* Astronomical algorithms used to study tumour samples
* Automated system taps software for exploring night sky
By Ben Hirschler
LONDON, Feb 20 In an unlikely tie-up,
astronomers and cancer researchers have joined forces to study
breast tumours using image analysis software originally
developed to explore the distant stars.
The automated system offers a speedy way to test if tumours
are aggressive and may mean pathologists one day no longer have
to peer down a microscope to spot subtle differences in tissue
Scientists at the University of Cambridge said on Wednesday
that astronomical algorithms, or problem-solving procedures,
adapted to biology had proved much faster and just as accurate
as traditional tumour analysis procedures.
Astronomers have long used sophisticated computer systems to
help pick out indistinct objects in the night sky, and the
software used by the Cambridge team first developed to help spot
planets that might harbour life outside our solar system.
But such star-gazing skills have gone largely unnoticed in
biomedical field, at least until now.
"In shows that we don't cross-communicate as much as we
ought to," said lead researcher Raza Ali, a pathologist from
Cancer Research UK's Cambridge Institute.
Ali and colleagues studied just over 2,000 tumour samples
and found the astronomical algorithm system could process them
in a day, compared to the week they would have taken to analyse
They now plan a larger international study involving samples
from more than 20,000 breast cancer patients to refine the
Studying tumour samples is a key part of breast cancer
treatment since differences can show whether or not a tumour
expresses a certain protein. A "positive" result means a patient
may be suitable for a targeted drug like Roche's
Some diagnostics companies are already looking at other ways
to automate the analysis of tumour samples but Ali said this was
the first example of exploiting know-how adapted from astronomy.
The team of Cambridge cancer researchers and astronomers,
who published their findings in the British Journal of Cancer,
have placed all their algorithms and images in the public domain
in the hope of encouraging further collaboration.
(Editing by Louise Heavens)