Dataset Information

Identification of a ferroptosis-related lncRNA signature with prognosis for Wilms tumor.

ABSTRACT:

Background

Wilms tumor (WT) is a widespread urologic tumor in children. Ferroptosis, on the other hand, is a novel form of cell death associated with tumor development. In this study, we aim to explore the predictability of ferroptosis-related biomarkers in estimating prognosis in WT patients.

Methods

To determine a link between ferroptosis-related gene expression and WT prognosis, we first collected RNA sequencing data and clinical information, involving 124 WT and 6 healthy tissue samples, from the TARGET database. Next, we screened the collected information for ferroptosis-related long non-coding RNA using Cox regression analysis, and constructed a signature model, as well as a nomogram, related to prognosis. Finally, we explored a potential link between ferroptosis-related lncRNA and tumor immunity and screened for possible immune checkpoints.

Results

We constructed a WT prognosis prediction signature containing 12 ferroptosis-related lncRNAs. The area under the curves values, from the ROC curves, predicting overall survival rates at the 1, 3-, and 5-year timepoints were 0.775, 0.867, and 0.891 respectively. Moreover, we generated a nomogram, using clinical features and risk scores, carrying a C-index value of 0.836, which suggested a high predictive value. We also demonstrated significant differences in tumor immunity between low- and high-risk WT patients, particularly in the presence of B cells, NK cells, Th1 cells, Treg cells, inflammation promoting, and type I and II IFN responses. In addition, we showed that immune checkpoints like SIRPA, ICOSLG, LAG3, PVRIG, NECTIN1, and SIRPB2 can serve as potential therapeutic targets for WT.

Conclusions

Based on our analyses, we generated a ferroptosis-related lncRNA signature that can both estimate prognosis of WT patients and may provide basis for future WT therapy.

SUBMITTER: Liu H

PROVIDER: S-EPMC8578763 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Publications

Identification of a ferroptosis-related lncRNA signature with prognosis for Wilms tumor.

Liu Hengchen H Zhang Mingzhao M Zhang Tingting T Shi Manyu M Lu Wenjun W Yang Shulong S Cui Qingbo Q Li Zhaozhu Z

Translational pediatrics 20211001 10

<h4>Background</h4>Wilms tumor (WT) is a widespread urologic tumor in children. Ferroptosis, on the other hand, is a novel form of cell death associated with tumor development. In this study, we aim to explore the predictability of ferroptosis-related biomarkers in estimating prognosis in WT patients.<h4>Methods</h4>To determine a link between ferroptosis-related gene expression and WT prognosis, we first collected RNA sequencing data and clinical information, involving 124 WT and 6 healthy tiss ...[more]

PMID: 34765465

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Project description:BackgroundFerroptosis is an iron-dependent form of cell death. In this study, we identified ferroptosis-related long noncoding RNAs (FRlncRNAs) to investigate their association with hepatocellular carcinoma (HCC) in prognosis, tumor immune environment, and genome instability.MethodsTranscriptome profile data of HCC were retrieved from a public database. FRlncRNAs were identified by co-expression analysis. Patients were randomly divided into training and test cohorts. Univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were performed to construct a risk model. Patients were divided into high- and low-risk groups based on the risk model. AUC and C index were used to assess the risk model. Survival analysis, immune status, and genome instability were compared between the two groups.ResultsSixteen FRlncRNAs were identified and used to construct an FRlncRNA signature for the risk model. The Kaplan-Meier analysis revealed that patients in the high-risk group had poorer overall survival than patients in the low-risk group. The area under curve of the risk model was 0.879, 0.809, and 0.757 in the training cohort and 0.635, 0.688, and 0.739 in the test cohort at 1, 2, and 3 years, respectively. The risk model was an independent prognostic predictor and showed excellent prediction of prognosis compared with clinicopathological features. For the differentially expressed ferroptosis-related genes, many enriched metabolic pathways were identified in the functional enrichment analysis. Immune cells such as CD8+ T cells, macrophages M1, natural killer cells, and B cells, which may be associated with antitumor immune responses, differed between the high- and low-risk groups. Genome instability based on the risk model was also explored. A total of 61 genes were differently mutated between the two risk groups, and among them, TP53, HECW2, TRIM66, MCTP2, and KIAA1551 had the most significant mutation frequency differences.ConclusionThe FRlncRNA signature is closely related with overall survival, tumor immune environment, and genome instability in HCC.

