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Biomedical professor’s research receives $2.4 million in NIH funding By Chris Kocher
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WATSON REVIEW
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ore than 1.5 million Americans are diagnosed each year with solitary pulmonary nodules (SPNs). These abnormalities in the lungs, often found during routine X-rays or CT scans, are isolated groups of cells up to 3 centimeters in size. Many SPNs are benign, but figuring out which ones are malignant isn’t easy. One method is to scan patients again in three to six months so the nodules can be rechecked. If it looks like they’ve grown or changed, there’s a risk they could be a malignant lesion and cancer cells already are traveling through the bloodstream to other parts of the patient’s body. Another method is to perform tissue biopsies, but those can be painful and difficult to accomplish because the nodules are relatively tiny. Missing the target and taking surrounding healthy cells instead can lead to misdiagnosis. Assistant Professor Yuan Wan from Watson College’s Department of Biomedical Engineering wants to develop a faster, less painful way to diagnose malignant SPNs. In 2021, he received a five-year, $2.4 million grant from the National Institutes of Health (NIH), with the possibility of two years’ additional funding pending initial results. The funding is through the NIH’s prestigious MERIT (Method to Extend Research in Time) Award program. Established in 1986, the MERIT program supports both experienced researchers as well as early-stage investigators such as Wan who are in the first 10 years of their careers. Awards through the program are known as R37 awards. Wan hopes to reduce detection time so patients would know within a week whether their SPNs
should be removed. The method would analyze extracellular vesicles, which are small sacs of proteins, lipids and nucleic acids that cells secrete for intercellular communication. Under Wan’s vision, a patient would give blood, and the vesicles would be extracted from the plasma and enriched using specially designed microfluidic devices. “If we can collect these vesicles and use a very high-sensitivity detection technology,” he says, “we probably can tell if there is some abnormal information from the extracellular vesicles and give a diagnosis about whether it’s a tumor or just benign based on the mutation information.” In a collaboration with Johns Hopkins University, the effectiveness of these new tests would be judged against tissue samples collected from patients with SPNs. “In cancer diagnoses right now, tissue samples are still the gold standard, so when you develop any new technology, you always need to compare with the tissue sample,” Wan says. “In this experiment, we’re going to collect the samples from patients with malignant tumors as well as normal tissue samples and benign SPN samples as negative controls. We will extract the DNA from the tumor sample and the normal sample, and then use a 565-gene panel to learn about mutation evolution in cancer progression, look at the mutation pattern and find out the mutation hallmarks of malignant SPNs.” From there, Wan would zero in on 60 or fewer gene mutations that are telltale signs of malignancy and develop a commercial version of the test for use by medical providers. His ambition
