Tape-Assisted Photolithographic-Free Microfluidic Chip Cell

Nov 30, 2017 - In this work, we developed a new methodology (tape-assisted photolithographic-free microfluidic chip, TAPMiC) that can realize homogene...
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Tape Assisted Photolithographic-free Microfluidic Chip (TAPMiC) Cell Patterning for Tumor Metastasis Study Liang Zhao, Tengfei Guo, Lirong Wang, Yang Liu, Ganyu Chen, Hao Zhou, and Meiqin Zhang Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b03225 • Publication Date (Web): 30 Nov 2017 Downloaded from http://pubs.acs.org on December 1, 2017

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Tape Assisted Photolithographic-free Microfluidic Chip (TAPMiC) Cell Patterning for Tumor Metastasis Study Liang Zhao*,†, Tengfei Guo†,‡, Lirong Wang, Yang Liu, Ganyu Chen, Hao Zhou,§ Meiqin Zhang* Research Center for Bioengineering and Sensing Technology, School of Chemistry and Biological Engineering, Beijing Key Laboratory for Bioengineering and Sensing Technology, University of Science and Technology Beijing, Beijing, China, 100083 AUTHOR INFORMATION *: To whom correspondence should be addressed.

[email protected] [email protected] ORCID® Liang Zhao: orcid.org/0000-0001-6273-2651 Meiqin Zhang: orcid.org/0000-0002-6082-8438 †: These authors contributed equally to this work and considered co-first authors. Present address ‡: Micro Systems Engineering Department, CapitalBio Corporation, Life Science Park Road 18#, Changping District, Beijing, China §: Department of Biomedical Engineering, University of Southern California, 1042 Downey Way, Los Angeles, CA 90089, USA.

Abstract: 1 ACS Paragon Plus Environment

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Cancer metastatic dissemination is a complex event during tumor progression which involves cell-cell, cell-matrix interactions. Micro-patterning is one of the most efficient ways to study tumor development because it can tune the distribution of cells with spatial and temporal control. Extensive studies have shown that microfluidics can provide a feasible method for cell patterning. However, the current technique requires a microfabrication laboratory to manufacture the chip, which results in inaccessibility to researchers especially biologists who focus on the disclosing biological mechanisms rather than the methods. In this work, we developed a new methodology (Tape Assisted Photolithographic-free Microfluidic Chip, TAPMiC) that can realize homogeneous and heterogeneous micro-patterning (45 features, 300 µm diameter of each) on culture dish without the photolithographic procedure. We have applied this method to study critical biological problems, such as tumor cell migration under different conditions, including anti-tumor pharmaceutics and candidate gene RNAi assay that was relevant to tumor translocation and invasion. Moreover, this platform can achieve co-patterning to recapitulate tumor invasion scenario with single cell trackable analysis. To decode regulation during metastasis, we conducted in situ recovering for qPCR analysis from each cell type from tumor-fibroblast co-pairing. Regulation of several essential genes has been unveiled that matrix degradation gene MMP2 and angiogenesis associated gene VEGFA were up-regulated in tumor cells in fibroblast enriched niche comparing with homogenous cultivation. Therefore, this approach constitutes a novel tool for investigating metastasis with quantitative measurements both on phenotype and genetical information.

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Introduction: An estimated 90% of cancer patients deaths are attributed to the metastatic development of cancer,1 demanding the need for new insight into tumor metastasis. Several steps involved in the metastatic process, such as cell migration from the original site, intravasation into the blood vessel, survival in circulation, extravasation from vascular networks, and proliferation in a distal location.2 The tumor microenvironment has long been identified as a critical factor influencing cancer metastasis, invasion, and development.3 In tumor niche, extracellular matrix, extracellular molecules and different types of cells are highly organized in spatiality and time.4, 5 Fibroblasts are the most abundant and considered as one of the most active parts in the tumor microenvironment.6 To better understand metastatic tumor progression, recapitulating tumor microenvironment in vitro and dissecting quantitative biological information is one of the best ways to canvass tumor migration and invasion at the very beginning of metastasis. Therefore, many technologies have been developed to study cell migration or tumor cell invasion in vitro, such as Boyden chamber assay

7

and scratch assay,

8

which is the

most straightforward and economical method to measure cell migration in vitro. However, compared to other approaches, scratch assay presents several limitations. This technique brings a drawback when study limited source, such as clinic samples because the relatively large amount of cells and chemicals will be asked to perform a scratch assay. Besides, it takes a long time to complete test (8-18 hours) and requires one to two days to form cell monolayer.9 Likewise, this assay lacks repeatability due to the jagged edge from uncontrollable scratching operation. Additionally, the incapability 3 ACS Paragon Plus Environment

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of studying the interactions between multiple cell types in scratch assay limits its applications and therefore may not be suitable for recapitulating tumor cell niches. Boyden chamber assays, another popular method, allows investigations between different cell types and chemotaxis of cells. Nonetheless, this approach is challenging to analyze cell migration and invasion quantitatively and dynamically. Moreover, precise tracking the movement of individual cells is also hard to perform on Boyden chamber assay.10 Microfabrication methods based in vitro cell patterning enable mimicking physiological events involves cell migration and cell-cell interactions such as wound healing by selfassembled monolayers,11 microchannel selective cell lysis,12 and in situ injury inside a microfluidic chamber.13 Other patterning approaches realized tumor migration evaluation14 and interactions between different cell types including hepatocyte-stroma,15 embryonic stem cells-fibroblasts,16, effects18,

19

17

and tumor-endothelium for studying paracrine

and local metabolism or hypoxia-induced tumor metastasis.20,

21

Those

scalable strategies have been developed to overcome drawbacks of above mentioned conventional ways by lowering cell and sample consumptions, increasing throughput, improving repeatability and addressing the problems for co-culture with spatial configuration. However, most of these methods rely on delicate surface chemistry,22, 23 sophisticated photolithography,24,

