Ferroptosis-associated lncRNA prognostic signature predicts prognosis and immune response in clear cell renal cell carcinoma

Disulfidptosis-Related LncRNA Signatures for Prognostic Prediction in Kidney Renal Clear Cell Carcinoma

INTRODUCTION BACKGROUND

Disulfidptosis is a prevalent apoptotic mechanism, intrinsically linked to cancer prognosis. However, the specific involvement of disulfidptosis-related long non-coding RNA (DRLncRNAs) in Kidney renal clear cell carcinoma (KIRC) remains incompletely understood. This study aims to elucidate the potential prognostic significance of disulfidptosis-related LncRNAs in KIRC.

MATERIALS AND METHODS

Expression profiles and clinical data of KIRC patients were retrieved from the TCGA database to discern differentially expressed DRLncRNAs correlated with overall survival. Cox univariate analysis, Lasso Regression, and Cox multivariate analysis were used to construct a clinical prediction model.

RESULTS

Six signatures, namely FAM83C.AS1, AC136475.2, AC121338.2, AC026401.3, AC254562.3, and AC000050.2, were established to evaluate overall survival (OS) in the context of Kidney renal clear cell carcinoma (KIRC) in this study. Survival analysis and ROC curves demonstrated the strong predictive performance of the associated signature. The nomogram exhibited accurate prognostic predictions for overall patient survival, offering substantial clinical utility. Gene set enrichment analysis revealed that risk signals were enriched in various immune-related pathways. Furthermore, the risk features exhibited significant correlations with immune cells, immune function, immune cell infiltration, and immune checkpoints.

CONCLUSION

This study has unveiled, for the first time, six disulfdptosis-related LncRNA signatures, laying a solid foundation for enhanced and precise prognostic predictions in KIRC.

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

Background: Tumor angiogenesis is closely related to the progression of clear cell renal cell carcinoma (ccRCC). Long non-coding RNAs (lncRNAs) regulating angiogenesis could be potential biomarkers for predicting ccRCC prognosis. With this study, we aimed to construct a prognostic model based on lncRNAs and explore its underlying mechanisms. Methods: RNA data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Angiogenesis-related genes (ARGs) were extracted from the Molecular Signatures database. Pearson correlation and LASSO and COX regression analyses were performed to identify survival-related AR-lncRNAs (sAR-lncRNAs) and construct a prognostic model. The predictive power of the prognostic model was verified according to Kaplan‒Meier curve, receiver operating characteristic (ROC) curve and nomogram analyses. The correlation between the prognostic model and clinicopathological characteristics was assessed via univariate and multivariate analyses. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was subsequently performed to elucidate the mechanisms of the sAR-lncRNAs. In vitro qPCR, immunohistochemistry, migration and invasion assays were conducted to confirm the angiogenic function of sAR-lncRNAs. Results: Three sAR-lncRNAs were used to construct a prognostic model. The model was moderately accurate in predicting 1- , 3- and 5-year ccRCC prognosis, and the risk score according to this model was closely related to clinicopathological characteristics such as T grade and T stage. A nomogram was constructed to precisely estimate the overall survival of ccRCC patients. KEGG enrichment analysis indicated that the MAPK and Notch pathways were highly enriched in high-risk patients. Additionally, we found that the expression of the lncRNAs AC005324.4 and AC104964.4 in the prognostic model was lower in ccRCC cell lines and cancer tissues than in the HK-2 cell line and paracancerous tissues, while the expression of the lncRNA AC087482.1 showed the opposite trend. In a coculture model, knockdown of lncRNA AC005324.4 and lncRNA AC104964.4 significantly promoted the migration and invasion of human umbilical vein endothelial cells (HUVECs), but siR-AC087482.1 transfection alleviated these effects. Conclusions: We constructed a prognostic model based on 3 sAR-lncRNAs and validated its value in clinicopathological characteristics and prognostic prediction of ccRCC patients, providing a new perspective for ccRCC treatment decision making.

