Development of an in vitro microfluidic model to study the role of microenvironmental cells in oral cancer metastasis

HUVEC cell culture

Human umbilical vein endothelial cells (HUVECs, Lonza, cat. no. C2519A; RRID: CVCL_2959) were obtained from Lonza and cultured in EGM-2 medium (Promocell) at 37°C with 5% CO₂. Cells were passaged when a 70–80% confluence was reached. To passage the cells, a wash with phosphate buffered saline (PBS) was first performed and cells were detached using 0.05% Trypsin-EDTA 1X (2.5 ml per T75 flask, Sigma) for 1.5 minutes. EGM-2 was then added to neutralise the trypsin. Cells were used until passage six.

OSCC cell culture

OSCC cells (see Table 1 below for details) were cultured at 37°C with 5% CO₂ in Dulbecco's Modified Eagle Medium (DMEM)-F12 (1:1) + GlutaMAX (31331093, Thermofisher Scientific), supplemented with 10% Fetal Bovine serum (FBS, FB-1001, Biosera), 1% Penicillin-Streptomycin (Pen-strep, Sigma-Aldrich) and 1% RM+ (composed of 10 ng/ml Epidermal Growth Factor [EGF-1, Serotec], 10^-10 M Cholera Toxin [Sigma-Aldrich], 0.4 μg/ml Hydrocortisone [Sigma-Aldrich], 5 μg/ml Insulin [Sigma-Aldrich], 5 μg/ml Transferrin [Sigma-Aldrich], 2×10^-11M 3,3′,5-Triiodo-L-Thyronine Sodium Salt [Sigma-Aldrich] in DMEM-F12 medium). Cells were passaged when a 70% confluence was reached, by washing them with PBS and detaching them using 0.05% Trypsin-EDTA 1X (Sigma). Once detached, growth medium was added to neutralise the trypsin. Cells were used only at low passage from frozen stocks (up to approx. passage eight), and discarded if gross changes in cell and colony morphology in tissue culture were observed. Retroviral transduction for production of a GFP tagged CA1 OSCC cell line was performed previously (Gemenetzidis et al., 2015).

Microfluidic chip fabrication

The microfluidic chip pattern was designed on AutoCAD^® and printed as a film photomask. The device was composed of three channels (700 μm width, ~75 μm height), separated from each other by an array of trapezoidal posts which prevent gel leakage into the side channels whilst allowing cells and signalling molecules to move freely across (100 μm base, 100 μm apart, Figure 1A).

Figure 1. Microfluidic device structure.

A. 3-channel microfluidic chip device. Medium is added in the side channels whereas the gel is added in the middle channel. Each channel width is 700 μm, and the height is 75 μm; this enables a minimal working distance from the coverslip. The side channels are delineated from the middle channels by an array of posts, which are 100 μm large and 100 μm apart. B. A cut out PDMS block with side channel inlets (black arrows) and central inlets (white arrows), showing the size of the microfluidic device. It will be bonded to a glass cover slip on the bottom.

To fabricate the device, a silicon wafer bearing the positive pattern of the chip was generated by photolithography. First, the wafer (PI-KEM) was washed, using acetone and isopropan-2-ol, and dried with nitrogen gas. The wafer was then spin-coated with SU-8 2050 photoresist (Kayaku Advanced Materials), by using the following spinning protocol: 500 RPM for 15 seconds with an acceleration of 100 RPM/s and 1700 RPM for 36 seconds with an acceleration of 300 RPM/s. Soft bake was performed by heating the wafer at 65°C for five minutes and 95°C for 15 minutes. The photomask, bearing the pattern of the chip, was placed on the wafer and exposed to UV light (45 mW/cm²) for one second. The wafer was then heated at 65°C for five minutes and 95°C for 10 minutes, before being immersed in the developing solution, propylene glycol methyl ether acetate (PGMEA, Sigma-Aldrich), for a maximum of five minutes. Finally, a hard bake was conducted by exposing the wafer at 150°C for three minutes.

