Cuproptosis status affects treatment options about immunotherapy and targeted therapy for patients with kidney renal clear cell carcinoma

Mechanisms of cuproptosis and its relevance to distinct diseases

Copper is a trace element required by the organism, but once the level of copper exceeds the threshold, it becomes toxic and even causes death. The underlying mechanisms of copper-induced death are inconclusive, with different studies showing different opinions on the mechanism of copper-induced death. Multiple investigations have shown that copper induces oxidative stress, endoplasmic reticulum stress, nucleolar stress, and proteasome inhibition, all of which can result in cell death. The latest research elucidates a copper-dependent death and denominates it as cuproptosis. Cuproptosis takes place through the combination of copper and lipoylated proteins of the tricarboxylic acid cycle, triggering agglomeration of lipoylated proteins and loss of iron-sulfur cluster proteins, leading to proteotoxic stress and ultimately death. Given the toxicity and necessity of copper, abnormal levels of copper lead to diseases such as neurological diseases and cancer. The development of cancer has a high demand for copper, neurological diseases involve the change of copper contents and the binding of copper to proteins. There is a close relationship between these two kinds of diseases and copper. Here, we summarize the mechanisms of copper-related death, and the association between copper and diseases, to better figure out the influence of copper in cell death and diseases, thus advancing the clinical remedy of these diseases.

Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

Cuproptosis is a novel type to regulate cell death with copper-dependent manner, and has been reported to involve in the occurrence and development of various malignant tumors. However, the association between cuproptosis and the tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) remained unclear. To address this question, we integrated the single cell RNA sequencing (scRNA-seq) datasets of ccRCC across different stages, systematically examined the distinctive expression patterns of cuproptosis-related genes (CRGs) within the TME of ccRCC, and explored the crucial signatures using the spatial transcriptome sequencing (ST-seq) dataset. The cuproptosis activities reduced in cancer tissues along with the ccRCC development, and recovered after therapy. We identified HILPDA+ ccRCC1 subtype, characterized with hypoxia, as cuproptosis susceptible cells associated with a better prognosis. The main co-expression modules of HILPDA+ ccRCC1 subtype highlighted the role in anion transport, response to oxygen species and PD-L1-PD-1 pathway. Furthermore, the immunosuppressive cells might interact with HILPDA+ ccRCC1 subtype via HAVCR2-LGALS9, C3-C3AR1, HLA-A-CD8B and HLA-C-CD8A axises to shape the cuproptosis-related TME landscape. In summary, we anticipate that this study will offer valuable insights and potential strategies of cuproptosis for therapy of ccRCC.

Systematic analysis of cuproptosis abnormalities and functional significance in cancer

BACKGROUND

Cuproptosis is a recently discovered type of cell death, but the role and behavior of cuproptosis-related genes (CuRGs) in cancers remain unclear. This paper aims to address these issues by analyzing the multi-omics characteristics of cancer-related genes (CuRGs) across various types of cancer.

METHOD

To investigate the impact of somatic copy number alterations (SCNA) and DNA methylation on CRG expression, we will analyze the correlation between these factors. We developed a cuproptosis index (CPI) model to measure the level of cuproptosis and investigate its functional roles. Using this model, we assessed the clinical prognosis of colorectal cancer patients and analyzed genetic changes and immune infiltration features in different CPI levels.

RESULTS

The study's findings indicate that the majority of cancer-related genes (CuRGs) were suppressed in tumors and had a positive correlation with somatic copy number alterations (SCNA), while having a negative correlation with DNA methylation. This suggests that both SCNA and DNA methylation have an impact on the expression of CuRGs. The CPI model is a reliable predictor of survival outcomes in patients with colorectal cancer and can serve as an independent prognostic factor. Patients with a higher CPI have a worse prognosis. We conducted a deeper analysis of the genetic alterations and immune infiltration patterns in both CPI positive and negative groups. Our findings revealed significant differences, indicating that CuRGs may play a crucial role in tumor immunity mechanisms. Additionally, we have noticed a positive correlation between CuRGs and various crucial pathways that are linked to the occurrence, progression, and metastasis of tumors.

