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

Integrated single-cell and bulk RNA sequencing in pancreatic cancer identifies disulfidptosis-associated molecular subtypes and prognostic signature

Pancreatic cancer (PC) is known for its high degree of heterogeneity and exceptionally adverse outcome. While disulfidptosis is the most recently identified form of cell death, the predictive and therapeutic value of disulfidptosis-related genes (DRGs) for PC remains unknown. RNA sequencing data with the follow-up information, were retrieved from the TCGA and ICGC databases. Consensus clustering analysis was conducted on patient data using R software. Subsequently, the LASSO regression analysis was conducted to create a prognostic signature for foreseeing the outcome of PC. Differences in relevant pathways, mutational landscape, and tumor immune microenvironment were compared between PC samples with different risk levels. Finally, we experimentally confirmed the impact of DSG3 on the invasion and migration abilities of PC cells. All twenty DRGs were found to be hyperexpressed in PC tissues, and fourteen of them significantly associated with PC survival. Using consensus clustering analysis based on these DRGs, four DRclusters were identified. Additionally, altogether 223 differential genes were evaluated between clusters, indicating potential biological differences between them. Four gene clusters (geneClusters) were recognized according to these genes, and a 10-gene prognostic signature was created. High-risk patients were found to be primarily enriched in signaling pathways related to the cell cycle and p53. Furthermore, the rate of mutations was markedly higher in high-risk patients, besides important variations were present in terms of immune microenvironment and chemotherapy sensitivity among patients with different risk levels. DSG3 could appreciably enhance the invasion and migration of PC cells. This work, based on disulfidoptosis-related genes (DRGs), holds the promise of classifying PC patients and predicting their prognosis, mutational landscape, immune microenvironment, and drug therapy. These insights could boost an improvement in a better comprehension of the role of DRGs in PC as well as provide new opportunities for prognostic prediction and more effective treatment strategies.

Pan-cancer Analysis of the Disulfidptosis-related Gene NCKAP1 and Its Prognostic Value for Lung Adenocarcinoma

BACKGROUND

The nck-associated protein 1 (NCKAP1) of the disulfidptosis-related gene is essential in programmed cell death. However, a comprehensive analysis of the biological significance of NCKAP1 in pan-cancer is lacking.

METHODS

Gene expression matrices and clinical expression information of cancers were obtained from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEX) databases. A comprehensive analysis of NCKAP1 expression, biological function, gene mutation, immune cell infiltration, DNA methylation, and drug sensitivity profiles in pan-cancer was performed using the Timer2.0, HPA, GEPIA, STRING, cBioPortal, UALCAN and CellMiner databases. The prognostic value of NCKAP1 was investigated based on COX regression analysis and the Kaplan-Meier(K-M) curves. A nomogram was established to verify the clinical value of NCKAP1 for LUAD. The correlation between NCKAP1 and immune cells and signaling pathways were investigated by single-sample gene set enrichment analysis(ssGSEA). Validation was performed using PCR, Western Blot (WB), and Transwell assays.

RESULT

Significant differences in expression levels, mutation levels, and methylation levels of NCKAP1 between tumor and normal samples. NCKAP1 affects the prognosis of various cancers. NCKAP1 is strongly associated with microsatellite instability (MSI) and tumor mutational burden (TMB). The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicate that NCKAP1 is strongly associated with cell death and tumor immunity. The expression of NCKAP1 affects the sensitivity to various drugs. Moreover, NCKAP1 is an independent predictor of prognosis in LUAD patients. The results of ssGSEA showed that elevated NCKAP1 expression was positively correlated with multiple immune-related signaling pathways. PCR analysis showed that the expression of NCKAP1 was increased in LUAD cells. Transwell invasion assay showed that overexpression of NCKAP1 resulted in enhanced invasion of LUAD cells.

CONCLUSIONS

We comprehensively analyzed the relationship between NCKAP1 and pan-cancer and its potential clinical value. NCKAP1 could be a potential immune marker for various cancers (especially LUAD), providing new insights and insights for cancer therapy.

Copper homeostasis and cuproptosis in tumor pathogenesis and therapeutic strategies

Copper is an indispensable micronutrient for the development and replication of all eukaryotes, and its redox properties are both harmful and beneficial to cells. An imbalance in copper homeostasis is thought to be involved in carcinogenesis. Importantly, cancer cell proliferation, angiogenesis, and metastasis cannot be separated from the effects of copper. Cuproposis is a copper-dependent form of cell death that differs from other existing modalities of regulatory cell death. The role of cuproptosis in the pathogenesis of the nervous and cardiovascular systems has been widely studied; however, its impact on malignant tumors is yet to be fully understood from a clinical perspective. Exploring signaling pathways related to cuproptosis will undoubtedly provide a new perspective for the development of anti-tumor drugs in the future. Here, we systematically review the systemic and cellular metabolic processes of copper and the regulatory mechanisms of cuproptosis in cancer. In addition, we discuss the possibility of targeting copper ion drugs to prolong the survival of cancer patients, with an emphasis on the most representative copper ionophores and chelators. We suggest that attention should be paid to the potential value of copper in the treatment of specific cancers.

Single-cell and genetic multi-omics analysis combined with experiments confirmed the signature and potential targets of cuproptosis in hepatocellular carcinoma

Background: Cuproptosis, as a recently discovered type of programmed cell death, occupies a very important role in hepatocellular carcinoma (HCC) and provides new methods for immunotherapy; however, the functions of cuproptosis in HCC are still unclear. Methods: We first analyzed the transcriptome data and clinical information of 526 HCC patients using multiple algorithms in R language and extensively described the copy number variation, prognostic and immune infiltration characteristics of cuproptosis related genes (CRGs). Then, the hub CRG related genes associated with prognosis through LASSO and Cox regression analyses and constructed a prognostic prediction model including multiple molecular markers and clinicopathological parameters through training cohorts, then this model was verified by test cohorts. On the basis of the model, the clinicopathological indicators, immune infiltration and tumor microenvironment characteristics of HCC patients were further explored via bioinformation analysis. Then, We further explored the key gene biological function by single-cell analysis, cell viability and transwell experiments. Meantime, we also explored the molecular docking of the hub genes. Results: We have screened 5 hub genes associated with HCC prognosis and constructed a prognosis prediction scoring model. And the model results showed that patients in the high-risk group had poor prognosis and the expression levels of multiple immune markers, including PD-L1, CD276 and CTLA4, were higher than those patients in the low-risk group. We found a significant correlation between risk score and M0 macrophages and memory CD4+ T cells. And the single-cell analysis and molecular experiments showed that BEX1 were higher expressed in HCC tissues and deletion inhibited the proliferation, invasion and migration and EMT pathway of HCC cells. Finally, it was observed that BEX1 could bind to sorafenib to form a stable conformation. Conclusion: The study not only revealed the multiomics characteristics of CRGs in HCC but also constructed a new high-accuracy prognostic prediction model. Meanwhile, BEX1 were also identified as hub genes that can mediate the cuproptosis of hepatocytes as potential therapeutic targets for HCC.

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.

A novel defined risk signature of cuproptosis-related long non-coding RNA for predicting prognosis, immune infiltration, and immunotherapy response in lung adenocarcinoma

Background: Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor immunity formation and patient-tailored treatment optimization of lung adenocarcinoma (LUAD) is still unclear. Methods: RNA sequencing and survival data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database for model training. The patients with LUAD in GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081 were used for validation. The proofed cuproptosis-related genes were extracted from the previous studies. The Pearson correlation was applied to select cuproptosis-related lncRNAs. We chose differentially expressed cuproptosis-related lncRNAs in the tumor and normal tissues and allowed them to go to a Cox regression and a LASSO regression for a lncRNA signature that predicts the LUAD prognosis. Kaplan-Meier estimator, Cox model, ROC, tAUC, PCA, nomogram predictor, decision curve analysis, and real-time PCR were further deployed to confirm the model's accuracy. We examined this model's link to other regulated cell death forms. Applying TMB, immune-related signatures, and TIDE demonstrated the immunotherapeutic capabilities of signatures. We evaluated the relationship of our signature to anticancer drug sensitivity. GSEA, immune infiltration analysis, and function experiments further investigated the functional mechanisms of the signature and the role of immune cells in the prognostic power of the signature. Results: An eight-lncRNA signature (TSPOAP1-AS1, AC107464.3, AC006449.7, LINC00324, COLCA1, HAGLR, MIR4435-2HG, and NKILA) was built and demonstrated owning prognostic power by applied to the validation cohort. Each signature gene was confirmed differentially expressed in the real world by real-time PCR. The eight-lncRNA signature correlated with 2321/3681 (63.05%) apoptosis-related genes, 11/20 (55.00%) necroptosis-related genes, 34/50 (68.00%) pyroptosis-related genes, and 222/380 (58.42%) ferroptosis-related genes. Immunotherapy analysis suggested that our signature may have utility in predicting immunotherapy efficacy in patients with LUAD. Mast cells were identified as key players that support the predicting capacity of the eight-lncRNA signature through the immune infiltrating analysis. Conclusion: In this study, an eight-lncRNA signature linked to cuproptosis was identified, which may improve LUAD management strategies. This signature may possess the ability to predict the effect of LUAD immunotherapy. In addition, infiltrating mast cells may affect the signature's prognostic power.

