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RhoA-ROCK Competes with YAP to Regulate Amoeboid Breast Cancer Cell Migration in Response to Lymphatic-like Flow

Overview
Journal FASEB Bioadv
Specialty Biology
Date 2022 May 6
PMID 35520391
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Abstract

Lymphatic drainage generates force that induces prostate cancer cell motility via activation of Yes-associated protein (YAP), but whether this response to fluid force is conserved across cancer types is unclear. Here, we show that shear stress corresponding to fluid flow in the initial lymphatics modifies taxis in breast cancer, whereas some cell lines use rapid amoeboid migration behavior in response to fluid flow, a separate subset decrease movement. Positive responders displayed transcriptional profiles characteristic of an amoeboid cell state, which is typical of cells advancing at the edges of neoplastic tumors. Regulation of the HIPPO tumor suppressor pathway and YAP activity also differed between breast subsets and prostate cancer. Although subcellular localization of YAP to the nucleus positively correlated with overall velocity of locomotion, YAP gain- and loss-of-function demonstrates that YAP inhibits breast cancer motility but is outcompeted by other pro-taxis mediators in the context of flow. Specifically, we show that RhoA dictates response to flow. GTPase activity of RhoA, but not Rac1 or Cdc42 Rho family GTPases, is elevated in cells that positively respond to flow and is unchanged in cells that decelerate under flow. Disruption of RhoA or the RhoA effector, Rho-associated kinase (ROCK), blocked shear stress-induced motility. Collectively, these findings identify biomechanical force as a regulator amoeboid cell migration and demonstrate stratification of breast cancer subsets by flow-sensing mechanotransduction pathways.

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RhoA-ROCK competes with YAP to regulate amoeboid breast cancer cell migration in response to lymphatic-like flow.

Mohammadalipour A, Diaz M, Livingston M, Ewere A, Zhou A, Horton P FASEB Bioadv. 2022; 4(5):342-361.

PMID: 35520391 PMC: 9065582. DOI: 10.1096/fba.2021-00055.

References
1.
Schmidt A, Hall A . Guanine nucleotide exchange factors for Rho GTPases: turning on the switch. Genes Dev. 2002; 16(13):1587-609. DOI: 10.1101/gad.1003302. View

2.
Jacob A, Prekeris R . The regulation of MMP targeting to invadopodia during cancer metastasis. Front Cell Dev Biol. 2015; 3:4. PMC: 4313772. DOI: 10.3389/fcell.2015.00004. View

3.
Araki H, Knapp C, Tsai P, Print C . GeneSetDB: A comprehensive meta-database, statistical and visualisation framework for gene set analysis. FEBS Open Bio. 2013; 2:76-82. PMC: 3642118. DOI: 10.1016/j.fob.2012.04.003. View

4.
Cantelli G, Orgaz J, Rodriguez-Hernandez I, Karagiannis P, Maiques O, Matias-Guiu X . TGF-β-Induced Transcription Sustains Amoeboid Melanoma Migration and Dissemination. Curr Biol. 2015; 25(22):2899-914. PMC: 4651903. DOI: 10.1016/j.cub.2015.09.054. View

5.
Liu R, Holik A, Su S, Jansz N, Chen K, Leong H . Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. Nucleic Acids Res. 2015; 43(15):e97. PMC: 4551905. DOI: 10.1093/nar/gkv412. View