ArticleAging2020
Identification of potential novel differentially-expressed genes and their role in invasion and migration in renal cell carcinoma.
Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Machine learning-derived mast cell-associated angiogenesis features can serve as prognostic targets for clear cell renal cell carcinoma.Translational andrology and urology · 2026Article
- Integrative Transcriptomic Analysis Identifies Hypoxia-responsive Cell Cycle Hub Genes as Prognostic Markers in Glioblastoma.Annals of neurosciences · 2026Article
- SERPINE1 and its co-expressed genes are associated with the progression of clear cell renal cell carcinoma.BMC urology · 2023Article
- Integrated Protein-Protein Interaction and Weighted Gene Co-expression Network Analysis Uncover Three Key Genes in Hepatoblastoma.Frontiers in cell and developmental biology · 2021Article
- The Choice of Candidates in Survival Markers Based on Coordinated Gene Expression in Renal Cancer.Frontiers in oncology · 2021Article
- Overexpression of PKMYT1 Facilitates Tumor Development and Is Correlated with Poor Prognosis in Clear Cell Renal Cell Carcinoma.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clear cell renal cell carcinoma (ccRCC) remains one of the most common cancer types globally, and while it has been extensively studied, the molecular basis for its pathology remains incompletely understood. Herein, we profiled three previously published datasets (GSE66272, GSE100666, and GSE105261) in a single integrated analysis aimed at identifying disease-associated patterns of gene expression that may offer mechanistic insight into the drivers of this disease. We pooled expression data from 39 normal kidney samples and 39 kidney tumors, leading us to identify 310 differentially expressed genes (DEGs) that were linked to kidney cancer in all three analyzed datasets. Of these genes, 133 and 177 were up- and down-regulated, respectively, in cancer samples. We then incorporated these DEGs into a protein-protein interaction network with the STRING and Cytoscape tools, and we were able to identify signaling pathways significantly enriched for these DEGs. The relationship between DEG expression and ccRCC patient survival was further evaluated using a Kaplan-Meier approach, leading us to identify
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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.