Minn. — The molecular makeup of brain tumors can be used to
sort patients with gliomas into five categories, each with
different clinical features and outcomes, researchers at Mayo
Clinic and the University of California San Francisco have
shown. The finding could change the methods that physicians
rely on to determine prognosis and treatment options.
Previously, they relied on how patients’ tumors look under
the microscope. The study is published online in the New
England Journal of Medicine.
findings are going to weigh heavily on the future
classification of brain tumors. The time of classifying these
tumors solely according to histology as astrocytoma,
oligodendroglioma or mixed oligoastrocytoma could be a thing
of the past," says lead study author Dr. Daniel H.
Lachance, a neuro oncologist at Mayo Clinic. "This
molecular data helps us better classify glioma patients, so we
can begin to understand who needs to be treated more
aggressively and who might be able to avoid unnecessary
approach categorizes gliomas according to the presence of
three genetic alterations. Two two are already checked
routinely in clinical practice, so a test that incorporates
all three tumor markers could be available as early as this
are tumors that arise from the glial cells of the brain and
spine, and are among the most difficult forms of cancer to
treat. Patients are typically managed with a combination of
surgery, radiation therapy and chemotherapy, but even with
aggressive treatment the majority succumb to the disease. For
a significant number of cases, the standard methods — which
use histology to classify gliomas according to their visible
characteristics — are not effective enough to accurately
predict the tumor’s subsequent behavior, potential for
response to therapy and longer -term prognosis.
last 25 years, scientists have found hundreds of genetic
defects that could form the basis of a more improved
classification system. Three of these alterations stand out
because they occur early during glioma formation, are more
prevalent in gliomas and are sometimes associated with
desirable clinical outcomes.
study, the Mayo researchers explored whether the three tumor
markers could be used to define molecular groups that better
inform glioma treatment.
results will enable clinicians to make better predictions
about which specific treatment course is necessary for each
individual patient. For example, the researchers found that
the molecular classification can identify patients with
histologically defined lower-grade tumors who have less
favorable outcomes and deserve more aggressive therapy.
this molecular data enables us to develop a better picture of
what is going in a patient. When we analyzed patient outcomes
adjusting for molecular group, histological type was no longer
associated with outcome — instead, it was dictated by the
molecular group. Having more meaningful classifications can
have a huge impact on patients; it opens up all kinds of
treatment options," said lead study author Jeanette E.
Eckel-Passow, an associate professor of biostatistics at Mayo
the researchers focused on three main mutations to define
their molecular groups, they recognized that gliomas likely
contain other genetic alterations, such as variants that might
predispose to cancer and mutations that might be acquired as
tumors grow and progress. They looked for associations between
the five molecular groups and variants they had previously
shown were linked to glioma risk, as well as other mutations
known to accumulate in cancer. The researchers found that
these other genetic changes recurred in specific patterns
within the molecular groups, further validating their biologic
molecular groups could represent distinct types of gliomas,
with different origins and paths to progression," says
Dr. Jenkins, the Ting Tsung and Wei Fong Chao Professor of
Individualized Medicine Research. "Now that we know more
about the germline alterations that predispose to these tumors
and the ensemble of mutations that are associated with each
type of glioma, we can start thinking about building models of
the disease that can help us find new therapies to precisely
target specific types of glioma."