The resulting silicon wafer bearing the pattern of the desired chip was placed in a petri dish, covered with PDMS and left to set at 80°C. Once crosslinked, the PDMS block was cut out so that new PDMS could be poured onto the silicon wafer, to make new blocks. Blocks were cleaned using ispropan-2-ol and sealed to a glass coverslip via plasma bonding, to close the microchannels. Devices were placed at 80°C for three days, to allow the hydrophobicity of the PDMS to recover, and autoclaved before use for cell culture assays.

Cell culture in the microfluidic device

A fibrin gel was prepared using fibrinogen from bovine plasma (10–15 mg/ml in PBS, Sigma) and thrombin from bovine plasma (5 U/ml in PBS, Sigma-Aldrich). The gel was added in the middle channel via one of the two inlets and pipetted down at a slow pace to prevent leakage (Figure 2i, ii). The gel was left to set at 37°C for 30 minutes, before adding medium to the side channels.

Figure 2. Co-culture experiment set-up.

i) Microfluidic Device. ii) A fibrin gel was added in the middle channel. iii-iv) HUVECs were seeded in the left side channel and left to grow in the fibrin gel of the middle channel. v-vi) OSCC cells were then seeded in the right side channel and left to grow in the middle channel.

As bubbles may assemble around the posts soon after the addition of medium to the side channels, the devices were left at 37°C overnight to allow these bubbles to dissolve. Medium was then aspirated from all the side channels inlets and 8 μl of a 5 million cells/ml HUVECs suspension was added to one of the inlets of the left side channel (Figure 2iii). To allow cells to adhere to the gel interface, the devices were flipped at 90° for 30 minutes. EGM-2 medium was supplemented with VEGF (50 ng/ml, Peprotech) and added to all the side channels. To enhance sprouting of the HUVECs, to form a developing vascular network within the gel, a flow against the cells was set up by increasing the volume of medium added in the opposite side channel (110 μl of medium in the inlets of the right side channels and 90 μl of the medium in the inlets of the HUVECs side channel). Medium was replaced every 24 hours.

When a vasculature was formed (after approx. four days) (Figure 2iv), OSCC cells were added in the opposite side channel (Figure 2v). Medium was aspirated from all the side channel inlets and 8 μl of a 5 million cells/ml OSCC solution was added to one of the inlets of the right side channel. To allow cells to adhere to the gel interface, the devices were flipped at 90° for 30 minutes. EGM-2 medium supplemented with VEGF (50 ng/ml, Peprotech) was added to both medium channels. Note that DMEM-F12 was not used in the co-culture, to allow the maintenance of endothelial cells in the device.

When the desired time-point of co-culture was reached (Figure 2vi), cells were washed twice with PBS and fixed by adding 100 μl of 4% paraformaldehyde (PFA) in all the inlets for 15 minutes. Cells were washed twice with PBS and left in PBS at 4°C until stained and imaged.

Staining and imaging

Staining reagents were added into both medium channels. Cells were permeabilised with 0.1% Triton X-100 (Sigma-Aldrich) for 10 minutes and blocked for three hours (3% BSA in PBS), at room temperature. If stained with phalloidin (1/500, Scientific Laboratory Supplies) and DAPI (1/1000 in PBS from 1 mg/ml stocks, 10236276001, Roche) or just DAPI, these stains were mixed with the blocking buffer directly and added in each microfluidic chip inlet (100 μl per inlet) for one hour, at room temperature. Cells were washed twice with PBS and left in PBS at 4°C until imaged. When conjugated antibodies were used (see Table 2, below), the antibody mix was prepared using blocking buffer. After the blocking step, 60 μl of the antibody mix was added in each inlet of the microfluidic chips and left overnight at 4°C. Cells were then stained with DAPI for one hour, washed twice with PBS and left in PBS at 4°C until imaged.

