285Proteomics of Brain Cancer Protein biomarkers of brain tumors have the potential
for clinical usefulness to predict effi cacy of anticancer agents. Surgical samples of
human GBM can be analyzed with 2D GE and MS. In vitro chemosensitivities to
various anticancer agents (e.g. cyclophosphamide, nimustine, cisplatin, cytosine
arabinoside, mitomycin C, adriamycin, etoposide, vincristine, and paclitaxel) can
be measured by fl ow cytometric detection of apoptosis. Proteins that signifi cantly
affect in vitro chemosensitivity to each category of anticancer agents are identifi ed.
Many of the proteins that correlate with chemoresistance are categorized into the
signal transduction proteins including the G-proteins. Thus proteomic analysis
using 2D GE could provide a list of proteins that may be the potential predictive
biomarkers for chemosensitivity in human gliomas. They can also be direct and
rational targets for anticancer therapy and be used for sensitization to the conven-
tional chemotherapeutic regimens.
Epigenetic Biomarkers of GBM One of the most intrigued subtypes is the long-
term survival GBM, which responds better to current therapies. An investigation
based on molecular epigenetic, clinical and histopathological analyses was carried
out to identify biomarkers useful for distinguishing long-term survival form from
classic GBM (Martinez et al. 2007 ). It involved analysis of the promoter methyla-
tion status of key regulator genes implicated in tumor invasion (TIMP2, TIMP3),
apoptosis and infl ammation (TMS1/ASC, DAPK) as well as overall survival, ther-
apy status and tumor pathological features. A methylation-specifi c PCR approach
was performed to analyze the CpG island promoter methylation status of each gene.
The results of this study indicate that, compared to classic GBM, long-term survival
form of GBM displays distinct epigenetic characteristics, which might provide
additional prognostic biomarkers for the assessment of this malignancy.
O6-methylguanine methyltransferase (MGMT) promoter methylation has been
observed in a considerable proportion of all grades and subtypes of gliomas, with no
signifi cant correlation with other known genetic alterations. On extensive literature
review, in both low- and high-grade gliomas, wide variability of data on the fre-
quency of MGMT methylation and its association with other molecular alterations
from various centers was noted, mostly owing to technical causes (Jha et al. 2010 ).
This raises questions regarding the capacity of this test for use as an objective and
reproducible biomarker for customized treatment in individual cases.
Multigene Predictor of Outcome in GBM No single biomarker is a predictor of
outcome in GBM. An analysis using GBM microarray data from four independent
data sets of the genes consistently associated with patient outcome revealed a con-
sensus 38-gene survival set (Colman et al. 2010 ). Worse outcome was associated
with increased expression of genes associated with mesenchymal differentiation
and angiogenesis. Application to FFPE samples using real-time RT-PCR assays
resulted in a 9-gene subset which appeared robust in these samples. This 9-gene set
was then validated in an additional independent sample set. Multivariate analysis
confi rmed that the 9-gene set was an independent predictor of outcome after adjust-
ing for clinical factors and methylation of the methyl-guanine methyltransferase
promoter. The 9-gene profi le was also positively associated with biomarkers of
Personalized Management of Cancers of Various Organs