| Task Description: |
We will improve solid tumor risk estimation for astronauts. Improvements will be based in large part on analyzing data resulting from our high-energy iron ion and proton in vivo irradiations. Our mathematical risk modeling will use standard computational approaches which minimize theoretical assumptions and also use minimally-parameterized, 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 various cell populations within the tumor (e.g. tumor cells, endothelial cells and stroma).
The in vivo models used are highly suitable for the program. These include the transgenic conditional k-ras lung tumor model from the Tyler Jacks’s laboratory that will allow the study of radiation modulation of all steps in carcinogenesis. These mice have a recombinant adenovirus expressing Cre recombinase to induce k-ras expression which synchronizes tumor onset, allowing numerous tumors to develop simultaneously in the lungs. The number of tumors and rate as which they progress though the four stages of carcinogenesis (e.g. time-dependent ratio of hyperplastic to neoplastic lesions) can then be traced as a function of the timing, dose and quality of the radiation. We will also use dormant human breast tumor xenograft models which allow us to place particular emphasis on dissecting the progression stage of carcinogenesis. These in vivo models offer specific advantages: solid tumor sites of concern to NASA (lung, breast, and later thyroid) will be studied; middle-age mice will be used; and due to the nature of these models comparatively few mice will be needed and post-irradiation study times will be comparatively short.
In this Program we implement a multi-level approach with whole organism-, tissue- cell-, and molecular-level endpoints used to measure radiation response. For examples, in addition to radiation influence on latency periods or the time-dependent ratio of dysplastic versus frankly neoplastic lung lesions, we examine cell signaling, use matrix and clustering computer algorithms for analyzing transcriptome data, and interpret chromosome aberrations scored with mFISH/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 stromal and endothelial cells (including circulating endothelial cells). It is turning out that such tissues can help support or repress tumors (i.e. play a major role in promotion and progression), and due to the relative stability of their genomes they are simpler to analyze for radiation-induced DNA damage. 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, e.g. initiation, but is at least as important. There is now strong evidence that microscopic dormant neoplastic sites are far more prevalent in adults than previously 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, Director L. Hlatky, Associate Director R. Sachs along with the other Project leaders J. Folkman, P. Huber, and P. Hahnfeldt will carry out the 5 closely interrelated Projects: (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 data from the first four Projects as well as drawing on results from the literature. It will culminate in a composite radiation carcinogenesis model designed to reduce the uncertainties in risk estimates for astronauts by addressing cell interaction effects and including in the multi-step carcinogenesis analysis the overlooked step of progression. |
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