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Cutaneous melanoma is the most lethal of all skin tumors. Recently, cuproptosis, a novel form of cell death linked to oxidative phosphorylation, has emerged as an important factor. However, the precise role of cuproptosis in melanoma remains unclear. Our research explored the potential links between cuproptosis-related genes, prognosis, immune microenvironments, and melanoma treatments. Significantly, cuproptosis regulators showed remarkable differences between melanoma and normal tissues, establishing their relevance to melanoma. The newly developed cuproptosis-related gene signature (CGS) demonstrated a robust ability to predict overall survival (OS) in melanoma. We constructed a novel nomogram that combined clinical features with CGS to improve predictive accuracy. In addition, the study revealed correlations between CGS and immune cell populations, including CD8+T cells, Tfh cells, B cells, and myeloid-derived suppressor cells. Within the CGS, Peptidylprolyl isomerase C (PPIC) emerged as the most strongly associated with poor prognosis and drug resistance in melanoma. PPIC was identified as a promoter of melanoma progression, enhancing cell invasiveness while concurrently suppressing CD8+T cell activation. This comprehensive study not only elucidated the intricate connections between CGS, melanoma prognosis, immune microenvironment, and drug resistance but also provided compelling evidence supporting PPIC as a promising biomarker for predicting OS in melanoma treatment.

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To investigate the differences in methylation levels of cuproptosis related genes in cervical cancer and their effects on clinical prognosis.Methods:The methylation data of 310 cervical tissue specimens were acquired from public databases. The UALCAN database was used to analyze the methylation level differences of 12 cuproptosis-related genes and study their level in different stages or grades of cervical cancer. Genes with statistically significant differences were selected for prognosis analysis using the EWAS datahub. Finally, gene-enrichment analysis, pathway analysis, immune infiltration analysis, the mutation rate and tumor mutation burden (TMB) of the genes in cervical cancer were analyzed using the cBioportal database. Two independent samples rank-sum test was used for differences in methylation levels and immune cell infiltration; comparative analyses of overall survival were performed using KM survival curves and Log-rank two-sided tests. TMB analyses were performed using the Wilcoxon Test for statistical analyses; Pearson correlation analysis was used for assessment in GSEA and pathway analyses.Results:The methylationβvalue of Cyclin Dependent Kinase Inhibitor 2A (CDKN2A gene) in the cervical cancer tissues of patients was 0.075 which was significantly higher than the methylationβvalue of 0.049 in normal human tissues ( P=0.008). Dihydrolipoamide S-Acetyltransferase (DLAT gene) methylation with a β value of 0.102 was significantly higher than normal human tissue methylation with a β value of 0.08 ( P=0.002), and the methylation level β value of Lipoyltransferase 1 (LIPT1 gene) in cervical cancer tissues was 0.06,which was significantly lower than normal human tissue methylation value of 0.092 ( P=0.009). Patients with CDKN2A gene methylation levels≥0.199 had an overall survival of 14.75 years, which was lower than that of patients with methylation levels<0.199 (17.56 years) ( P=0.034).The results of gene enrichment analysis indicated that it mainly involves biological processes such as the response to type I interferon and DNA replication. The expression of CDKN2A gene is positively correlated with the number of neutrophils and dendritic cells in the tumor microenvironment( P<0.05), and negatively correlated with the number ofmacrophages( P<0.05). TMB was higher in the group of variants of the CDKN2A gene than in the group of non-variants ( P=0.019). Conclusion:CDKN2A methylation is a potential biomarker for predicting the prognosis of cervical cancer.

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

Asunto(s)

Apoptosis , Aterosclerosis , Enfermedades Cardiovasculares , Placa Aterosclerótica , Humanos , Aterosclerosis/diagnóstico , Aterosclerosis/genética , Biomarcadores , Proteínas Portadoras , Proteínas Mitocondriales , Superóxido Dismutasa-1 , Cobre

