A combined experimental-computational approach uncovers a role for the Golgi matrix protein Giantin in breast cancer progression
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Published:2023-04-17
Issue:4
Volume:19
Page:e1010995
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ISSN:1553-7358
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Container-title:PLOS Computational Biology
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language:en
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Short-container-title:PLoS Comput Biol
Author:
Ghannoum SalimORCID,
Fantini Damiano,
Zahoor Muhammad,
Reiterer Veronika,
Phuyal Santosh,
Leoncio Netto Waldir,
Sørensen ØysteinORCID,
Iyer ArvindORCID,
Sengupta Debarka,
Prasmickaite Lina,
Mælandsmo Gunhild Mari,
Köhn-Luque Alvaro,
Farhan Hesso
Abstract
Our understanding of how speed and persistence of cell migration affects the growth rate and size of tumors remains incomplete. To address this, we developed a mathematical model wherein cells migrate in two-dimensional space, divide, die or intravasate into the vasculature. Exploring a wide range of speed and persistence combinations, we find that tumor growth positively correlates with increasing speed and higher persistence. As a biologically relevant example, we focused on Golgi fragmentation, a phenomenon often linked to alterations of cell migration. Golgi fragmentation was induced by depletion of Giantin, a Golgi matrix protein, the downregulation of which correlates with poor patient survival. Applying the experimentally obtained migration and invasion traits of Giantin depleted breast cancer cells to our mathematical model, we predict that loss of Giantin increases the number of intravasating cells. This prediction was validated, by showing that circulating tumor cells express significantly less Giantin than primary tumor cells. Altogether, our computational model identifies cell migration traits that regulate tumor progression and uncovers a role of Giantin in breast cancer progression.
Funder
Kreftforeningen
Norwegian Research Council
Anders Jahre Foundation
Rakel og Otto Kristian Bruun’s Legat
Austrian Science Foundation
center for research-based-innovation BigInsight funded by the Research Council of Norway
Research Council of Norway
Horizon 2020
UiO:Life Science convergent environment PerCaThe
Publisher
Public Library of Science (PLoS)
Subject
Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics
Reference71 articles.
1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.;F Bray;CA: a cancer journal for clinicians.,2018
2. Breast cancer: insights into risk factors, pathogenesis, diagnosis and management.;AM Kabel;Journal of Cancer Research and Treatment.,2015
3. Breast cancer metastasis;OJ Scully;Cancer Genomics-Proteomics,2012
4. Breast cancer as a systemic disease: a view of metastasis;AJ Redig;Journal of internal medicine,2013
5. Models of epithelial–mesenchymal transition.;A Eger;Drug Discovery Today: Disease Models.,2005
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