With certain cancers, such as ovarian cancers, a significant number of patients are non-responsive to the standard chemotherapy treatment. These patients, therefore, experience the negative side effects of chemotherapy without clinical benefits. With the ever-increasing number of available anti-cancer drug alternatives to chemotherapy, there is tremendous pressure on clinicians to make the right treatment choice. The biomarker approach—a statistical method that associates drug-response rates with specific patient characteristics—is effective for predicting which patients will respond best to a given treatment. However, only very specific cancer subtypes have associated biomarkers (i.e., the BRCA mutation for breast cancer). There is a crucial need, therefore, for a complementary predictive method that is applicable to virtually all types of cancers.
Clusters of cells, known as spheroids, are the most popular 3D tissue model in cancer research. These samples, which have standard diameters of around 400μm, are relatively easy to culture and they represent patient tumors better than traditional 2D cell cultures.1 The spheroids are often formed and cultured in miniaturized fluidic systems—or microfluidic chips—in which biological assays are performed. However, spheroids have been of little use in personalized therapy because they are formed using generic cell lines that do not reproduce the specificities of a patient's tumor. A promising alternative would be to directly test therapies on small amounts of cancer tissue from patients, but this approach has had limited success in the past because of challenges associated with culturing patient tissue outside the human body and with developing detection methods to measure drug response in 3D tissue.
In response to these issues, we have proposed a novel approach for testing many drugs simultaneously on tissue from a specific patient (see Figure 1).2,3 We first developed a technique to cut biopsied tumor tissue down to the size of spheroids. To simplify the manipulation of such miniature samples, we designed a microfluidic chip with which we could trap and incubate several microtissues and expose them to different cancer drugs. Our proposed tissue format is about 100 times smaller than those used previously. Our approach therefore enables a greater number of independent assays on limited amounts of biopsied material, while maintaining high viability because of the facilitated access to nutrients.
Figure 1. Personalized approach for the selection of an optimal anti-cancer treatment. Small amounts of tissue from a patient are sectioned into spheroid-sized samples. These individual samples are then introduced into a microsystem, in which different treatment options can be tested and their effects measured using various detection systems. Inset shows a top-view image of a sample trapped inside a well. The sample is labeled with fluorescent probes marking cells that are viable (green) and dead (red), and is imaged using confocal fluorescence microscopy. The results of the test may help medical specialists choose the most effective treatment for each patient.
We used fluorescent probes, which are widely used to visualize cell biology, to show experimentally that tumor tissue remains viable under normal conditions within our microfluidic chip. Typically, these probes have broad emission spectra. This means that we can detect only a limited number of the probes using traditional instruments, i.e., without overlapping signals. To quantify the overall viability of the microtissues, we used fluorescent probes that targeted viable and dead cells. We detected these probes with confocal microscopy and flow cytometry. We thus showed that microtissues—formed from mouse xenograft tumors and used as a cancer tissue model—remained alive for more than a week when cultured under non-treated conditions within our microsystems (see Figure 2).
Figure 2. Viability results of the micro-dissected tumor tissue samples produced from mouse xenografts (formed using the OV90 ovarian cancer cell line) and cultured in a microfluidic chip. (A) Confocal microscopy results representing the relative area of live cells, over the total area of both viable and dead cells. The live and dead cells are labeled with CellTracker GreenTM (green) and with propidium iodide (red), respectively. Representative confocal images are shown with their respective computed viability scores. Scale bars indicate 100μm. (B) Flow cytometry results of the samples dissociated into single cells and categorized by the instrument into three cell groups: late apoptotic/dead (7-aminoactinomycin D labeling), early apoptotic (annexin V labeling), and viable (absence of labeling). Error bars show the standard error of the mean, from at least three independent experiments.
We used these results to spearhead tests on human tumor tissue that was obtained from consenting patients who had undergone surgery at the University of Montreal's hospital. Results from our preliminary chemoresponse tests seem promising. Ongoing improvements to our detection system, however, will increase the statistical significance of our results through greater multiplexing of fluorophores, allowing multiple measurements to be taken from a single microtissue at multiple time points.
