Comprehensive multiomics analysis of cuproptosis-related gene characteristics in hepatocellular 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.

Analysis of the Upregulated Expression Mechanism of Apoptotic Chromatin Condensation Inducer 1 in Hepatocellular Carcinoma Based on Bioinformatics

BACKGROUND/AIMS

 A large number of differentially expressed molecules exist in hepatocellular carcinoma (HCC), and the mechanism by which they upregulate or downregulate expression is still unclear. The purpose of this study is to explore the possible mechanism of differential expression of apoptotic chromatin condensation inducer 1 (Acin1) in HCC.

MATERIALS AND METHODS

 A mouse HCC model was constructed, and the expression of Acin1 in HCC was analyzed by whole transcriptome sequencing, bioinformatics analysis, and reverse transcription-quantitative polymerase chain reaction, and differentially expressed Acin1-related genes were screened to construct a protein-protein interaction and competing endogenous RNA (ceRNA) network. The microRNA (miRNAs) targeting Acin1 were further predicted using online databases and finally compared with sequencing data.

RESULTS

 The expression of Acin1 was significantly up-regulated in HCC compared to the paracancerous and healthy control groups (P<.001). The top 10 upregulated genes closely related to Acin1 (Slc3a2, Wiz, Srrm2, Akt1, Hnrnpu, Sap18b, Pabpn1, Ddx39b, Eif4a3, and Rnps1) were mainly involved in pathways such as messenger RNA (mRNA) surveillance, RNA transport, spliceosome, Janus kinase/ signal transducers and activators of transcription signaling, apoptosis, and ubiquitin-mediated proteolysis. The ceRNA network identified several molecules (2 long noncoding RNAs, 50 miRNAs, and 49 mRNAs) interacting with Acin1, among which miR-674-5p was highly expressed in all sample tissues, and higher than that of other differentially expressed miRNAs, and significantly downregulated in HCC. Multiple online databases such as miRWalk also predicted that miR-674-5p targets Acin1. This shows that miR-674-5p may be an important molecule for targeting Acin1.

CONCLUSION

 Acin1 is overexpressed in HCC, and the overexpressed Acin1 is most likely regulated by miR-674-5p and other ceRNA molecules.

Copper metabolism and hepatocellular carcinoma: current insights

Copper is an essential trace element that acts as a cofactor in various enzyme active sites in the human body. It participates in numerous life activities, including lipid metabolism, energy metabolism, and neurotransmitter synthesis. The proposal of "Cuproptosis" has made copper metabolism-related pathways a research hotspot in the field of tumor therapy, which has attracted great attention. This review discusses the biological processes of copper uptake, transport, and storage in human cells. It highlights the mechanisms by which copper metabolism affects hepatocellular carcinogenesis and metastasis, including autophagy, apoptosis, vascular invasion, cuproptosis, and ferroptosis. Additionally, it summarizes the current clinical applications of copper metabolism-related drugs in antitumor therapy.

Impact of Cuproptosis-related markers on clinical status, tumor immune microenvironment and immunotherapy in colorectal cancer: A multi-omic analysis

Background

Cuproptosis, a novel identified cell death form induced by copper, is characterized by aggregation of lipoylated mitochondrial enzymes and the destabilization of Fe-S cluster proteins. However, the function and potential clinical value of cuproptosis and cuproptosis-related biomarkers in colorectal cancer (CRC) remain largely unknown.

Methods

A comprehensive multi-omics (transcriptomics, genomics, and single-cell transcriptome) analysis was performed for identifying the influence of 16 cuproptosis-related markers on clinical status, molecular functions and tumor microenvironment (TME) in CRC. A novel cuproptosis-related scoring system (CuproScore) based on cuproptosis-related markers was also constructed to predict the prognosis of CRC individuals, TME and the response to immunotherapy. In addition, our transcriptome cohort of 15 paired CRC tissue, tissue-array, and various assays in 4 kinds of CRC cell lines in vitro were applied for verification.

Results

Cuproptosis-related markers were closely associated with both clinical prognosis and molecular functions. And the cuproptosis-related molecular phenotypes and scoring system (CuproScore) could distinguish and predict the prognosis of CRC patients, TME, and the response to immunotherapy in both public and our transcriptome cohorts. Besides, the expression, function and clinical significance of these markers were also checked and analyzed in CRC cell lines and CRC tissues in our own cohorts.

Conclusions

In conclusion, we indicated that cuproptosis and CPRMs played a significant role in CRC progression and in modeling the TME. Inducing cuproptosis may be a useful tool for tumor therapy in the future.

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.

Identification and validation of a novel cuproptosis-related genes signature associated with prognosis, clinical implications and immunotherapy of hepatocellular carcinoma

Background: Cuproptosis is a novel type of regulated cell death and is reported to promote tumor occurrence and progression. However, whether a cuproptosis-related signature has an impact on hepatocellular carcinoma (HCC) is still unclear. Materials and methods: We analyzed the transcriptome data of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database, and searched for tumor types with different cuproptosis patterns through consistent clustering of cuproptosis genes. We then constructed a Cuproptosis-Related Genes (CRGs)-based risk signature through LASSO COX regression, and further analyzed its impact on the prognosis, clinical characteristics, immune cell infiltration, and drug sensitivity of HCC. Results: We identified the expression changes of 10 cuproptosis-related genes in HCC, and all the patients can be divided into two subtypes with different prognosis by applying the consensus clustering algorithm. We then constructed a cuproptosis-related risk signature and identified five CRGs, which were highly correlated with prognosis and representative of this gene set, namely G6PD, PRR11, KIF20A, EZH2, and CDCA8. Patients in the low CRGs signature group had a favorable prognosis. We further validated the CRGs signature in ICGC cohorts and got consistent results. Besides, we also discovered that the CRGs signature was significantly associated with a variety of clinical characteristics, different immune landscapes and drug sensitivity. Moreover, we explored that the high CRGs signature group was more sensitive to immunotherapy. Conclusion: Our integrative analysis demonstrated the potential molecular signature and clinical applications of CRGs in HCC. The model based on CRGs can precisely predict the survival outcomes of HCC, and help better guide risk stratification and treatment strategy for HCC patients.

