Comprehensive Analysis of Cuproptosis-Related Genes in Immune Infiltration and Prognosis in Melanoma

Copper in melanoma: At the crossroad of protumorigenic and anticancer roles

Copper is an essential micronutrient that is a cofactor for various enzymes involved in multiple cellular processes. Melanoma patients have high serum copper levels, and elevated copper concentrations are found in melanoma tumors. Copper influences the activity of several melanoma-related proteins involved in cell survival, proliferation, pigmentation, angiogenesis, and metastasis. Targeting these processes with copper chelators has shown efficacy in reducing tumor growth and overcoming drug resistance. In contrast, excessive copper can also have detrimental effects when imported into melanoma cells. Multiple distinct cellular effects of copper overload, including the induction of different types of cell death, have been reported. Cuproptosis, a novel type of copper-dependent cell death, has been recently described and is associated with the metabolic phenotype. Melanoma cells can switch between glycolysis and oxidative phosphorylation, which are crucial for tumor growth and drug resistance. In this respect, metabolic plasticity might be exploited for the use of copper-delivery strategies, including repurposing of disulfiram, which is approved for the treatment of noncancer patients. In addition, the development of nanomedicines can improve the targeted delivery of copper to melanoma cells and enable the use of these drugs alone or in combination as copper has been shown to complement targeted therapy and immunotherapy in melanoma cells. However, further research is needed to explore the specific mechanisms of both copper restriction and excess copper-induced processes and determine effective biomarkers for predicting treatment sensitivity in melanoma patients. In this review, we discuss the dual role of copper in melanoma biology.

Identification of a long non-coding RNA signature associated with cuproptosis for prognosis and immunotherapy response prediction in patients with lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD), the most common histotype of lung cancer, exhibits high heterogeneity due to molecular variations. Cuproptosis is a newly discovered type of cell death that is linked to copper metabolism and long non-coding RNAs (lncRNAs) may play a significant role in this process. We conducted a comprehensive analysis of lncRNA related to cuproptosis and identified a CRLscore to predict the prognosis and immune landscape for LUAD patients.

METHODS

The LUAD patient cohort obtained from TCGA database was divided into training and validation sets. A range of statistical methods were employed to identify lncRNAs associated with cuproptosis. Multivariate Cox regression was then utilized to develop the CRLscore, which was further used to construct and evaluate a nomogram. Additionally, we investigated the biological functions, gene mutations, and immune landscape.

RESULTS

A CRLscore, comprising six cuproptosis-related lncRNAs, was developed to stratify patients into high- and low-risk groups. The CRLscore demonstrated its ability to independently predict prognosis in both the training set and the validation set. Utilizing the CRLscore, we constructed a nomogram that exhibited favorable predictive efficiency. Furthermore, the cuproptosis-related lncRNAs exhibited associations with important signaling pathways such as p53 signaling, MYC Targets V1, and G2M Checkpoint. Notably, the CRLscore displayed substantial differences in somatic mutations and immune landscape. Finally, qRT-PCR results showed the significant differential expression of five cuproptosis-related lncRNAs between LUAD and normal cells.

CONCLUSION

The CRLscore could serve as a potential prognostic indicator and may predict the response to immunotherapy in LUAD patients.

CDKN2A, a key gene in copper-induced cell death model, influencing melanoma invasion and apoptosis

Skin cutaneous melanoma (SKCM) is one of the most lethal cancers translating into 75% of skin cancer-related deaths. Despite the advances in SKCM management and treatment strategies, the overall survival of patients remains unsatisfactory due to the metastatic properties of SKCM as well as the absence of effective prognostic biomarkers. Recent studies have shown that overload copper renders accumulation of mitochondrial proteins and fuels a form of cell death at odds with known death mechanisms and is hinged on mitochondrial respiration, the so-called cuproptosis. However, the exact role of cuproptosis in SKCM development and progression is unknown, and painting a clear picture of its functions in SKCM is fraught with challenges. A more systematic investigation is justified. In this study, we were posed to dissect the clout and latent regulatory mechanisms of cuproptosis-related genes (CRGs) in reining in SKCM progression. Also, we identified three CRGs that stood out were used to construct a prognostic model, which could be employed to predict the prognosis of patients with SKCM. Finally, through pan-cancer analysis, we found that the four cuproptosis key genes play a role in multiple tumors, suggesting that cuproptosis may impact tumor progression at the pan-cancer level. Taken together, these findings may not only contribute to the development of treatment strategies but also provide clues for treatment decision-making.

Cuproptosis-related genes signature could predict prognosis and the response of immunotherapy in cervical cancer

Background

A lot of studies have shown a close relationship between cuproptosis and cancer. The main purpose of this study is to analyze the impact of cuproptosis on cervical cancer (CC).

Methods

Using The Cancer Genome Atlas (TCGA) public database, we analyzed the genetic correlation, expression, and prognostic value of 25 cuproptosis-related genes (CRGs) in CC. A least absolute shrinkage and selection operator (LASSO) risk regression model was constructed to compare the changes in associated pathways, prognosis, immune infiltration, and antibody programmed cell death-ligand 1 (anti-PD-L1) treatment response of the high- and low-risk groups. In addition, we collected CC tissue samples before and after radiotherapy for ribonucleic acid (RNA) sequencing, and analyzed the relationship between CRGs and radiotherapy.

Results

The results showed CRGs were differentially expressed and were associated with multiple metabolic pathways. High expression of COX7B, PIH1D2, NDUFA1, NDUFA2 and NDUFB1 indicated a better prognosis. CRGs signature could predict prognosis (P<0.001) and affect immune infiltration. The prognosis was better in the low-risk group, while the high-risk group was more correlated with PD-L1. SLC25A5 downregulated expression (P=0.001) and SLC6A3 upregulated (P=0.02) after radiotherapy. SLC25A5 was related to the degree of differentiation of CC; the worse the differentiation, the higher the expression.

Conclusions

CRGs may further affect patient prognosis and response to immunotherapy by influencing metabolic pathways and immune infiltration. Radiation could alter the expression of CRGs, which may have potential research value in evaluating the efficacy of radiotherapy.

Sensitivity of renal cell carcinoma to cuproptosis: a bioinformatics analysis and experimental verification

Purpose: Targeting cuproptosis is considered as a promising therapeutic strategy for the prevention of tumors. However, the potential role of cuproptosis and its related genes in clear cell renal cell carcinoma (ccRCC) remains elusive. The present study aims to explore the sensitivity of ccRCC to cuproptosis and its underlying mechanism. Methods: Cuproptosis differential genes (CDGs) were extracted using the GSE53757 and GSE66272 datasets. A comprehensive analysis of the role of CDGs was conducted through multiple public databases and experiments. Results: It was found that cuproptosis inducer elesclomol significantly induced cell death in 786-O and A498 cells. FDX and DLAT exhibited significantly low expression, which were independent prognostic factors for poor survival, and had a strong positive correlation in ccRCC patients. Functional analysis of differentially expressed genes positively or negatively correlated with both FDX1 and DLAT indicated that acetyl-CoA biosynthetic process and acetyl-CoA metabolic process were remarkably affected. In ccRCC patients, the methylation levels and sites of FDX1 and DLAT genes were dramatically correlated with overall survival (OS). The expressions of FDX1 and DLAT were closely related to immune infiltration and immune checkpoints. Docking results indicated that mitotane, adicicol and dihydrolipoic acid might be potential drug targets for FDX1 and DLAT. Conclusions: Overall, the present study demonstrates the sensitivity of ccRCC to cuproptosis, and targeting the combination of FDX1 and DLAT may be a novel therapeutic strategy to induce cuproptosis in ccRCC.

