Indian-origin MIT engineer’s inhalable sensors to detect lung cancer early

IANS-

Diagnosing lung cancer could become as easy as inhaling nanoparticle sensors and then taking a urine test that reveals whether a tumor is present, according to an Indian-origin engineer at the Massachusetts Institute of Technology (MIT) in the US.

The new diagnostic is based on nanosensors that can be delivered by an inhaler or a nebulizer.

If the sensors encounter cancer-linked proteins in the lungs, they produce a signal that accumulates in the urine, where it can be detected with a simple paper test strip.

This approach could potentially replace or supplement the current gold standard for diagnosing lung cancer, low-dose computed tomography (CT). It could have an especially significant impact in low- and middle-income countries that don’t have widespread availability of CT scanners, according to the research published in the journal Science Advances.

“Around the world, cancer is going to become more and more prevalent in low- and middle-income countries. The epidemiology of lung cancer globally is that it’s driven by pollution and smoking, so we know that those are settings where accessibility to this kind of technology could have a big impact,” said Sangeeta Bhatia, Professor of Health Sciences and Technology and of Electrical Engineering and Computer Science at MIT.

“We were really pushing this assay to be point-of-care available in a low-resource setting, so the idea was to not do any sample processing, not do any amplification, just to be able to put the sample right on the paper and read it out in 20 minutes,” Bhatia said.

The researchers tested their diagnostic system in mice that are genetically engineered to develop lung tumours similar to those seen in humans.

The sensors were administered 7.5 weeks after the tumors started to form, a time point that would likely correlate with stage 1 or 2 cancer in humans.

In their first set of experiments in the mice, the researchers measured the levels of 20 different sensors designed to detect different proteases.

Using a machine learning algorithm to analyze those results, the researchers identified a combination of just four sensors that was predicted to give accurate diagnostic results. They then tested that combination in the mouse model and found that it could accurately detect early-stage lung tumors.

For use in humans, more sensors might be needed to make an accurate diagnosis, but that could be achieved by using multiple paper strips, each of which detects four different DNA barcodes, the researchers said.

 

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