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Method Article
The purpose of the method presented here is to show how microenvironment microarrays (MEMA) can be fabricated and used to interrogate the impact of thousands of simple combinatorial microenvironments on the phenotype of cultured cells.
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.
Culturing of cancer cell lines on plastic in two-dimensional (2D) monolayers remains one of the major workhorses for cancer researchers. However, the microenvironment is increasingly being recognized for its ability to impact cellular phenotypes. In cancer, the tumor microenvironment is known to influence multiple cellular behaviors, including growth, survival, invasion, and response to therapy1,2. Traditional monolayer cell cultures typically lack microenvironment influences, which has led to the development of more complex three-dimensional (3D) assays to grow cells, including commercially available purified basement membrane extracts. However, these purified matrices are typically complicated to use and suffer from technical problems such as batch variability3 and complex compositions3. As a result, it can be difficult to assign function to specific proteins that may be impacting cellular phenotypes3.
To address these limitations, we have developed the microenvironment microarray (MEMA) technology, which reduces the microenvironment down to simple combinations of extracellular matrix (ECM) and soluble growth factor proteins4,5. The MEMA platform enables identification of dominant microenvironmental factors that impact the behavior of cells. By using an array format, thousands of combinations of microenvironment factors can be assayed in a single experiment. The MEMA described here interrogates ~2,500 different unique microenvironment conditions. ECM proteins printed into well plates form growth pads upon which cells can be cultured. Soluble ligands are added to individual wells, creating unique combinatorial microenvironments (ECM + ligand) on each different spot to which the cells are exposed. Cells are cultured for several days, then fixed, stained, and imaged to assess cellular phenotypes as a result of exposure to these specific microenvironment combinations. Since the microenvironments are simple combinations, it is straightforward to identify proteins that drive major phenotypic changes in cells. MEMAs have been used successfully to identify factors that influence multiple cellular phenotypes, including those that drive cell fate decisions and response to therapy4,5,6,7. These responses can be validated in simple 2D experiments and can then be assessed under conditions that more fully recapitulate the complexity of the tumor microenvironment. The MEMA platform is highly adaptable to a variety of cell types and endpoints, provided that good phenotypic biomarkers are available.
NOTE: An overview of the entire MEMA process, including estimated time, is outlined in the flow diagram shown in Figure 1. This protocol details the fabrication of MEMAs in 8-well plates. The protocol may be adapted for other plates or slides.
1. Preparation of Protein, Diluent, and Staining Buffers
2. Preparation of an ECM Source Plate
3. Creation of the Source Plate Using a Liquid Handler
4. Printing MEMAs Using an Array Printing Robot
NOTE: The following part of the protocol specifically describes the preparation and use of MEMA to investigate the impact of different microenvironment proteins on the growth and proliferation of MCF7 cells. However, the protocol can easily be adapted to use different ligands, ECMs, and cells to study other cell lines and endpoints of interest.
5. Creation of Ligand Treatment Plates
6. Culturing Cells on MEMAs
7. Fixing and Staining MEMAs
8. Imaging of MEMAs
9. Data Analysis
NOTE: Data analysis consists of normalization, variation correction, and summarization of the raw CellProfiler derived data. In this instance, the R-environment with custom code is used to perform all the steps. However, any statistical environment or software program can be utilized to perform the equivalent actions. An example of the open source custom code for the R environment for analysis is available at: https://www.synapse.org/#!Synapse:syn2862345/wiki/72486.
To simplify microenvironmental impacts on cell growth and proliferation and to identify conditions that promoted or inhibited cell growth and proliferation, the breast cancer cell line MCF7 was seeded on a set of eight 8-well MEMAs as described in the protocol. This assay exposed the cells to 48 different ECMs and 57 different ligands, for a total of 2736 combinatorial microenvironmental conditions. After 71 h in culture, cells were pulsed with EdU, fixed, permeablized, and stained with DAPI, the reaction for EdU detecti...
