Cuproptosis-Related Risk Score Predicts Prognosis and Characterizes the Tumor Microenvironment in Hepatocellular Carcinoma

Deciphering cuproptosis-related signatures in pediatric allergic asthma using integrated scRNA-seq and bulk RNA-seq analysis

OBJECTIVE

Allergic asthma (AA) is common in children. Excess copper is observed in AA patients. It is currently unclear whether copper imbalance can cause cuproptosis in pediatric AA.

METHODS

The datasets about pediatric AA (GSE40732 and GSE40888) were obtained from Gene Expression Omnibus (GEO) database. The expression of cuproptosis-related genes (CRGs) and immune cell infiltration in pediatric AA samples were analyzed. Single-cell RNA sequencing (scRNA-seq) data (GSE193816) were used to evaluate the expression patterns of CRGs in AA. The identification of differentially expressed genes within clusters was conducted using weighted gene co-expression network analysis. Subsequently, disease progression and cuproptosis-related models were screened using random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and general linear model (GLM) algorithms.

RESULTS

Four CRGs were notably increased in pediatric AA samples. CD4+ T cells, macrophages and mast cells exhibited a lower cuproptosis score in AA samples, indicating that these immune cells may be closely associated with cuproptosis in AA development. Co-expression network of CRGs in AA was constructed. AA samples were divided into two cuprotosis clusters. Following construction of four machine-learning models, SVM model exhibited the highest efficacy of prediction in the testing set (AUC = 0.952). SVM model containing five important variables can be used for prediction of AA.

CONCLUSION

This work provided a machine learning model containing five important variables, which may have good diagnostic efficiency for pediatric AA.

Copper homeostasis and cuproptosis in health and disease

Copper is a vital trace element in human physiology, essential for the synthesis of numerous crucial metabolic enzymes and facilitation of various biological processes. Regulation of copper levels within a narrow range is imperative for maintaining metabolic homeostasis. Numerous studies have demonstrated the significant roles of copper homeostasis and cuproptosis in health and disease pathogenesis. However, a comprehensive and up-to-date systematic review in this domain remains absent. This review aims to consolidate recent advancements in understanding the roles of cuproptosis and copper homeostasis in health and disease, focusing on the underlying mechanisms and potential therapeutic interventions. Dysregulation of copper homeostasis, manifesting as either copper excess or deficiency, is implicated in the etiology of various diseases. Cuproptosis, a recently identified form of cell death, is characterized by intracellular copper overload. This phenomenon mediates a diverse array of evolutionary processes in organisms, spanning from health to disease, and is implicated in genetic disorders, liver diseases, neurodegenerative disorders, and various cancers. This review provides a comprehensive summary of the pathogenic mechanisms underlying cuproptosis and copper homeostasis, along with associated targeted therapeutic agents. Furthermore, it explores future research directions with the potential to yield significant advancements in disease treatment, health management, and disease prevention.

Alterations in Astrocyte Subpopulations in Glioma and Identification of Cuproptosis-Related Genes Using Single-Cell RNA Sequencing

Purpose

Mitochondrial metabolism is essential for energy production and the survival of brain cells, particularly in astrocytes. Cuproptosis is a newly identified form of programmed cell death that occurs due to the disruption of mitochondrial metabolism caused by excessive copper toxicity. However, the relationship between cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) and the prognosis of gliomas remains unclear.

Patients and Methods

In this study, we utilized 32,293 cells obtained from three in-house single-cell RNA sequencing (scRNA-seq) datasets, along with 6,148 cells acquired from the Chinese Glioma Genome Atlas (CGGA) involving 14 glioma patients, to identify and validate the TME of gliomas.

Results

Based on an analysis of 32,293 single cells, we investigated intra-tumor heterogeneity, intercellular communication, and astrocyte differentiation trajectories in gliomas. Our findings revealed that the TGFβ signaling pathway exhibited a higher relative strength in astrocyte subpopulations. Additionally, we identified a novel three-gene signature (CDKN2A, SOX2, and MPC1) was identified for prognostic prediction. Furthermore, glioma patients with a high-risk score demonstrated poorer overall survival (OS) compared to those with a low-risk score in both training and testing datasets (P training set < 0.001; P test set = 0.037).

Conclusion

Our study revealed the prognostic value of the CRGs in astrocytes exhibiting tumor immunosuppressive characteristics in glioma. We established a novel three-gene prognostic model that offers new insights into the prognosis and treatment strategies for gliomas.

From bioinformatics to clinical applications: a novel prognostic model of cuproptosis-related genes based on single-cell RNA sequencing data in hepatocellular carcinoma

OBJECTIVE AND METHODS

To ascertain the connection between cuproptosis-related genes (CRGs) and the prognosis of hepatocellular carcinoma (HCC) via single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data, relevant data were downloaded from the GEO and TCGA databases. The differentially expressed CRGs (DE-CRGs) were filtered by the overlaps in differentially expressed genes (DEGs) between HCC patients and normal controls (NCs) in the scRNA-seq database, DE-CRGs between high- and low-CRG-activity cells, and DEGs between HCC patients and NCs in the TCGA database.

RESULTS

Thirty-three DE-CRGs in HCC were identified. A prognostic model (PM) was created employing six survival-related genes (SRGs) (NDRG2, CYB5A, SOX4, MYC, TM4SF1, and IFI27) via univariate Cox regression analysis and LASSO. The predictive ability of the model was validated via a nomogram and receiver operating characteristic curves. Research has employed tumor immune dysfunction and exclusion as a means to examine the influence of PM on immunological heterogeneity. Macrophage M0 levels were significantly different between the high-risk group (HRG) and the low-risk group (LRG), and a greater macrophage level was linked to a more unfavorable prognosis. The drug sensitivity data indicated a substantial difference in the half-maximal drug-suppressive concentrations of idarubicin and rapamycin between the HRG and the LRG. The model was verified by employing public datasets and our cohort at both the protein and mRNA levels.

CONCLUSION

A PM using 6 SRGs (NDRG2, CYB5A, SOX4, MYC, TM4SF1, and IFI27) was developed via bioinformatics research. This model might provide a fresh perspective for assessing and managing HCC.

Metal-polyphenol-network coated R612F nanoparticles reduce drug resistance in hepatocellular carcinoma by inhibiting stress granules

Stress granules (SGs) are considered to be the nonmembrane discrete assemblies present in the cytoplasm to cope with various environmental stress. SGs can promote the progression and drug resistance of hepatocellular carcinoma (HCC). Therefore, it is important to explore the mechanism of SG formation to reduce drug resistance in HCC. In this study, we demonstrate that p110α is required for SGs assembly. Mechanistically, the Arg-Gly (RG) motif of p110α is required for SG competence and regulates the recruitment of SG components. The methylation of p110α mediated by protein arginine methyltransferase 1 (PRMT1) interferes with the recruitment of p110α to SG components, thereby inhibiting the promotion of p110α to SGs. On this basis, we generated metal-polyphenol-network-coated R612F nanoparticles (MPN-R612F), which can efficiently enter HCC cells and maintain the hypermethylation state of p110α, thereby inhibiting the assembly of SGs and ultimately reducing the resistance of HCC cells to sorafenib. The combination of MPN-R612F nanoparticles and sorafenib can kill HCC cells more effectively and play a stronger anti-tumor effect. This study provides a new perspective for targeting SGs in the treatment of HCC.

New perspectives on chemokines in hepatocellular carcinoma therapy: a critical pathway for natural products regulation of the tumor microenvironment

Hepatocellular carcinoma (HCC) is one of the most common primary neoplasms of the liver and one of the most common solid tumors in the world. Its global incidence is increasing and it has become the third leading cause of cancer-related deaths. There is growing evidence that chemokines play an important role in the tumor microenvironment, regulating the migration and localization of immune cells in tissues and are critical for the function of the immune system. This review comprehensively analyses the expression and activity of chemokines in the TME of HCC and describes their interrelationship with hepatocarcinogenesis and progression. Special attention is given to the role of chemokine-chemokine receptors in the regulation of immune cell accumulation in the TME. Therapeutic strategies targeting tumor-promoting chemokines or the induction/release of beneficial chemokines are reviewed, highlighting the potential value of natural products in modulating chemokines and their receptors in the treatment of HCC. The in-depth discussion in this paper provides a theoretical basis for the treatment of HCC. It is an important reference for new drug development and clinical research.

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.

Cuproptosis, the novel type of oxidation-induced cell death in thoracic cancers: can it enhance the success of immunotherapy?

