The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Identification of cuproptosis-related genes in Alzheimer's disease based on bioinformatic analysis

OBJECTIVE

To explore the role of cuproptosis in Alzheimer's disease (AD).

METHODS

An AD-related microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database (GSE140830). Weighted gene co-expression network analysis was used to identify AD-related modular genes. The Venn analysis was performed to obtain module genes associated with apoptosis and cuproptosis. Besides, we conducted an enrichment analysis of overlapped genes and constructed the protein-protein interaction (PPI) network, followed by screening hub genes and those significantly associated with AD were used to construct models of apoptosis and cuproptosis, respectively. Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models. Finally, the accuracy and reliability of AD prediction models were verified by GSE26927.

RESULTS

We obtained 42 module genes related to apoptosis and 9 module genes related to cuproptosis. The enrichment analysis results revealed MAPK signaling pathway as the common signaling pathway of apoptosis- and cuproptosis-related genes. Next, the hub genes associated with apoptosis (TRADD, FADD, BIRC2, and CASP2) and cuproptosis (MAP2K1, SLC31A1, and PDHB) in AD were identified, which were used to construct apoptosis and cuproptosis models to distinguish AD patients from the control group (P < 0.05). The ROC, DCA, and subgroup analysis results showed that apoptosis-related models and cuproptosis-related models had comparable ability in predicting AD. GSE26927 further confirmed that the two models have comparable predictive effects for AD.

CONCLUSIONS

The cuproptosis model had a certain performance in predicting AD. Three hub genes (MAP2K1, SLC31A1, and PDHB) closely related to cuproptosis in AD might serve as biomarkers for AD diagnosis and treatment.

The cuproptosis-related gene UBE2D2 functions as an immunotherapeutic and prognostic biomarker in pan-cancer

BACKGROUND

Cuproptosis, as a unique modality of regulated cell death, requires the involvement of ubiquitin-binding enzyme UBE2D2. However, the prognostic and immunotherapeutic values of UBE2D2 in pan-cancer remain largely unknown.

METHODS

Using UCSC Xena, TIMER, Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA) databases, we aimed to explore the differential expression pattern of UBE2D2 across multiple cancer types and to evaluate its association with patient prognosis, clinical features, and genetic variations. The association between UBE2D2 and immunotherapy response was assessed by gene set enrichment analysis, tumor microenvironment, immune gene co-expression and drug half maximal inhibitory concentration (IC50) analysis.

RESULTS

The mRNA and protein levels of UBE2D2 were markedly elevated in most cancer types, and UBE2D2 exhibited prognostic significance in liver hepatocellular carcinoma (LIHC), kidney chromophobe (KICH), uveal melanomas (UVM), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and kidney renal papillary cell carcinoma (KIRP). UBE2D2 expression was correlated with clinical features, tumor mutation burden, microsatellite instability, and anti-tumor drug resistance in several tumor types. Gene enrichment analysis showed that UBE2D2 was significantly associated with immune-related pathways. The expression level of UBE2D2 was correlated with immune cell infiltration, including CD4 + T cells、Macrophages M2、CD8 + T cells in pan-cancer. PDCD1, CD274 and CTLA4 expression levels were positively correlated with UBE2D2 level in multiple cancers.

CONCLUSIONS

We comprehensively investigated the potential value of UBE2D2 as a prognostic and immunotherapeutic predictor for pan-cancer, providing a novel insight for cancer immunotherapy.

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.

Multiomics Analysis of Interleukin-21 as a Potential Immunologic and Biomarker in Hepatocellular Carcinoma

Interleukin-21 (IL-21) is an important antitumor cytokine that contributes to the proliferation and differentiation of CD8 + T cells. It has been proven to enhance the response to immune checkpoint inhibitors (ICIs) in various solid tumors. However, its role in hepatocellular carcinoma (HCC) has not yet been clarified. In this research, we aimed to investigate the antitumor effect of IL-21 in HCC and its effect on ICI treatment. Through transcriptome sequencing analysis and immunohistochemistry validation, we found that patients with high IL-21 expression had a better prognosis. HCCs with high expression of IL-21 had higher infiltration of CD8 + T cells, increased expression of immune checkpoints, and an improved response to ICI treatment. In conclusion, IL-21 can enhance the efficacy of ICI treatment and improve the prognosis of patients by promoting the infiltration of CD8 + T cells and the expression of immune checkpoint-related genes.

