ArticleMedical science monitor : international medical journal of experimental and clinical research2019
Identification of a 5-Gene Signature Predicting Progression and Prognosis of Clear Cell Renal Cell Carcinoma.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 44 citations in OpenAlex.
- ADCY4 promotes brain metastasis in small cell lung cancer and is associated with energy metabolism.Heliyon · 2024Article
- Integration of basement membrane-related genes in a risk signature for prognosis in clear cell renal cell carcinoma.Scientific reports · 2024Article
- A novel DNA methylation signature revealed GDF6 and RCC1 as potential prognostic biomarkers correlated with cell proliferation in clear cell renal cell carcinoma.Molecular biology reports · 2023Article
- Two-Dimensional-PAGE Coupled with nLC-MS/MS-Based Identification of Differentially Expressed Proteins and Tumorigenic Pathways in MCF7 Breast Cancer Cells Transfected for JTB Protein Silencing.Molecules (Basel, Switzerland) · 2023Article
- Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma.Biomedicines · 2023Article
- KRAB-ZFPs and cancer stem cells identity.Genes & diseases · 2023Review
- Identification and validation of a DNA methylation-driven gene-based prognostic model for clear cell renal cell carcinoma.BMC genomics · 2023Article
- Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia.BMC bioinformatics · 2023Article
- Expression of gasdermin D in clear cell renal cell carcinoma and its effect on its biological function.Frontiers in oncology · 2023Article
- Construction and validation of a prognostic model for kidney renal clear cell carcinoma based on podocyte-associated genes.Cancer medicine · 2022Article
- Article
- Weighted Gene Coexpression Network Analysis Identifies TBC1D10C as a New Prognostic Biomarker for Breast Cancer.Analytical cellular pathology (Amsterdam) · 2022Article
- Prognostic Role of the Ubiquitin Proteasome System in Clear Cell Renal Cell Carcinoma: A Bioinformatic Perspective.Journal of Cancer · 2021Article
- Profiles of overall survival-related gene expression-based risk signature and their prognostic implications in clear cell renal cell carcinoma.Bioscience reports · 2020Article
- A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma.Scientific reports · 2020Article
- Development and validation of an integrative methylation signature and nomogram for predicting survival in clear cell renal cell carcinoma.Translational andrology and urology · 2020Article
- Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis.Animal cells and systems · 2020Article
- Construction of a 13-Gene Signature as a Novel Prognostic Marker for Patients with Clear Cell Renal Cell Carcinoma and the Role of XCR1 in Cell Proliferation.Cancer management and research · 2020Article
- DNA Methylation-Based Panel Predicts Survival of Patients With Clear Cell Renal Cell Carcinoma and Its Correlations With Genomic Metrics and Tumor Immune Cell Infiltration.Frontiers in cell and developmental biology · 2020Article
- Development and validation of an immune prognostic classifier for clear cell renal cell carcinoma.Cancer biomarkers : section A of Disease markers · 2020Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Although the mortality rates of clear cell renal cell carcinoma (ccRCC) have decreased in recent years, the clinical outcome remains highly dependent on the individual patient. Therefore, identifying novel biomarkers for ccRCC patients is crucial. MATERIAL AND METHODS In this study, we obtained RNA sequencing data and clinical information from the TCGA database. Subsequently, we performed integrated bioinformatic analysis that includes differently expressed genes analysis, gene ontology and KEGG pathway analysis, protein-protein interaction analysis, and survival analysis. Moreover, univariate and multivariate Cox proportional hazards regression models were constructed. RESULTS As a result, we identified a total of 263 dysregulated genes that may participate in the metastasis of ccRCC, and established a predictive signature relying on the expression of OTX1, MATN4, PI3, ERVV-2, and NFE4, which could serve as significant progressive and prognostic biomarkers for ccRCC. CONCLUSIONS We identified differentially expressed genes that may be involved in the metastasis of ccRCC. Moreover, a predictive signature based on the expression of OTX1, MATN4, PI3, ERVV-2, and NFE4 could be an independent prognostic factor for ccRCC.
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