Copper is an important metal micronutrient, required for the balanced growth and normal physiological functions of human organism. Copper-related toxicity and dysbalanced metabolism were associated with the disruption of intracellular respiration and the development of various diseases, including cancer. Notably, copper-induced cell death was defined as cuproptosis which was also observed in malignant cells, representing an attractive anti-cancer instrument. Excess of intracellular copper leads to the aggregation of lipoylation proteins and toxic stress, ultimately resulting in the activation of cell death. Differential expression of cuproptosis-related genes was detected in normal and malignant tissues. Cuproptosis-related genes were also linked to the regulation of oxidative stress, immune cell responses, and composition of tumor microenvironment. Activation of cuproptosis was associated with increased expression of redox-metabolism-regulating genes, such as ferredoxin 1 (FDX1), lipoic acid synthetase (LIAS), lipoyltransferase 1 (LIPT1), dihydrolipoamide dehydrogenase (DLD), drolipoamide S-acetyltransferase (DLAT), pyruvate dehydrogenase E1 subunit alpha 1 (PDHA1), and pyruvate dehydrogenase E1 subunit beta (PDHB)). Accordingly, copper-activated network was suggested as an attractive target in cancer therapy. Mechanisms of cuproptosis and regulation of cuproptosis-related genes in different cancers and tumor microenvironment are discussed in this study. The analysis of current findings indicates that therapeutic regulation of copper signaling, and activation of cuproptosis-related targets may provide an effective tool for the improvement of immunotherapy regimens.

Cuproptosis and physical training: A review

Copper is an essential element in the human body, involved in many physiological and metabolic functions, including coagulation, oxidative metabolism, and hormone production. The maintenance of copper homeostasis within cells is a complex procedure that is intrinsically controlled by a multitude of intricate mechanisms. Disorders of copper homeostasis encompass a wide range of pathological conditions, including degenerative neurological diseases, metabolic disorders, cardio-cerebrovascular diseases, and tumors. Cuproptosis, a recently identified non-apoptotic mode of cell death mode, is characterized by copper dependence and the regulation of mitochondrial respiration. Cuproptosis represents a novel form of cell death distinct from the previously described modes, including apoptosis, necrosis, pyroptosis, and ferroptosis. Excess copper has been shown to induce cuproptosis by stimulating protein toxic stress responses via copper-dependent abnormal oligomerization of lipoylation proteins within the tricarboxylic acid cycle and the subsequent reduction of iron-sulfur cluster protein levels. Ferredoxin1 facilitates the lipoacylation of dihydrolipoyl transacetylase, which in turn degrades iron-sulfur cluster proteins by reducing Cu2+ to Cu+, thereby inducing cell death. Furthermore, copper homeostasis is regulated by the copper transporter, and disturbances in this homeostasis result in cuproptosis. Current evidence suggests that cuproptosis plays an important role in the onset and development of several cardiovascular diseases. Copper-chelating agents, including ammonium tetrathiomolybdate (VI) and DL-penicillamine, have been shown to facilitate the alleviation of cardiovascular disease by inhibiting cuproptosis. It is hypothesized that oxidative phosphorylation inhibitors such as physical training may inhibit cuproptosis by inhibiting the protein stress response. In conclusion, the implementation of physical training may be a viable strategy to reducte the incidence of cuproptosis.

Developing an advanced diagnostic model for hepatocellular carcinoma through multi-omics integration leveraging diverse cell-death patterns

Introduction

Hepatocellular carcinoma (HCC), representing more than 80% of primary liver cancer cases, lacks satisfactory etiology and diagnostic methods. This study aimed to elucidate the role of programmed cell death-associated genes (CDRGs) in HCC by constructing a diagnostic model using single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data.

Methods

Six categories of CDRGs, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA-seq data from blood-derived exosomes were sourced from the exoRBase database, RNA-seq data from cancer tissues from the TCGA database, and scRNA-seq data from the GEO database. Subsequently, we intersected the differentially expressed genes (DEGs) of the HCC cohort from exoRBase and TCGA databases with CDRGs, as well as DEGs obtained from single-cell datasets. Candidate biomarker genes were then screened using clinical indicators and a machine learning approach, resulting in the construction of a seven-gene diagnostic model for HCC. Additionally, scRNA-seq and spatial transcriptome sequencing (stRNA-seq) data of HCC from the Mendeley data portal were used to investigate the underlying mechanisms of these seven key genes and their association with immune checkpoint blockade (ICB) therapy. Finally, we validated the expression of key molecules in tissues and blood-derived exosomes through quantitative Polymerase Chain Reaction (qPCR) and immunohistochemistry experiments.

Results

Collectively, we obtained a total of 50 samples and 104,288 single cells. Following the meticulous screening, we established a seven-gene diagnostic model for HCC, demonstrating high diagnostic efficacy in both the exoRBase HCC cohort (training set: AUC = 1; testing set: AUC = 0.847) and TCGA HCC cohort (training set: AUC = 1; testing set: AUC = 0.976). Subsequent analysis revealed that HCC cluster 3 exhibited a higher stemness index and could serve as the starting point for the differentiation trajectory of HCC cells, also displaying more abundant interactions with other cell types in the microenvironment. Notably, key genes TRIB3 and NQO1 displayed elevated expression levels in HCC cells. Experimental validation further confirmed their elevated expression in both tumor tissues and blood-derived exosomes of cancer patients. Additionally, stRNA analysis not only substantiated these findings but also suggested that patients with high TRIB3 and NQO1 expression might respond more favorably to ICB therapy.

Conclusions

The seven-gene diagnostic model demonstrated remarkable accuracy in HCC screening, with TRIB3 emerging as a promising diagnostic tool and therapeutic target for HCC.

Multi-omics analysis of the prognostic and biological role of cuproptosis-related gene in gastric cancer

Background

A considerable number of gastric cancer (GC) patients cannot receive benefits from current treatments. We aimed to identify possible biomarkers of cuproptosis-related genes (CRGs) in GC patients, which may help guide precision medicine-based decision-making.

Methods

RNA sequencing data, copy number variations (CNVs) data, and single nucleotide variant (SNV) data were obtained from The Cancer Genome Atlas (TCGA) database and Gene Set Cancer Analysis (GSCA) database. Chi-squared test was adopted to screen differentially expressed CRGs (DE-CRGs) between samples from 14 kinds of carcinoma and adjacent tissue samples. Then, GC samples were divided into high- and low-expressed groups based on DE-CRGs for further survival analyses and the selection of biomarkers. Methylation sites related with biomarkers were acquired. The correlation between immune cells and biomarkers was verified. Finally, miRNA-mRNA, TFs-mRNA, and co-expression networks were established to detect factors with regulating effects on biomarkers.

Results

Three CRGs including LIAS, GLS, and CDKN2A were identified as biomarkers in GC patients. Three methylation sites with a significant survival effect including cg13601799, 07562918, and 07253264 were acquired. Then, we found that B cells native was significantly correlated with CDKN2A, four immune cells such as T cells regulatory are significantly correlated with GLS, and two immune cells such as T cells CD4 memory activated were significantly correlated with LIAS. Moreover, 10 miRNAs in the miRNA-mRNA network and three transcription factors (TFs) in the TFs-mRNA network had a significant correlation with overall survival (OS). Finally, 20 enrichment functions were obtained on the basis of the co-expression network.

Conclusions

Three biomarkers with a prognosis prediction value of GC were found, and multi-factor regulatory networks were constructed to screen out 13 factors with regulating influences of biomarkers.

Cuproptosis in cancer: biological implications and therapeutic opportunities

Cuproptosis, a newly identified copper (Cu)-dependent form of cell death, stands out due to its distinct mechanism that sets it apart from other known cell death pathways. The molecular underpinnings of cuproptosis involve the binding of Cu to lipoylated enzymes in the tricarboxylic acid cycle. This interaction triggers enzyme aggregation and proteotoxic stress, culminating in cell death. The specific mechanism of cuproptosis has yet to be fully elucidated. This newly recognized form of cell death has sparked numerous investigations into its role in tumorigenesis and cancer therapy. In this review, we summarized the current knowledge on Cu metabolism and its link to cancer. Furthermore, we delineated the molecular mechanisms of cuproptosis and summarized the roles of cuproptosis-related genes in cancer. Finally, we offered a comprehensive discussion of the most recent advancements in Cu ionophores and nanoparticle delivery systems that utilize cuproptosis as a cutting-edge strategy for cancer treatment.

