npj Precision Oncology,
Journal Year:
2025,
Volume and Issue:
9(1)
Published: March 11, 2025
The
tumor
microenvironment
(TME)
plays
a
crucial
role
in
orchestrating
cell
behavior
and
cancer
progression.
Recent
advances
spatial
profiling
technologies
have
uncovered
novel
signatures,
including
univariate
distribution
patterns,
bivariate
relationships,
higher-order
structures.
These
signatures
the
potential
to
revolutionize
mechanism
treatment.
In
this
review,
we
summarize
current
state
of
signature
research,
highlighting
computational
methods
uncover
spatially
relevant
biological
significance.
We
discuss
impact
these
on
fundamental
biology
translational
address
challenges
future
research
directions.
Nature Methods,
Journal Year:
2024,
Volume and Issue:
unknown
Published: March 20, 2024
Abstract
Spatially
resolved
omics
technologies
are
transforming
our
understanding
of
biological
tissues.
However,
the
handling
uni-
and
multimodal
spatial
datasets
remains
a
challenge
owing
to
large
data
volumes,
heterogeneity
types
lack
flexible,
spatially
aware
structures.
Here
we
introduce
SpatialData,
framework
that
establishes
unified
extensible
multiplatform
file-format,
lazy
representation
larger-than-memory
data,
transformations
alignment
common
coordinate
systems.
SpatialData
facilitates
annotations
cross-modal
aggregation
analysis,
utility
which
is
illustrated
in
context
multiple
vignettes,
including
integrative
analysis
on
Xenium
Visium
breast
cancer
study.
Lab on a Chip,
Journal Year:
2024,
Volume and Issue:
24(5), P. 1307 - 1326
Published: Jan. 1, 2024
This
review
outlines
the
current
advances
of
high-throughput
microfluidic
systems
accelerated
by
AI.
Furthermore,
challenges
and
opportunities
in
this
field
are
critically
discussed
as
well.
Analytical and Bioanalytical Chemistry,
Journal Year:
2023,
Volume and Issue:
415(28), P. 7011 - 7024
Published: Oct. 16, 2023
Abstract
The
integration
of
matrix-assisted
laser
desorption/ionization
mass
spectrometry
imaging
(MALDI-MSI)
with
single
cell
spatial
omics
methods
allows
for
a
comprehensive
investigation
information
and
matrisomal
N-glycan
extracellular
matrix
protein
imaging.
Here,
the
performance
antibody-directed
workflows
coupled
MALDI-MSI
are
evaluated.
Miralys™
photocleavable
mass-tagged
antibody
probes
(MALDI-IHC,
AmberGen,
Inc.),
GeoMx
DSP®
(NanoString,
Imaging
Mass
Cytometry
(IMC,
Standard
BioTools
Inc.)
were
used
in
series
N-glycans
peptides
on
formalin-fixed
paraffin-embedded
tissues.
Single
protocols
performed
before
after
MALDI-MSI.
data
suggests
that
each
modality
combination,
there
is
an
optimal
order
performing
both
techniques
same
tissue
section.
An
overall
conclusion
studies
may
be
completed
section
as
modalities.
This
work
increases
access
to
combined
cellular
within
microenvironment
enhance
research
pathological
origins
disease.
Graphical
Briefings in Bioinformatics,
Journal Year:
2024,
Volume and Issue:
25(2)
Published: Jan. 22, 2024
Abstract
Spatially
resolved
transcriptomics
(SRT)
is
a
pioneering
method
for
simultaneously
studying
morphological
contexts
and
gene
expression
at
single-cell
precision.
Data
emerging
from
SRT
are
multifaceted,
presenting
researchers
with
intricate
matrices,
precise
spatial
details
comprehensive
histology
visuals.
Such
rich
datasets,
unfortunately,
render
many
conventional
methods
like
traditional
machine
learning
statistical
models
ineffective.
The
unique
challenges
posed
by
the
specialized
nature
of
data
have
led
scientific
community
to
explore
more
sophisticated
analytical
avenues.
