high immune score group (C1) and the low immune score group (C2). Significant heterogeneity in immunity between clusters was revealed by functional analyses results. The module genes with the strongest correlation to the 2 clusters were identified by weighted gene co-expression network analysis results. Seven hub genes were found using the Cytoscape software. Ultimately, 2 validated diagnostic biomarkers of IPF, CDKN2A and NEDD4, were obtained. Subsequently, the results were validated in GSE47460. Our investigation illustrates that CDKN2A and NEDD4 may be valid biomarkers that were useful for IPF diagnosis and copper-related clustering.

Comprehensive exploration of the involvement of cuproptosis in tumorigenesis and progression of neuroblastoma

BACKGROUND

Copper-induced cell death, or "cuproptosis," as an apoptotic process, has recently received much attention in human diseases. Recent studies on cuproptosis have provided novel insights into the pathogenesis of various diseases, especially cancers. However, the association between neuroblastoma (NB) and cuproptosis in terms of their clinical outcomes, tumorigenesis, and treatment response remains unclear.

METHODS

To determine the role of cuproptosis in NB tumorigenesis and progression, this study employed a systematic technique to explore the characteristic patterns of 10 key cuproptosis-related genes (CUGs) in NB. Consensus clustering analysis of the TARGET and GEO databases divided the NB patients into two subgroups that showed different clinicopathological attributes, molecular patterns, survival outcomes, disease-associated pathways, tumor immune microenvironment (TIME) features, and treatment responses. Moreover, a cuproptosis scoring scheme was established, which divided the patients with NB into two groups with high scores and low scores as per the median score. Furthermore, this research developed a nomogram and risk signature on the basis of this cuproptosis score to better elucidate its function in predicting NB prognosis. In vitro experiments were carried out using Transwell Assay, HLECs tube formation assay, Colony formation assay, Western Blotting Assay, Immunohistochemical (IHC) Staining, Immunofluorescence (IF) Staining and Flow Cytometry Analysis.

RESULTS

The results demonstrated that the established cuproptosis score and prediction model could effectively distinguish between the individuals in low and high-risk groups and had a high predictive value. Lastly, bioinformatics analysis and in vitro experiments enabled the identification of PDHA1, a key CUG, which was involved in both DNA replication-related pathways and the cell cycle. It was also associated with tumorigenesis and progression of NB.

CONCLUSION

Cuproptosis, especially PDHA1, play a crucial role in the TIME characteristics, tumor progression, and long-term prognosis of NB. The patterns of cuproptosis assessed in this research may improve the understanding of the overall concept of NB tumorigenesis, thus facilitating the development of more effective therapeutic interventions.

Cuproptosis and cuproptosis-related genes: Emerging potential therapeutic targets in breast cancer

Breast cancer is one of the most common malignant tumors in women worldwide, and thus, it is important to enhance its treatment efficacy [1]. Copper has emerged as a critical trace element that affects various intracellular signaling pathways, gene expression, and biological metabolic processes [2], thereby playing a crucial role in the pathogenesis of breast cancer. Recent studies have identified cuproptosis, a newly discovered type of cell death, as an emerging therapeutic target for breast cancer treatment, thereby offering new hope for breast cancer patients. Tsvetkov's research has elucidated the mechanism of cuproptosis and uncovered the critical genes involved in its regulation [3]. Manipulating the expression of these genes could potentially serve as a promising therapeutic strategy for breast cancer treatment. Additionally, using copper ionophores and copper complexes combined with nanomaterials to induce cuproptosis may provide a potential approach to eliminating drug-resistant breast cancer cells, thus improving the therapeutic efficacy of chemotherapy, radiotherapy, and immunotherapy and eventually eradicating breast tumors. This review aims to highlight the practical significance of cuproptosis-related genes and the induction of cuproptosis in the clinical diagnosis and treatment of breast cancer. We examine the potential of cuproptosis as a novel therapeutic target for breast cancer, and we explore the present challenges and limitations of this approach. Our objective is to provide innovative ideas and references for the development of breast cancer treatment strategies based on cuproptosis.

Copper homeostasis and cuproptosis in tumor pathogenesis and therapeutic strategies

Copper is an indispensable micronutrient for the development and replication of all eukaryotes, and its redox properties are both harmful and beneficial to cells. An imbalance in copper homeostasis is thought to be involved in carcinogenesis. Importantly, cancer cell proliferation, angiogenesis, and metastasis cannot be separated from the effects of copper. Cuproposis is a copper-dependent form of cell death that differs from other existing modalities of regulatory cell death. The role of cuproptosis in the pathogenesis of the nervous and cardiovascular systems has been widely studied; however, its impact on malignant tumors is yet to be fully understood from a clinical perspective. Exploring signaling pathways related to cuproptosis will undoubtedly provide a new perspective for the development of anti-tumor drugs in the future. Here, we systematically review the systemic and cellular metabolic processes of copper and the regulatory mechanisms of cuproptosis in cancer. In addition, we discuss the possibility of targeting copper ion drugs to prolong the survival of cancer patients, with an emphasis on the most representative copper ionophores and chelators. We suggest that attention should be paid to the potential value of copper in the treatment of specific cancers.

