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Towards Predicting Late-stage Radiation Toxicity

Date:
November 1, 2006
Source:
Public Library of Science
Summary:
Radiation is a brutal and in many cases necessary part of cancer therapy. A small fraction of patients develop severe late radiation toxicity, months or years after their treatment. A new study now suggests that in the future scientists might be able to tell who is at higher risk for such late toxicity and adjust treatments accordingly.
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Radiation is a brutal and in many cases necessary part of cancer therapy. More 50% of cancer patients receive radiotherapy as part of their treatment, and many experience concurrent negative side effects. In addition, a smaller fraction of patients develop severe late radiation toxicity, months or years after their treatment in normal tissues near the tumor site. For example, in prostate cancer--a tumor in the prostate gland that lies between the bladder and the rectum--late radiation toxicity affects rectal, bladder, and sexual function in 5--10% of patients.

A new study by Micheline Giphart-Gassler (Leiden University Medical Center) and colleagues published in the international open-access journal PLoS Medicine now suggests that in the future scientists might be able to tell who is at higher risk for such late toxicity and adjust treatments accordingly.

Scientists don't know why some patients develop late radiation toxicity, but one theory is that some patients have a genetic predisposition. Giphart-Gassler and colleagues tested this by comparing radiation-induced changes in the gene expression profiles in blood cells from 21 patients who had late radiation toxicity after radiotherapy with the changes seen in cells from patients who did not developed such complications.

Irradiation with X-rays induced the expression of numerous genes in the cells, including many known radiation-responsive genes. From those, the researchers derived a gene expression profile (or molecular signature) that was associated with late radiation toxicity. A signature based on the radiation response of 50 individual genes correctly classified 63% of the patient population in terms of whether they had developed late radiation toxicity. A signature based on the radiation response of gene sets containing genes linked by function or cellular localization correctly classified 86% of the patient population.

While these results are not robust enough to apply them in a clinical setting, they support the idea that some patients are genetically predisposed to develop late radiation toxicity and also provide clues about which cellular pathways might be involved. The study suggests that it might one day be possible to predict which patients are at high and at low risk for late-radiation toxicity, respectively, and adjust their treatment accordingly. The results also point to certain molecular pathways involved in response to radiation which might be targets for interventions that protect against the toxic side effects of radiation.

As Adrian Begg (Radboud University Medical Center) states in an accompanying Perspective article, these are intriguing, preliminary results on an important question that has been difficult to answer. Future studies are needed to determine whether expression profiles such as this one can serve as robust predictors of late radiation toxicity.

Citation: Svensson JP, Stalpers LJA, Esveldt--van Lange REE, Franken NAP, Haveman J, et al. (2006) Analysis of gene expression using gene sets discriminates cancer patients with and without late radiation toxicity. PLoS Med 3(10): e422. (http://dx.doi.org/10.1371/journal.pmed.0030422)


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Public Library of Science. "Towards Predicting Late-stage Radiation Toxicity." ScienceDaily. ScienceDaily, 1 November 2006. <www.sciencedaily.com/releases/2006/10/061031192519.htm>.
Public Library of Science. (2006, November 1). Towards Predicting Late-stage Radiation Toxicity. ScienceDaily. Retrieved April 24, 2024 from www.sciencedaily.com/releases/2006/10/061031192519.htm
Public Library of Science. "Towards Predicting Late-stage Radiation Toxicity." ScienceDaily. www.sciencedaily.com/releases/2006/10/061031192519.htm (accessed April 24, 2024).

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