AI-driven eyelid tumor classification in ocular oncology using proteomic data

Eyelid tumors pose diagnostic challenges due to their diverse pathological types and limited biopsy materials. This study aimed to develop an artificial intelligence (AI) diagnostic system for accurate classification of eyelid tumors. Utilizing mass spectrometry-based proteomics, we analyzed proteomic data from eight tissue types and identified eighteen novel biomarkers based on 233 formalin-fixed, paraffin-embedded (FFPE) samples from 150 patients. The 18-protein model, validated by an independent cohort (99 samples from 60 patients), exhibited high accuracy (84.8%), precision (86.2%), and recall (84.8%) in multi-class classification. The model demonstrated distinct clustering of different lesion types, as visualized through UMAP plots. Receiver operator characteristic (ROC) curve analysis revealed strong predictive ability with area under the curve (AUC) values ranging from 0.80 to 1.00. This AI-based diagnostic system holds promise for improving the efficiency and precision of eyelid tumor diagnosis, addressing the limitations of traditional pathological methods.

Construction of a novel copper-induced-cell-death-related gene signature for prognosis in colon cancer, with focus on KIF7

BACKGROUND

Colon cancer (CC) is a leading cause of cancer-related mortality worldwide. Accurate prognostic markers are essential for patient risk stratification and personalized treatment. Copper-induced cell-death-related genes (CRG) have emerged as potential players in cancer prognosis, yet their role in CC remains unclear.

METHODS

This study aimed to comprehensively evaluate the expression of CRG and their roles in CC using gene expression and clinical data from TCGA and GEO databases. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses identified prognostic genes, leading to the construction of a CRG prognostic signature. The signature's predictive accuracy was validated using Kaplan-Meier survival curves, Receiver Operating Characteristic (ROC) curves, and a nomogram model. Additionally, we conducted experiments including immunofluorescence staining and cellular assays to validate the key genes' biological functions.

RESULTS

A 12-gene CRG signature was significantly associated with overall survival in CC patients. The high-risk group, as classified by median risk score, exhibited significantly shorter survival times compared to the low-risk group. The signature's predictive accuracy was further confirmed with Area Under the Curve (AUC) scores exceeding 0.75 in TCGA and GSE17536 cohorts. Notably, the risk score was significantly correlated with immune checkpoints, chemotherapy sensitivity, and tumor microenvironment. Furthermore, the risk score showed a strong association with immunotherapy response in patients from GSE78220 and GSE39688 cohorts. Bioinformatics analysis of KIF7, a key gene within the signature, revealed its upregulation in CC and significant associations with tumor mutation burden, microsatellite instability, and immune cell infiltration across various cancers. Experiments confirmed that KIF7 was upregulated in CC and its knockdown reduced cell proliferation, migration, and invasion.

CONCLUSION

The CRG prognostic signature can effectively predict overall survival, immune microenvironment and chemotherapy response in CC. KIF7, as a potential prognostic marker, has significant potential for the prediction and treatment of CC.

A New Cuproptosis-Related lncRNAs Model for Predicting the Prognosis of Hepatitis B Virus-Associated Hepatocellular Carcinoma and Experimental Validation of LINC01269

Background

Hepatocellular carcinoma (HCC) triggered by Hepatitis B virus (HBV) remains a significant clinical challenge, necessitating novel therapeutic interventions. Copper ionophores, recognized for introducing an innovative type of programmed cell death termed cuproptosis, present promising potentials for cancer therapy. Nevertheless, The role of cuproptosis-related lncRNAs (CRLRs) in HBV-HCC has not been clearly elucidated.

Methods

This study utilised univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariable Cox regression analyses to establish a signature for CRLRs in HBV-HCC. This prognostic model was validated with an independent internal validation cohort, combined with clinical parameters, and used to construct a nomogram for patient survival predictions. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were employed to explore associated biological pathways. Additionally, a protein-protein interaction (PPI) network was developed, and implications for tumour mutational burden (TMB) and drug response were examined. A comprehensive bioinformatics analysis of these hub CRLRs was performed, followed by experimental validation through quantitative real-time PCR (qRT-PCR) and functional cellular assays.

Results

The nomogram showed high predictive accuracy for HBV-HCC patient survival. GO and GSEA analyses indicated that these lncRNAs are involved in pathways related to cancer and oestrogen metabolism. A PPI network consisting of 201 nodes and 568 edges was developed, and the TMB and drug response differed significantly between high- and low-risk groups. Analyses identified three hub CRLRs, SOS1-IT1, AC104695.3, and LINC01269, which were significantly differentially expressed in HCC tissues. In vitro, LINC01269 was found to enhance HCC cell proliferation, invasion, and migration.

Conclusion

The first systematic exploration of the roles of CRLRs in HBV-HCC demonstrates their critical involvement in the disease's pathogenesis and possible therapeutic implication. The distinct expression patterns and significant biological pathways suggest that these lncRNAs may facilitate novel therapeutic targets.

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.

Unveiling Cuproptosis: Mechanistic insights, roles, and leading advances in oncology

Copper, a vital micronutrient, performs essential functions in numerous biological settings. Its disrupted metabolism is implicated in both the initiation of tumors and therapeutic interventions for cancer, underscoring the critical necessity of preserving copper homeostasis. Cuproptosis, a regulated cell death (RCD) modulated by copper, is activated in response to elevated copper concentrations, prompting an investigation into its implication in oncogenesis. Within this review, an exploration is conducted into copper dynamics and homeostasis maintenance within cells. Furthermore, it delves into the mechanisms underlying cuproptosis and its interplay with signaling pathways implicated in cancer. The potential synergy between cuproptosis and ferroptosis and its impact on tumor immunomodulation is discussed. Additionally, promising avenues for addressing cuproptosis in cancer involve assessing the utility of copper chelators and ionophores. By addressing pressing questions surrounding cuproptosis and outlining its pivotal role in cancer pathogenesis and treatment, this review propounds targeting cuproptosis as a promising frontier in antitumor therapy, potentially revolutionizing cancer treatment strategies.

Copper-Based Composites Nanoparticles Improve Triple-Negative Breast Cancer Treatment with Induction of Apoptosis-Cuproptosis and Immune Activation

The synergistic effect of apoptosis and cuproptosis, along with the activation of the immune system, presents a promising approach to enhance the efficacy against triple-negative breast cancer (TNBC). Here, two prodrugs are synthesized: a reactive oxygen species (ROS)-responsive prodrug PEG-TK-DOX and a glutathione (GSH)-responsive prodrug PEG-DTPA-SS-CPT. These prodrugs are self-assembled and chelated Cu2+ to prepare nanoparticle PCD@Cu that simultaneously loaded doxorubicin (DOX), camptothecin (CPT), and Cu2+. The elevated levels of ROS and GSH in TNBC cells disrupted the PCD@Cu structure, leading to the release of Cu+, DOX, and CPT and the depletion of GSH. DOX and CPT triggered apoptosis with immunogenic cell death (ICD) in TNBC cells. Simultaneously, PCD@Cu downregulated the expression of copper transporting ATPase 2 (ATP7B), causing a significant accumulation of copper ions in TNBC cells. This further induced the aggregation of lipoylated dihydrolipoamide S-acetyltransferase (DLAT) and downregulation of iron-sulfur (Fe-S) cluster proteins, ultimately leading to cuproptosis and ICD in TNBC. In vitro and in vivo experiments confirmed that PCD@Cu induced apoptosis and cuproptosis in TNBC and activated the immune system, demonstrating strong anti-tumor capabilities. Moreover, PCD@Cu exhibited an excellent biosafety profile. Overall, this study provides a promising strategy for effective TNBC therapy.

