Cell Reports Medicine,
Journal Year:
2024,
Volume and Issue:
5(3), P. 101446 - 101446
Published: March 1, 2024
Germline
variation
and
somatic
alterations
contribute
to
the
molecular
profile
of
cancers.
We
combine
RNA
with
whole
genome
sequencing
across
1,218
cancer
patients
determine
extent
germline
structural
variants
(SVs)
impact
expression
nearby
genes.
For
hundreds
genes,
recurrent
common
SV
breakpoints
within
100
kb
associate
increased
or
decreased
in
tumors
spanning
various
tissues
origin.
A
significant
fraction
associations
involves
duplication
intergenic
enhancers
3′
UTR
disruption.
Genes
altered
by
both
SVs
include
ATRX
CEBPA.
essential
cell
lines
BARD1
IRS2.
breakpoint
patterns
associated
patient
survival
GCLM.
Our
results
capture
a
class
phenotypic
at
work
disease
setting,
including
genes
roles.
Specific
represent
potential
risk
for
genetic
testing,
those
involving
targeting
implications.
Nature,
Journal Year:
2019,
Volume and Issue:
575(7781), P. 210 - 216
Published: Oct. 23, 2019
Abstract
Metastatic
cancer
is
a
major
cause
of
death
and
associated
with
poor
treatment
efficacy.
A
better
understanding
the
characteristics
late-stage
required
to
help
adapt
personalized
treatments,
reduce
overtreatment
improve
outcomes.
Here
we
describe
largest,
our
knowledge,
pan-cancer
study
metastatic
solid
tumour
genomes,
including
whole-genome
sequencing
data
for
2,520
pairs
normal
tissue,
analysed
at
median
depths
106×
38×,
respectively,
surveying
more
than
70
million
somatic
variants.
The
characteristic
mutations
lesions
varied
widely,
that
reflect
those
primary
types,
high
rates
duplication
events
(56%).
Individual
were
relatively
homogeneous,
vast
majority
(96%)
driver
being
clonal
up
80%
tumour-suppressor
genes
inactivated
bi-allelically
by
different
mutational
mechanisms.
Although
genomes
showed
similar
landscape
tumours,
find
could
contribute
responsiveness
therapy
or
resistance
in
individual
patients.
We
implement
an
approach
review
clinically
relevant
associations
their
potential
actionability.
For
62%
patients,
identify
genetic
variants
may
be
used
stratify
patients
towards
therapies
either
have
been
approved
are
clinical
trials.
This
demonstrates
importance
comprehensive
genomic
profiling
precision
medicine
cancer.
Nature Communications,
Journal Year:
2020,
Volume and Issue:
11(1)
Published: Feb. 5, 2020
Abstract
In
cancer,
the
primary
tumour’s
organ
of
origin
and
histopathology
are
strongest
determinants
its
clinical
behaviour,
but
in
3%
cases
a
patient
presents
with
metastatic
tumour
no
obvious
primary.
Here,
as
part
ICGC/TCGA
Pan-Cancer
Analysis
Whole
Genomes
(PCAWG)
Consortium
,
we
train
deep
learning
classifier
to
predict
cancer
type
based
on
patterns
somatic
passenger
mutations
detected
whole
genome
sequencing
(WGS)
2606
tumours
representing
24
common
types
produced
by
PCAWG
Consortium.
Our
achieves
an
accuracy
91%
held-out
tumor
samples
88%
83%
respectively
independent
samples,
roughly
double
trained
pathologists
when
presented
without
knowledge
Surprisingly,
adding
information
driver
reduced
accuracy.
results
have
applicability,
underscore
how
encode
state
cell
origin,
can
inform
future
strategies
detect
source
circulating
DNA.
Nature Communications,
Journal Year:
2020,
Volume and Issue:
11(1)
Published: Oct. 16, 2020
Abstract
To
increase
understanding
of
the
genomic
landscape
acral
melanoma,
a
rare
form
melanoma
occurring
on
palms,
soles
or
nail
beds,
whole
genome
sequencing
87
tumors
with
matching
transcriptome
for
63
was
performed.
Here
we
report
that
mutational
signature
analysis
reveals
subset
tumors,
mostly
subungual,
an
ultraviolet
radiation
signature.
Significantly
mutated
genes
are
BRAF,
NRAS
,
NF1
NOTCH2
PTEN
and
TYRP1
.
Mutations
amplification
KIT
also
common.
Structural
rearrangement
copy
number
signatures
show
duplication,
aneuploidy
complex
rearrangements
Complex
occur
recurrently
associated
TERT
CDK4
MDM2
CCND1
PAK1
GAB2
indicating
potential
therapeutic
options.
Genome biology,
Journal Year:
2018,
Volume and Issue:
19(1)
Published: Dec. 1, 2018
DNA
is
subject
to
constant
chemical
modification
and
damage,
which
eventually
results
in
variable
mutation
rates
throughout
the
genome.
Although
detailed
molecular
mechanisms
of
damage
repair
are
well
understood,
impact
execution
across
a
genome
remain
poorly
defined.To
bridge
gap
between
our
understanding
distributions,
we
developed
novel
method,
AP-seq,
capable
mapping
apurinic
sites
8-oxo-7,8-dihydroguanine
bases
at
approximately
250-bp
resolution
on
genome-wide
scale.
We
directly
demonstrate
that
accumulation
rate
varies
widely
genome,
with
hot
spots
acquiring
many
times
more
than
cold
spots.
Unlike
single
nucleotide
variants
(SNVs)
cancers,
burden
correlates
marks
for
open
chromatin
notably
H3K9ac
H3K4me2.
Apurinic
oxidative
also
highly
enriched
transposable
elements
other
repetitive
sequences.
In
contrast,
observe
reduction
loop
anchors
increased
load
towards
inactive
compartments.
Less
found
promoters,
exons,
termination
sites,
but
not
introns,
seemingly
transcription-independent
GC
content-dependent
manner.
Leveraging
cancer
genomic
data,
find
locally
reduced
SNV
coding
sequence,
functional
elements.Our
study
reveals
differ
strongly
culminate
previously
unappreciated
mechanism
safeguards
regulatory
regions
genes
from
mutations.
Nature Ecology & Evolution,
Journal Year:
2021,
Volume and Issue:
6(2), P. 207 - 217
Published: Dec. 23, 2021
Characterizing
the
mode-the
way,
manner
or
pattern-of
evolution
in
tumours
is
important
for
clinical
forecasting
and
optimizing
cancer
treatment.
Sequencing
studies
have
inferred
various
modes,
including
branching,
punctuated
neutral
evolution,
but
it
unclear
why
a
particular
pattern
predominates
any
given
tumour.
Here
we
propose
that
tumour
architecture
key
to
explaining
variety
of
observed
genetic
patterns.
We
examine
this
hypothesis
using
spatially
explicit
population
genetics
models
demonstrate
that,
within
biologically
relevant
parameter
ranges,
different
spatial
structures
can
generate
four
evolutionary
modes:
rapid
clonal
expansion,
progressive
diversification,
branching
effectively
almost
evolution.
Quantitative
indices
describing
classifying
these
modes
are
presented.
Using
indices,
show
our
model
predictions
consistent
with
empirical
observations
types
corresponding
structures.
The
cell
dispersal
range
cell-cell
interactions
found
be
essential
factors
accurately
characterizing,
controlling