Cell Reports Methods,
Journal Year:
2023,
Volume and Issue:
3(1), P. 100384 - 100384
Published: Jan. 1, 2023
Gene
regulation
is
a
central
topic
in
cell
biology.
Advances
omics
technologies
and
the
accumulation
of
data
have
provided
better
opportunities
for
gene
studies
than
ever
before.
For
this
reason
deep
learning,
as
data-driven
predictive
modeling
approach,
has
been
successfully
applied
to
field
during
past
decade.
In
article,
we
aim
give
brief
yet
comprehensive
overview
representative
deep-learning
methods
regulation.
Specifically,
discuss
compare
design
principles
datasets
used
by
each
method,
creating
reference
researchers
who
wish
replicate
or
improve
existing
methods.
We
also
common
problems
approaches
prospectively
introduce
emerging
paradigms
that
will
potentially
alleviate
them.
hope
article
provide
rich
up-to-date
resource
shed
light
on
future
research
directions
area.
Journal of Hematology & Oncology,
Journal Year:
2021,
Volume and Issue:
14(1)
Published: June 9, 2021
Single-cell
sequencing,
including
genomics,
transcriptomics,
epigenomics,
proteomics
and
metabolomics
is
a
powerful
tool
to
decipher
the
cellular
molecular
landscape
at
single-cell
resolution,
unlike
bulk
which
provides
averaged
data.
The
use
of
sequencing
in
cancer
research
has
revolutionized
our
understanding
biological
characteristics
dynamics
within
lesions.
In
this
review,
we
summarize
emerging
technologies
recent
progress
obtained
by
information
related
landscapes
malignant
cells
immune
cells,
tumor
heterogeneity,
circulating
underlying
mechanisms
behaviors.
Overall,
prospects
facilitating
diagnosis,
targeted
therapy
prognostic
prediction
among
spectrum
tumors
are
bright.
near
future,
advances
will
undoubtedly
improve
highlight
potential
precise
therapeutic
targets
for
patients.
Nature Methods,
Journal Year:
2023,
Volume and Issue:
20(9), P. 1355 - 1367
Published: July 13, 2023
Abstract
Joint
profiling
of
chromatin
accessibility
and
gene
expression
in
individual
cells
provides
an
opportunity
to
decipher
enhancer-driven
regulatory
networks
(GRNs).
Here
we
present
a
method
for
the
inference
GRNs,
called
SCENIC+.
SCENIC+
predicts
genomic
enhancers
along
with
candidate
upstream
transcription
factors
(TFs)
links
these
target
genes.
To
improve
both
recall
precision
TF
identification,
curated
clustered
motif
collection
more
than
30,000
motifs.
We
benchmarked
on
diverse
datasets
from
different
species,
including
human
peripheral
blood
mononuclear
cells,
ENCODE
cell
lines,
melanoma
states
Drosophila
retinal
development.
Next,
exploit
predictions
study
conserved
TFs,
GRNs
between
mouse
types
cerebral
cortex.
Finally,
use
dynamics
regulation
differentiation
trajectories
effect
perturbations
state.
is
available
at
scenicplus.readthedocs.io
.
Nature Communications,
Journal Year:
2021,
Volume and Issue:
12(1)
Published: Nov. 1, 2021
Abstract
During
tumor
progression,
cancer
cells
come
into
contact
with
various
non-tumor
cell
types,
but
it
is
unclear
how
tumors
adapt
to
these
new
environments.
Here,
we
integrate
spatially
resolved
transcriptomics,
single-cell
RNA-seq,
and
single-nucleus
RNA-seq
characterize
tumor-microenvironment
interactions
at
the
boundary.
Using
a
zebrafish
model
of
melanoma,
identify
distinct
“interface”
state
where
contacts
neighboring
tissues.
This
interface
composed
specialized
microenvironment
that
upregulate
common
set
cilia
genes,
proteins
are
enriched
only
microenvironment.