CONCLUSIONS

Overall, our study systematically analyzes cuproptosis and its regulatory genes, emphasizing the potential of using cuproptosis as a basis for cancer therapy.

Machine learning-driven prognostic analysis of cuproptosis and disulfidptosis-related lncRNAs in clear cell renal cell carcinoma: a step towards precision oncology

Cuproptosis and disulfidptosis, recently discovered mechanisms of cell death, have demonstrated that differential expression of key genes and long non-coding RNAs (lncRNAs) profoundly influences tumor development and affects their drug sensitivity. Clear cell renal cell carcinoma (ccRCC), the most common subtype of kidney cancer, presently lacks research utilizing cuproptosis and disulfidptosis-related lncRNAs (CDRLRs) as prognostic markers. In this study, we analyzed RNA-seq data, clinical information, and mutation data from The Cancer Genome Atlas (TCGA) on ccRCC and cross-referenced it with known cuproptosis and disulfidptosis-related genes (CDRGs). Using the LASSO machine learning algorithm, we identified four CDRLRs-ACVR2B-AS1, AC095055.1, AL161782.1, and MANEA-DT-that are strongly associated with prognosis and used them to construct a prognostic risk model. To verify the model's reliability and validate these four CDRLRs as significant prognostic factors, we performed dataset grouping validation, followed by RT-qPCR and external database validation for differential expression and prognosis of CDRLRs in ccRCC. Gene function and pathway analysis were conducted using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) for high- and low-risk groups. Additionally, we have analyzed the tumor mutation burden (TMB) and the immune microenvironment (TME), employing the oncoPredict and Immunophenoscore (IPS) algorithms to assess the sensitivity of diverse risk categories to targeted therapeutics and immunosuppressants. Our predominant objective is to refine prognostic predictions for patients with ccRCC and inform treatment decisions by conducting an exhaustive study on cuproptosis and disulfidptosis.

Identification of molecular characteristics of FUT8 and alteration of core fucosylation in kidney renal clear cell cancer

BACKGROUND

Kidney renal clear cell cancer (KIRC) is a type of urological cancer that occurs worldwide. Core fucosylation (CF), as the most common post-translational modification, is involved in the tumorigenesis.

METHODS

The alterations of CF-related genes were summarized in pan-cancer. The "ConsensusClusterPlus" package was utilized to identify two CF-related KIRC subtypes. The "ssgsea" function was chosen to estimate the CF score, signaling pathways and cell deaths. Multiple algorithms were applied to assess immune responses. The "oncoPredict" was utilized to estimate the drug sensitivity. The IHC and subgroup analysis was performed to reveal the molecular features of FUT8. Single-cell RNA sequencing (scRNA-seq) data were scrutinized to evaluate the CF state.

RESULTS

In pan-cancer, there was a noticeable alteration in the expression of CF-related genes. In KIRC, two CF-related subtypes (i.e., C1, C2) were obtained. In comparison to C2, C1 exhibited a higher CF score and correlated with poorer overall survival. Additionally, the TME of C2 demonstrated increased activity in neutrophils, macrophages, myeloid dendritic cells, and B cells, alongside a higher presence of silent mast cells, NK cells, and endothelial cells. Compared to normal samples, higher expression of FUT8 is observed in KIRC. The mutation of SETD2 was more frequent in low-FUT8 samples while the mutation of DNAH9 was more frequent in high-FUT8 samples. scRNA-seq analyses revealed that the CF score was predominantly higher in endothelial cells and fibroblast cells.

CONCLUSIONS

Two CF-related subtypes with distinct prognosis and TME were identified in KIRC. FUT8 exhibited elevated expression in KIRC samples.

