APRIL 2, 2020, New York— A team led by Ludwig MIT researcher Sangeeta Bhatia has devised a new approach to early diagnosis of lung cancer: a nanotechnology-based urine test that can detect the presence of proteins linked to the disease. The noninvasive test, reported in the current issue of Science Translational Medicine, has the potential to improve early detection of lung cancer. Five-year survival rates are at least six times higher when lung tumors are detected before they spread to distant locations in the body.
People at high risk for lung cancer, such as heavy smokers, are often screened with computed tomography (CT). Unfortunately, CT scans have a high rate of false positives, as they also pick up benign nodules in the lungs. Adapted to human use, the test devised by Bhatia and her colleagues could also reduce the number of false positives associated with CT scans.
“The CT scan is a good tool that can see a lot of things,” says Bhatia, who is also the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science and a member of MIT’s Koch Institute for Integrative Cancer Research. “The problem with it is that 95 percent of what it finds is not cancer, and right now you have to biopsy too many patients who test positive.”
For several years, Bhatia’s lab has been developing nanoparticles that can detect cancer by interacting with enzymes called proteases, which aid tumor metastasis. The nanoparticles are coated with peptides (short protein fragments) that are targeted by cancer-linked proteases. They accumulate at tumor sites, where the peptides are cleaved, releasing biomarkers that can then be detected in urine.
To customize the sensors for lung cancer, the researchers identified proteases that are abundant in lung cancer by searching The Cancer Genome Atlas and created a panel of 14 peptide-coated nanoparticles that could interact with these enzymes.
Bhatia and her colleagues then tested the sensors in two different mouse models of lung cancer, injecting the particles directly into the airways of the animals. They found that they could accurately detect tumors in one of the mouse models as early as 7.5 weeks after tumors began growing, when they were only 2.8 cubic millimeters in size, on average. In the other strain of mice, tumors could be detected at 5 weeks. The sensors’ success rate was comparable to or better than that of CT scans performed at the same time points.
The researchers also found that the sensors could distinguish between early-stage cancer and noncancerous inflammation of the lungs. Lung inflammation, common in people who smoke, is one of the reasons that CT scans produce so many false positives.
Bhatia suggests the nanoparticle sensors could be used as a noninvasive diagnostic for people who get a positive result on a screening test, potentially eliminating the need for a biopsy. For humans, her team is working on a form of the particles that could be inhaled as a dry powder or through a nebulizer. Another possible application is using these sensors to monitor how well lung tumors respond to treatment, such as drugs or immunotherapies.
“A great next step would be to take this into patients who have known cancer, and are being treated, to see if they’re on the right medicine,” Bhatia says.
The MIT News article from which this summary is derived can be found here.