Crosstalk of non-apoptotic RCD panel in hepatocellular carcinoma reveals the prognostic and therapeutic optimization

Non-apoptotic regulated cell death (RCD) of tumor cells profoundly affects tumor progression and plays critical roles in determining response to immune checkpoint inhibitors (ICIs). Prognosis-distinctive HCC subtypes were identified by consensus cluster analysis based on the expressions of 507 non-apoptotic RCD genes obtained from databases and literature. Meanwhile, a set of bioinformatic tools was integrated to analyze the differences of the tumor immune microenvironment infiltration, genetic mutation, copy number variation, and epigenetics alternations within two subtypes. Finally, a non-apoptotic RCDRS signature was constructed and its reliability was evaluated in HCC patients' tissues. The high-RCDRS HCC subgroup showed a significantly lower overall survival and less sensitivity to ICIs compared to low-RCDRS subgroup, but higher sensitivity to cisplatin, paclitaxel, and sorafenib. Overall, we established an RCDRS panel consisting of four non-apoptotic RCD genes, which might be a promising predictor for evaluating HCC prognosis, guiding therapeutic decision-making, and ultimately improving patient outcomes.

Clinical features and molecular landscape of cuproptosis signature-related molecular subtype in gastric cancer

Recent studies have highlighted the biological significance of cuproptosis in disease occurrence and development. However, it remains unclear whether cuproptosis signaling also has potential impacts on tumor initiation and prognosis of gastric cancer (GC). In this study, 16 cuproptosis-related genes (CRGs) transcriptional profiles were harnessed to perform the regularized latent variable model-based clustering in GC. A cuproptosis signature risk scoring (CSRS) scheme, based on a weighted sum of principle components of the CRGs, was used to evaluate the prognosis and risk of individual tumors of GC. Four distinct cuproptosis signature-based clusters, characterized by differential expression patterns of CRGs, were identified among 1136 GC samples across three independent databases. The four clusters were also associated with different clinical outcomes and tumor immune contexture. Based on the CSRS, GC patients can be divided into CSRS-High and CSRS-Low subtypes. We found that DBT, MTF1, and ATP7A were significantly elevated in the CSRS-High subtype, while SLC31A1, GCSH, LIAS, DLAT, FDX1, DLD, and PDHA1 were increased in the CSRS-Low subtype. Patients with CSRS-Low score were characterized by prolonged survival time. Further analysis indicated that CSRS-Low score also correlated with greater tumor mutation burden (TMB) and higher mutation rates of significantly mutated genes (SMG) in GC. In addition, the CSRS-High subtype harbored more significantly amplified focal regions related to tumorigenesis (3q27.1, 12p12.1, 11q13.3, etc.) than the CSRS-Low tumors. Drug sensitivity analyses revealed the potential compounds for the treatment of gastric cancer with CSRS-High score, which were experimentally validated using GC cells. This study highlights that cuproptosis signature-based subtyping is significantly associated with different clinical features and molecular landscape of GC. Quantitative evaluation of the CSRS of individual tumors will strengthen our understanding of the occurrence and development of cuproptosis and the treatment progress of GC.

A Cuproptosis-Related LncRNA Risk Model for Predicting Prognosis and Immunotherapeutic Efficacy in Patients with Hepatocellular Carcinoma

Cuproptosis is a novel programmed cell death pathway that is initiated by direct binding of copper to lipoylated tricarboxylic acid (TCA) cycle proteins. Recent studies have demonstrated that cuproptosis-related genes regulate tumorigenesis. However, the potential role and clinical significance of cuproptosis-related long noncoding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) have not been established. We performed a bioinformatics analyses of RNA-sequencing data of HCC patients extracted from The Cancer Genome Atlas (TCGA) dataset to identify and validate a cuproptosis-related lncRNA prognostic signature. Furthermore, we analyzed the clinical significance of the prognostic signature of cuproptosis-related lncRNA in predicting the immunotherapeutic efficacy and the status of the tumor immune microenvironment. The RNA-sequencing data, genomic mutations, and clinical information were downloaded for 374 HCC samples and 50 normal liver samples from TCGA-Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. Co-expression analysis of Gene-lncRNA pairs with 49 known cuproptosis-related prognostic genes was used to define cuproptosis-related prognostic lncRNAs. We performed the LASSO algorithm and univariate and multivariate Cox regression analysis, respectively, to gradually identify the prognostic risk models of cuproptosis-related lncRNA based on the TCGA-LIHC dataset. Subsequently, the predictive performance of the model was evaluated using receiver operation characteristic (ROC) curves, Kaplan-Meier survival curves, and prognostic nomogram. The analysis of gene-lncRNA co-expression with 49 known cuproptosis-related genes identified 1359 cuproptosis-related lncRNAs in the TCGA-LIHC data set. A prognostic model was constructed with nine cuproptosis-related prognostic lncRNAs (AC007998.3, AC003086.1, AC009974.2, IQCH-AS1, LINC0256 1, AC105345.1, ZFPM2-AS1, AL353708.1 and WAC-AS1) using LASSO regression and Cox regression analyses. Risk scores were calculated for all HCC patient samples based on the four cuproptosis-related lncRNA prognostic models. All HCC patients were divided into high-risk and low-risk subgroups according to a 1:1 ratio column. The Kaplan-Meier survival curve analysis showed that the overall survival rate (OS) of the high-risk group patients was significantly lower than that of the low-risk group. The principal component analysis (PCA) confirmed that the prognostic lncRNA model accurately distinguished between high- and low-risk HCC patients. Furthermore, regression analysis as well as ROC curves confirmed the prognostic value of the risk score. A nomogram with risk scores and other clinicopathological characteristics was constructed. The nomogram accurately predicted the probability of 1-, 3-, and 5-year OS in HCC patients. Tumor mutation burden (TMB) scores were higher for high-risk patients than for low-risk patients. HCC patients in the low-risk group showed lower TIDE scores and greater sensitivity to antitumor drugs than those in the high-risk group. Tumor immune responses and tumor immune cell infiltration were significantly different between the high-risk and low-risk groups of patients with HCC. Our study identified a 9-cuproptosis-related lncRNA signature that accurately predicted prognosis, immunotherapeutic efficacy, and the status of the tumor immune microenvironment in HCC patients. Therefore, this cuproptosis-related lncRNA risk model is a potential prognostic biometric feature in HCC and shows high clinical value in identifying HCC patients who are potentially responsive to immunotherapy.

Distinct cuproptosis patterns in hepatocellular carcinoma patients correlate with unique immune microenvironment characteristics and cell-cell communication, contributing to varied overall survival outcomes

Background

Hepatocellular carcinoma (HCC), a prevalent cancer, is linked to cuproptosis in tumor progression. However, cuproptosis's impact on HCC prognosis and its role in the tumor microenvironment remain unclear. We aimed to explore the correlation between cellular cuproptosis and the immune microenvironment in HCC, providing potential immunotherapeutic insights.

Methods

Examining cuproptosis-related genes and the immune microenvironment through consensus clustering and WGCNA. Risk models were constructed using LASSO Cox analysis and validated in an independent cohort. Gene expression data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized. We scored cuproptosis expression and explored immunoinfiltration and cell-cell communication. Differential signals in T_memory cells were compared across different cuproptosis levels.

Results

Cuproptosis genes associated with fibroblast recruitment (GLS) and macrophage infiltration (FDX1). Liver cancer patients categorized into two subtypes based on cuproptosis gene expression. High expression of DLAT, GLS, and CDKN2A linked to immunosuppression (TGF-β), while high FDX1, MTF1, LIAS, and LIPT1 expression enhanced communication with non-immune cells. Developed reliable prognostic signature score and nomogram using cuproptosis-related genes. Single-cell analysis revealed differences in T_memory and TAM infiltration based on cuproptosis scores, with SPP1 and MIF as dominant signaling molecules. Finally, the results of in vitro experiments showed that when DLAT or CDKN2A was knocked down, the proliferation, migration, and invasion of HCC cells were significantly decreased.

Conclusion

Our study demonstrates that cuproptosis affects the immune microenvironment and cell-cell communication. Identified 9 genetic markers predicting survival outcomes and immunotherapy responses. Evaluating cuproptosis signaling can optimize immunotherapeutic strategies for hepatocellular carcinoma.

A cuproptosis-related signature predicts prognosis and indicates cross-talk with immunocyte in ovarian cancer

PURPOSE

Cuproptosis, programmed cell death by intracellular copper-mediated lipoylated protein aggregation, is involved in various tumorigenesis and drug resistance abilities by mediating the tumor microenvironment. Previous studies have demonstrated that serum copper levels are higher in OC patients than in normal subjects. However, the exact relationship between cuproptosis and ovarian cancer progression remains to be further elucidated.