Project description:PurposeFerroptosis-related lncRNAs are promising biomarkers for predicting the prognosis of many cancers. However, a ferroptosis-related signature to predict the prognosis of cutaneous melanoma (CM) has not been identified. The purpose of this study was to construct a ferroptosis-related lncRNA signature to predict prognosis and immunotherapy efficacy in CM.MethodsFerroptosis-related differentially expressed genes (FDEGs) and lncRNAs (FDELs) were identified using TCGA, GTEx, and FerrDb datasets. We performed Cox and LASSO regressions to identify key FDELs, and constructed a risk score to stratify patients into high- and low-risk groups. The lncRNA signature was evaluated using the areas under the receiver operating characteristic curves (AUCs) and Kaplan-Meier analyses in the training, testing, and entire cohorts. Multivariate Cox regression analyses including the lncRNA signature and common clinicopathological characteristics were performed to identify independent predictors of overall survival (OS). A nomogram was developed for clinical use. We performed gene set enrichment analyses (GSEA) to identify significantly enriched pathways. Differences in the tumor microenvironment (TME) between the 2 groups were assessed using 7 algorithms. To predict the efficacy of immune checkpoint inhibitors (ICI), we analyzed the association between PD1 and CTLA4 expression and the risk score. Finally, differences in Tumor Mutational Burden (TMB) and molecular drugs Sensitivity between the 2 groups were performed.ResultsWe identified 5 lncRNAs (AATBC, AC145423.2, LINC01871, AC125807.2, and AC245041.1) to construct the risk score. The AUC of the lncRNA signature was 0.743 in the training cohort and was validated in the testing and entire cohorts. Kaplan-Meier analyses revealed that the high-risk group had poorer prognosis. Multivariate Cox regression showed that the lncRNA signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The 1-, 3-, and 5-year survival probabilities for CM patients were 92.7%, 57.2%, and 40.2% with an AUC of 0.804, indicating a good accuracy and reliability of the nomogram. GSEA showed that the high-risk group had lower ferroptosis and immune response. TME analyses confirmed that the high-risk group had lower immune cell infiltration (e.g., CD8+ T cells, CD4+ memory-activated T cells, and M1 macrophages) and lower immune functions (e.g., immune checkpoint activation). Low-risk patients whose disease expressed PD1 or CTLA4 were likely to respond better to ICIs. The analysis demonstrated that the TMB had significantly difference between low- and high- risk groups. Chemotherapy drugs, such as sorafenib, Imatinib, ABT.888 (Veliparib), Docetaxel, and Paclitaxel showed Significant differences in the estimated IC50 between the two risk groups.ConclusionOur novel ferroptosis-related lncRNA signature was able to accurately predict the prognosis and ICI outcomes of CM patients. These ferroptosis-related lncRNAs might be potential biomarkers and therapeutic targets for CM.

Project description:Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer in China and is closely associated with malignant biological characteristics and poor survival. Ferroptosis is a newly discovered iron-dependent mode of cell death that plays an important role in the biological behavior of ESCC cells. The clinical significance of ferroptosis-related long noncoding RNAs (FRLs) in ESCC remains unknown and warrants further research. The current study obtained RNA sequencing profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and FRLs were obtained through coexpression analysis. Consensus clustering was employed to divide the subjects into clusters, and immune-associated pathways were identified by functional analysis. The current study observed significant differences in the enrichment scores of immune cells among different clusters. Patients from TCGA-ESCC database were designated as the training cohort. A ten-FRL prediction signature was established using the least absolute shrinkage and selection operator Cox regression model and validated using the GEO cohort and our own independent validation database. Real-time quantitative polymerase chain reaction was used to verify the expression of the ten FRLs, and the ssGSEA analysis was employed to evaluate their function. In addition, the IMvigor database was used to assess the predictive value of the signature in terms of immunotherapeutic responses. Multivariate Cox and stratification analyses revealed that the ten-FRL signature was an independent predictor of the overall survival (OS). Patients with ESCC in the high-risk group displayed worse survival, a characteristic tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the risk model established in this study could serve as a promising predictor of prognosis and immunotherapeutic response in patients with ESCC.

Project description:Background: Ferroptosis is closely related to the occurrence and development of cancer. An increasing number of studies have induced ferroptosis as a treatment strategy for cancer. However, the predictive value of ferroptosis-related lncRNAs in bladder cancer (BC) still need to be further elucidated. The purpose of this study was to construct a predictive signature based on ferroptosis-related long noncoding RNAs (lncRNAs) to predict the prognosis of BC patients. Methods: We downloaded RNA-seq data and the corresponding clinical and prognostic data from The Cancer Genome Atlas (TCGA) database and performed univariate and multivariate Cox regression analyses to obtain ferroptosis-related lncRNAs to construct a predictive signature. The Kaplan-Meier method was used to analyze the overall survival (OS) rate of the high-risk and low-risk groups. Gene set enrichment analysis (GSEA) was performed to explore the functional differences between the high- and low-risk groups. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the predictive signature and immune status. Finally, the correlation between the predictive signature and the treatment response of BC patients was analyzed. Results: We constructed a signature composed of nine ferroptosis-related lncRNAs (AL031775.1, AL162586.1, AC034236.2, LINC01004, OCIAD1-AS1, AL136084.3, AP003352.1, Z84484.1, AC022150.2). Compared with the low-risk group, the high-risk group had a worse prognosis. The ferroptosis-related lncRNA signature could independently predict the prognosis of patients with BC. Compared with clinicopathological variables, the ferroptosis-related lncRNA signature has a higher diagnostic efficiency, and the area under the receiver operating characteristic curve was 0.707. When patients were stratified according to different clinicopathological variables, the OS of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the high-risk group. ssGSEA showed that the predictive signature was significantly related to the immune status of BC patients. High-risk patients were more sensitive to anti-PD-1/L1 immunotherapy and the conventional chemotherapy drugs sunitinib, paclitaxel, cisplatin, and docetaxel. Conclusion: The predictive signature can independently predict the prognosis of BC patients, provides a basis for the mechanism of ferroptosis-related lncRNAs in BC and provides clinical treatment guidance for patients with BC.

Dataset Information

Identification of a ferroptosis-related lncRNA signature with prognosis for Wilms tumor.

Background

Methods

Results

Conclusions

Publications

Identification of a ferroptosis-related lncRNA signature with prognosis for Wilms tumor.

Similar Datasets

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