Chinese researchers have created an effective method for identifying and distinguishing non–small lung cancer (NSCLC) subtypes, utilizing nanotechnology in conjunction with statistical methods.
The field of nanotechnology, the science and engineering of controlling matter at the molecular level to create devices with novel, chemical, physical, or biological properties, is an emerging resource for health care providers, as advancements continue to provide new methods for cancer treatment and diagnosis. Still, nanotechnology methods are still far from perfect, as researchers continue to test and explore these approaches.
In a study published in Royal Society of Chemistry, researchers were able to successfully identify three subtypes of NSCLC cells through the use of surface-enhanced Raman scattering or spectroscopy (SERS), a powerful technique that can be applied to enhance the sensitivity of biochemical analysis of bodily fluids, such as serum.
The researchers used a statistical modeling approach to determine the prediction accuracy of their SERS technique. In independent “unknown” cell samples, models had a prediction accuracy of 88.75% and an accuracy of ~95% for subtypes in mixed samples on a single-cell level. Therefore, researchers concluded that their method was highly effective for non-invasively diagnosing NSCLC subtype through the evaluation of circulating tumor cells.
NSCLC is the most common form of lung cancer, comprising about 75% of all cases; however, the disease can present in a number of different subtypes. Identifying what specific subtype of NSCLC a patient has can be key in guiding therapy strategies to improve outcomes.
