Molecular Subtyping Based on Cuproptosis-Related Genes and Characterization of Tumor Microenvironment Infiltration in Kidney Renal Clear Cell Carcinoma

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.

Unravelling infiltrating T-cell heterogeneity in kidney renal clear cell carcinoma: Integrative single-cell and spatial transcriptomic profiling

Kidney renal clear cell carcinoma (KIRC) pathogenesis intricately involves immune system dynamics, particularly the role of T cells within the tumour microenvironment. Through a multifaceted approach encompassing single-cell RNA sequencing, spatial transcriptome analysis and bulk transcriptome profiling, we systematically explored the contribution of infiltrating T cells to KIRC heterogeneity. Employing high-density weighted gene co-expression network analysis (hdWGCNA), module scoring and machine learning, we identified a distinct signature of infiltrating T cell-associated genes (ITSGs). Spatial transcriptomic data were analysed using robust cell type decomposition (RCTD) to uncover spatial interactions. Further analyses included enrichment assessments, immune infiltration evaluations and drug susceptibility predictions. Experimental validation involved PCR experiments, CCK-8 assays, plate cloning assays, wound-healing assays and Transwell assays. Six subpopulations of infiltrating and proliferating T cells were identified in KIRC, with notable dynamics observed in mid- to late-stage disease progression. Spatial analysis revealed significant correlations between T cells and epithelial cells across varying distances within the tumour microenvironment. The ITSG-based prognostic model demonstrated robust predictive capabilities, implicating these genes in immune modulation and metabolic pathways and offering prognostic insights into drug sensitivity for 12 KIRC treatment agents. Experimental validation underscored the functional relevance of PPIB in KIRC cell proliferation, invasion and migration. Our study comprehensively characterizes infiltrating T-cell heterogeneity in KIRC using single-cell RNA sequencing and spatial transcriptome data. The stable prognostic model based on ITSGs unveils infiltrating T cells' prognostic potential, shedding light on the immune microenvironment and offering avenues for personalized treatment and immunotherapy.

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.

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.

Novel cuproptosis-related prognostic gene profiles in preeclampsia

BACKGROUND

Preeclampsia (PE) is a pregnancy-specific disorder with complex pathogenesis. Cuproptosis is a novel identified form of programmed cell death, however, the link between cuproptosis and clinical outcomes in PE is still not fully understood. In this study, we searched for cuproptosis-related genes (CRGs) in the placental tissues of normal and PE patients to clarify the importance of cuproptosis in the development of PE and provide potential predictive indicators for the occurrence of PE.

METHODS

Using RNA sequencing data in the GEO database, we conducted functional enrichment analysis of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), supported by linear regression model and operating characteristic curve (ROC) curve analysis, and summarized the role of CRGs in preeclampsia.

RESULTS

A total of 2831 differentially expressed genes related to PE were screened through multiple database analyses. After further intersection with 19 reported CRGs, 5 CRGs have been closely associated with the pathogenesis of PE, including NFE2L2, PDHA1, PDHB, DLD and GLS. NFE2L2 was identified as a key central gene. Pearson correlation analysis showed that CRGs could be related to several maternal and fetal outcome factors, including the highest pregnancy blood pressure, placenta weight, umbilical blood flow pulsatility index (PI), and neonatal weight. Linear regression equation revealed that the expression of NFE2L2 is negatively correlated with the highest pregnancy blood pressure and umbilical blood flow PI but positively correlated with placental weight and neonatal weight. QRT-PCR showed that the expression of these CRGs was significantly lower in placental tissues.

CONCLUSIONS

This cuproptosis pattern may be a potential prognostic factor in patients with PE and could provide new insights into disease progression.

Crosstalk of cuproptosis-related prognostic signature and competing endogenous RNAs regulation in hepatocellular carcinoma

BACKGROUND

Cuproptosis is a new type of programmed cell death involved in the regulation of neuroendocrine tumors, immune microenvironment, and substance metabolism. However, the role of cuproptosis-related genes (CRGs) in Hepatocellular carcinoma (HCC) remains unclear.

METHOD

Through multiple bioinformatics analysis, we constructed a prognostic gene model and competing endogenous RNA (ceRNA) network. The correlation between CRGs and prognosis, immune infiltration, immune checkpoints, microsatellite instability (MSI) and tumor mutational burden (TMB) was analyzed by Kaplan-Meier curve, univariate Cox, multivariate regression, and Spearman's analysis in HCC patients. Besides, the qRT-PCR and immunohistochemistry assays were used to determine prognostic CRGs mRNA and protein expression in HCC.

RESULTS

We established a novel 3-gene signature related to CRGs for evaluating the prognosis of HCC patients. HCC patients with high risk scores had a poor prognosis with an area under the curve of 0.737, 0.646, and 0.634 on 1-year, 3-year, and 5-year receiver operating characteristic curves. Significant correlation was observed between prognostic CRGs and immune infiltration, immune checkpoints, MSI and TMB. We also developed five ceRNA networks to regulate the occurrence and progression of HCC. CDKN2A, DLAT, and PDHA1 protein expression was up-regulated in HCC versus normal tissues. Besides, the mRNA expression levels of CDKN2A, DLAT, GLS, and PDHA1 were elevated in the HCC cell lines compared to the normal liver cell lines.

