Researchers develop highly effective tool to detect cancer, HIV
22 Mar 2016
Stanford University researchers have developed a new technique that they claim to be thousands of times more sensitive than current techniques in diagnosing diseases, from cancer to a virus like HIV.
The technique, which was found to be effective in laboratory experiments, is described in the journal ACS Central Science.
It is currently under testing in clinical trials. When a disease starts growing in the body, the immune system produces antibodies in response.
Isolating these antibodies or related biomarkers from the blood was one way that scientists inferred the presence of a disease.
This involved designing a molecule that the biomarker would bind to, and which came with an identifying ''flag.'' The flag could be isolated through a series of specialised chemical reactions, known as an immunoassay, to provide a proxy measurement of the disease.
The new technique, developed in the lab of Carolyn Bertozzi, professor of chemistry at Stanford, augmented the standard procedure with powerful DNA screening technology.
In the new technique the standard flag was replaced with a short strand of DNA, which could then be teased out of the sample using DNA isolation technologies that were far more sensitive than those possible for traditional antibody detections.
"This is spiritually related to a basic science tool we were developing to detect protein modifications, but we realised that the core principles were pretty straightforward and that the approach might be better served as a diagnostic tool," said Peter Robinson, a graduate student in Bertozzi's group.
The technique was tested with the signature DNA flag, against four commercially available, US Food and Drug Administration (FDA)-approved tests for a biomarker for thyroid cancer.
According to the researchers, it outperformed the sensitivity of all of them, by at least 800 times, and up to 10,000 times, researchers.
"The thyroid cancer test has historically been a fairly challenging immunoassay, because it produces a lot of false positives and false negatives, so it was not clear if our test would have an advantage," Robinson said.