25

and energy-consuming transducer26,

27

to perform

cell patterning. Furthermore, few techniques can seamlessly redeem the quantitation for cell migration, interactions between different cell types and correlated gene expression. Recent examples in the microfluidic platform have represented precise measurements of cell motility at single cell resolution,28 imaging corresponding gene expression among

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cell patterning,29 and refined transcriptional regulation caused by cell-cell interactions.30 Likewise, these systems still can not avoid lithographically micro-fabrication that enables cell confinement on a surface. Furthermore, above scenario plagues the use micro-scaled systems to perform specific assay such as cell migration and tumor metastasis because the microfabrication was inaccessible to the biological routine lab setting. Thus, the development of lithography-free procedures to obtain controllable micropatterning and even co-patterning with the compatibility of analyzing images and gene expression is therefore necessary and acute. Herein, we developed a new approach that can realize cell patterning and quantitative analysis of tumor migration and tumor-fibroblast interactions during imitative metastasis by a microfluidic device, which is made by tape-based handcraft fabrication without photolithography.

This

method,

named

“Tape

Assisted

Photolithographic-free

Microfluidic Chip assay, TAPMiC assay”, allows us to precisely determine dynamic cell migration

under

specific

microenvironment

like

differences

in

growth

factor

concentrations, tumor cell types, biochemical inhibitors, and even silenced genes. Compared with other methods,31 we specifically implemented this technique in recapitulating cancer cell migration and invasion into fibroblasts for quantitative analysis cell migration, invasion and genetic regulations during metastasis. From first cell seeding to completion of data gaining, this device uses merely few hundreds of cells, taking only 7 to 8 hours to accomplish co-culture based study of tumor-fibroblast invasion model with statistical readout. Consequently, to demonstrate that our method is capable of deciphering valuable biological information not only from imaging phenotype but also from genetics, after formulating tumor-fibroblasts co-patterning, we dissected

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expression level of 10 critical genes in tumor and stroma, that relevant to transcription regulation. To the extent of our knowledge, this metastatic invasion assay is the first lithography-free microfluidic example that demonstrated quantitative cell migration and gene expression analysis during in vitro cell metastasis.

Experimental section. Fabrication of TAPMiC Device. From mold fabrication to cell patterning on any planar substrate, our “TAPMiC-assay” consists only four steps as shown in Figure 1(a). Different from a previous report,31 we used transparent adhesive tape (Scotch®, 3M), with the thickness of 52 µm as a material to fabricate the mold. The “TAPMiC” chips were made by using a modified Polydimethylsiloxane (PDMS) prototyping method. The mold was fabricated from a tape (Scotch® 3M, USA) which has been crafted by knife (OLFA, Japan) and puncher (ø=0.3 mm, SYNEO LLC, USA). The handcrafted tape contains numbers of holes that each has 300 μm in diameter and 104 μm in height. Briefly, two layers of tape (~104 µm, shown in Figure S1) was stuck on the film (obtained from Shenzhen MicroCAD photomask Co. Ltd.) with chip features for making punch positioning and shape cutting easier. The tapes were firstly stuck on the photomask and were manually drilled by a hand-holding puncher. For multiple usages of the photomask, we transferred the tape into the petri dish after punching and hand cutting. However, this procedure may also slightly hurt the photomask (plastic film). Thus, the photomask can be reused about 20 times and may reach to 50 times

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use with careful and gentle punch. Each photomask cost about 10 USD and thus it only cost less than a quarter for each use. To fabricate the chip, 20 g PDMS (10 A: 1 B, Sylgard 184 silicone elastomer kit, Dow Corning) was mixed and degassed, poured onto the “tape mold” and cured at 80 °C for 1 hour. PDMS was replicated from tape mold and trimmed to an appropriate size. The holes were punched for inlets and outlets using 3 mm diameter biopsy punch (World Precision Instruments, USA) as shown in figure 1(b). The chip was then sterilized by ultraviolet exposure for 15 min before the experiment. Cell Patterning on TAPMiC device. Four kinds of tumor cell line, HT1080, A549, MDA-MB-231, MCF-7 and Normal Human Dermal Fibroblasts (NHDF, ScienCell Research Laboratories, USA) are cultured according to the manufacturer's protocol. All cancer cell lines were kindly provided by Stem Cell Bank, Chinese Academy of Sciences. Briefly, cancer cell lines were cultivated in Dulbecco’s Modified Eagle Medium (DMEM, Gibco, Thermo Fisher Scientific) with 10 % fetal bovine serum and 1 % Pen/Strep (Invitrogen, Thermo Fisher Scientific). The fibroblast cell line NHDF were cultured in FM medium (ScienCell, USA) with 10 % FBS. All cells were cultured in a humidified incubator with 5 % CO2 at 37 ºC. When reached to 80% confluence, cells were detached by Trypsin-EDTA (Invitrogen, Thermo Fisher Scientific) and centrifuged at 1000 rpm for 2 min for passaging. We incubate collagen I (50 μg/ml, Collagen I Rat Protein, Tail, Thermo Fisher Scientific, USA) on Petri dishes (10 x 35 mm, ThermoFisher Scientific) overnight, washed with PBS, and natural dry. Because the collagen I is an extracellular matrix protein to 7 ACS Paragon Plus Environment