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

Background

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

Methods

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

Results

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

Conclusion

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

Identification and validation of a novel cuproptosis-related stemness signature to predict prognosis and immune landscape in lung adenocarcinoma by integrating single-cell and bulk RNA-sequencing

Background

Cancer stem cells (CSCs) play vital roles in lung adenocarcinoma (LUAD) recurrence, metastasis, and drug resistance. Cuproptosis has provided a novel insight into the treatment of lung CSCs. However, there is a lack of knowledge regarding the cuproptosis-related genes combined with the stemness signature and their roles in the prognosis and immune landscape of LUAD.

Methods

Cuproptosis-related stemness genes (CRSGs) were identified by integrating single-cell and bulk RNA-sequencing data in LUAD patients. Subsequently, cuproptosis-related stemness subtypes were classified using consensus clustering analysis, and a prognostic signature was constructed by univariate and least absolute shrinkage operator (LASSO) Cox regression. The association between signature with immune infiltration, immunotherapy, and stemness features was also investigated. Finally, the expression of CRSGs and the functional roles of target gene were validated in vitro.

Results

We identified six CRSGs that were mainly expressed in epithelial and myeloid cells. Three distinct cuproptosis-related stemness subtypes were identified and associated with the immune infiltration and immunotherapy response. Furthermore, a prognostic signature was constructed to predict the overall survival (OS) of LUAD patients based on eight differently expressed genes (DEGs) with cuproptosis-related stemness signature (KLF4, SCGB3A1, COL1A1, SPP1, C4BPA, TSPAN7, CAV2, and CTHRC1) and confirmed in validation cohorts. We also developed an accurate nomogram to improve clinical applicability. Patients in the high-risk group showed worse OS with lower levels of immune cell infiltration and higher stemness features. Ultimately, further cellular experiments were performed to verify the expression of CRSGs and prognostic DEGs and demonstrate that SPP1 could affect the proliferation, migration, and stemness of LUAD cells.

Conclusion

This study developed a novel cuproptosis-related stemness signature that can be used to predict the prognosis and immune landscape of LUAD patients, and provided potential therapeutic targets for lung CSCs in the future.

Role of cuproptosis in understanding diseases

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

Cuproptosis illustrates tumor micro-environment features and predicts prostate cancer therapeutic sensitivity and prognosis

BACKGROUND

Prostate cancer (PCA) is a common malignant genitourinary tumor that significantly impacts patient survival. Cuproptosis, a copper-dependent programmed cell death mechanism, plays a vital role in tumor development, therapy resistance, and immune microenvironment regulation in PCA. However, research on cuproptosis in prostate cancer is still in its early stages.

METHODS

Using the publicly available datasets TCGA and GEO, we first acquired the transcriptome and clinical information of PCA patients. The expression of cuprotosis-related genes (CRG) was identified and a prediction model was established based on LASSO-COX method. The predictive performance of this model was evaluated based on Kaplan-Meier method. Using GEO datasets, we further confirmed the critical genes level in the model. Tumor responses to immune checkpoint (ICP) inhibitors were predicted based on Tumor Immune Dysfunction and Exclusion (TIDE) score. The Genomics of Drug Sensitivity in Cancer (GDSC) was utilized to forecast drug sensitivity in cancer cells, whereas the GSVA was employed to analyze enriched pathways related to the cuproptosis signature. Subsequently, the function of PDHA1 gene in PCA was verified.

RESULTS

A predictive risk model on basis of five cuproptosis-related genes (ATP7B, DBT, LIPT1, GCSH, PDHA1) were established. The progression free survival of low-risk group was obviously longer than the high-risk group, and exhibit better response to ICB therapy.Furthermore,PDHA1 is very important in the pathological process of PCA according to regressions analysis result, and the validation of external data sets were conducted. High PDHA1 expression patients with PCA not only had a shorter PFS and were less likely to benefit from ICB treatment, but they were also less responsive to multiple targeted therapeutic drugs. In preliminary research, PDHA1 knockdown significantly decreased the proliferation and invasion of PCA cells.

CONCLUSION

This study established a novel cuproptosis-related gene-based prostate cancer prediction model that accurately predicts the prognosis of PCA patients. The model benefits individualized therapy and can assist clinicians in making clinical decisions for PCA patients. Furthermore, our data show that PDHA1 promotes PCA cell proliferation and invasion while modulating the susceptibility to immunotherapy and other targeted therapies. PDHA1 can be regarded as an important target for PCA therapy. This study conforms to the standards of cancer research and is linguistically fluent and meets native language standards.

