National Aeronautics and Space Administration
Biodosimetry Results from the ISS
&
Biomarkers from the NASA Space
Radiation Program
Francis A. Cucinotta, Ph.D.
Human Research Program
Space Radiation Program Element
U.S.R.A. Brown Bag Luncheon
September 13, 2007
Categories of Biomarkers
• Biomarkers of exposure
or initial damage
– e.g., Biodosimetry
• Biomarkers of Risk
– Including individual
sensitivity studies
• Biomarkers of Disease
– e.g., early detection or
preventive medicine
UTSW-NSCOR
Biomarkers and Space Radiation
• Biomarkers of exposure
– Space doses are well known
and sufficient methods exist and
implemented on ISS
• Biomarkers of Risk
– This is a major focus of the
NASA Space Radiation
Program (SRP) in support of
risk assessment
– Largest focus on individual
sensitivity
• Biomarkers of Disease
– This is not a focus of SRP
research, however provides
insights
GCR iron nuclei energy deposition at D=0.1 Gy
ISS Biodosimetry Program
• All NASA astronauts
participate
• Methods
– 3 color Fluorescence in-situ
hybridization to score
chromosome aberrations
– Pre-flight blood draw
exposed to low doses of
gamma-rays to determine
individual calibration curve
– Post-flight blood draw used
as comparison and for
determination of biological
dose
– Follow-up at first annual
physics > 6 months postmission
Biodosimetry Rationale
• Aspects of Biodosimetry
– Estimate of “biological dose” to blood forming organs
• Shielding similar to Tissue average organ shielding
– Advantages over physical dosimetry:
• accounts for self-shielding of body, and
• efficient response to all radiation typed including neutrons
–
–
–
–
LET response is similar to Q(LET) function
Individual sensitivity test
Includes low-dose rate reduction factors
Considers interaction of radiation with stress,
microgravity etc
• Possible limitations
– Statistics for low doses and possible decay with time
– Clonal aberrations or rogue cells can be confounders
– Quality of blood sample
Cytogenetic damage- FISH Methods
•
Use multi-color FISH painting
to count frequency of specific
aberrations
– Inter-changes
(dicentrics,
translocations)
– Complex aberrations
– Total exchanges =
sum over all aberration
types
•
•
PCC=premature chromosome
condensation allows
observations in G1
Metaphase spreads = cells
more likely to transmit damage
to progeny
Metaphase
PCC
Dose Eq = D Q(LET)
BioDose = D x RBEPCC(max)
40
Q60(L) or RBEmax
Expt of George and Cucinotta
30
Q(L)
20
10
0
1
10
100
<LET>dose, keV/μm
1000
International Space Station
Astronaut Biodosimetry
0.04
Before mission
After mission
total exchanges per cell
0.035
0.03
0.025
0.02
0.015
0.01
Number
of cell analyzed for each astronaut
0.005
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16
Total exchanges increased post-mission in all cases
Accuracy of Dose Models: + 15%
ISS Mission Phantom Torso
Pre-flight Data fit to
Weighted linear
regression:
A, Total Exchanges
ISS Biodosimetry and Age
Y = A + B Dose
0.10
0.03
0.02
0.01
0.0020
0.0015
B, cGy-Eq-1
Regression
coefficients used to
Estimate post-flight
Biological dose
0.0010
0.0005
Biodose = (Ypost-Ypre-A)/B
0.0000
35
40
45
Age, yr
50
55
Pre-flight Calibration
0.10
0.14
Pre-Flight data
W eighted Regression
Sigma-plot Regression
Total Exchanges
0.12
0.08
0.10
0.06
0.08
0.04
0.06
0.04
0.02
0.02
0.00
0.12
0.00
0.08
Total Exchanges
Pre-Flight data
W eighted Regression
Sigma-plot Regression
0.10
0.06
0.08
0.04
0.06
0.04
0.02
0.02
0.00
0
10
20
30
Dose, rad
40
50
0.00
0
20
40
Dose, rad
60
80
Comparison to Physical Dosimetry
ISS, Mir, and Hubble results
Astronaut Population Assessment
Astronaut Individual Assessment
30
30
25
Astronaut Data
Plot 1 Regr
Biodose, cGy-Eq
Biodose, cGy-Eq
25
20
15
10
20
15
10
5
5
0
0
0
5
10
Effective Dose, cSv
15
Astronaut Data
Plot 1 Regr
0
5
10
Effective Dose, cSv
Effective Dose = Dbadge x Qave x ηtissue
Q, η, and TLD correction from HZETRN/QMSFRG models
15
Clonal Aberrations from ISS
• Defined as balanced aberrations that have clonally
expanded in vivo, resulting in a population of cells (3 or
more) with identical rearrangements
• Clones may results in over estimation of damage
• ISS results indicate clones may be more prevalent than
has been reported in the literature, especially for healthy
individuals with little or not radiation exposure.