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

Background

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

Methods

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

Results

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

Conclusion

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

Cuproptosis- and m6A-Related lncRNAs for Prognosis of Hepatocellular Carcinoma

Cuproptosis and N6-methyladenosine (m6A) have potential as prognostic predictors in cancer patients, but their roles in hepatocellular carcinoma (HCC) are unclear. This study aimed to screen a total of 375 HCC samples were retrieved from the TCGA database, and lncRNAs related to cuproptosis and m6A were obtained through correlation analysis. To construct a risk assessment model, univariate Cox regression analysis and LASSO Cox regression were employed. Analyze the regulatory effect of relevant risk assessment models on tumor mutation load (TMB) and immune microenvironment. A total of five lncRNAs (AC007405.3, AL031985.3, TMCC1-AS1, MIR210HG, TMEM220-AS1) with independent overall survival-related risk models were obtained by LASSO survival regression. TP53 and CTNNB1 were the three genes found to have the most mutations in high-risk group patients. The high-risk group with low TMB had the worst survival, whereas the low-risk group with high TMB had the best survival. KEGG pathway analysis revealed that the high-risk group was enriched with cell cycle, oocyte meiosis, cell senescence, and glycolysis/glucose production pathways. We constructed a reliable cuproptosis- and m6A-related lncRNA model for the prognosis of HCC. The model may provide new insights into managing HCC patients, but further research is needed to validate it.

The signature of cuproptosis-related immune genes predicts the tumor microenvironment and prognosis of prostate adenocarcinoma

Background

Cuproptosis plays a crucial role in cancer, and different subtypes of cuproptosis have different immune profiles in prostate adenocarcinoma (PRAD). This study aimed to investigate immune genes associated with cuproptosis and develop a risk model to predict prognostic characteristics and chemotherapy/immunotherapy responses of patients with PRAD.

Methods

The CIBERSORT algorithm was used to evaluate the immune and stromal scores of patients with PRAD in The Cancer Genome Atlas (TCGA) cohort. Validation of differentially expressed genes DLAT and DLD in benign and malignant tissues by immunohistochemistry, and the immune-related genes of DLAT and DLD were further screened. Univariable Cox regression were performed to select key genes. Least absolute shrinkage and selection operator (LASSO)-Cox regression analyse was used to develop a risk model based on the selected genes. The model was validated in the TCGA, Memorial Sloan-Kettering Cancer Center (MSKCC) and Gene Expression Omnibus (GEO) datasets, as well as in this study unit cohort. The genes were examined via functional enrichment analysis, and the tumor immune features, tumor mutation features and copy number variations (CNVs) of patients with different risk scores were analysed. The response of patients to multiple chemotherapeutic/targeted drugs was assessed using the pRRophetic algorithm, and immunotherapy was inferred by the Tumor Immune Dysfunction and Exclusion (TIDE) and immunophenoscore (IPS).

Results

Cuproptosis-related immune risk scores (CRIRSs) were developed based on PRLR, DES and LECT2. High CRIRSs indicated poor overall survival (OS), disease-free survival (DFS) in the TCGA-PRAD, MSKCC and GEO datasets and higher T stage and Gleason scores in TCGA-PRAD. Similarly, in the sample collected by the study unit, patients with high CRIRS had higher T-stage and Gleason scores. Additionally, higher CRIRSs were negatively correlated with the abundance of activated B cells, activated CD8+ T cells and other stromal or immune cells. The expression of some immune checkpoints was negatively correlated with CRIRSs. Tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) scores were all higher in the high-CRIRS group. Multiple chemotherapeutic/targeted drugs and immunotherapy had better responsiveness in the low-CRIRS group.

Conclusion

Overall, lower CRIRS indicated better response to treatment strategies and better prognostic outcomes.

Multi-omics analysis uncovers clinical, immunological, and pharmacogenomic implications of cuproptosis in clear cell renal cell carcinoma

OBJECTIVE

The latest research proposed a novel copper-dependent programmed cell death named cuproptosis. We aimed to elucidate the influence of cuproptosis in clear cell renal cell carcinoma (ccRCC) from a multi-omic perspective.

METHODS

This study systematically assessed mRNA expression, methylation, and genetic alterations of cuproptosis genes in TCGA ccRCC samples. Through unsupervised clustering analysis, the samples were classified as different cuproptosis subtypes, which were verified through NTP method in the E-MTAB-1980 dataset. Next, the cuproptosis score (Cuscore) was computed based on cuproptosis-related genes via PCA. We also evaluated clinical and immunogenomic features, drug sensitivity, immunotherapeutic response, and post-transcriptional regulation.

RESULTS

Cuproptosis genes presented multi-layer alterations in ccRCC, and were linked with patients' survival and immune microenvironment. We defined three cuproptosis subtypes [C1 (moderate cuproptosis), C2 (low cuproptosis), and C3 (high cuproptosis)], and the robustness and reproducibility of this classification was further proven. Overall survival was best in C3, moderate in C1, and worst in C2. C1 had the highest sensitivity to pazopanib, and sorafenib, while C2 was most sensitive to sunitinib. Furthermore, C1 patients benefited more from anti-PD-1 immunotherapy. Patients with high Cuscore presented the notable survival advantage. Cuscore was highly linked with immunogenomic features, and post-transcriptional events that contributed to ccRCC development. Finally, several potential compounds and druggable targets (NMU, RARRES1) were selected for low Cuscore group.

CONCLUSION

Overall, our study revealed the non-negligible role of cuproptosis in ccRCC development. Evaluation of the cuproptosis subtypes improves our cognition of immunogenomic features and better guides personalized prognostication and precision therapy.

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

Introduction

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

Methods

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

Results

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

Discussion

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

A cuproptosis-related lncRNA signature predicts the prognosis and immune cell status in head and neck squamous cell carcinoma

Introduction

The incidence of head and neck squamous cell carcinoma (HNSCC), one of the most prevalent tumors, is increasing rapidly worldwide. Cuproptosis, as a new copper-dependent cell death form, was proposed recently. However, the prognosis value and immune effects of cuproptosis-related lncRNAs (CRLs) have not yet been elucidated in HNSCC.

Methods

In the current study, the expression pattern, differential profile, clinical correlation, DNA methylation, functional enrichment, univariate prognosis factor, and the immune effects of CRLs were analyzed. A four-CRL signature was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm.

Results

Results showed that 20 CRLs had significant effects on the stage progression of HNSCC. Sixteen CRLs were tightly correlated with the overall survival (OS) of HNSCC patients. Particularly, lnc-FGF3-4 as a single risk factor was upregulated in HNSCC tissues and negatively impacted the prognosis of HNSCC. DNA methylation probes of cg02278768 (MIR9-3HG), cg07312099 (ASAH1-AS1), and cg16867777 (TIAM1-AS1) were also correlated with the prognosis of HNSCC. The four-CRL signature that included MAP4K3-DT, lnc-TCEA3-1, MIR9-3HG, and CDKN2A-DT had a significantly negative effect on the activation of T cells follicular helper and OS probability of HNSCC. Functional analysis revealed that cell cycle, DNA replication, and p53 signal pathways were enriched.

Discussion

A novel CRL-related signature has the potential of prognosis prediction in HNSCC. Targeting CRLs may be a promising therapeutic strategy for HNSCC.

A Newly Established Cuproptosis-Related Gene Signature for Predicting Prognosis and Immune Infiltration in Uveal Melanoma

Uveal melanoma (UVM) is the most common primary ocular malignancy in adults and involves several types of regulated cell death. Cuproptosis is a novel method of regulating cell death by binding lipoylated TCA cycle proteins. There is still no research on the relationship between cuproptosis-related genes (CRGs) and UVM. Here, we aimed to develop a prognostic CRG signature for UVM. After a prognostic CRG signature was constructed, we determined the relationship between the signature and immune infiltration, bioinformatics analysis and experimental validation. Finally, a prognostic cuproptosis-related three-gene (CRTG) signature was constructed, which comprised ORAI2, ACADSB and SLC47A1. The risk score of the CRTG signature was negatively correlated with the overall survival (OS) and progression-free survival (PFS) of patients, which revealed strong predictive ability and its independent prognostic value. In addition, we found that the risk score was negative for chromosomes 3 and 6p, and positive for 8q, and high-risk UVM patients showed an increase in protumor immune infiltrates and a high expression of immune checkpoints. Finally, experimental validation verified that the migratory ability of MUM-2B cells was suppressed by the knockdown of the identified genes in vitro. We constructed a CRTG signature that is helpful in predicting prognosis and guiding treatment for patients with UVM.

