A new study has introduced a promising
blood test that health professionals may
soon use to accurately detect brain
cancer.

A simple blood test could make a great difference
for those with brain cancer.

Dr. Matthew J. Baker, a reader in the Department of
Pure and Applied Chemistry at the University of
Strathclyde in Glasgow, United Kingdom, is the lead
author of the new research.

He and his colleagues have now published their
findings in the journal Nature Communications .
Of the study, Dr. Baker says, "This is the first
publication of data from our clinical feasibility
study, and it is the first demonstration that our
blood test works in the clinic."

Although it is quite rare, brain cancer often has a
poor outlook.

According to the National Cancer Institute, around
0.6% of people will develop brain cancer or another
cancer of the nervous system in their lifetime.
However, the 5 year survival rate for those who do
receive such a diagnosis is less than 33%.

Largely, the poor outlook is due to the fact that
brain tumors have very nonspecific symptoms,
which makes them more difficult to distinguish from
other conditions.

Study co-author Dr. Paul Brennan — a senior clinical
lecturer and consultant neurosurgeon at the
University of Edinburgh in the U.K. — explains,
"Diagnosing brain tumors is difficult, leading to
delays and frustration for lots of [people]."

"The problem is that symptoms of brain tumor are
quite nonspecific, such as headache , or memory
problems. It can be difficult for doctors to tell
which people are most likely to have a brain
tumor," he adds.

The lack of cost effective tests that can help
doctors triage people with brain tumors in primary
care also means that it takes longer to accurately
diagnose brain cancer. This ultimately results in a
poorer outlook.

The team's new blood test brings much needed
hope in this regard. Dr. Baker and colleagues used
infrared light to create a "bio-signature" of people's
blood samples and applied artificial intelligence to
scan for signs of cancer.

The test correctly identified brain cancer in a cohort
of 104 people 87% of the time.

A more rapid means of
diagnosis

As the researchers explain in their paper, they used
a technique called attenuated total reflection-Fourier
transform infrared (ATR-FTIR) spectroscopy and
coupled it with machine learning technology to
detect brain cancer.

The authors explain that the technique is "a simple,
label free, noninvasive, nondestructive" way of
analyzing the biochemical profile of a blood sample
without requiring extensive preparation of the
sample.

Dr. Baker and team trained a machine learning
algorithm to use these biochemical fingerprints to
diagnose brain cancer in a retrospective cohort of
724 people. This cohort included people with
primary and secondary cancers as well as control
participants without cancer.

They then used the algorithm to predict brain cancer
cases in a sample of 104 participants. Of these, 12
people had cancer, including four cases of
glioblastoma. This is one of the most aggressive
forms of brain tumor.

The findings revealed a sensitivity of 83.3% and a
specificity of 87% for the blood test. "With this new
test, we have shown that we can help doctors
quickly identify which [people] with these
nonspecific symptoms should be prioritized for
urgent brain imaging," says Dr. Brennan.

"This," he adds, "means a more rapid diagnosis for
people with a brain tumor, and quicker access to
treatment."

Hayley Smith — an ambassador for the Brain Tumor
Charity in Hampshire, U.K. — adds that it is "very
encouraging to hear that this blood test can lead to
a quicker diagnosis for brain cancer."