Clinical Significance and Immune Infiltration Analyses of the Cuproptosis-Related Human Copper Proteome in Gastric Cancer

Harnessing nanomaterials for copper-induced cell death

Copper (Cu), an essential micronutrient with redox properties, plays a pivotal role in a wide array of pathological and physiological processes across virtually all cell types. Maintaining an optimal copper concentration is critical for cellular survival: insufficient copper levels disrupt respiration and metabolism, while excess copper compromises cell viability, potentially leading to cell death. Similarly, in the context of cancer, copper exhibits a dual role: appropriate amount of copper can promote tumor progression and be an accomplice, yet beyond befitting level, copper can bring about multiple types of cell death, including autophagy, apoptosis, ferroptosis, immunogenic cell death, pyroptosis, and cuproptosis. These forms of cell death are beneficial against cancer progression; however, achieving precise copper regulation within tumors remains a significant challenge in the pursuit of effective cancer therapies. The emergence of nanodrug delivery systems, distinguished by their precise targeting, controlled release, high payload capacity, and the ability to co-deliver multiple agents, has revitalized interest in exploiting copper's precise regulatory capabilities. Nevertheless, there remains a dearth of comprehensive review of copper's bidirectional effects on tumorigenesis and the role of copper-based nanomaterials in modulating tumor progression. This paper aims to address this gap by elucidating the complex role in cancer biology and highlighting its potential as a therapeutic target. Through an exploration of copper's dualistic nature and the application of nanotechnology, this review seeks to offer novel insights and guide future research in advancing cancer treatment.

The role of cuproptosis in gastric cancer

As a biologically essential transition metal, copper is widely involved in various enzymatic reactions and crucial biological processes in the body. It plays an increasingly important role in maintaining normal cellular metabolism and supporting the growth and development of the human body. As a trace element, copper maintains the dynamic balance of its concentration in body fluids through active homeostatic mechanisms. Both excess and deficiency of copper ions can impair cell function, ultimately leading to cell damage and death. Cuproptosis is a novel form of cell death where copper ions cause cell death by directly binding to the lipoylated components of the citric acid cycle (CAC) in mitochondrial respiration and interfering with the levels of iron-sulfur cluster (Fe-S cluster) proteins, ultimately causing protein toxic stress. Its primary characteristics are Cu2+ concentration dependence and high expression in mitochondrial respiratory cells. Recent research has revealed that, compared to other forms of programmed cell death such as apoptosis, necrosis, and autophagy, cuproptosis has unique morphological and biochemical features. Cuproptosis is associated with the occurrence and development of various diseases, including cancer, neurodegenerative diseases, and cardiovascular diseases. This article focuses on a review of the relevance of cuproptosis in gastric cancer (GC).

The functions of cuproptosis in gastric cancer: therapy, diagnosis, prognosis

Gastric cancer (GC) is the fifth most prevalent type of cancer in the whole world. Cuproptosis is discovered as a programmed cell death pathway and connected to cells' growth and death, as well as tumorigenesis. The relationship between cuproptosis and GC is still elusive. Two aspects of this study will elaborate the relationship between cuproptosis and immunotherapy as well as biomarkers in GC. Notably, the herein review is intended to highlight what has been accomplished regarding the cuproptosis for the diagnosis, immunotherapy, and prognosis in GC. The aim of this study is to offer a potential directions and the strategies for future research regarding cuproptosis inside the GC.

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.

The role of ARL4C in predicting prognosis and immunotherapy drug susceptibility in pan-cancer analysis