Confirmation of the predictive function of cuproptosis-related gene FDX1 in clear cell renal carcinoma using qRT-PCR and western blotting

BACKGROUND

Cuproptosis is a novel cell death mechanism, and FDX1 is a key gene associated with cuproptosis. However, it is unclear whether FDX1 has prognostic and immunotherapeutic value for clear cell renal carcinoma (ccRCC).

METHODS

Data on FDX1 expression in ccRCC were extracted from various databases and validated using qRT-PCR and western blotting. Moreover, the survival prognosis, clinical features, methylation, and biological functions of FDX1 were evaluated, and the tumor immune dysfunction and exclusion (TIDE) score was used to explore the immunotherapy response to FDX1 in ccRCC.

RESULTS

The expression of FDX1 in ccRCC tissues was significantly lower than that in normal tissues, as validated by qRT-PCR and western blotting of patient samples (P < 0.01). Moreover, low FDX1 expression was related to shorter survival time and high immune activation, as indicated by alterations in the tumor mutational burden and tumor microenvironment, stronger immune cell infiltration and immunosuppression point expression, and a higher TIDE score.

CONCLUSIONS

FDX1 could serve as a novel and accessible biomarker for predicting survival prognosis, tumor immune landscape, and immune responses in ccRCC.

Copper metabolism and hepatocellular carcinoma: current insights

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

Prediction of Prognosis and Chemotherapeutic Sensitivity Based on Cuproptosis-Associated lncRNAs in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Cervical cancer is the fourth most common cancer. The 5-year survival rate for metastatic cervical cancer is less than 10%. The survival time of patients with recurrent cervical cancer is approximately 13-17 months. Cuproptosis is a novel type of cell death related to mitochondrial respiration. Accumulative studies showed that long non-coding RNAs (lncRNAs) regulated cervical cancer progression. Compressive bioinformatic analysis showed that nine cuproptosis-related lncRNAs (CRLs), including C002128.2, AC002563.1, AC009237.14, AC048337.1, AC145423.1, AL117336.1, AP001542.3, ATP2A1-AS1, and LINC00426, were independently correlated with the overall survival (OS) of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients. The time-dependent area under curve value reached 0.716 at 1 year, 0.718 at 3 years, and 0.719 at 5 years. Notably, CESC patients in the low-risk group had increased immune cell infiltration and expression of several immune checkpoints, which indicated that they may benefit more from immune checkpoint blockade therapy. In addition, we also used the model for drug sensitivity analysis. Several drug sensitivities were more sensitive in high-risk patients and showed significant correlations with the risk models, such as Bortezomib_1191, Luminespib_1559, and Rapamycin_1084, suggesting that these drugs may be candidate clinical drugs for patients with a high risk of CESC. In summary, this study further explored the mechanism of CRLs in CESC and provided a more optimized prognostic model and some insights into chemotherapy of CESC.

Construction and validation of a novel IGFBP3-related signature to predict prognosis and therapeutic decision making for Hepatocellular Carcinoma

Background

IGFBP3 plays a pivotal role in carcinogenesis by being anomalously expressed in some malignancies. However, the clinical value of IGFBP3 and the role of IGFBP3-related signature in HCC remain unclear.

Methods

Multiple bioinformatics methods were used to determine the expression and diagnostic values of IGFBP3. The expression level of IGFBP3 was validated by RT-qPCR and IHC. A IGFBP3-related risk score (IGRS) was built via correlation analysis and LASSO Cox regression analysis. Further analyses, including functional enrichment, immune status of risk groups were analyzed, and the role of IGRS in guiding clinical treatment was also evaluated.

Results

IGFBP3 expression was significantly downregulated in HCC. IGFBP3 expression correlated with multiple clinicopathological characteristics and demonstrated a powerful diagnostic capability for HCC. In addition, a novel IGRS signature was developed in TCGA, which exhibited good performance for prognosis prediction and its role was further validated in GSE14520. In TCGA and GSE14520, Cox analysis also confirmed that the IGRS could serve as an independent prognostic factor for HCC. Moreover, a nomogram with good accuracy for predicting the survival of HCC was further formulated. Additionally, enrichment analysis showed that the high-IGRS group was enriched in cancer-related pathways and immune-related pathways. Additionally, patients with high IGRS exhibited an immunosuppressive phenotype. Therefore, patients with low IGRS scores may benefit from immunotherapy.

Conclusions

IGFBP3 can act as a new diagnostic factor for HCC. IGRS signature represents a valuable predictive tool in the prognosis prediction and therapeutic decision making for Hepatocellular Carcinoma.

Identification of disulfidptosis related subtypes, characterization of tumor microenvironment infiltration, and development of DRG prognostic prediction model in RCC, in which MSH3 is a key gene during disulfidptosis

Disulfidptosis is a newly discovered mode of cell death induced by disulfide stress. However, the prognostic value of disulfidptosis-related genes (DRGs) in renal cell carcinoma (RCC) remains to be further elucidated. In this study, consistent cluster analysis was used to classify 571 RCC samples into three DRG-related subtypes based on changes in DRGs expression. Through univariate regression analysis and LASSO-Cox regression analysis of differentially expressed genes (DEGs) among three subtypes, we constructed and validated a DRG risk score to predict the prognosis of patients with RCC, while also identifying three gene subtypes. Analysis of DRG risk score, clinical characteristics, tumor microenvironment (TME), somatic cell mutations, and immunotherapy sensitivity revealed significant correlations between them. A series of studies have shown that MSH3 can be a potential biomarker of RCC, and its low expression is associated with poor prognosis in patients with RCC. Last but not least, overexpression of MSH3 promotes cell death in two RCC cell lines under glucose starvation conditions, indicating that MSH3 is a key gene in the process of cell disulfidptosis. In summary, we identify potential mechanism of RCC progression through DRGs -related tumor microenvironment remodeling. In addition, this study has successfully established a new disulfidptosis-related genes prediction model and discovered a key gene MSH3. They may be new prognostic biomarkers for RCC patients, provide new insights for the treatment of RCC patients, and may inspire new methods for the diagnosis and treatment of RCC patients.

Prediction of risk and clinical outcome of cuproptosis in lung squamous carcinoma

BACKGROUND

Lung squamous cell carcinoma (LUSC) is an important subtype of non-small cell lung cancer. Its special clinicopathological features and molecular background determine the limitations of its treatment. A recent study published on Science defined a newly regulatory cell death (RCD) form - cuproptosis. Which manifested as an excessive intracellular copper accumulation, mitochondrial respiration-dependent, protein acylation-mediated cell death. Different from apoptosis, pyroptosis, necroptosis, ferroptosis and other forms of regulatory cell death (RCD). The imbalance of copper homeostasis in vivo will trigger cytotoxicity and further affect the occurrence and progression of tumors. Our study is the first to predict the prognosis and immune landscape of cuproptosis-related genes (CRGs) in LUSC.

METHODS

The RNA-seq profiles and clinical data of LUSC patients were downloaded from TCGA and GEO databases and then combined into a novel cohort. R language packages are used to analyze and process the data, and CRGs related to the prognosis of LUSC were screened according to the differentially expressed genes (DEGs). After analyzed the tumor mutation burden (TMB), copy number variation (CNV) and CRGs interaction network. Based on CRGs and DEGs, cluster analysis was used to classify LUSC patients twice. The selected key genes were used to construct a CRGs prognostic model to further analyze the correlation between LUSC immune cell infiltration and immunity. Through the risk score and clinical factors, a more accurate nomogram was further constructed. Finally, the drug sensitivity of CRGs in LUSC was analyzed.

RESULTS

Patients with LUSC were divided into different cuproptosis subtypes and gene clusters, showing different levels of immune infiltration. The risk score showed that the high-risk group had higher tumor microenvironment score, lower tumor mutation load frequency and worse prognosis than the low-risk group. In addition, the high-risk group was more sensitive to vinorelbine, cisplatin, paclitaxel, doxorubicin, etoposide and other drugs.

CONCLUSIONS

Through bioinformatics analysis, we successfully constructed a prognostic risk assessment model based on CRGs, which can not only accurately predict the prognosis of LUSC patients, but also evaluate the patient 's immune infiltration status and sensitivity to chemotherapy drugs. This model shows satisfactory predictive results and provides a reference for subsequent tumor immunotherapy.