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.

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

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

Cuproptosis-related gene DLAT is a biomarker of the prognosis and immune microenvironment of gastric cancer and affects the invasion and migration of cells

OBJECTIVE

Cuproptosis is a novel cell death dependent on mitochondrial respiration and regulated by copper. This study aimed to investigate the cuproptosis-related gene DLAT potential value in gastric cancer (GC).

METHODS

Bioinformatics was used to analyze DLAT expression. DLAT expression in GC cell lines was detected using qRT-PCR. Cell proliferation ability was assessed using CCK8 and cell cycle assay. Cell migration and invasion were assessed using wound healing and transwell assay. A prognostic assessment was performed through survival and Cox regression analysis. DLAT protein expression was analyzed through HPA immunohistochemistry. Biological functions and processes were analyzed through GO and KEGG enrichment analysis and PPI. Correlation with immune cell infiltration and immune checkpoint genes was analyzed for DLAT.

RESULTS

DLAT expression was upregulated in GC tissues and cells and correlated with shorter survival for patients. Age, gender, histological typing, lymph node metastasis, and distant metastasis were identified as independent prognostic factors affecting OS in GC. DLAT protein was upregulated in GC. The biological functions and pathways enriched in DLAT were mainly linked to mitochondrial respiration and the TCA cycle. The expression of DLAT was found to be positively correlated with the infiltration of Th and Th2 immune cells and only positively correlated with the expression of the BTN2A1 immune checkpoint gene.

CONCLUSION

DLAT has the potential to serve as a prognostic assessment factor in GC. The expression of DLAT was correlated with immune infiltration and tumor immune escape, providing a new target for immunotherapy of GC.

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.

Butyrate inhibits the malignant biological behaviors of breast cancer cells by facilitating cuproptosis-associated gene expression

BACKGROUND

Butyrate is a common short-chain fatty acids (SCFA), and it has been demonstrated to regulate the development of breast cancer (BC), while the underlying mechanism is still unreported.

METHODS

Gas chromatography was used to measure the amounts of SCFA (acetate, propionate, and butyrate) in the feces. Cell viability was measured by the CCK-8 assay. The wound healing assay demonstrated cell migration, and the transwell assay demonstrated cell invasion. The levels of protein and gene were determined by western blot assay and RT-qPCR assay, respectively.

RESULTS

The levels of SCFA were lower in the faecal samples from BC patients compared to control samples. In cellular experiments, butyrate significantly suppressed the cell viability, migration and invasion of T47D in a dose-dependent manner. In animal experiments, butyrate effectively impeded the growth of BC tumors. Toll like receptor 4 (TLR4) was highly expressed in the tumors from BC patients. Butyrate inhibited the expression of TLR4. In addition, butyrate promoted the expression of cuproptosis-related genes including PDXK (pyridoxal kinase) and SLC25A28 (solute carrier family 25 member 28), which was lowly expressed in BC tumors. Importantly, overexpression of TLR4 can reverses the promotion of butyrate to PDXK and SLC25A28 expression and the prevention of butyrate to the malignant biological behaviors of T47D cells.

CONCLUSION

In summary, butyrate inhibits the development of BC by facilitating the expression of PDXK and SLC25A28 through inhibition of TLR4. Our investigation first identified a connection among butyrate, TLR4 and cuproptosis-related genes in BC progression. These findings may provide novel target for the treatment of BC.

From mechanism to therapy: the journey of CD24 in cancer

CD24 is a glycosylphosphatidylinositol-anchored protein that is expressed in a wide range of tissues and cell types. It is involved in a variety of physiological and pathological processes, including cell adhesion, migration, differentiation, and apoptosis. Additionally, CD24 has been studied extensively in the context of cancer, where it has been found to play a role in tumor growth, invasion, and metastasis. In recent years, there has been growing interest in CD24 as a potential therapeutic target for cancer treatment. This review summarizes the current knowledge of CD24, including its structure, function, and its role in cancer. Finally, we provide insights into potential clinical application of CD24 and discuss possible approaches for the development of targeted cancer therapies.

Bioinformatics analysis and experimental validation of m6A and cuproptosis-related lncRNA NFE4 in clear cell renal cell carcinoma

PURPOSE

This study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using the information acquired from The Cancer Genome Atlas (TCGA) database.