Integrative analysis revealed that distinct cuprotosis patterns reshaped tumor microenvironment and responses to immunotherapy of colorectal cancer

Background

Cuprotosis is a novel form of programmed cell death that involves direct targeting of key enzymes in the tricarboxylic acid (TCA) cycle by excess copper and may result in mitochondrial metabolic dysfunction. However, whether cuprotosis may mediate the tumor microenvironment (TME) and immune regulation in colorectal cancer (CRC) remains unclear.

Methods

Ten cuprotosis-related genes were selected and unsupervised consensus clustering was performed to identify the cuprotosis patterns and the correlated TME characteristics. Using principal component analysis, a COPsig score was established to quantify cuprotosis patterns in individual patients. The top 9 most important cuprotosis signature genes were analyzed using single-cell transcriptome data.

Results

Three distinct cuprotosis patterns were identified. The TME cell infiltration characteristics of three patterns were associated with immune-excluded, immune-desert, and immune-inflamed phenotype, respectively. Based on individual cuprotosis patterns, patients were assigned into high and low COPsig score groups. Patients with a higher COPsig score were characterized by longer overall survival time, lower immune cell as well as stromal infiltration, and greater tumor mutational burden. Moreover, further analysis demonstrated that CRC patients with a higher COPsig score were more likely to respond to immune checkpoint inhibitors and 5-fluorouracil chemotherapy. Single-cell transcriptome analysis indicated that cuprotosis signature genes recruited tumor-associated macrophages to TME through the regulation of TCA and the metabolism of glutamine and fatty acid, thus influencing the prognosis of CRC patients.

Conclusion

This study indicated that distinct cuprotosis patterns laid a solid foundation to the explanation of heterogeneity and complexity of individual TME, thus guiding more effective immunotherapy as well as adjuvant chemotherapy strategies.

Identification of cuproptosis hub genes contributing to the immune microenvironment in ulcerative colitis using bioinformatic analysis and experimental verification

Instruction

Ulcerative colitis (UC) can cause a variety of immune-mediated intestinal dysfunctions and is a significant model of inflammatory bowel disease (IBD). Colorectal cancer (CRC) mostly occurs in patients with ulcerative colitis. Cuproptosis is a type of procedural death that is associated with different types of diseases to various degrees.

Methods

We used a combination of bioinformatic prediction and experimental verification to study the correlation between copper poisoning and UC. We used the Gene Expression Omnibus database to obtain disease gene expression data and then identified relevant genes involved in various expression levels in normal and UC samples. The Kyoto Encyclopedia of Genes and Genomes pathway analysis was performed to cluster the genes that are highly responsible and find the central interaction in gene crosstalk. Notably, DLD, DLAT, and PDHA1 were present in high-scoring PPI networks. In addition, hub gene expression information in UC tissues was integrated to estimate the relationship between UC copper poisoning and the immune environment.

Results

In our study, the expression of DLD, DLAT, and PDHA1 in UC tissues was lower than that in normal tissues. The key genes associated with cuproptosis have therapeutic effects on immune infiltration. We verified the expression of DLD, DLAT, and PDHA1 using real-time quantitative polymerase chain reaction in mouse models of UC induced by DSS.

Discussion

Notably, this study clearly indicates that bioinformatic analysis performed to verify the experimental methods provides evidence that cuproptosis is associated with UC. This finding suggests that immune cell infiltration in UC patients is associated with cuproptosis. The key genes associated with cuproptosis can be helpful for discovering the molecular mechanism of UC, thus facilitating the improvement of UC treatment and preventing the associated CRC.

Cuproptosis: mechanisms and links with cancers

Cuproptosis was a copper-dependent and unique kind of cell death that was separate from existing other forms of cell death. The last decade has witnessed a considerable increase in investigations of programmed cell death, and whether copper induced cell death was an independent form of cell death has long been argued until mechanism of cuproptosis has been revealed. After that, increasing number of researchers attempted to identify the relationship between cuproptosis and the process of cancer. Thus, in this review, we systematically detailed the systemic and cellular metabolic processes of copper and the copper-related tumor signaling pathways. Moreover, we not only focus on the discovery process of cuproptosis and its mechanism, but also outline the association between cuproptosis and cancers. Finally, we further highlight the possible therapeutic direction of employing copper ion ionophores with cuproptosis-inducing functions in combination with small molecule drugs for targeted therapy to treat specific cancers.

Insights into prognosis and immune infiltration of cuproptosis-related genes in breast cancer

Introduction

Breast cancer (BC) has been ranking first in incidence and the leading cause of death among female cancers worldwide based on the latest report. Regulated cell death (RCD) plays a significant role in tumor initiation and provides an important target of cancer treatment. Cuproptosis, a novel form of RCD, is ignited by mitochondrial stress, particularly the lipoylated mitochondrial enzymes aggregation. However, the role of cuproptosis-related genes (CRGs) in tumor generation and progression remains unclear.