Disulfidptosis status influences prognosis and therapeutic response in clear cell renal cell carcinoma

Disulfidptosis is a recently identified type of programmed cell death. It is characterized by aberrant accumulation of intracellular disulfides. The clinical implications of disulfidptosis in clear cell renal cell carcinoma (ccRCC) remain unclear. A series of bioinformatics approaches were employed to analyze ten disulfidptosis-related molecules. Firstly, the expression patterns of the disulfidptosis-related molecules were different between normal and ccRCC tissues. A comprehensive cohort of patients with ccRCC was then assembled from three public databases and subjected to cluster analysis based on disulfidptosis-related molecules. Consensus cluster analysis revealed three distinct disulfidptosis clusters. We then conducted weighted gene co-expression network analysis (WGCNA) to identify highly correlated genes. 267 hub genes were screened out through WGCNA, and three gene clusters were then determined. Finally, we identified 87 genes with prognostic value and then used them to develop a disulfidptosis scoring (DSscore) system, which was proven to independently predict survival in ccRCC. Patients in the high-DSscore group exhibited a significant survival advantage and better immunotherapeutic responses compared with those in the low-DSscore group. However, the patients in the low-DSscore group exhibited a greater degree of chemotherapeutic response. In addition, the expression of disulfidptosis-related molecules was validated by qRT-PCR, and the potential of disulfidptosis-related molecules to indicate distinct cell subtypes were validated by single-cell RNA-sequencing. In conclusion, DSscore is a promising index for predicting the prognosis and efficacy of immunotherapy in patients with ccRCC and may provide a basis for novel strategies for future studies.

Comprehensive analysis of the role of cuproptosis-related genes in the prognosis and immune infiltration of adrenocortical Carcinoma

Background

Cuproptosis is a recently discovered form of nonapoptotic programmed cell death. However, no research on cuproptosis in the context of adrenocortical carcinoma has been conducted, and the prognostic value of assessing cuproptosis remains unclear.

Methods

In this study, we established comprehensive models to assess gene expression changes, mutation status, and prognosis prediction and developed a prognostic nomogram for cuproptosis-related genes. Using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Genotype-Tissue Expression (GTEx) databases, an analysis of 11 cuproptosis-related genes was performed. Additionally, a risk scoring method and nomogram were used to assess the relationships among cuproptosis-associated genes, transcript expression, clinical characteristics, and prognosis. The connections among tumors, immune checkpoints, and immune infiltration were also analyzed.

Results

The patterns observed in patients with adrenocortical carcinoma who were assessed using cuproptosis-associated risk scores provide useful information for understanding gene mutations, clinical outcomes, immune cell infiltration, and immune checkpoint analysis results. FDX1, LIPT1, MTF1, COX11, CYP2D6, DLAT, ATP7Band CDKN2A were differentially expressed in patients with adrenocortical carcinoma and normal controls. In addition, higher risk scores were significantly associated with poor overall survival and progression-free interval. The nomogram model subsequently developed to facilitate the clinical application of the analysis showed good predictive and calibration capabilities. GSE10927 and GSE33371 were used for independent cohort validation. Moreover, CDKN2A, FDX1, and other cuproptosis-related genes were significantly associated with immune infiltration and checkpoints.

Conclusion

We confirmed that our model had excellent predictive ability in patients with adrenocortical carcinoma. Therefore, an in-depth evaluation of patients using cuproptosis-related risk scores is clinically essential and can assist in therapy in the future.

Bioinformatic Analysis and Clinical Case Studies Identify CD276 as a Promising Diagnostic Biomarker for Clear Cell Renal Cell Carcinoma

OBJECTIVE

This study aimed to explore the relationship between CD276 and clear cell renal carcinoma (ccRCC) and assess the diagnostic value of CD276 in ccRCC.

METHODS

Expression levels of CD276 in ccRCC and para-cancer tissues were compared and analyzed retrospectively using data obtained from TCGA and GEO databases. The clinical data was analyzed prospectively. Immunohistochemistry and RT-PCR analyses were used to analyze the expression of CD276 at the mRNA and protein levels. These analyses compared the expression between ccRCC tissues and para-cancer tissues obtained from 70 patients with ccRCC. Next, ELISA was used to analyze peripheral blood samples from 70 patients with ccRCC and 72 healthy individuals, facilitating the differentiation of ccRCC patients from normal controls. Finally, we utilized the Kaplan-Meier method to generate ROC curves for assessing the diagnostic value of CD276 for ccRCC.

