Now showing 1 - 2 of 2
  • Publication
    Signalling mechanisms regulating phenotypic changes in breast cancer cells
    In MCF-7 breast cancer cells epidermal growth factor (EGF) induces cell proliferation, whereas heregulin (HRG)/neuregulin (NRG) induces irreversible phenotypic changes accompanied by lipid accumulation. Although these changes in breast cancer cells resemble processes that take place in the tissue, there is no understanding of signalling mechanisms regulating it. To identify molecular mechanisms mediating this cell-fate decision process, we applied different perturbations to pathways activated by these growth factors. The results demonstrate that phosphoinositide 3 (PI3) kinase (PI3K) and mammalian target of rapamycin (mTOR) complex (mTORC)1 activation is necessary for lipid accumulation that can also be induced by insulin, whereas stimulation of the extracellular-signal-regulated kinase (ERK) pathway is surprisingly dispensable. Interestingly, insulin exposure, as short as 4 h, was sufficient for triggering the lipid accumulation, whereas much longer treatment with HRG was required for achieving similar cellular response. Further, activation patterns of ATP citratelyase (ACLY), an enzyme playing a central role in linking glycolytic and lipogenic pathways, suggest that lipids accumulated within cells are produced de novo rather than absorbed from the environment. In the present study, we demonstrate that PI3K pathway regulates phenotypic changes in breast cancer cells, whereas signal intensity and duration is crucial for cell fate decisions and commitment. Our findings reveal that MCF-7 cell fate decisions are controlled by a network of positive and negative regulators of both signalling and metabolic pathways.
      351Scopus© Citations 9
  • Publication
    Catching transcriptional regulation by thermostatistical modeling
    Gene expression is frequently regulated by multiple transcription factors (TFs). Thermostatistical methods allow for a quantitative description of interactions between TFs, RNA polymerase and DNA, and their impact on the transcription rates. We illustrate three different scales of the thermostatistical approach: the microscale of TF molecules, the mesoscale of promoter energy levels and the macroscale of transcriptionally active and inactive cells in a cell population. We demonstrate versatility of combinatorial transcriptional activation by exemplifying logic functions, such as AND and OR gates. We discuss a metric for cell-to-cell transcriptional activation variability known as Fermi entropy. Suitability of thermostatistical modeling is illustrated by describing the experimental data on transcriptional induction of NFκB and the c-Fos protein.
      440Scopus© Citations 8