Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer

A Cuproptosis-Related gene Signature as a Prognostic Biomarker in Thyroid Cancer Based on Transcriptomics

Thyroid cancer (THCA) is the most prevalent endocrine tumor, and its incidence continues to increase every year. However, the processes underlying the aggressive progression of thyroid cancer are unknown. We concentrated on the prognostic and biological importance of thyroid cancer cuproptosis-related genes in this investigation. Genomic and clinical data were obtained from the UCSC XENA website, and cuproptosis-related genes were obtained from the FerrDb website. We performed differential expression analysis and Cox regression analysis to identify possible predictive targets associated with thyroid cancer prognosis. To assess the role of CDKN2A in thyroid cancer and the ability to predict prognosis on the basis of the CDKN2A expression level, we performed immunohistochemical staining, survival analysis, immunological analysis, functional analysis, and clinical analysis with respect to CDKN2A gene expression. CDKN2A expression levels were found to be inversely correlated with thyroid cancer prognosis. Higher levels of CDKN2A expression were associated with higher T, N, and clinicopathological stage and more residual tumor cells. Through univariate and multivariate Cox regression analyses, the CDKN2A expression level was shown to be linked with thyroid cancer patients' overall survival (OS). Moreover, we discovered that CDKN2A expression was linked to a dysfunctional tumor immune microenvironment. The study shows that CDKN2A, a cuproptosis-related gene, can be used as a prognostic marker for thyroid cancer.

Omics sciences for cervical cancer precision medicine from the perspective of the tumor immune microenvironment

Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer (CC). However, the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment (TIME). Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME. Furthermore, integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior. In this review, we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC, highlighting their utility in identifying metastasis dissemination, recurrence risk, and therapeutic resistance in patients treated with immunotherapeutic approaches. This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms. Additionally, an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.

Cuproptosis-related genes signature could predict prognosis and the response of immunotherapy in cervical cancer

Background

A lot of studies have shown a close relationship between cuproptosis and cancer. The main purpose of this study is to analyze the impact of cuproptosis on cervical cancer (CC).

Methods

Using The Cancer Genome Atlas (TCGA) public database, we analyzed the genetic correlation, expression, and prognostic value of 25 cuproptosis-related genes (CRGs) in CC. A least absolute shrinkage and selection operator (LASSO) risk regression model was constructed to compare the changes in associated pathways, prognosis, immune infiltration, and antibody programmed cell death-ligand 1 (anti-PD-L1) treatment response of the high- and low-risk groups. In addition, we collected CC tissue samples before and after radiotherapy for ribonucleic acid (RNA) sequencing, and analyzed the relationship between CRGs and radiotherapy.

Results

The results showed CRGs were differentially expressed and were associated with multiple metabolic pathways. High expression of COX7B, PIH1D2, NDUFA1, NDUFA2 and NDUFB1 indicated a better prognosis. CRGs signature could predict prognosis (P<0.001) and affect immune infiltration. The prognosis was better in the low-risk group, while the high-risk group was more correlated with PD-L1. SLC25A5 downregulated expression (P=0.001) and SLC6A3 upregulated (P=0.02) after radiotherapy. SLC25A5 was related to the degree of differentiation of CC; the worse the differentiation, the higher the expression.

Conclusions

CRGs may further affect patient prognosis and response to immunotherapy by influencing metabolic pathways and immune infiltration. Radiation could alter the expression of CRGs, which may have potential research value in evaluating the efficacy of radiotherapy.

Review to Elucidate the Correlation between Cuproptosis-Related Genes and Immune Infiltration for Enhancing the Detection and Treatment of Cervical Cancer

Copper is a vital trace element in oxidized and reduced forms. It plays crucial roles in numerous biological events such as redox chemistry, enzymatic reactions, mitochondrial respiration, iron metabolism, autophagy, and immune modulation. Maintaining the balance of copper in the body is essential because its deficiency and excess can be harmful. Abnormal copper metabolism has a two-fold impact on the development of tumors and cancer treatment. Cuproptosis is a form of cell death that occurs when there is excessive copper in the body, leading to proteotoxic stress and the activation of a specific pathway in the mitochondria. Research has been conducted on the advantageous role of copper ionophores and chelators in cancer management. This review presents recent progress in understanding copper metabolism, cuproptosis, and the molecular mechanisms involved in using copper for targeted therapy in cervical cancer. Integrating trace metals and minerals into nanoparticulate systems is a promising approach for controlling invasive tumors. Therefore, we have also included a concise overview of copper nanoformulations targeting cervical cancer cells. This review offers comprehensive insights into the correlation between cuproptosis-related genes and immune infiltration, as well as the prognosis of cervical cancer. These findings can be valuable for developing advanced clinical tools to enhance the detection and treatment of cervical cancer.

