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Cellular regulatory networks are not static, but continuously reconfigure in response to stimuli via alterations in protein abundance and confirmation. However, typical computational approaches treat them as static interaction networks derived from a single time point. Here, we provide methods for learning the dynamic modulation of relationships between proteins from static single-cell data. We demonstrate our approach using TGFß induced epithelial-to-mesenchymal transition (EMT) in murine breast cancer cell line, profiled with mass cytometry. We take advantage of the asynchronous rate of transition to EMT in the data and derive a pseudotime EMT trajectory. We propose methods for visualizing and quantifying time-varying edge behavior over the trajectory, and a metric of edge dynamism to predict the effect of drug perturbations on EMT.
High grade serous ovarian cancer (HGSC) is the most common and deadly type of ovarian cancer, largely due to difficulties in early diagnosis and rapid metastasis throughout the peritoneal cavity. Previous studies have shown that expression of Notch3 correlates with worse prognosis and increased tumorigenic cell behaviors in HGSC. We investigated the mechanistic role of Notch3 in a model of metastatic ovarian cancer using the murine ovarian surface epithelial cell line, ID8 IP2. Notch3 was activated in ID8 IP2 cells via expression of the Notch3 intracellular domain (Notch3IC). Notch3IC ID8 IP2 cells injected intraperitoneally caused accelerated ascites and reduced survival compared to control ID8 IP2, particularly in early stages of disease. We interrogated downstream targets of Notch3IC in ID8 IP2 cells by RNA sequencing and found significant induction of genes that encode adhesion and extracellular matrix proteins. Notch3IC ID8 IP2 showed increased expression of ITGA1 mRNA and cell-surface protein. Notch3IC-mediated increase of ITGA1 was also seen in two human ovarian cancer cells. Notch3IC ID8 IP2 cells showed increased adhesion to collagens I and IV in vitro. We propose that Notch3 activation in ovarian cancer cells causes increased adherence to collagen-rich peritoneal surfaces. Thus, the correlation between increased Notch3 signaling and poor prognosis may be influenced by increased metastasis of HGSC via increased adherence of disseminating cells to new metastatic sites in the peritoneum.
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