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MRI: A window
to genetic properties of Brain Tumors
Newswise — Doctors
diagnose and prescribe treatment for brain
tumors by studying, under a microscope,
tumor tissue and cell samples obtained
through invasive biopsy or surgery.
Now,
researchers at the University of California,
San Diego (UCSD) School of Medicine have
shown that Magnetic Resonance Imaging (MRI)
technology has the potential to
non-invasively characterize tumors and
determine which of them may be responsive to
specific forms of treatment, based on their
specific molecular properties.
“This approach reveals
that, using existing imaging techniques, we
can identify the molecular properties of
tumors,” said Michael Kuo, M.D., assistant
professor of interventional radiology at
UCSD School of Medicine. Kuo and colleagues
analyzed more than 2,000 genes that had
previously been shown to have altered
expression in Glioblastoma multiforme (GBM)
tumors.
They then mapped the correlations
between gene expression and MRI features.
The researchers also
identified characteristic imaging features
associated with overall survival of patients
with GBM, the most common and lethal type of
primary brain tumor.
The researchers
discovered five distinct MRI features that
were significantly linked with particular
gene expression patterns.
For example, one
specific characteristic seen in some images
is associated with proliferation of the
tumor, and another with growth and formation
of new blood vessels within the tumor–both
of which are susceptible to treatment with
specific drugs.
These physiological
changes seen in the images are caused by
genetic programs, or patterns of gene
activation within the tumor cells.
Some of
these programs are tightly associated with
drug targets, so when they are detected,
they could indicate which patients would
respond to a particular anti-cancer therapy,
according to the researchers.
“For the first time, we
have shown that the activity of specific
molecular programs in these tumors can be
determined based on MRI scans alone,” said
Kuo.
“We were also able to link the MRI with
a group of genes that appear to be involved
in tumor cell invasion–a phenotype
associated with a reduced rate of patient
survival.”
Laboratory work that
relies on tissue samples is routinely used
to diagnose and guide treatment for GBM.
However, the biological activity shown may
depend on the portion of the tumor from
which the tissue sample is obtained.
The
researchers have shown that MRI could be
used to identify differences in gene
expression programs within the same tumor.
“Gene expression
results in the production of proteins, which
largely determine a tumor’s characteristics
and behavior.
"This non-invasive MRI method
could, for example, detect which part of a
tumor expresses genes related to blood
vessel formation and growth or tumor cell
invasion,” said Kuo.
“Understanding the
genetic activity could prove to be a very
strong predictor of survival in patients,
and help explain why some patients have
better outcomes than others.”
Kuo also led a study,
published in Nature Biotechnology in May
2007, correlating CT images of cancerous
tissue with gene expression patterns in
liver tumors.
“In the new study, we were
able to take a different imaging technology,
MRI, and apply it to a totally different
tumor type,” he said, noting that the
studies open up promising new avenues for
non-invasive diagnoses and classification of
cancer.
Contributors to the
paper include first author Maximilian Diehn,
UCSD Department of Radiology and Department
of Radiation Oncology at Stanford University
School of Medicine; Christine Nardini and
David S. Wang, UCSD Department of Radiology;
Susan McGovern and Kenneth Aldape,
Department of Neuropathology, University of
Texas M.D. Anderson Cancer Center, Houston;
Mahesh Jayaraman, Department of Radiology,
Brown University; Yu Liang, UCSF Brain Tumor
Research Center, and Soonmee Cha, Department
of Radiology, UCSF Medical Center.
The research was funded
in part by the National Institutes of
Health.
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