Copper homeostasis and copper-induced cell death in tumor immunity: implications for therapeutic strategies in cancer immunotherapy

Copper is an important trace element for maintaining key biological functions such as cellular respiration, nerve conduction, and antioxidant defense. Maintaining copper homeostasis is critical for human health, and its imbalance has been linked to various diseases, especially cancer. Cuproptosis, a novel mechanism of copper-induced cell death, provides new therapeutic opportunities for metal ion regulation to interact with cell fate. This review provides insights into the complex mechanisms of copper metabolism, the molecular basis of cuproptosis, and its association with cancer development. We assess the role of cuproptosis-related genes (CRGs) associated with tumorigenesis, their importance as prognostic indicators and therapeutic targets, and the impact of copper homeostasis on the tumor microenvironment (TME) and immune response. Ultimately, this review highlights the complex interplay between copper, cuproptosis, and cancer immunotherapy.

Identification of SLC31A1 as a prognostic biomarker and a target for therapeutics in breast cancer

Copper-induced cell death is regulated through protein lipoylation, which is critical for gene expression and phenotypic regulation. Neverless, the role of Cuproptosis-related genes in breast cancer (BC) remains unknown. This study aimed to construct a prognostic signature based on the expression of Cuproptosis-related genes in order to guide the diagnosis and treatment for BC. Cuproptosis-related genes prognostic signature has ata of 1250 BC tissues and 583 normal breast tissues were obtained from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), and GEO GSE65212. The prognostic signature was established and evaluated with nineteen Cuproptosis-related genes. A series of in silico analyses based on SLC31A1, included expression analysis, independent prognostic analysis, correlation analysis, immune-related analysis and survival analysis. Finally, a series of cell experiments (including quantitative real-time polymerase chain reaction and western blot), and mice experiments were applied to evaluate the impact of SLC31A1 on BC. Cuproptosis-related genes prognostic signature has good predictive promising for survival in BC patients. We discovered that SLC31A1SLC31A1 was overexpressed in BC and was its independent prognostic factor. High expression of the SLC31A1 was correlated with poor prognosis and immune infiltrating of BC. SLC31A1 expression is associated with immune, chemotherapeutic and targeted therapy outcomes in BC. The proliferation, migration, and invasiveness of Her2 + enriched BC cells were decreased by SLC31A1 knockdown, also resulting in a decrease in tumor volume in mouse model. SLC31A1 is a candidate biomarker or therapeutic target in precision oncology, with diagnostic and prognostic significance in BC.

Repositioning fluphenazine as a cuproptosis-dependent anti-breast cancer drug candidate based on TCGA database

Breast cancer is one of the most prevalent malignancies among women. Enhancing the prognosis is an effective approach to enhance the survival rate of breast cancer. Cuproptosis, a copper-dependent programmed cell death process, has been associated with patient prognosis. Inducing cuproptosis is a promising approach for therapy. However, there is currently no anti-breast cancer drug that induces cuproptosis. In this study, we repositioned the clinical drug fluphenazine as a potential agent for breast cancer treatment by inducing cuproptosis. Firstly, we utilized the Cancer Genome Atlas (TCGA) database and Connectivity Map (CMap) database to identify 22 potential compounds with anti-breast cancer activity through inducing cuproptosis. Subsequently, our findings demonstrated that fluphenazine effectively suppressed the viability of MCF-7 cells. Fluphenazine also significantly inhibited the viability of triple negative breast cancer cells MDA-MB-453 and MDA-MB-231. Furthermore, our study revealed that fluphenazine significantly down-regulated the expression of potential prognostic biomarkers associated with cuproptosis, increased copper ion levels, and reduced intracellular pyruvate accumulation. Additionally, it up-regulated the expression of FDX1 at both the mRNA and protein levels, which has been reported to play a crucial role in the induction of cuproptosis. These findings suggest that fluphenazine has the potential to be used as an anti-breast cancer drug by inducing cuproptosis. Therefore, this research provides an insight for the development of novel cuproptosis-dependent anti-cancer agents.

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.

A cuproptosis-related prognostic signature for guiding clinical diagnosis and treatment in uveal melanoma patients

Background

Cuproptosis, one of the most recently discovered forms of cell death, is induced by the disruption of copper binding to the mitochondrial respiratory acylation components. However, the mechanism underlying cuproptosis in uveal melanoma (UM) has not yet been adequately studied.

Methods

RNA and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed cuproptosis-related genes were identified by R software. A prognostic signature was constructed by applying LASSO regression and Cox regression models. The associations between the signature and the immune microenvironment, overall survival, and drug sensitivity were studied. In addition, qPCR and Western blotting were performed on UM cells and RPE cell lines to verify the expression levels of the genes encoding dihydrolipoamide dehydrogenase (DLD) and dihydrolipoamide S-succinyltransferase (DLST) in UM cases.

Results

Using a cuproptosis-related prognostic signature, UM samples were classified into high- and low-risk groups. A significant difference in overall survival between the two risk groups was evident. Receiver operating characteristic curves demonstrated that the signature is a reliable predictor of prognosis. Immune cell infiltration, drug sensitivity, and immune checkpoint expression were analysed. Significant immune difference between the two high-risk groups was found, and the high expression of immune checkpoints in high-risk groups suggests significant immunotherapy potential. In addition, drug sensitivity analysis experiments suggest that erlotinib may be a potential treatment for high-risk patients. The results of in vitro experiments confirmed that DLD and DLST had higher expression levels in UM cell lines.

Conclusions

The prognostic signature developed in this study is a reliable biomarker for predicting the prognosis of UM and may serve as a tool for personalised treatment of patients with UM.

Comprehensive analysis of cuproptosis-related ceRNA network and immune infiltration in diabetic kidney disease

Background

Diabetic kidney disease (DKD) is the primary contributor to renal failure and poses a severe threat to human health. Accumulating studies demonstrated that competing endogenous RNA (ceRNA) network is involved in cuproptosis and DKD progression. However, the role of cuproptosis-associated ceRNA network and immune infiltration in DKD remains largely unclear. This study aimed to investigate the cuproptosis-related ceRNA regulation network and immune infiltration in DKD.

Methods

The rat model of DKD was induced by combining the nephrectomy of the left kidney, high-fat diet, and streptozotocin. Differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs) between normal and DKD rats were obtained. DEGs were intersected with cuproptosis-related genes (CRGs) to obtain DE-CRGs. LncRNAs and miRNAs were predicted based on the DE-CRGs, and they were intersected with DEMs and DELs, respectively. Subsequently, a cuproptosis-associated lncRNA-miRNA-mRNA network was established in DKD. In addition, the relative proportion of 22 infiltrating immune cell types in each sample was calculated, and the relationship between hub DE-CRGs and immune cells was explored.

Results

In total, there were 429 DEGs, 22 DEMs, and 48 DELs between CON and MOD groups. Then, 73 DE-CRGs were obtained, which were significantly enriched in 22 pathways, such as MAPK signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. In addition, a core cuproptosis-related ceRNA network that included one lncRNA (USR0000B2476D), one miRNA (miR-34a-3p), and eight mRNAs (Mmp9, Pik3c3, Prom1, Snta1, Slc51b, Ntrk3, Snca, Egf) was established. In addition, 18 hub DE-CRGs were obtained. CIBERSORT algorithms showed that resting dendritic cells and resting NK cells were more infiltrated whereas regulatory T cells were less infiltrated in DKD rats than in normal rats. Spearman's correlation analysis revealed that hub DE-CRGs showed significant positive or negative correlations with naive B cells, regulatory T cells, resting NK cells, M0 macrophages, resting dendritic cells, and resting mast cells.