• Yields are not be stable with time.
– This indicates that careful screening and/or multiple sampling
required for biodosimetry.
• Clones are involved in the process of cell transformation,
so may be associated with increased risk of cancer.
Summary of ISS results
• Increase in total exchanges found for all long
duration flights
– Complex aberration increase not significant
• Good correlation of population average biodose
with Effective dose from physics
– Large differences occur for individual base
comparison
• Clonal aberrations are observed in several
astronauts both pre- and post-flight
– Found to decay in follow-up samples
• Yields of aberrations decay in most follow-up
samples for apparently stable aberrations
Biomarkers for NASA Missions?
Biomarker Limitations include
•
Current uncertainties in risk estimates preclude proper assessment
of need for biomarkers
– Mechanisms of risk pathways are not sufficiently understood
•
Large number of risks of concern is a significant issue
– Compounded by large number of tissues of concern and
heterogeneity within tissues
•
•
•
•
Possible differences in disease etiology between background, low
LET, and high LET cancer
Many methodologies use averages over >103 cells making
interpretation of results limited (cDNA, micro-RNA, protein arrays)
Statistical limitations
Kinetics of damage induction, decay, and propagation
SRP Research focus in near-term
•
•
What are the mechanisms of risk pathways
Reducing uncertainties in risk projection models
National Aeronautics and Space Administration
Categories of Radiation Risk
Four categories of risk of concern to NASA:
– Carcinogenesis (morbidity and mortality
risk)
– Acute and Late Central Nervous System
(CNS) risks
9 immediate or late functional changes
– Chronic & Degenerative Tissue Risks
9 cataracts, heart-disease, etc.
Lens changes in cataracts
– Acute Radiation Risks – sickness or death
Differences in biological damage of heavy
nuclei in space with x-rays, limits Earth-based
data on health effects for space applications
– New knowledge on risks must be
obtained
– Confounds biomarker development and
interpretation
First experiments for leukemia induction with GCR
Tissues in Overall Radiation Risk
There are large
differences
In the oncogenes,
and mechanisms
of cancer
progression
across the many
tissue types and
within tissue types
that contribute to
radiation
carcinogenesis
SRP Biomarker studies
•
•
•
•
Microsatellite mutations and instability (J. Bacher)
Micro-RNAs (L. Smilenov)
γH2AX and individual sensitivity (J. Bedford)
Immunohistochemistry for a variety of markers
(several groups)
• Advanced FISH techniques
– mBAND (H. Wu)
– RxFISH, MFISH (several groups)
• Flow cytometry (several groups)
• cDNA or protein arrays (several groups)
RX-FISH plus Telomere painting using PNA probes allows
positive identification of the deletion in chromosome 1 as
terminal and the deletion in chromosome 11 as interstitial.
Durante, George, Cucinotta, 2006
Damage at 3rd or Later Division
0.4
0.2
Interchanges
A
0.35
35
Intrachanges
B
30
1 GeV/u Iron
0.15
0.25
0.2
0.15
0.1
25
RBEmax
Intrachanges/cell
Translocations/cell
0.3
0.1
0.05
Gamma rays
Fe-ions
20
15
10
0.05
5
0
0
0
0.5
1
1.5
2
2.5
3
3.5
0
0.5
1
Dose (Gy)
1.5
2
2.5
3
3.5
0
Dose (Gy)
0
0.25
Terminal deletions/cell
Complex exchanges/cell
0.2
0.1
0.1
0.05
0.05
0
0
0
0.5
1
1.5
2
Dose (Gy)
2.5
3
3.5
3
Terminal deletions
D
Complexes
0.15
2
No. Cell Divisions
0.15
C
1
0
0.5
1
1.5
2
Dose (Gy)
2.5
3
3.5
RBE’s for Interchanges
at first division are
highly correlated with
Quality Factor vs LET;
However do not appear
to be transmissible at
high frequency
4
Mutations in DNA repeats as a Biomarker
LET Dependence of
Biomarkers
• Total exchanges have
a close correlation with
Q(L), however the LET
dependence for cancer
or other late effects is
now well known
• DNA damage and
micro-satellite
mutations (J. Bacher)
have low RBE’s <2
• RBE for Cancer is?
