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      Cell, Isoform, and Environment Factors Shape Gradients and Modulate Chemotaxis

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          Abstract

          Chemokine gradient formation requires multiple processes that include ligand secretion and diffusion, receptor binding and internalization, and immobilization of ligand to surfaces. To understand how these events dynamically shape gradients and influence ensuing cell chemotaxis, we built a multi-scale hybrid agent-based model linking gradient formation, cell responses, and receptor-level information. The CXCL12/CXCR4/CXCR7 signaling axis is highly implicated in metastasis of many cancers. We model CXCL12 gradient formation as it is impacted by CXCR4 and CXCR7, with particular focus on the three most highly expressed isoforms of CXCL12. We trained and validated our model using data from an in vitro microfluidic source-sink device. Our simulations demonstrate how isoform differences on the molecular level affect gradient formation and cell responses. We determine that ligand properties specific to CXCL12 isoforms (binding to the migration surface and to CXCR4) significantly impact migration and explain differences in in vitro chemotaxis data. We extend our model to analyze CXCL12 gradient formation in a tumor environment and find that short distance, steep gradients characteristic of the CXCL12-γ isoform are effective at driving chemotaxis. We highlight the importance of CXCL12-γ in cancer cell migration: its high effective affinity for both extracellular surface sites and CXCR4 strongly promote CXCR4+ cell migration. CXCL12-γ is also more difficult to inhibit, and we predict that co-inhibition of CXCR4 and CXCR7 is necessary to effectively hinder CXCL12-γ-induced migration. These findings support the growing importance of understanding differences in protein isoforms, and in particular their implications for cancer treatment.

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          Most cited references62

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          A methodology for performing global uncertainty and sensitivity analysis in systems biology.

          Accuracy of results from mathematical and computer models of biological systems is often complicated by the presence of uncertainties in experimental data that are used to estimate parameter values. Current mathematical modeling approaches typically use either single-parameter or local sensitivity analyses. However, these methods do not accurately assess uncertainty and sensitivity in the system as, by default, they hold all other parameters fixed at baseline values. Using techniques described within we demonstrate how a multi-dimensional parameter space can be studied globally so all uncertainties can be identified. Further, uncertainty and sensitivity analysis techniques can help to identify and ultimately control uncertainties. In this work we develop methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models. We compare two specific types of global sensitivity analysis indexes that have proven to be among the most robust and efficient. Through familiar and new examples of mathematical and computer models, we provide a complete methodology for performing these analyses, in both deterministic and stochastic settings, and propose novel techniques to handle problems encountered during these types of analyses.
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            Molecular characterization of the tumor microenvironment in breast cancer.

            Here we describe the comprehensive gene expression profiles of each cell type composing normal breast tissue and in situ and invasive breast carcinomas using serial analysis of gene expression. Based on these data, we determined that extensive gene expression changes occur in all cell types during cancer progression and that a significant fraction of altered genes encode secreted proteins and receptors. Despite the dramatic gene expression changes in all cell types, genetic alterations were detected only in cancer epithelial cells. The CXCL14 and CXCL12 chemokines overexpressed in tumor myoepithelial cells and myofibroblasts, respectively, bind to receptors on epithelial cells and enhance their proliferation, migration, and invasion. Thus, chemokines may play a role in breast tumorigenesis by acting as paracrine factors.
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              Interstitial dendritic cell guidance by haptotactic chemokine gradients.

              Directional guidance of cells via gradients of chemokines is considered crucial for embryonic development, cancer dissemination, and immune responses. Nevertheless, the concept still lacks direct experimental confirmation in vivo. Here, we identify endogenous gradients of the chemokine CCL21 within mouse skin and show that they guide dendritic cells toward lymphatic vessels. Quantitative imaging reveals depots of CCL21 within lymphatic endothelial cells and steeply decaying gradients within the perilymphatic interstitium. These gradients match the migratory patterns of the dendritic cells, which directionally approach vessels from a distance of up to 90-micrometers. Interstitial CCL21 is immobilized to heparan sulfates, and its experimental delocalization or swamping the endogenous gradients abolishes directed migration. These findings functionally establish the concept of haptotaxis, directed migration along immobilized gradients, in tissues.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                24 April 2015
                2015
                : 10
                : 4
                : e0123450
                Affiliations
                [1 ]Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
                [2 ]Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
                [3 ]Department of Macromolecular Science and Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
                [4 ]Center for Molecular Imaging, Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
                [5 ]Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
                Washington University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SLC SPC ST GDL JJL. Performed the experiments: SLC SPC. Analyzed the data: SLC SPC GDL JJL. Contributed reagents/materials/analysis tools: ST GDL. Wrote the paper: SLC SPC GDL JJL.

                Article
                PONE-D-14-52041
                10.1371/journal.pone.0123450
                4409393
                25909600
                a07518c6-71f9-4486-be4b-7dd6603740e9
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 22 November 2014
                : 4 March 2015
                Page count
                Figures: 6, Tables: 1, Pages: 24
                Funding
                This work was supported by the United States National Institutes of Health Grants R01CA136553, R01CA142750, R21CA182333, and P50CA093990. Both S.L.C. and S.P.C. were supported on NSF Predoctoral Fellowship Project Grants # DGE 0718128 and # F031543, respectively. S.L.C. was also supported under a University of Michigan Rackham Merit Fellowship and S.P.C. was supported under an Advanced Proteome informatics of Cancer Training Grant # T32 CA140044. J.J.L. was supported by National Institutes of Health grants EB012579 and GM096040. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
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                All relevant data are within the paper and its Supporting Information files.

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