Global genetic response in a cancer cell: self-organized coherent expression dynamics.
Understanding the basic mechanism of the spatio-temporal self-control of genome-wide gene expression engaged with the complex epigenetic molecular assembly is one of major challenges in current biological science. In this study, the genome-wide dynamical profile of gene expression was analyzed for MCF-7 breast cancer cells induced by two distinct ErbB receptor ligands: epidermal growth factor (EGF) and heregulin (HRG), which drive cell proliferation and differentiation, respectively. We focused our attention to elucidate how global genetic responses emerge and to decipher what is an underlying principle for dynamic self-control of genome-wide gene expression. The whole mRNA expression was classified into about a hundred groups according to the root mean square fluctuation (rmsf). These expression groups showed characteristic time-dependent correlations, indicating the existence of collective behaviors on the ensemble of genes with respect to mRNA expression and also to temporal changes in expression. All-or-none responses were observed for HRG and EGF (biphasic statistics) at around 10-20 min. The emergence of time-dependent collective behaviors of expression occurred through bifurcation of a coherent expression state (CES). In the ensemble of mRNA expression, the self-organized CESs reveals distinct characteristic expression domains for biphasic statistics, which exhibits notably the presence of criticality in the expression profile as a route for genomic transition. In time-dependent changes in the expression domains, the dynamics of CES reveals that the temporal development of the characteristic domains is characterized as autonomous bistable switch, which exhibits dynamic criticality (the temporal development of criticality) in the genome-wide coherent expression dynamics. It is expected that elucidation of the biophysical origin for such critical behavior sheds light on the underlying mechanism of the control of whole genome.
Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan; Systems Biology Program, School of Media and Governance, Keio University, Fujisawa, Japan.
Masa
M
Tsuchiya
Graduate School of Frontier Science, The University of Tokyo, Kashiwa, Japan.
Midori
M
Hashimoto
Nanosystem Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan.
Yoshiko
Y
Takenaka
Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Ikuko N
IN
Motoike
Faculty of Life and Medical Sciences, Doshisha University, Kyotanabe, Japan.
Kenichi
K
Yoshikawa
D000465:Algorithms; D019295:Computational Biology; D004815:Epidermal Growth Factor / Q000378:metabolism; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D055106:Genome-Wide Association Study; D023281:Genomics; D006801:Humans; D061986:MCF-7 Cells; D008957:Models, Genetic; D015233:Models, Statistical; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism*; D020890:Neuregulin-1 / Q000378:metabolism; D017434:Protein Structure, Tertiary; D012333:RNA, Messenger / Q000378:metabolism; D013997:Time Factors
C094131:NRG1 protein, human; D020890:Neuregulin-1; D012333:RNA, Messenger; D004815:Epidermal Growth Factor