CONCLUSIONS

This novel prognostic CRGs signature could be accurately predict the prognosis of patients with HCC. The ceRNA regulatory network might be potential prognostic biomarkers and therapeutic targets for HCC patients.

Machine learning algorithms for a novel cuproptosis-related gene signature of diagnostic and immune infiltration in endometriosis

Endometriosis (EMT) is an aggressive disease of the reproductive system, also called "benign cancer". However, effective treatments for EMT are still lacking in clinical practice. Interestingly, immune infiltration is significantly involved in EMT pathogenesis. Currently, no studies have shown the involvement of cuproptosis-related genes (CRGs) in regulating immune infiltration in EMT. This study identified three CRGs such as GLS, NFE2L2, and PDHA1, associated with EMT using machine learning algorithms. These three CRGs were upregulated in the endometrium of patients with moderate/severe EMT and downregulated in patients with infertility. Single sample genomic enrichment analysis (ssGSEA) revealed that these CRGs were closely correlated with autoimmune diseases such as systemic lupus erythematosus. Furthermore, these CRGs were correlated with immune cells such as eosinophils, natural killer cells, and macrophages. Therefore, profiling patients based on these genes aid in a more accurate diagnosis of EMT progression. The mRNA and protein expression levels of GLS, NFE2L2 and PDHA1 were validated by qRT-PCR and WB studies in EMT samples. These findings provide a new idea for the pathology and treatment of endometriosis, suggesting that CRGs such as GLS, NFE2L2 and PDHA1 may play a key role in the occurrence and development of endometriosis.

Copper-mediated novel cell death pathway in tumor cells and implications for innovative cancer therapies

Previous investigations have unraveled an array of cellular demise modalities, encompassing apoptosis, necrosis, pyroptosis, iron death, and several others. These diverse pathways of cell death have been harnessed as therapeutic strategies for eradicating tumor cells. Recent scientific inquiries have unveiled a novel mode of cell death, namely copper death, which is contingent upon intracellular copper levels. Diverging from conventional cell death mechanisms, copper death exhibits a heightened reliance on mitochondrial respiration, specifically the tricarboxylic acid (TCA) cycle. Tumor cells exhibit distinctive metabolic profiles and an elevated copper content compared to their normal counterparts. The emergence of copper death presents a tantalizing prospect for targeted therapies in the realm of cancer treatment. Thus, the primary objective of this review is to introduce the proteins and intricate mechanisms underlying copper death, while comprehensively summarizing the extensive body of knowledge concerning its ramifications across diverse tumor types. The insights garnered from this comprehensive synthesis will serve as an invaluable reference for driving the development of tailor-made therapeutic interventions for tumors.

The potential of targeting cuproptosis in the treatment of kidney renal clear cell carcinoma

Renal cell carcinoma (RCC) is one of the top ten malignancies and tumor-related causes of death worldwide. The most common histologic subtype is kidney renal clear cell carcinoma (KIRC), accounting for approximately 75% of all RCC cases. Early resection is considered the basic treatment for patients with KIRC. However, approximately 30% of these patients experience recurrence post-operation. Cuproptosis, an autonomous mechanism for controlling cell death, encompasses various molecular mechanisms and multiple cellular metabolic pathways. These pathways mainly include copper metabolic signaling pathways, mitochondrial metabolism signaling pathways, and lipoic acid pathway signaling pathways. Recent evidence shows that cuproptosis is identified as a key cell death modality that plays a meaningful role in tumor progression. However, there is no published systematic review that summarizes the correlation between cuproptosis and KIRC, despite the fact that investigations on cuproptosis and the pathogenesis of KIRC have increased in past years. Researchers have discovered that exogenous copper infusion accelerates the dysfunction of mitochondrial dysfunction and suppresses KIRC cells by inducing cuproptosis. The levels of tricarboxylic acid cycle proteins, lipoic acid protein, copper, and ferredoxin 1 (FDX1) were dysregulated in KIRC cells, and the prognosis of patients with high FDX1 expression is better than that of patients with low expression. Cuproptosis played an indispensable role in the regulation of tumor microenvironment features, tumor progression, and long-term prognosis of KIRC. In this review, we summarized the systemic and cellular metabolic processes of copper and the copper-related signaling pathways, highlighting the potential targets related to cuproptosis for KIRC treatment.

A novel cuproptosis pattern and tumor immune microenvironment characterization in urothelial carcinoma of the bladder

Background

Urothelial carcinoma of the bladder (UCB) is the most prevalent malignant tumor of the urinary system worldwide, which has a significant recurrence rate despite multiple treatment options available. As a unique and novel copper-dependent programmed cell death mechanism, the comprehensive impact of cuproptosis on the tumor immune microenvironment, clinicopathological characteristics and the prognosis of patients remains largely unclear.

