A team of mechanical engineers has created a new diagnostic platform that can be used to detect various cancers and other serious medical conditions with greater efficiency.
Researchers in the labs of Tony Jun Huang, William Bevan distinguished professor of mechanical engineering and materials science, and Tuan Vo-Dinh, R. Eugene and Susie E. Goodson distinguished professor of biomedical engineering, collaborated on the study, which was published March 8 in the Science Advances journal.
The study centers around exosomes, which are tiny biological particles released by cells that contain genetic material in the form of ribonucleic acid (RNA).
“Exosomes are … highly indicative of their cells of origin,” said Ty Naquin, a fourth-year graduate student in the department of mechanical engineering and materials science who was one of the principal researchers involved with the study. “The idea is that if you can isolate these exosomes, you can look at the protein and RNA content present and diagnose for tons of diseases.”
Naquin explained that because exosomes are so small, they are difficult to isolate in organic material like blood or plasma where there are many other contaminants present. However, Huang’s lab was able to successfully isolate exosomes from blood in 2017 using acoustofluidics, the process of separating biological particles in fluids by passing them through sound waves.
Naquin explained that the current “gold standard” for exosome separation is an ultracentrifuge, which is a large machine that spins at very high speeds. However, Naquin noted that in addition to being time-intensive and requiring a large sample volume, this process can be damaging to the exosomes and often results in low purity and low yield.
“We wanted to find something that could isolate the exosomes much more efficiently, much faster, much more biocompatibly [sic],” he said.
To do so, the team developed a process that involves shooting sound waves into a water droplet containing a biological sample, which causes the droplet to spin up to 6,000 revolutions per minute. Then, a small disc is placed on top of the droplet, which begins to spin as well and acts as a centrifuge — one that is much less damaging due to its smaller scale.
At the same time that Naquin was working on this spinning disc technology, Aidan Canning, a graduate student in the department of biomedical engineering, published his first paper on microRNA sensing, improving upon existing exosome analysis methods.
Canning creates plasmonic nanoparticles that enhance the electromagnetic fields around them, which in turn enhance the Raman scattering — a type of scattered light whose intensity can be correlated to different disease biomarkers, making it useful for detection.
The students decided to combine their work in exosome separation and analysis to create a “fully integrated system” of diagnosis.
“Theoretically the diagnostic microRNAs would be present in exosomes in a higher proportion, so if we could isolate those easily and then put them to my platform, it may be even better at detecting disease,” Canning said.
Naquin says it is the first system he’s aware of that “does amplification-free, sample-to-answer detection of exosomal biomarkers,” which is “really exciting.”
Canning says the technology improves upon the standard diagnostic platform of reverse transcriptase-polymerase chain reaction (RT-PCR) — commonly used in tests for COVID-19 — because it doesn’t require exponential amplification, which can lead to inaccuracy when there are low sample amounts.
The study uses samples from colorectal cancer patients as a test of the new technology’s diagnostic ability, but both Naquin and Canning agree that it could have implications for a wide variety of cancers, in addition to other serious afflictions like Alzheimer’s and Parkinson’s disease and even traumatic injuries.
“[This new technology offers] a way to sense microRNAs quickly, reliably and without the need of waiting for technician staff to run these assays [when] we could just take plasma and use it,” Canning said. “I think people would get a much quicker answer, and also it would enable very easy early screening for types of diseases which may not have early screening methods currently.”
“To get diagnosed for cancer, you can’t do it until symptoms are already occurring. Right now, I think imaging is the main way to do it, and of course you have to have some sort of sizable tumor to see it,” Naquin said. “For many cancers, that’s way too late.”
Naquin posited that in the future, biomarker detection technology using exosomes could be useful for identifying disease predisposition in addition to current affliction.
Canning said his lab’s future work will focus on gearing this microRNA detection technology specifically toward a number of cancers — including lung, ovarian and pancreatic — that currently have no widely available treatment method.
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Zoe Kolenovsky is a Trinity sophomore and news editor of The Chronicle's 120th volume.