Design of the 3D Tumor-Endothelial Intravasation Microfluidic-Based Assay.

The microfluidic assay consists of two independently addressable microchannels (Fig. 1A), where tumor and endothelial cells are seeded. These two channels are interconnected via a 3D ECM hydrogel, which includes 37 regions (Fig. 1B) enabling multiple simultaneous observations. The tumor cells invade in 3D in response to externally applied growth-factor gradients [e.g., epidermal growth factor (EGF) (26, 27)] or paracrine signals by the endothelial cells or other stromal cell types [e.g., macrophages (28, 29)]. On the 3D ECM-endothelial channel interface, a continuous endothelial monolayer is formed, which enables the observation of intravasation across a hollow vascular lumen, and allows for access to the basal and apical endothelial surfaces through the microchannels. Another important advantage compared to two-dimensional and transwell assays, is the introduction of a 3D matrix, which allows for both paracrine and juxtacrine signaling between tumor and endothelial cells.

• Download figure
• Open in new tab
• Download powerpoint

Fig. 1.

Microfluidic tumor-vascular interface model. (A) Endothelial channel (green), tumor channel (red), and 3D ECM (dark gray) between the two channels. Channels are 500 μm wide, 20 mm in length, and 120 μm in height. Black arrow shows the y-junction. (Scale bar: 2 mm.) (B) Phase contrast image showing the fibrosarcoma cells (HT1080, red) invading through the ECM (gray) toward the endothelium (MVEC, green). A single 3D ECM hydrogel matrix region is outlined with the white dashed square. (Scale bar: 300 μm.) (C) VE-cadherin and DAPI staining to show the confluency of the endothelial monolayer on the 3D ECM (outlined with white square in B). (D) Three-dimensional rendering of a confocal z-stack of a single region showing the tumor cells invading in 3D and adhering to the endothelium. (Scale bar: 30 μm.) (E) HT1080 cell (white arrow) invading in 3D toward the endothelium. (Scale bar: 30 μm.) (F) HT1080 cells in contact with the endothelial monolayer. In C–F all scale bars are 30 μm. Green, VE-cadherin; blue, DAPI; red, HT1080-mCherry. x-, y-, z- coordinate indication is appropriately adjusted in A, C, and D.

To demonstrate the formation of confluent, 3D endothelial barriers (Fig. 1C), we visualized the endothelial cell-cell junctions using a vascular endothelial-cadherin (VE-cadherin) antibody. The endothelial cells formed continuous cell-cell junctions spanning the full area of the microchannel surfaces and the 3D ECM-endothelial channel interface (Fig. 1C). These confluent endothelial monolayers formed in the presence of invading tumor cells in 3D (Fig. 1D). High-resolution imaging allowed us to monitor endothelial cell-cell cadherin junctions as the tumor cells invaded toward the endothelial monolayer (Fig. 1E) and contacted the endothelial cells (Fig. 1F).

Characterization of Endothelial Monolayer Barrier Function.

Using fluorescence conjugated dextran we established a diffusion-based solute flux across the endothelial monolayer (Fig. 2A) that was used to measure the diffusive endothelial permeability (P_D). Detailed computational modeling (Fig. 2B) based on device geometry and measured permeability coefficients predicted the experimental concentration distribution, thus confirming the validity of our quantification framework. By monitoring the intensity profiles (Fig. 2C) in time, we could also measure the temporal response of the endothelium to biochemical factors (Fig. S1). P_D was measured in the presence of tumor cells for 10 and 70 kDa dextrans, yielding values of 4.08 ± 1.11 × 10^-5 cm/s and 0.75 ± 0.093 × 10^-5 cm/s, respectively. The ratio of 10 to 70 kDa P_D values was 5.5 (Fig. 2D), indicating that the endothelial monolayer within our devices forms a size-selective barrier for transendothelial transport.

• Download figure
• Open in new tab
• Download powerpoint

Fig. 2.