Copper homeostasis and cuproptosis in gynecological cancers

Copper (Cu) is an essential trace element involved in a variety of biological processes, such as antioxidant defense, mitochondrial respiration, and bio-compound synthesis. In recent years, a novel theory called cuproptosis has emerged to explain how Cu induces programmed cell death. Cu targets lipoylated enzymes in the tricarboxylic acid cycle and subsequently triggers the oligomerization of lipoylated dihydrolipoamide S-acetyltransferase, leading to the loss of Fe-S clusters and induction of heat shock protein 70. Gynecological malignancies including cervical cancer, ovarian cancer and uterine corpus endometrial carcinoma significantly impact women's quality of life and even pose a threat to their lives. Excessive Cu can promote cancer progression by enhancing tumor growth, proliferation, angiogenesis and metastasis through multiple signaling pathways. However, there are few studies investigating gynecological cancers in relation to cuproptosis. Therefore, this review discusses Cu homeostasis and cuproptosis while exploring the potential use of cuproptosis for prognosis prediction as well as its implications in the progression and treatment of gynecological cancers. Additionally, we explore the application of Cu ionophore therapy in treating gynecological malignancies.

Bioinformatics analysis and experimental validation of m6A and cuproptosis-related lncRNA NFE4 in clear cell renal cell carcinoma

PURPOSE

This study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using the information acquired from The Cancer Genome Atlas (TCGA) database.

METHODS

First, the co-expression analysis was performed to identify lncRNAs linked with N6-methyladenosine (m6A) and cuproptosis in ccRCC. Then, a model encompassing four candidate lncRNAs was constructed via univariate, least absolute shrinkage together with selection operator (LASSO), and multivariate regression analyses. Furthermore, Kaplan-Meier, principal component, functional enrichment annotation, and nomogram analyses were performed to develop a risk model that could effectively assess medical outcomes for ccRCC cases. Moreover, the cellular function of NFE4 in Caki-1/OS-RC-2 cultures was elucidated through CCK-8/EdU assessments and Transwell experiments. Dataset outcomes indicated that NFE4 can have possible implications in m6A and cuproptosis, and may promote ccRCC progression.

RESULTS

We constructed a panel of m6A and cuproptosis-related lncRNAs to construct a prognostic prediction model. The Kaplan-Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. Furthermore, the m6A and cuproptosis-related lncRNA model indicated higher diagnostic efficiency than other clinical features. Moreover, the NFE4 function analysis indicated a gene associated with m6A and cuproptosis-related lncRNAs in ccRCC. It was also revealed that the proliferation and migration of Caki-1 /OS-RC-2 cells were inhibited in the NFE4 knockdown group.

CONCLUSION

Overall, this study indicated that NFE4 and our constructed risk signature could predict outcomes and have potential clinical value.

A combination of cuproptosis and lncRNAs predicts the prognosis and tumor immune microenvironment in cervical cancer

BACKGROUND

Cuproptosis induces proteotoxic stress and eventually leads to cell death. However, the relationship between cuproptosis and lncRNAs in cervical cancer has not been fully elucidated. Therefore, we aim to explore the association among lncRNAs, cuproptosis and clinical features in cervical cancer.

METHODS

RNA sequencing, genetic mutations, and clinical data of CESC patients were obtained from TCGA. Cuproptosis-associated genes were gathered. WGCNA was used to cluster important modules, and KEGG, GO, GSEA and GSVA were used to explore functional and pathway enrichment. The association between immune microenvironment and cuproptosis-related lncRNAs was performed by using cibersort algorithm and other platforms, including XCELL, TIMER, QUANTISEQ, MCPCOUNTER and EPIC. Fluorescence quantitative PCR was employed to detect the expression of LINC01833 and LINC02321, and CCK-8 and cell scratch assays were used to assess cell proliferation and migration capabilities after LINCRNA interference.

RESULTS

202 upregulated and 45 downregulated lncRNAs were selected. The survival analysis showed that there was a statistically significant difference in survival rates between the high-risk and low-risk groups. The prognosis of tumour mutation burden and the degree of immune infiltration were differed noticeably between the high-risk and low-risk groups. BHG712, TL-2-105, FR-180204, Masitinib, TAK-715, ODI-027, JW-7-24-2, and OSI-930 had substantially higher IC50 values in the high-risk group. Notably, we found AL360178.1 was associated with RNF44 E3 ubiquitin ligase expression. In cervical cancer cell lines, LINC01833 and LINC02321 displayed significant upregulation. Efficient siRNA transfection led to a decreased expression of LINC01833 and LINC02321. This knockdown significantly hindered both cell proliferation and migration capabilities in cervical cancer cells compared to the negative control.

CONCLUSION

In conclusion, we constructed five cuprotosis-related lncRNA prognostic models, which may be new tumor therapeutic targets for the prevention and treatment of cervical cancer.