Conclusion

A ceRNA network was comprehensively constructed, and 18 hub DE-CRGs were obtained, which will provide novel insights into the pathologic mechanism elucidation and targeted therapy development of DKD.

Mechanisms associated with cuproptosis and implications for ovarian cancer

Ovarian cancer, a profoundly fatal gynecologic neoplasm, exerts a substantial economic strain on nations globally. The formidable challenge of its frequent relapse necessitates the exploration of novel cytotoxic agents, efficacious antineoplastic medications with minimal adverse effects, and strategies to surmount resistance to primary chemotherapeutic agents. These endeavors aim to supplement extant pharmacological interventions and elucidate molecular mechanisms underlying induced cytotoxicity, distinct from conventional therapeutic modalities. Recent scientific research has unveiled a novel form of cellular demise, known as copper-death, which is contingent upon the intracellular concentration of copper. Diverging from conventional mechanisms of cellular demise, copper-death exhibits a pronounced reliance on mitochondrial respiration, particularly the tricarboxylic acid (TCA) cycle. Tumor cells manifest distinctive metabolic profiles and elevated copper levels in comparison to their normal counterparts. The advent of copper-death presents alluring possibilities for targeted therapeutic interventions within the realm of cancer treatment. Hence, the primary objective of this review is to present an overview of the proteins and intricate mechanisms associated with copper-induced cell death, while providing a comprehensive summary of the knowledge acquired regarding potential therapeutic approaches for ovarian cancer. These findings will serve as valuable references to facilitate the advancement of customized therapeutic interventions for ovarian cancer.

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.

The role of cuproptosis-related genes in pan-cancer and the development of cuproptosis-related risk model in colon adenocarcinoma

Cancer is widely regarded as a leading cause of death in humans, with colon adenocarcinoma (COAD) ranking among the most prevalent types. Cuproptosis is a novel form of cell death mediated by protein lipoylation. Cuproptosis-related genes (CRGs) participate in tumourigenesis and development. Their role in pan-cancer and COAD require further investigation. This study comprehensively evaluated the relationship among CRGs, pan-cancer, and COAD. Our research revealed the differential expression of CRGs and the cuproptosis potential index (CPI) between normal and tumour tissues, and further explored the correlation of CRGs or CPI with prognosis, immune infiltration, tumor mutant burden(TMB), microsatellite instability (MSI), and drug sensitivity in pan-cancer. Gene set enrichment analysis (GSEA) revealed that oxidative phosphorylation and fatty acid metabolism pathways were significantly enriched in the high CPI group of most tumours. FDX1 and CDKN2A were chosen for further exploration, and we found an independent association between FDX1 and CDKN2A and prognosis, immune infiltration, TMB, and MSI in pan-cancer. Furthermore, a prognostic risk model based on the association between CRGs and COAD was built, and the correlations between the risk score and prognosis, immune-related characteristics, and drug sensitivity were analysed. COAD was then divided into three subtypes using cluster analysis, and the differences among the subtypes in prognosis, CPI, immune-related characteristics, and drug sensitivity were determined. Due to the level of LIPT1 was notably positive related with the risk score, the cytological identification was carried out to identify the association of LIPT1 with proliferation and migration of colon cancer cells. In summary, CRGs can be used as potential prognostic biomarkers to predict immune infiltration levels in patients with pan-cancer. In addition, the risk model could more accurately predict the prognosis and immune infiltration levels of COAD and better guide the direction of clinical medication. Thus, FDX1, CDKN2A, and LIPT1 may serve as prospective new targets for cancer therapy.

Superior cuproptotic efficacy of diethyldithiocarbamate-Cu4O3 nanoparticles over diethyldithiocarbamate-Cu2O nanoparticles in metastatic hepatocellular carcinoma

Metastatic hepatocellular carcinoma (HC) is a serious health concern. The stemness of cancer stem cells (CSCs) is a key driver for HC tumorigenesis, apoptotic resistance, and metastasis, and functional mitochondria are critical for its maintenance. Cuproptosis is Cu-dependent non-apoptotic pathway (mitochondrial dysfunction) via inactivating mitochondrial enzymes (pyruvate dehydrogenase "PDH" and succinate dehydrogenase "SDH"). To effectively treat metastatic HC, it is necessary to induce selective cuproptosis (for halting cancer stemness genes) with selective oxidative imbalance (for increasing cell susceptibility to cuproptosis and inducing non-CSCs death). Herein, two types of Cu oxide nanoparticles (Cu4O3 "C(I + II)" NPs and Cu2O "C(I)" NPs) were used in combination with diethyldithiocarbamate (DD, an aldehyde dehydrogenase "ALDH" inhibitor) for comparative anti-HC investigation. DC(I + II) NPs exhibited higher cytotoxicity, mitochondrial membrane potential, and anti-migration impact than DC(I) NPs in the treated human HC cells (HepG2 and/or Huh7). Moreover, DC(I + II) NPs were more effective than DC(I) NPs in the treatment of HC mouse groups. This was mediated via higher selective accumulation of DC(I + II) NPs in only tumor tissues and oxidant activity, causing stronger selective inhibition of mitochondrial enzymes (PDH, SDH, and ALDH2) than DC(I)NPs. This effect resulted in more suppression of tumor and metastasis markers as well as stemness gene expressions in DC(I + II) NPs-treated HC mice. In addition, both nanocomplexes normalized liver function and hematological parameters. The computational analysis found that DC(I + II) showed higher binding affinity to most of the tested enzymes. Accordingly, DC(I + II) NPs represent a highly effective therapeutic formulation compared to DC(I) NPs for metastatic HC.

The crosstalk between copper-induced oxidative stress and cuproptosis: a novel potential anticancer paradigm

Copper is a crucial trace element that plays a role in various pathophysiological processes in the human body. Copper also acts as a transition metal involved in redox reactions, contributing to the generation of reactive oxygen species (ROS). Under prolonged and increased ROS levels, oxidative stress occurs, which has been implicated in different types of regulated cell death. The recent discovery of cuproptosis, a copper-dependent regulated cell death pathway that is distinct from other known regulated cell death forms, has raised interest to researchers in the field of cancer therapy. Herein, the present work aims to outline the current understanding of cuproptosis, with an emphasis on its anticancer activities through the interplay with copper-induced oxidative stress, thereby providing new ideas for therapeutic approaches targeting modes of cell death in the future.

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.

Long non-coding RNAs in ferroptosis and cuproptosis impact on prognosis and treatment in hepatocellular carcinoma

Ferroptosis and cuproptosis are recently discovered forms of cell death that have gained interest as potential cancer treatments, particularly for hepatocellular carcinoma. Long non-coding RNAs (lncRNAs) influence cancer cell activity by interacting with various nucleic acids and proteins. However, the role of ferroptosis and cuproptosis-related lncRNAs (FCRLs) in cancer remains underexplored. Ferroptosis and cuproptosis scores for each sample were assessed using Gene Set Variation Analysis (GSVA). Weighted correlation network analysis identified the FCRLs most relevant to our study. A risk model based on FCRLs was developed to categorize patients into high-risk and low-risk groups. We then compared overall survival (OS), tumor immune microenvironment, and clinical characteristics between these groups. The IPS score and ImmuCellAI webpage were used to predict the association between FCRL-related signatures and immunotherapy response. Finally, we validated the accuracy of FCRLs in hepatocellular carcinoma cell lines using induction agents (elesclomol and erastin). Patients in different risk subgroups showed significant differences in OS, immune cell infiltration, pathway activity, and clinical characteristics. Cellular assays revealed significant changes in the expression of AC019080.5, AC145207.5, MIR210HG, and LINC01063 in HCC cell lines following the addition of ferroptosis and cuproptosis inducers. We created a signature of four FCRLs that accurately predicted survival in HCC patients, laid the foundation for basic research related to ferroptosis and cuproptosis in hepatocellular carcinoma, and provided therapeutic recommendations for HCC patients.