METHODS

First, the co-expression analysis was performed to identify lncRNAs linked with N6-methyladenosine (m6A) and cuproptosis in ccRCC. Then, a model encompassing four candidate lncRNAs was constructed via univariate, least absolute shrinkage together with selection operator (LASSO), and multivariate regression analyses. Furthermore, Kaplan-Meier, principal component, functional enrichment annotation, and nomogram analyses were performed to develop a risk model that could effectively assess medical outcomes for ccRCC cases. Moreover, the cellular function of NFE4 in Caki-1/OS-RC-2 cultures was elucidated through CCK-8/EdU assessments and Transwell experiments. Dataset outcomes indicated that NFE4 can have possible implications in m6A and cuproptosis, and may promote ccRCC progression.

RESULTS

We constructed a panel of m6A and cuproptosis-related lncRNAs to construct a prognostic prediction model. The Kaplan-Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. Furthermore, the m6A and cuproptosis-related lncRNA model indicated higher diagnostic efficiency than other clinical features. Moreover, the NFE4 function analysis indicated a gene associated with m6A and cuproptosis-related lncRNAs in ccRCC. It was also revealed that the proliferation and migration of Caki-1 /OS-RC-2 cells were inhibited in the NFE4 knockdown group.

CONCLUSION

Overall, this study indicated that NFE4 and our constructed risk signature could predict outcomes and have potential clinical value.

Integrative analysis revealed a correlation of PIAS family genes expression with prognosis, immunomodulation and chemotherapy

BACKGROUND

Protein inhibitor of activated STATs (PIAS) has pleiotropic biological effects, such as protein post-translational modification, transcriptional coregulation and gene editing. It is reported that PIAS family genes are also correlated with immune cells infiltration in cancers that highlights their unnoticed biological role in tumor progression. However, the relationship of their expression with prognosis, immune cell infiltration, tumor microenvironment, and immunotherapy in pan-cancer has been rarely reported.

METHODS

The multi-omics data were used to investigate the expression level of PIAS family members in pan-cancer, and the prognostic value of their expression in different tumors was analyzed by univariate Cox regression and Kaplan-Meier. Correlation analysis was used to investigate the relationship of PIAS gene expression with tumor microenvironment, immune infiltrating subtypes, stemness score and drug sensitivity. In addition, we also used wound healing and transwell assays to verify the biological effects of PIAS family gene expression on invasion and metastasis of HCC cells.

RESULTS

We found that PIAS family genes expression is significantly heterogeneous in tumors by multi-genomic analysis, and associated with poor prognosis in patients with multiple types of cancer. Furthermore, we also found that genetic alterations of PIAS family genes were not only common in different types of human tumors, but were also significantly associated with disease-free survival (DFS) across pan-cancer. Single-cell analysis revealed that PIAS family genes were mainly distributed in monocytes/macrophages. Additionally, we also found that their expression was associated with tumor microenvironment (including stromal cells and immune cells) and stemness score (DNAss and RNAss). Drug sensitivity analysis showed that PIAS family genes were able to predict the response to chemotherapy and immunotherapy. PIAS family genes expression is closely related to tumor metastasis, especially PIAS3. High PIAS3 expression significantly promotes the migration and invasion of liver cancer cell lines (HCC-LM3 and MHCC97-H).

CONCLUSIONS

Taking together, these findings contribute to determine whether the PIAS family genes are a potential oncogenic target gene, which have important contribution for the development of cancer immunotherapy.

Cuproptosis-associated ncRNAs predict breast cancer subtypes

BACKGROUND

Cuproptosis is a novel copper-dependent mode of cell death that has recently been discovered. The relationship between Cuproptosis-related ncRNAs and breast cancer subtypes, however, remains to be studied.

METHODS

The aim of this study was to construct a breast cancer subtype prediction model associated with Cuproptosis. This model could be used to determine the subtype of breast cancer patients. To achieve this aim, 21 Cuproptosis-related genes were obtained from published articles and correlation analysis was performed with ncRNAs differentially expressed in breast cancer. Random forest algorithms were subsequently utilized to select important ncRNAs and build breast cancer subtype prediction models.

