Implication of the Autologous Immune System in BCR–ABL Transcript Variations in Chronic Myelogenous Leukemia Patients Treated with Imatinib

Abstract

Imatinib and other tyrosine kinase inhibitors (TKI) have improved treatment of chronic myelogenous leukemia (CML); however, most patients are not cured. Deeper mechanistic understanding may improve TKI combination therapies to better control the residual leukemic cell population. In analyzing our patients' data, we found that many patients who otherwise responded well to imatinib therapy still showed variations in their BCR-ABL transcripts. To investigate this phenomenon, we applied a mathematical model that integrates CML and an autologous immune response to the patients' data. We define an immune window or a range of leukemic loads for which the autologous immune system induces an improved response. Our modeling results suggest that,

BCR-ABL transcript variations in chronic phase chronic myelogenous leukemia patients on imatinib first-line: Possible role of the autologous immune system

“…10 The initial two phases are similar to the biphasic decline described previously. 3,4 During this time, because leukemic loads are still large, the immune system plays a minimal role, and the decline in the leukemic population is driven primarily by the drug.…”

“…1A) that integrates CML and the intervention of an autologous immune response. 10 We encode an immune response in which small leukemic loads are an insufficient stimulus, while large leukemic loads suppress the immune system, thereby limiting its response to CML. However, at intermediate levels of leukemia, which we call an immune window, a balance between immunostimulation and immunosuppression is achieved, and the autologous immune system is able to mount an efficient response against CML.…”

Dynamical models of mutated chronic myelogenous leukemia cells for a post-imatinib treatment scenario: Response to dasatinib or nilotinib therapy

“…Alternative deterministic models that take a clonal competition of normal and cancer cells into account have also been investigated [28, 69], linking other physiological phenomena to population dynamics, such as combination treatment [28] or the effects of immune response [23, 27]. …”

“…In selecting PP14 and PP15, we were interested in CML cell population evolutions which exhibit bi- or multiphasic decay patterns under second-line dasatinib or nilotinib administration because this type of response has been identified as a hallmark of the involvement of quiescent stem cells in the context of first-line treatment with imatinib [19, 25, 27, 28, 49]. …”

“…Komarova and Wodarz [25] introduced a stochastic model that explicitly includes populations of both cycling and non-cycling stem cells in order to explain biphasic decay of wild-type CML cell populations upon treatment with imatinib . Levy et al added immune system response terms [26, 27]. Michor et al included the quiescent state of stem cells explicitly in a deterministic model [28].…”