New technique could aid targeted lung cancer treatment
Researchers from the University of Edinburgh and NHS Lothian have developed a new diagnostic technique using fluorescence lifetime imaging microscopy (FLIM) to identify lung cancer mutations. This AI-driven method offers a faster, cheaper, and non-invasive alternative to traditional genetic sequencing.
Why it matters
This innovation could significantly improve patient outcomes by accelerating the diagnostic process and enabling earlier access to targeted cancer therapies.
(c) National Cancer Institute - unsplash.com
The technology was able to identify specific genetic changes with high accuracy, offering a potentially faster, more efficient and cheaper testing option than traditional methods. The findings, published in the journal Cancer Research , have the potential to accelerate testing for lung cancer patients, helping doctors to identify the right treatment for patients more quickly, experts say.
Lung cancer remains the leading cause of cancer-related death worldwide. Some lung cancers carry specific DNA genetic changes, such as mutations in the EGFR gene, which can determine whether patients would benefit from targeted treatments. Detecting these mutations currently requires laboratory tests like gene sequencing, which can be expensive, time-consuming, and use up valuable tissue from small biopsy samples. Availability of tissue is often limited, so there is a need for non-invasive approaches to identify EGFR mutations.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in