ArticleCancer research2019
Modeling Cellular Response in Large-Scale Radiogenomic Databases to Advance Precision Radiotherapy.
Article in Cancer research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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.
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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
20 citing papers in PubMed, 31 citations in OpenAlex.
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- Differentiation Stage Predicts Radiosensitivity in Mesenchymal-Like Pancreatic Cancer.International journal of radiation oncology, biology, physics · 2025Article
- Narrative Review of the Use of Genomic-Adjusted Radiation Dose (GARD) in Radiotherapy.Cancers · 2025Review
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- Gene expression signature predicts radiation sensitivity in cell lines using the integral of dose-response curve.BMC cancer · 2024Article
- Validation of In Vitro Trained Transcriptomic Radiosensitivity Signatures in Clinical Cohorts.Cancers · 2023Article
- Clinical and genome-wide association analysis of chemoradiation-induced hearing loss in nasopharyngeal carcinoma.Human genetics · 2023Article
- Biological Characterization of the Effects of Filtration on the Xoft Axxent® Electronic Brachytherapy Source for Cervical Cancer Applications.Radiation research · 2023Article
- Translation of Precision Medicine Research Into Biomarker-Informed Care in Radiation Oncology.Seminars in radiation oncology · 2022Review
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- Orchestrating and sharing large multimodal data for transparent and reproducible research.Nature communications · 2021Article
- Development and validation of genomic predictors of radiation sensitivity using preclinical data.BMC cancer · 2021Article
- Cell lines of the same anatomic site and histologic type show large variability in intrinsic radiosensitivity and relative biological effectiveness to protons and carbon ions.Medical physics · 2021Article
- Personalizing Radiotherapy Prescription Dose Using Genomic Markers of Radiosensitivity and Normal Tissue Toxicity in NSCLC.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2021Article
- Roadmap: proton therapy physics and biology.Physics in medicine and biology · 2021Review
- Purine metabolism regulates DNA repair and therapy resistance in glioblastoma.Nature communications · 2020Article
- ARe we there yet? Understanding androgen receptor signaling in breast cancer.NPJ breast cancer · 2020Review
- Gene Expression Profiling Identifies Akt as a Target for Radiosensitization in Gastric Cancer Cells.Frontiers in oncology · 2020Article
- Article
- Creating reproducible pharmacogenomic analysis pipelines.Scientific data · 2019Article
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Authors and funding
10 authors at 3 institutions in 3 countries.
Funding
Abstract
Radiotherapy is integral to the care of a majority of patients with cancer. Despite differences in tumor responses to radiation (radioresponse), dose prescriptions are not currently tailored to individual patients. Recent large-scale cancer cell line databases hold the promise of unravelling the complex molecular arrangements underlying cellular response to radiation, which is critical for novel predictive biomarker discovery. Here, we present RadioGx, a computational platform for integrative analyses of radioresponse using radiogenomic databases. We fit the dose-response data within RadioGx to the linear-quadratic model. The imputed survival across a range of dose levels (AUC) was a robust radioresponse indicator that correlated with biological processes known to underpin the cellular response to radiation. Using AUC as a metric for further investigations, we found that radiation sensitivity was significantly associated with disruptive mutations in genes related to nonhomologous end joining. Next, by simulating the effects of different oxygen levels, we identified putative genes that may influence radioresponse specifically under hypoxic conditions. Furthermore, using transcriptomic data, we found evidence for tissue-specific determinants of radioresponse, suggesting that tumor type could influence the validity of putative predictive biomarkers of radioresponse. Finally, integrating radioresponse with drug response data, we found that drug classes impacting the cytoskeleton, DNA replication, and mitosis display similar therapeutic effects to ionizing radiation on cancer cell lines. In summary, RadioGx provides a unique computational toolbox for hypothesis generation to advance preclinical research for radiation oncology and precision medicine. SIGNIFICANCE: The RadioGx computational platform enables integrative analyses of cellular response to radiation with drug responses and genome-wide molecular data. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/79/24/6227/F1.large.jpg.
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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.