Open Access

A novel system for predicting the toxicity of irinotecan based on statistical pattern recognition with UGT1A genotypes

  • Authors:
    • Ryouichi Tsunedomi
    • Shoichi Hazama
    • Yusuke Fujita
    • Naoko Okayama
    • Shinsuke Kanekiyo
    • Yuka Inoue
    • Shigefumi Yoshino
    • Takahiro Yamasaki
    • Yutaka Suehiro
    • Koji Oba
    • Hideyuki Mishima
    • Junichi Sakamoto
    • Yoshihiko Hamamoto
    • Masaaki Oka
  • View Affiliations

  • Published online on: July 22, 2014     https://doi.org/10.3892/ijo.2014.2556
  • Pages: 1381-1390
  • Copyright: © Tsunedomi et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

To predict precisely severe toxicity of irinotecan, we evaluated the association of UGT1A variants, haplotypes and the combination of UGT1A genotypes to severe toxicity of irinotecan. UGT1A1*6 (211G>A), UGT1A1*28 (TA6>TA7), UGT1A1*60 (-3279T>G), UGT1A7 (387T>G), UGT1A7 (622T>C), and UGT1A9*1b (-118T9>T10, also named *22) were genotyped in 123 patients with metastatic colorectal cancer who had received irinotecan-based chemotherapy. Among the 123 patients, 73 were enrolled in either of two phase II studies of the FOLFIRI (leucovorin, 5-fluorouracil and irinotecan) regimen; these patients constituted the training population, which was used to construct the predicting system. The other 50 patients constituted the validation population; these 50 patients either had participated in a phase II study of irinotecan/5'-deoxy-5-fluorouridine or were among consecutive patients who received FOLFIRI therapy. This prediction system used sequential forward floating selection based on statistical pattern recognition using UGT1A genotypes, gender and age. Several UGT1A genotypes [UGT1A1*6, UGT1A7 (387T>G), UGT1A7 (622T>C) and UGT1A9*1b] were associated with the irinotecan toxicity. Among the haplotypes, haplotype-I (UGT1A1: -3279T, TA6, 211G; UGT1A7: 387T, 622T; UGT1A9: T10) and haplotype-II (UGT1A1: -3279T, TA6, 211A; UGT1A7: 387G, 622C; UGT1A9: T9) were also associated with irinotecan toxicity. Furthermore, our new system for predicting the risk of irinotecan toxicity was 83.9% accurate with the training population and 72.1% accurate with the validation population. Our novel prediction system using statistical pattern recognition depend on genotypes in UGT1A, age and gender; moreover, it showed high predictive performance even though the treatment regimens differed among the training and validation patients.
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October 2014
Volume 45 Issue 4

Print ISSN: 1019-6439
Online ISSN:1791-2423

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Copy and paste a formatted citation
APA
Tsunedomi, R., Hazama, S., Fujita, Y., Okayama, N., Kanekiyo, S., Inoue, Y. ... Oka, M. (2014). A novel system for predicting the toxicity of irinotecan based on statistical pattern recognition with UGT1A genotypes. International Journal of Oncology, 45, 1381-1390. https://doi.org/10.3892/ijo.2014.2556
MLA
Tsunedomi, R., Hazama, S., Fujita, Y., Okayama, N., Kanekiyo, S., Inoue, Y., Yoshino, S., Yamasaki, T., Suehiro, Y., Oba, K., Mishima, H., Sakamoto, J., Hamamoto, Y., Oka, M."A novel system for predicting the toxicity of irinotecan based on statistical pattern recognition with UGT1A genotypes". International Journal of Oncology 45.4 (2014): 1381-1390.
Chicago
Tsunedomi, R., Hazama, S., Fujita, Y., Okayama, N., Kanekiyo, S., Inoue, Y., Yoshino, S., Yamasaki, T., Suehiro, Y., Oba, K., Mishima, H., Sakamoto, J., Hamamoto, Y., Oka, M."A novel system for predicting the toxicity of irinotecan based on statistical pattern recognition with UGT1A genotypes". International Journal of Oncology 45, no. 4 (2014): 1381-1390. https://doi.org/10.3892/ijo.2014.2556