Background: ARLs, which are a class of small GTP-binding proteins, play a crucial role in facilitating tumor tumorigenesis and development. ARL4C, a vital member of the ARLs family, has been implicated in the progression of tumors, metastatic dissemination, and development of resistance to therapeutic drugs. Nevertheless, the precise functional mechanisms of ARL4C concerning tumor prognosis and immunotherapy drug susceptibility remain elusive. Methods: By combining the GTEx and TCGA databases, the presence of ARL4C was examined in 33 various types of cancer. Immunohistochemistry and immunofluorescence staining techniques were utilized to confirm the expression of ARL4C in particular tumor tissues. Furthermore, the ESTIMATE algorithm and TIMER2.0 database were utilized to analyze the tumor microenvironment and immune infiltration associated with ARL4C. The TISCH platform facilitated the utilization of single-cell RNA-seq datasets for further analysis. ARL4C-related immune escape was investigated using the TISMO tool. Lastly, drug sensitivity analysis was conducted to assess the sensitivity of different types of tumors to compounds based on the varying levels of ARL4C expression. Results: The study found that ARL4C was highly expressed in 23 different types of cancer. Moreover, the presence of high ARL4C expression was found to be associated with a poor prognosis in BLCA, COAD, KIRP, LGG, and UCEC. Notably, ARL4C was also expressed in immune cells, and its high expression was found to be correlated with cancer immune activation. Most importantly, the drug sensitivity analysis revealed a positive correlation between ARL4C expression and the heightened sensitivity of tumors to Staurosporine, Midostaurin, and Nelarabine. Conclusion: The findings from our study indicate that the expression level of ARL4C may exert an influence on cancer development, prognosis, and susceptibility to immunotherapy drugs. In addition, the involvement of ARL4C in the tumor immune microenvironment has expanded the concept of ARL4C-targeted immunotherapy.

A novel copper-induced cell death-related lncRNA prognostic signature associated with immune infiltration and clinical value in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most important malignancies and has a poor prognosis. Copper-induced cell death, recently termed cuproptosis, may directly affect the outcome of GC. Long noncoding RNAs (lncRNAs), possessing stable structures, can influence the prognosis of cancer and may serve as potential prognostic prediction factors for various cancers. However, the role of copper cell death-related lncRNAs (CRLs) in GC has not been thoroughly investigated. Here, we aim to elucidate the role of CRLs in predicting prognosis, diagnosis, and immunotherapy in GC patients.

METHODS

RNA expression data for 407 GC patients from The Cancer Genome Atlas (TCGA) were gathered, and differentially expressed CRLs were identified. Subsequently, the researchers applied univariate, LASSO, and multivariate Cox regression to construct a prognostic signature consisting of 5 lncRNAs based on the CRLs. Stratified by the median CRLSig risk score, Kaplan-Meier analysis was utilized to compare overall survival (OS) between the high- and low-risk groups. Among the two groups, gene set enrichment analysis (GSEA), tumor microenvironment (TME), drug sensitivity analysis, and immune checkpoint analysis were conducted. In addition, consensus clustering and nomogram analysis were performed to predict OS. Cell experiments and 112 human serum samples were employed to verify the effect of lncRNAs on GC. Furthermore, the diagnostic value of the CRLSig in the serum of GC patients was analyzed by the receiver operating characteristic (ROC) curve.

RESULTS

A prognostic signature for GC patients was constructed based on CRLs, composed of AC129926.1, AP002954.1, AC023511.1, LINC01537, and TMEM75. According to the K-M survival analysis, high-risk GC patients had a lower OS rate and progression-free survival rate than low-risk GC patients. Further support for the model's accuracy was provided by ROC, principal component analysis, and the validation set. The area under the curve (AUC) of 0.772 for GC patients showed a better prognostic value than any other clinicopathological variable. Furthermore, immune infiltration analysis showed that the high-risk group had greater antitumor immune responses in the tumor microenvironment. In the high-risk subgroup, 23 immune checkpoint genes had significantly higher expression levels than in the low-risk subgroup (p < 0.05). The half-maximal inhibitory concentrations (IC50) of 86 drugs were found to be significantly different in the two groups. Accordingly, the model is capable of predicting the effectiveness of immunotherapy. In addition, the five CRLs in GC serum exhibited statistically significant expression levels. The AUC of this signature in GC serum was 0.894, with a 95% CI of 0.822-0.944. Moreover, lncRNA AC129926.1 was significantly overexpressed in GC cell lines and the serum of GC patients. Importantly, colony formation, wound healing, and transwell assays further confirmed the oncogenic role of AC129926.1 in GC.

CONCLUSION

In this study, a prognostic signature model consisting of five CRLs was developed to improve OS prediction accuracy in GC patients. The model also has the potential to predict immune infiltration and immunotherapy effectiveness. Furthermore, the CRLSig might serve as a novel serum biomarker to differentiate GC patients from healthy individuals.