FDX1 serves as a prognostic biomarker and promotes glioma progression by regulating the immune response

The present study investigates the prognostic value of the FDX1 gene and its association with immune infiltration in gliomas. Gene expression profiles and corresponding clinical parameters of glioma patients were obtained from the Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. In vitro experiments were also performed to validate its impact on malignant phenotypes of glioma cells. Kaplan-Meier analysis demonstrated that high FDX1 expression was associated with poor prognosis in glioma. Function and pathway enrichment for FDX1 predominantly demonstrated immunomodulatory function. In addition, the high-FDX1 expression group had higher Estimation of Stromal and Immune cells in malignant tumor tissues using Expression data, stromal, and immune scores (p<0.001). On evaluation of immunotherapy response, TIDE and dysfunction scores were higher in the low-FDX1 group, while the exclusion score demonstrated an opposite trend. In vitro tests showed that FDX1 silencing-induced inhibition of cell invasion and migration inactivated the nucleotide oligomerization domain (NOD)-like receptor signaling pathway by regulating PD-L1 expression. Notably, NOD1 expression was reversed in FDX1-knockdown cells after treatment with NOD1 agonists. In conclusion, FDX1 may play an important role in the diagnosis and treatment of gliomas. Regulating its expression may therefore help improve immunotherapy for these tumors.

Tumor cuproptosis and immune infiltration improve survival of patients with hepatocellular carcinoma with a high expression of ferredoxin 1

Background

Cuproptosis is a novel cell death pathway dependent on cellular copper ions and ferredoxin 1 (FDX1). Hepatocellular carcinoma (HCC) is derived from healthy liver as a central organ for copper metabolism. It remains no conclusive evidence whether cuproptosis is involved in survival improvement of patients with HCC.

Method

A 365-liver hepatocellular carcinoma (LIHC) cohort with RNA sequencing data and paired clinical and survival information was obtained from the The Cancer Genome Atlas (TCGA) dataset. A retrospective cohort of 57 patients with HCC with stages I/II/III was collected by Zhuhai People's Hospital from August 2016 to January 2022. Low- or high-FDX1 groups were divided according to the median value of FDX1 expression. Cibersort, single-sample gene set enrichment analysis, and multiplex immunohistochemistry analyzed immune infiltration in LIHC and HCC cohorts. Cell proliferation and migration of HCC tissues and hepatic cancer cell lines were evaluated using the Cell Counting Kit-8. Quantitative real-time PCR and RNA interference measured and downregulated FDX1 expression. Statistical analysis was conducted by R and GraphPad Prism software.

Results

High FDX1 expression significantly enhanced survival of patients with LIHC from the TCGA dataset, which was also demonstrated through a retrospective cohort with 57 HCC cases. Immune infiltration was different between the low- and high-FDX1 expression groups. Natural killer cells, macrophages, and B cells were significantly enhanced, and PD-1 expression was low in the high-FDX1 tumor tissues. Meanwhile, we found that a high expression of FDX1 decreased cell viability in HCC samples. HepG2 cells with FDX1 expression are sensitive to Cu²⁺, and interference of FDX1 promoted proliferation and migration of tumor cells. The consistent results were also demonstrated in Hep3B cells.

Conclusion

This study reveals that cuproptosis and tumor immune microenvironment were together involved in improvement of survival in patients with HCC with a high expression of FDX1.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Targeting copper death genotyping associated gene RARRES2 suppresses glioblastoma progression and macrophages infiltration

BACKGROUND

Copper homeostasis is associated with malignant biological behavior in various tumors. The excessive accumulation of copper can induce tumor death, which is named cuproptosis, and it is also closely related to tumor progression and the formation of the immune microenvironment. However, the associations of cuproptosis with glioblastoma (GBM) prognosis and microenvironment construction are poorly understood.

METHOD

First, TCGA and GEO (GSE83300, GSE74187) merged datasets were used to analyze the association of cuproptosis-related genes (CRGs) with GBM. Then, we performed cluster analysis of CRGs in GBM from the GEO (GSE83300, GSE74187) and TCGA merged datasets. Subsequently, the prognostic risk model was constructed by least absolute shrinkage and selection operator (LASSO) according to gene expression features in CRG clusters. Next, we performed a series of in-depth analyses, including tumor mutational burden (TMB) analysis, cluster analysis, and GBM IDH status prediction. Finally, RARRES2 was identified as a target gene for GBM treatment, especially IDH wild-type GBM. In addition, we further analyzed the correlation of CRG clusters and RARRES2 expression with the GBM immune microenvironment by ESTIMATE and CIBERSORT analyses. In vitro experiments were conducted to demonstrate that targeting RARRES2 inhibits glioblastoma progression and macrophage infiltration, particularly IDH wild-type GBM.

RESULTS

In the present study, we demonstrated that the CRG cluster was closely related to GBM prognosis and immune cell infiltration. Moreover, the prognostic risk model constructed with the three genes (MMP19, G0S2, RARRES2) associated with the CRG clusters could well evaluate the prognosis and immune cell infiltration in GBM. Subsequently, after further analyzing the tumor mutational burden (TMB) in GBM, we confirmed that RARRES2 in the prognostic risk model could be used as a crucial gene signature to predict the prognosis, immune cell infiltration and IDH status of GBM patients.

CONCLUSION

This study fully revealed the potential clinical impact of CRGs on GBM prognosis and the microenvironment, and determined the effect of the crucial gene (RARRES2) on the prognosis and tumor microenvironment construction of GBM, meanwhile, our study also revealed over-expressed RARRES2 is related to the IDH satus of GBM, which provides a novel strategy for the treatment of GBM, particularly IDH wild-type GBM.

A five-cuproptosis-related LncRNA Signature: predicting prognosis, assessing immune function & drug sensitivity in lung squamous cell carcinoma

Lung squamous cell carcinoma has so far lacked effective targets for diagnosis and treatment. In cancer research, long noncoding RNAs (LncRNAs) emerge as novel therapeutic targets and biomarkers. Cuprophosis is a new death type involving multiple biological processes in tumor cells. Here, we aimed to explore whether Cuprophosis-related lncRNAs could be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients. The Cancer Genome Map (TCGA) was used to obtain genome and clinical data, and Cuprophosis-relevant genes were found in the literature. A cuproptosis-related lncRNA risk model was built using co-expression analysis, univariate/multivariate Cox regression, and LASSO analysis. The survival analysis was used to assess the model's prognostic value. The univariate and multivariate Cox regression analyses were performed to determine whether risk score, age, gender, or clinical stages could be used as independent prognostic factors. Gene Set Enrichment Analysis and mutation analysis were performed on differentially expressed mRNA between high-risk and low-risk groups. The (TIDE) algorithm was used to conduct immunological functional analysis and drug sensitivity testing. Five cuproptosis-related LncRNAs were identified, and the selected LncRNAs constructed a prognosis model. According to the Kaplan-Meier survival analysis, the overall survival time for patients in the high-risk group was shorter than for those in the low-risk group. For LUSC patients, the risk score serves as an independent prognostic indicator. The GO and KEGG enrichment analysis revealed that the differentially expressed mRNAs between the high- and low-risk groups were enriched in several immune-related processes. The enrichment score of differentially expressed mRNAs in the high-risk group is higher than that of the low-risk group in multiple immune function pathways, including the IFN-γ and MHC I pathways. The Tumor Immune Dysfunction and Exclusion (TIDE) test revealed that the high-risk group was more likely to experience immune escape. The drug sensitivity analysis showed that patients with low-risk ratings were likely to respond to GW441756 and Salubrinal. In contrast, patients with higher risk scores were more responsive to dasatinib and Z-LLNIe CHO. The 5-Cuprophosis-related lncRNA signature can be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients.

Developing CuS for Predicting Aggressiveness and Prognosis in Lung Adenocarcinoma

Cuproptosis is a newfound cell death form that depends on copper (Cu) ionophores to transport Cu into cancer cells. Studies on the relationship have covered most common cancer types and analyzed the links between cuproptosis-related genes (CRGs) and various aspects of tumor characteristics. In this study, we evaluated the role of cuproptosis in lung adenocarcinoma (LUAD) and constructed the cuproptosis-related score (CuS) to predict aggressiveness and prognosis in LUAD, so as to achieve precise treatment for patients. CuS had a better predictive performance than cuproptosis genes, possibly due to the synergy of SLC family genes, and patients with a high CuS had a poor prognosis. Functional enrichment analysis revealed the correlation between CuS and immune and mitochondrial pathways in multiple datasets. Furthermore, we predicted six potential drugs targeting high-CuS patients, including AZD3759, which is a targeted drug for LUAD. In conclusion, cuproptosis is involved in LUAD aggressiveness, and CuS can accurately predict the prognosis of patients. These findings provide a basis for precise treatment of patients with high CuS in LUAD.