Identification of potential crucial cuproptosis-related genes in myocardial ischemia-reperfusion injury through the bioinformatic analysis

BACKGROUND

Cuproptosis is known to regulate diverse physiological functions in many diseases, but its role in regulating Myocardial Ischemia-Reperfusion Injury (MI/RI) remains unclear.

METHODS

For this purpose, the MI/RI microarray datasets GSE61592 were downloaded from the Gene Expression Omnibus (GEO) database, and the Differently Expressed Genes (DEGs) in MI/RI were identified using R software. Moreover, the MI/RI mice model was established to confirm further the diagnostic value of Pyruvate Dehydrogenase B (Pdhb), Dihydrolipoamide S-acetyltransferase (Dlat), and Pyruvate dehydrogenase E1 subunit alpha 1 (Pdhα1).

RESULTS

The analysis of microarray datasets GSE61592 revealed that 798 genes were upregulated and 768 were downregulated in the myocardial tissue of the ischemia-reperfusion injury mice. Furthermore, Dlat, Pdhb, Pdhα1, and cuproptosis-related genes belonged to the downregulated genes. The receiver operating characteristics curve analysis results indicated that the Dlat, Pdhb, and Pdhα1 levels were downregulated in MI/RI and were found to be potential biomarkers for MI/RI diagnosis and prognosis. Similarly, analysis of Dlat, Pdhb, and Pdhα1 levels in the MI/RI mice revealed Pdhb being the key diagnostic marker.

CONCLUSIONS

This study demonstrated the prognostic value of cuproptosis-related genes (Dlat, Pdhb, and Pdhα1), especially Pdhb, MI/RI, providing new insight into the MI/RI treatment.

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.

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

Background

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

Methods

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

Results

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

Conclusions

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

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.

Crosstalk of different cell-death patterns predicts prognosis and drug sensitivity in glioma

BACKGROUND

Glioma is a malignant brain tumor originating from glial cells, and there still a challenge to accurately predict the prognosis. Programmed cell death (PCD) plays a key role in tumorigenesis and immune response. However, the crosstalk and potential role of various PCDs in prognosis and tumor microenvironment remains unknown. Therefore, we comprehensively discussed the relationship between different models of PCD and the prognosis of glioma and provided new ideas for the optimal targeted therapy of glioma.

MATERIALS AND METHODS

We compared and analyzed the role of 14 PCD patterns on the prognosis from different levels. We constructed the cell death risk score (CDRS) index and conducted a comprehensive analysis of CDRS and TME characteristics, clinical characteristics, and drug response.

RESULTS

Effects of different PCDs at the genomic, functional, and immune microenvironment levels were discussed. CDRS index containing 6 gene signatures and a nomogram were established. High CDRS is associated with a worse prognosis. Through transcriptome and single-cell data, we found that patients with high CDRS showed stronger immunosuppressive characteristics. Moreover, the high-CDRS group was resistant to the traditional glioma chemotherapy drug Vincristine, but more sensitive to the Temozolomide and the clinical experimental drug Bortezomib. In addition, we identified 19 key potential therapeutic targets during malignant differentiation of tumor cells.

CONCLUSION

Overall, we provide the first systematic description of the role of 14 PCDs in glioma. A new CDRS model was built to predict the prognosis and to provide a new idea for the targeted therapy of glioma.

Molecular subtypes of clear cell renal carcinoma based on PCD-related long non-coding RNAs expression: insights into the underlying mechanisms and therapeutic strategies

BACKGROUND

PCD-related long non-coding RNAs (PRLs) are rarely investigated in relation to clear cell renal carcinoma (ccRCC). As part of this study, we evaluated the immunological potential of PRL signatures as a biomarker for ccRCC prognosis and immunological function.

MATERIALS AND METHODS

Data were downloaded from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. A Pearson correlation analysis was conducted on the 27 PCD-associated genes to determine whether lncRNAs were significantly associated with PCD. Kaplan-Meier analysis, biological function identification, immune infiltration analysis, estimation of efficacy of immunotherapy and targeted drug screening, and exploration of the landscape of mutation status were conducted by analyzing the risk scores.

RESULTS

Seven PRLs, LINC02747, AP001636.3, AC022126.1, LINC02657, LINC02609, LINC02154, and ZNNT1, were used to divide patients with ccRCC into groups with high and low risk. High-risk patients had a worse prognosis than low-risk patients, according to the results, and the PRL signature showed promising predictive ability. More immune cells were clustered in the high-risk group, whereas the immune cell function of the low-risk group was significantly suppressed. The high-risk group was less sensitive to immunotherapy, whereas the low-risk group had positive responses to most drugs.

CONCLUSIONS

Collectively, we established and verified a PRL signature that could competently guide the prognostic survival and immunotherapy of ccRCC. In addition, molecular subtypes were determined for ccRCC based on PRL expression, which may help elucidate the underlying molecular mechanism of ccRCC and develop targeted treatments.

Identification of a novel prognostic cuproptosis-associated LncRNA signature for predicting prognosis and immunotherapy response in patients with esophageal cancer

Nowadays, effective prognostic models for esophageal cancer (ESCA) are still lacking. Long noncoding RNAs (lncRNAs) are commonly utilized as indicators for diagnosing cancer and forecasting patient outcomes. Cuproptosis is regulated by multiple genes and is crucial to the progression of ESCA. However, it is not yet clear what role the cuproptosis-associated lncRNAs (CuALs) play in ESCA. To tackle this problem, a prognostic signature incorporating three CuALs was created. This signature was constructed by the use of the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Subsequently, the signature effectively stratified ESCA samples into a high-risk group and a low-risk group. Those in the low-risk group demonstrated extended overall survival (OS), as well as increased infiltration of T cells, macrophages, and NK cells, suggesting a potentially enhanced response to immunotherapy. The ROC curve analysis demonstrated that this prognostic signature outperformed conventional clinical factors in predicting patient prognosis (AUC = 0.708). K-M survival analysis and correlation analysis identified UGDH-AS1 (a CuAL) as a protective factor positively associated with patient prognosis. The results of RT-qPCR and wound healing assays indicated that UGDH-AS1 is overexpressed in ESCA and could inhibit cancer cell migration. In general, the prognostic signature of CuALs demonstrated a robust capability in forecasting the immune environment and patient prognosis, highlighting its potential as a tool for enhancing personalized treatment strategies in ESCA.

Identification of a novel prognostic cuproptosis-associated LncRNA signature for predicting prognosis and immunotherapy response in patients with esophageal cancer

Nowadays, effective prognostic models for esophageal cancer (ESCA) are still lacking. Long noncoding RNAs (lncRNAs) are commonly utilized as indicators for diagnosing cancer and forecasting patient outcomes. Cuproptosis is regulated by multiple genes and is crucial to the progression of ESCA. However, it is not yet clear what role the cuproptosis-associated lncRNAs (CuALs) play in ESCA. To tackle this problem, a prognostic signature incorporating three CuALs was created. This signature was constructed by the use of the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Subsequently, the signature effectively stratified ESCA samples into a high-risk group and a low-risk group. Those in the low-risk group demonstrated extended overall survival (OS), as well as increased infiltration of T cells, macrophages, and NK cells, suggesting a potentially enhanced response to immunotherapy. The ROC curve analysis demonstrated that this prognostic signature outperformed conventional clinical factors in predicting patient prognosis (AUC = 0.708). K-M survival analysis and correlation analysis identified UGDH-AS1 (a CuAL) as a protective factor positively associated with patient prognosis. The results of RT-qPCR and wound healing assays indicated that UGDH-AS1 is overexpressed in ESCA and could inhibit cancer cell migration. In general, the prognostic signature of CuALs demonstrated a robust capability in forecasting the immune environment and patient prognosis, highlighting its potential as a tool for enhancing personalized treatment strategies in ESCA.

