ArticleFrontiers in oncology2021
Identification of an m6A-Related lncRNA Signature for Predicting the Prognosis in Patients With Kidney Renal Clear Cell Carcinoma.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed.
- The versatile roles of long non-coding RNAs in kidney disease.Nature reviews. Nephrology · 2026Review
- Establishment of a Prognostic Necroptosis-Related lncRNA Signature in Ovarian Cancer.Combinatorial chemistry & high throughput screening · 2026Article
- Article
- Study of an N6-methyladenosine- and ferroptosis-related prognostic model and the mechanisms underlying the molecular network in neuroblastoma based on multiple datasets.Discover oncology · 2025Article
- Correlation study of LINC02609 and SNHG17 as prognostic biomarkers of kidney renal clear cell carcinoma and therapeutic sensitivity based on public data andFrontiers in immunology · 2025Article
- Development and validation of a prognostic model based on m6A-related lncRNAs to predict prognosis for papillary renal cell cancer patients.Scientific reports · 2024Article
- Disulfidptosis-associated LncRNA signature predicts prognosis and immune response in kidney renal clear cell carcinoma.Biology direct · 2024Article
- Comprehensive Analysis for Predicting Prognoses and Immune Responses of m6A-Related lncRNAs in Women with Lung Adenocarcinoma.Biochemical genetics · 2024Article
- Comprehensive landscape of m6A regulator-related gene patterns and tumor microenvironment infiltration characterization in gastric cancer.Scientific reports · 2024Article
- Basement membrane-related lncRNA signature for the prognosis of hepatocellular carcinoma.Heliyon · 2024Article
- Machine Learning Gene Signature to Metastatic ccRCC Based on ceRNA Network.International journal of molecular sciences · 2024Article
- Cuproptosis gene-related, neural network-based prognosis prediction and drug-target prediction for KIRC.Cancer medicine · 2024Article
- LncRNA AGAP2 antisense RNA 1 stabilized by insulin-like growth factor 2 mRNA binding protein 3 promotes macrophage M2 polarization in clear cell renal cell carcinoma through regulation of the microRNA-9-5p/THBS2/PI3K-Akt pathway.Cancer cell international · 2023Article
- N6-methyladenosine methylation in kidney injury.Clinical epigenetics · 2023Review
- Article
- A novel oxidative-stress related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma.Scientific reports · 2023Article
- SERPINE1 and its co-expressed genes are associated with the progression of clear cell renal cell carcinoma.BMC urology · 2023Article
- The integrated comprehension of lncRNA HOXA-AS3 implication on human diseases.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022Review
- Clinical significance and immune landscape of cuproptosis-related lncRNAs in kidney renal clear cell carcinoma: a bioinformatical analysis.Annals of translational medicine · 2022Article
- LTBP2 inhibits prostate cancer progression and metastasis via the PI3K/AKT signaling pathway.Experimental and therapeutic medicine · 2022Article
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Authors and funding
10 authors.
Funding
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Abstract
purposeThis study aimed to construct an m6A-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using data obtained from The Cancer Genome Atlas (TCGA) database.
methodsThe KIRC patient data were downloaded from TCGA database and m6A-related genes were obtained from published articles. Pearson correlation analysis was implemented to identify m6A-related lncRNAs. Univariate, Lasso, and multivariate Cox regression analyses were used to identifying prognostic risk-associated lncRNAs. Five lncRNAs were identified and used to construct a prognostic signature in training set. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were applied to evaluate reliability and sensitivity of the signature in testing set and overall set, respectively. A prognostic nomogram was established to predict the probable 1-, 3-, and 5-year overall survival of KIRC patients quantitatively. GSEA was performed to explore the potential biological processes and cellular pathways. Besides, the lncRNA/miRNA/mRNA ceRNA network and PPI network were constructed based on weighted gene co-expression network analysis (WGCNA). Functional Enrichment Analysis was used to identify the biological functions of m6A-related lncRNAs.
resultsWe constructed and verified an m6A-related lncRNAs prognostic signature of KIRC patients in TCGA database. We confirmed that the survival rates of KIRC patients with high-risk subgroup were significantly poorer than those with low-risk subgroup in the training set and testing set. ROC curves indicated that the prognostic signature had a reliable predictive capability in the training set (AUC = 0.802) and testing set (AUC = 0.725), respectively. Also, we established a prognostic nomogram with a high C-index and accomplished good prediction accuracy. The lncRNA/miRNA/mRNA ceRNA network and PPI network, as well as functional enrichment analysis provided us with new ways to search for potential biological functions.
conclusionsWe constructed an m6A-related lncRNAs prognostic signature which could accurately predict the prognosis of KIRC patients.
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