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.

Identification of biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis in alcoholic hepatitis by bioinformatics and experimental verification

Backgrounds

Alcoholic hepatitis (AH) is a major health problem worldwide. There is increasing evidence that immune cells, iron metabolism and copper metabolism play important roles in the development of AH. We aimed to explore biomarkers that are co-associated with M1 macrophages, ferroptosis and cuproptosis in AH patients.

Methods

GSE28619 and GSE103580 datasets were integrated, CIBERSORT algorithm was used to analyze the infiltration of 22 types of immune cells and GSVA algorithm was used to calculate ferroptosis and cuproptosis scores. Using the "WGCNA" R package, we established a gene co-expression network and analyzed the correlation between M1 macrophages, ferroptosis and cuproptosis scores and module characteristic genes. Subsequently, candidate genes were screened by WGCNA and differential expression gene analysis. The LASSO-SVM analysis was used to identify biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis. Finally, we validated these potential biomarkers using GEO datasets (GSE155907, GSE142530 and GSE97234) and a mouse model of AH.

Results

The infiltration level of M1 macrophages was significantly increased in AH patients. Ferroptosis and cuproptosis scores were also increased in AH patients. In addition, M1 macrophages, ferroptosis and cuproptosis were positively correlated with each other. Combining bioinformatics analysis with a mouse model of AH, we found that ALDOA, COL3A1, LUM, THBS2 and TIMP1 may be potential biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis in AH patients.

Conclusion

We identified 5 potential biomarkers that are promising new targets for the treatment and diagnosis of AH patients.

Comprehensive Analysis of Cuproptosis-Related Genes in Prognosis and Immune Infiltration of Hepatocellular Carcinoma Based on Bulk and Single-Cell RNA Sequencing Data

Background: Studies on prognostic potential and tumor immune microenvironment (TIME) characteristics of cuproptosis-related genes (CRGs) in hepatocellular carcinoma (HCC) are limited. Methods: A multigene signature model was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The cuproptosis-related multivariate cox regression analysis and bulk RNA-seq-based immune infiltration analysis were performed. The results were verified using two cohorts. The enrichment of CRGs in T cells based on single-cell RNA sequencing (scRNA-seq) was performed. Real-time polymerase chain reaction (RT-PCR) and multiplex immunofluorescence staining were performed to verify the reliability of the conclusions. Results: A four-gene risk scoring model was constructed. Kaplan−Meier curve analysis showed that the high-risk group had a worse prognosis (p < 0.001). The time-dependent receiver operating characteristic (ROC) curve showed that the OS risk score prediction performance was good. These results were further confirmed in the validation queue. Meanwhile, the Tregs and macrophages were enriched in the cuproptosis-related TIME of HCC. Conclusions: The CRGs-based signature model could predict the prognosis of HCC. Treg and macrophages were significantly enriched in cuproptosis-related HCC, which was associated with the depletion of proliferating T cells.

A prognostic signature of cuproptosis and TCA-related genes for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver. Cuproptosis is a newly defined form of cell death. Copper ion induces cell death by binding to the tricarboxylic acid cycle (TCA). The effect of cuproptosis-related and TCA-related genes on the clinical prognosis of HCC is still unclear. In this study, we explores the genetic changes of cuproptosis-related genes that affect the TCA process and their potential therapeutic value in HCC patients.

Methods

The cuproptosis and TCA-related genes were obtained from cuproptosis-related articles and the molecular signatures database. The prognosis signatures of eight related genes were constructed using the last absolute shrinkage and selection operator (LASSO), and Receiver Operating Characteristic (ROC) curves were used to evaluate the signature. In addition, we analyzed downstream functional enrichment and immune infiltration to explore cuproptosis-inducing drugs and immunotherapeutic responses. All these analyses were validated using multiple datasets of the International Cancer Genome Consortium (ICGC).

Results

TCA and copper malnutrition-related genes (CDKN2A, IDH1, OGDHL, IDH3G, IDH3B, GLS, DLAT, LIPT1) were finally included. According to the risk score, they were divided into high-risk and low-risk groups. Survival analysis showed that the overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group. We established a risk prognostic feature to predict the OS of patients with HCC. Based on this feature and the clinical stage, we constructed a nomogram. Functional enrichment analysis revealed pathways related to organelle division and the cell cycle. Different risk scores had different immune abundances in immune cells (including macrophages and regulatory T-cells) and immune pathways (including antigen-presenting cells co-stimulation). Moreover, the drug sensitivity of eleschomol and PD-L1 in the high-risk group was better than that in the low-risk group. The status of TP53 somatic mutation was also closely related to the risk score.

Conclusion

In this study, we established a new prediction signature of eight genes related to cuproptosis and the TCA process, which can effectively predict the prognosis of HCC patients.