Comprehensive bioinformatics analytics and in vivo validation reveal SLC31A1 as an emerging diagnostic biomarker for acute myocardial infarction

BACKGROUND

Globally, Acute Myocardial Infarction (AMI) is a common cause of heart failure (HF), which has been a leading cause of mortality resulting from non-communicable diseases. On the other hand, increasing evidence suggests that the role of energy production within the mitochondria strongly links to the development and progression of heart diseases, while Cuproptosis, a newly identified cell death mechanism, has not yet been comprehensively analyzed from the aspect of cardiovascular medicine.

MATERIALS AND METHODS

8 transcriptome profiles curated from the GEO database were integrated, from which a diagnostic model based on the Stacking algorithm was established. The efficacy of the model was evaluated in a multifaced manner (i.e., by Precision-Recall curve, Receiver Operative Characteristic curve, etc.). We also sequenced our animal models at the bulk RNA level and conducted qPCR and immunohistochemical staining, with which we further validated the expression of the key contributor gene to the model. Finally, we explored the immune implications of the key contributor gene.

RESULTS

A merged machine learning model containing 4 Cuproptosis-related genes (i.e., PDHB, CDKN2A, GLS, and SLC31A1) for robust AMI diagnosis was developed, in which SLC31A1 served as the key contributor. Through in vivo modeling, we validated the aberrant overexpression of SLC31A1 in AMI. Besides, further transcriptome analysis revealed that its high expression was correlated with significant potential immunological implications in the infiltration of many immune cell types, especially monocyte.

CONCLUSIONS

We constructed an AMI diagnostic model based on Cuproptosis-related genes and validated the key contributor gene in animal modeling. We also analyzed the effects on the immune system for its overexpression in AMI.

Identification of cuproptosis-related long non-coding RNA and construction of a novel prognostic signature for bladder cancer: An observational study

Bladder Urothelial Carcinoma (BLCA), a prevalent and lethal cancer, lacks understanding regarding the roles and prognostic value of cuproptosis-related lncRNAs (CRLs), a novel form of cell death induced by copper. We collected RNA-seq data, clinical information, and prognostic data for 414 BLCA samples and 19 matched controls from The Cancer Genome Atlas. Using multivariate and univariate Cox regression analyses, we identified CRLs to create a prognostic signature. Patients were then divided into low- and high-risk groups based on their risk scores. We analyzed overall survival using the Kaplan-Meier method, evaluated stromal and immune scores, and explored functional differences between these risk groups with gene set enrichment analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were also conducted to understand the links between CRLs and BLCA development. We developed a prognostic signature using 4 independent CRLs: RC3H1-IT1, SPAG5-AS1, FAM13A-AS1, and GNG12-AS1. This signature independently predicted the prognosis of BLCA patients. High-risk patients had worse outcomes, with gene set enrichment analysis revealing enrichment in tumor- and immune-related pathways in the high-risk group. Notably, high-risk patients exhibited enhanced responses to immunotherapy and conventional chemotherapy drugs like sunitinib, paclitaxel, and gemcitabine. The independent prognostic signature variables RC3H1-IT1, SPAG5-AS1, FAM13A-AS1, and GNG12-AS1 predicted the prognoses of BLCA patients and provided a basis for the study of the mechanism of CRLs in BLCA development and progression, and the guidance of clinical treatments for patients with BLCA.

Cuproptosis: unveiling a new frontier in cancer biology and therapeutics

Copper plays vital roles in numerous cellular processes and its imbalance can lead to oxidative stress and dysfunction. Recent research has unveiled a unique form of copper-induced cell death, termed cuproptosis, which differs from known cell death mechanisms. This process involves the interaction of copper with lipoylated tricarboxylic acid cycle enzymes, causing protein aggregation and cell death. Recently, a growing number of studies have explored the link between cuproptosis and cancer development. This review comprehensively examines the systemic and cellular metabolism of copper, including tumor-related signaling pathways influenced by copper. It delves into the discovery and mechanisms of cuproptosis and its connection to various cancers. Additionally, the review suggests potential cancer treatments using copper ionophores that induce cuproptosis, in combination with small molecule drugs, for precision therapy in specific cancer types.

Environmental copper exposure, placental cuproptosis, and miscarriage

Copper pollution has become global environmental concern. Widespread Cu pollution results in excessive Cu exposure in human. Epidemiological studies and animal experiments revealed that Cu exposure might have reproductive toxicity. Cuproptosis is a newly reported Cu-dependent and programmed cell death formTsvetkov et al., 2022. However, whether copper exposure at real environmental exposure dose might cause placental cuproptosis and induce miscarriage was completely unexplored. In this study, we found that Cu exposure during pregnancy induced miscarriage or complete pregnancy loss by inducing placenta cuproptosis in CuCl2-exposed pregnant mice. Notably, Cu exposure at 1.3 mg/kg/d (a real environmental exposure dose) was enough to cause placenta cuproptosis. CuCl2 exposure disrupts the TCA cycle, causes proteotoxic stress, increases Cu2+ ion import/decreases Cu2+ export, and results in the loss of Fe-S cluster proteins in mouse placenta, which induces placenta cuproptosis. Moreover, we also identified that Cu exposure down-regulates the expression levels of mmu-miR-3473b, which interacts with Dlst or Rtel1 mRNA and simultaneously positively regulates Dlst or Rtel1 expression, thereby disrupting the TCA cycle and resulting in the loss of Fe-S cluster proteins, and thus epigenetically regulates placental cuproptosis. Treatment with TTM (a cuproptosis inhibitor) suppressed placental cuproptosis and alleviated miscarriage in CuCl2-exposed mice. This work provides novel reproductive toxicity of Cu exposure in miscarriage or complete pregnancy loss by causing placental cuproptosis. This study also provides new ways for further studies on other toxicological effects of Cu and proposes a new approach for protection against Cu-induced reproductive diseases.

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.

Crosstalk between metabolism and cell death in tumorigenesis

It is generally recognized that tumor cells proliferate more rapidly than normal cells. Due to such an abnormally rapid proliferation rate, cancer cells constantly encounter the limits of insufficient oxygen and nutrient supplies. To satisfy their growth needs and resist adverse environmental events, tumor cells modify the metabolic pathways to produce both extra energies and substances required for rapid growth. Realizing the metabolic characters special for tumor cells will be helpful for eliminating them during therapy. Cell death is a hot topic of long-term study and targeting cell death is one of the most effective ways to repress tumor growth. Many studies have successfully demonstrated that metabolism is inextricably linked to cell death of cancer cells. Here we summarize the recently identified metabolic characters that specifically impact on different types of cell deaths and discuss their roles in tumorigenesis.

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.

Identification of cuproptosis-related genes and immune infiltration in dilated cardiomyopathy

BACKGROUND

Dilated cardiomyopathy (DCM) is a leading cause of heart failure. Cuproptosis is involved in various diseases, although its role in DCM is still unclear. Here, this study aims to investigate the feasibility of using genes related to cuproptosis as diagnostic biomarkers for DCM and the association of their expression with immune infiltration and drug target in cardiac tissue.