Methods

A total of 568 UCB samples were thoroughly examined for cuproptosis patterns using data downloaded from TCGA and GEO, based on 10 cuproptosis-related genes reported previously. Then, the univariate COX regression analysis was performed on the genes that differed across the various patterns. To measure individual cuproptosis pattern, a cuproptosis score system was constructed using a principal component analysis algorithm. To validate the scoring system, immunohistochemical staining was performed on tumor tissues with different pathological grades, and experiments in vitro were conducted about the differentially expressed genes related to prognosis. Finally, the capacity of scoring system to predict the response to immunotherapy was verified by using data from IMvigor 210 cohort.

Results

Four unique cuproptosis clusters and two gene clusters were finally found by the investigation. The clinical features and prognosis of patients, as well as the mRNA transcriptome, pathway enrichment, and immune cell infiltration in TME, varied dramatically between various cuproptosis clusters and gene clusters. To identify individual cuproptosis patterns in UCB patients, we also established a cuproptosis scoring system. After validation with multiple methods, it was indicated that the score system could predict the prognosis of UCB patients and was significantly connected to clinical features such TNM category, tumor grade, molecular type and ultimate survival status. The clinical outcomes of UCB patients were predicted effectively according to the tumor mutation burden in conjunction with the scoring system. Furthermore, we found that the cuproptosis score had a significant correlation with the response to immunotherapy and the sensitivity to chemotherapy.

Conclusion

This study revealed the potential impact of cuproptosis on the UCB tumor immune microenvironment and clinical pathological characteristics. The cuproptosis score system could effectively predict the prognosis of patients and the response to chemotherapy and immunotherapy.

Cuproptosis-related gene expression is associated with immune infiltration and CD47/CD24 expression in glioblastoma, and a risk score based on these genes can predict the survival and prognosis of patients

Introduction

Glioblastoma (GBM) is the most invasive type of glioma, is insensitive to radiotherapy and chemotherapy, and has high proliferation and invasive ability, with a 5-year survival rate of <5%. Cuproptosis-related genes (CRGs) have been successfully used to predict the prognosis of many types of tumors. However, the relationship between cuproptosis and GBM remains unclear.

Methods

Here, we sought to identify CRGs in GBM and elucidate their role in the tumor immune microenvironment and prognosis. To that aim, changes in CRGs in The Cancer Genome Atlas (TCGA) transcriptional and Gene Expression Omnibus (GEO) datasets (GEO4290 and GEO15824) were characterized, and the expression patterns of these genes were analyzed.

Results

A risk score based on CRG expression characteristics could predict the survival and prognosis of patients with GBM and was significantly associated with immune infiltration levels and the expression of CD47 and CD24, which are immune checkpoints of the "don't eat me "signal. Furthermore, we found that the CDKN2A gene may predict GBM sensitivity and resistance to drugs.

Discussion

Our findings suggest that CRGs play a crucial role in GBM outcomes and provide new insights into CRG-related target drugs/molecules for cancer prevention and treatment.

Cuproptosis-related risk score predicts prognosis and characterizes the tumor microenvironment in colon adenocarcinoma

Introduction

Cuproptosis is a novel copper-dependent regulatory cell death (RCD), which is closely related to the occurrence and development of multiple cancers. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of colon adenocarcinoma (COAD) remains unclear.

Methods

Transcriptome, somatic mutation, somatic copy number alteration and the corresponding clinicopathological data of COAD were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). Difference, survival and correlation analyses were conducted to evaluate the characteristics of CRGs in COAD patients. Consensus unsupervised clustering analysis of CRGs expression profile was used to classify patients into different cuproptosis molecular and gene subtypes. TME characteristics of different molecular subtypes were investigated by using Gene set variation analysis (GSVA) and single sample gene set enrichment analysis (ssGSEA). Next, CRG Risk scoring system was constructed by applying logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis and multivariate cox analysis. Real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) were used to exam the expression of key Risk scoring genes.

Results

Our study indicated that CRGs had relatively common genetic and transcriptional variations in COAD tissues. We identified three cuproptosis molecular subtypes and three gene subtypes based on CRGs expression profile and prognostic differentially expressed genes (DEGs) expression profile, and found that changes in multilayer CRGs were closely related to the clinical characteristics, overall survival (OS), different signaling pathways, and immune cell infiltration of TME. CRG Risk scoring system was constructed according to the expression of 7 key cuproptosis-related risk genes (GLS, NOX1, HOXC6, TNNT1, GLS, HOXC6 and PLA2G12B). RT-qPCR and IHC indicated that the expression of GLS, NOX1, HOXC6, TNNT1 and PLA2G12B were up-regulated in tumor tissues, compared with those in normal tissues, and all of GLS, HOXC6, NOX1 and PLA2G12B were closely related with patient survival. In addition, high CRG risk scores were significantly associated with high microsatellite instability (MSI-H), tumor mutation burden (TMB), cancer stem cell (CSC) indices, stromal and immune scores in TME, drug susceptibility, as well as patient survival. Finally, a highly accurate nomogram was constructed to promote the clinical application of the CRG Risk scoring system.

Discussion

Our comprehensive analysis showed that CRGs were greatly associated with TME, clinicopathological characteristics, and prognosis of patient with COAD. These findings may promote our understanding of CRGs in COAD, providing new insights for physicians to predict prognosis and develop more precise and individualized therapy strategies.