RESULTS

Analysis of TCGA and GEO data revealed that the mRNA expression of CD276 was higher in ccRCC tissues than in para-cancer tissues (P < .05). Clinical validation using IHC and RT-PCR confirmed that the expression of CD276 was higher in ccRCC tissues than in para-cancer tissues, both at the mRNA and protein levels (P < .05). ELISA demonstrated that the expression of CD276 was higher in ccRCC patients than in normal individuals, and patients with a higher pathological grade showed higher expression of CD276 in the peripheral blood than those with a lower pathological grade (P < .05). ROC curves drawn from the above three datasets demonstrated that CD276 had a high diagnostic value for ccRCC (AUC = .894, .795, .938, respectively).

CONCLUSION

The expression of CD276 was higher in ccRCC tissues and positively associated with the pathological grade. Therefore, CD276 may serve as a molecular biomarker for ccRCC prediction.

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

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

Characterization of tumor microenvironment and sensitive chemotherapy drugs based on cuproptosis-related signatures in renal cell carcinoma

Cuproptosis is a novel type of copper-induced cell death and is considered as a new therapeutic target for many cancers. Distant metastases occur in about 40% of patients with advanced renal cell carcinoma (RCC), with a poor 5-year prognosis of about 10%. Through a series of comprehensive analyses, four differentially expressed cuproptosis-related lncRNAs (DECRLs) were identified as candidate biomarkers for RCC. The risk model constructed by using these four DECRLs can better predict the prognosis of patients with RCC, which is determined by the receiver operating characteristic (Time dependent area under curve value at 1-year, 3-year, 5-year, and 10-year were 0.82, 0.80, 0.76, and 0.73 respectively). There were significant differences in immune status between high-risk and low-risk RCC patients. The differentially expressed gene enrichment terms between high- and low-risk patients was also dominated by immune-related terms. The risk score was also correlated with immunotherapy as measured by the tumor immune dysfunction and exclusion (TIDE) score. In addition, we also found that the sensitivity of many chemotherapy drugs varies widely between high- and low-risk patients. The sensitivity of the three chemotherapy drugs (AZD4547, Vincristine, and WEHI-539) varied among high- and low-risk patients, and was significantly negatively correlated with risk values, suggesting that they could be used as clinical treatment drugs for RCC. Our study not only obtained four potential biomarkers, but also provided guidance for immunotherapy and chemotherapy treatment of RCC, as well as new research strategies for the screening of other cancer biomarkers and sensitive drugs.

Deciphering key genes involved in cisplatin resistance in kidney renal clear cell carcinoma through a combined in silico and in vitro approach

The low survival rate of Kidney renal clear cell carcinoma (KIRC) patients is largely attributed to cisplatin resistance. Rather than focusing solely on individual proteins, exploring protein-protein interactions could offer greater insight into drug resistance. To this end, a series of in silico and in vitro experiments were conducted to identify hub genes in the intricate network of cisplatin resistance-related genes in KIRC chemotherapy. The genes involved in cisplatin resistance across KIRC were retrieved from the National Center for Biotechnology Information (NCBI) database using search terms as "Kidney renal clear cell carcinoma" and "Cisplatin resistance". The genes retrieved were analyzed for hub gene identification using the STRING database and Cytoscape tool. Expression and promoter methylation profiling of the hub genes was done using UALCAN, GEPIA, OncoDB, and HPA databases. Mutational, survival, functional enrichment, immune cell infiltration, and drug prediction analyses of the hub genes were performed using the cBioPortal, GEPIA, GSEA, TIMER, and DrugBank databases. Lastly, expression and methylation levels of the hub genes were validated on two cisplatin-resistant RCC cell lines (786-O and A-498) and a normal renal tubular epithelial cell line (HK-2) using two high throughput techniques, including targeted bisulfite sequencing (bisulfite-seq) and RT-qPCR. A total of 124 genes were identified as being associated with cisplatin resistance in KIRC. Out of these genes, MCL1, IGF1R, CCND1, and PTEN were identified as hub genes and were found to have significant (p < 0.05) variations in their mRNA and protein expressions and effects on the overall survival (OS) of the KIRC patients. Moreover, an aberrant promoter methylation pattern was found to be associated with the dysregulation of the hub genes. In addition to this, hub genes were also linked with different cisplatin resistance-causing pathways. Thus, hub genes can be targeted with Alvocidib, Estradiol, Tretinoin, Capsaicin, Dronabinol, Metribolone, Calcitriol, Acetaminophen, Acitretin, Cyclosporine, Azacitidine, Genistein, and Resveratrol drugs. As the pathogenesis of KIRC is complex, targeting hub genes and associated pathways involved in cisplatin resistance could bring a milestone change in the drug discovery and management of drug resistance, which might uplift overall survival among KIRC patients.