METHODS

Gene expression data from nonfailure (NF) and DCM samples were retrieved from the GEO database. Cuproptosis scores were calculated using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) was used to screen key modules associated with DCM and cuproptosis. Random forest and least absolute shrinkage and selection operator (LASSO) were applied to identify signature genes. Finally, immune cell infiltration was assessed using ssGSEA. mRNA-miRNA-lncRNA regulatory networks and chemical-drug regulatory networks based on signature genes were analyzed by Cytoscape.

RESULTS

8 modules were aggregated by WGCNA, among which MEblue was significantly associated with cuproptosis scores and DCM. A diagnostic model made up of six signature genes including SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1 was selected. Furthermore, immune infiltration studies showed significant differences between DCM and NF. Drugs networks and ceRNA regulatory network based on six signature genes were successfully constructed.

CONCLUSION

Six signature genes (SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1) were identified as novel diagnostic biomarkers in DCM. In addition, the expression of these genes was associated with immune cell infiltration, suggesting that cuproptosis may be involved in the immune regulation of DCM.

Transcriptome and single-cell transcriptomics reveal prognostic value and potential mechanism of anoikis in skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) is a highly lethal cancer, ranking among the top four deadliest cancers. This underscores the urgent need for novel biomarkers for SKCM diagnosis and prognosis. Anoikis plays a vital role in cancer growth and metastasis, and this study aims to investigate its prognostic value and mechanism of action in SKCM.

METHODS

Utilizing consensus clustering, the SKCM samples were categorized into two distinct clusters A and B based on anoikis-related genes (ANRGs), with the B group exhibiting lower disease-specific survival (DSS). Gene set enrichment between distinct clusters was examined using Gene Set Variation Analysis (GSVA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

RESULTS

We created a predictive model based on three anoikis-related differently expressed genes (DEGs), specifically, FASLG, IGF1, and PIK3R2. Moreover, the mechanism of these prognostic genes within the model was investigated at the cellular level using the single-cell sequencing dataset GSE115978. This analysis revealed that the FASLG gene was highly expressed on cluster 1 of Exhausted CD8( +) T (Tex) cells.

CONCLUSIONS

In conclusion, we have established a novel classification system for SKCM based on anoikis, which carries substantial clinical implications for SKCM patients. Notably, the elevated expression of the FASLG gene on cluster 1 of Tex cells could significantly impact SKCM prognosis through anoikis, thus offering a promising target for the development of immunotherapy for SKCM.

The Transcriptional Landscape of Immune-Response 3'-UTR Alternative Polyadenylation in Melanoma

The prognosis of patients with malignant melanoma has been improved in recent decades due to advancements in immunotherapy. However, a considerable proportion of patients are refractory to treatment, particularly at advanced stages. This underscores the necessity of developing a new strategy to improve it. Alternative polyadenylation (APA), as a marker of crucial posttranscriptional regulation, has emerged as a major new type of epigenetic marker involved in tumorigenesis. However, the potential roles of APA in shaping the tumor microenvironment (TME) are largely unexplored. Herein, we collected two cohorts comprising melanoma patients who received immune checkpoint inhibitor (ICI) immunotherapy to quantify transcriptome-wide discrepancies in APA. We observed a global change in 3'-UTRs between responders and non-responders, which might involve DNA damage response, angiogenesis, PI3K-AKT signaling pathways, etc. Ten putative master APA regulatory factors for those APA events were detected via a network analysis. Notably, we established an immune response-related APA scoring system (IRAPAss), which exhibited a great performance of predicting immunotherapy response in multiple cohorts. Furthermore, we examined the correlation of APA with TME at the single-cell level using four single-cell immune profiles of tumor-infiltrating lymphocytes (TILs), which revealed an overall discrepancy in 3'-UTR length across diverse T cell populations, probably contributing to immunoregulation in melanoma. In conclusion, our study provides a transcriptional landscape of APA implicated in immunoregulation, which might lay the foundation for developing a new strategy for improving immunotherapy response for melanoma patients by targeting APA.

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.

The effect of lipid metabolism on cuproptosis-inducing cancer therapy

Cuproptosis provides a new therapeutic strategy for cancer treatment and is thought to have broad clinical application prospects. Nevertheless, some oncological clinical trials have yet to demonstrate favorable outcomes, highlighting the need for further research into the molecular mechanisms underlying cuproptosis in tumors. Cuproptosis primarily hinges on the intracellular accumulation of copper, with lipid metabolism exerting a profound influence on its course. The interaction between copper metabolism and lipid metabolism is closely related to cuproptosis. Copper imbalance can affect mitochondrial respiration and lipid metabolism changes, while lipid accumulation can promote copper uptake and absorption, and inhibit cuproptosis induced by copper. Anomalies in lipid metabolism can disrupt copper homeostasis within cells, potentially triggering cuproptosis. The interaction between cuproptosis and lipid metabolism regulates the occurrence, development, metastasis, chemotherapy drug resistance, and tumor immunity of cancer. Cuproptosis is a promising new target for cancer treatment. However, the influence of lipid metabolism and other factors should be taken into consideration. This review provides a brief overview of the characteristics of the interaction between cuproptosis and lipid metabolism in cancer and analyses potential strategies of applying cuproptosis for cancer treatment.

Comprehensive analysis of the effects of the cuprotosis-associated gene SLC31A1 on patient prognosis and tumor microenvironment in human cancer

BACKGROUND

Solute carrier family 31 (copper transporter), member 1 (SLC31A1) is a key factor in maintaining intracellular copper concentration and an important factor affecting cancer energy metabolism. Therefore, exploring the potential biological function and value of SLC31A1 could provide a new direction for the targeted therapy of tumors.

METHODS

This study assessed gene expression levels, survival, clinicopathology, gene mutations, methylation levels, the tumor mutational burden (TMB), microsatellite instability (MSI), and the immune cell infiltration of SLC31A1 in pan-cancer using the Tumor Immune Estimation Resource 2.0 (TIMER2.0), Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham CANcer (UALCAN) data analysis portal, and cBioPortal databases. To further understand the potential biological mechanisms of SLC31A1 in different cancers, single-cell level sequencing and a Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analysis of SLC31A1 were also performed. Finally, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting (WB) were used to validate the expression of SLC31A1 in cancers, such as gastric cancer.

RESULTS

SLC31A1 was expressed in most cancer tissues. In kidney renal clear cell carcinoma (KIRC), the high expression of SLC31A1 was associated with good overall survival (OS), while in adrenocortical carcinoma (ACC), breast invasive carcinoma (BRCA), lower grade glioma (LGG), mesothelioma (MESO), and skin cutaneous melanoma (SKCM), the low expression of SLC31A1 was associated with good OS. The highest frequency of SLC31A1 amplification was observed in ACC. In addition, missense mutations accounted for a major portion of the mutation types. The truncation mutation S105Y may be a putative cancer driver. SLC31A1 affected methylation levels in cancer and was associated with the TMB, MSI, and the level of infiltration of various immune cells. Additionally, the single-cell sequencing results showed that SLC31A1 was associated with multiple biological functions in cancer. Finally, the SLC31A1 enrichment analysis revealed that the SLC31A1-related genes were mainly enriched in the mitochondrial matrix and envelope vesicles. The RT-qPCR and WB results were consistent with the predicted results.

CONCLUSIONS

SLC31A1 may be a potential target related to cancer energy metabolism and may have prognostic value.

