Editorial Feature

Detecting Lung Cancer Early with Non-Invasive Nanosensors


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Nanosensors have come a long way in the last few years. The high sensitivities possible from using advanced materials with active surfaces in the sensing mechanism has meant that nanosensors have become one of the most widely researched application areas for nanomaterials.

Even though some nanomaterials may not be biocompatible for use within the body, many of the organic-based and organic-ligand functionalized nanomaterials are. This has enabled nanosensors to be developed that are usable within the human body. Researchers from the Massachusetts Institute of Technology (MIT) have now come up with a non-invasive nanosensor for detecting lung cancer.

Lung Cancer

Lung cancer is a huge killer around the world and can be caused by a number of factors, mainly lifestyle choices such as smoking, but environmental factors such as poor air quality also play their part in causing people to develop lung cancer. The different factors responsible in each country tend to be dependent on lifestyle and air quality in each country, which in turn tends to determine the development rates for the local population.

For example, in the United States (US), lung cancer is the most common cause of cancer-related deaths at 25.3%, with a five-year survival rate of only 18.6%, and an annual mortality rate of around 150,000 each year. However, if the cancer is detected early on, the five-year survival rates increase by 6- to 13-fold compare to patients who are at a more advanced stage, i.e. before the cancer spreads out from the central primary tumor.

Current Early Detection Tests for Lung Cancer

Many of the early detection tests in the US rely on low-dose computed tomography (LDCT) and are used as a routine procedure for those deemed to be high risk, such as smokers. However, despite its widespread use, its accuracy has come under fire, because it tends to produce false-positive results by picking up benign nodules in the lungs.

This causes extra time, effort and money to be needlessly spent following up on false results and performing biopsies. This is one of the reasons why this approach is not used anywhere else other than in the US and the researchers from MIT believe there is a need to develop more accurate testing capabilities in the US.

Nanoparticle Developments

The researchers from MIT, led by Sangeeta Bhatia, have been developing nanoparticles in their lab that can interact with proteases.Proteases are a type of enzyme that cleave proteins by breaking the peptide bonds, causing the proteins to break down into smaller polypeptide chains and amino acids. In lung tumors, these enzymes can help the tumor cells to break free from the primary tumor by cutting through the proteins of the extracellular matrix. This means they can be carried to other locations and form secondary tumors, thus making it much harder to treat the patient.

The nanoparticles created by the Bhatia lab were coated with peptide ligands so that they would interact with proteases, and because the nanoparticles accumulate around tumor sites, they are targeted by the protease enzymes around cancerous tumors in the lung. The Bhatia lab has already deployed these nanoparticles in other sensors for detecting ovarian and colon cancer.

New Nanosensor Development at MIT

After the success of using the nanoparticles in ovarian and colon cancer sensors, the team wanted to use them in detecting lung cancers. More specifically, they wanted to use them as a tool for confirming if a patient definitely has cancer after a positive CT result, separating the false-positive results from the actual positive results without needing to perform a biopsy. To adapt it for lung cancer, the researchers had to identify which proteases were present around lung tumors and this led to them creating 14 peptide-coated nanoparticles that had an affinity to these proteases.

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The nanoparticle sensors were delivered into two different genetic mouse models—one driven by Kras/Trp53 (KP) mutations and the other by Eml4-Alk (EA) fusion to develop lung cancer spontaneously. The researchers performed diagnostic tests at 5, 7.5 and 10.5 weeks after the tumors had started growing in order to test the effectiveness of the sensor. The tests were performed by injecting the nanoparticles directly into the airway of the mice. As the nanoparticles reached the tumor site, the proteases interacted with and cleaved the specifically designed peptide ligands on the surface of the nanoparticles and the relevant biomarkers could be found and analyzed in the subject’s urine.

Machine learning algorithms were employed to ensure the data analysis was more accurate and could effectively distinguish the differences in the data between mice with tumors and mice without tumors. The results of the tests showed that the sensor could identify the presence of tumors in one mouse model after 5 weeks and 7.5 weeks in the other, when tumors were, on average, only 2.8 mm3 in size.

One of the defining features of this test is that it could be used to distinguish between cancerous tumors and non-cancerous inflammation in the lungs (which is common among smokers), something which has been lacking with conventional CT scan tests.

This negates the need for unnecessary biopsies to be performed and offers a more reliable way of catching the cancer early, before it spreads, potentially enabling more lives to be saved. More tests will have to be performed as mouse models can produce different results to human trials, but the initial results are positive and it is thought that these nanosensors could also be used to see how well lung tumors respond to drug or immunotherapy treatments.

References and Further Reading

Himmelstein, S. (2020). Early lung cancer detection with noninvasive nanosensors. Engineering 360. Available from: https://insights.globalspec.com/article/13883/early-lung-cancer-detection-with-noninvasive-nanosensors

Kirkpatrick, J.D. et al. (2020). Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling. Science Translational Medicine, 12(537). DOI: 10.1126/scitranslmed.aaw0262


Liam Critchley

Written by

Liam Critchley




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