Points to Consider From the ESTP Pathology 2.0 Working Group: Overview on Spatial Omics Technologies Supporting Drug Discovery and Development
Toxicologic Pathology,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 10, 2025
Recent
advances
in
bioanalytical
and
imaging
technologies
have
revolutionized
our
ability
to
assess
complex
biological
pathological
changes
within
tissue
samples.
Spatial
omics,
a
rapidly
evolving
technology,
enables
the
simultaneous
detection
of
multiple
biomolecules
sections,
allowing
for
high-dimensional
molecular
profiling
microanatomical
contexts.
This
offers
powerful
opportunity
precise,
multidimensional
exploration
disease
pathophysiology.
The
Pathology
2.0
working
group
European
Society
Toxicologic
(ESTP)
includes
subgroup
dedicated
spatial
omics
technologies.
Their
primary
goal
is
raise
awareness
about
these
emerging
their
potential
applications
discovery
toxicologic
pathology.
review
provides
an
overview
commonly
used,
commercially
available
platforms
transcriptomic,
proteomic,
multiomic
analysis,
discussing
technical
aspects
illustrative
examples
applications.
To
harness
power
translational
drug
human
safety
risk
assessment,
we
emphasize
important
role
pathologists
at
every
stage
workflow—from
hypothesis
generation
sample
preparation,
data
interpretation.
offer
novel
opportunities
target
discovery,
lead
selection,
preclinical
clinical
development
compound
development.
Язык: Английский
Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystem
Jiaji George Chen,
Joselyn Cristina Chávez-Fuentes,
Matthew O’Brien
и другие.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Ноя. 27, 2023
Emerging
spatial
omics
technologies
continue
to
advance
the
molecular
mapping
of
tissue
architecture
and
investigation
gene
regulation
cellular
crosstalk,
which
in
turn
provide
new
mechanistic
insights
into
a
wide
range
biological
processes
diseases.
Such
an
increasingly
large
amount
information
content
at
multiple
scales.
However,
representing
harmonizing
diverse
datasets
efficiently,
including
combining
modalities
or
scales
scalable
flexible
manner,
remains
substantial
challenge.
Here,
we
present
Giotto
Suite,
suite
open-source
software
packages
that
underlies
fully
modular
integrated
data
analysis
toolbox.
At
its
core,
Suite
is
centered
around
innovative
technology-agnostic
framework
embedded
R
environment,
allows
representation
integration
virtually
any
type
resolution.
In
addition,
provides
both
extensible
end-to-end
solutions
for
analysis,
integration,
visualization.
integrates
molecular,
morphology,
spatial,
annotated
feature
create
responsive
workflow
multi-scale,
multi-omic
analyses,
as
demonstrated
here
by
applications
several
state-of-the-art
technologies.
Furthermore,
builds
upon
interoperable
interfaces
structures
bridge
established
fields
genomics
science,
thereby
enabling
independent
developers
custom-engineered
pipelines.
As
such,
creates
immersive
ecosystem
analysis.
Язык: Английский
Bering:joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Сен. 22, 2023
Single-cell
spatial
transcriptomics
such
as
Язык: Английский
Spatial motifs reveal patterns in cellular architecture of complex tissues
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 11, 2024
Abstract
Spatial
organization
of
cells
is
crucial
to
both
proper
physiological
function
tissues
and
pathological
conditions
like
cancer.
Recent
advances
in
spatial
transcriptomics
have
enabled
joint
profiling
gene
expression
context
the
cells.
The
outcome
an
information
rich
map
tissue
where
individual
cells,
or
small
regions,
can
be
labeled
based
on
their
state.
While
excels
its
capacity
profile
numerous
genes
within
same
sample,
most
existing
methods
for
analysis
data
only
examine
distribution
one
two
labels
at
a
time.
These
approaches
overlook
potential
identifying
higher-order
associations
between
cell
types
–
that
play
pivotal
role
understanding
development
complex
tissues.
In
this
context,
we
introduce
novel
method
detecting
motifs
neighborhood
graphs.
Each
motif
represents
arrangement
occurs
more
frequently
than
expected
by
chance.
To
identify
motifs,
developed
algorithm
uniform
sampling
paths
from
graphs
combined
it
with
finding
inspired
previous
DNA
sequences.
Using
synthetic
known
ground
truth,
show
our
high
accuracy
sensitivity.
Applied
maps
mouse
retinal
bipolar
hypothalamic
preoptic
region,
reveals
previously
unrecognized
patterns
type
arrangements.
some
cases,
these
differ
other
type,
providing
insights
into
functional
significance
motifs.
results
suggest
illuminate
substantial
complexity
neural
tissues,
provide
insight
even
well
studied
models,
generate
experimentally
testable
hypotheses.
Язык: Английский
A computational pipeline for spatial mechano-transcriptomics
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Авг. 5, 2023
Abstract
Advances
in
spatial
profiling
technologies
are
providing
insights
into
how
molecular
programs
influenced
by
local
signaling
and
environmental
cues.
However,
cell
fate
specification
tissue
patterning
involve
the
interplay
of
biochemical
mechanical
feedback.
Here,
we
develop
a
computational
framework
that
enables
joint
statistical
analysis
transcriptional
signals
context
transcriptomics.
To
illustrate
application
utility
approach,
use
transcriptomics
data
from
developing
mouse
embryo
to
infer
forces
acting
on
individual
cells,
these
results
identify
mechanical,
morphometric,
gene
expression
signatures
predictive
compartment
boundaries.
In
addition,
geoadditive
structural
equation
modeling
modules
predict
behavior
cells
an
unbiased
manner.
This
is
easily
generalized
other
contexts,
generic
scheme
for
exploring
biomolecular
cues
tissues.
Язык: Английский