Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer.


Journal

Journal of visualized experiments : JoVE
ISSN: 1940-087X
Titre abrégé: J Vis Exp
Pays: United States
ID NLM: 101313252

Informations de publication

Date de publication:
21 05 2019
Historique:
entrez: 11 6 2019
pubmed: 11 6 2019
medline: 9 4 2020
Statut: epublish

Résumé

Understanding the impact of the microenvironment on the phenotype of cells is a difficult problem due to the complex mixture of both soluble growth factors and matrix-associated proteins in the microenvironment in vivo. Furthermore, readily available reagents for the modeling of microenvironments in vitro typically utilize complex mixtures of proteins that are incompletely defined and suffer from batch to batch variability. The microenvironment microarray (MEMA) platform allows for the assessment of thousands of simple combinations of microenvironment proteins for their impact on cellular phenotypes in a single assay. The MEMAs are prepared in well plates, which allows the addition of individual ligands to separate wells containing arrayed extracellular matrix (ECM) proteins. The combination of the soluble ligand with each printed ECM forms a unique combination. A typical MEMA assay contains greater than 2,500 unique combinatorial microenvironments that cells are exposed to in a single assay. As a test case, the breast cancer cell line MCF7 was plated on the MEMA platform. Analysis of this assay identified factors that both enhance and inhibit the growth and proliferation of these cells. The MEMA platform is highly flexible and can be extended for use with other biological questions beyond cancer research.

Identifiants

pubmed: 31180341
doi: 10.3791/58957
pmc: PMC6736605
mid: NIHMS1035773
doi:

Substances chimiques

Extracellular Matrix Proteins 0
Ligands 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Video-Audio Media

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NCI NIH HHS
ID : U54 CA209988
Pays : United States
Organisme : NHGRI NIH HHS
ID : U54 HG008100
Pays : United States

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Auteurs

Rebecca Smith (R)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

Kaylyn Devlin (K)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

David Kilburn (D)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

Sean Gross (S)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

Damir Sudar (D)

Quantitative Imaging Systems LLC.

Elmar Bucher (E)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

Michel Nederlof (M)

Quantitative Imaging Systems LLC.

Mark Dane (M)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

Joe W Gray (JW)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

Laura Heiser (L)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University.

James E Korkola (JE)

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University; korkola@ohsu.edu.

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Classifications MeSH