METHODS

The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) datasets were utilized to establish a cuproptosis-related prognostic signature in ovarian cancer. Subsequently, the bulk RNA-seq analysis and single-cell RNA-seq analysis were used to identify the relationship between signature with immune cell infiltration, chemotherapy, and cuproptosis-related scoring (CuRS) system. Finally, the potential biological functional roles of target genes in cuproptosis were validated in vitro.

RESULTS

By using LASSO-Cox regression analysis to establish the cuproptosis-related prognostic model, our works demonstrated the accuracy and efficiency of our model in the TCGA (583 OC patients) and GEO (260 OC patients) OC cohorts, and the high-scoring groups showed worse survival outcomes. Notably, there were substantial differences between the high and low-risk groups in extensive respects, such as the activating transcription factors, cell pseudotime features, cell intercommunication patterns, immunocytes infiltration, chemotherapy response, and potential drug resistance. KIF26B was selected to construct a prognostic model from the identified 33 prognosis-related genes, and high expression of KIF26B predicted poorer prognosis in ovarian cancer. Ultimately, further in vitro experiments demonstrated that KIF26B participated in the proliferation and cisplatin resistance of OC cells. Knockdown of KIF26B increased the sensitivity of OC cells to elesclomol, a cuproptosis agonists.

CONCLUSION

This study constructed a new cuproptosis-related gene signature that has a good prognostic capacity in assessing the outcome of OC patients. This study enhances our understanding of cuproptosis associated with ovarian cancer aggressiveness, cross-talk with immunocytes, and serves as a novel chemotherapy strategy.

The role of programmed cell death in osteosarcoma: From pathogenesis to therapy

Osteosarcoma (OS) is a prevalent bone solid malignancy that primarily affects adolescents, particularly boys aged 14-19. This aggressive form of cancer often leads to deadly lung cancer due to its high migration ability. Experimental evidence suggests that programmed cell death (PCD) plays a crucial role in the development of osteosarcoma. Various forms of PCD, including apoptosis, ferroptosis, autophagy, necroptosis, and pyroptosis, contribute significantly to the progression of osteosarcoma. Additionally, different signaling pathways such as STAT3/c-Myc signal pathway, JNK signl pathway, PI3k/AKT/mTOR signal pathway, WNT/β-catenin signal pathway, and RhoA signal pathway can influence the development of osteosarcoma by regulating PCD in osteosarcoma cell. Therefore, targeting PCD and the associated signaling pathways could offer a promising therapeutic approach for treating osteosarcoma.

Cuproptosis: unveiling a new frontier in cancer biology and therapeutics

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

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.

Immune patterns of cuproptosis in ischemic heart failure: A transcriptome analysis

Cuproptosis is a recently discovered programmed cell death pattern that affects the tricarboxylic acid (TCA) cycle by disrupting the lipoylation of pyruvate dehydrogenase (PDH) complex components. However, the role of cuproptosis in the progression of ischemic heart failure (IHF) has not been investigated. In this study, we investigated the expression of 10 cuproptosis-related genes in samples from both healthy individuals and those with IHF. Utilizing these differential gene expressions, we developed a risk prediction model that effectively distinguished healthy and IHF samples. Furthermore, we conducted a comprehensive evaluation of the association between cuproptosis and the immune microenvironment in IHF, encompassing infiltrated immunocytes, immune reaction gene-sets and human leukocyte antigen (HLA) genes. Moreover, we identified two different cuproptosis-mediated expression patterns in IHF and explored the immune characteristics associated with each pattern. In conclusion, this study elucidates the significant influence of cuproptosis on the immune microenvironment in ischemic heart failure (IHF), providing valuable insights for future mechanistic research exploring the association between cuproptosis and IHF.

Establishment and verification of a prognostic model based on coagulation and fibrinolysis-related genes in hepatocellular carcinoma

BACKGROUND

Studies have shown that coagulation and fibrinolysis (CFR) are correlated with Hepatocellular carcinoma (HCC) progression and prognosis. We aim to build a model based on CFR-correlated genes for risk assessment and prediction of HCC patient.

METHODS

HCC samples were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases respectively. The Molecular Signatures Database (MSigDB) was used to select the CFR genes. RiskScore model were established by single sample gene set enrichment analysis (ssGSEA), weighted correlation network analysis (WGCNA), multivariate Cox regression analysis, LASSO regression analysis.

RESULTS

PCDH17, PGF, PDE2A, FAM110D, FSCN1, FBLN5 were selected as the key genes and designed a RiskScore model. Those key genes were Differential expressions in HCC cell and patients. Overexpression PDE2A inhibited HCC cell migration and invasion. The higher the RiskScore, the lower the probability of survival. The model has high AUC values in the first, third and fifth year prediction curves, indicating that the model has strong prediction performance. The difference analysis of clinicopathological features found that a great proportion of high clinicopathological grade samples showed higher RiskScore. RiskScore were positively correlated with immune scores and TIDE scores. High levels of immune checkpoints and immunomodulators were observed in high RiskScore group. High RiskScore groups may benefit greatly from taking traditional chemotherapy drugs.

CONCLUSIONS

We screened CFR related genes to design a RiskScore model, which could accurately evaluate the prognosis and survival status of HCC patients, providing certain value for optimizing the clinical treatment of cancer in the future.

Cuproptosis-Related Gene FDX1 Suppresses the Growth and Progression of Colorectal Cancer by Retarding EMT Progress

Colorectal cancer (CRC) is a usual cancer and a kind of lethiferous cancer. Cuproptosis-related gene ferredoxin 1 (FDX1) has been discovered to act as a suppressor, thereby suppressing some cancers' progression. But, the regulatory functions of FDX1 in CRC progression keep vague. In this work, at first, through TCGA database, it was revealed that FDX1 exhibited lower expression in COAD (colon adenocarcinoma) tissues, and CRC patients with lower FDX1 expression had worse prognosis. Furthermore, FDX1 expression was verified to be down-regulated in CRC tissues (n = 30) and cells. It was further uncovered that FDX1 expression was positively correlated with CDH1 and TJP1 (epithelial marker), and negatively correlated with CDH2, TWIST1, and FN1 (stromal marker), suggesting that FDX1 was closely associated with the epithelial-mesenchymal transition (EMT) progress. Next, it was demonstrated that overexpression of FDX1 suppressed cell viability, invasion, and migration in CRC. Furthermore, it was verified that FDX1 retarded the EMT progress in CRC. Lastly, through rescue assays, the inhibited CRC progression mediated by FDX1 overexpression was rescued by EGF (EMT inducer) treatment. At last, it was uncovered that the tumor growth and metastasis were relieved after FDX1 overexpression, but these changes were reversed after EGF treatment. In conclusion, FDX1 inhibited the growth and progression of CRC by inhibiting EMT progress. This discovery hinted that FDX1 may act as an effective candidate for CRC treatment.

Genomic and immune landscape in hepatocellular carcinoma: Implications for personalized therapeutics

Hepatocellular carcinoma (HCC) is a globally prevalent malignancy, marked by genetic heterogeneity and intricate tumor microenvironment interactions. In this study, we undertook a detailed single-cell analysis of six active HCC patients, highlighting strong correlations between gene expression levels and cellular characteristics. UMAP clustering revealed seven distinct cell categories with associated gene expressions. A divergence was observed in tumor cells into high and low cuproptosis groups, each associated with distinct pathways: oxidative stress for the high cuproptosis group and inflammatory and angiogenesis pathways for the low group. CellChat analysis on the TCGA-LIHC cohort displayed unique intercellular interactions among hepatocytes, T cells, and other cells, with pathways like COLLAGEN and VEGF being pivotal. Functional enrichment analyses exposed pathways enriched between cuproptosis groups, with KEGG emphasizing diseases like Parkinson's. COX survival analysis identified key prognostic genes, revealing distinct survival rates between risk groups in TCGA and GSE14520 cohorts. Mutation data highlighted missense mutations, with TTN, TP53, and CTNNB1 being the most mutated in HCC. Immune infiltration analysis via CIBERSORTx indicated differences between risk groups in NK cells, neutrophils, and other cells. Our drug sensitivity investigation showed significant correlations between model genes and drug responsiveness, emphasizing the importance of patient risk stratification for therapeutic approaches. Further, ATP6V1G1 was recognized in its role in apoptosis and migration in HCC cells. In conclusion, our findings illuminate the complexities of HCC progression, potential predictive genetic markers for drug response, and the pivotal role of ATP6V1G1, suggesting avenues for targeted therapeutic strategies in HCC.

