Unraveling the Receptor-Ligand Interactions between Bladder Cancer Cells and the Endothelium Using AFM

Abstract

Adhesion of cancer cells to endothelial cells is a key step in cancer metastasis; therefore, identifying the key molecules involved during this process promises to aid in efforts to block the metastatic cascade. We have previously shown that intercellular adhesion molecule-1 (ICAM-1) expressed by endothelial cells is involved in the interactions of bladder cancer cells (BCs) with the endothelium. However, the ICAM-1 ligands have never been investigated. In this study, we combined adhesion assays and atomic force microscopy (AFM) to identify the ligands involved and to quantify the forces relevant in such interactions. We report the expression of MUC1 and CD43 on BCs, and demonstrate that these ligands interact with ICAM-1 to mediate cancer cell-endothelial cell adhesion in the case of the more invasive BCs. This was achieved with the use of adhesion assays, which showed a strong decrease in the attachment of BCs to endothelial cells when MUC1 and CD43 were blocked by antibodies. In addition, AFM measurements showed a similar decrease, by up to 70%, in the number of rupture events that occurred when MUC1 and CD43 were blocked. When we applied a Gaussian mixture model to the AFM data, we observed a distinct force range for receptor-ligand bonds, which allowed us to precisely identify the interactions of ICAM-1 with MUC1 or CD43. Furthermore, a detailed analysis of the rupture events suggested that CD43 is strongly connected to the cytoskeleton and that its interaction with ICAM-1 mainly corresponds to force ramps followed by sudden jumps. In contrast, MUC1 seems to be weakly connected to the cytoskeleton, as its interactions with ICAM-1 are mainly associated with the formation of tethers. This analysis is quite promising and may also be applied to other types of cancer cells.

Figure 1

Interactions between cancer cells and ECs, as measured by SCFS. (A) Sketch of the different substrates (rICAM-1, BSA, and HUVECs) used for SCFS experiments. (B and D) Sketch of the approach-retraction method and typical retraction force curve in terms of the piezo displacement. The HUVEC monolayer approaches the cancer cell at a constant velocity (5 μm/s). Then, the HUVECs come into contact with the cancer cell during 10 s (under 500 pN applied force) to create several bond complexes within the adhesion area. The HUVEC substrate is then retracted at a constant velocity to detach the adhesive bonds. The retraction curve shows force jumps and tethers corresponding to bond rupture forces. The adhesive energy (shaded area) represents the detachment work needed to completely unbind the cell from the substrate. The detachment force is the force necessary to stretch the cancer cell and the HUVEC until bonds start to detach. Note that some force jumps can follow a plateau corresponding to tether formation (see Discussion). (C) Picture of an AFM cantilever with an attached cancer cell above the HUVEC monolayer. (Inset) Fluorescence image of a fluorescent cancer cell attached to the cantilever. Scale bar, 20 μm. To see this figure in color, go online.

Figure 2

Flow-cytometry analyses of MUC1 and CD43 expression in BCs. (A–F) Expression levels of MUC1 and CD43 (red curve) as determined by flow-cytometry analysis in comparison with an irrelevant antibody (black curve): RT112 cells (A and B), T24 cells (C and D), and J82 cells (E and F). To see this figure in color, go online.

Figure 3

Quantification of BC-EC adhesion. (A–C) In adhesion assays, we quantified the percentage (mean ± SE) of 3 BCs (RT112 (A), T24 (B), and J82 (C)) adhering to ECs while blocking ICAM-1 on ECs and blocking MUC1, CD43, and MUC1+CD43 on cancer cells. One-way analysis of variance was performed to determine significance with respect to the control; ^∗∗∗∗p ≤ 0.0001, ^∗∗p ≤ 0.01.

Figure 4

SCFS analysis of BC-EC adhesion. Force histograms showing the distribution of rupture events for adhesion of the HUVEC monolayer with J82 BCs in different conditions were obtained from force curves (applied force 500 pN, time of contact 10 s, velocity 5 μm/s). (A–C) Histograms obtained while blocking MUC1 (A), CD43 (B), and MUC1+CD43 (C) on J82 cells (white histogram) were compared with the control without antibody (gray histogram). (D) The rupture force histogram for nonspecific interactions was obtained with the use of a BSA-coated substrate.

Figure 5

MUC1 and CD43 expressed on BCs interact with ECs with different force ranges. (A) GMM function analysis on the control, showing three different subpopulations: nonspecific interactions (green) and interactions of MUC1 (blue) and CD43 (black). (B) After blocking of MUC1, showing two subpopulations: nonspecific interactions (green) and interaction of CD43 (black). (C) After blocking of CD43, showing two subpopulations: nonspecific interactions (green) and interaction of MUC1 (blue). To see this figure in color, go online.

Figure 6

MUC1 and CD43 interact with ICAM-1 through tethers and jumps. (A) Histogram showing the (mean ± SE) number and type of ruptures (jumps and tethers >36 pN) while blocking the receptors involved in the interaction, using HUVECs as the substrate. GLMM-R software was used to determine significance with respect to the control; ^∗∗∗p < 0.001, ^∗p < 0.05, and n.s. p > 0.5. (B) Pie charts showing the percentage of jumps and tethers for each condition. The percentage of jumps is indicated.

Figure 7

Effect of Lat-A on the number of tethers. (A) Histogram showing the number (mean ± SE) and types of ruptures (jumps and tethers >30 pN) for control or after Lat-A treatment. GLMM was performed to check the significance with respect to control. ^∗∗p ≤ 0.01. (B) Pie charts showing the proportion of jumps and tethers for both conditions. The percentage of jumps is indicated.