Massachusetts Institute of Technology (MIT) researchers have used nanoparticles to detect the protease activity of lung cancer, which can be read with a simple urine test.
Lung cancer is the leading cause of cancer-related death in the United States, accounting for 25.3% of all cancer-related deaths. There is a poor prognosis for patients when a diagnosis is made, with fewer than 19% surviving for more than 5 years. The reason is many patients are only diagnosed in the latter stages of the disease once the cancer has metastasized. If lung cancer is detected before metastasis, the survival rate is 6-13-fold higher.
Detecting lung cancer in the earlier stages when treatments can be provided and are likely to be effective would greatly improve patient outcomes. The current approach for detecting lung cancer in at-risk groups is a low-dose CT scan, which has a high false positive rate. Low-dose CT scans also pick up benign nodules in the lungs, meaning patients have to have an unnecessary invasive biopsy, which carries a risk of complications.
“The CT scan is a good tool that can see a lot of things,” said Sangeeta Bhatia, PhD, John and Dorothy Wilson professor of health sciences and technology and electrical engineering and computer science at MIT and lead author of the paper. “The problem with it is that 95% of what it finds is not cancer, and right now you have to biopsy too many patients who test positive.”
The nanoparticles have been developed over several years by the MIT researchers. They have been developed to be attacked by cancer-related proteases. After being introduced, the peptide-coated nanoparticles collect at tumor sites where the peptides are cleaved from the coating by the cancer proteases. Those peptides can then be detected in the urine. The nanoparticle test was able to differentiate between lung inflammation and lung cancer. The nanoparticles did not detect the protease activity in a colorectal cancer xenograft model.
In their tests, the researchers injected the nanoparticles directly into the airways of mice and conducted the diagnostic test at 5 weeks, 7.5 weeks, and 10 weeks after tumor growth had stated. Using an AI-based system to help interpret the results and differentiate between mice that had lung cancer and those that did not, they were able to detect lung cancer as early as 7.5 weeks after tumor formation had started in one strain of mice and 5 weeks in the other. The test was demonstrated to be as good as or better than CT scans for detecting cancer at the same time points and the researchers were able to detect lung cancer tumors as small as 2.8 mm³.
“Intrapulmonary administration of the nanosensors to a Kras- and Trp53-mutant lung adenocarcinoma mouse model confirmed the role of metalloproteases in lung cancer and enabled accurate detection of localized disease, with 100% specificity and 81% sensitivity,” said the researchers. “Furthermore, this approach generalized to an alternative autochthonous model of lung adenocarcinoma, where it detected cancer with 100% specificity and 95% sensitivity and was not confounded by lipopolysaccharide-driven lung inflammation.”
The researchers suggest that their diagnostic test could be used on patients who have had a positive result from a low-dose CT scan rather than sending patients for an invasive test such as a lung tissue biopsy.
The researchers are developing their nanoparticles to be used in humans through a nebulizer, or as a dry powder inhaler. They are also developing nanoparticles that could be used to differentiate between viral and bacterial pneumonia, which could help clinicians determine which patients should be given antibiotics.
You can read more about the study in the paper – Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling – which was recently published in the journal Science Translational Medicine. DOI: 10.1126/scitranslmed.aaw0262