Copper-binding proteins genes set predicting the overall survival and immune infiltration in hepatocellular carcinoma by bioinformatic analysis

Abnormal Copper (Cu) accumulation shared a close association with hepatocellular carcinoma (HCC), but the regulatory role of Copper-binding proteins in HCC remains largely unknown. The aim of study was to identify the potential regulatory role of Cu-binding proteins, including copper homeostasis maintainer and the downstream effectors of Cu, in the progression of HCC. We conducted a comprehensive bioinformatic analysis of Cu-binding proteins in HCC using data from TCGA and ICGC database. Univariate cox regression analysis was conducted, and four prognostic Cu-binding proteins was identified to be differentially expressed between the normal liver tissues and HCC tissues. In addition, the Cu-binding proteins-based predictive signature (CuPscore) model was generated using the least absolute shrinkage and selection operator (LASSO) cox regression model. Here, we identified the crucial prognostic value of CuPscore in HCC. The pathological stage and CuPscore were independent risk factors for the prognosis of HCC patients. Pathological stage and CuPscore-based nomogram model exhibited great performance in predicting the prognosis of HCC patients. We also observed that the CuPscore shared a close association with several immunomodulatory molecules and the proportion of several tumor infiltrating immune cells, suggesting a potential value of CuPscore in predicting the response to immunotherapy in HCC. Our results demonstrated the prognostic value of Cu-binding proteins and its correlation with immune microenvironment in HCC, providing a therapeutic basis for the precision medicine strategy through targeting Cu-binding proteins in HCC.

Gasdermin D Plays an Oncogenic Role in Glioma and Correlates to an Immunosuppressive Microenvironment

BACKGROUND

Understanding the molecular mechanisms driving oncogenic processes in glioma is important in order to develop efficient treatments. Recent studies have proposed gasdermin D (GSDMD) as a newly discovered pyroptosis executive protein associated with tumorigenesis. However, the precise effect of GSDMD on glioma progression remains unknown.

METHODS

The expression levels of GSDMD in 931 glioma and 1157 normal control tissues were collected. A series of bioinformatic approaches and in vivo and in vitro experiments were used to investigate the roles and mechanisms of GDSMD in glioma.

RESULTS

Significant upregulation of GSDMD was detected in glioma tissues compared to normal brain tissues. Patients with glioma and higher GSDMD levels had shorter overall survival, and the Cox regression analysis revealed that GSDMD was an independent risk factor. In addition, upregulation of GSDMD was associated with higher tumor mutation burden and PD-1/PD-L1 expression. Immune infiltration and single-cell analyses indicated that GSDMD was positively associated with an immunosuppressive microenvironment with more infiltrated macrophages and cancer-associated fibroblasts. Furthermore, the in vitro and in vivo experiments revealed that GSDMD knockdown inhibited glioma proliferation, migration, and growth in vivo.

CONCLUSION

Our analyses revealed a relatively comprehensive understanding of the oncogenic role of GSDMD in glioma. GSDMD is a promising prognostic biomarker and a potential target for glioma treatment.

Novel targets for gastric cancer: The tumor microenvironment (TME), N6-methyladenosine (m6A), pyroptosis, autophagy, ferroptosis and cuproptosis

Gastric cancer (GC) is a fatal illness, and its mortality rate is very high all over the world. At present, it is a serious health problem for any country. It is a multifactorial disease due to the rising drug resistance and the increasing global cancer burden, the treatment of GC still faces many obstacles and problems. In recent years, research on GC is being carried out continuously, and we hope to address the new targets of GC treatment through this review. At the same time, we also hope to discover new ways to fight GC and create more gospel for clinical patients. First, we discuss the descriptive tumor microenvironment (TME), N6-methyladenosine (m6A), pyroptosis, autophagy, ferroptosis, and cuproptosis. Finally, we expounded on the new or potential targets of GC treatment.

