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Fractionated Irradiation of Five Human Lung Cancer Cell Lines and Prediction of Survival According to a Radiobiology Model
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Oncology.
2011 (English)In: Anticancer Research, ISSN 0250-7005, Vol. 31, no 4, 1125-1130 p.Article in journal (Refereed) Published
Abstract [en]

Background: This study evaluates a predictive radiobiology model by measurements of surviving fraction (SF) by the clonogenic assay or the extrapolation method and the proliferation rate in vitro. It is hypothesized that incorporating proliferation to intrinsic radiosensitivity, measured by SF, to predict radiation responsiveness after fractionated irradiation adds to the model's accuracy. Materials and Methods. Five lung cancer cell lines with known SF after 1 Gy (SF1), and also SF2 and SF5, were irradiated with three different fractionation regimes; 10x1 Gy, 5x2 Gy or 2x5 Gy during the same total time to achieve empirical SF. In addition, the SF1, SF2 and SF5 after fractionated irradiation was calculated for each cell line based on the already known single fraction SF and with or without a proliferation factor. The results were compared to the empirical data. Results and Discussion: By using the clonogenic assay to measure radiosensitivity, prediction of radiosensitivity was improved after fractionated radiotherapy when proliferation was used in the radiobiology model. However, this was not the case in the cell lines where the extrapolation method was used to calculate SF. Thus, a radiobiology model including intrinsic radiosensitivity, measured by the clonogenic assay, as well as proliferation, is better at predicting survival after fractionated radiotherapy, compared to the use of intrinsic radiosensitivity alone.

Place, publisher, year, edition, pages
2011. Vol. 31, no 4, 1125-1130 p.
Keyword [en]
Human lung cancer cell lines, surviving fraction, doubling time, radiobiology model, clonogenic assay
National Category
Medical and Health Sciences
URN: urn:nbn:se:uu:diva-154123ISI: 000290292000004OAI: oai:DiVA.org:uu-154123DiVA: diva2:419312
Available from: 2011-05-26 Created: 2011-05-26 Last updated: 2011-05-26Bibliographically approved

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