ArticleiScience2021
Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Metabolic Messengers: Extracellular Vesicles as Central Mediators of Metabolic Reprogramming in Renal Cell Cancer.Biomedicines · 2026Review
- Sensitivity of renal cell carcinoma to cuproptosis: a bioinformatics analysis and experimental verification.Journal of Cancer · 2025Article
- Identifying Hub Genes and Metabolic Pathways in Collagen VI-Related Dystrophies: A Roadmap to Therapeutic Intervention.Biomolecules · 2024Article
- A pan-cancer analysis identifies SOAT1 as an immunological and prognostic biomarker.Oncology research · 2023Article
- The Modifying Effect of Obesity on the Association of Matrix Metalloproteinase Gene Polymorphisms with Breast Cancer Risk.Biomedicines · 2022Article
- Article
- Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.Frontiers in oncology · 2022Review
- Systems Biology Approaches to Decipher the Underlying Molecular Mechanisms of Glioblastoma Multiforme.International journal of molecular sciences · 2021Review
- Heterogeneity of Platelet Derived Growth Factor Pathway Gene Expression Profile Defines Three Distinct Subgroups of Renal Cell Carcinomas.Cancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
13 authors at 7 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common histological type of kidney cancer and has high heterogeneity. Stratification of ccRCC is important since distinct subtypes differ in prognosis and treatment. Here, we applied a systems biology approach to stratify ccRCC into three molecular subtypes with different mRNA expression patterns and prognosis of patients. Further, we developed a set of biomarkers that could robustly classify the patients into each of the three subtypes and predict the prognosis of patients. Then, we reconstructed subtype-specific metabolic models and performed essential gene analysis to identify the potential drug targets. We identified four drug targets, including
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.