Prioritizing drug targets by perturbing biological network response functions.

Therapeutic interventions are designed to perturb the function of a biological system. However, there are many types of proteins that cannot be targeted with conventional small molecule drugs. Accordingly, many identified gene-regulatory drivers and downstream effectors are currently undruggable. Drivers and effectors are often connected by druggable signaling and regulatory intermediates. Methods to identify druggable intermediates therefore have general value in expanding the set of targets available for hypothesis-driven validation. Here we identify and prioritize potential druggable intermediates by developing a network perturbation theory, termed NetPert, for response functions of biological networks. Dynamics are defined by a network structure in which vertices represent genes and proteins, and edges represent gene-regulatory interactions and protein-protein interactions. Perturbation theory for network dynamics prioritizes targets that interfere with signaling from driver to response genes. Applications to organoid models for metastatic breast cancer demonstrate the ability of this mathematical framework to identify and prioritize druggable intermediates. While the short-time limit of the perturbation theory resembles betweenness centrality, NetPert is superior in generating target rankings that correlate with previous wet-lab assays and are more robust to incomplete or noisy network data. NetPert also performs better than a related graph diffusion approach. Wet-lab assays demonstrate that drugs for targets identified by NetPert, including targets that are not themselves differentially expressed, are active in suppressing additional metastatic phenotypes.

Coordination of Receptor Tyrosine Kinase Signaling and Interfacial Tension Dynamics Drives Radial Intercalation and Tube Elongation.

We sought to understand how cells collectively elongate epithelial tubes. We first used 3D culture and biosensor imaging to demonstrate that epithelial cells enrich Ras activity, phosphatidylinositol (3,4,5)-trisphosphate (PIP3), and F-actin to their leading edges during migration within tissues. PIP3 enrichment coincided with, and could enrich despite inhibition of, F-actin dynamics, revealing a conserved migratory logic compared with single cells. We discovered that migratory cells can intercalate into the basal tissue surface and contribute to tube elongation. We then connected molecular activities to subcellular mechanics using force inference analysis. Migration and transient intercalation required specific and similar anterior-posterior ratios of interfacial tension. Permanent intercalations were distinguished by their capture at the boundary through time-varying tension dynamics. Finally, we integrated our experimental and computational data to generate a finite element model of tube elongation. Our model revealed that intercalation, interfacial tension dynamics, and high basal stress are together sufficient for mammary morphogenesis.

Non-straight cell edges are important to invasion and engulfment as demonstrated by cell mechanics model.

Computational models of cell-cell mechanical interactions typically simulate sorting and certain other motions well, but as demands on these models continue to grow, discrepancies between the cell shapes, contact angles and behaviours they predict and those that occur in real cells have come under increased scrutiny. To investigate whether these discrepancies are a direct result of the straight cell-cell edges generally assumed in these models, we developed a finite element model that approximates cell boundaries using polylines with an arbitrary number of segments. We then compared the predictions of otherwise identical polyline and monoline (straight-edge) models in a variety of scenarios, including annealing, single- and multi-cell engulfment, sorting, and two forms of mixing--invasion and checkerboard pattern formation. Keeping cell-cell edges straight influences cell motion, cell shape, contact angle, and boundary length, especially in cases where one cell type is pulled between or around cells of a different type, as in engulfment or invasion. These differences arise because monoline cells have restricted deformation modes. Polyline cells do not face these restrictions, and with as few as three segments per edge yielded realistic edge shapes and contact angle errors one-tenth of those produced by monoline models, making them considerably more suitable for situations where angles and shapes matter, such as validation of cellular force-inference techniques. The findings suggest that non-straight cell edges are important both in modelling and in nature.