Development and Validation of the novel Cuproptosis- and Immune-related Signature for Predicting Prognosis in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma often results in late-stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. Method: We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. Results: Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk-scoring model was developed using gene expression, effectively categorizing patients into low- or high-risk groups. Validated in the ICGC dataset, high-risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low-risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. Conclusions: The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.

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

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

HTRA1 promotes EMT through the HDAC6/Ac-α-tubulin pathway in human GBM cells

BACKGROUND

The infiltrative nature of human gliomas renders complete surgical removal of tumors futile. Thus, illuminating mechanisms of their infiltrative properties may improve therapies and outcomes of glioma patients.

METHODS

Comprehensive bioinformatic analyses of PRSS family were undertaken. Transfection of HTRA1 siRNAs was used to suppress HTRA1 expression. CCK-8, EdU, and colony formation assay were employed to assess cell viability, and cell migration/invasion was detected by transwell, wound healing, and 3D tumor spheroid invasion assays. Immunoprecipitation was applied to study the mechanism that HTRA1 affected cell migration. In addition, in situ xenograft tumor model was employed to explore the role of HTRA1 in glioma growth in vivo.

RESULTS

HTRA1 knockdown could lead to suppression of cell viability, migration and invasion, as well as increased apoptosis. Immunoprecipitation results indicates HTRA1 might facilitate combination between HDAC6 and α-tubulin to enhance cell migration by decreasing α-tubulin acetylation. Besides, HTRA1 knockdown inhibited the growth of xenografts derived from orthotopic implantation of GBM cells and prolonged the survival time of tumor-bearing mice.

CONCLUSION

Our results indicate that HTRA1 promotes the proliferation and migration of GBM cells in vitro and in vivo, and thus may be a potential target for treatment in gliomas.

Adverse clinical outcomes and immunosuppressive microenvironment of RHO-GTPase activation pattern in hepatocellular carcinoma

BACKGROUND

Emerging evidence suggests that Rho GTPases play a crucial role in tumorigenesis and metastasis, but their involvement in the tumor microenvironment (TME) and prognosis of hepatocellular carcinoma (HCC) is not well understood.

METHODS

We aim to develop a tumor prognosis prediction system called the Rho GTPases-related gene score (RGPRG score) using Rho GTPase signaling genes and further bioinformatic analyses.

RESULTS

Our work found that HCC patients with a high RGPRG score had significantly worse survival and increased immunosuppressive cell fractions compared to those with a low RGPRG score. Single-cell cohort analysis revealed an immune-active TME in patients with a low RGPRG score, with strengthened communication from T/NK cells to other cells through MIF signaling networks. Targeting these alterations in TME, the patients with high RGPRG score have worse immunotherapeutic outcomes and decreased survival time in the immunotherapy cohort. Moreover, the RGPRG score was found to be correlated with survival in 27 other cancers. In vitro experiments confirmed that knockdown of the key Rho GTPase-signaling biomarker SFN significantly inhibited HCC cell proliferation, invasion, and migration.

CONCLUSIONS

This study provides new insight into the TME features and clinical use of Rho GTPase gene pattern at the bulk-seq and single-cell level, which may contribute to guiding personalized treatment and improving clinical outcome in HCC.

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

Background

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

Methods

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

Results

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

Conclusion

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

Cuproptosis-related genes score and its hub gene GCSH: A novel predictor for cholangiocarcinomas prognosis based on RNA seq and experimental analyses

Background: Recent researches have demonstrated that cuproptosis, a copper-dependent cell death mechanism, is related to tumorigenesis, progression, clinical prognosis, tumor microenvironment, and drug sensitivity. Nevertheless, the function and impact of cuproptosis in cholangiocarcinoma (CCA), remain elusive. Methods: Utilizing data obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA-CHOL) datasets, we conducted subgroup typing of CCA according to cuproptosis-related genes (CRGs) and explored functional differences and prognostic value between groups. A CRG score was established considering clinical prognosis and gene expression. Furthermore, differences in the immune microenvironment, response to immunotherapy, metabolic patterns, and cancer progression characteristics between high- and low-risk groups were examined on the basis of these scores. In vitro experiments validated the function of the key gene glycine cleavage system protein H (GCSH) in cellular and tissues, respectively. Results: Prognostic models established on the basis of subgroup genetic differences achieved satisfactory results in validation. Metabolic-related gene expression levels and tumor microenvironment distribution were significantly different between the high and low CRG groups. GCSH was revealed as the singular prognostic CRG in CCA (HR =6.04; 95% CI: 1.15-31.80). Moreover, inhibition of the cupcoptosis key gene GCSH attenuated the malignant ability of CCA cell lines in vitro, including cell proliferation, migration and invasion, and this function of GCSH may be achieved via JAK-STAT signaling in CCA. Conclusion: The CRG scoring system accurately predicts prognosis and opens up new possibilities for cuproptosis-related therapy for CCA. The cuproptosis key gene GCSH has been preliminarily confirmed as a reliable therapeutic target or prognostic marker for CCA patients.

Cuproptosis-Related lncRNAs Modulate the Prognosis of MIBC by Regulating the Expression Pattern of Immunosuppressive Molecules Within the Tumor Microenvironment

Background

Cuproptosis-related gene and long non-coding RNA (lncRNA) modulation of cancer regulation is well-established. This investigation aimed to elucidate the prognostic implications of cuproptosis-associated lncRNAs in muscle-invasive bladder cancer (MIBC).

Methods

Employing the Cancer Genome Atlas (TCGA) and IMvigor210 cohorts, bioinformatics and statistical analyses probed the prognostic relevance of cuproptosis-related lncRNAs.

Results

Co-expression analysis revealed tight associations between lncRNA expression and cuproptosis-linked genes, with 13 cuproptosis-related lncRNAs found to correlate with MIBC prognosis. Lasso regression identified a six-lncRNA prognostic signature, enabling patient stratification into high- and low-risk categories. Tissue validation substantiated differential expression of FAM13A-AS1, GHRLOS, LINC00456, OPA1-AS1, RAP2C-AS1, and UBE2Q1-AS1 between MIBC tumor and normal tissues. Comparative analyses of tumor microenvironments and immune profiles between risk groups disclosed elevated immunosuppressive molecule expression, including programmed cell death-1 (PD-L1) and T-cell immunoglobulin-3 (TIM-3), in high-risk individuals.

Conclusion

These findings suggest that cuproptosis-related lncRNAs may modulate the expression of immunosuppressive molecules, thereby influencing MIBC tumorigenesis and progression. Further exploration is warranted to unveil novel therapeutic targets for MIBC based on the expression patterns of cuproptosis-related lncRNAs and their impact on immune responses in the tumor microenvironment.

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.

Immunomodulation of cuproptosis and ferroptosis in liver cancer

According to statistics, the incidence of liver cancer is increasing yearly, and effective treatment of liver cancer is imminent. For early liver cancer, resection surgery is currently the most effective treatment. However, resection does not treat the disease in advanced patients, so finding a method with a better prognosis is necessary. In recent years, ferroptosis and cuproptosis have been gradually defined, and related studies have proved that they show excellent results in the therapy of liver cancer. Cuproptosis is a new form of cell death, and the use of cuproptosis combined with ferroptosis to inhibit the production of hepatocellular carcinoma cells has good development prospects and is worthy of in-depth discussion by researchers. In this review, we summarize the research progress on cuproptosis combined with ferroptosis in treating liver cancer, analyze the value of cuproptosis and ferroptosis in the immune of liver cancer, and propose potential pathways in oncotherapy with the combination of cuproptosis and ferroptosis, which can provide background knowledge for subsequent related research.

Identification of a new gene signature for prognostic evaluation in cervical cancer: based on cuproptosis-associated angiogenesis and multi-omics analysis

Patients with recurrent or metastatic cervical cancer are in urgent need of novel prognosis assessment or treatment approaches. In this study, a novel prognostic gene signature was discovered by utilizing cuproptosis-related angiogenesis (CuRA) gene scores obtained through weighted gene co-expression network analysis (WGCNA) of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. To enhance its reliability, the gene signature was refined by integrating supplementary clinical variables and subjected to cross-validation. Meanwhile, the activation of the VEGF pathway was inferred from an analysis of cell-to-cell communication, based on the expression of ligands and receptors in cell transcriptomic datasets. High-CuRA patients had less infiltration of CD8 + T cells and reduced expression of most of immune checkpoint genes, which indicated greater difficulty in immunotherapy. Lower IC50 values of imatinib, pazopanib, and sorafenib in the high-CuRA group revealed the potential value of these drugs. Finally, we verified an independent prognostic gene SFT2D1 was highly expressed in cervical cancer and positively correlated with the microvascular density. Knockdown of SFT2D1 significantly inhibited ability of the proliferation, migration, and invasive in cervical cancer cells. CuRA gene signature provided valuable insights into the prediction of prognosis and immune microenvironment of cervical cancer, which could help develop new strategies for individualized precision therapy for cervical cancer patients.

