Actin polymerization and assembly into stress fibers (SFs) is central to many cellular processes. However, how SFs form in response to the mechanical interaction of cells with their environment is not fully understood. Here we have identified Piezo2 mechanosensitive cationic channel as a transducer of environmental physical cues into mechanobiological responses. Piezo2 is needed by brain metastatic cells from breast cancer (MDA-MB-231-BrM2) to probe their physical environment as they anchor and pull on their surroundings or when confronted with confined migration through narrow pores. Piezo2-mediated Ca²⁺ influx activates RhoA to control the formation and orientation of SFs and focal adhesions (FAs). A possible mechanism for the Piezo2-mediated activation of RhoA involves the recruitment of the Fyn kinase to the cell leading edge as well as calpain activation. Knockdown of Piezo2 in BrM2 cells alters SFs, FAs, and nuclear translocation of YAP; a phenotype rescued by overexpression of dominant-positive RhoA or its downstream effector, mDia1. Consequently, hallmarks of cancer invasion and metastasis related to RhoA, actin cytoskeleton, and/or force transmission, such as migration, extracellular matrix degradation, and Serpin B2 secretion, were reduced in cells lacking Piezo2. Significance The actin cytoskeleton is central to many cellular processes involving changes in cell shape, migration, and adhesiveness. Therefore, there is a great interest in the identification of the signaling pathways leading to the regulation of actin polymerization and assembly into stress fibers (SFs). However, to date it is not well understood how the mechanical interactions between cells and their environment activate the assembly of SFs. Here, we demonstrate that the mechanosensitive Piezo2 channel is required to sense physical cues from the environment to generate a calcium signal that maintains RhoA active and the formation and orientation of SFs and focal adhesions. Besides, this Piezo2-initiated signaling pathway has implications for different hallmarks of cancer invasion and metastasis.

TRPM7 senses hydraulic pressure and modulates cortical actomyosin to guide migrating cells towards the path of lower resistance.

Dorsoventral polarity directs confined cell migration mode and efficiency by tuning nuclear stiffness and RhoA activity.

Background: Primary progressive aphasia (PPA) is a neurodegenerative disorder characterized by a progressive decline of language functions. Its symptoms are grouped into three PPA variants: nonfluent PPA, logopenic PPA, and semantic PPA. Grammatical deficiencies differ depending on the PPA variant. Aims: This study aims to determine the differences between PPA variants with respect to part of speech (POS) production and to identify morphological markers that classify PPA variants using machine learning. By fulfilling these aims, the overarching goal is to provide objective measures that can facilitate clinical diagnosis, evaluation, and prognosis. Method and Procedure: Connected speech productions from PPA patients produced in a picture description task were transcribed, and the POS class of each word was estimated using natural language processing, namely, POS tagging. We then implemented a twofold analysis: (a) linear regression to determine how patients with nonfluent PPA, semantic PPA, and logopenic PPA variants differ in their POS productions and (b) a supervised classification analysis based on POS using machine learning models (i.e., random forests, decision trees, and support vector machines) to subtype PPA variants and generate feature importance (FI). Outcome and Results: Using an automated analysis of a short picture description task, this study showed that content versus function words can distinguish patients with nonfluent PPA, semantic PPA, and logopenic PPA variants. Verbs were less important as distinguishing features of patients with different PPA variants than earlier thought. Finally, the study showed that among the most important distinguishing features of PPA variants were elaborative speech elements, such as adjectives and adverbs.