Characterization of endothelial permeability. (A) Single confocal slice showing the distribution of a 10 kDa fluorescent dextran in a 3D hydrogel ECM region. Warmer colors indicate higher fluorescent intensities. (Scale bar: 50 μm.) (B) Computational simulation of biomolecular transport under the experimental conditions of A. (C) Normalized fluorescent intensity profile along the dashed line in A illustrating the sharp drop of dextran concentration across the endothelial monolayer and the steady diffusive flux inside the 3D ECM. (D) Diffusive permeability (P_D) of endothelial monolayer (MVEC) in the presence of tumor cells (HT1080) for 10 and 70 kDa dextrans. Average values across n = 10 regions within a single device; error bars represent SEM (P = 0.013). Fluorescence intensity in C was normalized with respect to the value at the starting point of the dashed line in A.

Macrophages Regulate Tumor Cell Intravasation Across the Endothelium.

To model a physiologically relevant intravasation phenotype, we seeded human breast carcinoma cells in the 3D matrix and investigated whether the presence of macrophages in contact with the endothelium regulates intravasation. Intravasation is indicated by the migration of tumor cells from within the 3D matrix across the basal endothelial surface and subsequent appearance on the apical endothelial surface inside the vascular lumen. Fig. 3A, demonstrates a characteristic example of an intravasation event, where the breast tumor cell has adhered to the apical surface of the endothelium, as shown by the top and side views. In the absence of macrophages, tumor cells were observed predominantly on the basal side of the endothelial monolayer (Fig. 3B). This finding was also confirmed by quantifying the tumor cell numbers in contact with the endothelium (Fig. S2A) and was further validated by live cell imaging, (Fig. 3C and Movie S1). Intravasation was a rare and inefficient event and occurred for a small fraction of the tumor cells in contact with the endothelial monolayer. In the presence of macrophages a significantly (P = 0.048) higher percentage of tumor cells (4.08 ± 0.87%; 13 out of 289 cells) intravasated, compared to control conditions (0.45 ± 0.28%; 2 out of 304 cells), i.e., a ninefold increase (Fig. 3D). Furthermore, we showed that macrophages enabled tumor cell intravasation for endothelial cells of different origin, and that the percentage of tumor cells that had intravasated (Fig. S2B) was similar for human microvascular endothelial (MVEC) and human umbilical vein endothelial (HUVEC) cells. To examine the effects of macrophages on the endothelial monolayer, we monitored changes in endothelial barrier function and measured a statistically significant (P = 0.03) 2.83-fold increase in endothelial diffusive permeability to 70 kDa dextran (Fig. 3E). Macrophages were present in both the subluminal and luminal endothelial spaces (Fig. S2C) at similar numbers (6.42 ± 1.88 vs. 5.29 ± 1.00 cells/region, P = 0.61).

• Download figure
• Open in new tab
• Download powerpoint

Fig. 3.

Macrophages enable tumor cell intravasation. (A) Top (Upper Left) and side (Upper Right) views showing the device schematic with the endothelial monolayer, the tumor cells, and the location of the 3D ECM. (Lower) Confocal images, demonstrating intravasation of a single breast carcinoma cell (green) across the endothelium (MVEC, stained red for VE-cadherin). (Scale bar: 30 μm.) (B) Top (Upper Left) and side (Upper Right) views with the same orientation as in A, showing tumor cells on the basal side of the endothelium. (C) Time sequence of a single confocal slices showing a breast carcinoma cell (white arrow) in the process of intravasaton across a HUVEC monolayer (magenta) in the presence of macrophages (RAW264.7). The dashed line illustrates the endothelial-ECM interface. (Scale bar: 30 μm.) (D) Percentage of carcinoma cells that intravasated across a HUVEC monolayer was increased in the presence of macrophages (Mφ, P = 6 × 10^-4). Blocking TNF-α resulted in a significant reduction in intravasation compared to the IgG antibody control (P = 0.035). Average values (n = 3 devices) for each condition. (E) Quantification of endothelial permeability to 70 kDa dextrans. Presence of macrophage led to significant permeability increase (P = 0.002). TNF-α blocking also resulted in a significant reduction (P = 0.036) compared to the IgG antibody control. Average values (n = 12 regions); error-bars represent SEM.

TNF-α Stimulation of Endothelial Monolayer Modulates Tumor Cell Intravasation, Tumor-Endothelial Cell Interactions, and Endothelial Barrier Function.

