283(APVACs) tailored for each patient based on the individual aspects of the patient’s
tumor and immune system. The latest technologies, including next-generation
sequencing, high-sensitivity MS and innovative immunomonitoring approaches,
will be combined to generate an optimal therapy for the individual patient. At the
core of the project is GAPVAC-101, a phase I clinical trial on newly diagnosed
GBM patients, which started in 2014. Newly diagnosed GBM patients are repeti-
tively immunized with an actively personalized peptide vaccine specifi cally pre-
pared for each plus polyimmunomodulators concurrent to fi rst line temozolomide
maintenance therapy. An extensive biomarker program will investigate the
mechanism- of-action and identify biomarker signature candidates to predict which
patients are most likely to benefi t from treatment with APVACs.
Prognosis of Glioblastoma Multiforme Based on Its Genetic Landscape
The alteration of multiple networking genes by recurrent chromosomal aberrations
in gliomas deregulates critical signaling pathways through multiple, cooperative
mechanisms (Bredel et al. 2009 ). These mutations, which are likely due to nonran-
dom selection of a distinct genetic landscape during gliomagenesis, are associated
with patient prognosis.
A clinical study has shown that 14-3-3zeta positive expression was observed in
approximately 74.5 % of patients with GBM who had lower overall survival rates
and median survival time than those in the 14-3-3zeta negative group (Yang et al.
2011 ). 14-3-3zeta positive expression in tumor cells also was correlated with a
shorter interval to tumor recurrence. Univariate and multivariate analyses showed
that 14-3-3zeta positive expression was an independent prognostic factor for GBM
and can be used as a biomarker.
GBMs often have both monosomy of chromosome 10 and gains of the EGFR
gene locus on chromosome 7. Chromosome 10 losses that decrease tumor suppres-
sor gene ANXA7 levels correspond to a rise in EGFR levels that increase tumor
aggressiveness and decrease survival times. This provides a clinically relevant
mechanism to augment EGFR signaling in glioblastomas beyond that resulting
from amplifi cation of the EGFR gene (Yadav et al. 2009 ). Further work is continu-
ing to characterize the mechanism by which ANXA7 regulates EGFR.
Seven of the 31 most intriguing landscape genes are independently associated
with patient survival in GBM: POLD2, CYCS, MYC, AKR1C3, YME1L1, ANXA7,
and PDCD4. This seven-gene set could retrospectively classify patients into
subgroups linked to survival times. Individuals who have alterations in between
zero and two of the seven genes are classifi ed as low risk, while those with fi ve or
more affected genes are considered high risk. Those in between are classifi ed as
high risk. This type of approach could have clinical applications both for improving
brain tumor classifi cation methods (currently based on histology and clinical factors
such as age) and guiding treatment decisions. These fi ndings will spur the develop-
ment of new therapies based on key brain cancer pathways. Prospective clinical
trials are planned for testing the clinical utility of the seven-gene set. A similar
Personalized Management of Cancers of Various Organs