Speaker
Prof.
Sui Huang
(Institute for Systems Biology)
Description
The transition from one cell phenotype to another represents
a non-genetic (mutation-less) change of phenotype and plays
a central role not only in metazoan development
(differentiation) but also in cancer. From a systems
dynamics point of view such a (typically quasi-discrete)
“switch” of a cell in the stable steady state S(A) to state
S(B) can be formalized as a transition between
high-dimensional attractor states with respect to the
network state S(t)=[x_1(t), x_2(t), ..x_N(t)] where x_i(t)
is the expression level gene i of the gene network that
consists of N genes and drives the transition. Such
elementary state transition processes, however, are not
simply first-order probabilistic transition as measurements
in living cells reveal, but exhibit interesting kinetics.
Notably, tissues and tumors consist of populations of cells
which, even if they are clonal (isogenic), exhibit a complex
phenotype dynamics that is not described by an ensemble of
replicates of identical cells. By contrast, cell population
level state transitions are influenced by stochastic
cell-cell variability in transition rates, by cell-cell
interactions (cooperation) and by differential growth rates
between the states. These features give rise to non-trivial,
rarely considered dynamics of phenotype change. In this talk
I will emphasize the experimental observables and show
examples of cell phenotype switching and counterintuitive
properties. The goal is to provide physicists a “feel” of
the state–of-the-art in experimental biology of mammalian
cell dynamics. I will discuss the profound implications of
cell state transitions for understanding cancer as a disease
of quantitative cell population dynamics rather than
qualitative genetics, as commonly thought. This is important
at a time when (in the U.S.) broad governmental efforts to
involve physicists in cancer research are underway in an
attempt to bring in fresh ideas and lead us out of the
stalemate in the war on cancer.
Primary author
Prof.
Sui Huang
(Institute for Systems Biology)