Imaging was performed using the IN Cell Analyzer 6000 (GE healthcare). Five to six fields of views, using the 20× magnification, were taken to cover the entire middle channel.

Detailed protocols

Photolithography

Please note: SU8-2050 is light sensitive, steps 1 to 6 need to be conducted in the dark and under a fume hood

PDMS pouring and plasma bonding

Addition of the gel in the microfluidic chips

Addition of the cells in the microfluidic chips

Developer toolbox (GE Healthcare, version 1.10) protocols

In the following, the parameters for the two image analysis protocols in Developer Toolbox (GE Healthcare) are described, allowing the reader to recreate the protocol in the software. Applying a step-by-step process, the software allows the user to interactively adapt parameters to achieve optimal segmentation. In each step, a specific target is segmented using the user’s chosen algorithm, then postprocessing steps are applied to refine the segmentation, and lastly measures for the target are identified. Once target objects are segmented, they can be used to identify other targets in the following steps.

Segmentation algorithms include object segmentation, nuclear segmentation, and intensity segmentation. Object segmentation is kernel-based; kernel size and intensity sensitivity (i.e. minimum object brightness-to-background brightness ratio) are chosen by the user. The nuclear segmentation algorithm segments into rounded or octagonal objects using a minimum target area and sensitivity given by the user. Lastly, intensity segmentation identifies objects based on an intensity range defined by the user allowing any object size.

Post-processing steps used here include binary erosion, clump breaking, hole filling and a binary sieve. Binary erosion allows the user to smooth object boundaries using a kernel. Clump breaking utilises a second target to create segmentation between objects. For example, when clump breaking is applied to the ‘GFP cells’ target, the distance between the nuclei targets is calculated and segmentations are made at equal distances. Hole filling removes exclusions from objects, and the sieve removes objects larger or smaller than a user-defined area threshold.

After object segmentation of various targets, targets are linked to create the final cell objects. In this case, cell targets are linked to the nuclei targets. Any cell object that does not overlap with a nucleus object by at least 80% is removed, to ensure that all cell objects are nucleated.

Protocol 1

The following protocol was used in image analysis to segment two cell types in each field of view. One cell type was GFP-tagged (GFP cells). All the cells were stained with phalloidin (red fluorophore). Hence, two groups of cells were segmented: the red-only cells and the red and green cells.

Here, a ‘seed’ target is used to optimise nuclei segmentation. In this case, a seed target describes a small object located at the brightest part of the nucleus. By using a seed, the algorithm receives a starting point for nuclei segmentation, which improves segmentation performance compared to seedless segmentation. Next, GFP-positive cells were segmented based on their GFP fluorophore intensity. Then, all cells were segmented (Cells) based on the phalloidin intensity. GFP-negative cells were segmented by subtracting the GFP cells target from the Cells targets.

Target sets

Target linking

* Note: this step allows to subtract all the GFP cells target from the Cells target to segment the red-only cells. The end image result of Cells, GFP cells and GFP negative cells should be set on the 11^th, 10^th and 9^th windows of the programme respectively. GFP negative cells is a subtraction of GFP cells (window 10) from Cells (window 11).

Protocol 2

The following protocol was used to segment two cell types in each field of view, with two distinct fluorophores. One cell type was GFP-tagged (GFP cells), the other was RFP-tagged (RFP cells).

Target sets

Target linking

Angiogenesis assay

A simple representation of the angiogenesis process was reproduced in the microfluidic chips, by adding HUVECs in the left side channel and leaving them to grow into the fibrin gel in the middle channel. Results showed that endothelial cells formed sprouts in the matrix (Figure 3A). Furthermore, these tubular structures appeared to have a lumen, as when sprouts had grown across the whole middle channel, cells added in the opposite side channels directly migrated into these structures (Figure 3B). Hence, by simply adding HUVECs in our device containing fibrin, we have been able to reproduce a growing vascular network, with features resembling those observed in vivo. This is in good agreement with comparable reports of microvascularised chips, presenting lumenated perfusable structures at this time point (Kim et al., 2013; Dibble et al., 2022).

