CdGAP is a talin-binding protein and a target of TGF-β signaling that promotes HER2-positive breast cancer growth and metastasis

Epithelial-to-mesenchymal transition (EMT) plays a crucial role in metastasis, which is the leading cause of death in breast cancer patients. Here, we show that Cdc42 GTPase-activating protein (CdGAP) promotes tumor formation and metastasis to lungs in the HER2-positive (HER2+) murine breast cancer model. CdGAP facilitates intravasation, extravasation, and growth at metastatic sites. CdGAP depletion in HER2+ murine primary tumors mediates crosstalk with a Dlc1-RhoA pathway and is associated with a transforming growth factor β (TGF-β)-induced EMT transcriptional signature. CdGAP is positively regulated by TGF-β signaling during EMT and interacts with the adaptor talin to modulate focal adhesion dynamics and integrin activation. Moreover, HER2+ breast cancer patients with high CdGAP mRNA expression combined with a high TGF-β-EMT signature are more likely to present lymph node invasion. Our results suggest CdGAP as a candidate therapeutic target for HER2+ metastatic breast cancer by inhibiting TGF-β and integrin/talin signaling pathways.

Polarity and mixed-mode oscillations may underlie different patterns of cellular migration

In mesenchymal cell motility, several migration patterns have been observed, including directional, exploratory and stationary. Two key members of the Rho-family of GTPases, Rac and Rho, along with an adaptor protein called paxillin, have been particularly implicated in the formation of such migration patterns and in regulating adhesion dynamics. Together, they form a key regulatory network that involves the mutual inhibition exerted by Rac and Rho on each other and the promotion of Rac activation by phosphorylated paxillin. Although this interaction is sufficient in generating wave-pinning that underscores cellular polarization comprised of cellular front (high active Rac) and back (high active Rho), it remains unclear how they interact collectively to induce other modes of migration detected in Chinese hamster Ovary (CHO-K1) cells. We previously developed a six-variable (6V) reaction-diffusion model describing the interactions of these three proteins (in their active/phosphorylated and inactive/unphosphorylated forms) along with other auxiliary proteins, to decipher their role in generating wave-pinning. In this study, we explored, through computational modeling and image analysis, how differences in timescales within this molecular network can potentially produce the migration patterns in CHO-K1 cells and how switching between migration modes could occur. To do so, the 6V model was reduced to an excitable 4V spatiotemporal model possessing three different timescales. The model produced not only wave-pinning in the presence of diffusion, but also mixed-mode oscillations (MMOs) and relaxation oscillations (ROs). Implementing the model using the Cellular Potts Model (CPM) produced outcomes in which protrusions in the cell membrane changed Rac-Rho localization, resulting in membrane oscillations and fast directionality variations similar to those observed experimentally in CHO-K1 cells. The latter was assessed by comparing the migration patterns of experimental with CPM cells using four metrics: instantaneous cell speed, exponent of mean-square displacement ([Formula: see text]-value), directionality ratio and protrusion rate. Variations in migration patterns induced by mutating paxillin's serine 273 residue were also captured by the model and detected by a machine classifier, revealing that this mutation alters the dynamics of the system from MMOs to ROs or nonoscillatory behaviour through variation in the scaled concentration of an active form of an adhesion protein called p21-Activated Kinase 1 (PAK). These results thus suggest that MMOs and adhesion dynamics are the key mechanisms regulating CHO-K1 cell motility.

Metabolic networks of the human gut microbiota

The human gut microbiota controls factors that relate to human metabolism with a reach far greater than originally expected. Microbial communities and human (or animal) hosts entertain reciprocal exchanges between various inputs that are largely controlled by the host via its genetic make-up, nutrition and lifestyle. The composition of these microbial communities is fundamental to supply metabolic capabilities beyond those encoded in the host genome, and contributes to hormone and cellular signalling that support the dynamic adaptation to changes in food availability, environment and organismal development. Poor functional exchange between the microbial communities and their human host is associated with dysbiosis, metabolic dysfunction and disease. This review examines the biology of the dynamic relationship between the reciprocal metabolic state of the microbiota-host entity in balance with its environment (i.e. in healthy states), the enzymatic and metabolic changes associated with its imbalance in three well-studied diseases states such as obesity, diabetes and atherosclerosis, and the effects of bariatric surgery and exercise.