ArticleCell2014
Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules.
Article in Cell, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 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.
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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
137 citing papers in PubMed, 279 citations in OpenAlex.
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- 75 Years of Mathematical Oncology.bioRxiv : the preprint server for biology · 2026Article
- Mathematical Oncology: How Modeling Is Transforming Clinical Decision-Making.Cancer research · 2025Review
- Measurable imaging-based changes in enhancement of intrahepatic cholangiocarcinoma after radiotherapy reflect physical mechanisms of response.NPJ systems biology and applications · 2025Article
- Probability Distribution for Rare Neutral Mutations in Cancers and Application to Dynamic Precision Medicine of Cancer.bioRxiv : the preprint server for biology · 2025Article
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- Mathematical modeling framework enhances clinical trial design for maintenance treatment in oncology.Scientific reports · 2024Article
- Data Science Opportunities To Improve Radiotherapy Planning and Clinical Decision Making.Seminars in radiation oncology · 2024Review
- A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.NPJ systems biology and applications · 2024Review
- Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells.Science advances · 2024Article
77 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
Abstract
Glioblastomas (GBMs) are the most common and malignant primary brain tumors and are aggressively treated with surgery, chemotherapy, and radiotherapy. Despite this treatment, recurrence is inevitable and survival has improved minimally over the last 50 years. Recent studies have suggested that GBMs exhibit both heterogeneity and instability of differentiation states and varying sensitivities of these states to radiation. Here, we employed an iterative combined theoretical and experimental strategy that takes into account tumor cellular heterogeneity and dynamically acquired radioresistance to predict the effectiveness of different radiation schedules. Using this model, we identified two delivery schedules predicted to significantly improve efficacy by taking advantage of the dynamic instability of radioresistance. These schedules led to superior survival in mice. Our interdisciplinary approach may also be applicable to other human cancer types treated with radiotherapy and, hence, may lay the foundation for significantly increasing the effectiveness of a mainstay of oncologic therapy. PAPERCLIP:
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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.