Microsatellites: 1-6bp short tandem repeats
A
A
AA
–
Mono-nucleotide repeat:
–
Di-nucleotide repeat:
CA
CA
–
Tri-nucleotide repeat:
GAA
GAA
–
Tetra-nucleotide repeats:
–
Penta-nucleotide repeats:
A
A
CA
CA
AA
CA
CA
GAA
GAA
GATA
GATA
CAAAA
CAAAA
AA
A
A
CA
CA
GAA
GAA
GATA
GATA
CAAAA
CAAAA
CA
CA
GAA
GAA
GATA
GATA
CAAAA
CAAAA
• Overall length <500bp, easy to PCR
• Mutation rates 100-1000x higher than non-repetitive DNA
Iron vs. gamma
0.014
Iron
Gamma
0.012
y 0.010
c
n
e
u
q 0.008
e
r
F
n 0.006
io
t
ta
u
M 0.004
0.002
0.000
0.0
0.2
0.4
0.6
0.8
Dose (Gy)
RBE = 1.4 @ 1 Gy, B6 blood cells
1.0
1.2
miRNAs as a Biomarker
•
•
•
New Award of L. Smilenov
(Columbia)
Micro-RNA’s are small
non-protein coding genes,
coding micron-RNA’s
Up to 30% of the Human
genes involve some level
of control my miRNAs
– A single miRNA may bind
1000 targets
•
•
Application of miRNA is
similar to cDNA arrays and
also can be performed
using flow cytometry
Sminelov will study miRNA
as a measure of damage
and look for radiation
quality dependence of
miRNA expression
O’Donnell et al., Nature, 2005
γH2AX and Radiation Sensitivity
•
The histone variant, H2AX has been shown to
become phosphorylated after double strandbreak induction
γH2AX kinases are ATM, ATR, and DNAPKcs
•
•
Residual gH2AX are a sign of instability or
repair defects that contribute to cancer risk
J. Bedford has been selected to study
relationship between residual γH2AX foci and
individual risk
– Bedford has shown that genetic
dependence on residual foci is enhanced
using low dose-rate irradiation
– Earlier studies using 2 Gy gamma were
made by Peggy Olive
•
New studies will look at diverse set of
genotypes and space radiation components
Desai et al, Rad Res
NHEJ Reaction Pathway
[C0]
k2
k1
[C2P]
[C2]
Ionizing Radiation
kP1
[C1]
[C2PP]
kP2j
kDc
k3j
[C3]
DSBj
Ku70/80
DNA-PKcs
LigIV/XRCC4
kPγ ([C2P]+[C2PP])
γH2AX
H2AX
kPγ
[ATMD]
kMRN
[ATM]
kDγ
H2AX
[ATMP]
kdimer
kPauto
[ATMP]
J=class of DSB
Quantifying Radiation Sensitivity
• The large number of radiation sensitivity studies
supported by SRP suggests an integrative approach is
needed
• The JSC Risk Assessment Project has developed a
quantitative approach to this problem using Systems
Biology
• Metabolic control coefficients characterize effects of
Enzymatic steps on a “Flux” (Kacser and Burns):
CkF=(k/F)dF/dk;
Σ CkF=1
γH2AX Foci and System Responses
‰ Properties of gH2AX response curves
have been associated with important
biological outcomes
– Radiation sensitivity
– Genomic instability
DSB
Replication
Stress
Ku70/80
MRN
ATRIP
‰ Signaling time and duration, measure
γH2AX persistence for different
radiation qualities/doses
‰ Signal time total amount kinase
activated
τγ
tγ (t )dt
∫
=
∫ γ (t )dt
DNA-PKcs
ATM
ATR
γH2AX
‰ γH2AX signal duration measure of
variance about the mean
t γ (t )dt
∫
Q=
∫ γ (t )dt
2
Dγ
=
Qγ − τ γ
2
with
This approach allows for the
pathway steps which make
the largest contribution to
radiation sensitivity to be
ranked
γH2AX Foci- Time Course and Dose
Response (Cucinotta et al – in press)
HF19 Cells 1 Gy
Human TG cells
75
Rejoining
25
γH2AX Foci/Cell
Ave. Number of Foci per Cell
30
20
γH2AX
15
10
60
30 min post IR
45
30
2 hrs post IR
15
5
0
0
2
4
6
8
Repair time, hrs
Expts of Leatherbarrow et al. (2006)
0
0.0
0.5
1.0
1.5
2.0
2.5
Dose, Gy
Expts of Short et al. Rad Res (2005)
3.0
National Aeronautics and Space Administration
Summary
Biomarkers of exposure provide adequate characterization
of doses for space missions with CA preferred method
Biomarkers of Risk are under development, however until
the mechanisms of risk are fully elucidated a biomarker
for risk projection is not feasible
Collaborators
Biodosimetry
Kerry George, Todd Elliott, Veronica Willingham,
Marco Durante
γH2AX Studies
H Wu, N Desai, P O’Neill (MRC), J Anderson (MRC),
E Davis, J Harper (MRC), J Pluth (LBL), M Whalen
(LBL)
Risk Assessment Project
A. Ponomarev, J. Pluth (LBL), J. Huff, H. Nikjoo, S. Hu,
C. Carra, M Whalen (LBL)