Role of cuproptosis in understanding diseases

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

Expression and potential immune involvement of cuproptosis in kidney renal clear cell carcinoma

Cuproptosis is a newly identified programmed cell death pathway mediated by intracellular free copper. Cuproptosis genes were studied in this study for a better insight into the role of cuproptosis in cancers. The analysis identified kidney renal clear cell carcinoma (KIRC) as a cancer type most likely to be affected by cuproptosis. This study analyzed the multi-omic data to explore the cancer-noncancer expression pattern and potential immune involvement of the cuproptosis pathway in KIRC. This study clustered the TCGA KIRC samples based on the gene set of 12 cuproptosis genes to study the role of cuproptosis in the KIRC immune microenvironment and found the potential value of cuproptosis signature for immunotherapy prognosis. This study concluded that cuproptosis might affect KIRC and had potential application value in immune therapy. Hopefully, this study can contribute to the application of cuproptosis in the clinical therapy of KIRC.

Cuproptosis: mechanisms and links with cancers

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

ETNK2 Low-Expression Predicts Poor Prognosis in Renal Cell Carcinoma with Immunosuppressive Tumor Microenvironment

Background

The ethanolamine kinase 2 (ETNK2) gene is implicated in carcinogenesis, but its expression and involvement in kidney renal clear cell carcinoma (KIRC) remain unknown.

Methods

Initially, we conducted a pan-cancer study in which we searched the Gene Expression Profiling Interactive Analysis, the UALCAN, and the Human Protein Atlas databases to determine the expression level of the ETNK2 gene in KIRC. The Kaplan-Meier curve was then used to calculate the overall survival (OS) of KIRC patients. We then used the differentially expressed genes (DEGs) and enrichment analysis to explain the mechanism of the ETNK2 gene. Finally, the immune cell infiltration analysis was performed.

Results

Although the ETNK2 gene expression was lower in KIRC tissues, the findings illustrated a link between the ETNK2 gene expression and a shorter OS time for KIRC patients. DEGs and enrichment analysis revealed that the ETNK2 gene in KIRC involved multiple metabolic pathways. Finally, the ETNK2 gene expression has been linked to several immune cell infiltrations.

Conclusions

According to the findings, the ETNK2 gene plays a crucial role in tumor growth. It can potentially serve as a negative prognostic biological marker for KIRC by modifying immune infiltrating cells.

A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis

Background

Melanoma is a common and aggressive cutaneous malignancy characterized by poor prognosis and a high fatality rate. Recently, due to the application of Immune-checkpoint inhibitors (ICI) in melanoma treatment, melanoma patients' prognosis has been tremendously improved. However, the treatment effect varies quite differently from patient to patient. In this study, we aim to construct and validate a Cuproptosis-related risk model to improve outcome prediction of ICIs in melanoma and divide patients into subtypes with different Cuproptosis-related genes.

Methods

Here, according to differentially expressed genes from four melanoma datasets in GEO (Gene Expression Omnibus), and one in TCGA (The Cancer Genome Atlas) database, a novel signature was developed through LASSO and Cox regression analysis. We used 781 melanoma samples to examine the molecular subtypes associated with Cuproptosis-related genes and studied the related gene mutation and TME cell infiltration. Patients with melanoma can be divided into at least three subtypes based on gene expression profile. Survival pan-cancer analysis was also conducted for melanoma patients.

Results

The Cuproptosis risk score can predict tumor immunity, subtype, survival, and drug sensitivity for melanoma. And Cuproptosis-associated subtypes can help predict therapeutic outcomes.

Conclusion

Cuproptosis risk score is a promising potential biomarker in cancer diagnosis, molecular subtypes determination, TME cell infiltration characteristics, and therapy response prediction in melanoma patients.

Expression Profiles of Cuproptosis-Related Genes Determine Distinct Subtypes of Pancreatic Ductal Adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent subtype of pancreatic cancer and one of the most malignant tumors worldwide. Due to the heterogeneity of its genomics and proteomics, the prognosis of PDAC remains disappointing despite advances in surgery and medicines. Recently, a novel form of programmed cell death, cuproptosis, was proposed, although its role in PDAC has not been investigated. This study aimed to quantify the expression of cuproptosis-related genes and characterize the novel subtypes of PDAC.

METHODS

To evaluate the pattern of cuproptosis in PDAC, the gene expression data and clinical information of 372 samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A consensus cluster analysis was performed using the transcriptional levels, genetic alterations, and individual prognostic values of seven pre-selected cuproptosis-related genes (DLAT, LIPT1, FDX1, DLD, PDHB, PDHA1, and LIAS) to identify the novel subtypes associated with cuproptosis in PDAC. A univariate Cox regression analysis was used to determine the significant prognostic indicators and cuproptosis scores among the differentially expressed genes (DEGs) between the dividing subclusters, followed by a principal component analysis. The prognostic values, immune profiles, treatment sensitivities, and cuproptosis scores were evaluated between the different subgroups.

