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Proteomic-based prognosis of brain tumor patients using
direct-tissue matrix-assisted laser desorption ionization mass spectrometry
Schwartz
SA, Weil
RJ, Thompson
RC, Shyr
Y, Moore
JH, Toms
SA, Johnson
MD, Caprioli
RM
Department of Biochemistry, Vanderbilt University School of Medicine,
Nashville, Tennessee 37232-8575, USA.
Clinical diagnosis and treatment decisions for a subset of primary human
brain tumors, gliomas, are based almost exclusively on tissue histology.
Approaches for glioma diagnosis can be highly subjective due to the
heterogeneity and infiltrative nature of these tumors and depend on the
skill of the neuropathologist.
There is therefore a critical need to develop
more precise, non-subjective, and systematic methods to classify human
gliomas.
To this end, mass spectrometric analysis has been applied to these
tumors to determine glioma-specific protein patterns.
Protein profiles have
been obtained from human gliomas of various grades through direct analysis
of tissue samples using matrix-assisted laser desorption ionization mass
spectrometry (MS).
Statistical algorithms applied to the MS profiles from
tissue sections identified protein patterns that correlated with tumor
histology and patient survival.
Using a data set of 108 glioma patients, two
patient populations, a short-term and a long-term survival group, were
identified based on the tissue protein profiles.
In addition, a subset of 57
patients diagnosed with high-grade, grade IV, malignant gliomas were
analyzed and a novel classification scheme that segregated short-term and
long-term survival patients based on the proteomic profiles was developed.
The protein patterns described served as an independent indicator of patient
survival.
These results show that this new molecular approach to monitoring
gliomas can provide clinically relevant information on tumor malignancy and
is suitable for high-throughput clinical screening.
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