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Microfluidic mapping of cancer cell-protein binding interaction Zongbin Liu, Xin Han, Rui Chen, Kai Zhang, Ying Li, Shelby Fruge, Joon Hee Jang, Yuan Ma, and Lidong Qin ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b03728 • Publication Date (Web): 20 Jun 2017 Downloaded from http://pubs.acs.org on June 22, 2017
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ACS Applied Materials & Interfaces
Microfluidic mapping of cancer cell-protein binding interaction Zongbin Liu,†,‡ Xin Han,†,‡ Rui Chen,†,‡,§ Kai Zhang,†,‡ Ying Li,†,‡ Shelby Fruge,†, ǁ Joon hee Jang,†,‡ Yuan Ma,†,‡ and Lidong Qin*,†,‡ †
Department of Nanomedicine, Houston Methodist Research Institute, Houston, TX 77030,
United States ‡
Department of Cell and Developmental Biology, Weill Medical College of Cornell University,
New York, NY 10065, United States §
The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical
University, Guangzhou, Guangdong 510150, China ǁ
Division of Infectious Diseases, Department of Pediatrics, School of Medicine, Emory
University, Atlanta, GA 30302, United States
KEYWORDS: microfluidic, metastasis, cancer cell-extracellular matrix (ECM) interaction, fibrinogen, integrin, cytoskeleton, cancer drug discovery
ABSTRACT: The interaction between tumor cells and microenvironment during metastasis is mediated by the binding of cell surface receptors, such as integrins and selectins, with protein ligands. Delineation of their binding interaction and identification of key receptors may be particularly important both in understanding ECM remodeling and in developing potential therapeutic targets. Here we present a microfluidic chip that allows qualitative and quantitative mapping of large population cell-protein interaction. It was found that β1 integrin showed stronger binding interaction with collagen than with other ECM proteins. The upregulated β1
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integrin in invasive cancer cells enhanced cell-ECM interaction and may promote ECM remodeling. Cancer cells also showed strong interaction with plasma fibrinogen, the elevated level of which may help cancer cells arrest on blood vessels. We also verified that the chip may provide a platform for drug discovery by targeting integrins and cytoskeletons.
INTRODUCTION Cancer is not only a disease of genetic disorder of tumor cells, but also a disease of imbalance between tumor cells and tumor microenvironment.1-2 During tumor progression, extracellular matrix (ECM) proteins undergo considerable remodeling, including increased deposition of collagens and enhanced matrix crosslinking, which results in increased density of tumor tissue.3-6 The progressive ECM remodeling and the altered cell-ECM interaction regulate the growth, survival and migration of tumor cells and may also promote their extrusion through basement membrane into the circulatory system.4 After entry into the circulatory system, tumor cells interact with blood components, such as fibrinogen and platelets, forming emboli to prolong tumor cell survival. Fibrinogen and platelets can also act as bridges between tumor cells and endothelial cells and help tumor cells arrest within the microvasculature of target organs.7 It is reported that patients with elevated levels of fibrinogen and platelets had worse prognosis in various solid tumor types including lung, breast and esophageal.8-10 The interaction between tumor cells and microenvironment during metastasis is mediated by the binding of cell surface receptors, such as integrins and selectins, with protein ligands.11-15 Delineation of their binding interaction and identification of key receptors may be particularly important both in understanding ECM remodeling and in developing potential therapeutic targets.16 However, tools to quantify their binding interaction are lacking. Traditionally, some
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micromanipulation approaches including atomic force microscopy (AFM), optical stretching and magnetic tweezers, can achieve the quantification.17-18 However, these micromanipulation approaches are complicated, labor intensive and produce a low throughput when statistical analysis of a cell population is required. In this study, we report a microfluidic cell-substrate interaction chip (MCI-Chip) that mimics the squeezing of cancer cells through microgaps during metastasis to map cell-ECM interaction. The MCI-Chip consists of 8 parallel chambers that can achieve the coating of 8 different ECM proteins. Each chamber is composed of rectangular micropost arrays with gap width decreasing from the inlet to the outlet. When cancer cells are perfused into the chip, shorter trapping distance indicates stronger cell-ECM interaction. Our previous study19 shows that the capability of cells to pass through micro-constrictions can be characterized by a parameter “transportability”, which is calculated from cell size, cell stiffness and cell-substrate interaction. Given a cell population, they have the same average size and stiffness; the overall transportability only depends on cell-substrate interaction in each chamber. Therefore, transportability is capable to quantify cell-ECM interaction. Compared to conventional micromanipulation platforms, the MCI-Chip has the advantages of high throughput (tens of thousands cells), multiple-protein coating and fast analysis, and is particularly useful for mapping large population cell-ECM interaction. In this study, we demonstrated the potential application of the MCI-Chip in identification of key receptors and in drug discovery. EXPERIMENTAL SECTION Chip design, fabrication and modeling. The MCI-Chip was designed using auto computeraided design (CAD) software, and fabricated following standard photolithography and soft
