Researchers at the Stanford University School of Medicine say the approach, which should be broadly applicable to many types of cancers, is highly sensitive and specific. (Agencies)
With it they were able to accurately identify about 50 per cent of people in the study with stage-1 lung cancer and all patients whose cancers were more advanced.
"We set out to develop a method that overcomes two major hurdles in the circulating tumour DNA field," said Maximilian Diehn, assistant professor of radiation oncology.
Even in the absence of treatment, cancer cells are continuously dividing and dying.
As they die, they release DNA into the bloodstream, like tiny genetic messages in a bottle.
Learning to read these messages — and to pick out the one in 1,000 or 10,000 that come from a cancer cell — can allow clinicians to quickly and noninvasively monitor the volume of
tumour, a patient's response to therapy and even how the tumour mutations evolve over time in the face of treatment or other selective pressures.
"We needed a comprehensive strategy for isolating the circulating DNA from blood and detecting the rare, cancer-associated mutations. To boost the sensitivity of the technique, we optimised methods for extracting, processing and analysing the DNA," said Bratman.
The researchers' technique, dubbed CAPP-Seq, for Cancer Personalised Profiling by deep Sequencing, is sensitive enough to detect just one molecule of tumour DNA in a sea of 10,000 healthy DNA molecules in the blood.
Although the researchers focused on patients with non-small-cell lung cancer (which includes most lung cancers, including adenocarcinomas, squamous cell carcinoma and large cell carcinoma), the approach should be widely applicable to many different solid tumours throughout the body.
It's also possible that it could be used not just to track the progress of a previously diagnosed patient, but also to screen healthy or at-risk populations for signs of trouble.
CAPP-Seq may also be useful as a prognostic tool, the researchers found.
The findings were published in the journal Nature Medicine.
Researchers at the Stanford University School of Medicine say the approach, which should be broadly applicable to many types of cancers, is highly sensitive and specific.