In vitro analysis of PI3K pathway activation genes for exploring novel biomarkers and therapeutic targets in clear cell renal carcinoma

OBJECTIVES

The regulation of various cellular functions such as growth, proliferation, metabolism, and angiogenesis, is dependent on the PI3K pathway. Recent evidence has indicated that kidney renal clear cell carcinoma (KIRC) can be triggered by the deregulation of this pathway. The objective of this research was to investigate 25 genes associated with activation of the PI3K pathway in KIRC and control samples to identify four hub genes that might serve as novel molecular biomarkers and therapeutic targets for treating KIRC.

METHODS

Multi-omics in silico and in vitro analysis was employed to find hub genes related to the PI3K pathway that may be biomarkers and therapeutic targets for KIRC.

RESULTS

Using STRING software, a protein-protein interaction (PPI) network of 25 PI3K pathway-related genes was developed. Based on the degree scoring method, the top four hub genes were identified using Cytoscape's Cytohubba plug-in. TCGA datasets, KIRC (786-O and A-498), and normal (HK2) cells were used to validate the expression of hub genes. Additionally, further bioinformatic analyses were performed to investigate the mechanisms by which hub genes are involved in the development of KIRC. Out of a total of 25 PI3K pathway-related genes, we developed and validated a diagnostic and prognostic model based on the up-regulation of TP53 (tumor protein 53) and CCND1 (Cyclin D1) and the down-regulation of PTEN (Phosphatase and TENsin homolog deleted on chromosome 10), and GSK3B (Glycogen synthase kinase-3 beta) hub genes. The hub genes included in our model may be a novel therapeutic target for KIRC treatment. Additionally, associations between hub genes and infiltration of immune cells can enhance comprehension of immunotherapy for KIRC.

CONCLUSION

We have created a new diagnostic and prognostic model for KIRC patients that uses PI3K pathway-related hub genes (TP53, PTEN, CCND1, and GSK3B). Nevertheless, further experimental studies are required to ascertain the efficacy of our model.

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.

Comprehensive analysis identifies cuproptosis-related gene DLAT as a potential prognostic and immunological biomarker in pancreatic adenocarcinoma

BACKGROUND

Cuproptosis is a regulated cell death form associated with tumor progression, clinical outcomes, and immune response. However, the role of cuproptosis in pancreatic adenocarcinoma (PAAD) remains unclear. This study aims to investigate the implications of cuproptosis-related genes (CRGs) in PAAD by integrated bioinformatic methods and clinical validation.

METHODS

Gene expression data and clinical information were downloaded from UCSC Xena platform. We analyzed the expression, mutation, methylation, and correlations of CRGs in PAAD. Then, based on the expression profiles of CRGs, patients were divided into 3 groups by consensus clustering algorithm. Dihydrolipoamide acetyltransferase (DLAT) was chosen for further exploration, including prognostic analysis, co-expression analysis, functional enrichment analysis, and immune landscape analysis. The DLAT-based risk model was established by Cox and LASSO regression analysis in the training cohort, and then verified in the validation cohort. Quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays were performed to examine the expression levels of DLAT in vitro and in vivo, respectively.