To test the hypothesis that the macrophage-induced permeability increase results in higher intravasation rates, we perturbed the endothelial barrier using biochemical factors and measured intravasation rates. We modulated endothelial permeability by stimulation of the endothelial monolayer with 2 ng/mL TNF-α in the presence of breast carcinoma cells alone, while simultaneously establishing a 20 ng/mL per mm EGF gradient to guide carcinoma cells toward the endothelial channel. We observed a significantly (P = 0.034) higher number (9 out of 124 cells) of intravasated tumor cells compared to control (2 out of 304 cells), suggesting that TNF-α stimulation increased endothelial permeability (Fig. S1C) and enhanced intravasation rate (Fig. S3A). Moreover, to characterize the TNF-α-induced endothelial barrier disruption in detail we measured permeability at different doses of TNF-α (0, 0.2, 2 and 20 ng/mL) and observed a graded response in endothelial permeability (Fig. S1A).

We further investigated the role of endothelial permeability in tumor-endothelial interactions during tumor cell invasion. Here, we used a highly invasive human fibrosarcoma (HT1080) cell line, in the absence of macrophages. To facilitate analysis, we developed a quantification framework that enabled the automatic detection (SI Materials and Methods) of tumor-endothelial interaction events, defined as a tumor cell in direct physical contact with the endothelial monolayer. This event can occur in the endothelial channel, or on the ECM-endothelial channel interface after migration of the tumor cell from the 3D matrix toward the endothelial barrier. Fig. 4 A and B show two confocal image 3D volume renderings at t = 0 and t = 10 h of the HT1080 fibrosarcoma cells inside the 3D matrix as they invade toward the endothelial monolayer. The number of tumor cells that had migrated beyond the ECM-endothelial channel interface (Fig. 4 C and D) increased with time, as the tumor cells were migrating in response to the EGF gradient toward the endothelium. Stimulation of the endothelium with 2 ng/mL TNF-α resulted in a 1.7-fold (P = 0.006) increase in percentage of tumor cells that interacted with the endothelium compared to the control (Fig. 4E). We confirmed that at t = 0 h, prior to tumor cell migration toward the endothelium, the number of tumor cells located within 250 μm from the ECM-endothelial channel interface was similar between the two conditions (Fig. S3B).

• Download figure
• Open in new tab
• Download powerpoint

Fig. 4.

TNF-α effects on tumor-endothelial interactions and endothelial permeability. (A and B) Three-dimensional rendering of a single hydrogel region showing fibrosarcoma tumor cells (HT1080, red) next to endothelial monolayer (MVEC, green) at time t = 0 h (A) and t = 10 h (B). Inset shows image orientation in the device. (Scale bar: 50 μm.) (C and D) Projected confocal slices showing all tumor cells (red dots) located within 250 μm from the 3D ECM-endothelial channel interface (outlined with a thick black line) at t = 0 h (C) and t = 10 h (D). (Scale bar: 50 μm.) (E) Percentage of tumor cells that interacted with the endothelium to the total cells in the hydrogel region (P = 0.006). Average values (n = 3 devices) for each condition. (F) Normalized change in permeability after 10 h, for the control and TNF-α conditions (P = 0.002). Average values for at least n = 10 hydrogel regions; error-bars represent SEM.

In addition to changes in the number of tumor-endothelial interaction events, the TNF-α stimulated endothelium showed a fivefold increase (P = 0.002) in endothelial permeability compared to the control (Fig. 4F). Real-time measurements of P_D also confirmed the endothelial barrier impairment for 10 and 70 kDa dextrans (Fig. S1A). The TNF-α concentration (2 ng/mL) used was determined by titration experiments on endothelial monolayers seeded on collagen hydrogels to ensure a confluent endothelial monolayer was present after 24 h of stimulation (SI Materials and Methods and Fig. S3C).

Characterization of Macrophage Polarization and Role of Macrophage-Secreted TNF-α in Regulating Tumor Cell Intravasation and Endothelial Barrier Function.