RESULTS

Seven cuproptosis-related genes showed aberrant expression levels and genetic alterations in the PDAC tumor microenvironment. Among them, LIPT1, LIAS, DLAT, PDHA1, and DLD were significantly correlated with overall survival. Based on the expression profiles of the seven cuproptosis-related genes, three cuproptosis clusters (Clusters A, B, and C) were identified, which were represented by different clinicopathologic features, gene expression levels, and biological processes. A total of 686 DEGs were identified among the three cuproptosis clusters, of which 35 prognosis-related DEGs were selected to further classify the PDAC samples into two subgroups with different survival rates, clinicopathologic features, immune infiltration levels, and drug sensitivities. Higher cuproptosis scores were associated with a significantly poorer prognosis.

CONCLUSION

The cuproptosis subtypes, scores, and relevant genes represent valuable information for assessing the heterogeneity, treatment, and prognosis of PDAC.

Development and validation of a cuproptosis-associated prognostic model for diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous disease. Therefore, more reliable biomarkers are required to better predict the prognosis of DLBCL. Cuproptosis is a novel identified form of programmed cell death (PCD) that is different from oxidative stress-related cell death (e.g., apoptosis, ferroptosis, and necroptosis) by Tsvetkov and colleagues in a recent study released in Science. Cuproptosis is copper-dependent PCD that is closely tied to mitochondrial metabolism. However, the prognostic value of cuproptosis-related genes (CRGs) in DLBCL remains to be further elucidated. In the present study, we systematically evaluated the molecular changes of CRGs in DLBCL and found them to be associated with prognosis. Subsequently, based on the expression profiles of CRGs, we characterized the heterogeneity of DLBCL by identifying two distinct subtypes using consensus clustering. Two isoforms exhibited different survival, biological functions, chemotherapeutic drug sensitivity, and immune microenvironment. After identifying differentially expressed genes (DEGs) between CRG clusters, we built a prognostic model with the Least absolute shrinkage and selection operator (LASSO) Cox regression analysis and validated its prognostic value by Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves. In addition, the risk score can predict clinical characteristics, levels of immune cell infiltration, and prognosis. Furthermore, a nomogram incorporating clinical features and risk score was generated to optimize risk stratification and quantify risk assessment. Compared to the International Prognostic Index (IPI), the nomogram has demonstrated more accuracy in survival prediction. Furthermore, we validated the prognostic gene expression levels through external experiments. In conclusion, cuproptosis-related gene signature can serve as a potential prognostic predictor in DLBCL patients and may provide new insights into cancer therapeutic targets.

Cuproptosis-associated CDKN2A is targeted by plicamycin to regulate the microenvironment in patients with head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC), the most common malignancy of the head and neck, has an overall 5-year survival rate of <50%. Genes associated with cuproptosis, a newly identified copper-dependent form of cell death, are aberrantly expressed in various tumours. However, their role in HNSCC remains unknown. In this study, bioinformatic analysis revealed that the cuproptosis-related gene CDKN2A was correlated with the malignant behaviour of HNSCC. Kaplan-Meier (KM) curves showed that patients with high CDKN2A expression had a better prognosis. Multiomic analysis revealed that CDKN2A may be associated with cell cycle and immune cell infiltration in the tumour microenvironment and is important for maintaining systemic homeostasis in the body. Furthermore, molecular docking and molecular dynamics simulations suggested strong binding between plicamycin and CDKN2A. And plicamycin inhibits the progression of HNSCC in cellular assays. In conclusion, this study elucidated a potential mechanism of action of the cuproptosis-associated gene CDKN2A in HNSCC and revealed that plicamycin targets CDKN2A to improve the prognosis of patients.

Prognosis and personalized treatment prediction in lung adenocarcinoma: An in silico and in vitro strategy adopting cuproptosis related lncRNA towards precision oncology

Background: There is a rapid increase in lung adenocarcinomas (LUAD), and studies suggest associations between cuproptosis and the occurrence of various types of tumors. However, it remains unclear whether cuproptosis plays a role in LUAD prognosis. Methods: Dataset of the TCGA-LUAD was treated as training cohort, while validation cohort consisted of the merged datasets of the GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081. Ten studied cuproptosis-related genes (CRG) were used to generated CRG clusters and CRG cluster-related differential expressed gene (CRG-DEG) clusters. The differently expressed lncRNA that with prognosis ability between the CRG-DEG clusters were put into a LASSO regression for cuproptosis-related lncRNA signature (CRLncSig). Kaplan-Meier estimator, Cox model, receiver operating characteristic (ROC), time-dependent AUC (tAUC), principal component analysis (PCA), and nomogram predictor were further deployed to confirm the model's accuracy. We examined the model's connections with other forms of regulated cell death, including apoptosis, necroptosis, pyroptosis, and ferroptosis. The immunotherapy ability of the signature was demonstrated by applying eight mainstream immunoinformatic algorithms, TMB, TIDE, and immune checkpoints. We evaluated the potential drugs for high risk CRLncSig LUADs. Real-time PCR in human LUAD tissues were performed to verify the CRLncSig expression pattern, and the signature's pan-cancer's ability was also assessed. Results: A nine-lncRNA signature, CRLncSig, was built and demonstrated owning prognostic power by applied to the validation cohort. Each of the signature genes was confirmed differentially expressed in the real world by real-time PCR. The CRLncSig correlated with 2,469/3,681 (67.07%) apoptosis-related genes, 13/20 (65.00%) necroptosis-related genes, 35/50 (70.00%) pyroptosis-related genes, and 238/380 (62.63%) ferroptosis-related genes. Immunotherapy analysis suggested that CRLncSig correlated with immune status, and checkpoints, KIR2DL3, IL10, IL2, CD40LG, SELP, BTLA, and CD28, were linked closely to our signature and were potentially suitable for LUAD immunotherapy targets. For those high-risk patients, we found three agents, gemcitabine, daunorubicin, and nobiletin. Finally, we found some of the CRLncSig lncRNAs potentially play a vital role in some types of cancer and need more attention in further studies. Conclusion: The results of this study suggest our cuproptosis-related CRLncSig can help to determine the outcome of LUAD and the effectiveness of immunotherapy, as well as help to better select targets and therapeutic agents.