Identification of cuproptosis-related lncRNA for predicting prognosis and immunotherapeutic response in cervical cancer

Patients diagnosed with advanced cervical cancer (CC) have poor prognosis after primary treatment, and there is a lack of biomarkers for predicting patients with an increased risk of recurrence of CC. Cuproptosis is reported to play a role in tumorigenesis and progression. However, the clinical impacts of cuproptosis-related lncRNAs (CRLs) in CC remain largely unclear. Our study attempted to identify new potential biomarkers to predict prognosis and response to immunotherapy with the aim of improving this situation. The transcriptome data, MAF files, and clinical information for CC cases were obtained from the cancer genome atlas, and Pearson correlation analysis was utilized to identify CRLs. In total, 304 eligible patients with CC were randomly assigned to training and test groups. LASSO regression and multivariate Cox regression were performed to construct a cervical cancer prognostic signature based on cuproptosis-related lncRNAs. Afterwards, we generated Kaplan-Meier curves, receiver operating characteristic curves and nomograms to verify the ability to predict prognosis of patients with CC. Genes for assessing differential expression among risk subgroups were also evaluated by functional enrichment analysis. Immune cell infiltration and the tumour mutation burden were analysed to explore the underlying mechanisms of the signature. Furthermore, the potential value of the prognostic signature to predict response to immunotherapy and sensitivity to chemotherapy drugs was examined. In our study, a risk signature containing eight cuproptosis-related lncRNAs (AL441992.1, SOX21-AS1, AC011468.3, AC012306.2, FZD4-DT, AP001922.5, RUSC1-AS1, AP001453.2) to predict the survival outcome of CC patients was developed, and the reliability of the risk signature was appraised. Cox regression analyses indicated that the comprehensive risk score is an independent prognostic factor. Moreover, significant differences were found in progression-free survival, immune cell infiltration, therapeutic response to immune checkpoint inhibitors, and IC50 for chemotherapeutic agents between risk subgroups, suggesting that our model can be well employed to assess the clinical efficacy of immunotherapy and chemotherapy. Based on our 8-CRLs risk signature, we were able to independently assess the outcome and response to immunotherapy of CC patients, and this signature might benefit clinical decision-making for individualized treatment.

An integrative analysis revealing cuproptosis-related lncRNAs signature as a novel prognostic biomarker in hepatocellular carcinoma

Background: Cuproptosis is a newly defined form of cell death, whether cuproptosis involved in hepatocellular carcinoma (HCC) remains elusive. Method: We obtained patients' RNA expression data and follow-up information from University of California Santa Cruz (UCSC) and The Cancer Genome Atlas (TCGA). We analyzed the mRNA level of Cuproptosis-related genes (CRGs) and performed univariate Cox analysis. Liver hepatocellular carcinoma (LIHC) was chosen for further investigation. Real-Time quantitative PCR (RT-qPCR), Western blotting (WB), Immunohistochemical (IHC), and Transwell assays were used to determine expression patterns and functions of CRGs in LIHC. Next, we identified CRGs-related lncRNAs (CRLs) and differentially expressed CRLs between HCC and normal cases. Univariate Cox analysis, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to construct the prognostic model. Univariate and multivariate Cox analysis was used to assess whether the risk model can act as an independent risk factor of overall survival duration. Different risk groups performed immune correlation analysis, tumor mutation burden (TMB), and Gene Set Enrichment Analysis (GSEA) analysis were performed in different risk groups. Finally, we assessed the performance of the predictive model in drug sensitivity. Results: CRGs expression levels have significant differences between tumor and normal tissues. High expression of Dihydrolipoamide S-Acetyltransferase (DLAT) correlated to metastasis of HCC cells and indicated poor prognosis for HCC patients. Our prognostic model consisted of four cuproptosis-related lncRNA (AC011476.3, AC026412.3, NRAV, MKLN1-AS). The prognostic model performed well in predicting survival rates. The results from Cox regression analysis suggested that risk score can serve as an independent prognostic element for survival durations. Survival analysis revealed that low risk patients have extended survival periods compared with those with high risk. The results of the immune analysis indicated that risk score has a positive correlation with B cell and CD4⁺ T cell Th2, while has a negative relationship with endothelial cell and hematopoietic cells. Besides, immune checkpoint genes have higher expression folds in the high-risk set than in the low-risk set. The high-risk group had higher rates of genetic mutation than the low-risk set while having a shorter survival time. GSEA revealed the signaling pathways enriched in the high-risk group were mostly immune-related, while metabolic-related pathways were enriched in the low-risk group. Drugs sensitivity analysis indicated that our model has the ability to predict the efficacy of clinical treatment. Conclusion: The Cuproptosis-related lncRNAs prognostic formula is a novel predictor of HCC patients' prognosis and drug sensitivity.

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

BACKGROUND

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

METHOD

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

RESULT

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

CONCLUSIONS

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