Quantitative modeling of chronic myeloid leukemia: insights from radiobiology

Abstract

Mathematical models of chronic myeloid leukemia (CML) cell population dynamics are being developed to improve CML understanding and treatment. We review such models in light of relevant findings from radiobiology, emphasizing 3 points. First, the CML models almost all assert that the latency time, from CML initiation to diagnosis, is at most ϳ 10 years. Meanwhile, current radiobiologic estimates, based on Japanese atomic bomb survivor data, indicate a substantially higher maximum, suggesting longer-term relapses and extra resistance mutations. Second, different CML models assume different numbers, between 400 and 10 6 , of normal HSCs. Radiobiologic estimates favor values > 10 6 for the number of normal cells (often assumed to be the HSCs) that are at risk for a CML-initiating BCR-ABL translocation. Moreover, there is some evidence for an HSC dead-band hypothesis, consistent with HSC numbers being very different across different healthy adults. Third, radiobiologists have found that sporadic (background, agedriven) chromosome translocation incidence increases with age during adulthood. BCR-ABL translocation incidence increasing with age would provide a hitherto underanalyzed contribution to observed background adult-onset CML incidence acceleration with age, and would cast some doubt on stage-number inferences from multistage carcinogenesis models in general. (Blood. 2012; 119(19):4363-4371) IntroductionChronic myeloid leukemia (CML) is characterized by Ph ϩ cells, that is, cells having a Philadelphia (BCR-ABL) chromosome translocation. 1,2 Treatment with the tyrosine kinase inhibitor (TKI) imatinib mesylate ("imatinib"), which suppresses bcr-abl oncoprotein action, 3 improves patient prognosis dramatically. 4 However, in some cases this treatment fails, a problem mitigated but not fully solved by the use of more recently developed TKI. 5,6 Moreover, many patients may need to continue TKI treatment indefinitely to avoid relapse. 7 CML is one of the best understood cancers; it has a simpler etiology than most cancers 8 and its time course is comparatively easy to monitor in the clinic. 9,10 Consequently, despite being much less prevalent than major solid tumors, CML has often been regarded as a kind of "model organism" for quantitative modeling of human carcinogenesis. 11,12 CML cell population dynamicsIn this review, we emphasize how radiobiologic studies impact CML models grounded in understanding underlying cell population dynamics. These models track CML time evolution by differential equations and/or stochastic formalisms. Such biologically based quantitative models are more ambitious, more comprehensive, and as yet less definitive than models often used in statistical analyses, which emphasize correlations analyzed by adjusting parameters in functions chosen mainly for mathematical convenience.After work by Rubinow and Lebowitz 13 on hematopoiesis, biologically based, mathematical CML models were pioneered by Clarkson and coworkers. 14 Many additional models have been suggested in the last decade. Recent a...

Reduced tyrosine kinase inhibitor dose is predicted to be as effective as standard dose in chronic myeloid leukemia: a simulation study based on phase III trial data

“…Sampling from a distribution of CML latency times as reported by Radivoyevitch et al . 27 [median latency time = 6.9 years, IQR (5.0,10.1)] ( Online Supplementary Figure S6B ) and taking into account the observed TKI response, we obtained an individual distribution of possible proliferation rates p Y for each patient ( Online Supplementary Figure S6C ). In other words, we fit our mathematical model several times under different, plausible assumptions about the aggressiveness of the underlying leukemia.…”

Phylogenetic reconstruction of myeloproliferative neoplasm reveals very early origins and lifelong evolution

“…In patients with blood cancers, the observation of normal blood counts months to years prior to diagnosis has led to the prediction that tumour development occurs quickly, and therefore driver mutations must occur late in life. Estimates from cancer incidences in Japanese atomic survivors who developed chronic myeloid leukaemia have suggested a mean latency time of only 8 years between BCR-ABL1 induction and clinical presentation 6 . However, the presence of driver mutations in normal tissues [7][8][9][10][11][12] , including blood from healthy individuals who harbor age-related clonal haematopoiesis (CH) [13][14][15][16][17] , some of whom subsequently develop malignancies, supports a longer multi-hit evolutionary trajectory of cancer.…”

Sex differences in the incidence of chronic myeloid leukemia

“…Because CML is a comparatively well-characterized neoplasm, many mechanistic mathematical models of CML have been developed (Radivoyevitch et al 2012). …”