Multi-omics analysis reveals cuproptosis and mitochondria-based signature for assessing prognosis and immune landscape in osteosarcoma

Background

Osteosarcoma (OSA), the most common primary mesenchymal bone tumor, is a health threat to children and adolescents with a dismal prognosis. While cuproptosis and mitochondria dysfunction have been demonstrated to exert a crucial role in tumor progression and development, the mechanisms by which they are regulated in OSA still await clarification.

Methods

Two independent OSA cohorts containing transcriptome data and clinical information were collected from public databases. The heterogeneity of OSA were evaluated by single cell RNA (scRNA) analysis. To identify a newly molecular subtype, unsupervised consensus clustering was conducted. Cox relevant regression methods were utilized to establish a prognostic gene signature. Wet lab experiments were performed to confirm the effect of model gene in OSA cells.

Results

We determined 30 distinct cell clusters and assessed OSA heterogeneity and stemness scRNA analysis. Then, univariate Cox analysis identified 24 candidate genes which were greatly associated with the prognosis of OSA. Based on these prognostic genes, we obtained two molecular subgroups. After conducting step Cox regression, three model genes were selected to construct a signature showing a favorable performance to forecast clinical outcome. Our proposed signature could also evaluate the response to chemotherapy and immunotherapy of OSA cases.

Conclusion

We generated a novel risk model based on cuproptosis and mitochondria-related genes in OSA with powerful predictive ability in prognosis and immune landscape.

Cuproptosis gene-related, neural network-based prognosis prediction and drug-target prediction for KIRC

BACKGROUND

Kidney renal clear cell carcinoma (KIRC), as a common case in renal cell carcinoma (RCC), has the risk of postoperative recurrence, thus its prognosis is poor and its prognostic markers are usually based on imaging methods, which have the problem of low specificity. In addition, cuproptosis, as a novel mode of cell death, has been used as a biomarker to predict disease in many cancers in recent years, which also provides an important basis for prognostic prediction in KIRC. For postoperative patients with KIRC, an important means of preventing disease recurrence is pharmacological treatment, and thus matching the appropriate drug to the specific patient's target is also particularly important. With the development of neural networks, their predictive performance in the field of medical big data has surpassed that of traditional methods, and this also applies to the field of prognosis prediction and drug-target prediction.

OBJECTIVE

The purpose of this study is to screen for cuproptosis genes related to the prognosis of KIRC and to establish a deep neural network (DNN) model for patient risk prediction, while also developing a personalized nomogram model for predicting patient survival. In addition, sensitivity drugs for KIRC were screened, and a graph neural network (GNN) model was established to predict the targets of the drugs, in order to discover potential drug action sites and provide new treatment ideas for KIRC.

METHODS

We used the Cancer Genome Atlas (TCGA) database, International Cancer Genome Consortium (ICGC) database, and DrugBank database for our study. Differentially expressed genes (DEGs) were screened using TCGA data, and then a DNN-based risk prediction model was built and validated using ICGC data. Subsequently, the differences between high- and low-risk groups were analyzed and KIRC-sensitive drugs were screened, and finally a GNN model was trained using DrugBank data to predict the relevant targets of these drugs.

RESULTS

A prognostic model was built by screening 10 significantly different cuproptosis-related genes, the model had an AUC of 0.739 on the training set (TCGA data) and an AUC of 0.707 on the validation set (ICGC data), which demonstrated a good predictive performance. Based on the prognostic model in this paper, patients were also classified into high- and low-risk groups, and functional analyses were performed. In addition, 251 drugs were screened for sensitivity, and four drugs were ultimately found to have high sensitivity, with 5-Fluorouracil having the best inhibitory effect, and subsequently their corresponding targets were also predicted by GraphSAGE, with the most prominent targets including Cytochrome P450 2D6, UDP-glucuronosyltransferase 1A, and Proto-oncogene tyrosine-protein kinase receptor Ret. Notably, the average accuracy of GraphSAGE was 0.817 ± 0.013, which was higher than that of GAT and GTN.

CONCLUSION

Our KIRC risk prediction model, constructed using 10 cuproptosis-related genes, had good independent prognostic ability. In addition, we screened four highly sensitive drugs and predicted relevant targets for these four drugs that might treat KIRC. Finally, literature research revealed that four drug-target interactions have been demonstrated in previous studies and the remaining targets are potential sites of drug action for future research.

Cuproptosis Regulates Microenvironment and Affects Prognosis in Prostate Cancer

Current immunotherapy for prostate cancer is still in the stage of clinical trials. This delay is thought to be caused by an unclear regulatory mechanism of the immune microenvironment, which makes it impossible to distinguish patients suitable for immunotherapy. Cuprotosis may be related to the heterogeneity of immune microenvironment, which was regarded as a new copper-dependent cell death mode, was proposed, and gain attention. We explored for the first time the relationship between cuprotosis and the immune microenvironment of prostate cancer and constructed cuprotosis score. RNA sequencing data sets for prostate cancer were downloaded from public databases. Consensus clustering was applied to distinguish cuprotosis phenotype based on the expression of cuproptosis-related genes (CRGs) identified as prognostic factors. Genomic phenotypes of CRG clusters were depicted via consensus clustering. Cuprotosis score was established on the basis of differentially expressed genes (DEGs) identified as prognostic factors via principal component analysis. Cuprotosis score = the first principal component of prognostic factors + the second principal component of prognostic factors. The value of cuproptosis score in predicting prognosis and immunotherapy response was evaluated. PDHA1 (HR = 3.86, P < 0.001) and GLS (HR = 1.75, P = 0.018) were risk factors for prognosis of prostate cancer patients, while DBT (HR = 0.66, P = 0.048) was a favorable factor for prognosis of prostate cancer patients. CRG clusters had different prognosis and immune cell infiltration. So as gene clusters. Prostate cancer patients with low cuprotosis score showed better prognosis for biochemical relapse-free survival. Cuprotosis score is accompanied with high immune score and Gleason score. As cuprotosis genes, PDHA1, GLS, and DBT were identified as independent prognostic factors of prostate cancer. Cuprotosis score was established via principal component analysis of PDHA1, GLS, and DBT, which can be used as a predictor of prognosis and immunotherapy response of prostate cancer patients, and can characterize immune cells infiltration in tumors. Cuproptosis was involved in the regulation of immune microenvironment, which may depend on the effect of tricarboxylic acid cycle. Our study provided clues to reveal the relationship between copper death and immune microenvironment, highlighted the clinical significance of cuproptosis, and provided a reference for the development of personalized immunotherapy.

Impact of hepatectomy and postoperative adjuvant transarterial chemoembolization on serum tumor markers and prognosis in intermediate-stage hepatocellular carcinoma

BACKGROUND

Primary hepatocellular carcinoma (HCC) is a common malignant tumour, and its early symptoms are often not obvious, resulting in many patients experiencing middle- to late-stage disease at the time of diagnosis. The optimal time for surgery is often missed for these patients, and those who do undergo surgery have unsatisfactory long-term outcomes and a high recurrence rate within five years. Therefore, postoperative follow-up treatments, such as transhepatic arterial chemoembolization (TACE), have become critical to improving survival and reducing recurrence rates.

AIM

To validate the prophylactic role of TACE after hepatic resection and to assess its impact on patient prognosis.

METHODS

This study investigated the efficacy of TACE in patients with intermediate-stage HCC after hepatectomy. When the post-treatment results of the observation group and the control group were compared, it was found that the inclusion of TACE significantly improved the clinical efficacy, reduced the levels of tumour markers and did not aggravate the damage to liver function. Thus, this may be an effective and comprehensive treatment strategy for patients with intermediate-stage HCC that helps to improve their quality of life and survival time.

RESULTS

When the baseline data were analysed, no statistical differences were found between the two groups in terms of gender, age, hepatitis B virus, cirrhosis, Child-Pugh grading, number of tumours, maximum tumour diameter and degree of tumour differentiation. The assessment of clinical efficacy showed that the post-treatment overall remission rate of the observation group was significantly higher than that of the control group. In terms of changes in tumour markers, the alpha-fetoprotein and carcinoembryonic antigen levels in the patients in the observation group decreased more significantly after treatment compared with those in the control group. When post-treatment changes in liver function indicators were analysed, no statistical differences were found in the total bilirubin, alanine aminotransferase and aspartate aminotransferase levels between the two groups.