To characterize whether macrophages were polarized in the microfluidic device, we performed immunostaining for M1 and M2 markers (SI Materials and Methods and Fig. S4). Although we found that macrophages within the device could be driven toward an M1 or M2 phenotype through stimulation with lipopolysaccharide (LPS) or interleukin-4 (IL4) (Fig. S4C), respectively, when in the presence of tumor cells and endothelial cells the macrophages were variable in their expression for M1 or M2-specific markers (Fig. S4 D and E). Furthermore, coculture of macrophages with tumor cells within the device did not significantly change their phenotype vs. culture of macrophages alone (Fig. S4 D and E). We also characterized macrophage-secreted factors under control conditions and M1/M2 polarization and confirmed that the macrophages secreted TNF-α (Fig. S4 A and B).

To investigate whether the effects of macrophages on intravasation and endothelial permeability are regulated via paracrine signals, we performed antibody blocking experiments to neutralize soluble TNF-α and measured significant changes in permeability (Fig. 3E, 1.67-fold decrease, P = 0.04) and intravasation (Fig. 3D, 2.45-fold decrease, P = 0.03) compared to control IgG antibody. We also performed permeability measurements to investigate the effects of other cell types (tumor and epithelial cells) on endothelial barrier function compared to macrophages. Interestingly, the presence of all cell types resulted in increased endothelial permeability (Fig. S2D) compared to the control condition. However, the presence of macrophages resulted in a significant increase in P_D compared to tumor cells (5.6 × 10^-5 cm/s vs. 3.9 × 10^-5 cm/s, P = 0.049), whereas there was no significant difference compared to the epithelial cell (5.6 × 10^-5 cm/s vs. 4.5 × 10^-5 cm/s, P = 0.36) condition.

Dynamics of Tumor-Endothelial Cell Interactions.

Our ability to visualize the endothelium en face allows a qualitative characterization of the process of tumor cell migration at a 3D endothelial monolayer with a well-defined lumen (Fig. 1C). Such dynamic observation of tumor-endothelial cell interactions can offer valuable insights into the timescales, spatial organization, and mechanism of tumor cell intravasation, complementary to detailed immunofluorescent staining (Fig. 3A and Fig. S5). Fig. 5A shows a time series of images demonstrating one example of a fibrosarcoma cell migrating from the 3D matrix to the endothelial monolayer. Analysis of the time-lapse movies led to a number of interesting observations: (i) Invasive protrusions form dynamically and appear to probe the surrounding 3D environment. (ii) Tumor cells exhibit significant cell shape changes as they migrate from the 3D matrix, adhere to the endothelium, and migrate through it to the endothelial channel. (iii) Tumor cells were observed to migrate toward remodeled regions (Fig. S5) of the endothelium or next to a macrophage (Fig. S2C).

• Download figure
• Open in new tab
• Download powerpoint

Fig. 5.

Dynamics of tumor-endothelial interactions. (A) Time series of confocal images showing a HT1080 cell (red, white arrow) invading toward the TNF-α stimulated endothelial monolayer (MVEC, green). (Scale bar: 50 μm.) (B) Tumor cell trajectories over 10 h under control (Left) and TNF-α conditions (Right). (C) Time required for tumor cells to migrate over a 60 μm distance across the EC-matrix (P = 0.02). (D) Mean migration speed of HT1080 cells in the 3D matrix (P = 0.99). Average values for at least n = 10 trajectories per condition in A–D; error-bars represent SEM.

We studied the dynamic interactions of tumor-endothelial cells under control and TNF-α conditions by tracking tumor cell trajectories (Fig. 5B) and quantifying the time (Fig. 5C) required for tumor cells to migrate a specific distance (60 μm) across the ECM-endothelial channel interface. Tumor cells migrated faster from the 3D matrix into the endothelial channel in the TNF-α stimulated (1.35 ± 0.25 h) compared to the control monolayer (2.42 ± 0.38 h) (P = 0.024). To confirm that TNF-α did not modulate tumor cell invasion in the 3D matrix, we quantified tumor cell migration speeds (Fig. 5D) and found similar values (29.59 ± 2.57 vs. 29.53 ± 4.16 μm/h, P = 0.99) under the two conditions. These findings suggest that impaired endothelial barrier function facilitates faster tumor cell invasion across the EC-matrix barrier and are in agreement with our observations of increased endothelial permeability and higher number of tumor cells interacting with the TNF-α stimulated endothelium.