2001
Biologically based risk estimation for radiation-induced CML - Inferences from BCR and ABL geometric distributions
RADIVOYEVITCH, Tom; Stanislav KOZUBEK a RK SACHSZákladní údaje
Originální název
Biologically based risk estimation for radiation-induced CML - Inferences from BCR and ABL geometric distributions
Autoři
RADIVOYEVITCH, Tom; Stanislav KOZUBEK a RK SACHS
Vydání
Radiation and Environmental Biophysics, New York, Springer-Verlag, 2001, 0301-634X
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10610 Biophysics
Stát vydavatele
Spojené státy
Utajení
není předmětem státního či obchodního tajemství
Impakt faktor
Impact factor: 1.776
Označené pro přenos do RIV
Ne
Organizační jednotka
Přírodovědecká fakulta
Změněno: 1. 11. 2002 12:29, prof. RNDr. Michal Kozubek, Ph.D.
Anotace
V originále
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 G(0) 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.