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A random Abstract
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Functional copy-number alterations in cancer.
[pleomorphic liposarcoma]
Understanding
the
molecular
basis
of
cancer
requires
characterization
of
its
genetic
defects
.
DNA
microarray
technologies
can
provide
detailed
raw
data
about
chromosomal
aberrations
in
tumor
samples
.
Computational
analysis
is
needed
(
1
)
to
deduce
from
raw
array
data
actual
amplification
or
deletion
events
for
chromosomal
fragments
and
(
2
)
to
distinguish
causal
chromosomal
alterations
from
functionally
neutral
ones
.
We
present
a
comprehensive
computational
approach
,
RAE
,
designed
to
robustly
map
chromosomal
alterations
in
tumor
samples
and
assess
their
functional
importance
in
cancer
.
To
demonstrate
the
methodology
,
we
experimentally
profile
copy
number
changes
in
a
clinically
aggressive
subtype
of
soft
-tissue
sarcoma
,
pleomorphic
liposarcoma
,
and
computationally
derive
a
portrait
of
candidate
oncogenic
alterations
and
their
target
genes
.
Many
affected
genes
are
known
to
be
involved
in
sarcomagenesis
;
others
are
novel
,
including
mediators
of
adipocyte
differentiation
,
and
may
include
valuable
therapeutic
targets
.
Taken
together
,
we
present
a
statistically
robust
methodology
applicable
to
high
-resolution
genomic
data
to
assess
the
extent
and
function
of
copy-number
alterations
in
cancer
.
Diseases
Validation
Diseases presenting
"high-resolution genomic data"
symptom
pleomorphic liposarcoma
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