CONCLUSION

In patients with intermediate-stage HCC, post-hepatectomy TACE significantly improved clinical outcomes, reduced tumour-marker levels and may have improved the prognosis by removing residual lesions. Thus, this may be an effective and comprehensive treatment strategy for patients with intermediate-stage HCC.

Systematic analysis based on the cuproptosis-related genes identifies ferredoxin 1 as an immune regulator and therapeutic target for glioblastoma

Glioblastoma multiforme (GBM) is recognized as the prevailing malignant and aggressive primary brain tumor, characterized by an exceedingly unfavorable prognosis. Cuproptosis, a recently identified form of programmed cell death, exhibits a strong association with cancer progression, therapeutic response, and prognostic outcomes. However, the specific impact of cuproptosis on GBM remains uncertain. To address this knowledge gap, we obtained transcriptional and clinical data pertaining to GBM tissues and their corresponding normal samples from various datasets, including TCGA, CGGA, GEO, and GTEx. R software was utilized for the analysis of various statistical techniques, including survival analysis, cluster analysis, Cox regression, Lasso regression, gene enrichment analysis, drug sensitivity analysis, and immune microenvironment analysis. Multiple assays were conducted to investigate the expression of genes related to cuproptosis and their impact on the proliferation, invasion, and migration of glioblastoma multiforme (GBM) cells. The datasets were obtained and prognostic risk score models were constructed and validated using differentially expressed genes (DEGs) associated with cuproptosis. To enhance the practicality of these models, a nomogram was developed.Patients with glioblastoma multiforme (GBM) who were classified as high risk exhibited a more unfavorable prognosis and shorter overall survival compared to those in the low risk group. Additionally, we specifically chose FDX1 from the differentially expressed genes (DEGs) within the high risk group to assess its expression, prognostic value, biological functionality, drug responsiveness, and immune cell infiltration. The findings demonstrated that FDX1 was significantly upregulated and associated with a poorer prognosis in GBM. Furthermore, its elevated expression appeared to be linked to various metabolic processes and the susceptibility to chemotherapy drugs. Moreover, FDX1 was found to be involved in immune cell infiltration and exhibited correlations with multiple immunosuppressive genes, including TGFBR1 and PDCD1LG2. The aforementioned studies offer substantial assistance in informing the chemotherapy and immunotherapy approaches for GBM. In summary, these findings contribute to a deeper comprehension of cuproptosis and offer novel perspectives on the involvement of cuproptosis-related genes in GBM, thereby presenting a promising therapeutic strategy for GBM patients.

Alternative splicing variants involved in pyroptosis and cuproptosis contribute to phenotypic remodeling of the tumor microenvironment in cervical cancer

Cervical cancer (CC) remains a prevalent gynecological malignancy, posing a significant health burden among women worldwide. With the remarkable discoveries of cellular pyroptosis and cuproptosis, there has been a growing focus on exploring the intricate relationship between these two forms of cell death and their impact on tumor progression. In recent years, alternative splicing has emerged as a significant field in cancer research. Thus, the integration of alternative splicing, pyroptosis, and cuproptosis holds immense value in studying their collective impact on the occurrence and progression of cervical cancer. In this study, alternative splicing data of pyroptosis- and cuproptosis-associated genes were integrated with public databases, including TCGA, to establish a prognostic model for cervical cancer based on COX regression modeling. Subsequently, the tumor microenvironment (TME) phenotypes in the high-risk and low-risk patient groups were characterized through a comprehensive bioinformatics analysis. The findings of this study revealed that the low-risk group exhibited a predominant immune-active TME phenotype, while the high-risk group displayed a tumor-favoring metabolic phenotype. These results indicate that the alternative splicing of pyroptosis- and cuproptosis-associated genes plays a pivotal role in remodeling the phenotypic landscape of the cervical cancer TME by modulating immune responses and metabolic pathways. This study provides valuable insights into the interplay between alternative splicing variants involved in pyroptosis and cuproptosis and the TME, contributing to a deeper understanding of cervical cancer pathogenesis and potential therapeutic avenues.

Comprehensive analysis of diverse programmed cell death patterns in the prognosis, tumor microenvironment and drug sensitivity in hepatocellular carcinoma

Treatment failure in patients with liver hepatocellular carcinoma (LIHC) is primarily caused by tumor progression and therapy resistance. Tumor immunity plays a crucial role in regulating the homeostasis of cells through the process of programmed cell death (PCD). However, the expression profile and clinical significance of PCD-related genes in LIHC require further investigation. In this study, we analyzed twelve commonly observed PCD patterns to construct a prognostic model. We collected RNA-seq data, genomics, and clinical information from TCGA-LIHC and GSE14520 cohorts to validate the prognostic gene signature. We discovered 75 PCD-related differentially expressed genes (DEGs) with prognostic significance in LIHC. Using these genes, we constructed a PCD-related score (PCDscore) with an 11-gene signature through LASSO COX regression analysis. Validation in the GSE14520 cohort demonstrated that LIHC patients with high PCDscore had poorer prognoses. Unsupervised clustering based on the 11 model genes revealed 3 molecular subtypes of LIHC with distinct prognoses. By incorporating PCDscore with clinical features, we constructed a highly predictive nomogram. Additionally, PCDscore was correlated with immune checkpoint genes and immune cell infiltration. LIHC patients with high PCDscore exhibited sensitivity to common chemotherapy drugs (such as cisplatin and docetaxel). To summarize, our study developed a novel PCDscore model that comprehensively analyzed different cell death modes, providing an accurate prediction of clinical prognosis and drug sensitivity for LIHC patients.

Cuproptosis-related molecular patterns and gene (ATP7A) in hepatocellular carcinoma and their relationships with tumor immune microenvironment and clinical features

BACKGROUND

Cuproptosis has been studied in various aspects as a new form of cell death.

AIMS

We hope to explore the molecular patterns and genes related to cuproptosis in evaluating and predicting the prognosis of hepatocellular carcinoma (HCC), as well as the impact of tumor immune microenvironment.

METHODS AND RESULTS

Sixteen cuproptosis related gene (CRGs) and cuproptosis related molecular and gene characteristics were comprehensively analyzed from 492 HCC samples. Cuproptosis related molecular patterns were generated by consensus clustering algorithm, including cuproptosis clusters, cuproptosis gene clusters (CGC) and cuproptosis score (CS). The characteristics of tumor microenvironment (TME) and tumor immune cells were described by the ssGSEA and ESTIMATE algorithms. Cuproptosis score was established to assess the clinical characteristics, prognostic and immunotherapy. The role and mechanism of CRG (ATP7A) in HCC, as well as its relationship with TME and immune checkpoints, have been further explored. The results of somatic mutation, copy number variations (CNV), and CRGs expression in HCC suggested the CRGs might participate in the HCC oncogenesis. The cuproptosis clusters were closely related to the clinical pathological characteristics, biological processes, and prognosis of HCC. The three CGC was revealed to be consistent with the three immune infiltration characterizations, including immune-high, immune-mid, and immune-low subtypes. Higher CS was characterized by decreased TMB, activated immunity, higher immune cell proportion score (IPS) and better overall survival (OS), which indicated higher CS was immune-high type and with better treatment effect and prognosis. The ATP7A had the highest hazard ratio (HR = 1.465, p < .001), was high expression in HCC tissues and with a shorter 5-year OS. Knocking down ATP7A could enhance intracellular copper concentration, cause a decrease in DLAT expression, and induce cuproptosis and inhibit cell proliferation and migration. ATP7A was also positively correlated with most cancer immune cells and immune checkpoints.

CONCLUSION

Taken together, this research revealed the cuproptosis related molecular patterns and genes associated with the clinical pathological characteristics, TME phenotype and prognosis of HCC. The CS will further deepen our understanding of the TME characteristics of HCC, and the involvement of ATP7A in cuproptosis will provide new ideas for predicting HCC prognosis and immunotherapy.