A Five Glutamine-Associated Signature Predicts Prognosis of Prostate Cancer and Links Glutamine Metabolism with Tumor Microenvironment

Glutamine has been recognized as an important amino acid that provide a variety of intermediate products to fuel biosynthesis. Glutamine metabolism participates in the progression of the tumor via various mechanisms. However, glutamine-metabolism-associated signatures and its significance in prostate cancer are still unclear. In this current study, we identified five genes associated with glutamine metabolism by univariate and Lasso regression analysis and constructed a model to predict the biochemical recurrence free survival (BCRFS) of PCa. Further validation of the prognostic risk model demonstrated a good efficacy in predicting the BCRFS in PCa patients. Interestingly, based on the CIBERSORTx, ssGSEA and ESTIMATE algorithms predictions, we noticed a distinct immune cell infiltration and immune pathway pattern in the prediction of the two risk groups stratified by the risk model. Drug sensitivity prediction revealed that patients in the high-risk group were more suitable for chemotherapy. Last but not least, glutamine deprivation significantly inhibited cell growth in GLUL or ASNS knock down prostate cancer cell lines. Therefore, we proposed a novel prognostic model by using glutamine metabolism genes for PCa patients and identified potential mechanism of PCa progression through glutamine-related tumor microenvironment remodeling.

A cuproptosis-related signature for predicting the prognosis of gastric cancer

Background

Gastric cancer (GC) is one of the most common malignancies. Cuproptosis is a newly discovered type of cell death caused by protein toxicity stress, with copper having considerable importance in GC development.

Methods

First, differentially expressed (DE) cuproptosis-related genes (CRGs) were screened in GC. The tumor mutation burden (TMB) of CRGs was analyzed. We then performed enrichment analyses of DE-CRGs. Next, we constructed a GC cuproptosis-related (CR) signature (CRs) using Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. The predictive efficacy was assessed using receiver operating characteristic (ROC) curves. Furthermore, we performed gene set enrichment analysis (GSEA). Different methods were used to assess tumor immunity of the CRs, and the Wilcoxon test was used to examine the expressions of m6A-, m7G-, and ferroptosis-related genes. The "pRRophetic" R package (The R Foundation for Statistical Computing) was used to predict the half maximal inhibitory concentration IC50 of common chemotherapeutic agents. Finally, the expression of CRGs in different clusters was analyzed using single-cell RNA sequencing (scRNA-seq).

Results

We identified 8 DE-CRGs in GC. There were 9 CRGs with TMB values >1%. We constructed gene expression networks and CRs for GC. The DE-CRGs were involved in important mitochondrial metabolic pathways, and the CRs was a valuable independent prognosis factor. The GSEA revealed that angiogenesis and metabolic-related pathways were enriched in the high-risk group, whereas the low-risk group showed enrichment in DNA replication mismatch and repair pathways. The expressions of immunological checkpoints, ferroptosis-, m6A-, and m7G-related genes, type II interferon (INF) response, major histocompatibility complex (MHC class-I), and the IC50 of the copper-based carrier drug elesclomol were significantly different between the 2 groups of the CRs. Furthermore, the scRNA-seq analysis showed that most CRGs were mainly upregulated in endothelial cells.

Conclusions

The novel CRs could predict the prognosis of GC.

Copper Death Inducer, FDX1, as a Prognostic Biomarker Reshaping Tumor Immunity in Clear Cell Renal Cell Carcinoma

BACKGROUND

Progress in the diagnosis and treatment of clear cell renal cell carcinoma (ccRCC) has significantly prolonged patient survival. However, ccRCC displays an extreme heterogenous characteristic and metastatic tendency, which limit the benefit of targeted or immune therapy. Thus, identifying novel biomarkers and therapeutic targets for ccRCC is of great importance.

METHOD

Pan cancer datasets, including the expression profile, DNA methylation, copy number variation, and single nucleic variation, were introduced to decode the aberrance of copper death regulators (CDRs). Then, FDX1 was systematically analyzed in ccRCC to evaluate its impact on clinical characteristics, prognosis, biological function, immune infiltration, and therapy response. Finally, in vivo experiments were utilized to decipher FDX1 in ccRCC malignancy and its role in tumor immunity.

RESULT

Copper death regulators were identified at the pancancer level, especially in ccRCC. FDX1 played a protective role in ccRCC, and its expression level was significantly decreased in tumor tissues, which might be regulated via CNV events. At the molecular mechanism level, FDX1 positively regulated fatty acid metabolism and oxidative phosphorylation. In addition, FDX1 overexpression restrained ccRCC cell line malignancy and enhanced tumor immunity by increasing the secretion levels of IL2 and TNFγ.

CONCLUSIONS

Our research illustrated the role of FDX1 in ccRCC patients' clinical outcomes and its impact on tumor immunity, which could be treated as a promising target for ccRCC patients.