Recent
trends
indicate
an
increasing
reliance
on
deep
algorithms,
especially
in
areas
such
as
clustering,
identification
spatially
variable
genes
alignment
tasks.
In
this
manuscript,
we
provide
rigorous
critique
these
advanced
methodologies,
probing
into
their
merits,
limitations
avenues
further
refinement.
Our
in-depth
analysis
underscores
that
while
recent
innovations
tailored
been
promising,
there
remains
substantial
potential
enhancement.
A
crucial
area
demands
attention
development
can
incorporate
biological
nuances,
phylogeny-aware
processing
or
minuscule
image
segments.
Furthermore,
addressing
elimination
batch
effects,
perfecting
normalization
techniques
countering
overdispersion
zero
inflation
patterns
seen
pivotal.
To
support
broader
endeavors,
meticulously
assembled
directory
readily
accessible
databases,
hoping
serve
foundation
future
research
initiatives.
Journal of Hematology & Oncology,
Journal Year:
2024,
Volume and Issue:
17(1)
Published: Aug. 24, 2024
The
emergence
of
spatial
multi-omics
has
helped
address
the
limitations
single-cell
sequencing,
which
often
leads
to
loss
context
among
cell
populations.
Integrated
analysis
genome,
transcriptome,
proteome,
metabolome,
and
epigenome
enhanced
our
understanding
biology
molecular
basis
human
diseases.
Moreover,
this
approach
offers
profound
insights
into
interactions
between
intracellular
intercellular
mechanisms
involved
in
development,
physiology,
pathogenesis
In
comprehensive
review,
we
examine
current
advancements
technologies,
focusing
on
their
evolution
refinement
over
past
decade,
including
improvements
throughput
resolution,
modality
integration,
accuracy.
We
also
discuss
pivotal
contributions
revealing
heterogeneity,
constructing
detailed
atlases,
deciphering
crosstalk
tumor
immunology,
advancing
translational
research
cancer
therapy
through
precise
mapping.
Nature Communications,
Journal Year:
2025,
Volume and Issue:
16(1)
Published: Feb. 1, 2025
Technical
limitations
in
spatial
and
single-cell
omics
sequencing
pose
challenges
for
capturing
describing
multimodal
information
at
the
scale.
To
address
this,
we
develop
SIMO,
a
computational
method
designed
Spatial
Integration
of
Multi-Omics
datasets
through
probabilistic
alignment.
Unlike
previous
tools,
SIMO
not
only
integrates
transcriptomics
with
RNA-seq
but
expands
beyond,
enabling
integration
across
multiple
modalities,
such
as
chromatin
accessibility
DNA
methylation,
which
have
been
co-profiled
spatially
before.
We
benchmark
on
simulated
datasets,
demonstrating
its
high
accuracy
robustness.
Further
application
biological
reveals
SIMO's
ability
to
detect
topological
patterns
cells
their
regulatory
modes
layers.
Through
comprehensive
analysis
real-world
data,
uncovers
heterogeneity,
offering
deeper
insights
into
organization
regulation
molecules.
These
findings
position
powerful
tool
advancing
biology
by
revealing
previously
inaccessible
insights.
Military Medical Research,
Journal Year:
2023,
Volume and Issue:
10(1)
Published: Aug. 17, 2023
Abstract
The
respiratory
system’s
complex
cellular
heterogeneity
presents
unique
challenges
to
researchers
in
this
field.
Although
bulk
RNA
sequencing
and
single-cell
(scRNA-seq)
have
provided
insights
into
cell
types
the
system,
relevant
specific
spatial
localization
interactions
not
been
clearly
elucidated.
Spatial
transcriptomics
(ST)
has
filled
gap
widely
used
studies.
This
review
focuses
on
latest
iterative
technology
of
ST
recent
years,
summarizing
how
can
be
applied
physiological
pathological
processes
with
emphasis
lungs.
Finally,
current
potential
development
directions
are
proposed,
including
high-throughput
full-length
transcriptome,
integration
multi-omics,
temporal
omics,
bioinformatics
analysis,
etc.
These
viewpoints
expected
advance
study
systematic
mechanisms,
