Here we share information about breath analysis and its applications to improve people’s health.

Lung cancer breath analysis Part2

by Felix Schmidt

Lung cancer is the leading cause of cancer death worldwide - not because of its aggressive biology, but because it is often detected too late. Most lung cancer patients show genetic and metabolic aberrations represented by biological messengers (putative biomarkers). But can breath analysis reveal clues to lung cancer?

In our latest article on lung cancer, we described the potential of lung cancer breath research and presented the global landscape of research hotspots. Furthermore, we reported on the origin of putative lung cancer breath biomarkers and explained the difference between online and offline breath measurement.  

Today we want to give an overview about several technologies that have been found useful for lung cancer detection and monitoring. In general, we can distinguish between animal detection methods, pattern recognition methods, and methods that identify putative biomarkers.

 

Dogs smell lung cancer

Dogs smell lung cancer

Dogs can differentiate between different smells up to 100,000 times better than we humans can, and numerous studies have reported that the powerful canine nose can detect diseases — with especially promising results for lung cancer. Labradors, golden retrievers, and German shepherds appear to be best suited for olfactory detection.

If you want to read more about these interesting findings, check out the following links on BMC Cancer:


Is the electronic nose better than a dog’s nose?

Various sensors are used in different fields and have also been used to study exhaled human breath. Therefore, it makes sense to evaluate their efficiency for lung cancer detection. The electronic nose (eNose) approach is the most promising one in the category of pattern recognition. This emerging technology is based on the binding of VOCs (volatile organic compounds) to various sensors or sensor arrays, mostly within handheld devices. The binding of VOCs to these sensors generates an electrical signal that can be measured and interpreted. There are different technologies commercially available, and one validation study showed promising results.

👉 Please check the following sources:

Identification of putative breath biomarker in exhaled breath of lung cancer patients

The identification of molecules in exhaled breath turns out fast difficult. To detect the appearance of lung cancer via a non-invasive breath measurement, high-tech cutting-edge methods are needed. The most studied biomarker identifying methods are GC-MS, PTR-MS, and EBC assays. These have also had widespread use in other fields over time. Recently developed methods like HPPI-MS or SESI-HRMS reported more simpler sampling procedures and a higher clinical feasibility. These methods show higher sensitivity, more patient-convenient measurement procedures, and simpler biomarker identification processes. SESI-HRMS has the advantage of online measurement potential in clinical routine. However, mass spectrometry methods always need trained personnel and highly developed technical infrastructure. Thus, research into biomarkers for identifying lung cancer by breath analysis is primarily located in innovation-orientated research facilities worldwide.

👉 For further information, read the following articles:

Glossary:

  • SPME-GC-MS: Solid-phase micro-extraction – gas chromatography – mass spectrometry
  • GC-MS: Gas chromatography – mass spectrometry
  • PTR-MS: Proton transfer reaction – mass spectrometry
  • HPPI-MS: High-pressure photon ionization – time-of-flight-mass spectrometry
  • EBC: Exhaled breath condensate
  • SESI-HRMS: Secondary electrospray ionization – high-resolution mass spectrometry

We at DBI support research exploring the early diagnosis of lung cancer using state-of-the-art breath analysis. Being able to diagnose this disease early would dramatically increase the survival rate. Learn more about DBI’s technology & solution.

See the following video about breath research:

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