Melanoma biology and treatment: a review of novel regulated cell death-based approaches

The incidence of melanoma, the most lethal form of skin cancer, has increased due to ultraviolet exposure. The treatment of advanced melanoma, particularly metastatic cases, remains challenging with poor outcomes. Targeted therapies involving BRAF/MEK inhibitors and immunotherapy based on anti-PD1/anti-CTLA4 antibodies have achieved long-term survival rates of approximately 50% for patients with advanced melanoma. However, therapy resistance and inadequate treatment response continue to hinder further breakthroughs in treatments that increase survival rates. This review provides an introduction to the molecular-level pathogenesis of melanoma and offers an overview of current treatment options and their limitations. Cells can die by either accidental or regulated cell death (RCD). RCD is an orderly cell death controlled by a variety of macromolecules to maintain the stability of the internal environment. Since the uncontrolled proliferation of tumor cells requires evasion of RCD programs, inducing the RCD of melanoma cells may be a treatment strategy. This review summarizes studies on various types of nonapoptotic RCDs, such as autophagy-dependent cell death, necroptosis, ferroptosis, pyroptosis, and the recently discovered cuproptosis, in the context of melanoma. The relationships between these RCDs and melanoma are examined, and the interplay between these RCDs and immunotherapy or targeted therapy in patients with melanoma is discussed. Given the findings demonstrating melanoma cell death in response to different stimuli associated with these RCDs, the induction of RCD shows promise as an integral component of treatment strategies for melanoma.

Identification and validation of a copper homeostasis-related gene signature for the predicting prognosis of breast cancer patients via integrated bioinformatics analysis

The prognostic value of copper homeostasis-related genes in breast cancer (BC) remains largely unexplored. We analyzed copper homeostasis-related gene profiles within The Cancer Genome Atlas Program breast cancer cohorts and performed correlation analysis to explore the relationship between copper homeostasis-related mRNAs (chrmRNA) and lncRNAs. Based on these results, we developed a gene signature-based risk assessment model to predict BC patient outcomes using Cox regression analysis and a nomogram, which was further validated in a cohort of 72 BC patients. Using the gene set enrichment analysis, we identified 139 chrmRNAs and 16 core mRNAs via the Protein-Protein Interaction network. Additionally, our copper homeostasis-related lncRNAs (chrlncRNAs) (PINK1.AS, OIP5.AS1, HID.AS1, and MAPT.AS1) were evaluated as gene signatures of the predictive model. Kaplan-Meier survival analysis revealed that patients with a high-risk gene signature had significantly poorer clinical outcomes. Receiver operating characteristic curves showed that the prognostic value of the chrlncRNAs model reached 0.795 after ten years. Principal component analysis demonstrated the capability of the model to distinguish between low- and high-risk BC patients based on the gene signature. Using the pRRophetic package, we screened out 24 anticancer drugs that exhibited a significant relationship with the predictive model. Notably, we observed higher expression levels of the four chrlncRNAs in tumor tissues than in the adjacent normal tissues. The correlation between our model and the clinical characteristics of patients with BC highlights the potential of chrlncRNAs for predicting tumor progression. This novel gene signature not only predicts the prognosis of patients with BC but also suggests that targeting copper homeostasis may be a viable treatment strategy.

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

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

Identification of Key Genes and Immunological Features Associated with Copper Metabolism in Parkinson's Disease by Bioinformatics Analysis

To explore diagnostic genes associated with cuproptosis in Parkinson's disease (PD) and to characterize immune cell infiltration by comprehensive bioinformatics analysis, three PD datasets were downloaded from the GEO database, two of which were merged and preprocessed as the internal training set and the remaining one as the external validation set. Based on the internal training set, differential analysis was performed to obtain differentially expressed genes (DEGs), and weighted gene co-expression network analysis (WGCNA) was conducted to obtain significant module genes. The genes obtained here were intersected to form the intersecting genes. The intersecting genes obtained from DEGs and WGCNA were intersected with cuproptosis-related genes (CRGs) to generate cuproptosis-related disease signature genes, and functional enrichment analysis was performed on Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, LASSO analysis of the cuproptosis-related disease signature genes was performed to identify key genes and construct a diagnostic and predictive model. Then, single sample gene set enrichment analysis (ssGSEA) was performed on the internal training set to further analyze the correlation between key genes and immune cells. Lastly, the results were validated using an external validation set. A total of 405 DEGs were obtained by differential analysis, and 6 gene modules were identified by WGCNA analysis. The genes in the most significant modules were intersected with the DEGs to obtain 21 intersecting genes. The functions of the intersecting genes were mainly enriched in neurotransmitter transport, GABA-ergic synapse, synaptic vesicle cycle, serotonergic synapse, phenylalanine metabolism, tyrosine metabolism, tryptophan metabolism, etc. Subsequently, the intersecting genes were intersected with CRGs, and LASSO regression analysis was performed to screen 3 key cuproptosis-related disease signature genes, namely, SLC18A2, SLC6A3, and SV2C. The calibration curve of the nomogram model constructed based on these 3 key genes to predict PD showed good agreement, with a C-index of 0.944 and an area under the ROC (AUC) of 0.944 (0.833-1.000). It was also validated by the external dataset that the model constructed with these 3 key genes had good diagnostic and predictive power for PD. The ssGSEA analysis revealed that neutrophils might be the potential core immune cells and that SLC18A2, SLC6A3, and SV2C were significantly negatively correlated with neutrophils, which was also verified in the validation set. PD diagnosis and prediction model based on CRGs (SLC18A2, SLC6A3, and SV2C) has good diagnostic and predictive performance and could be a useful tool in the diagnosis of PD.

Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion

Background

Given the lack of research on disulfidptosis, our study aimed to dissect its role in pan-cancer and explore the crosstalk between disulfidptosis and cancer immunity.

Methods

Based on TCGA, ICGC, CGGA, GSE30219, GSE31210, GSE37745, GSE50081, GSE22138, GSE41613, univariate Cox regression, LASSO regression, and multivariate Cox regression were used to construct the rough gene signature based on disulfidptosis for each type of cancer. SsGSEA and Cibersort, followed by correlation analysis, were harnessed to explore the linkage between disulfidptosis and cancer immunity. Weighted correlation network analysis (WGCNA) and Machine learning were utilized to make a refined prognosis model for pan-cancer. In particular, a customized, enhanced prognosis model was made for glioma. The siRNA transfection, FACS, ELISA, etc., were employed to validate the function of c-MET.

Results

The expression comparison of the disulfidptosis-related genes (DRGs) between tumor and nontumor tissues implied a significant difference in most cancers. The correlation between disulfidptosis and immune cell infiltration, including T cell exhaustion (Tex), was evident, especially in glioma. The 7-gene signature was constructed as the rough model for the glioma prognosis. A pan-cancer suitable DSP clustering was made and validated to predict the prognosis. Furthermore, two DSP groups were defined by machine learning to predict the survival and immune therapy response in glioma, which was validated in CGGA. PD-L1 and other immune pathways were highly enriched in the core blue gene module from WGCNA. Among them, c-MET was validated as a tumor driver gene and JAK3-STAT3-PD-L1/PD1 regulator in glioma and T cells. Specifically, the down-regulation of c-MET decreased the proportion of PD1+ CD8+ T cells.

Conclusion

To summarize, we dissected the roles of DRGs in the prognosis and their relationship with immunity in pan-cancer. A general prognosis model based on machine learning was constructed for pan-cancer and validated by external datasets with a consistent result. In particular, a survival-predicting model was made specifically for patients with glioma to predict its survival and immune response to ICIs. C-MET was screened and validated for its tumor driver gene and immune regulation function (inducing t-cell exhaustion) in glioma.