The importance of "dimensionality" and context has been a motivating factor in the development of in vitro culture systems as tools in the characterization of cancer cells through their interaction with the microenvironment11, and the ability of in vitro culture systems to mimic the in vivo environment is a driving force behind the quest to improve those culture systems. In vitro systems, however, remain significant tools of cancer research precisely because of their ability to distil...
The authors have nothing to disclose.
The work in this manuscript was supported by the NIH Common Fund Library of Network Cellular Signatures (LINCS) U54 grant HG008100 (J.W.G., L.M.H., and J.E.K) and NCI Cancer Systems Biology Consortium (CSBC) U54 CA209988grant (J.W.G., L.M.H., and J.E.K).
Name | Company | Catalog Number | Comments |
Aushon 2470 | Aushon BioSystems | Arrayer robot system used in the protocol | |
Nikon HCA | Nikon | High Content Imaging system designed around Nikon Eclipse Ti Inverted Microscope | |
BioTek Precision XS liquid Handler | BioTek | liquid handling robot used in the protocol | |
Trizma hydrochloride buffer solution | Sigma | T2069 | |
EDTA | Invitrogen | 15575-038 | |
Glycerol | Sigma | G5516 | |
Triton X100 | Sigma | T9284 | |
Tween 20 | Sigma | P7949 | |
Kolliphor P338 | BASF | 50424591 | |
384-well microarray plate, cylindrical well | Thermo Fisher | ab1055 | |
Nunc 8 well dish | Thermo Fisher | 267062 | |
Paraformaldehyde 16% solution | Electron Microscopy Science | 15710 | |
BSA | Fisher | BP-1600 | |
Sodium Azide | Sigma | S2002 | |
Cell Mask | Molecular Probes | H32713 | |
Click-iTEdU Alexa Fluor | Molecular Probes | C10357 | |
DAPI | Promo Kine | PK-CA70740043 | |
ALCAM | R & D Systems | 656-AL | ECM |
Cadherin-20 (CDH20) | R & D Systems | 5604-CA | ECM |
Cadherin-6 (CDH6) | R & D Systems | 2715-CA | ECM |
Cadherin-8 (CDH8) | R & D Systems | 188-C8 | ECM |
CD44 | R & D Systems | 3660-CD | ECM |
CEACAM6 | R & D Systems | 3934-CM | ECM |
Collagen I | Cultrex | 3442-050-01 | ECM |
Collagen Type II | Millipore | CC052 | ECM |
Collagen Type III | Millipore | CC054 | ECM |
Collagen Type IV | Sigma | C5533 | ECM |
Collagen Type V | Millipore | CC077 | ECM |
COL23A1 | R & D Systems | 4165-CL | ECM |
Desmoglein 2 | R & D Systems | 947-DM | ECM |
E-cadherin (CDH1) | R & D Systems | 648-EC | ECM |
ECM1 | R & D Systems | 3937-EC | ECM |
Fibronectin | R & D Systems | 1918-FN | ECM |
GAP43 | Abcam | ab114188 | ECM |
HyA-500K | R & D Systems | GLR002 | ECM |
HyA-50K | R & D Systems | GLR001 | ECM |
ICAM-1 | R & D Systems | 720-IC | ECM |
Laminin | Sigma | L6274 | ECM |
Laminin-5 | Abcam | ab42326 | ECM |
Lumican | R & D Systems | 2846-LU | ECM |
M-Cad (CDH15) | R & D Systems | 4096-MC | ECM |
Nidogen-1 | R & D Systems | 2570-ND | ECM |
Osteoadherin/OSAD | R & D Systems | 2884-AD | ECM |