Cuproptosis-a potential target for the treatment of osteoporosis

Osteoporosis is an age-related disease of bone metabolism marked by reduced bone mineral density and impaired bone strength. The disease causes the bones to weaken and break more easily. Osteoclasts participate in bone resorption more than osteoblasts participate in bone formation, disrupting bone homeostasis and leading to osteoporosis. Currently, drug therapy for osteoporosis includes calcium supplements, vitamin D, parathyroid hormone, estrogen, calcitonin, bisphosphates, and other medications. These medications are effective in treating osteoporosis but have side effects. Copper is a necessary trace element in the human body, and studies have shown that it links to the development of osteoporosis. Cuproptosis is a recently proposed new type of cell death. Copper-induced cell death regulates by lipoylated components mediated via mitochondrial ferredoxin 1; that is, copper binds directly to the lipoylated components of the tricarboxylic acid cycle, resulting in lipoylated protein accumulation and subsequent loss of iron-sulfur cluster proteins, leading to proteotoxic stress and eventually cell death. Therapeutic options for tumor disorders include targeting the intracellular toxicity of copper and cuproptosis. The hypoxic environment in bone and the metabolic pathway of glycolysis to provide energy in cells can inhibit cuproptosis, which may promote the survival and proliferation of various cells, including osteoblasts, osteoclasts, effector T cells, and macrophages, thereby mediating the osteoporosis process. As a result, our group tried to explain the relationship between the role of cuproptosis and its essential regulatory genes, as well as the pathological mechanism of osteoporosis and its effects on various cells. This study intends to investigate a new treatment approach for the clinical treatment of osteoporosis that is beneficial to the treatment of osteoporosis.

Identification of hub cuproptosis related genes and immune cell infiltration characteristics in periodontitis

Introduction

Periodontitis is an inflammatory disease and its molecular mechanisms is not clear. A recently discovered cell death pathway called cuproptosis, may related to the disease.

Methods

The datasets GSE10334 of human periodontitis and control were retrieved from the Gene Expression Omnibus database (GEO) for analysis.Following the use of two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature removal (SVM-RFE) were used to find CRG-based signature. Then the Receiver operating characteristic (ROC) curves was used to evaluate the gene signature's discriminatory ability. The CIBERSORT deconvolution algorithm was used to study the link between hub genes and distinct types of immune cells. Next, the association of the CRGs with immune cells in periodontitis and relevant clusters of cuproptosis were found. The link between various clusters was ascertained by the GSVA and CIBERSORT deconvolution algorithm. Finally, An external dataset (GSE16134) was used to confirm the diagnosis capacity of the identified biomarkers. In addition, clinical samples were examined using qRT-PCR and immunohistochemistry to verifiy the expression of genes related to cuprotosis in periodontitis and the signature may better predict the periodontitis.

Results

15 periodontitis-related DE-CRGs were found,then 11-CRG-based signature was found by using of LASSO and SVM-RFE. ROC curves also supported the value of signature. CIBERSORT results of immune cell signature in periodontitis showed that signature genes is a crucial component of the immune response.The relevant clusters of cuproptosis found that the NFE2L2, SLC31A1, FDX1,LIAS, DLD, DLAT, and DBT showed a highest expression levels in Cluster2 ,while the NLRP3, MTF1, and DLST displayed the lowest level in Cluster 2 but the highest level in Cluster1. The GSVA results also showed that the 11 cuproptosis diagnostic gene may regulate the periodontitis by affecting immune cells. The external dataset (GSE16134) confirm the diagnosis capacity of the identified biomarkers, and clinical samples examined by qRT-PCR and immunohistochemistry also verified that these cuprotosis related signiture genes in periodontitis may better predict the periodontitis.

Conclusion

These findings have important implications for the cuproptosis and periodontitis, and highlight further research is needed to better understand the mechanisms underlying this relationship between the cuproptosis and periodontitis.

The cuproptosis-associated 11 gene signature as a predictor for outcomes and response to Bacillus Calmette-Guerin and immune checkpoint inhibitor therapies in bladder carcinoma

Bladder cancer (BC) or carcinoma (BLCA) is predominantly derived from urothelium and includes non-muscle invasive BC (NMIBC) and muscle invasive BC (MIBC). Bacillus Calmette-Guerin (BCG) has long been applied for NMIBC to effectively reduce disease recurrence or progression, whereas immune checkpoint inhibitors (ICIs) were recently introduced to treat advanced BLCA with good efficacy. For BCG and ICI applications, reliable biomarkers are required to stratify potential responders for better personalized interventions, and ideally, they can replace or reduce invasive examinations such as cystoscopy in monitoring treatment efficacy. Here we developed the cuproptosis-associated 11 gene signature (CuAGS-11) model to accurately predict survival and response to BCG and ICI regimens in BLCA patients. In both discovery and validation cohorts where BLCA patients were divided into high- and low-risk groups based on a median CuAGS-11 score as the cutoff, the high-risk group was associated with significantly shortened overall survival (OS) and progression-free survival (PFS) independently. The survival predictive accuracy was comparable between CuAGS-11 and stage, and their combination-based nomograms showed high consistence between predicted and observed OS/PFS. The analysis of 3 BLCA cohorts treated with BCG unveiled lower response rates and higher frequencies of recurrence or progression coupled with shorter survival in CuAGS-11 high-risk groups. In contrast, almost none of patients underwent progression in low-risk groups. In IMvigor210 cohort of 298 BLCA patients treated with ICI Atezolizumab, complete/partial remissions were 3-fold higher accompanied by significantly longer OS in the CuAGS-11 low- than high-risk groups (P = 7.018E-06). Very similar results were obtained from the validation cohort (P = 8.65E-05). Further analyses of Tumor Immune Dysfunction and Exclusion (TIDE) scores revealed that CuAGS-11 high-risk groups displayed robustly higher T cell exclusion scores in both discovery (P = 1.96E-05) and validation (P = 0.008) cohorts. Collectively, the CuAGS-11 score model is a useful predictor for OS/PFS and BCG/ICI efficacy in BLCA patients. For BCG-treated patients, reduced invasive examinations are suggested for monitoring the CuAGS-11 low-risk patients. The present findings thus provide a framework to improve BLCA patient stratification for personalized interventions and to reduce invasive monitoring inspections.

Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer

Background

Prostate cancer (PCa) is the most common malignant tumor of the male urinary system. Cuproptosis, as a novel regulated cell death, remains unclear in PCa. This study aimed to investigate the role of cuproptosis-related genes (CRGs) in molecular stratification, prognostic prediction, and clinical decision-making in PCa.

Methods

Cuproptosis-related molecular subtypes were identified by consensus clustering analysis. A prognostic signature was constructed with LASSO cox regression analyses with 10-fold cross-validation. It was further validated in the internal validation cohort and eight external validation cohorts. The tumor microenvironment between the two risk groups was compared using the ssGSEA and ESTIMATE algorithms. Finally, qRT-PCR was used to explore the expression and regulation of these model genes at the cellular level. Furthermore, 4D Label-Free LC-MS/MS and RNAseq were used to investigate the changes in CRGs at protein and RNA levels after the knockdown of the key model gene B4GALNT4.

Results

Two cuproptosis-related molecular subtypes with significant differences in prognoses, clinical features, and the immune microenvironment were identified. Immunosuppressive microenvironments were associated with poor prognosis. A prognostic signature comprised of five genes (B4GALNT4, FAM83D, COL1A, CHRM3, and MYBPC1) was constructed. The performance and generalizability of the signature were validated in eight completely independent datasets from multiple centers. Patients in the high-risk group had a poorer prognosis, more immune cell infiltration, more active immune-related functions, higher expression of human leukocyte antigen and immune checkpoint molecules, and higher immune scores. In addition, anti-PDL-1 immunotherapy prediction, somatic mutation, chemotherapy response prediction, and potential drug prediction were also analyzed based on the risk signature. The validation of five model genes' expression and regulation in qPCR was consistent with the results of bioinformatics analysis. Transcriptomics and proteomics analyses revealed that the key model gene B4GALNT4 might regulate CRGs through protein modification after transcription.

Conclusion

The cuproptosis-related molecular subtypes and the prognostic signature identified in this study could be used to predict the prognosis and contribute to the clinical decision-making of PCa. Furthermore, we identified a potential cuproptosis-related oncogene B4GALNT4 in PCa, which could be used as a target to treat PCa in combination with cuproptosis.

Prospects for the Use of Metal-Based Nanoparticles as Adjuvants for Local Cancer Immunotherapy

Immunotherapy is among the most effective approaches for treating cancer. One of the key aspects for successful immunotherapy is to achieve a strong and stable antitumor immune response. Modern immune checkpoint therapy demonstrates that cancer can be defeated. However, it also points out the weaknesses of immunotherapy, as not all tumors respond to therapy and the co-administration of different immunomodulators may be severely limited due to their systemic toxicity. Nevertheless, there is an established way through which to increase the immunogenicity of immunotherapy-by the use of adjuvants. These enhance the immune response without inducing such severe adverse effects. One of the most well-known and studied adjuvant strategies to improve immunotherapy efficacy is the use of metal-based compounds, in more modern implementation-metal-based nanoparticles (MNPs), which are exogenous agents that act as danger signals. Adding innate immune activation to the main action of an immunomodulator makes it capable of eliciting a robust anti-cancer immune response. The use of an adjuvant has the peculiarity of a local administration of the drug, which positively affects its safety. In this review, we will consider the use of MNPs as low-toxicity adjuvants for cancer immunotherapy, which could provide an abscopal effect when administered locally.