Cuproptosis-Related Genes Are Associated with Cell Cycle and Serve as the Prognostic Signature for Clear Cell Renal Cell Carcinoma

Cuproptosis is a newly discovered type of cell death. The role and potential mechanism of Cuproptosis-related genes (CRGs) in the prognosis of cancer patients are not fully understood. In this study, we included two cohorts of clear cell renal cell carcinoma patients, TCGA and E-MTAB-1980. The TCGA cohort is used as a training set to construct a CRG signature using the LASSO-cox regression analysis, and E-MTAB-1980 is used as a cohort for verification. A total of eight genes (FDX1, LIAS, LIPT1, DLAT, PDHA1, MTF1, GLS, CDKN2A) were screened to construct a prognostic model in the TCGA cohort. There is a significant difference in OS (p < 0.0001) between the high and low cuproptosis score group, and a similar difference is also observed in the OS (p = 0.0054) of the E-MTAB-1980 cohort. The area under the ROC curves (AUC) were 0.87, 0.82, and 0.78 at 1, 3, and 5 years in the TCGA cohort, respectively. Finally, gene set enrichment analysis revealed that CRGs were associated with cell cycle and mitotic signaling pathways.

Prognostic and immune correlation evaluation of a novel cuproptosis-related genes signature in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the world's malignant tumors with high morbidity and mortality. Cuproptosis is a novel form of cell death. However, the prognostic evaluation and immune relevance of cuproptosis-related genes (CRGs) in HCC are largely unknown. In our study, we constructed a prognostic model of CRGs in HCC and performed immune infiltration, functional analysis, immune checkpoint and drug sensitivity analysis. Systematically elaborated the prognostic and immune correlation of CRGs in HCC. The results showed that 15 CRGs were up-regulated or down-regulated in HCC, and the mutation frequency of CRGs reached 10.33% in HCC, with CDKN2A having the highest mutation frequency. These 19 CRGs were mainly involved in the mitochondrion, immune response and metabolic pathways. Five selected genes (CDKN2A, DLAT, DLST, GLS, PDHA1) were involved in constructing a prognostic CRGs model that enables the overall survival in HCC patients to be predicted with moderate to high accuracy. Prognostic CRGs, especially CDKN2A, the independent factor of HCC prognosis, may be closely associated with immune-cell infiltration, tumor mutation burden (TMB), microsatellite instability(MSI), and immune checkpoints. CD274, CTLA4, LAG3, PDCD1, PDCD1LG2 and SIGLEC15 may be identified as potential therapeutic targets and CD274 correlated highly with prognostic genes. Quantitative Real-Time PCR (qRT-PCR) and immunohistochemical were performed to validate the mRNA and protein expression levels of CDKN2A in adjacent normal tissues and HCC tissues, and the results were consistent with gene difference analysis. In conclusion, CRGs, especially CDKN2A, may serve as potential prognostic predictors in HCC patients and provide novel insights into cancer therapy.

Establishment and experimental validation of a novel cuproptosis-related gene signature for prognostic implication in cholangiocarcinoma

Background

Cholangiocarcinoma (CCA) is a highly malignant, heterogeneous bile duct malignancy with poor treatment options. A novel type of cell death termed cuproptosis was recently demonstrated to closely correlate with tumor progression. To gain more insight into the role of cuproptosis in CCA, we investigated the prognostic implications of cuproptosis related genes (CRGs) and their relationship to the development of CCA.

Methods

Gene expression data for CCA were obtained from the European Bioinformatics Institute (EMBL-EBI) database. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression was used to construct a prognostic risk model based on CRGs. RNA-seq, qRT-PCR and immunohistochemistry staining were used to verify the expression of CRGs in human CCA tissues or cell lines. Further in vitro experiments were performed to demonstrate the role of cuproptosis in CCA.

Results

We established a 4-gene signature (ATP7A, FDX1, DBT and LIAS) that exhibited good stability and was an independent prognostic factor for CCA. Seventy-five CCA samples were divided into high- and low-risk groups based on the risk score. Enrichment analysis revealed increased extracellular activity in the high-risk group and increased lipid metabolic activity in the low-risk group. Moreover, the 4 signature genes were verified in clinical samples and cell lines by RNA-seq, qRT-PCR and immunohistochemistry. Further experiments confirmed that cuproptosis can significantly inhibit the viability of CCA cells. Knockdown of the key gene LIAS ameliorated the toxicity of cuproptosis to CCA cells.