RESULTS

A total of 94 ncRNAs significantly associated with Cuproptosis were obtained and the top five essential features were chosen to build a predictive model. These five biomarkers were differentially expressed in the five breast cancer subtypes and were closely associated with immune infiltration, RNA modification, and angiogenesis.

CONCLUSION

The random forest model constructed based on Cuproptosis-related ncRNAs was able to accurately predict breast cancer subtypes, providing a new direction for the study of clinical therapeutic targets.

Comprehensive bioinformatics analysis reveals the role of cuproptosis-related gene Ube2d3 in myocardial infarction

Background

Myocardial infarction (MI) caused by severe coronary artery disease has high incidence and mortality rates, making its prevention and treatment a central and challenging aspect of clinical work for cardiovascular practitioners. Recently, researchers have turned their attention to a novel mechanism of cell death caused by Cu2+, cuproptosis.

Methods

This study integrated data from three MI-related bulk datasets downloaded from the Gene Expression Omnibus (GEO) database, and identified 16 differentially expressed genes (DEGs) related to cuproptosis by taking intersection of the 6378 DEGs obtained by differential analysis with 49 cuproptosis-related genes. Four hub genes, Dbt, Dlat, Ube2d1 and Ube2d3, were screened out through random forest analysis and Lasso analysis. In the disease group, Dbt, Dlat, and Ube2d1 showed low expression, while Ube2d3 exhibited high expression.

Results

Focusing on Ube2d3 for subsequent functional studies, we confirmed its high expression in the MI group through qRT-PCR and Western Blot detection after successful construction of a MI mouse model by left anterior descending (LAD) coronary artery ligation, and further clarified the correlation of cuproptosis with MI development by detecting the levels of cuproptosis-related proteins. Moreover, through in vitro experiments, Ube2d3 was confirmed to be highly expressed in oxygen-glucose deprivation (OGD)-treated cardiomyocytes AC16. In order to further clarify the role of Ube2d3, we knocked down Ube2d3 expression in OGD-treated AC16 cells, and confirmed Ube2d3's promoting role in the hypoxia damage of AC16 cells by inducing cuproptosis, as evidenced by the detection of MTT, TUNEL, LDH release and cuproptosis-related proteins.

Conclusion

In summary, our findings indicate that Ube2d3 regulates cuproptosis to affect the progression of MI.

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.

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

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

Cuproptosis: emerging biomarkers and potential therapeutics in cancers

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

A novel cuproptosis-related genes model in breast cancer prognosis

Breast cancer (BRCA) is a highly heterogeneous malignancy with an urgent need to build a proper model to predict its prognosis. Cuproptosis is a recently discovered form of cell death, mediated by protein fatty acylation and tightly associated with mitochondrial metabolism. The role of cuproptosis-related genes (CRGs) in BRCA remains to be explored. We aimed to investigate the applications of CRGs in BRCA prognosis in different clinical contexts, including chemotherapy and immunotherapy, via bioinformatics analysis of the messenger RNA profiles and clinical data obtained from public databases. Molecular subtyping of CRGs was performed through consistent clustering analysis. Differentially expressed genes between different CRG clusters were identified. The differentially expressed genes were then used to build a risk assessment model using least absolute shrinkage and selection operator regression to predict patient survival with BRCA. The model was then validated with the data from the Molecular Taxonomy of Breast Cancer International Consortium, GSE96058, and GSE20685. Differences in somatic mutations, copy number variations, hallmark pathways, drug responses, and prognosis of immunotherapy and chemotherapy were analyzed by comparing the high-risk and low-risk groups. Patients with high-risk scores showed worse overall survival than those with low-risk scores. The results indicated significant differences between the 2 groups immune-related biological pathways and the variable immune status. It also suggests the differential sensitivity to chemotherapy between the 2 groups. The CRGs model showed the promise to predict the prognosis of BRCA patients and shed light on their treatment.

The signature of cuproptosis-related immune genes predicts the tumor microenvironment and prognosis of prostate adenocarcinoma

Background

Cuproptosis plays a crucial role in cancer, and different subtypes of cuproptosis have different immune profiles in prostate adenocarcinoma (PRAD). This study aimed to investigate immune genes associated with cuproptosis and develop a risk model to predict prognostic characteristics and chemotherapy/immunotherapy responses of patients with PRAD.