Basement membrane-related regulators for prediction of prognoses and responses to diverse therapies in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) remains a global health threat. Finding a novel biomarker for assessing the prognosis and new therapeutic targets is vital to treating this patient population. Our study aimed to explore the contribution of basement membrane-related regulators (BMR) to prognostic assessment and therapeutic response prediction in HCC.

MATERIAL AND METHODS

The RNA sequencing and clinical information of HCC were downloaded from TCGA-LIHC, ICGC-JP, GSE14520, GSE104580, and CCLE datasets. The BMR signature was created by the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and used to separate HCC patients into low- and high-risk groups. We conducted analyses using various R 4.1.3 software packages to compare prognoses and responses to immunotherapy, transcatheter arterial chemoembolization (TACE), and chemotherapeutic drugs between the groups. Additionally, stemness indices, molecular functions, and somatic mutation analyses were further explored in these subgroups.

RESULTS

The BMR signature included 3 basement membrane-related genes (CTSA, P3H1, and ADAM9). We revealed that BMR signature was an independent risk contributor to poor prognosis in HCC, and high-risk group patients presented shorter overall survival. We discovered that patients in the high-risk group might be responsive to immunotherapy, while patients in the low-risk group may be susceptible to TACE therapy. Over 300 agents were screened to identify effective drugs for the two subgroups.

CONCLUSION

Overall, basement membrane-related regulators represent novel biomarkers in HCC for assessing prognosis, response to immunotherapy, the effectiveness of TACE therapy, and drug susceptibility.

A bibliometric analysis of ferroptosis, necroptosis, pyroptosis, and cuproptosis in cancer from 2012 to 2022

This study aims to visualize research hotspots and trends of "ferroptosis in cancer", "necroptosis in cancer", "pyroptosis in cancer", and "cuproptosis in cancer" through a bibliometric analysis to facilitate understanding of future developments in basic and clinical research and to provide a new perspective on cancer treatment. From January 1, 2012 to October 31, 2022, in the field of "ferroptosis in cancer", a total of 2467 organizations from 79 different countries published 3302 articles. 2274 organizations from 72 different countries published 2233 articles in the field of " necroptosis in cancer". 1366 institutions from 58 different countries contributed 1445 publications in the field of "pyroptosis in cancer". In the field of " cuproptosis in cancer", the number of articles published in the last 10 years is relatively low, with a total of 109 articles published by 116 institutions from four different countries. In the field of "ferroptosis in cancer", Tang Daolin had published 66 documents, ranked the first, while Dixon SJ is the most cited author, cited 3148 times; In the fields of "necroptosis in cancer", Vandenabeele peter had published 35 papers and Degterev had been cited 995 times, ranked the first, respectively; Kanneganti thirumala-devi had published 24 papers, is the highest number of publications in the fields of "pyroptosis in cancer", while Shi JJ was the most cited author with being cited 508 times. Both Huang Yan and Wang Tao published three papers and tied for first place and Tsvetkov p ranks first with being cited 107 times in "cuproptosis in cancer". "Cell", "Cell", "Nature", and "Science" was the most frequently co-cited journal on "ferroptosis in cancer", "necroptosis in cancer", "pyroptosis in cancer", and "cuproptosis in cancer", respectively. Further exploration of inhibitors of different Programmed cell death (PCD) and their targeted therapies are potential treatment options for cancer, but more direct clinical evidence as well as higher level clinical trials remain to be explored. Further clarification of the mechanisms of crosstalk between these PCDs may provide effective cancer treatments. And the role of different types of PCDs, especially the novel ones discovered, in cancer can be expected to remain a hot topic of research in the cancer field for quite some time to come.

Identification and validation of cuproptosis related genes and signature markers in bronchopulmonary dysplasia disease using bioinformatics analysis and machine learning

BACKGROUND

Bronchopulmonary Dysplasia (BPD) has a high incidence and affects the health of preterm infants. Cuproptosis is a novel form of cell death, but its mechanism of action in the disease is not yet clear. Machine learning, the latest tool for the analysis of biological samples, is still relatively rarely used for in-depth analysis and prediction of diseases.

METHODS AND RESULTS

First, the differential expression of cuproptosis-related genes (CRGs) in the GSE108754 dataset was extracted and the heat map showed that the expression of NFE2L2 gene was significantly higher in the control group whereas the expression of GLS gene was significantly higher in the treatment group. Chromosome location analysis showed that both the genes were positively correlated and associated with chromosome 2. The results of immune infiltration and immune cell differential analysis showed differences in the four immune cells, significantly in Monocytes cells. Five new pathways were analyzed through two subgroups based on consistent clustering of CRG expression. Weighted correlation network analysis (WGCNA) set the screening condition to the top 25% to obtain the disease signature genes. Four machine learning algorithms: Generalized Linear Models (GLM), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGB) were used to screen the disease signature genes, and the final five marker genes for disease prediction. The models constructed by GLM method were proved to be more accurate in the validation of two datasets, GSE190215 and GSE188944.

CONCLUSION

We eventually identified two copper death-associated genes, NFE2L2 and GLS. A machine learning model-GLM was constructed to predict the prevalence of BPD disease, and five disease signature genes NFATC3, ERMN, PLA2G4A, MTMR9LP and LOC440700 were identified. These genes that were bioinformatics analyzed could be potential targets for identifying BPD disease and treatment.

Identification of a cuproptosis and copper metabolism gene-related lncRNAs prognostic signature associated with clinical and immunological characteristics of hepatocellular carcinoma

Background

The relationship between cuproptosis and HCC is still in the exploratory stage. Long noncoding RNAs (lncRNAs) have recently been linked to the progression of hepatocellular carcinoma (HCC). However, the clinical significance of lncRNAs associated with cuproptosis remains unclear.

Methods

Based on The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma (LIHC) dataset, we identified characteristic prognostic lncRNAs by univariate, LASSO, and multifactorial regression analysis, and constructed a prognostic signature of cuproptosis-related lncRNAs in HCC. The role of lncRNAs were identified through CCK-8, clone formation in Huh-7 cells with high expression of FDX1. Prognostic potential of the characteristic lncRNAs was evaluated in each of the two cohorts created by randomly dividing the TCGA cohort into a training cohort and a test cohort in a 1:1 ratio. Immune profiles in defined subgroups of cuproptosis-related lncRNA features as well as drug sensitivity were analyzed.

Results

We constructed a multigene signature based on four characteristic prognostic lncRNAs (AL590705.3, LINC02870, KDM4A-AS1, MKLN1-AS). These four lncRNAs participated in the development of cuproptosis. HCC patients were classified into high-risk and low-risk groups based on the median value of the risk score. The receiver operating characteristic curve area under the curve values for 1-, 3-, and 5-year survival were 0.773, 0.728, and 0.647, respectively, for the training cohort, and 0.764, 0.671, and 0.662, respectively, for the test cohort. Univariate and multifactorial regression analyses indicated that this prognostic feature was an independent prognostic factor for HCC. Principal component analysis plots clearly distinguished between low- and high-risk patients in terms of their probability of survival. Furthermore, gene set enrichment analysis showed that a variety of processes associated with tumor proliferation and progression were enriched in the high-risk group compared with the low-risk group. Moreover, there were significant differences in the expression of immune cell subpopulations, immune checkpoint genes, and potential drug screening, which provided distinct therapeutic recommendations for individuals with various risks.

Conclusions

We constructed a novel cuproptosis-associated lncRNA signature with a significant predictive value for the prognosis of patients with HCC. Cuproptosis-associated lncRNAs are associated with the tumor immune microenvironment of HCC and even the efficacy of tumor immunotherapy.

Identification of the cuproptosis-related hub genes and therapeutic agents for sarcopenia

Background: Along with acceleration of population aging, the increasing prevalence of sarcopenia has posed a heavy burden on families as well as society. In this context, it is of great significance to diagnose and intervene sarcopenia as early as possible. Recent evidence has indicated the role of cuproptosis in the development of sarcopenia. In this study, we aimed to seek the key cuproptosis-related genes that can be used for identification and intervention of sarcopenia.

Methods: The GSE111016 dataset was retrieved from GEO. The 31 cuproptosis-related genes (CRGs) were obtained from previous published studies. The differentially expressed genes (DEGs) and Weighed gene co-expression network analysis (WGCNA) were subsequently analyzed. The core hub genes were acquired by the intersection of DEGs, WGCNA and CRGs. Through logistic regression analysis, we established a diagnostic model of sarcopenia based on the selected biomarkers and was validated in muscle samples from GSE111006 and GSE167186. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis were performed on these genes. Furthermore, the gene set enrichment analysis (GSEA), and immune cell infiltration were also conducted on the identified core genes. Finally, we screened the potential drugs targeting the potential biomarkers of sarcopenia.