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promote cell adhesion and growth, we can, therefore, simulate microenvironment for cell invasion and metastasis. We put the chip on the collagen I coated petri dish and added 1X PBS (ThermoFisher Scientific) into chip inlets and outlets respectively. The whole culture plate with the chip was then degassed for 2 min by using a vacuum pump (Edwards, USA). This step played an important role to ensure liquid infusion into the TAPMiC chip. Cell seeding and attaching on the surface only took less than 1-2 hours depending on adherent cell type. Lastly, to generate cell micro-pattern, we carefully peeled the whole chip off in a deep culture plate were filled with Hanks' Balanced Salt Solution (Thermofisher Scientific). This peeling off procedure should be taken with care and gentle, especially try to avoid chip-bottom scratching before complete separation. We find that this protocol is robust and with a high success rate (8 to 9 times success out of 10, data not shown). No noticeable cell loss can be identified by carefully examining cell patterning on the plate surface under a microscope (Figure 1c and Figure S2). To validate the cell viability, the patterned A549 cells were stained with live/ dead double staining kit (Dojindo, Japan) composed of calcein-AM and propidium iodide (PI), both before and after the chip removal. For co-patterning, we seed second cell type such as tumor cells in the petri dish for 30 to 60 min to allow the additional cells adhere to cell-free zone (CFZ) from first cell patterning. We then thoroughly washed the culturewell by using HBSS to remove any non-adhered cells. Cell Staining and Image Acquisition To study the co-patterned cell features, each type of cells has been labeled with different CellTracker dye before performing cell patterning. This strategy allows us to distinguish different cell types in after co-patterning formed. All cancer cell lines (MCF-7, 8 ACS Paragon Plus Environment

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A549, HT1080, and MDA-MB-231) were stained with CellTrackerTM Red CMTPX whereas fibroblast cell (NHDF) was stained by CellTrackerTM Green CMFDA (ThermoFisher Scientific, USA). We next monitored cell migration by collecting images on laser confocal microscope (FV1200, Olympus, Japan) at 25 min intervals (FV1200 Multi Area Time Lapse Software Module). Meanwhile, Cell migration and interaction was determined by the images tracking the positions of staining cell. To distinguish net cell migration from cell proliferation, we analyzed cell proliferation rate in patterned features by using time-lapse imaging at the time resolution of 15 min. Statistic result from micro-patterns shows that only less than 10% cell population present mitosis (Figure S3). Drug Treatment Four components were chosen to be used as a model drug to test cell migration under different chemical stress. We optimized the concentration for each drug treatment, Cytochalasin28 (CytoD, 2 μ M, Sigma-Aldrich), GM600132 (Galardin, 1 µM, Abcam), Reversine30 (5 μM, Sigma-Aldrich), and Cycloheximide33 (CHX, 100 µM, Sigma-Aldrich) respectively. The A549 cancer cell migration in control group and cytochalasin treatment have been recorded in Movie S1 and S2. RNAi Assay We performed transfection when the cells confluence for the petri dish area reach to 50% to 70%. We selected five genes related to cell migration and metastasis to test siRNA silence effect on cell migration, VDAC (Voltage-dependent anion-selective 9 ACS Paragon Plus Environment

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channel protein 1), MMP9 (Matrix metallopeptidase 9), ROCK1 (Rho-associated, coiledcoil-containing protein kinase 1), AQP-1 (Aquaporin 1) and Transmembrane 4 L6 family member 1 (TM4SF1). The sequence of 2’-OMe-phosphorodithioate-modified siRNAs (GenePharma, Shanghai, China) for each gene is shown in the supplementary information. Gene Expression Analysis from Homo- or Co-culture Patterning To assess gene expression in micro-patterned cells, we retrieved a small number of cells from patterning features directly by using mouth pipette. Basically, after tumor and fibroblast co-patterning overnight, we used mouth pipette with a self-pulled capillary (tip open ~40 µm) to retrieve both cancer and fibroblast cells. Those two types of cells have been previously labeled with cell-tracker dye (CellTracker™, ThermoFisher Scientific, USA) and observed under a fluorescent microscope (AZ100, Nikon, Japan) to distinguish the targeted type of cells. Retrieved cells were then transferred into PCR tube (with lysis buffer) directly from mouth pipette and perform cell lysis. Detailed procedures can be found in our previous study.29 The expression of GAPDH, VEGFA, MMP14, MMP2, PLAU, GREM1, CCL2 and MYC-1 were analyzed by real-time PCR (q225, Kubo Technology, Beijing, China).

Results and Discussion. Design principle on “TAPMiC”. Lithography provides a highly precise and reproducible manner for manufacturing structures or features at a micro- or even nanometer scale. This technology inherently asks for sophisticated environments and facilities to fabricate micro-mold or chip. 10 ACS Paragon Plus Environment

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Currently, biologists who are interested in utilizing new micro-scale tools to address biological questions have been largely blocked by above scenario. To circumvent the lithographic process and facilitate micro-patterning, we only use common tools in any laboratory and developed a new strategy for studying tumor metastasis. Our Tape Assisted Photolithographic-free Microfluidic Chip (TAPMiC) based cell patterning consists of 4 steps (Figure 1a): (i) tape hand-craft cutting and hole making; (ii) Polydimethylsiloxane (PDMS) casting; (iii) cell seeding into device for cell attachment and (iv) chip removal for realizing cell patterning. All the procedures contain no conventional photolithography, and therefore can be reproduced in any biological laboratory. Moreover, by using adhesive tape, we can easily archive different channel height by sticking multiple tape layers and cutting them together. We characterized the multiple layer mold in Figure S1. The micrographs show that the channel’s cross-section height of the PDMS chip was increased proportionally with stacking layers of tape. A lower chip may cause difficulties and unevenness when introducing the cell suspensions from inlet due to the high flow resistance. This stacking mold was especially useful in our application for patterning cells due to the higher channel can provide a smooth operation during cell seeding into the chip. In the TAPMiC assay, we use two layers mold (104 µm in height) to fabricate our device. Although the zigzagged wall can be found in PDMS chip due to tapes stacking (Figure S1), this unevenness of side wall does not hinder our experiment during cell patterning. However, molds within more than three layers will result in difficulties in punching the holes on the tape. Besides, other than our purpose for cell patterning, we believe this stacking up tape mold technique can be useful in multiple height chip applications.

