Risks
associated with exposure to low doses of ionizing radiation
are highly uncertain. Recently considerably research effort
has been devoted to improve our understanding of biological
processes that control low dose radiation response. Unexpected
findings including bystander effects, cell killing, mutation,
and genomic instability have been characterized. Bystander
effects have shown that biological effects occur not only
in cells with irradiated nuclei but in cells where only the
cytoplasm was hit, as well as in “non-hit” neighbors
of irradiated cells. Early adaptive response can be induced
that reduces the response to a high dose of radiation following
a low dose. At very low doses some cells appear to be hypersensitive
to radiation.
A
multistage cancer model will be meshed with models of new
biological phenomena: genomic instability, adaptive response,
bystander effects, and low-dose hypersensitivity to help understand
the impact of these phenomena on radiation risk. The model
will also consider the influence of the cell cycle on these
observations.
These
phenomena will be incorporated into models of carcinogenesis
that include multiple events leading to the initiation of
cells and malignant conversion of cells. These multistage
clonal expansion (MSCE) models can easily be extended to incorporate
genomic instability, bystander effects, adaptive response
and low-dose hypersensitivity. Collaboration with experimentalists
and other modelers to focus on important features of these
phenomena while avoiding unnecessary details will be an important
part of this project.
A
hierarchy of biological archetypes will be useful in determining
parameters of these detailed models including cell cultures,
3D human cell clusters, cultured human tissues, and populations.
Mechanistic models of these phenomena will be optimized using
data from in vitro experiments. Combining these submodels
will make it possible to incorporate them as components of
in vivo models. Such modeling will make it possible to better
relate in vitro mechanistic studies to in vivo
observations.
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