Methods

The CIBERSORT algorithm was used to evaluate the immune and stromal scores of patients with PRAD in The Cancer Genome Atlas (TCGA) cohort. Validation of differentially expressed genes DLAT and DLD in benign and malignant tissues by immunohistochemistry, and the immune-related genes of DLAT and DLD were further screened. Univariable Cox regression were performed to select key genes. Least absolute shrinkage and selection operator (LASSO)-Cox regression analyse was used to develop a risk model based on the selected genes. The model was validated in the TCGA, Memorial Sloan-Kettering Cancer Center (MSKCC) and Gene Expression Omnibus (GEO) datasets, as well as in this study unit cohort. The genes were examined via functional enrichment analysis, and the tumor immune features, tumor mutation features and copy number variations (CNVs) of patients with different risk scores were analysed. The response of patients to multiple chemotherapeutic/targeted drugs was assessed using the pRRophetic algorithm, and immunotherapy was inferred by the Tumor Immune Dysfunction and Exclusion (TIDE) and immunophenoscore (IPS).

Results

Cuproptosis-related immune risk scores (CRIRSs) were developed based on PRLR, DES and LECT2. High CRIRSs indicated poor overall survival (OS), disease-free survival (DFS) in the TCGA-PRAD, MSKCC and GEO datasets and higher T stage and Gleason scores in TCGA-PRAD. Similarly, in the sample collected by the study unit, patients with high CRIRS had higher T-stage and Gleason scores. Additionally, higher CRIRSs were negatively correlated with the abundance of activated B cells, activated CD8+ T cells and other stromal or immune cells. The expression of some immune checkpoints was negatively correlated with CRIRSs. Tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) scores were all higher in the high-CRIRS group. Multiple chemotherapeutic/targeted drugs and immunotherapy had better responsiveness in the low-CRIRS group.

Conclusion

Overall, lower CRIRS indicated better response to treatment strategies and better prognostic outcomes.

Prediction of Prognosis and Chemotherapeutic Sensitivity Based on Cuproptosis-Associated lncRNAs in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Cervical cancer is the fourth most common cancer. The 5-year survival rate for metastatic cervical cancer is less than 10%. The survival time of patients with recurrent cervical cancer is approximately 13-17 months. Cuproptosis is a novel type of cell death related to mitochondrial respiration. Accumulative studies showed that long non-coding RNAs (lncRNAs) regulated cervical cancer progression. Compressive bioinformatic analysis showed that nine cuproptosis-related lncRNAs (CRLs), including C002128.2, AC002563.1, AC009237.14, AC048337.1, AC145423.1, AL117336.1, AP001542.3, ATP2A1-AS1, and LINC00426, were independently correlated with the overall survival (OS) of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients. The time-dependent area under curve value reached 0.716 at 1 year, 0.718 at 3 years, and 0.719 at 5 years. Notably, CESC patients in the low-risk group had increased immune cell infiltration and expression of several immune checkpoints, which indicated that they may benefit more from immune checkpoint blockade therapy. In addition, we also used the model for drug sensitivity analysis. Several drug sensitivities were more sensitive in high-risk patients and showed significant correlations with the risk models, such as Bortezomib_1191, Luminespib_1559, and Rapamycin_1084, suggesting that these drugs may be candidate clinical drugs for patients with a high risk of CESC. In summary, this study further explored the mechanism of CRLs in CESC and provided a more optimized prognostic model and some insights into chemotherapy of CESC.

Deciphering the contributions of cuproptosis in the development of hypertrophic scar using single-cell analysis and machine learning techniques

Hypertrophic scar (HS) is a chronic inflammatory skin disease characterized by excessive deposition of extracellular matrix, but the exact mechanisms related to its formation remain unclear, making it difficult to treat. This study aimed to investigate the potential role of cuproptosis in the information of HS. To this end, we used single-cell sequencing and bulk transcriptome data, and screened for cuproptosis-related genes (CRGs) using differential gene analysis and machine learning algorithms (random forest and support vector machine). Through this process, we identified a group of genes, including ATP7A, ULK1, and MTF1, as novel therapeutic targets for HS. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to confirm the mRNA expression of ATP7A, ULK1, and MTF1 in both HS and normal skin (NS) tissues. We also constructed a diagnostic model for HS and analyzed the immune infiltration characteristics. Additionally, we used the expression profiles of CRGs to perform subgroup analysis of HS. We focused mainly on fibroblasts in the transcriptional profile at single-cell resolution. By calculating the cuproptosis activity of each fibroblast, we found that cuproptosis activity of normal skin fibroblasts increased, providing further insights into the pathogenesis of HS. We also analyzed the cell communication network and transcription factor regulatory network activity, and found the existence of a fibroblast-centered communication regulation network in HS, where cuproptosis activity in fibroblasts affects intercellular communication. Using transcription factor regulatory activity network analysis, we obtained highly active transcription factors, and correlation analysis with CRGs suggested that CRGs may serve as potential target genes for transcription factors. Overall, our study provides new insights into the pathophysiological mechanisms of HS, which may inspire new ideas for the diagnosis and treatment.