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To gain statistic data, multiple-sites image based assessing of cell migration have been achieved by 45 pillars (300 µm in diameter, 104 µm in height), arrayed like the hexagonal lattice in TAPMiC chip, which is 1 cm X 2 cm as shown in figure 1b. Distinguished from the existing commercially developed assay, the exclusion zone in TAPMiC assay only occupies 70685 µm2 which are only 1/44 in area than that of the commercial assay.34 This configuration brings at least two merits: (i) the scalable format of initiating cell blank region allows shorted time for cell migration analysis and thus will smooth the timetable for data gaining (typically 400 min for fully healing compared with 14 hours in commercialized assay);34 (ii) this technology enables avoidance of confounding influence from proliferation during cell migration (Figure S3). The result in figure S3 shows that during this short time frame, cell mitosis rarely happens and can be neglected. Thus our approach can be used to dissect cell mobility without the interfering from cell mitosis, eliminating the requirement for cell synchronization before migration assay. Cell migration assay on “TAPMiC” We first applied our “TAPMiC assay” to determinate how the soluble promotive factor, such as fetal bovine serum (FBS) and dispiriting factors, like anti-motile components, can affect cell migration. For precisely evaluating cell migration, we measured the area of cell-free region plotted for time-series by analyzing time-lapse images using Fiji (NIH Image, https://fiji.sc/)35 when the cancer cells were migrated through ECM coated interface (see in supplementary information). Quantitatively, in figure 2a, results indicated that the higher content of FBS, the faster cell migrates. Figure 2b shows the corresponding images of a cell-free zone (CFZ, in light cyan) during cell migration under 12 ACS Paragon Plus Environment

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different FBS percentage of 0, 1, 5, 10, 15 and 20, respectively. These results indicate that our TAPMiC assay can detect the subtle difference in cell migration even for slight conditional variations in the microenvironment. Also, we performed time-lapse imaging to quantify cell migration both by scratching and TAPMiC with the time interval of 50 min (Figure S4). Migration curve suggests that compared with our method, scratch assay presents considerable variations (SD = ± 28%) than that of TAPMiC (SD = ± 5%). The variation in the scratch assay mainly came from i) difficulties of addressing observation area from last time-lapse image; ii) The unevenness of scratched cell-free area. This result indicated that in addition to providing spatial addressable CFZ, our approach shows 5-fold improvement in reproducibility by amending the jagged edge comparing scratch assay. Next, by similar measurement, we investigated the effects of different migration inhibitors on different tumor cell types. To assess the impact of different components on cell mobility, we added those inhibitors at 75 min after releasing pattern. The migration plotting on treatment group shows that after drug adding, those curves immediately separated from the control group (no inhibitor added, Movie S1) and decreased sharply due to the inhibition effect on cell movement (Figure 2c, d). In addition, the results suggest that, compared with other inhibitors, GM6001 (Ilomastat, or galardin), demonstrated the most powerful depressive effect on cell migration in both type of tumors (epithelial lung cancer A549 and fibrosarcoma HT1080), indicating that as a broad spectrum MMPs inhibitor, galardin can significantly reduce cancer cell mobility. Reversine, Cytochalasin D, and Cycloheximide presented moderate impeding validity on cell migration (Movie S2). We found that both cell death inducers reversine and

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cycloheximide present limited impact on cell migration in HT1080 cells whereas obstructing cell spread in A549 cancer cells (Figure 2c, d), indicating that different cell types could react differently to the same component. In general, malignant fibrosarcoma cell (HT1080) presents higher motility36 than lung cancer A549 and is sensitive to MMP inhibitor GM6001 and actin polymerization disturber Cytochalasin D. Motivated by heterogeneous migration behavior based on cell type itself, we then systematically investigated four different cell lines (MCF-7, MDA-MB231, HT1080, A549 and fibroblast NHDF) to profile the migration baseline for each cell type. We figured out that compared with other cancerous cell lines, the somatic fibroblast NHDF holds the lower cell motility indicated by CFZ index is around 0.5 after 400 min migration, and in contrast, the CFZ index is near to 0 (completed healing of CFZ) for HT1080, MDAMB231 and A549 tumor cells. Notably, the fibrosarcoma HT1080 and malignant breast cancer cell MDA-MB231 exhibited most vigorous metastasis on collagen coating with CFZ healing completely at 150 min, comparing with less malignant breast cancer cell MCF-7 and lung cancer A549.36 Thus, the ability to differentiate subtle changes in cell motility makes TAPMiC assay an ideal tool for analyzing cell metastasis and migration varying on different conditions. To verify this technology is capable of investigating relevant genes on migration pathway due to its precision on measurements, we then performed siRNA mediated gene silence in lung cancer A549 cells (see in Supplementary information) and analyzed cell migration on TAPMiC (Figure 2f). The results show that all selected siRNAs can decrease cell migration speed, and the dynamic curve enables distinguishing impalpable changes on cell migration between different siRNA. 14 ACS Paragon Plus Environment

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Importantly, the dynamic curves enable more accurate assessment of motilities after blocking specific gene expression in cells. We figured out that, silencing of MMP-9, an enzyme plays a pivotal role in the degradation of the extracellular matrix, can significantly inhibit tumor cell metastasis on collagen matrix coating.37 Likewise, other genes including TM4SF1, AQP-1, VDAC, and ROCK-1 also participated in cell metastasis even though not as effective as MMP-9 silencing, as shown in Figure 2f.