Results: A total of 902 DEGs and WGCNA containing 1,281 significant genes were preliminarily selected. Intersection of DEGs, WGCNA and CRGs yielded four core genes (PDHA1, DLAT, PDHB, and NDUFC1) as potential biomarkers for the prediction of sarcopenia. The predictive model was established and validated with high AUC values. KEGG pathway and Gene Ontology biological analysis indicated these core genes may play a crucial role in energy metabolism in mitochondria, oxidation process, and aging-related degenerative diseases. In addition, the immune cells may be involved in the development of sarcopenia through mitochondrial metabolism. Finally, metformin was identified as a promising strategy of sarcopenia treatment via targeting NDUFC1.

Conclusion: The four cuproptosis-related genes PDHA1, DLAT, PDHB and NDUFC1 may be the diagnostic biomarkers for sarcopenia, and metformin holds great potential to be developed as a therapy for sarcopenia. These outcomes provide new insights for better understanding of sarcopenia and innovative therapeutic approaches.

Identification of cuproptosis hub genes contributing to the immune microenvironment in ulcerative colitis using bioinformatic analysis and experimental verification

Instruction

Ulcerative colitis (UC) can cause a variety of immune-mediated intestinal dysfunctions and is a significant model of inflammatory bowel disease (IBD). Colorectal cancer (CRC) mostly occurs in patients with ulcerative colitis. Cuproptosis is a type of procedural death that is associated with different types of diseases to various degrees.

Methods

We used a combination of bioinformatic prediction and experimental verification to study the correlation between copper poisoning and UC. We used the Gene Expression Omnibus database to obtain disease gene expression data and then identified relevant genes involved in various expression levels in normal and UC samples. The Kyoto Encyclopedia of Genes and Genomes pathway analysis was performed to cluster the genes that are highly responsible and find the central interaction in gene crosstalk. Notably, DLD, DLAT, and PDHA1 were present in high-scoring PPI networks. In addition, hub gene expression information in UC tissues was integrated to estimate the relationship between UC copper poisoning and the immune environment.

Results

In our study, the expression of DLD, DLAT, and PDHA1 in UC tissues was lower than that in normal tissues. The key genes associated with cuproptosis have therapeutic effects on immune infiltration. We verified the expression of DLD, DLAT, and PDHA1 using real-time quantitative polymerase chain reaction in mouse models of UC induced by DSS.

Discussion

Notably, this study clearly indicates that bioinformatic analysis performed to verify the experimental methods provides evidence that cuproptosis is associated with UC. This finding suggests that immune cell infiltration in UC patients is associated with cuproptosis. The key genes associated with cuproptosis can be helpful for discovering the molecular mechanism of UC, thus facilitating the improvement of UC treatment and preventing the associated CRC.

Cuproptosis: mechanisms and links with cancers

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

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

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

The Role of Ferroptosis and Cuproptosis in Curcumin against Hepatocellular Carcinoma

BACKGROUND

Among cancer-related deaths, hepatocellular carcinoma (HCC) ranks fourth, and traditional Chinese medicine (TCM) treatment is an important complementary alternative therapy for HCC. Curcumin is a natural ingredient extracted from Curcuma longa with anti-HCC activity, while the therapeutic mechanisms of curcumin remain unclear, especially on ferroptosis and cuproptosis.

METHODS

Differentially expressed genes (DEGs) of curcumin treatment in PLC, KMCH, and Huh7 cells were identified, respectively. The common genes among them were then obtained to perform functional enrichment analysis and prognostic analysis. Moreover, weighted gene co-expression network analysis (WGCNA) was carried out for the construction of the co-expression network. The ferroptosis potential index (FPI) and the cuproptosis potential index (CPI) were subsequently used to quantitatively analyze the levels of ferroptosis and cuproptosis. Finally, single-cell transcriptome analysis of liver cancer was conducted.

RESULTS

We first identified 702, 515, and 721 DEGs from curcumin-treated PLC, KMCH, and Huh7 cells, respectively. Among them, HMOX1, CYP1A1, HMGCS2, LCN2, and MTTP may play an essential role in metal ion homeostasis. By WGCNA, grey60 co-expression module was associated with curcumin treatment and involved in the regulation of ion homeostasis. Furthermore, FPI and CPI assessment showed that curcumin had cell-specific effects on ferroptosis and cuproptosis in different HCC cells. In addition, there are also significant differences in ferroptosis and cuproptosis levels among 16 HCC cell subtypes according to single-cell transcriptome data analysis.

CONCLUSIONS

We developed CPI and combined it with FPI to quantitatively analyze curcumin-treated HCC cells. It was found that ferroptosis and cuproptosis, two known metal ion-mediated forms of programmed cell death, may have a vital effect in treating HCC with curcumin, and there are significant differences in various liver cancer cell types and curcumin treatment which should be considered in the clinical application of curcumin.

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

Background

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

Methods

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

Results

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

Conclusion

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

FNBP4 is a Potential Biomarker Associated with Cuproptosis and Promotes Tumor Progression in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that lacks an efficient therapeutic approach because of its elusive molecular mechanisms. This study aimed to investigate the biological function and potential mechanism of formin-binding protein 4 (FNBP4) in HCC.

Methods

FNBP4 expression in tissues and cells were detected by quantitative real-time PCR (qRT‒PCR), Western blot, and immunohistochemistry (IHC). The Kaplan-Meier method was used to explore the correlation between the FNBP4 expression and clinical survival. MTT, EdU incorporation, colony formation, and Transwell assays were performed to evaluate the function of FNBP4 in cell proliferation and migration in vitro. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to explore the potential mechanism of FNBP4. The prognostic risk signature and nomogram were constructed to demonstrate the prognostic value of FNBP4.

Results

We found that FNBP4 was upregulated in patients with HCC and associated with poor overall survival (OS). Furthermore, knockdown of FNBP4 inhibited the proliferation and migration in HCC cells. Then, we performed a KEGG pathway analysis of the coexpressed genes associated with FNBP4 and found that FNBP4 may be associated with tumor-related signaling pathways and cuproptosis. We verified that FNBP4 could cause cell cycle progression and inactivation of the hippo signaling pathway. A prognostic risk signature containing three FNBP4-related differentially expressed cuproptosis regulators (DECRs) was established and can be used as an independent risk factor to evaluate the prognosis of patients with HCC. In addition, a nomogram including a risk score and clinicopathological factors was used to predict patient survival probabilities.

Conclusion

FNBP4, as a potential biomarker associated with cuproptosis, promotes HCC cell proliferation and metastasis. We provide a new potential strategy for HCC treatment by targeting FNBP4.

Identification and verification of m7G-Related genes as biomarkers for prognosis of sarcoma

Background: Increasing evidence indicates a crucial role for N7-methylguanosine (m7G) methylation modification in human disease development, particularly cancer, and aberrant m7G levels are closely associated with tumorigenesis and progression via regulation of the expression of multiple oncogenes and tumor suppressor genes. However, the role of m7G in sarcomas (SARC) has not been adequately evaluated. Materials and methods: Transcriptome and clinical data were gathered from the TCGA database for this study. Normal and SARC groups were compared for the expression of m7G-related genes (m7GRGs). The expression of m7GRGs was verified using real-time quantitative PCR (RT-qPCR) in SARC cell lines. Then, differentially expressed genes (DEGs) were identified between high and low m7GRGs expression groups in SARC samples, and GO enrichment and KEGG pathways were evaluated. Next, prognostic values of m7GRGs were evaluated by Cox regression analysis. Subsequently, a prognostic model was constructed using m7GRGs with good prognostic values by Lasso regression analysis. Besides, the relationships between prognostic m7GRGs and immune infiltration, clinical features, cuproptosis-related genes, and antitumor drugs were investigated in patients with SARC. Finally, a ceRNA regulatory network based on m7GRGs was constructed. Results: The expression of ten m7GRGs was higher in the SARC group than in the control group. DEGs across groups with high and low m7GRGs expression were enriched for adhesion sites and cGMP-PKG. Besides, we constructed a prognostic model that consists of EIF4A1, EIF4G3, NCBP1, and WDR4 m7GRGs for predicting the survival likelihood of sarcoma patients. And the elevated expression of these four prognostic m7GRGs was substantially associated with poor prognosis and elevated expression in SARC cell lines. Moreover, we discovered that these four m7GRGs expressions were negatively correlated with CD4⁺ T cell levels, dendritic cell level and tumor purity, and positively correlated with tumor mutational burden, microsatellite instability, drug sensitivity and cuproptosis-related genes in patients with sarcomas. Then, a triple regulatory network of mRNA, miRNA, and lncRNA was established. Conclusion: The current study identified EIF4A1, EIF4G3, NCBP1, and WDR4 as prognostic genes for SARC that are associated with m7G.These findings extend our knowledge of m7G methylation in SARC and may guide the development of innovative treatment options.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Development and validation of a novel ferroptosis‑related lncRNA prognostic signature for pancreatic adenocarcinoma