RESULTS

Most CRGs were highly expressed in PAAD. Among these genes, increased DLAT could serve as an independent risk factor for survival. Co-expression network and functional enrichment analysis indicated that DLAT was engaged in multiple tumor-related pathways. Moreover, DLAT expression was positively correlated with diverse immunological characteristics, such as immune cell infiltration, cancer-immunity cycle, immunotherapy-predicted pathways, and inhibitory immune checkpoints. Submap analysis demonstrated that DLAT-high patients were more responsive to immunotherapeutic agents. Notably, the DLAT-based risk score model possessed high accuracy in predicting prognosis. Finally, the upregulated expression of DLAT was verified by RT-qPCR and IHC assays.

CONCLUSIONS

We developed a DLAT-based model to predict patients' clinical outcomes and demonstrated that DLAT was a promising prognostic and immunological biomarker in PAAD, thereby providing a new possibility for tumor therapy.

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.

Identification and development of a novel risk model based on cuproptosis-associated RNA methylation regulators for predicting prognosis and characterizing immune status in hepatocellular carcinoma

BACKGROUND

Cuproptosis, a novel cell death caused by excess copper, is quite obscure in hepatocellular carcinoma (HCC) and needs more investigation.

METHODS

RNA-seq and clinical data of HCC patients TCGA database were analyzed to establish a predictive model through LASSO Cox regression analysis. External dataset ICGC was used for the verification. GSEA and CIBERSORT were applied to investigate the molecular mechanisms and immune microenvironment of HCC. Cuproptosis induced by elesclomol was confirmed via various in vitro experiments. The expression of prognostic genes was verified in HCC tissues using qRT-PCR analysis.

RESULTS

Initially, 18 cuproptosis-associated RNA methylation regulators (CARMRs) were selected for prognostic analysis. A nine-gene signature was created by applying the LASSO Cox regression method. Survival and ROC assays were carried out to validate the model using TCGA and ICGC database. Moreover, there exhibited obvious differences in drug sensitivity in terms of common drugs. A higher tumor mutation burden was shown in the high-risk group. Additionally, significant discrepancies were found between the two groups in metabolic pathways and RNA processing via GSEA analysis. Meanwhile, CIBERSORT analysis indicated different infiltrating levels of various immune cells between the two groups. Elesclomol treatment caused a unique form of programmed cell death accompanied by loss of lipoylated mitochondrial proteins and Fe-S cluster protein. The results of qRT-PCR indicated that most prognostic genes were differentially expressed in the HCC tissues.

CONCLUSION

Overall, our predictive signature displayed potential value in the prediction of overall survival of HCC patients and might provide valuable clues for personalized therapies.

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-Related MiR-21-5p/FDX1 Axis in Clear Cell Renal Cell Carcinoma and Its Potential Impact on Tumor Microenvironment

As a newly identified type of programmed cell death, cuproptosis may have an impact on cancer development, including clear cell renal cell carcinoma (ccRCC). Herein, we first noticed that the expression levels of cuproptosis regulators exhibited a tight correlation with the clinicopathological characteristics of ccRCC. The cuproptosis-sensitive sub-type (CSS), classified via consensus clustering analysis, harbored a higher overall survival rate compared to the cuproptosis-resistant sub-type (CRS), which may have resulted from the differential infiltration of immune cells. FDX1, the cuproptosis master regulator, was experimentally determined as a tumor suppressor in ccRCC cells by suppressing the cell growth and cell invasion of ACHN and OSRC-2 cells in a cuproptosis-dependent and -independent manner. The results from IHC staining also demonstrated that FDX1 expression was negatively correlated with ccRCC tumor initiation and progression. Furthermore, we identified the miR-21-5p/FDX1 axis in ccRCC and experimentally verified that miR-21-5p directly binds the 3'-UTR of FDX1 to mediate its degradation. Consequently, a miR-21-5p inhibitor suppressed the cell growth and cell invasion of ACHN and OSRC-2 cells, which could be compensated by FDX1 knockdown, reinforcing the functional linkage between miR-21-5p and FDX1 in ccRCC. Finally, we evaluated the ccRCC tumor microenvironment under the miR-21-5p/FDX1 axis and noted that this axis was strongly associated with the infiltration of immune cells such as CD4⁺ T cells, Treg cells, and macrophages, suggesting that this signaling axis may alter microenvironmental components to drive ccRCC progression. Overall, this study constructed the miR-21-5p/FDX1 axis in ccRCC and analyzed its potential impact on the tumor microenvironment, providing valuable insights to improve current ccRCC management.