38

In addition, all the knocking down treatments have been validated by western blotting in siRNA transfected A549 (see in supplementary information). These differences are not able to be unveiled by conventional ways like scratching assay which incapable of distinguishing net cell migration from cell division, which may alleviate siRNA in cells and turn slightly affects cell migration results. Co-patterning and single cell tracking When a cancer cell metastasizes, it first will migrate in ECM, exposed to cancer associated fibroblasts, and then get through normal fibroblasts in the immediate tumor microenvironment. Thus fabricating a microenvironment that can recapitulate tumor niche with multiple types of cells is doubtlessly urgent. To address this scenario, we implemented our TAPMiC technique and realized co-patterning of tumor and fibroblast cells on a collagen I coated culture plate. We first performed fibroblast cell patterning in TAPMiC chip as described. After incubation and careful wash, tumor cells then selectively seeded on the CFZ due to the occupation of fibroblast (Figure 3a). The tumor cells and fibroblasts were well patterned on ECM coated surface where only few cancer cells were located on the seams between fibroblast cells (see Figure S5.).

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To investigate the tumor-fibroblast interactions during cancer progression, we conducted time-lapse imaging to depict tumor cell invasion process with fibroblast around quantitatively. The tumor cells continuously spread and invaded into fibroblast cells as shown in figure 3a. Benefits from short time interval imaging-process, we can track the dynamic motion of every individual cell in the field of view and even multiple spots by laser confocal microscope (FV1200, Olympus, Japan) with the multi-area timelapse software module. After co-pattern has formed on the collagen-coated substrate, we encoded the software to snap bright and fluorescent-filed images on specific view spot where tumor-fibroblast co-patterns generated. Supported by automated motorized microscope stage (Prior Scientific, UK), this coding allows us to take pictures back and forth on interested co-culture regions with the time interval of 15 min. To gain dynamic invasion and metastasis at single cell level, we illustrated few trajectories of single tumor cell migration in Figure 3b and trajectories of tumor cells. Video records were also included, demonstrating the tumor-fibroblast metastasis in Movie S3. The results suggest that during tumor metastasis, the tumor cells show sinuous but ceaseless overrunning into adjacent fibroblast which was in turn, retreated due to the contact inhibition of locomotion.39 Moreover, to analyze different tumors, we further applied co-patterning and cell metastasis assay using different tumor-fibroblast pairs including HT1080, MCF-7 and A549 cells with fibroblast. The fibrosarcoma HT1080 shows most invasive ability and malignancy, taking less than 8 hours to doubled cancer region and invaded adjacent fibroblast that has retreated from the field of view, which consists with previous migration assay (Figure 3c).36 After 12 hours copatterning, the breast tumor cell line MCF-7 region expanded 1.5X from initiation,

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implying less malignancy than HT1080 cells. Interestingly, at the beginning (4 hours), the epithelial lung cancer A549 shrank first whereas fibroblast stepped forward and then ceased with consequent withdrew after 4 hours from initiation of metastasis. This quantitively phenotypic observation, which is benefit from our technology due to the ability to detect subtle changing of cell migration during tumor-fibroblast interactions, hints complicated mechanism may still behind tumor invasion other than an intuitive hypothesis. Therefore, our approach not only allows cell migration analysis with short time frame but also cell-cell interactions imaging deciphering during tumor invasion and metastasis. Gene expression analysis of tumor-fibroblast pairing. Last but not the least, the signaling pathway regulation is a hallmark of cancer invasion and metastasis. Previously, no examples that are enabling cell co-patterning interactions analysis together with gene expression profiling on a scalable microfluidic device have been presented. We next applied our TAPMiC device to dissect gene expression on each type of cells by using quantitative PCR during tumor metastasis. Around 10-20 cells were picked up and put into lysis buffer directly to perform single-cell transcriptome amplification and subsequent qPCR analysis.40 Due to the precision of mouth pipette, we can accurately retrieve specific cells (around 30 cells) from cell-cell co-patterning from cell pairing or mono-typical cell migration (Figure 4a). Those picked cells were double-checked under a fluorescent microscope to guarantee homo-typical selection for either tumor cells or fibroblast cells. To determine gene expression level with and without cell-cell interactions, we carried out qPCR testing on 11 genes, MMP2, VEGFA, MYC-1, PLAU, GREM1, MMP14, CCL2, PCNA, CCND1, LDHA, and GAPDH 17 ACS Paragon Plus Environment

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which was used as a reference gene for normalization. Gene expression heat map shows that matrix metalloproteinase-2 (MMP-2) was significantly up-regulated in A549 cancer cells under tumor-fibroblast interactions, indicating a hint that tumor cells have enhanced their function for ECM degradation, which allows cancer cells to migrate out of the primary site to form metastases (Figure 4b).41, 42 Likewise, most dominate inducer for the growth of blood vessels like VEGFA also shows transcriptional enhancement at co-patterning case.43 VEGFA promotion in the tumor itself would be used for recruiting endothelial cells for enabling angiogenesis in the microenvironment.44 One of the essential factor in DNA synthesis and repairing, proliferating cell nuclear antigen (PCNA), also present a remote up-regulation in fibroblast

co-cultured

tumor cells

compared

with

a

homo-cultivated

tumor.45

Unexpectedly, another extracellular matrix metalloproteinase MMP14 and a serine protease gene (PLAU), which also involved in degradation of the extracellular matrix and possibly tumor cell migration and proliferation, were down-regulated slightly in tumor under co-patterning condition. Those results with up- and down-regulatory patterns of different genes underlines a delicate balance between positive and negative factors during metastatic process, emphasizing the complexity of the cancer progression and the possible contrasting of varying protein family members. Interestingly, the fibroblast around tumor cells shows significant up-regulation on not only VEGFA but also PCNA and GREM1 (gremlin), which has been reported that is widely expressed by cancer-associated stromal cells and can promote tumor cell proliferation.46 This data hints that during metastasis, tumor-fibroblast pairing may interact reciprocally to each other and in turn, facilitating tumor progression.6, 47

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Noticeably, above regulation occurs in a relatively short period (within 12 hours) before we retrieve the cell pellets from co-patterning, and regarding cell-cell interaction, longterm co-culture may bring some in-depth and comprehensive analysis together with short-term co-patterning because cell-cell communication may take time for pathway regulation in each type of cells. Therefore, besides analyzing cellular prototype such as migration, our TAPMiC method also allows recapitulating metastatic microenvironment and consequently dissecting gene expression regulation between tumor and fibroblast pairing.