Conclusion

We established a 4-gene prognostic signature based on cuproptosis and explored the role of cuproptosis in CCA. The results provide an effective indicator for predicting the prognosis of cuproptosis in CCA.

[Cuproptosis-related immune gene signature predicts clinical benefits from anti-PD-1/PD-L1 therapy in non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) remains the major cause of cancer-related death. Immune checkpoint inhibition has become the cornerstone treatment for NSCLC. Cuproptosis is a newly identified form of cell death relying on mitochondrial respiration that might play a role in shaping tumor immune microenvironment (TIME). The clinical significance of cuproptosis-related genes (CRGs) remains unclear and warrant investigation. The current study extracted RNA sequencing profiles and corresponding clinical information from six aggregated datasets from the Gene Expression Omnibus (GEO) repository as the training set, and from The Cancer Genome Atlas (TCGA) database as the testing set. Cuproptosis-related immune genes (CRIMGs) were obtained through coexpression analysis, univariate Cox regression analysis, and LASSO analysis for overall survival (OS) association analysis. Consensus clustering was employed to divide the subjects into clusters. Stepwise multivariate Cox regression was used to establish the prognostic CRIMG_score from the CRIMGs. A 17-gene prediction signature was established that informed patients' OS both in the training and testing datasets (p < 0.001). The predictive value of the signature in terms of immunotherapeutic responses was assessed in two publicly available NSCLC immunotherapy datasets (POPLAR and OAK studies) and an internal dataset from Sun Yat-sen University Cancer Center (ORIENT-11 study). Patients in the high-risk group displayed worse survival, a characteristic suppressive tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the CRIMG_score established herein could serve as a promising indicator of prognosis and immunotherapeutic response in patients with NSCLC.

Construction of cuproptosis-related gene signature to predict the prognosis and immunotherapy efficacy of patients with bladder cancer through bioinformatics analysis and experimental validation

Background: A new form of cell death, copper-dependent cell death (termed cuproptosis), was illustrated in a recent scientific study. However, the biological function or prognostic value of cuproptosis regulators in bladder cancer (BLCA) remains unknown. Materials and Methods: Sequencing data obtained from BLCA samples in TCGA and GEO databases were preprocessed for analysis. Biological function and immune cell infiltration levels evaluated by gene set variation analysis (GSVA) were employed to calculate enrichment scores. Iteration least absolute shrinkage and selection operator (LASSO) and COX regression model were employed to select feature genes and construct a novel cuproptosis-related (CR) score signature. The genomics of drug sensitivity in cancer (GDSC) and tumor immune dysfunction and exclusion (TIDE) analysis were used to predict the chemotherapy and immunotherapy efficacy for BLCA patients. The relative expression of the genes involved in the signature was also verified by real-time quantitative PCR (qRT-PCR) in cell lines and tissues. Results: Expression abundance and the prognostic value of cuproptosis regulators proved that cuproptosis might play a vital part in the carcinogenesis of BLCA. GSVA revealed that cuproptosis regulators might be associated with metabolism and metastasis-related pathways such as TGF-β, protein secretion, oxidative Phosphorylation, MYC targets, MTORC1, and adipogenesis pathways. CR scores could predict the prognosis and evaluate the chemotherapy and immunotherapy efficacies of BLCA. CR scores were positively correlated with EMT, MYC, MTORC1, HEDGEHOG, and E2F signaling pathways; meanwhile, they were negatively correlated with several immune cell infiltration levels such as CD8+ T cells, γδT cells, and activated dendritic cells. Several GEO datasets were used to validate the power of prognostic prediction, and a nomogram was also established for clinical use. The expressions of DDX10, RBM34, and RPL17 were significantly higher in BLCA cell lines and tissues in comparison with those in the corresponding normal controls. Conclusion: Cuproptosis might play an essential role in the progression of BLCA. CR scores could be helpful in the investigation of prognostic prediction and therapeutic efficacy and could make contributions to further studies in BLCA.

Identification of molecular subtypes and a six-gene risk model related to cuproptosis for triple negative breast cancer

Background: Breast cancer is the mostly diagnosed cancer worldwide, and triple negative breast cancer (TNBC) has the worst prognosis. Cuproptosis is a newly identified form of cell death, whose mechanism has not been fully explored in TNBC. This study thought to unveil the potential association between cuproptosis and TNBC. Materials and Methods: Gene expression files with clinical data of TNBC downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were included in this study. Consensus clustering was utilized to perform molecular subtyping based on cuproptosis-associated genes. Limma package was applied to distinguish differentially expressed genes. Univariate Cox regression was used to identify prognostic genes. Least absolute shrinkage and selection operator and stepwise Akaike information criterion optimized and established a risk model. Results: We constructed three molecular subtypes based on cuproptosis-associated genes, and the cuproptosis-based subtyping showed a robustness in different datasets. Clust2 showed the worst prognosis and immune-related pathways such as chemokine signaling pathway were significantly activated in clust2. Clust2 also exhibited a high possibility of immune escape to immune checkpoint blockade. In addition, a six-gene risk model was established manifesting a high AUC score over 0.85 in TCGA dataset. High- and low-risk groups had distinct prognosis and immune infiltration. Finally, a nomogram was constructed with strong performance in predicting TNBC prognosis than the staging system. Conclusion: The molecular subtyping system related to cuproptosis had a potential in guiding immunotherapy for TNBC patients. Importantly, the six-gene risk model was effective and reliable to predict TNBC prognosis.