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Background: Kidney renal clear cell carcinoma (KIRC) is not sensitive to radiotherapy and chemotherapy, and only some KIRC patients can benefit from immunotherapy and targeted therapy. Cuproptosis is a new mechanism of cell death, which is closely related to tumor progression, prognosis and immunity. The identification of prognostic markers related to cuproptosis in KIRC may provide targets for treatment and improve the prognosis of KIRC patients. Methods: Ten cuproptosis-related genes were analyzed for differential expression in KIRC-TCGA and a prognostic model was constructed. Nomogram diagnostic model was used to screen independent prognostic molecules. The screened molecules were verified in multiple datasets (GSE36895 and GSE53757), and in KIRC tumor tissues by RT-PCR and immunohistochemistry (IHC). Clinical correlation of cuproptosis-related independent prognostic molecules was analyzed. According to the molecular expression, the two groups were divided into high and low expression groups, and the differences of immune checkpoint and tumor infiltrating lymphocytes (TILs) between the two groups were compared by EPIC algorithm. The potential Immune checkpoint blocking (ICB) response of high and low expression groups was predicted by the "TIDE" algorithm. Results: FDX1 and DLAT were protective factors, while CDKN2A was a risk factor. FDX1 was an independent prognostic molecule by Nomogram, and low expressed in tumor tissues compared with adjacent tissues (p < 0.05). FDX1 was positively correlated with CD274, HAVCR2, PDCD1LG2, and negatively correlated with CTLA4, LAG3, and PDCD1. The TIDE score of low-FDX1 group was higher than that of high-FDX1 group. The abundance of CD4+ T cells, CD8+ T cells and Endothelial cells in FDX1-low group was lower than that in FDX1-high group (p < 0.05). Conclusion: FDX1, as a key cuproptosis-related gene, was also an independent prognostic molecule of KIRC. FDX1 might become an interesting biomarker and potential therapeutic target for KIRC.

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Objective: We aimed to use the cancer genome atlas and gene expression omnibus databases to explore the characterization of tumor microenvironment (TME) infiltration and construct a predictive index of prognosis and treatment effect based on cuproptosis-related genes (CRGs) in primary lung adenocarcinoma (LUAD). Methods: We described the alterations of CRGs in 954 LUAD samples from genetic and transcriptional fields and evaluated their expression patterns from three independent datasets. We identified two distinct molecular subtypes and found that multi-layer CRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell infiltrating characteristics. Then, a cuproptosis scoring system (CSS) for predicting the prognosis was constructed, and its predictive capability in LUAD patients was validated. Results: Two molecular subtypes of cuproptosis (Copper Genes cluster A and cluster B) in LUAD were identified. Copper Genes cluster B had better survival than those with Copper Genes cluster A (p <0.01). Besides, we found that the infiltration of activated CD4+ T cells, natural killer T cells, and neutrophils was stronger in cluster A than in cluster B. Then, we constructed a highly accurate CSS to predict the prognosis, targeted therapy effect, and immune response. Compared with the low-CSS subgroup, the mutations of the TP53, MUC16, and TTN genes were more common in the high-CSS subgroup, while the mutation of TP53, TTN, and CSMD3 genes were more common in the low-CSS subgroup than in high-CSS subgroup. The low-score CSS group had an inferior survival than high-score CSS group (p <0.01). In addition, CSS presented good ability to predict the immune response (area under curve [AUC], 0.726). Moreover, AZD5363 and AZD8186 were the inhibitors of AKT and PI3K, respectively, and had lower IC50 and AUC in the low-score CSS group than it in the high-score CSS group. Conclusions: CRGs are associated with the development, TME, and prognosis of LUAD. Besides, a scoring system based on CRGs can predict the efficacy of targeted drugs and immune response. These findings may improve our understanding of CRGs in LUAD and pave a new path for the assessment of prognosis and the development of more effective targeted therapy and immunotherapy strategies.

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

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Cuproptosis is the most recently discovered type of regulated cell death and is mediated by copper ions. Studies show that cuproptosis plays a significant role in cancer development and progression. Lower-grade gliomas (LGGs) are slow-growing brain tumors. The majority of LGGs progress to high-grade glioma, which makes it difficult to predict the prognosis. However, the prognostic value of cuproptosis-related genes (CRGs) in LGG needs to be further explored. mRNA expression profiles and clinical data of LGG patients were collected from public sources for this study. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model were used to build a multigene signature that could divide patients into different risk groups. The differences in clinical pathological characteristics, immune infiltration characteristics, and mutation status were evaluated in risk subgroups. In addition, drug sensitivity and immune checkpoint scores were estimated in risk subgroups to provide LGG patients with precision medication. We found that all CRGs were differentially expressed in LGG and normal tissues. Patients were divided into high- and low-risk groups based on the risk score of the CRG signature. Patients in the high-risk group had a considerably lower overall survival rate than those in the low-risk group. According to functional analysis, pathways related to the immune system were enriched, and the immune state differed across the two risk groups. Immune characteristic analysis showed that the immune cell proportion and immune scores were different in the different groups. High-risk group was characterized by low sensitivity to chemotherapy but high sensitivity to immune checkpoint inhibitors. The current study revealed that the novel CRG signature was related to the prognosis, clinicopathological features, immune characteristics, and treatment perference of LGG.