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

Introduction

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

Methods

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

Results

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

Conclusions

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

Identification of Three Cuproptosis-specific Expressed Genes as Diagnostic Biomarkers and Therapeutic Targets for Atherosclerosis

Atherosclerosis is a chronic, inflammatory disease characterized by a lipid-driven infiltration of inflammatory cells in large and medium arteries and is considered to be a major underlying cause of cardiovascular diseases. Cuproptosis, a novel form of cell death, is highly linked to mitochondrial metabolism and mediated by protein lipoylation. However, the clinical implication of cuproptosis-related genes (CRGs) in atherosclerosis remains unclear. In this study, genes collected from the GEO database intersected with CRGs were identified in atherosclerosis. GSEA, GO and KEGG pathway enrichment analyses were performed for functional annotation. Through the random forest algorithm and the construction of a protein-protein interaction (PPI) network, eight selected genes (LOXL2, SLC31A1, ATP7A, SLC31A2, COA6, UBE2D1, CP and SOD1) and a vital cuproptosis-related gene FDX1 were then further validated. Two independent datasets (GSE28829 (N = 29), GSE100927 (N = 104)) were collected to construct the signature of CRGs for validation in atherosclerosis. Consistently, the atherosclerosis plaques showed significantly higher expression of SLC31A1, SLC31A2 and lower expression of SOD1 than the normal intimae. The area under the curve (AUC) of SLC31A1, SLC31A2 and SOD1 performed well for the diagnostic validation in the two datasets. In conclusion, the cuproptosis-related gene signature could serve as a potential diagnostic biomarker for atherosclerosis and may offer novel insights into the treatment of cardiovascular diseases. Based on the hub genes, a competing endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA and a transcription factor regulation network were ultimately constructed to explore the possible regulatory mechanism in atherosclerosis.

Copper-related genes predict prognosis and characteristics of breast cancer

Background

The role of copper in cancer treatment is multifaceted, with copper homeostasis-related genes associated with both breast cancer prognosis and chemotherapy resistance. Interestingly, both elimination and overload of copper have been reported to have therapeutic potential in cancer treatment. Despite these findings, the exact relationship between copper homeostasis and cancer development remains unclear, and further investigation is needed to clarify this complexity.

Methods

The pan-cancer gene expression and immune infiltration analysis were performed using the Cancer Genome Atlas Program (TCGA) dataset. The R software packages were employed to analyze the expression and mutation status of breast cancer samples. After constructing a prognosis model to separate breast cancer samples by LASSO-Cox regression, we examined the immune statement, survival status, drug sensitivity and metabolic characteristics of the high- and low-copper related genes scoring groups. We also studied the expression of the constructed genes using the human protein atlas database and analyzed their related pathways. Finally, copper staining was performed with the clinical sample to investigate the distribution of copper in breast cancer tissue and paracancerous tissue.

Results

Pan-cancer analysis showed that copper-related genes are associated with breast cancer, and the immune infiltration profile of breast cancer samples is significantly different from that of other cancers. The essential copper-related genes of LASSO-Cox regression were ATP7B (ATPase Copper Transporting Beta) and DLAT (Dihydrolipoamide S-Acetyltransferase), whose associated genes were enriched in the cell cycle pathway. The low-copper related genes scoring group presented higher levels of immune activation, better probabilities of survival, enrichment in pathways related to pyruvate metabolism and apoptosis, and higher sensitivity to chemotherapy drugs. Immunohistochemistry staining showed high protein expression of ATP7B and DLAT in breast cancer samples. The copper staining showed copper distribution in breast cancer tissue.