To enhance the imaging speed and increase our ability to multiplex probes, we are developing a fluorescence spectroscopic imaging system that collects the fluorescence emitted by the samples at all wavelengths and forms a complete emission spectrum at each pixel of an image (i.e., a hyperspectral data cube). This custom-built widefield spectroscopic imaging system is based on the use of a liquid crystal tunable filter and has transmittance and fluorescence capabilities.4 As a proof of concept, we measured the fluorescence of spheroids that have two fluorescent markers. Our results showed that we can easily separate their contribution to the overall fluorescence, over the whole field of view of 1cm2 (see Figure 3). Since our imaging system is widefield and quantitative, the fluorescence intensity for each marker can be correlated to a number of marked cells, allowing us to measure cell viability of many samples over a wide area.
(A) Brightfield image of a microsystem containing 24 spheroids formed from ovarian cancer cell line OV90. (B) Fluorescence image at 520nm (fluorescence measured in arbitrary units) of the spheroids previously marked with the live cell markers CellTracker GreenTM
(CTG) and OrangeTM
(CTO). Each fluorescent image acquired was normalized to the acquisition time and gain of the camera, dark noise was removed, spectral calibration was applied, and spatial uniformity was corrected. A black square shows the area from which the average spectra presented in (C) were extracted. (C) Spectral unmixing to extract each marker's contribution to the overall fluorescence. Scale bars indicate 1mm. Figure is adapted from a previous paper.4
In summary, we have validated that microtissues remain viable within specifically designed microsystems, and have shown that it is possible to obtain rapid and simultaneous viability measurements on multiple samples. To take full advantage of the enhanced capabilities of our spectroscopic imaging system, we are currently optimizing the imaging intervals and determining the assortment of fluorescent probes that can be used to most accurately detect how anti-cancer agents affect the tissue. Our work will have a significant impact on patient survival and quality of life by providing medical teams with a new tool to predict patient responses to anti-cancer drugs.
This research was supported by the Québec Consortium for Drug Discovery , Prostate Cancer Canada, the Natural Sciences and Engineering Research Council of Canada, the Canadian Cancer Society Research Institute, and a Canadian Foundation for Innovation infrastructure grant.
Mélina Astolfi, Amélie St-Georges-Robillard, Frédéric Leblond, Thomas Gervais
École Polytechnique de Montréal
Mélina Astolfi recently obtained her master of applied sciences degree in biomedical engineering, in collaboration with the University of Montreal Hospital Research Center (CRCHUM).
Amélie St-Georges-Robillard is a PhD candidate in biomedical engineering, and is affiliated to CRCHUM.
Frédéric Leblond is an associate professor in the Department of Engineering Physics and a researcher at CRCHUM. His research emphasis is the development of optical instruments and methods for tissue characterization in oncology.
Thomas Gervais is an assistant professor of engineering physics. His research focuses on microfluidics and transport phenomena.
University of Montreal
Anne-Marie Mes-Masson is a full professor in the Department of Medicine and is head of the Montreal Cancer Institute. Her research focuses on the molecular characterization of ovarian and prostate cancers, as well as the development of new experimental models in oncology.
1. J. Friedrich, C. Seidel, R. Ebner, L. A. Kunz-Schughart, Spheroid-based drug screen: considerations and practical approach, Nat. Protocols 4, p. 309-324, 2009.
2. M. Astolfi, B. Peant, M. A. Lateef, N. Rousset, J. Kendall-Dupont, E. Carmona, F. Monet, et al., Micro-dissected tumor tissues on chip: an ex vivo method for drug testing and personalized therapy, Lab Chip 16, p. 312-325, 2016.
3. M. Astolfi, A. St-Georges-Robillard, N. Rousset, M. A. Lateef, B. Péant, M. Marimuthu, J. Kendall-Dupont, et al., Micro-dissected tumors on-chip: using microfluidics and fluorescence imaging for personalized drug response assays. Presented at SPIE Photonics West 2016.
4. A. St-Georges-Robillard, M. Masse, J. Kendall-Dupont, M. Strupler, B. Patra, M. Jermyn, A.-M. Mes-Masson, F. Leblond, T. Gervais, Spectroscopic imaging system for high-throughput viability assessment of ovarian spheroids or microdissected tumor tissues (MDTs) in a microfluidic chip, Proc. SPIE
9689, p. 9689-160, 2016. doi:10.1117/12.2211159