Comprehensive Analysis of N6-Methylandenosine-Related lncRNAs in Clear Cell Renal Cell Carcinoma: A Correlation With Prognosis, Tumor Progression, and Therapeutic Response

This study aims to develop a prognostic signature based on m6A-related lncRNAs for clear cell renal cell carcinoma (ccRCC). Differential expression analysis and Pearson correlation analysis were used to identify m6A-related lncRNAs associated with patient outcomes in The Cancer Genome Atlas (TCGA) database. Our approach led to the development of an m6A-related lncRNA risk score (MRLrisk), formulated using six identified lncRNAs: NFE4, AL008729.2, AL139123.1, LINC02154, AC124854.1 and ARHGAP31-AS1. Higher MRLrisk was identified as a risk factor for patients' prognosis in ccRCC. Furthermore, an MRLrisk-based nomogram was developed and demonstrated as a reliable tool for prognosis prediction in ccRCC. Enrichment analysis and tumor mutation signature studies were conducted to investigate MRLrisk-related biological phenotypes. The tumor immune dysfunction and exclusion (TIDE) score was employed to infer patients' response to immunotherapy, indicating a negative correlation between high MRLrisk and immunotherapy response. Our focus then shifted to LINC02154 for deeper exploration. We assessed LINC02154 expression in 28 ccRCC/normal tissue pairs and 3 ccRCC cell lines through quantitative real-time polymerase chain reaction (qRT-PCR). Functional experiments, including EdU incorporation, flow cytometry and transwell assays, were performed to assess the role of LINC02154 in ccRCC cell functions, discovering that its downregulation hinders cancer cell proliferation and migration. Furthermore, the influence of LINC02154 on ccRCC cells' sensitivity to Sunitinib was explored using CCK-8 assays, demonstrating that decreased LINC02154 expression increases Sunitinib sensitivity. In summary, this study successfully developed an MRLrisk model with significant prognostic value for ccRCC and established LINC02154 as a critical biomarker and prospective therapeutic target in ccRCC management.

Ferroptosis and cuproptposis in kidney Diseases: dysfunction of cell metabolism

Metal ions play an important role in living organisms and are involved in essential physiological activities. However, the overload state of ions can cause excess free radicals, cell damage, and even cell death. Ferroptosis and cuproptosis are specific forms of cell death that are distinct from apoptosis, necroptosis, and other regulated cell death. These unique modalities of cell death, dependent on iron and copper, are regulated by multiple cellular metabolic pathways, including steady-state metal redox treatment mitochondrial activity of lipid, amino acid and glucose metabolism, and various signaling pathways associated with disease. Although the mechanisms of ferroptosis and cuproptosis are not yet fully understood, there is no doubt that ion overload plays a crucial act in these metal-dependent cell deaths. In this review, we discussed the core roles of ion overload in ferroptosis and cuproptosis, the association between metabolism imbalance and ferroptosis and cuproptosis, the extract the diseases caused by ion overload and current treatment modalities.

Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma

Disulfidptosis, a novel form of regulated cell death, occurs due to the aberrant accumulation of intracellular cystine and other disulfides. Moreover, targeting disulfidptosis could identify promising approaches for cancer treatment. Long non-coding RNAs (lncRNAs) are known to be critically implicated in clear cell renal cell carcinoma (ccRCC) development. Currently, the involvement of disulfidptosis-related lncRNAs in ccRCC is yet to be elucidated. This study primarily dealt with identifying and validating a disulfidptosis-related lncRNAs-based signature for predicting the prognosis and immune landscape of individuals with ccRCC. Clinical and RNA sequencing data of ccRCC samples were accessed from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted for the identification of the disulfidptosis-related lncRNAs. Additionally, univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator Cox regression, and stepwise multivariate Cox analysis were executed to develop a novel risk prognostic model. The prognosis-predictive capacity of the model was then assessed using an integrated method. Variation in biological function was noted using GO, KEGG, and GSEA. Additionally, immune cell infiltration, the tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores were calculated to investigate differences in the immune landscape. Finally, the expression of hub disulfidptosis-related lncRNAs was validated using qPCR. We established a novel signature comprised of eight lncRNAs that were associated with disulfidptosis (SPINT1-AS1, AL121944.1, AC131009.3, AC104088.3, AL035071.1, LINC00886, AL035587.2, and AC007743.1). Kaplan-Meier and receiver operating characteristic curves demonstrated the acceptable predictive potency of the model. The nomogram and C-index confirmed the strong correlation between the risk signature and clinical decision-making. Furthermore, immune cell infiltration analysis and ssGSEA revealed significantly different immune statuses among risk groups. TMB analysis revealed the link between the high-risk group and high TMB. It is worth noting that the cumulative effect of the patients belonging to the high-risk group and having elevated TMB led to decreased patient survival times. The high-risk group depicted greater TIDE scores in contrast with the low-risk group, indicating greater potential for immune escape. Finally, qPCR validated the hub disulfidptosis-related lncRNAs in cell lines. The established novel signature holds potential regarding the prognosis prediction of individuals with ccRCC as well as predicting their responses to immunotherapy.

Analysis of lncRNAs profiles associated with ferroptosis can predict prognosis and immune landscape and drug sensitivity in patients with clear cell renal cell carcinoma

Ferroptosis is a novel kind of iron- and reactive oxygen-induced cell death, investigation into ferroptosis-associated long noncoding RNAs (FALs) in clear cell renal cell carcinoma (ccRCC) is scarce. The goal of the research was to look at FALs' possible predictive significance, as well as their interaction with the immune microenvironment and therapeutic responsiveness of ccRCC. The Cancer Genome Atlas database was employed to retrieve RNA sequencing data from 530 individuals with ccRCC. Patients with ccRCC were randomly assigned to one of two groups: training or testing. Pearson's correlation analysis through the identified ferroptosis-related genes was implemented to screen for FALs. Finally, a FALs signature composed of eight lncRNAs was discovered for predicting survival outcomes in ccRCC patients. ccRCC patients in the training, testing, and overall cohorts were separated into low-risk and high-risk groups based on their risk score. The FALs signature was identified to be an independent factor for overall survival in the multivariate Cox analysis (hazard ratio = 1.013, 95% confidence interval = 1.008-1.018, p < 0.001). A clinically prognostic nomogram was created depending on the FALs signature and clinical characteristics. The nomogram provides greater clinical practicability and may reliably estimate patients' overall survival. The FALs signature may additionally precisely represent ccRCC's immunological environment, immunotherapy reaction, and drug sensitivity. The eight FALs and their signature provide precise and reliable methods for evaluating the clinical effects of in ccRCC patients, and they could be biological markers and targets for therapy.

Targeting ferroptosis in renal cell carcinoma: Potential mechanisms and novel therapeutics

Renal cell carcinoma (RCC) is an increasingly prevalent urologic malignancy that impacts human health worldwide. Surgery is an effective strategy for early RCC treatment, but advanced RCC is resistant to chemotherapy, thus development of other potential therapeutic strategies is urgent. Ferroptosis is a newly defined form of programmed cell death characterized by accumulation of iron-dependent lipid peroxides and plays a crucial role in the tumor progression and drug resistance. Recent studies have shown that ferroptosis participates in RCC progression and chemoresistance. Therefore, identifying the potential role of ferroptosis in RCC could develop novel therapeutic targets and clinical markers for this disease. This review concisely summarizes the regulatory role of iron, amino acid, and lipid metabolism in ferroptosis, as well as discusses the relationship between ferroptosis and RCC, and details the role of ferroptosis in tumor progression, which indicates that various ferroptosis regulators are dysregulated in RCC and exert paradoxical effects, either tumor-suppressive or oncogenic. These ferroptosis-related regulators are expected to be used as clinical markers for RCC prognosis. Thus, targeting these regulators to trigger ferroptosis may be the key to the development of potential therapeutic strategies for this disease.