Molecular subtypes based on cuproptosis regulators and immune infiltration in kidney renal clear cell carcinoma

Copper toxicity involves the destruction of mitochondrial metabolic enzymes, triggering an unusual mechanism of cell death called cuproptosis, which proposes a novel approach using copper toxicity to treat cancer. However, the biological function of cuproptosis has not been fully elucidated in kidney renal clear cell carcinoma (KIRC). Using the expression profile of 13 cuproptosis regulators, we first identified two molecular subtypes related to cuproptosis defined as “hot tumor” and “cold tumor”, having different levels of biological function, clinical prognosis, and immune cell infiltration. We obtained three gene clusters using the differentially expressed genes between the two cuproptosis-related subtypes, which were associated with different molecular activities and clinical characteristics. Next, we developed and validated a cuproptosis prognostic model that included two genes (FDX1 and DBT). The calculated risk score could divide patients into high- and low-risk groups. The high-risk group had a poorer prognosis, lower level of immune infiltration, higher frequency of gene alterations, and greater levels of FDX1 methylation and limited DBT methylation. The risk score was also an independent predictive factor for overall survival in KIRC. The established nomogram calculating the risk score achieved a high predictive ability for the prognosis of individual patients (area under the curve: 0.860). We then identified small molecular inhibitors as potential treatments and analyzed the sensitivity to chemotherapy of the signature genes. Tumor immune dysfunction and exclusion (TIDE) showed that the high-risk group had a higher level of TIDE, exclusion and dysfunction that was lower than the low-risk group, while the microsatellite instability of the high-risk group was significantly lower. The results of two independent immunotherapy datasets indicated that cuproptosis regulators could influence the response and efficacy of immunotherapy in KIRC. Our study provides new insights for individualized and comprehensive therapy of KIRC.

The role of cuproptosis-related gene in the classification and prognosis of melanoma

Background

Melanoma, as one of the most aggressive and malignant cancers, ranks first in the lethality rate of skin cancers. Cuproptosis has been shown to paly a role in tumorigenesis, However, the role of cuproptosis in melanoma metastasis are not clear. Studying the correlation beteen the molecular subtypes of cuproptosis-related genes (CRGs) and metastasis of melanoma may provide some guidance for the prognosis of melanoma.

Methods

We collected 1085 melanoma samples in The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus(GEO) databases, constructed CRGs molecular subtypes and gene subtypes according to clinical characteristics, and investigated the role of CRGs in melanoma metastasis. We randomly divide the samples into train set and validation set according to the ratio of 1:1. A prognostic model was constructed using data from the train set and then validated on the validation set. We performed tumor microenvironment analysis and drug sensitivity analyses for high and low risk groups based on the outcome of the prognostic model risk score. Finally, we established a metastatic model of melanoma.

Results

According to the expression levels of 12 cuproptosis-related genes, we obtained three subtypes of A₁, B₁, and C₁. Among them, C₁ subtype had the best survival outcome. Based on the differentially expressed genes shared by A₁, B₁, and C₁ genotypes, we obtained the results of three gene subtypes of A₂, B₂, and C₂. Among them, the B₂ group had the best survival outcome. Then, we constructed a prognostic model consisting of 6 key variable genes, which could more accurately predict the 1-, 3-, and 5-year overall survival rates of melanoma patients. Besides, 98 drugs were screened out. Finally, we explored the role of cuproptosis-related genes in melanoma metastasis and established a metastasis model using seven key genes.

Conclusions

In conclusion, CRGs play a role in the metastasis and prognosis of melanoma, and also provide new insights into the underlying pathogenesis of melanoma.

A cuproptosis-related lncRNA signature identified prognosis and tumour immune microenvironment in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is a heterogeneous malignant tumor with high incidence, metastasis, and mortality. The imbalance of copper homeostasis can produce cytotoxicity and cause cell damage. At the same time, copper can also induce tumor cell death and inhibit tumor transformation. The latest research found that this copper-induced cell death is different from the known cell death pathway, so it is defined as cuproptosis. We included 539 KIRC samples and 72 normal tissues from the Cancer Genome Atlas (TCGA) in our study. After identifying long non-coding RNAs (lncRNAs) significantly associated with cuproptosis, we clustered 526 KIRC samples based on the prognostic lncRNAs and obtained two different patterns (Cuproptosis.C1 and C2). C1 indicated an obviously worse prognostic outcome and possessed a higher immune score and immune cell infiltration level. Moreover, a prognosis signature (CRGscore) was constructed to effectively and accurately evaluate the overall survival (OS) of KIRC patients. There were significant differences in tumor immune microenvironment (TIME) and tumor mutation burden (TMB) between CRGscore-defined groups. CRGscore also has the potential to predict medicine efficacy.