CDK1-SRC Interaction-Dependent Transcriptional Activation of HSP90AB1 Promotes Antitumor Immunity in Hepatocellular Carcinoma

This study aimed to analyze multiomics data and construct a regulatory network involving kinases, transcription factors, and immune genes in hepatocellular carcinoma (HCC) prognosis. The researchers used transcriptomic, proteomic, and clinical data from TCGA and GEO databases to identify immune genes associated with HCC. Statistical analysis, meta-analysis, and protein-protein interaction analyses were performed to identify key immune genes and their relationships. In vitro and in vivo experiments validated the CDK1-SRC-HSP90AB1 network's effects on HCC progression and antitumor immunity. A prognostic risk model was developed using clinicopathological features and immune infiltration. The immune genes LPA, BIRC5, HSP90AB1, ROBO1, and CCL20 were identified as the key prognostic factors. The CDK1-SRC-HSP90AB1 network promoted HCC cell proliferation and migration, with HSP90AB1 being transcriptionally activated by the CDK1-SRC interaction. Manipulating SRC or HSP90AB1 reversed the effects of CDK1 and SRC on HCC. The CDK1-SRC-HSP90AB1 network also influenced HCC tumor formation and antitumor immunity. Overall, this study highlights the importance of the CDK1-SRC-HSP90AB1 network as a crucial immune-regulatory network in the HCC prognosis.

Cuproptosis and its application in different cancers: an overview

Heavy metal ions are essential micronutrients for human health. They are also indispensable to maintaining health and regular operation of organs. Increasing or decreasing these metal ions will lead to cell death, such as ferroptosis. Tsvetkov et al. have recently proposed a novel cell death method called "Cuproptosis". Many researchers have linked this form of death to the diagnosis, prognosis, microenvironment infiltration, and prediction of immunotherapeutic efficacy of various tumors to better understand these tumors. Similarly, with the proposal of this mechanism, the killing effect of copper ionophores on cancer cells has come to our attention again. We introduced the mechanism of cuproptosis in detail and described the establishment of the corresponding prognostic model and risk score for uveal melanoma through cuproptosis. In addition, we describe the current progress in the study of cancer in other organs through cuproptosis and summarize the treatment of tumours by copper ionophore and its future research direction. With further research, the concept of cuproptosis may help us understand cancer and guide its clinical treatment.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Correlation between preoperative systemic immune inflammation index, nutritional risk index, and prognosis of radical resection of liver cancer

BACKGROUND

Radical surgery is the most commonly used treatment for hepatocellular carcinoma (HCC). However, the surgical effect remains not ideal, and prognostic evaluation is insufficient. Furthermore, clinical intervention is rife with uncertainty and not conducive to prolonging patient survival.

AIM

To explore correlations between the systemic immune inflammatory index (SII) and geriatric nutritional risk index (GNRI) and HCC operation prognosis.

METHODS

This retrospective study included and collected follow up data from 100 HCC. Kaplan-Meier survival curves were used to analyze the correlation between SII and GNRI scores and survival. SII and GNRI were calculated as follows: SII = neutrophil count × platelet count/lymphocyte count; GNRI = [1.489 × albumin (g/L) + 41.7 × actual weight/ideal weight]. We analyzed the predictive efficacy of the SII and GNRI in HCC patients using receiver operating characteristic (ROC) curves, and the relationships between the SII, GNRI, and survival rate using Kaplan-Meier survival curves. Cox regression analysis was utilized to analyze independent risk factors influencing prognosis.

RESULTS

After 1 year of follow-up, 24 patients died and 76 survived. The area under the curve (AUC), sensitivity, specificity, and the optimal cutoff value of SII were 0.728 (95% confidence interval: 0.600-0.856), 79.2%, 63.2%, and 309.14, respectively. According to ROC curve analysis results for predicting postoperative death in HCC patients, the AUC of SII and GNRI combination was higher than that of SII or GNRI alone, and SII was higher than that of GNRI (P < 0.05). The proportion of advanced differentiated tumors, tumor maximum diameter (5-10 cm, > 10 cm), lymph node metastasis, and TNM stage III-IV in patients with SII > 309.14 was higher than that in patients with SII ≤ 309.14 (P < 0.05). The proportion of patients aged > 70 years was higher in patients with GNRI ≤ 98 than that in patients with GNRI > 98 (P < 0.05). The 1-year survival rate of the SII > 309.14 group (compared with the SII ≤ 309.14 group) and GNRI ≤ 98 group (compared with the GNRI > 98 group) was lower (P < 0.05).

CONCLUSION

The prognosis after radical resection of HCC is related to the SII and GNRI and poor in high SII or low GNRI patients.

MELK promotes HCC carcinogenesis through modulating cuproptosis-related gene DLAT-mediated mitochondrial function

Cuproptosis caused by copper overload is mediated by a novel regulatory mechanism that differs from previously documented mechanisms regulating cell death. Cells dependent on mitochondrial respiration showed increased sensitivity to a copper ionophore elesclomol that induced cuproptosis. Maternal embryonic leucine zipper kinase(MELK) promotes tumorigenesis and tumor progression through the PI3K/mTOR pathway, which exerts its effects partly by targeting the pyruvate dehydrogenase complex(PDHc) and reprogramming the morphology and function of mitochondria. However, the role of MELK in cuproptosis remains unclear. Here, we validated that elevated MELK expression enhanced the activity of PI3K/mTOR signaling and subsequently promoted Dihydrolipoamide S-Acetyltransferase (DLAT) expression and stabilized mitochondrial function. This regulatory effect helped to improve mitochondrial respiration, eliminate excessive intracellular reactive oxygen species (ROS), reduce intracellular oxidative stress/damage and the possibility of mitochondria-induced cell fate alternations, and ultimately promote the progression of HCC. Meanwhile, elesclomol reduced translocase of outer mitochondrial membrane 20(TOM 20) expression and increased DLAT oligomers. Moreover, the above changes of MELK to HCC were abolished by elesclomol. In conclusion, MELK enhanced the levels of the cuproptosis-related signature(CRS) gene DLAT (especially the proportion of DLAT monomer) by activating the PI3K/mTOR pathway, thereby promoting elesclomol drug resistance, altering mitochondrial function, and ultimately promoting HCC progression.

The effect of cuproptosis-relevant genes on the immune infiltration and metabolism of gynecological oncology by multiply analysis and experiments validation

Gynecological cancers are a leading cause of mortality for women, including ovarian cancer (OC), cervical squamous cell carcinoma (CESC), and uterine corpus endometrial carcinoma (UCEC). Nevertheless, these gynecological cancer types have not elucidated the role of cuproptosis and the correlated tumor microenvironment (TME) infiltration features. CRGs had important potential molecular functions and prognostic significance in gynecological cancers, especially in UCEC. Hub CRG, FDX1, was correlated with the CD8+ T cell immune infiltration in UCEC and CESC. FDX1 OE could significantly repress the proliferation ability in UCEC cells by MTT, EdU, and clone formation. High levels of FDX1 could repress ATP and lactic acid but enhance ROS and glucose levels by metabolism assay. The xenograft tumor model indicated that FDX1 OE significantly inhibited the growth of UCEC and attenuated the PCNA, HK2, PKM2, and Ki-67 expression. These CRGs are significant roles that could be potential markers and treatment targets to optimize the TME immune cell infiltration features for gynecological cancer types. FDX1 is a hub CRGs in UCEC to promote immune infiltration and attenuate proliferation and metabolism.

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.

Molecular subtypes identified by multiomics analysis based on cuproptosis-related genes precisely predict response to immunotherapy and chemotherapy in colorectal cancer

Cuproptosis is a newly reported type of programmed cell death that is involved in the progression of various diseases. Some studies have reported its potential significance in multiple tumors. Colorectal cancer (CRC) is one of the malignant tumors with high incidence and mortality. The purpose of this study was to further explore the importance of cuproptosis in the CRC development and treatment. We analyzed the expression, alterations, and promoter methylation of cuproptosis-related genes (CRGs) in patients with CRC. Three machine learning methods was used to determine cuproptosis-related feature genes and a diagnostic model was built based on them. Using the unsupervised clustering, patients with CRC were classified into distinct clusters. Then, the LASSO method was used to establish a cuproptosis risk model. We analyzed the association of risk scores with outcomes, immune microenvironment, response to immunotherapy, and sensitivity to chemotherapeutic drugs. The results showed that the expression of CRGs was dysregulated in CRC. The diagnostic model based on cuproptosis-related feature genes showed great clinical value. The patients in two clusters displayed different prognosis and microenvironment. Furthermore, the risk score was correlated with clinical characteristics, immune infiltration and response to immunotherapy and chemotherapy. Above all, the present findings revealed the involvement of cuproptosis in CRC development and provided a diagnostic tool to evaluate CRC occurrence risk. The immune infiltration and drug sensitivity analysis results helped to predict the response of patients in different subtypes of CRC to immunotherapy and chemotherapy.