Conclusion: Tumorgenesis is regulated in a sophisticated manner as a result of interactions between malignant cells and surrounding microenvironment including the tumor stroma. A better understanding of the tumor phenotype such as metastatic migration and invasion that occurs in tumor niche in response to the presence of other cells types may lead to new insight for cancer development. Cell micro-patterning provides an efficient way to study tumor development in vitro due to the ability to recapitulate the tumor environment with spatial and temporal control. To circumvent requisite of a micro-fabricated device for performing cell patterning, we leveraged a hand-crafted tape mold to replicate PDMS chip. Our approach provides a lithographically independent, cost-effective way that can pattern or even co-pattern multiple types of cells, enabling quantitative parametric statistics on cell metastasis. We demonstrated that slight differences on metastatic migration could be unveiled by using this technique. Moreover, we redeemed RNA silencing of particular genes, single cell tracking, and genetical analysis several key gene regulations mediated by tumor-fibroblast interactions. Results show that MMP2 19 ACS Paragon Plus Environment

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VEGFA and PCNA have been up-regulated in both cell types in the tumor-fibroblast niche, implying reciprocal interactions between tumor and fibroblast. Therefore, this "TAPMiC" assay allows a simple and quantitative study on in vitro cancer metastasis.

Acknowledgement. We thank Prof. Hongwu Du, Prof. Yongqiang Wen, Prof. Lei Su, and Prof. Xueji Zhang in School of Chemistry and Biological Engineering, University of Science and Technology Beijing, and Dr. Lei Wang in CapitalBio Corporation for fruitful discussion. We acknowledge funding support from National Natural Science Foundation of China (21675011, 21305007). National Key R&D Program of China (2016YFC0106601), Beijing Higher Education Young Elite Teacher Project (YETP0423) and Chinese government scholarship from Chinese Scholarship Council (201406465024).

Notes The authors declare no competing financial interest.

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Figure Captions: Figure 1. The strategy of “TAPMiC” (Tape Assisted Photolithographic-free Microfluidic Chip) cell patterning. (a) Schematic workflow for fabricating device and patterning cells. (b) Picture of “TAPMic” chip. Chip was filled with red and blue food dye respectively. (c) Micrographic images for characterization cell patterning on the chip. Before and after chip removed from the substrate. Lung cancer cells A549 were stained with Calcein-AM (green) and PI (red) (Left). Scale bar: 100 µm.

Figure 2. TAPMiC based quantitative characterization of cell migration via imaging analysis. (a) Cell migration speed decreased proportionally as FBS concentration declined. Area of the cell-free zone (CFZ) blank region at certain time points was normalized to diagram cell migration. (n=6) (b) Series of time-lapse micrographs illustrate that high FBS concentration can facilitate A549 cell migration. CFZs are noted in each panel by light cyan. Scale bar is 300 µm. (c) Different chemical components inhibited HT1080 cell migration versus the control group. (n=6) (d) Migration curves indicate drug caused inhibition of A549 cells movement. All compounds were added at the time point of 75 min to demonstrate clear changes of cell mobilities affected by soluble factors in the microenvironment. (n=6) (e) Different cell type migration curves were measured to show heterogeneous cell mobility under 10% FBS concentration in the medium. (f) Migration curves of different RNAi assay on A549 cells, indicating positive roles of corresponding genes in migration pathway (Left). Western blotting validation for gene knockdown in A549 cells 48 hours after siRNA transfected (Right). Scrambling siRNA was used as a control. GAPDH is showed as a housekeeping gene loading control.

Figure 3. Analysis of recapitulated tumor-fibroblast metastasis by using TAPMiC copattering. (a) Time-lapse fluorescent confocal images illustrated tumor cells (A549) invasively metastasized into adjacent fibroblast by co-patterning cells on collagen I coated culture plate. (b) Single cell movement could be tracked during invasion process. Colored traces indicate individual tumor cells trajectory from image series. Scale bar is 100 µm. (c) Metastasis curves 21 ACS Paragon Plus Environment

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illustrate cell-cell interactions during different tumor cell (A549, HT1080, MCF-7) invasion. Cell occupied area in the field of view was used to characterize collective cell migration behaviors on tumor and fibroblast respectively. Different colors in metastasis curve indicate difference for tumor-fibroblast pairing, black for A549-NHDF, red for HT1080-NHDF, and blue for MCF7NHDF co-patterning respectively.

Figure 4. Analysis of gene regulation in tumor-fibroblast metastasis by using TAPMiC assay. (a) Fluorescent confocal images indicate that specific group of cells can be precisely retrieved by using mouth pipette. Fibroblast cells were previously stained with CellTracker Green CMFDA dye. Tumor cell A549 were labeled with CellTracker Red CMTPX dye. Scale bar is 100 µm. (b) Gene expression heat map shows regulated critical genes in co-patterned A549 cancer cells versus homo-pattern (-∆∆Ct method was applied for normalization). All genes expression level has been normalized with housekeeping gene GAPDH and bulk cultured condition. Three sample replicates were conducted in each group to show correlations and variation. (c) Expression heat map of NHDF fibroblast cells in co-patterning and homopatterning conditions. All conditions are same as in (b).

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References: (1)

Gupta, G. P.; Massague, J. Cell 2006, 127, 679-695.

(2)

Valastyan, S.; Weinberg, R. A. Cell 2011, 147, 275–292.

(3)

Friedl, P.; Alexander, S. Cell, 2011, 147, 992–1009.

(4)

Clark, A. G.; Vignjevic, D. M. Curr. Opin. Cell Biol. 2015, 36, 13-22.

