High resolution monitoring of chemotherapeutic agent potency in cancer cells using a CMOS capacitance biosensor
Introduction
Cell-based assays can analyze the effects of different materials and growth conditions on cells cultured in vitro. They are a vital tool in the drug discovery process and can be used to quantify the cytotoxic effects of drugs. Most cell-based screening studies require the use of specialized laboratory equipment and reagents, and they provide data through methods that require labeling such as fluorescent, bioluminescent, or colorometric staining. While these screens can provide high-throughput analysis through parallelization of experiments, they generally have high operational costs, can be labor intensive, require sub-sampling of analytes, and may lack specificity (Méry et al., 2017). Furthermore, most provide data at temporally and spatially sparse sampling points or are endpoint assays requiring cell fixation, and so do not provide information on the dynamics of live cell growth and motility.
Real-time monitoring of cell viability over the course of drug exposure and subsequent cell death may provide a more complete picture of the cytostatic and cytotoxic effects of drugs. In particular, profiling cancer cell responses with high-temporal resolution can provide insight into cell death kinetics enabling the development of more beneficial drug dosage regimens and better-targeted therapies (Forcina et al., 2017; Wolbers et al., 2004; Wolpaw et al., 2011). Indeed modern chemotherapeutic regimens generally involve the use of multiple drugs (Frei and Eder, 2003) administered sequentially or in alternation, with the aim of reducing drug resistance, reducing non-specific toxic effects, and maximizing overall efficacy. Computational models have been developed to generate adaptive therapeutic regimes (Gatenby et al., 2009) or select optimum strategies to address issues of tumor heterogeneity (Zhao et al., 2014). Therefore the ability to perform continuous cell measurements in real-time represents a significant advance over current methods of determining drug cytotoxicity and cancer cell susceptibility; replacing current assays with a more rapid and more relevant alternative could hasten the drug development process toward clinical implementation.
Complementary metal-oxide semiconductor (CMOS) technology has been leveraged to develop biosensors to meet this goal by bringing sensing and signal processing electronics into intimate contact with biology. This has the advantages of incorporating the signal transduction and readout pipeline into a single highly integrated platform, thus enabling miniaturization and high-fidelity measurements. Among the different possible sensing modalities for CMOS technologies, impedance and capacitance-based sensors have shown promise in cell viability monitoring. These sensors operate by monitoring the capacitive loading of cells at the cell-chip interface (Hong et al., 2011; Prakash and Abshire, 2005). Several such platforms have been developed for detecting bacterial cells (Couniot et al., 2016), monitoring bacterial growth (Ghafar-Zadeh et al., 2010), and tracking cancer cell proliferation (Laborde et al., 2015; Nabovati et al., 2017; Prakash and Abshire, 2008). A recent study looked at drug screening on chip using a capacitance sensor (Nabovati et al., 2019), comparing cells that were antibiotic-resistant with those that were non-resistant. Results showed a positive correlation with expected outcomes, although the temporal resolution of measurements was on the order of hours, which may limit the ability to observe drug-induced responses over short timespans. Other CMOS sensing modalities have also been studied for drug development, including electrical sensing of action potential variations upon drug dosing (Abbott et al., 2017; Lopez et al., 2018; Park et al., 2018).
In this work, a CMOS-based capacitance biosensor is presented that enables automatic, real-time, and label-free cell tracking to monitor chemotherapeutic agent potency. The device is able to generate measurements of cell-substrate coupling with high spatial, temporal, and amplitude resolution, which in turn can be used to monitor cell adhesion, proliferation, and viability in the presence of a cytotoxic agent. Prior work has presented sensor characterization results and preliminary live cell experiments (Senevirathna et al., 2019, 2018). Here, more comprehensive cell experiments are performed with the addition of time-lapse optical imaging of the sensor surface to verify measurements. This ground-truth validation confirms the operation of the chip and its ability to detect single-cell binding and detachment events. Furthermore, experiments were performed to use the biosensor as a proof-of-concept drug-screening tool. Two human ovarian cancer cell lines were grown on the device, one of which is sensitive to a chemotherapeutic agent and the other resistant. Repeated experiments were performed to monitor cell viability for different concentrations of the drug, and results demonstrate the ability to discriminate the resistant and sensitive cell lines through capacitance measurements. The high-temporal resolution measurements were then used, along with mathematical modeling, to estimate kinetics of cell death by measuring the time lag between drug exposure and death onset, and the rate of cell death. Results showed that cell death is induced faster with increased drug concentration, while the death rate remains unaffected. Capacitance and image data may be found online at http://dx.doi.org/10.21227/9zzd-w936 (Senevirathna et al., IEEE Dataport, 2019).
Section snippets
Cell-substrate coupling & chemotherapy
The CMOS biosensor operates by monitoring capacitive changes that occur at the cell-substrate interface as cells settle onto a substrate, adhere, proliferate, and eventually lift off due to cell death, forced detachment, or other morphological changes. Fig. 1a shows a diagram of three stages of the cell adhesion process. When cells are first placed in suspension they drift downwards and make an initial attachment with the substrate (top panel, Fig. 1a and b). They then begin attaching to the
Correlation of cell adhesion and capacitance measurements
In order to validate the capacitance sensor measurements, experiments were first conducted with the imaging and sensor recordings running concurrently. Fig. 3 shows time-lapse images taken using the in-incubator imaging system along with the corresponding capacitance measurements for four sensors in the array. A video of the images and data with alignment markers can be found in Supplementary Materials (SV1). During this portion of the experiment, cells were pipetted into the culture well over
Conclusion
This paper presents a CMOS biosensor that monitors the potency of chemotherapeutic agents in cancer cells in real-time. The custom CMOS chip contains a 4 × 4 array of capacitance sensor pixels that make high-resolution measurements of cell-substrate coupling, as an indicator of cell adhesion and viability. The sensor was first validated by simultaneously acquiring capacitance measurements and time-lapse images of the sensor surface during in vitro experiments. Results showed strong evidence of
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Funding
This study was supported the ClintoxNP program (Project #268944) and UMD-UMB 2015 Research and Innovation Seed Grant Program.
CRediT authorship contribution statement
Bathiya Senevirathna: Software, Validation, Formal analysis, Investigation, Data curation, Writing - original draft, Writing - review & editing, Visualization. Sheung Lu: Investigation, Writing - original draft, Visualization. Marc Dandin: Resources, Writing - review & editing. John Basile: Resources, Writing - review & editing, Funding acquisition. Elisabeth Smela: Conceptualization, Methodology, Resources, Writing - review & editing, Supervision, Project administration, Funding acquisition.
Acknowledgements
The CMOS chip used in this study was designed at UMD with technical feedback from Joni Kilpijärvi, Niina Halonen, Antti Hassinen, Maciej Sobocinski, Jari Juuti, and Sakari Kellokumpu from the University of Oulu, Finland and from Anita Lloyd Spetz, Kalle Bunnfors, Kajsa Uvdal, and Natalia Abrikossova from Linköping University, Sweden. The LTCC Ceramic packaging of the chip was processed at the Microelectronic Research Unit, University of Oulu, Finland. The authors would like to thank Dr. Yan Shu
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