A new thinking: deciphering the aberrance and clinical implication of copper-death signatures in clear cell renal cell carcinoma

RATIONALE

Recent research has indicated that cuprotosis, or copper induced cell death, is a novel type of cell death that could be utilized as a new weapon for cancer management. However, the characteristics and implications of such signatures in cancers, especially in clear cell renal cell cancer (ccRCC), remain elusive.

METHODS

Expression, methylation, mutation, clinical information, copy number variation, functional implication, and drug sensitivity data at the pan-cancer level were collected from The Cancer Genome Atlas. An unsupervised clustering algorithm was applied to decipher ccRCC heterogeneity. Immune microenvironment construction, immune therapy response, metabolic pattern, and cancer progression signature between subgroups were also investigated.

RESULTS

Cuprotosis related genes were specifically downregulated in various cancer tissues compared with normal tissues and were correlated with hypermethylation and copy number variation. Cuprotosis scores were also dysregulated in tumor tissues, and we found that such a signature could positively regulate oxidative phosphorylation and Myc and negatively regulate epithelial mesenchymal translation and myogenesis pathways. CPCS1 (cuprotosis scores high) and CPCS2 (cuprotosis scores low) in ccRCC displayed distinctive clinical profiles and biological characteristics; the CPCS2 subtype had a higher clinical stage and a worse prognosis and might positively regulate cornification and epidermal cell differentiation to fuel cancer progression. CPCS2 also displayed a higher tumor mutation burden and low tumor stemness index, while it led to a low ICI therapy response and dysfunctional tumor immunity state. The genome-copy numbers of CPCS2, including arm- gain and arm- loss, were higher than those of CPCS1. The prognostic model constructed based on subgroup biomarkers exerted satisfactory performance in both the training and validation cohorts. In addition, overexpression of the copper death activator DLAT suppressed the malignant ability, including cell migration and proliferation, of renal cell lines in vitro and in vivo. Finally, activation of cuprotosis in tumors could enhance antitumor immunity through dsDNA-cGAS-STING signaling in ccRCC.

CONCLUSION

The activation of cuprotosis might function as a promising approach among multiple cancers. The cuprotosis related signatures could reshape tumor immunity in the ccRCC microenvironment via cGAS-STING signal, thus activating tumor antigen-presenting process. Upregulation of DLAT expression in ccRCC cell lines could reactivate the copper death pattern and be treated as a suitable target for ccRCC.

Neutrophil extracellular traps-associated modification patterns depict the tumor microenvironment, precision immunotherapy, and prognosis of clear cell renal cell carcinoma

Background

Neutrophil extracellular traps (NETs) are web-like structures formed by neutrophils, and their main function is antimicrobial defense. Moreover, NETs have numerous roles in the pathogenesis and progression of cancers. However, the potential roles of NET-related genes in renal cell carcinoma remain unclear. In this study, we comprehensively investigated the NETs patterns and their relationships with tumor environment (TME), clinicopathological features, prognosis, and prediction of therapeutic benefits in the clear cell renal cell carcinoma (ccRCC) cohort.

Methods

We obtained the gene expression profiles, clinical characteristics, and somatic mutations of patients with ccRCC from The Cancer Genome Atlas database (TCGA), Gene Expression Omnibus (GEO), and ArrayExpress datasets, respectively. ConsensusCluster was performed to identify the NET clusters. The tumor environment scores were evaluated by the "ESTIMATE," "CIBERSORT," and ssGSEA methods. The differential analysis was performed by the "limma" R package. The NET-scores were constructed based on the differentially expressed genes (DEGs) among the three cluster patterns using the ssGSEA method. The roles of NET scores in the prediction of immunotherapy were investigated by Immunophenoscores (TCIA database) and validated in two independent cohorts (GSE135222 and IMvigor210). The prediction of targeted drug benefits was implemented using the "pRRophetic" and Gene Set Cancer Analysis (GSCA) datasets. Real-time quantitative reverse transcription polymerase chain reaction (RT-PCR) was performed to identify the reliability of the core genes' expression in kidney cancer cells.