Cilia
gene
expression
regulated
by
ETS-family
transcription
factors,
which
normally
act
suppress
genes
outside
interface.
A
cilia-enriched
conserved
in
human
patient
samples,
suggesting
feature
melanoma.
Our
results
demonstrate
power
transcriptomics
uncovering
mechanisms
allow
Nature Communications,
Journal Year:
2021,
Volume and Issue:
12(1)
Published: Jan. 4, 2021
Cell
lines
are
key
tools
for
preclinical
cancer
research,
but
it
remains
unclear
how
well
they
represent
patient
tumor
samples.
Direct
comparisons
of
and
cell
line
transcriptional
profiles
complicated
by
several
factors,
including
the
variable
presence
normal
cells
in
We
thus
develop
an
unsupervised
alignment
method
(Celligner)
apply
to
integrate
large-scale
RNA-Seq
datasets.
Although
our
aligns
majority
with
samples
same
type,
also
reveals
large
differences
similarity
across
lines.
Using
this
approach,
we
identify
hundred
from
diverse
lineages
that
present
a
more
mesenchymal
undifferentiated
state
exhibit
distinct
chemical
genetic
dependencies.
Celligner
could
be
used
guide
selection
closely
resemble
tumors
improve
clinical
translation
insights
gained
Molecular Cancer,
Journal Year:
2023,
Volume and Issue:
22(1)
Published: May 31, 2023
Epithelial
mesenchymal
transition
(EMT)
and
epithelial
(MET)
are
genetic
determinants
of
cellular
plasticity.
These
programs
operate
in
physiological
(embryonic
development,
wound
healing)
pathological
(organ
fibrosis,
cancer)
conditions.
In
cancer,
EMT
MET
interfere
with
various
signalling
pathways
at
different
levels.
This
results
gross
alterations
the
gene
expression
programs,
which
affect
most,
if
not
all
hallmarks
such
as
response
to
proliferative
death-inducing
signals,
tumorigenicity,
cell
stemness.
cancer
cells
involves
large
scale
reorganisation
cytoskeleton,
loss
integrity,
gain
traits,
type
migration.
this
regard,
EMT/MET
plasticity
is
highly
relevant
Go-or-Grow
concept,
postulates
dichotomous
relationship
between
motility
proliferation.
The
decisions
critically
important
processes
takes
central
stage,
mobilisation
stem
during
healing,
relapse,
metastasis.
Here
we
outline
maintenance
quiescence
metastatic
niches,
focusing
on
implication
regulatory
networks
switches.
particular,
discuss
analogy
residing
hybrid
quasi-mesenchymal
states
GAlert,
an
intermediate
phase
allowing
quiescent
enter
cycle
rapidly.
Cell,
Journal Year:
2024,
Volume and Issue:
187(1), P. 166 - 183.e25
Published: Jan. 1, 2024
To
better
understand
intrinsic
resistance
to
immune
checkpoint
blockade
(ICB),
we
established
a
comprehensive
view
of
the
cellular
architecture
treatment-naive
melanoma
ecosystem
and
studied
its
evolution
under
ICB.
Using
single-cell,
spatial
multi-omics,
showed
that
tumor
microenvironment
promotes
emergence
complex
transcriptomic
landscape.
Melanoma
cells
harboring
mesenchymal-like
(MES)
state,
population
known
confer
targeted
therapy,
were
significantly
enriched
in
early
on-treatment
biopsies
from
non-responders
TCF4
serves
as
hub
this
landscape
by
being
master
regulator
MES
signature
suppressor
melanocytic
antigen
presentation
transcriptional
programs.
Targeting
genetically
or
pharmacologically,
using
bromodomain
inhibitor,
increased
immunogenicity
sensitivity
ICB
therapy.
We
thereby
uncovered
TCF4-dependent
regulatory
network
orchestrates
multiple
programs
contributes
both
therapy
melanoma.
