title: Biologically based risk estimation for radiation-induced CML. Inferences from BCR and ABL geometric distributions.
abstract: Chronic myeloid leukemia (CML) invites biologically based radiation risk modeling because CML is simultaneously well-understood, homogeneous and prevalent. CML is known to be caused by a translocation involving the ABL and BCR genes, almost all CML patients have the BCR-ABL translocation, and CML is prevalent enough that its induction is unequivocally detected among Hiroshima A-bomb survivors. In a previous paper, a linear-quadratic-exponential (LQE) dose-response model was used to estimate the lifetime excess risk of CML in the limit of low doses of gamma-rays, R gamma. This estimate assumed that BCR-ABL translocation dose-response curves in stem cells for both neutrons and gamma-rays, differ only by a common proportionality constant from dicentric aberration dose-response curves in lymphocytes. In the present paper we challenge this assumption by predicting the BCR-ABL dose response. The predictions are based on the biophysical theory of dual radiation action (TDRA) as it applies to recent BCR-to-ABL distance data in G0 human lymphocytes; this data shows BCR and ABL geometric distributions that are not uniform and not independent, with close association of the two genes in some cells. The analysis speaks against the previous proportionality assumption. We compute 11 plausible LQE estimates of R gamma, 2 based on the proportionality assumption and 9 based on TDRA predictions. For each estimate of R gamma we also compute an associated estimate of the number of CML target cells, N; the biological basis of the LQE model allows us to form such estimates. Consistency between N and hematological considerations provides a plausibility check of the risk estimates. Within the group of estimates investigated, the most plausible lifetime excess risk estimates tend to lie near R gamma = 0.01 Gy-1, substantially higher than risk estimates based on the proportionality assumption.
authors.affiliation: Department of Mathematics, University of California, Berkeley 94720, USA. radivot@musc.edu
authors.forename: T
authors.initials: T
authors.lastname: Radivoyevitch
authors.forename: S
authors.initials: S
authors.lastname: Kozubek
authors.forename: R K
authors.initials: RK
authors.lastname: Sachs
mesh_terms: D016044:Fusion Proteins, bcr-abl / Q000235:genetics*; D016313:Genes, abl; D006801:Humans; D007564:Japan; D015464:Leukemia, Myelogenous, Chronic, BCR-ABL Positive / Q000453:epidemiology* / Q000235:genetics; D007953:Leukemia, Radiation-Induced / Q000453:epidemiology* / Q000235:genetics; D015233:Models, Statistical; D009689:Nuclear Warfare; D015513:Oncogene Proteins / Q000235:genetics; D009857:Oncogenes; D011505:Protein-Tyrosine Kinases; D011518:Proto-Oncogene Proteins; D051562:Proto-Oncogene Proteins c-bcr; D018570:Risk Assessment; D012307:Risk Factors; D014178:Translocation, Genetic; D014481:United States
chemical_list: D015513:Oncogene Proteins; D011518:Proto-Oncogene Proteins; D011505:Protein-Tyrosine Kinases; D016044:Fusion Proteins, bcr-abl; C496613:BCR protein, human; D051562:Proto-Oncogene Proteins c-bcr