Biologically-Based Risk Estimation for Radiation-Induced Chronic Myeloid Leukemia

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Biologically-Based Risk Estimation for
Radiation-Induced Chronic Myeloid Leukemia

• Radiation Carcinogenesis Applying Basic Science
  to Epidemiological Estimates of Low-Dose Risks

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Overview

• Bayesian methods and CML
• Linear-Quadratic-Exponential model
• Likelihood and prior data sets
• Baseline LQE estimate of CML risk
• Improved risk estimates based on BCR-to-ABL
  distances and CML target cell numbers
• Net lifetime CML risk Can it have a U-shaped
  low dose response?

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Bayesian Methods

• Priors likelihood estimates ? posteriors
• Posterior information equals prior plus
  likelihood information
• Posterior means are information-weighted averages
  of prior and likelihood means
• Posteriors are normal if the prior and
  likelihood estimates are normal
• Priors act as soft constraints on the parameters
• Priors and structures come from the same data

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Chronic Myeloid Leukemia

• CML is homogeneous, prevalent, radiation-induced,
  and caused by BCR-ABL
• The a2 intron of ABL is unusually large
• Leukemic endpoints have rapid kinetics
• White blood cells need fewer stages
• Linear CML risk is not biologically-based
• Linear-quadratic-exponential CML risk does have
  a biological basis

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Linear Risk Model
Using the BCR-ABL to CML waiting time density
and the linear model
we maximized the log-likelihood
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Linear-Quadratic-Exponential Model
The LQE model is
where
D?i and Dni are the gamma and neutron doses in
gray
N is the number of CML target cells per adult
P(baT) is the probability of BCR-ABL given a
translocation
This is a one-stage model of carcinogenesis.
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Likelihood Data

• CML is practically absent in Nagasaki
• High dose HF waiting times are too long
• HM data is consistent with prior expectations

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aage at diagnosis bO observed cases (E
expected background cases based on U.S. incidence
rates) ctsx average of the times since exposure
for the cases
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Prior Data Sources

• C1 and k SEER data
• kt Patients irradiated for BGD
• ?k, ?k and ?kn CAFC and MRA assays
• ?/? and ?n/? Lymphocyte dicentric yields
• C2 Depends on ?, kt, N, and P(baT)
• N SEER and translocation age structure data
• P(baT) BCR and ABL intron sizes, the genome
  size

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Parameter Estimates
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CML Risk Estimates
The lifetime excess CML risk in the limit of low
?-ray doses
yields

• Linear model
• R? 0.0075 Gy-1 and Q? 0.0158 Gy-1
• LQE posterior model
• R? 0.0022 Gy-1 and Q? 0.0042 Gy-1

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CML Target Cell Numbers

• A comparison of age responses for CML and total
  translocations suggests a CML target cell number
  of 2x108
• 1012 nucleated marrow cells per adult and one
  LTC-IC per 105 marrow cells suggests 107 CML
  target cells
• P(baT) 2TablTbcr/?2 may not hold

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BCR-to-ABL 2D distances in lymphocytes
Kozubek et al. (1999) Chromosoma 108 426-435
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Theory of Dual Radiation Action
P(baD) probability of a BCR-ABL translocation
per G0/G1 cell given a dose D tD(r)dr expected
energy at r given an ionization event at the
origin
intra-track component inter-track
component Sba(r) the BCR-to-ABL distance
probability density g(r) probability that two
DSBs misrejoin if they are created r units
apart Y 0.0058 DSBs per Mb per Gy ? mass
density TBCR 5.8 kbp TABL 300 kbp
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Estimation of g(r)
?d? in .01, .025, ?dx in .04, .05, ?d
in .05, .06
G35 DSB/Gy per cell 6.25 kev/um3 1 Gy
R 3.7 um ? r0 0.24 ?m, p0 0.06
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?
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Dead-Band Control of HSC levels

• Transplant doses of 10, 100, and 1000 CRU gt CRU
  levels 1-20 or 15-60 normal Blood (1996) 88
  2852-2858
• Broad variation in human HSC levels Stem
  Cells (1995) 13 512-516
• Low levels of HSCs in BMT patients
  Blood (1998) 91 1959-1965

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Figure 3 Hypersensitivity ratios in the
literature (left panel) and the log-survival dose
response for T98G human glioma cells (right
panel). Figures from Joiner, M.C., Marples, B.,
Lambin, P., Short, S.C. and Turesson, I.,
Low-dose hypersensitivity current status and
possible mechanisms. Int J Radiat Oncol Biol Phys
(2001) 49 379-389.
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Net Lifetime CML Risk
The net lifetime excess risk of CML is
Letting Dn 0 while D? ? 0
We solved R0 0 for ?k?s as a function of
exposure age x.
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Conclusions

• Bayesian methods provide a natural framework for
  biologically based risk estimation
• BCR-to-ABL distance data and knowledge of CML
  target cell numbers can be useful in a
  biologically based approach to CML risk
  estimation
• Low dose hypersensitivity to killing might lead
  to a U-shaped low dose response if there is a
  dead-band in the control of target cell numbers

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Acknowledgments

• Rainer Sachs
• David Hoel
• NIH and DOE