(5)

Paul, C. D.; Mistriotis, P.; Konstantopoulos, K. Nat. Rev. Cancer 2017, 17, 131140.

(6)

Madar, S.; Goldstein, I.; Rotter, V. Trends Mol. Med. 2013, 19, 447-453.

(7)

Boyden, S. V. J. Exp. Med. 1962, 115, 453-466.

(8)

Todaro, G. J.; Lazar,G. K.; Howard, G. J. Cell. Physiol. 1965, 66, 325-333.

(9)

Liang, C.; Park, A. Y.; Guan, J. Nat. Protoc. 2007, 2, 329-333.

(10)

Kramer, N.; Walzl, A.; Unger, C.; Rosner, M.; Krupitza, G.; Hengstschla¨ger, M.; Dolznig, H. Mutat. Res. 2013, 752, 10-24.

(11)

Wang, L.; Zhu, J.; Deng, C.; Xing, W. L.; Cheng, J. Lab Chip 2008, 8, 872-878.

(12)

Xie, Y. Y.; Zhang, W.; Wang, L. M.; Sun, K.; Sun, Y.; Jiang, X. Lab Chip 2011, 11, 2819-2822.

(13)

Sticker, D.; Lechner, S.; Jungreuthmayer, C.;Zanghellini, J.; Ertl, P. Anal. Chem. 2017, 89, 2326-2333.

(14)

Lei, Y.; Tang, L.; Xie, Y.; Xianyu, Y.; Zhang, L.; Wang, P.; Hamada, Y.; Jiang, Kai.; Zheng W.; Jiang, X. Nat. Commun. 2017, 8, 15130.

(15)

Hui, E. E.; Bhatia, S. N. Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 5722-5726.

(16)

Khademhosseini, A.; Ferreira, L.; Blumling III, J.; Yeh, J.; Karp, J. M.; Fukuda, J.; Langer, R. Biomaterials 2006, 27, 5968-5977.

(17)

Hwang, Y.; Chung, B. G.; Ortmann, D.; Hattori, N.; Moeller, H.; Khademhosseini, A. Proc. Natl. Acad. Sci. U. S. A. 2009, 106, 16978-16983.

(18)

Kaji, H.; Yokoi, T.; Kawashima, T.; Nishizawa, M. Lab Chip 2009, 9, 427-432.

(19)

Zheng, C.; Zhao, L.; Chen, G.; Zhou, Y.; Pang, Y.; Huang, Y. Anal. Chem. 2012, 84, 2088-2093.

23 ACS Paragon Plus Environment

Analytical Chemistry

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(20)

Page 24 of 30

Li, N.; Zhang, W. Khan, M.; Lin, L.; Lin, J. M. Biosensors and Bioelectronics, 2018, 99, 142-149.

(21)

Lin, X.; Chen, Q.; Liu, W.; Zhang, J.; Wang, S.; Lin, Z.; Lin, J. M. Scientific Reports 2015, 5, 9643.

(22)

Liu, D. B.; Xie, Y. Y.; Shao, H. W.; Jiang, X. Angew. Chem. Int. Ed. 2009, 48, 4406-4408.

(23)

Zhang, H.; Hao, Y.; Yang, J.; Zhou, Y.; Li, J.; Yin, S.; Sun, C.; Ma, M.; Huang, Y.; Xi, J. J. Nat. Commun. 2011, 2, 554.

(24)

Zhang, K.; Chou, C. K.; Xia, X.; Hung, M. C.; Qin L. Proc. Natl. Acad. Sci. U. S. A. 2014 111: 2948-2953.

(25)

Huang, L.; Chen, Y.; Weng, L. T.; Leung, M.; Xing, X.; Fan, Z.; Wu, H. Anal. Chem. 2016, 88, 12196-12203.

(26)

Collins, D. J.; Morahan, B.; Garcia-Bustos, J.; Doerig, C.; Plebanski M.; Neild A. Nat. Comm. 2015, 6, 8686.

(27)

Guo, F.; Li, P.; French, J. B.; Mao, Z.; Zhao, H.; Li, S.; Nama, N.; Fick, J. R.; Benkovic, S. J.; Huang, T. J. Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 43-48.

(28)

Zheng, C.; Yu, Z.; Zhou, Y.; Tao, L.; Pang, Y.; Chen, T.; Zhang, X.; Qiu, H.; Zhou, H.; Chen, Z.; Huang Y. Lab Chip, 2012, 12, 3063-3072.

(29)

Zhou, H.; Zhao, L.; Zhang, X. Anal. Chem. 2015, 87, 2048-2053.

(30)

Shen, K.; Luk, S.; Hicks, D. F.; Elman, J. S.; Bohr, S.; Iwamoto, Y.; Murray, R.; Pena, K.; Wang, F.; Seker, E.; Weissleder, R.; Yarmush, M. L.; Toner, M.; Sgroi, D.; Parekkadan, B. Nat. Commun. 2014, 5, 5662.

(31)

Javaherian, S.; O’Donnell, K. A.; McGuigan, A. P. PLoS One 2011, 6, e20909.

(32)

Nakata, M.; Kawaguchi, S.; Oikawa, A.; Inamura, A.; Nomoto, S.; Miyai, H.; Nonaka, T.; Ichimi, S.; Fujita-Yamaguchi, Y.; Luo, C. Gao, B.; Tang, W. Drug Discoveries & Therapeutics. 2015; 9, 417-421.

(33)

Zhao, L.; Cheng, P.; Li, J.; Zhang, Y.; Gu, M.; Liu, J.; Zhang J.; Zhu, J. J. Anal. Chem., 2009, 81, 7075-7080.

(34)

Glenn, H. L.; Messner, J.; Meldrum, D. R. Sci. Rep. 2016, 6, 31694.