Results

Three NET-related clusters were identified in the ccRCC cohort. The patients in Cluster A had more metabolism-associated pathways and better overall survival outcomes, whereas the patients in Cluster C had more immune-related pathways, a higher immune score, and a poorer prognosis than those in Cluster B. Based on the DEGs among different subtypes, patients with ccRCC were divided into two gene clusters. These gene clusters demonstrated significantly different immune statuses and clinical features. The NET scores were calculated based on the ten core genes by the Gene Set Variation Analysis (GSVA) package and then divided ccRCC patients into two risk groups. We observed that high NET scores were associated with favorable survival outcomes, which were validated in the E-MTAB-1980 dataset. Moreover, the NET scores were significantly associated with immune cell infiltration, targeted drug response, and immunotherapy benefits. Subsequently, we explored the expression profiles, methylation, mutation, and survival prediction of the 10 core genes in TCGA-KIRC. Though all of them were associated with survival information, only four out of the 10 core genes were differentially expressed genes in tumor samples compared to normal tissues. Finally, RT-PCR showed that MAP7, SLC16A12, and SLC27A2 decreased, while SLC3A1 increased, in cancer cells.

Conclusion

NETs play significant roles in the tumor immune microenvironment of ccRCC. Identifying NET clusters and scores could enhance our understanding of the heterogeneity of ccRCC, thus providing novel insights for precise individual treatment.

Prognostic value and immunological characteristics of a novel cuproptosis-related long noncoding RNAs risk signature in kidney renal clear cell carcinoma

Background: Cuproptosis has been found as a novel cell death mode significantly associated with mitochondrial metabolism, which may be significantly associated with the occurrence and growth of tumors. LncRNAs take on critical significance in regulating the development of kidney renal clear cell carcinoma (KIRC), whereas the correlation between cuproptosis-related LncRNAs (CRLs) and KIRC is not clear at present. Therefore, this study built a prognosis signature based on CRLs, which can achieve accurate prediction of the outcome of KIRC patients. Methods: The TCGA database provided the expression profile information and relevant clinical information of KIRC patients. Univariate Cox, Lasso, and multivariate Cox were employed for building a risk signature based on CRLs. Kaplan-Meier (K-M) survival analysis and time-dependent receiver operating characteristic (ROC) curve were employed for the verification and evaluation of the reliability and accuracy of risk signature. Then, qRT-PCR analysis of risk LncRNAs was conducted. Finally, the possible effect of the developed risk signature on the microenvironment for tumor immunization was speculated in accordance with ssGSEA and ESTIMATE algorithms. Results: A prognosis signature composed of APCDD1L-DT, MINCR, AL161782.1, and AC026401.3 was built based on CRLs. As revealed by the results of the K-M survival study, the OS rate and progression-free survival rate of highrisk KIRC patients were lower than those of lowrisk KIRC patients, and the areas under ROC curves of 1, 3, and 5 years were 0.828, 0.780, and 0.794, separately. The results of the immune analysis showed that there were significant differences in the status of immunization and the microenvironment of tumor between groups at low-risk and at high-risk. The qRT-PCR results showed that the relative expression level of MINCR and APCDD1L-DT were higher in 786-O and 769-P tumor cells than in HK-2 cells, which were normal renal tubular epithelial cells. Conclusion: The developed risk signature takes on critical significance in the prediction of the prognosis of patients with KIRC, and it can bring a novel direction for immunotherapy and clinical drug treatment of KIRC. In addition, 4 identified risk LncRNAs (especially APCDD1L-DT and MINCR) can be novel targets for immunotherapy of KIRC patients.