Literature DB >> 29328778

Engineering Approaches to Study Cellular Decision Making.

Pamela K Kreeger1,2,3,4, Laura E Strong1, Kristyn S Masters1,4,5.   

Abstract

In their native environment, cells are immersed in a complex milieu of biochemical and biophysical cues. These cues may include growth factors, the extracellular matrix, cell-cell contacts, stiffness, and topography, and they are responsible for regulating cellular behaviors such as adhesion, proliferation, migration, apoptosis, and differentiation. The decision-making process used to convert these extracellular inputs into actions is highly complex and sensitive to changes both in the type of individual cue (e.g., growth factor dose/level, timing) and in how these individual cues are combined (e.g., homotypic/heterotypic combinations). In this review, we highlight recent advances in the development of engineering-based approaches to study the cellular decision-making process. Specifically, we discuss the use of biomaterial platforms that enable controlled and tailored delivery of individual and combined cues, as well as the application of computational modeling to analyses of the complex cellular decision-making networks.

Entities:  

Keywords:  cell–cell communication; extracellular matrix; growth factors; intracellular signaling; microfluidics

Mesh:

Substances:

Year:  2018        PMID: 29328778      PMCID: PMC6327838          DOI: 10.1146/annurev-bioeng-062117-121011

Source DB:  PubMed          Journal:  Annu Rev Biomed Eng        ISSN: 1523-9829            Impact factor:   9.590


  142 in total

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Journal:  Adv Drug Deliv Rev       Date:  2012-02-04       Impact factor: 15.470

2.  Cells Sensing Mechanical Cues: Stiffness Influences the Lifetime of Cell-Extracellular Matrix Interactions by Affecting the Loading Rate.

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Journal:  ACS Nano       Date:  2015-12-29       Impact factor: 15.881

3.  Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.

Authors:  Sean C Bendall; Erin F Simonds; Peng Qiu; El-ad D Amir; Peter O Krutzik; Rachel Finck; Robert V Bruggner; Rachel Melamed; Angelica Trejo; Olga I Ornatsky; Robert S Balderas; Sylvia K Plevritis; Karen Sachs; Dana Pe'er; Scott D Tanner; Garry P Nolan
Journal:  Science       Date:  2011-05-06       Impact factor: 47.728

Review 4.  Redefining Signaling Pathways with an Expanding Single-Cell Toolbox.

Authors:  Suzanne Gaudet; Kathryn Miller-Jensen
Journal:  Trends Biotechnol       Date:  2016-03-09       Impact factor: 19.536

5.  Stiff collagen matrices increase tumorigenic prolactin signaling in breast cancer cells.

Authors:  Craig E Barcus; Patricia J Keely; Kevin W Eliceiri; Linda A Schuler
Journal:  J Biol Chem       Date:  2013-03-24       Impact factor: 5.157

Review 6.  Cell-cell communication in the tumor microenvironment, carcinogenesis, and anticancer treatment.

Authors:  Björn L D M Brücher; Ijaz S Jamall
Journal:  Cell Physiol Biochem       Date:  2014-07-08

Review 7.  Mechanics, malignancy, and metastasis: the force journey of a tumor cell.

Authors:  Sanjay Kumar; Valerie M Weaver
Journal:  Cancer Metastasis Rev       Date:  2009-06       Impact factor: 9.264

8.  Myocardial Tissue Engineering With Cells Derived From Human-Induced Pluripotent Stem Cells and a Native-Like, High-Resolution, 3-Dimensionally Printed Scaffold.

Authors:  Ling Gao; Molly E Kupfer; Jangwook P Jung; Libang Yang; Patrick Zhang; Yong Da Sie; Quyen Tran; Visar Ajeti; Brian T Freeman; Vladimir G Fast; Paul J Campagnola; Brenda M Ogle; Jianyi Zhang
Journal:  Circ Res       Date:  2017-01-09       Impact factor: 17.367

9.  Modulation of matrix elasticity with PEG hydrogels to study melanoma drug responsiveness.

Authors:  Emi Y Tokuda; Jennifer L Leight; Kristi S Anseth
Journal:  Biomaterials       Date:  2014-02-22       Impact factor: 12.479

10.  Prolactin signaling through focal adhesion complexes is amplified by stiff extracellular matrices in breast cancer cells.

Authors:  Craig E Barcus; Patricia J Keely; Kevin W Eliceiri; Linda A Schuler
Journal:  Oncotarget       Date:  2016-07-26
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  7 in total

Review 1.  An overview of substrate stiffness guided cellular response and its applications in tissue regeneration.

Authors:  Bingcheng Yi; Qi Xu; Wei Liu
Journal:  Bioact Mater       Date:  2021-12-25

Review 2.  The Many Microenvironments of Ovarian Cancer.

Authors:  Hannah M Micek; Mike R Visetsouk; Andrew J Fleszar; Pamela K Kreeger
Journal:  Adv Exp Med Biol       Date:  2020       Impact factor: 2.622

3.  Interleukin 17 and senescent cells regulate the foreign body response to synthetic material implants in mice and humans.

Authors:  Liam Chung; David R Maestas; Andriana Lebid; Ashlie Mageau; Gedge D Rosson; Xinqun Wu; Matthew T Wolf; Ada J Tam; Isabel Vanderzee; Xiaokun Wang; James I Andorko; Hong Zhang; Radhika Narain; Kaitlyn Sadtler; Hongni Fan; Daniela Čiháková; Claude Jourdan Le Saux; Franck Housseau; Drew M Pardoll; Jennifer H Elisseeff
Journal:  Sci Transl Med       Date:  2020-04-15       Impact factor: 19.319

4.  Investigation of wound healing process guided by nano-scale topographic patterns integrated within a microfluidic system.

Authors:  Insu Lee; Daegyu Kim; Ga-Lahm Park; Tae-Joon Jeon; Sun Min Kim
Journal:  PLoS One       Date:  2018-07-26       Impact factor: 3.240

5.  Hypothesis: Caco-2 cell rotational 3D mechanogenomic turing patterns have clinical implications to colon crypts.

Authors:  Gen Zheng; Alexandr A Kalinin; Ivo D Dinov; Walter Meixner; Shengtao Zhu; John W Wiley
Journal:  J Cell Mol Med       Date:  2018-09-25       Impact factor: 5.310

6.  Insights From the Ecology of Information to Cancer Control.

Authors:  Christopher J Whelan; Stanislav S Avdieiev; Robert A Gatenby
Journal:  Cancer Control       Date:  2020 Jul-Aug       Impact factor: 3.302

7.  STIM1, STIM2, and PDI Participate in Cellular Fate Decisions in Low Energy Availability Induced by 3-NP in Male Rats.

Authors:  Nazila Iranipour; Farrin Babaei-Balderlou; Ali Maleki; Mehdi Moslemi; Fariba Khodagholi
Journal:  Neurotox Res       Date:  2021-06-26       Impact factor: 3.911

  7 in total

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