Figure 3. Angiogenesis assay.

A. HUVECs in the middle channel of the microfluidic chip at day 10. Red, phalloidin; Blue, DAPI. Posts are highlighted in white (dashed line). Scale bar: 100 μm. B. Migration of CA1 OSCC cells into the sprouts when added in the opposite side channel. Arrows indicate cells that migrated into the sprouts. Scale bar: 100 μm.

Co-culture of endothelial cells and OSCC cells to study metastasis

To study the interactions between the OSCC cells and the vasculature, co-culture of HUVECs and OSCC cells was optimised in the microfluidic chip. To allow the discrimination of these two cell types and accurate analysis of the images, GFP-tagged CA1 OSCC cells were used for this experiment (Figure 4). These OSCC cells were added in the opposite side channel when the HUVECs had grown half way across the middle channel, as assessed daily by light microscopy (typically by day 4). Results showed that this co-culture was successful as OSCC cells invaded towards the endothelial cells in the fibrin gel (Figure 4). This successful co-culture will enable the development of experiments to follow and assess the interactions between OSCC cells and the vascular network to better understand the metastasis of OSCC.

Figure 4. Co-culture of OSCC cells and HUVECs in the microfluidic chip.

HUVECs and CA1-GFP OSCC cells in the microfluidic chip 4 days after adding the OSCC cells. Red, phalloidin; Green (GFP tag), OSCC cells; Blue, DAPI. Posts are highlighted in white (dashed line). Scale bar: 100 μm.

Optimisation of the staining

To better understand the interactions between the cancer cells and the vasculature, the expression of specific markers must be assessed. To assess the expression of markers via imaging, such as the lineage markers vimentin and keratin (marking mesenchymal and epithelial lineages respectively), antibodies are required. Non-conjugated antibodies, with primary and secondary antibodies added separately, have been widely used and optimised for imaging in biomedical research. This method allows flexibility over the fluorophore combinations used when multiple marker expressions are being assessed simultaneously. However, when tested in our microfluidic device, high background noise was detected with non-conjugated antibodies, whereas this was not the case with conjugated antibodies (Figure 5). This background noise may reflect some retention of unbound secondary antibodies in the 3D matrix. Hence, this data shows that it may be preferable to use conjugated antibodies in microfluidic devices, to prevent high background noise and thus better analysis of the images obtained.

Figure 5. Optimisation of the staining.

Staining of CA1 OSCC cells with conjugated and non-conjugated antibodies. OSCC cells without vasculature. Red, Keratin; Green, Vimentin; Blue, DAPI. Posts are highlighted in white (dashed line). Scale bars: 100 μm.

Image analysis

Image analysis of the microfluidic chip experiments can be performed using several methods. For instance, for an automated approach, Developer Toolbox (GE Healthcare, version 1.10) can be employed. This programme can segment cells based on their fluorophore intensity and includes a multitude of tools enabling accurate counting of cells, assessment of the area they cover, their X position in the field of view, their shape, etc. (Figure 6A). This automated tool can successfully segment different cell types within a field of view, as long as the cells can be differentiated with a fluorophore. For instance, in Figure 4, cancer cells are GFP-tagged and all the cells are stained with phalloidin (red). Hence, the red-only cells are endothelial cells and the red and green cells are cancer cells. Other tools can also be used for image analysis. For instance, FIJI version 2.9.0 enables drawing of regions of interest manually on each field of view, such as lines surrounding the front of the cell mass, allowing assessment of the complexity of the shape of these masses invading into the matrix (Figure 6B).

Figure 6. Image analysis method examples.

A. Segmentation of each individual CA1-GFP cell using Developer Toolbox. B. Drawing of a region of interest in FIJI (line around the cell mass). CA1 cells stained for Vimentin (green), pan-keratin (red) and DAPI (blue).