Methods

In this study, the mRNA expression data of CRGs in BC and normal breast tissue were extracted from TCGA database, and protein expression patterns of these CRGs were analyzed using UALCAN. The prognostic values of CRGs in BC were explored by using KaplanMeier plotter and Cox regression analysis. Genetic mutations profiles were evaluated using the cBioPortal database. Meanwhile, we utilized CIBERSORT and TIMER 2.0 database to perform the correlation analysis between CRGs and immune cell infiltration.

Results

Our results indicated that CRGs expression is significantly different in BC and normal breast tissues. Then we found that upregulated PDHA1 expression was associated with worse endpoint of BC. Moreover, we also performed immune infiltration analysis of CRGs, and demonstrated that PDHA1 expression was closely related to the infiltration levels of CD4+ memory T cell, macrophage M0 and M1 cell and mast cell in BC.

Conclusions

Our results demonstrated the prognostic and immunogenetic values of PDHA1 in BC. Therefore, PDHA1 can be an independent prognostic biomarker and potential target for immunotherapy of BC.

Prognostic Significance of Cuproptosis-Related Gene Signatures in Breast Cancer Based on Transcriptomic Data Analysis

Breast cancer (BRCA) remains a serious threat to women's health, with the rapidly increasing morbidity and mortality being possibly due to a lack of a sophisticated classification system. To date, no reliable biomarker is available to predict prognosis. Cuproptosis has been recently identified as a new form of programmed cell death, characterized by the accumulation of copper in cells. However, little is known about the role of cuproptosis in breast cancer. In this study, a cuproptosis-related genes (CRGs) risk model was constructed, based on transcriptomic data with corresponding clinical information relating to breast cancer obtained from both the TCGA and GEO databases, to assess the prognosis of breast cancer by comprehensive bioinformatics analyses. The CRGs risk model was constructed and validated based on the expression of four genes (NLRP3, LIPT1, PDHA1 and DLST). BRCA patients were then divided into two subtypes according to the CRGs risk model. Furthermore, our analyses revealed that the application of this risk model was significantly associated with clinical outcome, immune infiltrates and tumor mutation burden (TMB) in breast cancer patients. Additionally, a new clinical nomogram model based on risk score was established and showed great performance in overall survival (OS) prediction, confirming the potential clinical significance of the CRGs risk model. Collectively, our findings revealed that the CRGs risk model can be a useful tool to stratify subtypes and that the cuproptosis-related signature plays an important role in predicting prognosis in BRCA patients.

A novel cuproptosis-related subtypes and gene signature associates with immunophenotype and predicts prognosis accurately in neuroblastoma

Background

Neuroblastoma (NB) is the most frequent solid tumor in pediatrics, which accounts for roughly 15% of cancer-related mortality in children. NB exhibited genetic, morphologic, and clinical heterogeneity, which limited the efficacy of available therapeutic approaches. Recently, a new term 'cuproptosis' has been used to denote a unique biological process triggered by the action of copper. In this instance, selectively inducing copper death is likely to successfully overcome the limitations of conventional anticancer drugs. However, there is still a gap regarding the role of cuproptosis in cancer, especially in pediatric neuroblastoma.

Methods

We characterized the specific expression of cuproptosis-related genes (CRGs) in NB samples based on publicly available mRNA expression profile data. Consensus clustering and Lasso-Cox regression analysis were applied for CRGs in three independent cohorts. ESTIMATE and Xcell algorithm was utilized to visualize TME score and immune cell subpopulations' relative abundances. Tumor Immune Dysfunction and Exclusion (TIDE) score was used to predict tumor response to immune checkpoint inhibitors. To decipher the underlying mechanism, GSVA was applied to explore enriched pathways associated with cuproptosis signature and Connectivity map (CMap) analysis for drug exploration. Finally, qPCR verified the expression levels of risk-genes in NB cell lines. In addition, PDHA1 was screened and further validated by immunofluorescence in human clinical samples and loss-of-function assays.

Results

We initially classified NB patients according to CRGs and identified two cuproptosis-related subtypes that were associated with prognosis and immunophenotype. After this, a cuproptosis-related prognostic model was constructed and validated by LASSO regression in three independent cohorts. This model can accurately predict prognosis, immune infiltration, and immunotherapy responses. These genes also showed differential expression in various characteristic groups of all three datasets and NB cell lines. Loss-of-function experiments indicated that PDHA1 silencing significantly suppressed the proliferation, migration, and invasion, in turn, promoted cell cycle arrest at the S phase and apoptosis of NB cells.

Conclusions

Taken together, this study may shed light on new research areas for NB patients from the cuproptosis perspective.