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Abstract Acute Myeloid Leukemia (AML) is aggressive cancer that initiates in the bone marrow (BM) and circulates in the peripheral blood (PB). The AML initiation and progressions are complex disease evolution associated with gene mutations and chromosomal abnormalities that change expression profiles of downstream genes characterizing functional networks of leukemic cells. We previously reported the application of the state-transition theory to characterize AML disease progression by modeling transcriptome changes during AML progression as a dynamic system that undergoes state-transition in an AML state-space characterized by an AML potential. Here, we investigate the impact of treatment on transcriptome state-transition and examine the hypothesis that treatment dynamically alters the AML potential. We use the Cbfb-MYH11 (CM) knock-in AML mouse model and a ”5+3” chemotherapy regimen to model the impact of current standard of care for newly diagnosed AML. CM leukemic mice were treated with a combination of cytarabine (Ara-C; 50mg/kg/day; 5 days) and Daunorubicin (DNR; 1. 5mg/kg/day; 3 days) after detection of overt leukemia, defined by 20% leukemia blast (cKit+) detected by flow cytometry in the PB. Time-series samples of peripheral blood mononuclear cell (PBMC) (n=174) were collected weekly before, during, and following “5+3” chemotherapy and subjected to RNA sequencing. All samples were mapped to the AML state-space constructed based on time-sequential RNA-seq collected over the course of CM AML development. Based on the state-transition model, all 10 treated AML mice achieved partial response to chemotherapy with a mean time to relapse (return to leukemia state) of 5 weeks confirming the anti-leukemia effects of treatment by the blast percentages (ckit%). We used the state-transition treatment model to study the dynamics of chemotherapy on the AML potential using state-space trajectories before, during, and after “5+3” chemotherapy. Dynamic changes of concentrations of Ara-C and DNR in the CM mouse model during ”5+3” chemotherapy were modeled by drug doses, half-life, and Heaviside step function. The drug effects were introduced to the AML potential as anti-leukemic treatment forces. Several treatment protocols were examined to find combinations of drug doses and timing that showed the longest survival rates. The model predicted that sequential doses reducing 50% of the original “5+3” chemotherapy dose would produce the longest survival rate. The model suggests that controlling the state-space trajectories in the healthy state with reduced doses will provide the most effective outcomes from “5+3” chemotherapy. Citation Format: Lisa Uechi, Yu-Hsuan Fu, David E. Frankhouser, Lianjun Zhang, Ying-Chieh Chen, Denis O'Meally, Sergio Branciamore, Jihyun Irizarry, Bin Zhang, Guido Marcucci, Ya-Huei Kuo, Russell C. Rockne. Application of state transition theory for predicting responses of acute myeloid leukemia to chemotherapy abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 7397.
Uechi et al. (Fri,) studied this question.