New technique for early lung cancer detection

The conventional screening method for early lung cancer detection entails lying on a table and having a low-dose CT scan make detailed images of your lung. However, a new technology could change that.

A team of scientists have developed a new diagnostic method that involves inhaling nanoparticle sensors, administered through an inhaler or nebulise,  and then taking a urine test to check whether a tumour is present. 

To achieve that, the researchers created two formulations of their particles: a solution that can be aerosolised and delivered with a nebuliser, and a dry powder that can be delivered using an inhaler. When the sensors encounter cancer-linked proteins in the lungs, they generate a signal that builds up in the urine and can be identified using an easy paper test strip.

The innovative strip is engineered in such a way that it can detect up to four unique DNA barcodes, each indicative of the presence of a distinct protease. According to the researchers, no pre-treatment of the urine sample is required for the test. Furthermore, results can be obtained in just 20 minutes.

The researchers see this new technology as a game-changer in the medical sphere and a breakthrough for low-income countries where there is limited availability of CT scanners.  “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,” says Sangeeta Bhatia, one of the researchers, and a member of MIT’s Koch Institute for Integrative Cancer Research and the Institute for Medical Engineering and Science.

In earlier iterations, the sensors targeted other cancer locations such as the liver and ovaries and administered into a vein. For this specific diagnosis, the scientists say they wanted to create a version that those testing could inhale, making its adoption easier even in low-resource settings.

According to Bhatia, “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.”

To validate their diagnostic system, the researchers used mice that were genetically modified to develop lung tumours resembling those found in humans. The sensors were administered approximately 7.5 weeks after tumour initiation, a timeframe roughly equivalent to stage one or two cancer in humans. Employing a machine learning algorithm, the researchers identified a combination of four sensors that effectively detected early-stage lung tumours.

While diagnosis of lung cancer in humans may require more sensors, the researchers suggest the use of multiple paper strips, each detecting four different DNA barcodes. The next steps involve analysing human biopsy samples to assess the sensors’ efficacy in detecting human cancers, with the ultimate goal of conducting clinical trials. 

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