Conclusion

This study displayed the potential impacts of copper-related genes on the overall survival, immune infiltration, drug sensitivity and metabolic profile of breast cancer, which could predict patients' survival and tumor statement. These findings may serve to support future research efforts aiming at improving the management of breast cancer.

Development and validation of cuproptosis-related lncRNA signatures for prognosis prediction in colorectal cancer

BACKGROUND

Cuproptosis, a novel form of programmed cell death, plays an essential role in various cancers. However, studies of the function of cuproptosis lncRNAs (CRLs) in colorectal cancer (CRC) remain limited. Thus, this study aims to identify the cuprotosis-related lncRNAs (CRLs) in CRC and to construct the potential prognostic CRLs signature model in CRC.

METHODS

First, we downloaded RNA-Seq data and clinical information of CRC patients from TCGA database and obtained the prognostic CRLs based on typical expression analysis of cuproptosis-related genes (CRGs) and univariate Cox regression. Then, we constructed a prognostic model using the Least Absolute Shrinkage and Selection Operator algorithm combined with multiple Cox regression methods (Lasso-Cox). Next, we generated Kaplan-Meier survival and receiver operating characteristic curves to estimate the performance of the prognostic model. In addition, we also analysed the relationships between risk signatures and immune infiltration, mutation, and drug sensitivity. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT -PCR) to verify the prognostic model.

RESULT

Lasso-Cox analysis revealed that four CRLs, SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, were related to CRC prognosis. Receiver operating characteristic (ROC) and Kaplan-Meier analysis curves indicated that this model performs well in prognostic predictions of CRC patients. The DCA results also showed that the model included four gene signatures was better than the traditional model. In addition, GO and KEGG analyses revealed that DE-CRLs are enriched in critical signalling pathway, such as chemical carcinogenesis-DNA adducts and basal cell carcinoma. Immune infiltration analysis revealed significant differences in immune infiltration cells between the high-risk and low-risk groups. Furthermore, significant differences in somatic mutations were noted between the high-risk and low-risk groups. Finally, we also validated the expression of four CRLs in FHCs cell lines and CRC cell lines using qRT-PCR.

CONCLUSION

The signature composed of SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, which has better performance in predicting colorectal cancer prognosis and are promising biomarkers for prognosis prediction of CRC.

Identification of Potential Biomarkers for Coronary Artery Disease Based on Cuproptosis

Identifying peripheral biomarkers is an important noninvasive diagnosis method for coronary artery disease (CAD) which has aroused the strong interest of researchers. Cuproptosis, a newly reported kind of programmed cell death, is closely related to mitochondrial respiration, adenosine triphosphate (ATP) production, and the TCA cycle. Currently, no studies have been published about the effects of cuproptosis-related genes (CRGs) on diagnosing CAD. To screen marker genes for CAD from CRGs, we downloaded the whole blood cell gene expression profile of CAD patients and normal samples, i.e., the GSE20680 dataset, from the GEO database. By differential expression analysis, we obtained 10 differentially expressed CRGs (DE-CRGs), which were associated with copper ion response, immune response, and material metabolism. Based on the 10 DE-CRGs, we furtherly performed LASSO analysis and SVM-RFE analysis and identified 5 DE-CRGs as marker genes, including F5, MT4, RNF7, S100A12, and SORD, which had an excellent diagnostic performance. Moreover, the expression of the marker genes was validated in the GSE20681 and GSE42148 datasets, and consistent results were obtained. In mechanism, we conducted gene set enrichment analyses (GSEA) based on the marker genes, and the results implied that they might participate in the regulation of immune response. Therefore, we calculated the relative contents of 22 kinds of immune cells in CAD and normal samples using the CIBERSORT algorithm, followed by differential analysis and correlation analysis of the immune microenvironment, and found that regulatory T cell (Treg) significantly decreased and was negatively correlated with marker gene S100A12. To further reveal the regulation mechanisms, a lncRNA-miRNA-mRNA ceRNA network based on the marker genes was established. Finally, 13 potential therapeutic drugs targeting 2 marker genes (S100A12 and F5) were identified using the Drug Gene Interaction Database (DGIdb). In summary, our findings indicated that some CRGs may be diagnostic biomarkers and treatment targets for CAD and provided new ideas for further scientific research.

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.