ReviewCancers2022
Radiogenomics in Clear Cell Renal Cell Carcinoma: A Review of the Current Status and Future Directions.
Review in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- CT-Based Radiomics in the Characterization of Solid Renal Tumors: A Systematic Review.Cancers · 2026Review
- Emerging Role of ctDNA Fragmentomics and Epigenetic Signatures in the Early Detection, Minimal Residual Disease Assessment, and Precision Monitoring of Renal Cell Carcinoma.Journal of cellular and molecular medicine · 2026Review
- From Radiomics to Radiogenomics: Decoding Renal Cell Carcinoma Biology for Precision Medicine-a narrative review.Insights into imaging · 2025Review
- AI-driven radiogenomic analysis of clear cell renal cell carcinoma: perinephric adipose tissue stranding as a key feature of the NIPAL4-associated imaging pattern.The Canadian journal of urology · 2025Article
- Radiomics-Based Unsupervised Clustering Identifies Subtypes Associated With Prognosis and Immune Microenvironment in Clear Cell Renal Cell Carcinoma: A Multicenter Study.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.BMC cancer · 2025Article
- Article
- Preoperative prediction of high-grade osteosarcoma response to neoadjuvant therapy based on a plain CT radiomics model: A dual-center study.Journal of bone oncology · 2024Article
- Radiogenomics and Texture Analysis to Detect von Hippel-Lindau (VHL) Mutation in Clear Cell Renal Cell Carcinoma.Current issues in molecular biology · 2024Review
- Downregulation of Glycine N-Acyltransferase in Kidney Renal Clear Cell Carcinoma: A Bioinformatic-Based Screening.Diagnostics (Basel, Switzerland) · 2023Article
- Current Status of Cancer Genomics and Imaging Phenotypes: What Radiologists Need to Know.Radiology. Imaging cancer · 2023Review
- PI3K/AKT/mTOR Dysregulation and Reprogramming Metabolic Pathways in Renal Cancer: Crosstalk with the VHL/HIF Axis.International journal of molecular sciences · 2023Review
- Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects.International journal of molecular sciences · 2023Review
- Article
- Feasibility of using CT radiomic signatures for predicting CD8-T cell infiltration and PD-L1 expression in renal cell carcinoma.European journal of radiology open · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Radiogenomics is a field of translational radiology that aims to associate a disease's radiologic phenotype with its underlying genotype, thus offering a novel class of non-invasive biomarkers with diagnostic, prognostic, and therapeutic potential. We herein review current radiogenomics literature in clear cell renal cell carcinoma (ccRCC), the most common renal malignancy. A literature review was performed by querying PubMed, Medline, Cochrane Library, Google Scholar, and Web of Science databases, identifying all relevant articles using the following search terms: "radiogenomics", "renal cell carcinoma", and "clear cell renal cell carcinoma". Articles included were limited to the English language and published between 2009-2021. Of 141 retrieved articles, 16 fit our inclusion criteria. Most studies used computed tomography (CT) images from open-source and institutional databases to extract radiomic features that were then modeled against common genomic mutations in ccRCC using a variety of machine learning algorithms. In more recent studies, we noted a shift towards the prediction of transcriptomic and/or epigenetic disease profiles, as well as downstream clinical outcomes. Radiogenomics offers a platform for the development of non-invasive biomarkers for ccRCC, with promising results in small-scale retrospective studies. However, more research is needed to identify and validate robust radiogenomic biomarkers before integration into clinical practice.
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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.