Osteopontin (SPP) | R & D Systems | 1433-OP | ECM |
P-Cadherin (CDH3) | R & D Systems | 861-PC | ECM |
PECAM1 | R & D Systems | ADP6 | ECM |
Tenascin C | R & D Systems | 3358-TC | ECM |
VCAM1 | R & D Systems | ADP5 | ECM |
Vitronectin | R & D Systems | 2308-VN | ECM |
Biglycan | R & D Systems | 2667-CM | ECM |
Decorin | R & D Systems | 143-DE | ECM |
Periostin | R & D Systems | 3548-F2 | ECM |
SPARC/osteonectin | R & D Systems | 941-SP | ECM |
Thrombospondin-1/2 | R & D Systems | 3074-TH | ECM |
Brevican | R & D Systems | 4009-BC | ECM |
Elastin | BioMatrix | 5052 | ECM |
Fibrillin | Lynn Sakai Lab OHSU | N/A | ECM |
ANGPT2 | RnD_Systems_Own | 623-AN-025 | Ligand |
IL1B | RnD_Systems_Own | 201-LB-005 | Ligand |
CXCL8 | RnD_Systems_Own | 208-IL-010 | Ligand |
IGF1 | RnD_Systems_Own | 291-G1-200 | Ligand |
TNFRSF11B | RnD_Systems_Own | 185-OS | Ligand |
BMP6 | RnD_Systems_Own | 507-BP-020 | Ligand |
FLT3LG | RnD_Systems_Own | 308-FK-005 | Ligand |
CXCL1 | RnD_Systems_Own | 275-GR-010 | Ligand |
DLL4 | RnD_Systems_Own | 1506-D4-050 | Ligand |
HGF | RnD_Systems_Own | 294-HGN-005 | Ligand |
Wnt5a | RnD_Systems_Own | 645-WN-010 | Ligand |
CTGF | Life_Technologies_Own | PHG0286 | Ligand |
LEP | RnD_Systems_Own | 398-LP-01M | Ligand |
FGF2 | Sigma_Aldrich_Own | SRP4037-50UG | Ligand |
FGF6 | RnD_Systems_Own | 238-F6 | Ligand |
IL7 | RnD_Systems_Own | 207-IL-005 | Ligand |
TGFB1 | RnD_Systems_Own | 246-LP-025 | Ligand |
PDGFB | RnD_Systems_Own | 220-BB-010 | Ligand |
WNT10A | Genemed_Own | 90009 | Ligand |
PTN | RnD_Systems_Own | 252-PL-050 | Ligand |
BMP3 | RnD_Systems_Own | 113-BP-100 | Ligand |
BMP4 | RnD_Systems_Own | 314-BP-010 | Ligand |
TNFSF11 | RnD_Systems_Own | 390-TN-010 | Ligand |
CSF2 | RnD_Systems_Own | 215-GM-010 | Ligand |
BMP5 | RnD_Systems_Own | 615-BMC-020 | Ligand |
DLL1 | RnD_Systems_Own | 1818-DL-050 | Ligand |
NRG1 | RnD_Systems_Own | 296-HR-050 | Ligand |
KNG1 | RnD_Systems_Own | 1569-PI-010 | Ligand |
GPNMB | RnD_Systems_Own | 2550-AC-050 | Ligand |
CXCL12 | RnD_Systems_Own | 350-NS-010 | Ligand |
IL15 | RnD_Systems_Own | 247-ILB-005 | Ligand |
TNF | RnD_Systems_Own | 210-TA-020 | Ligand |
IGFBP3 | RnD_Systems_Own | 675-B3-025 | Ligand |
WNT3A | RnD_Systems_Own | 5036-WNP-010 | Ligand |
PDGFAB | RnD_Systems_Own | 222-AB | Ligand |
AREG | RnD_Systems_Own | 262-AR-100 | Ligand |
JAG1 | RnD_Systems_Own | 1277-JG-050 | Ligand |
BMP7 | RnD_Systems_Own | 354-BP-010 | Ligand |
TGFB2 | RnD_Systems_Own | 302-B2-010 | Ligand |
VEGFA | RnD_Systems_Own | 293-VE-010 | Ligand |
IL6 | RnD_Systems_Own | 206-IL-010 | Ligand |
CXCL12 | RnD_Systems_Own | 351-FS-010 | Ligand |
NRG1 | RnD_Systems_Own | 378-SM | Ligand |
IGFBP2 | RnD_Systems_Own | 674-B2-025 | Ligand |
SHH | RnD_Systems_Own | 1314-SH-025 | Ligand |
FASLG | RnD_Systems_Own | 126-FL-010 | Ligand |
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