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lithography techniques.20-21 In photolithography, photoresist of SU8-3025 was used for microstructure fabrication on silicon wafer. In soft lithography, the prepolymer solution of polydimethylsiloxane (PDMS) (Sylgard 184, Dow Corning, USA) was mixed with curing agent (10:1 w/w ratio) and was then degassed. The mixed solution was further poured onto fabricated silicon wafer mold. The curation of PDMS was carried out at 80 ℃ for 1 h. PDMS mold was then peeled off and holes were punched for inlets and outlets. The PDMS mold was then bonded to glass slide after oxygen plasma treatment (Plasma Etch, Inc., NV, USA). The fluidic flow in the MCI-Chip was analyzed using commercial software for computational fluid dynamics (CFD) simulation. The 3D microfluidic system was established using GAMBIT software. The mesh file was then analyzed by ANSYS FLUID software by setting compute parameters with acceptable grid densities and local grid refining. In simulation, laminar flow pattern was selected and analyzed by the Navier-Stokes equations. Cell culture and preparation. Breast cancer cell lines MCF-7 and MDA-MB-231(ATCC, Manassas, VA, USA) were used for cell culture. The protocol of cell culture was the same as described in our previous study. 19 Protein coating and cell perfusion. Human collagen I (SouthernBiotech, Birmingham, AL), Human collagen IV (SouthernBiotech), human fibronectin (EMD Millipore, Billerica, MA) and human laminin (EMD Millipore) were used for coating chip surface. The 8 chamber outlets were connected to 8 syringe tubes filled with phosphate buffered saline (PBS) solution, 0.05 mg/mL bovine albumin serum (BSA) solution, 0.05 mg/mL collagen I solution, 0.05 mg/mL collagen IV solution, 0.05 mg/mL collagen I/IV (1:1 ratio) solution, 0.05 mg/mL fibronectin solution, 0.05 mg/mL laminin solution and 0.05 mg/mL fibronectin/laminin (1:1 ratio) solution, respectively.
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Coating process was controlled by a pump at a flow rate of 20 µL/min for 30 min. Human plasma fibrinogen (Alexa Fluor 488 conjugate, Thermo Scientific, Waltham, MA) was also used for chip coating. The 8 chambers were perfused with 0, 0.03, 0.06, 0.09, 0.12, 0.15, 0.18, 0.21 mg/mL fibrinogen in PBS at a flow rate of 20 µL/min for 0.5 min. After coating, cancer cells prelabelled with CellTrackerTM Green CMFDA or CellTrackerTM Red CMTPX (Thermo Scientific) were suspended at 1 × 105 cells/mL and injected in the chip at a flow rate of 25 µL/min. If the flow rate was higher than 25 µL/min, some cells can easily perfuse out of chip. We used the flow rate of 25 µL/min to trap all cancer cells. When fluid injection was stopped, cancer cells trapped between gaps were restored to their original shape within 4 min. Diameter of each trapped cell was analyzed by the Olympus cellSens Dimension software. Immunofluorescence imaging and western blotting. Anti-β1 integrin antibody (Abcam, Cambridge, UK), anti-α1 integrin antibody (Abcam) and anti-α5 integrin antibody (Abcam) were used as primary antibodies for immunostaining and western blotting analysis. The protocol was the same as described in our previous study. 19 To stain F-actin on chip, the injection of staining solutions was controlled by pump at a flow rate of 10 µL/min. Alexa Fluor® 488-conjugated phalloidin (1:250; Thermo Scientific) was used to stain F-actin. Heat map analysis of cell distribution. The stitched fluorescence image of whole chip was taken with an inverted fluorescence microscope of Olympus IX81. The image of each chamber was then divided into 20 equal parts using ImageJ software. The fluorescence intensity of 20 parts was analyzed. If the total fluorescence intensity of one chamber was regarded as 100%, the
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percentage of fluorescence intensity of each part in total fluorescence intensity was calculated, and plotted together like a heat map. Cell-ECM interaction analysis. The trapped cancer cells were imaged by Olympus cellSens Dimension software. The gap width of microposts and the diameters of trapped cells were then obtained from the software. Transportability of each cell was calculated by the transportability equation19: ଵ
Transportability~ ஜ ~
(ୈି)భ.ఱ ୈబ.ఱ
Eq 1
where E, µ, D and g are ealstic modulus, frcition coefficient, cell diameter, and gap width respectively. The plots of transportability versus cell diameter Mathematics software were generated in the same way as described in our previous study. 19 Given a population of trapped cells, the friction coefficint µ can be used to characterize the average interaction level between cells and ECM coated surface, and can be calculated by the following equation: ଵ
μ~
Eq 2
where E is the average Young’s modulus of cells, and T is the average transportability. Young’s modulus of cancer cells was measured by atomic force microscopy (AFM) (Bioscope, Bruker Corporation, Billerica, MA). Statistical analysis. The comparison of two groups of data was done by the non-parametric test (Wilcoxon-MannWhitney test) using GraphPad software.
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