NASA grant. Lynn Hlatky PI. 2004-09. Ray Sachs
Associate Director
Abstract
We will improve solid tumor risk estimation for astronauts.
Improvements will be based in large part on analyzing effects
of our high energy iron ion and proton irradiation of
sophisticated modern mouse models. Our mathematical risk
modeling will use standard computational approaches which
minimize theoretical assumptions and also use minimally
parametrized, biologically-based carcinogenesis models
capable of interrelating epidemiological data, animal
experiments, and in vitro radiobiology. In our experiments
and our computational analyses, special emphasis will be
placed on tumor promotion and progression, as influenced by
intercellular signaling among nearby tissues.
The modern mouse models are highly suitable for the program.
One is a genetically engineered lung tumor model from Tyler
Jacks' laboratory with a molecular switch capable of
activating tumors on demand. Another is a deconstructable
human breast tumor xenograft model recently introduced in the
Weinberg laboratory at the Whitehead Institute. Our team has
extensive experience with both. Because of special features
of these models and a thyroid tumor model to be developed,
comparatively few mice will be needed and study times can be
comparatively short.
Whole organism-, tissue- cell-, and molecular-level endpoints
will be used to measure radiation response. For example, in
addition to basic cancer effects -- e.g. radiation influence
on latency periods or the numbers of dysplastic and frankly
neoplastic sites -- we will also study myc/ras endpoints??,
use matrix and clustering computer algorithms for analyzing
transcriptome data, and interpret chromosome aberrations
scored with mFISH or SKY using our established computer
simulation software.
Importantly for our emphasis on intercellular signaling as a
key aspect of carcinogenesis, we will assay not only tumor
cells but also tumor-associated stroma, associated
endothelial cells, and circulating endothelial cells; such
tissues can help support or repress tumor cells, and are in
certain ways simpler to analyze. An experimental and
theoretical emphasis on tumor progression is also planned,
based on the fact that this step in carcinogenesis has
hitherto received less attention from radiation risk modelers
than other steps but is likely to be at least as important.
There is now strong evidence that microscopic dormant
neoplastic sites are much more common in adults than usually
assumed and that their progression can be accelerated by
radiation. Radiation shortening of latency periods could thus
be a key component of solid tumor risk for middle aged
astronauts.
A tightly-knit interdisciplinary team, consisting of
biophysicists, cancer clinicians, cancer biologists,
molecular biologists and applied mathematicians is in place
to carry out our program. Director L. Hlatky, Associate
Director R. Sachs and Project leaders J. Folkman, P. Huber,
and P. Hahnfeldt will carry out 5 closely interrelated
Projects, as follows: (1) mouse models for assessing
carcinogenesis risk; (2) HZE and low LET irradiation; (3)
radiation transcriptome analyses; (4) quantitative chromosome
aberration analysis; and (5) quantitative estimation of solid
tumor risk. Project (5) will integrate the first four
Projects as well as drawing on results in the literature, and
is designed to reduce the uncertainties in risk estimates for
astronauts.
NASA grant project 4. Ray Sachs PI. 2004-09.
Abstract
Project 4. Chromosome Aberration Analyses (PI R. Sachs)
Project 4. Specific Aims
Chromosome aberrations are closely associated with cancers.
The relation is relatively well understood for blood-cell
cancers, where aberrations are known to be causative in
certain cases [Greaves 2004]. For solid tumors, including
breast, there are also important relations [Albertson et al.
2003; Berrieman et al. 2004; Mitelman et al. 2004] but
results to date have not been as informative as for
haematopoietic cancers. Reasons why solid tumors are less
amenable to analysis include the extreme complexity of their
karyotypes, genomic instability often being present, and
predominance of large-scale DNA deletions or additions
(including duplications) over balanced translocations.
Project 4 will conduct biologically-based mechanistic
computer analyses of our data on radiogenic aberrations in
tumors (Project 2); we will design new software, based on
preliminary studies in mathematical graph theory,
specifically to deal with large scale deletions and
additions. We will also use the novel and promising approach
of analyzing aberrations in associated stromal and
endothelial cells. These cells collaborate, via
intercellular signaling, in carcinogenesis, but are expected
to have less complicated, more informative karyotypes.
Aberration data should be systematically related to gene
expression data (Project 3), which give more sensitive and
more detailed probes of radiation effects. Such a comparison
is needed because so much is known about geometry and
molecular pathways of aberration formation, as well as the
relation of aberrations to cancers, while gene expression
data is now available in overwhelming intricacy that calls
for every interpretation tool we can bring to bear. We will
develop software to compare aberration and array data at low
and high LET, and elucidate the implications, especially
implications for intercellular signals that affect tumor
growth and radiation response.
Specific aims are:
1. Use SKY data and our established computer programs to
study the spectrum and complexity of radiation-induced
aberrations in endothelial and stromal cells that support and
communicate with epithelial tumor cells (compare Projects 1
and 2). We believe extra aberration complexity will
correlate with acceleration of tumor development caused by
disruption of normal signaling patterns.
2. Study human breast tumor xenographs after various
irradiation protocols. Extend current aberration software to
include large-scale DNA deletions and additions, important in
the highly complex, unstable karyotypes of solid tumor cells.
Extend graph-theoretical models to characterize sequences of
successive transmissible karyotype changes, as can occur in
chromosomal instability.
3. Use aberration (Project 2) and gene expression (Project
3) data to characterize radiation response in terms of gene
geometrical clustering in cell nuclei.
NASA