Long non‑coding RNAs (lncRNAs) serve a pivotal role in the regulation of cancer cell ferroptosis. However, the prognostic value of ferroptosis‑related lncRNAs in pancreatic adenocarcinoma (PAAD) largely remains unclear. We aimed at constructing a lncRNA‑based signature to improve the prognosis prediction of PAAD. In the present study, the transcriptome profiling data and clinical information of patients with PAAD were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Gene Consortium (ICGC) databases. Univariate Cox regression analysis of the TCGA cohort demonstrated that 26 ferroptosis‑related lncRNAs had significant prognostic value for PAAD (all P<0.01). Least absolute shrinkage and selection operator regression and multivariate Cox proportional hazards regression analyses were performed to construct a prognostic ferroptosis‑related lncRNA signature (FRLS) comprising nine ferroptosis‑related lncRNAs. The efficacy of this FRLS was verified in the training (TCGA) and validation (ICGC) cohorts. Based on the risk model, high risk scores were significantly correlated with poor overall survival (OS) (hazard ratio, 1.314; 95% confidence interval, 1.218‑1.418; P<0.001). The receiver operating characteristic curves and principal component analysis further demonstrated the robust prognostic ability of the FRLS. Furthermore, a nomogram with favorable predictive efficacy for the prediction of OS was constructed based on the FRLS and clinical features. Gene set enrichment analysis demonstrated that the genes in the FRLS participated in a number of cancer‑associated immunoregulatory pathways. Importantly, it was demonstrated that immune infiltration and response to cancer immunotherapy differed significantly between the high and low‑risk groups according to the FRLS. In conclusion, the risk signature based on the FRLS has potential for the clinical prediction of prognosis and immunotherapy response in patients with PAAD.

Revealing Prognostic and Immunotherapy-Sensitive Characteristics of a Novel Cuproptosis-Related LncRNA Model in Hepatocellular Carcinoma Patients by Genomic Analysis

Immunotherapy has shown strong anti-tumor activity in a subset of patients. However, many patients do not benefit from the treatment, and there is no effective method to identify sensitive immunotherapy patients. Cuproptosis as a non-apoptotic programmed cell death caused by excess copper, whether it is related to tumor immunity has attracted our attention. In the study, we constructed the prognostic model of 9 cuproptosis-related LncRNAs (crLncRNAs) and assessed its predictive capability, preliminarily explored the potential mechanism causing treatment sensitivity difference between the high-/low-risk group. Our results revealed that the risk score was more effective than traditional clinical features in predicting the survival of HCC patients (AUC = 0.828). The low-risk group had more infiltration of immune cells (B cells, CD8+ T cells, CD4+ T cells), mainly with anti-tumor immune function (p < 0.05). It showed higher sensitivity to immune checkpoint inhibitors (ICIs) treatment (p < 0.001) which may exert the effect through the AL365361.1/hsa-miR-17-5p/NLRP3 axis. In addition, NLRP3 mutation-sensitive drugs (VNLG/124, sunitinib, linifanib) may have better clinical benefits in the high-risk group. All in all, the crLncRNAs model has excellent specificity and sensitivity, which can be used for classifying the therapy-sensitive population and predicting the prognosis of HCC patients.

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

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

Cuproptosis regulatory genes greatly contribute to clinical assessments of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common abdominal cancer with dissatisfactory therapeutic effects. The discovery of cuproptosis lights on new approach for cancer treatment and assessment. So far, there is extremely limited research investigating the roles of cuproptosis-related (CR) genes in cancers.

METHODS

A novel CR risk signature was constructed using the Lasso regression analysis. Its prognostic value was assessed via a series of survival analyses and validated in three GEO cohorts. The effects of CR risk signature on tumor immune microenvironment (TIM) were explored through CIBERSORT, ESTIMATE, and ssGSEA algorithms. Using GESA, we investigated its impacts on various metabolism process. The somatic mutation features of CR signature genes were also explored via cBioPortal database. Using tumor mutation burden, expressions of immune checkpoints, TIDE score, IMvigor 210 cohort, and GSE109211 dataset, we explored the potential associations of CR risk score with the efficacy of immune checkpoint inhibitors (ICIs) and sorafenib. Finally, the biofunctions of DLAT in HCC cells were ascertained through qPCR, immunohistochemistry, colony formation, and Transwell assays.

RESULTS

FDX1, DLAT, CDKN2A and GLS constituted the CR risk signature. CR risk signature possessed high prognostic value and was also applicable to three validation cohorts. Meanwhile, it could improve the accuracy and clinical making-decision benefit of traditional prognostic model. Moreover, high CR risk was indicative of unfavorable anti-tumor immune response and active metabolisms of glycolysis and nucleotide. As for therapeutic correlation, CR risk score was a potential biomarker for predicting the efficacy of ICIs and sorafenib. Through qPCR and immunohistochemistry detection in clinical samples, we reconfirmed DLAT was significantly upregulated in HCC samples. Overexpression of DLAT could promote the proliferation, migration, and invasion of HepG2 and HuH-7 cells.

CONCLUSIONS

The novel CR risk signature greatly contributed to the clinical assessment of HCC. Cuproptosis regulatory gene DLAT possessed cancer-promoting capacities and was expected to be a promising therapeutic target for HCC.

Regulatory roles of copper metabolism and cuproptosis in human cancers

Copper is an essential micronutrient for human body and plays a vital role in various biological processes including cellular respiration and free radical detoxification. Generally, copper metabolism in the body is in a stable state, and there are specific mechanisms to regulate copper metabolism and maintain copper homeostasis. Dysregulation of copper metabolism may have a great connection with various types of diseases, such as Wilson disease causing copper overload and Menkes disease causing copper deficiency. Cancer presents high mortality rates in the world due to the unlimited proliferation potential, apoptosis escape and immune escape properties to induce organ failure. Copper is thought to have a great connection with cancer, such as elevated levels in cancer tissue and serum. Copper also affects tumor progression by affecting angiogenesis, metastasis and other processes. Notably, cuproptosis is a novel form of cell death that may provide novel targeting strategies for developing cancer therapy. Copper chelators and copper ionophores are two copper coordinating compounds for the treatment of cancer. This review will explore the relationship between copper metabolism and cancers, and clarify copper metabolism and cuproptosis for cancer targeted therapy.

A novel prognostic scoring model based on copper homeostasis and cuproptosis which indicates changes in tumor microenvironment and affects treatment response

Background: Intracellular copper homeostasis requires a complex system. It has shown considerable prospects for intervening in the tumor microenvironment (TME) by regulating copper homeostasis and provoking cuproptosis. Their relationship with hepatocellular carcinoma (HCC) remains elusive. Methods: In TCGA and ICGC datasets, LASSO and multivariate Cox regression were applied to obtain the signature on the basis of genes associated with copper homeostasis and cuproptosis. Bioinformatic tools were utilized to reveal if the signature was correlated with HCC characteristics. Single-cell RNA sequencing data analysis identified differences in tumor and T cells' pathway activity and intercellular communication of immune-related cells. Real-time qPCR analysis was conducted to measure the genes' expression in HCC and adjacent normal tissue from 21 patients. CCK8 assay, scratch assay, transwell, and colony formation were conducted to reveal the effect of genes on in vitro cell proliferation, invasion, migration, and colony formation. Results: We constructed a five-gene scoring system in relation to copper homeostasis and cuproptosis. The high-risk score indicated poor clinical prognosis, enhanced tumor malignancy, and immune-suppressive tumor microenvironment. The T cell activity was markedly reduced in high-risk single-cell samples. The high-risk HCC patients had a better expectation of ICB response and reactivity to anti-PD-1 therapy. A total of 156 drugs were identified as potential signature-related drugs for HCC treatment, and most were sensitive to high-risk patients. Novel ligand-receptor pairs such as FASLG, CCL, CD40, IL2, and IFN-Ⅱ signaling pathways were revealed as cellular communication bridges, which may cause differences in TME and immune function. All crucial genes were differentially expressed between HCC and paired adjacent normal tissue. Model-constructed genes affected the phosphorylation of mTOR and AKT in both Huh7 and Hep3B cells. Knockdown of ZCRB1 impaired the proliferation, invasion, migration, and colony formation in HCC cell lines. Conclusion: We obtained a prognostic scoring system to forecast the TME changes and assist in choosing therapy strategies for HCC patients. In this study, we combined copper homeostasis and cuproptosis to show the overall potential risk of copper-related biological processes in HCC for the first time.

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

Backgrounds

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

Methods

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

Results

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

Conclusion

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