@misc{oai:repo.qst.go.jp:00069771,
 author = {Imai, Takashi and Suga, Tomo and Ishikawa, Atsuko and Shoji, Yoshimi and Iwakawa, Mayumi and 今井 高志 and 菅 智 and 石川 敦子 and 荘司 好美 and 岩川 眞由美},
 month = {Jun},
 note = {The clinical radiosensitivity of normal tissue is likely to be a complex trait that is
dependent on the cumulative effect of many minor genetic determinants. We have
searched for polymorphisms associated with the radiosensitivity of normal tissue in
cancer patients who have undergone radiotherapy.
Between October 2001 and March 2009, 2,653 patients were recruited to our project,
including 773 breast cancer patients and 855 prostate cancer patients. The candidate
genes for SNP typing in this project were selected by our previous comprehensive gene
expression analyses data using human cultured cell lines and mouse strains. We also
added well-known genes in the literature as responsible genes for radiosensitivity. A
total of 190 genes were chosen and 1,300 SNPs have been typed using a matrix-assisted
laser desorption/ionization time-of-flight mass spectrometry system (MassARRAY,
Sequenom).
Thus far, we indentified multiple SNPs associated with risk of skin reaction after
radiation therapy in breast cancer patients and another group of SNPs associated with
risk of urinary morbidity after radiation therapy in prostate cancer patients.
These data suggest that multiple genetic factors are associated with individual
radiosensitivity in the cancer patient-groups, unlike a few Mendelian diseases with
hypesensitivity to ionizing irradiation caused by single gene mutation such as ATM.
Individuals in this study contain different numbers of minor alleles affecting radiation
sensitivity. This fact suggests that contribution of each allele to radiosensitivity may be
tissue-specific and the strength to the sensitivity of one allele might be small and
dissimilar each other. This would provide an understanding of the mechanisms
underlying the genetic variation in radiosensitivity among the population, and would
show the possibility of the risk prediction for the side effects prior to radiation therapy., Genomic Tools & Technologies Summit},
 title = {Genetic Variation in Individual Sensitivity to Clinical Radiotherapy},
 year = {2009}
}