(35)

Schindelin,J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saalfeld, S.; Schmid, B.; Tinevez, J.; White, D. J.;

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Page 25 of 30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

Hartenstein, V.; Eliceiri, K.; Tomancak, P.; Cardona, A. Nature Methods 2012, 9, 676-682. (36)

Gayan, S.; Teli, A.; Dey, T. Sci. Rep., 2017, 7, 11527.

(37)

Joshia, P.; Jeona, Y.; Laganàb, A.; Middletona, J.; Secchieroc, P.; Garofalod, M.; Crocea, C. M. Proc. Natl. Acad. Sci. U.S.A. 2015, 112, 8650-8655.

(38)

Allioli, N.; Vincent, S.; Vlaeminck-Guillem, V.; Decaussin-Petrucci, M.; Ragage, F.; Ruffion, A.; Samarut, J. Prostate. 2011, 71, 1239-1250.

(39)

Mayor, R.; Etienne-Manneville, S. Nature Rev. Mol. Cell Biol. 2016, 17, 97-109.

(40)

Tang, F.; Barbacioru, C.; Wang, Y.; Nordman, E.; Lee, C.; Xu, N.; Wang, X.; Tuch, B.; Bodeau, J.; Siddiqui, A.; Lao, K.; Surani, M. Nat. Methods 2009, 6, 377382.

(41)

Olsen, C. J.; Moreira, J.; Lukanidin, E. M.; Ambartsumian, N. S. BMC Cancer 2010, 10, 444.

(42)

Saad, S.; Bendall, L. J.; James, A.; Gottlieb, D. J.; Bradstock, K. F. Breast Cancer Res Treat. 2000, 63, 105-115.

(43)

Salvatore, V.; Teti, G.; Focaroli, S.; Mazzotti, M. C.; Mazzotti, A.; Falconi, M. Oncotarget, 2017, 8, 9608-9616.

(44)

Carmeliet, P. Oncology 2005, 69, 4-10.

(45)

Xu, L. N.; Xu, B. N.; Cai, J.; Yang, J. B.; Lin, N. Genet Mol Res. 2013, 12, 58635871.

(46)

Sneddon, J. B.; Zhen, H. H.; Montgomery, K.; van de Rijn, M.; Tward, A. D.; West, R.; Gladstone, H.; Chang, H. Y.; Morganroth, G. S.; Oro, A. E.; Brown, P. O. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 14842-14847.

(47)

Kessenbrock, K.; Plaks, V.; Werb, Z. Cell 2010, 141, 52-67.

TOC

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Figure 1. The strategy of “TAPMiC” (Tape Assisted Photolithographic-free Microfluidic Chip) cell patterning. (a) Schematic workflow for fabricating device and patterning cells. (b) Picture of “TAPMic” chip. Chip was filled with red and blue food dye respectively. (c) Micrographic images for characterization cell patterning on the chip. Before and after chip removed from the substrate. Lung cancer cells A549 were stained with Calcein-AM (green) and PI (red) (Left). Scale bar: 100 µm. 162x88mm (300 x 300 DPI)

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Figure 2. TAPMiC based quantitative characterization of cell migration via imaging analysis. (a) Cell migration speed decreased proportionally as FBS concentration declined. Area of the cell-free zone (CFZ) blank region at certain time points was normalized to diagram cell migration. (n=6) (b) Series of time-lapse micrographs illustrate that high FBS concentration can facilitate A549 cell migration. CFZs are noted in each panel by light cyan. Scale bar is 300 µm. (c) Different chemical components inhibited HT1080 cell migration versus the control group. (n=6) (d) Migration curves indicate drug caused inhibition of A549 cells movement. All compounds were added at the time point of 75 min to demonstrate clear changes of cell mobilities affected by soluble factors in the microenvironment. (n=6) (e) Different cell type migration curves were measured to show heterogeneous cell mobility under 10% FBS concentration in the medium. (f) Migration curves of different RNAi assay on A549 cells, indicating positive roles of corresponding genes in migration pathway (Left). Western blotting validation for gene knockdown in A549 cells 48 hours after siRNA transfected (Right). Scrambling siRNA was used as a control. GAPDH is showed as a housekeeping gene loading control. 177x190mm (300 x 300 DPI)

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Figure 3. Analysis of recapitulated tumor-fibroblast metastasis by using TAPMiC co-pattering. (a) Time-lapse fluorescent confocal images illustrated tumor cells (A549) invasively metastasized into adjacent fibroblast by co-patterning cells on collagen I coated culture plate. (b) Single cell movement could be tracked during invasion process. Colored traces indicate individual tumor cells trajectory from image series. Scale bar is 100 µm. (c) Metastasis curves illustrate cell-cell interactions during different tumor cell (A549, HT1080, MCF-7) invasion. Cell occupied area in the field of view was used to characterize collective cell migration behaviors on tumor and fibroblast respectively. Different colors in metastasis curve indicate difference for tumor-fibroblast pairing, black for A549-NHDF, red for HT1080-NHDF, and blue for MCF7-NHDF copatterning respectively. 84x89mm (300 x 300 DPI)

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Figure 4. Analysis of gene regulation in tumor-fibroblast metastasis by using TAPMiC assay. (a) Fluorescent confocal images indicate that specific group of cells can be precisely retrieved by using mouth pipette. Fibroblast cells were previously stained with CellTracker Green CMFDA dye. Tumor cell A549 were labeled with CellTracker Red CMTPX dye. Scale bar is 100 µm. (b) Gene expression heat map shows regulated critical genes in co-patterned A549 cancer cells versus homo-pattern (-∆∆Ct method was applied for normalization). All genes expression level has been normalized with housekeeping gene GAPDH and bulk cultured condition. Three sample replicates were conducted in each group to show correlations and variation. (c) Expression heat map of NHDF fibroblast cells in co-patterning and homo-patterning conditions. All conditions are same as in (b). 165x68mm (300 x 300 DPI)

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