Empirical chemosensitivity testing in a spheroid model of ovarian cancer using a microfluidics-based multiplex platform

Abstract

The use of biomarkers to infer drug response in patients is being actively pursued, yet significant challenges with this approach, including the complicated interconnection of pathways, have limited its application. Direct empirical testing of tumor sensitivity would arguably provide a more reliable predictive value, although it has garnered little attention largely due to the technical difficulties associated with this approach. We hypothesize that the application of recently developed microtechnologies, coupled to more complex 3-dimensional cell cultures, could provide a model to address some of these issues. As a proof of concept, we developed a microfluidic device where spheroids of the serous epithelial ovarian cancer cell line TOV112D are entrapped and assayed for their chemoresponse to carboplatin and paclitaxel, two therapeutic agents routinely used for the treatment of ovarian cancer. In order to index the chemoresponse, we analyzed the spatiotemporal evolution of the mortality fraction, as judged by vital dyes and confocal microscopy, within spheroids subjected to different drug concentrations and treatment durations inside the microfluidic device. To reflect microenvironment effects, we tested the effect of exogenous extracellular matrix and serum supplementation during spheroid formation on their chemotherapeutic response. Spheroids displayed augmented chemoresistance in comparison to monolayer culturing. This resistance was further increased by the simultaneous presence of both extracellular matrix and high serum concentration during spheroid formation. Following exposure to chemotherapeutics, cell death profiles were not uniform throughout the spheroid. The highest cell death fraction was found at the center of the spheroid and the lowest at the periphery. Collectively, the results demonstrate the validity of the approach, and provide the basis for further investigation of chemotherapeutic responses in ovarian cancer using microfluidics technology. In the future, such microdevices could provide the framework to assay drug sensitivity in a timeframe suitable for clinical decision making.

Figure 1

Schematic representation of the microfluidic device for spheroid entrapment. (a) Layout of the device showing six serially located traps, indicated by the asterisks. (b) Mechanistic elaboration of serial spheroid entrapment. Dimensions of bypass and trapping sections are shown. Height of the microchannels = 500 μm. Black arrows indicate the bypass flow following spheroid entrapment and subsequent flow through the device. The inset in panel (b) demonstrates a trapped spheroid and its imaging with CTG. (c) Detailed illustration of a trapping section. L₂ is the total length of the through channel, i.e.,sum of the lengths of trap and neck sections. Spheroid is depicted by the blue circle. (d) Phase-contrast image (4×objective) of two TOV112D spheroids trapped in a microfluidic device. (e) Image of a device containing 8 microchannel systems in a single glass slide, for parallelized analysis.

Figure 2

Critical aspects of device fabrication. (a) Schematic representation of the device fabrication process by soft-lithography or PDMS-based rapid prototyping. (b) Representative image of the microfluidic devices. (c) Illustration detailing the necessity for a narrow outlet to reduce backflow. Backflow is due to the height difference between outlet and inlet liquid column and it is directly proportional to $\pi (h_0-h_i)D_0^2$_, where h_i and h₀ are liquid column heights at the inlet and the outlet, respectively, and D₀ is the outlet diameter. Therefore, by reducing the diameter of outlet, it is possible to reduce the strength of backflow, although it cannot be completely eliminated in this system.

Figure 3

Spheroid loading and live-dead cell imaging. (a) Phase contrast images of six TOV112D spheroids entrapped in a single microfluidic device. These spheroids were subjected to live-dead imaging by dual fluorescent staining technique. (b) Confocal image of a CTG-PI stained spheroid, as projected over 15 confocal z-sections across the spheroid height. (b-I): CTG (green fluorescent). (b-II) PI (red fluorescent). (b-III) CTG-PI merged channels. Note that PI monitored cell death is minimal and is evenly distributed spatially. Scale bar represents 120 μm.

Figure 4

Distribution and temporal evolution of the mortality fraction. (a) Representative side view images of CTG-PI labeled TOV112D spheroids after 0, 6, and 24 h of incubation with 10× the TOV112D reference IC₅₀ of carboplatin. I, III, and V illustrate merged confocal images while II, IV, and VI are corresponding pseudo-color images highlighting the distribution of mortality, in which red represents high mortality. Note that red intensity is more prominent with increased treatment time (compare 6 to 24 h). (b) Graphical representation of the imaging scheme. From top to bottom, 15 different cross-sectional images (termed image layers) were acquired for each spheroid. (c) Distribution of mortality fraction (number of dead cells/total number of cells in a single section) across 15 image layers comparing controls and spheroids treated with 10× the TOV112D monolayer IC₅₀ of carboplatin for 6 or 24 h. Data are averaged over three independent experiments (total number of samples, n = 16) and shown as mean ± standard deviation.

Figure 5

Effect of carboplatin and paclitaxel on TOV112D spheroids. The reference IC₅₀ is based on drug responses in TOV112D monolayer cultures. (a) Merged CTG-PI confocal section (image layer #13) of spheroids subjected to carboplatin and paclitaxel at different concentrations. No image is provided for the 100 × IC₅₀ paclitaxel treated spheroids, as under these conditions they lost their structural integrity and were fragmented during the vital dye staining. (b) Variation in the distribution of mortality fractions across all z-sections with varying carboplatin concentrations (1, 10, and 100 × IC₅₀). (c)Variation in mortality distribution with changes in paclitaxel concentration (1 and 10 × IC₅₀). Treatment time is 24 h for all samples. Each data point is averaged over three independent experiments (with total number of samples, n = 16) and shown as mean ± standard deviation.

Figure 6

Radial distribution of the mortality fraction. (Left) Graphical delineation of the image analysis scheme to determine the radial distribution of the mortality fraction. (Middle, panels (a)–(c)) Averaged mortality distribution function of image layers 10-13. (Right) Representative sample images corresponding to the quantitative results. For each sample, distribution function has been normalized (dead cells within a radius range/the number total dead cells) so that integration of it over the whole radial domain remains one. The symbol * in (b) and (c) represents a point for which an increase or decrease in the mortality fraction is statistically significant (p < 0.01) with respect to controls. Each data point is averaged over three independent experiments (with total number of samples, n = 16) and shown as mean ± standard deviation. Note that treatment with carboplatin and paclitaxel showed a more prominent rise in mortality fraction closer to the spheroid center than near the edges.

Figure 7

Effect of extracellular matrix (matrigel) and increased serum supplementation during spheroid formation on the chemotherapeutic response. (a) Distribution of the mortality fraction in image layers 8-15 of confocal z-sections and its dependence on matrigel and increased serum supplementation. (b) Representative merged CTG-PI confocal sections (image layer 13) of spheroids showing the variation of mortality with different culture conditions. In this panel, control corresponds to cells not exposed to carboplatin. (c) Response to carboplatin treatment was variable depending on the culture conditions, as accessed by the average morality fraction over image layers 8-15 of samples. Note that the simultaneous addition of matrigel and increased serum (20%) supplementation showed a statistically significant increase in chemoresistance, while neither had a significant effect alone. In addition, in the absence of drug, addition of matrigel and 20% serum appears tosignificantly diminish basal cell death within the spheroids (statistically significant in image layers 12 and 15). Each datapoint is averaged over three independent experiments (with total number of samples, n = 16) and shown as mean ±standard deviation.