When it comes to the war on cancer, scientists are quickly realizing that the model systems which they commonly use to study cancer may not in fact accurately represent the disease which they purport to represent. While the historically low success rates for cancer drugs in clinical trials (<10%) might at first be a shocking statistic, this number is perhaps less surprising when one considers that many of these drugs were developed based on findings in cancer cells growing in a dish or from heavily inbred mouse models. In response to this challenge, cancer researchers have been hard at work inventing ever more sophisticated ways to manipulate cancer cells into structures that more accurately replicate the conditions inside of a cancer patient—these include aggregating cancer cells into 3-dimensional ‘spheroids’ and culturing entire chunks or slices of patient-derived tumor ex vivo.
But it’s not just the model systems that matter here. A better understanding of cancer will also necessitate better experimental methods to interrogate these newer, complex models. Recent work from the Folch lab in the UW Bioengineering Department, published in Science Advances and led by postdoctoral researcher Dr. Tran Nguyen, tackles this challenge with the development of a fundamentally new method of quantifying tumor sample responses to experimental treatments.
“One of the major limitations of the way that cancer drugs are currently tested,” begins Dr. Nguyen, “is that researchers mostly rely on endpoint analyses—they treat some tumor cells or tissue with a drug, wait some time, then destructively analyze the sample at the end of the assay. In the Folch lab, we think a lot about how to use advances in micro-scale technologies to better manipulate and measure tumor tissue and overcome some of these limitations.” One aspect of tumor cell biology that is often of interest to cancer researchers is cell death. A classic marker of cell death is the release of a small protein called cytochrome C into the culture media, which is commonly measured at the endpoint of assay using a variety of techniques. “In this project, we were looking for a method which would allow us to monitor the amount of released cytochrome C from living tumor tissue in real-time. This information could be useful in determining the kinetics of cell death following treatment with a drug, for instance—information that is inaccessible using endpoint analyses.”
To accomplish this goal, Nguyen and colleagues designed, fabricated, and tested a device which uses fragments of DNA to convert cytochrome C concentrations into a quantifiable electrical signal (sounds crazy, I know). At first glance, this device looks much like an ordinary, multi-well tissue culture plate. Unlike an ordinary culture plate, however, the bottom of this plate is studded with microscopic aptasensors—engineered pieces of single-stranded DNA that bind cytochrome C and also contain a redox-active molecule called methylene blue. When a single aptamer binds a single cytochrome C protein, it changes shape, bringing the methylene blue molecule closer to the gold-coated floor of the well and inducing a change in electrical current that can be monitored and quantified. By culturing chunks of patient-derived tumor tissue over a lawn of these aptasensors, the team is thus able to measure the real-time concentration of cytochrome C in the culture media over time in a non-destructive and label-free manner.
After embarking on some major engineering to produce the sensor plate, ensure that it detects cytochrome C with sensitivity and specificity, and optimize its performance, Nguyen and colleagues used it to measure cell death of colorectal tumor ‘cuboids’ treated with several common cancer drugs—importantly, their results agreed with established endpoint methods used to measure cytochrome C. They then turned to a different tumor source, this time embedding glioma (brain) tumor pieces in a gelatinous matrix called hydrogel, treating with several standard chemotherapies, and measuring cytochrome C levels for 48 hours. Reassuringly, this analysis showed drug dose-dependent increases in cytochrome C levels, which agreed with parallel imaging assays to measure cell death and proved that the aptasensor platform can accurately measure dynamic cytochrome C levels for multiple days at a time.
What’s next for this technology? “We’re looking to keep optimizing the sensitivity and specific of the sensor and increase its throughput to be able to measure more samples at once. One of the strengths of working at the micro-scale is that you can produce many tumor pieces from a single patient sample, and one use case for our technology is in high-content drug screens to rapidly test a patient’s specific tumor for sensitivity to different available therapeutics,” notes Nguyen. “While each target will require optimization, theoretically, this method can be adapted for any biological target which you can design an aptamer to bind. We expect that as this technology develops it will be adapted to measure other important biological parameters in useful ways.” Finally, both Dr. Nguyen and Dr. Taran Gujral, whose lab in the Human Biology Division at Fred Hutch supplied some of the tumor samples for this study, emphasize the value of collaboration through the Cancer Consortium to bring together researchers with wholly different expertise to tackle difficult biological questions. As Nguyen concluded, “We really couldn’t have done this work without support from Dr. Gujral and our other collaborators.”
The spotlighted work was funded by the National Institutes of Health and a Catalytic Collaboration Award from the Brotman Baty Institute.
Fred Hutch/University of Washington/Seattle Children’s Cancer Consortium members Drs. Albert Folch, Raymond Yeung, and Taran Gujral and contributed to this study.
Nguyen, T. N. H., Horowitz, L. F., Krilov, T., Lockhart, E., Kenerson, H. L., Gujral, T. S., Yeung, R. S., Arroyo-Currás, N., & Folch, A. (2024). Label-free, real-time monitoring of cytochrome C drug responses in microdissected tumor biopsies with a multi-well aptasensor platform. Science Advances, 10(36), eadn5875.
Science Spotlight writer David Sokolov is a graduate student in the Sullivan Lab at the Fred Hutch. He studies how cancer cells modify their metabolism to facilitate rapid proliferation and accommodate tumor-driving mitochondrial defects. He's originally from the east coast and has bachelors' and masters' degrees from West Virginia University. Outside of the lab, you'll find him enjoying the outdoors, playing music, or raising composting worms in his front yard.
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