ReviewRadiation oncology (London, England)2014
Integrative radiation systems biology.
Review in Radiation oncology (London, England), 2014. 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.
- Nonlinear Redox-Immune Coupling Under Low-Dose-Rate Radiation: A Compartment-Specific Framework for Biological Responses-A Narrative Review.Antioxidants (Basel, Switzerland) · 2026Review
- Wireless radiation and health: making the case for proteomics research of individual sensitivity.Frontiers in public health · 2024Article
- Simultaneous metabolite MALDI-MSI, whole exome and transcriptome analysis from formalin-fixed paraffin-embedded tissue sections.Laboratory investigation; a journal of technical methods and pathology · 2022Article
- All for one, though not one for all: team players in normal tissue radiobiology.International journal of radiation biology · 2022Review
- Brain Damage and Patterns of Neurovascular Disorder after Ionizing Irradiation. Complications in Radiotherapy and Radiation Combined Injury.Radiation research · 2021Review
- Radiomic and radiogenomic modeling for radiotherapy: strategies, pitfalls, and challenges.Journal of medical imaging (Bellingham, Wash.) · 2021Review
- Investigating Molecular Determinants of Cancer Cell Resistance to Ionizing Radiation Through an Integrative Bioinformatics Approach.Frontiers in cell and developmental biology · 2021Article
- Transcriptome network of the papillary thyroid carcinoma radiation marker CLIP2.Radiation oncology (London, England) · 2020Article
- Single-center versus multi-center data sets for molecular prognostic modeling: a simulation study.Radiation oncology (London, England) · 2020Article
- Review
- Gene Expression Studies for the Development of Particle Therapy.International journal of particle therapy · 2018Article
- Big Data Analytics for Prostate Radiotherapy.Frontiers in oncology · 2016Review
- Radiation Metabolomics: Current Status and Future Directions.Frontiers in oncology · 2016Review
- Integr(at)in(g) EGFR therapy in HNSCC.Annals of translational medicine · 2015Article
- A proliferation saturation index to predict radiation response and personalize radiotherapy fractionation.Radiation oncology (London, England) · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Maximisation of the ratio of normal tissue preservation and tumour cell reduction is the main concept of radiotherapy alone or combined with chemo-, immuno- or biologically targeted therapy. The foremost parameter influencing this ratio is radiation sensitivity and its modulation towards a more efficient killing of tumour cells and a better preservation of normal tissue at the same time is the overall aim of modern therapy schemas. Nevertheless, this requires a deep understanding of the molecular mechanisms of radiation sensitivity in order to identify its key players as potential therapeutic targets. Moreover, the success of conventional approaches that tried to statistically associate altered radiation sensitivity with any molecular phenotype such as gene expression proofed to be somewhat limited since the number of clinically used targets is rather sparse. However, currently a paradigm shift is taking place from pure frequentistic association analysis to the rather holistic systems biology approach that seeks to mathematically model the system to be investigated and to allow the prediction of an altered phenotype as the function of one single or a signature of biomarkers. Integrative systems biology also considers the data from different molecular levels such as the genome, transcriptome or proteome in order to partially or fully comprehend the causal chain of molecular mechanisms. An example for the application of this concept currently carried out at the Clinical Cooperation Group "Personalized Radiotherapy in Head and Neck Cancer" of the Helmholtz-Zentrum München and the LMU Munich is described. This review article strives for providing a compact overview on the state of the art of systems biology, its actual challenges, potential applications, chances and limitations in radiation oncology research working towards improved personalised therapy concepts using this relatively new methodology.
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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.