Trends in Pharmacological Sciences,
Год журнала:
2024,
Номер
45(4), С. 304 - 318
Опубликована: Март 6, 2024
Breast
cancer's
tendency
to
metastasize
poses
a
critical
barrier
effective
treatment,
making
it
leading
cause
of
mortality
among
women
worldwide.
A
growing
body
evidence
is
showing
that
translational
adaptation
emerging
as
key
mechanism
enabling
cancer
cells
thrive
in
the
dynamic
tumor
microenvironment
(TME).
Here,
we
systematically
summarize
how
breast
utilize
drive
metastasis,
highlighting
intricate
regulation
by
specific
translation
machinery
and
mRNA
attributes
such
sequences
structures,
along
with
involvement
tRNAs
other
trans-acting
RNAs.
We
provide
an
overview
latest
findings
concepts
this
area,
discussing
their
potential
implications
for
therapeutic
strategies
cancer.
The
precise
control
of
messenger
RNA
(mRNA)
translation
is
a
crucial
step
in
posttranscriptional
gene
regulation
cellular
physiology.
However,
it
remains
challenge
to
systematically
study
mRNA
at
the
transcriptomic
scale
with
spatial
and
single-cell
resolution.
Here,
we
report
development
ribosome-bound
mapping
(RIBOmap),
highly
multiplexed
three-dimensional
situ
profiling
method
detect
translatome.
RIBOmap
981
genes
HeLa
cells
revealed
cell
cycle-dependent
translational
colocalized
functional
modules.
We
mapped
5413
mouse
brain
tissues,
yielding
spatially
resolved
translatomic
profiles
for
119,173
revealing
type-specific
region-specific
regulation,
including
remodeling
during
oligodendrocyte
maturation.
Our
detected
widespread
patterns
localized
neuronal
glial
intact
tissue
networks.
Abstract
The
spatial
organization
of
molecules
in
a
cell
is
essential
for
their
functions.
While
current
methods
focus
on
discerning
tissue
architecture,
cell–cell
interactions,
and
expression
patterns,
they
are
limited
to
the
multicellular
scale.
We
present
Bento,
Python
toolkit
that
takes
advantage
single-molecule
information
enable
analysis
at
subcellular
Bento
ingests
molecular
coordinates
segmentation
boundaries
perform
three
analyses:
defining
domains,
annotating
localization
quantifying
gene–gene
colocalization.
demonstrate
MERFISH,
seqFISH
+
,
Molecular
Cartography,
Xenium
datasets.
part
open-source
Scverse
ecosystem,
enabling
integration
with
other
single-cell
tools.
Despite
recent
advances
in
imaging-
and
antibody-based
methods,
achieving
in-depth,
high-resolution
protein
mapping
across
entire
tissues
remains
a
significant
challenge
spatial
proteomics.
Here,
we
present
parallel-flow
projection
transfer
learning
omics
data
(PLATO),
an
integrated
framework
combining
microfluidics
with
deep
to
enable
of
thousands
proteins
whole
tissue
sections.
We
validated
the
PLATO
by
profiling
proteome
mouse
cerebellum,
identifying
2,564
groups
single
run.
then
applied
rat
villus
human
breast
cancer
samples,
resolution
25
μm
uncovering
proteomic
dynamics
associated
disease
states.
This
approach
revealed
spatially
distinct
tumor
subtypes,
identified
key
dysregulated
proteins,
provided
novel
insights
into
complexity
microenvironment.
believe
that
represents
transformative
platform
for
exploring
regulation
its
interplay
genetic
environmental
factors.
