Early dynamics of chronic myeloid leukemia on nilotinib predicts deep molecular response

Yuji Okamoto, Mitsuhito Hirano, Kai Morino, Masashi K. Kajita, Shinji Nakaoka, Mayuko Tsuda, Kei ji Sugimoto, Shigehisa Tamaki, Junichi Hisatake, Hisayuki Yokoyama, Tadahiko Igarashi, Atsushi Shinagawa, Takeaki Sugawara, Satoru Hara, Kazuhisa Fujikawa, Seiichi Shimizu, Toshiaki Yujiri, Hisashi Wakita, Kaichi Nishiwaki, Arinobu TojoKazuyuki Aihara

Research output: Contribution to journalArticlepeer-review

Abstract

Chronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase. Although ABL1-specific tyrosine kinase inhibitors (TKIs) including nilotinib have dramatically improved the prognosis of patients with CML, the TKI efficacy depends on the individual patient. In this work, we found that the patients with different nilotinib responses can be classified by using the estimated parameters of our simple dynamical model with two common laboratory findings. Furthermore, our proposed method identified patients who failed to achieve a treatment goal with high fidelity according to the data collected only at three initial time points during nilotinib therapy. Since our model relies on the general properties of TKI response, our framework would be applicable to CML patients who receive frontline nilotinib or other TKIs.

Original languageEnglish
Article number39
Journalnpj Systems Biology and Applications
Volume8
Issue number1
DOIs
Publication statusPublished - Dec 2022

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

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