AJP Cell Physiology,
Journal Year:
2021,
Volume and Issue:
321(2), P. C343 - C354
Published: June 30, 2021
Breast
cancer
is
the
quintessential
example
of
how
molecular
characterization
tumor
biology
guides
therapeutic
decisions.
From
discovery
estrogen
receptor
to
current
clinical
profiles
evolving
single-cell
analytics,
and
compartmentalization
breast
into
divergent
subtypes
clear.
However,
competing
with
this
model
recognition
intratumoral
heterogeneity,
which
acknowledges
possibility
that
multiple
different
exist
within
a
single
tumor.
Intratumoral
heterogeneity
driven
by
both
intrinsic
effects
cells
themselves
as
well
extrinsic
from
surrounding
microenvironment.
There
emerging
evidence
these
are
not
static;
rather,
plasticity
between
possible.
Interconversion
seemingly
drives
progression,
metastases,
treatment
resistance.
Therapeutic
strategies
must,
therefore,
contend
changing
phenotypes
in
an
individual
patient's
Identifying
targetable
drivers
may
improve
durability
disease
progression.
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.
The EMBO Journal,
Journal Year:
2021,
Volume and Issue:
40(11)
Published: May 5, 2021
To
examine
global
changes
in
breast
heterogeneity
across
different
states,
we
determined
the
single-cell
transcriptomes
of
>
340,000
cells
encompassing
normal
breast,
preneoplastic
BRCA1
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Dec. 19, 2023
Single-cell
and
spatial
technologies
that
profile
gene
expression
across
a
whole
tissue
are
revolutionizing
the
resolution
of
molecular
states
in
clinical
samples.
Current
commercially
available
provide
transcriptome
single-cell,
spatial,
or
targeted
situ
analysis.
Here,
we
combine
these
to
explore
heterogeneity
large,
FFPE
human
breast
cancer
sections.
This
integrative
approach
allowed
us
differences
exist
between
distinct
tumor
regions
identify
biomarkers
involved
progression
towards
invasive
carcinoma.
Further,
study
cell
neighborhoods
rare
boundary
cells
sit
at
critical
myoepithelial
border
confining
spread
malignant
cells.
demonstrate
each
technology
alone
provides
information
about
signatures
relevant
understanding
heterogeneity;
however,
it
is
integration
leads
deeper
insights,
ushering
discoveries
will
progress
oncology
research
development
diagnostics
therapeutics.
Genome Medicine,
Journal Year:
2024,
Volume and Issue:
16(1)
Published: Jan. 12, 2024
Abstract
Optimal
integration
of
transcriptomics
data
and
associated
spatial
information
is
essential
towards
fully
exploiting
to
dissect
tissue
heterogeneity
map
out
inter-cellular
communications.
We
present
SEDR,
which
uses
a
deep
autoencoder
coupled
with
masked
self-supervised
learning
mechanism
construct
low-dimensional
latent
representation
gene
expression,
then
simultaneously
embedded
the
corresponding
through
variational
graph
autoencoder.
SEDR
achieved
higher
clustering
performance
on
manually
annotated
10
×
Visium
datasets
better
scalability
high-resolution
than
existing
methods.
Additionally,
we
show
SEDR’s
ability
impute
denoise
expression
(URL:
https://github.com/JinmiaoChenLab/SEDR/
).
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2022,
Volume and Issue:
unknown
Published: Oct. 7, 2022
Abstract
Single
cell
and
spatial
technologies
that
profile
gene
expression
across
a
whole
tissue
are
revolutionizing
the
resolution
of
molecular
states
in
clinical
samples.
Commercially
available
methods
characterize
either
single
or
currently
limited
by
low
sample
throughput
and/or
plexy,
lack
on-instrument
analysis,
destruction
histological
features
epitopes
during
workflow.
Here,
we
analyzed
large,
serial
formalin-fixed,
paraffin-embedded
(FFPE)
human
breast
cancer
sections
using
novel
FFPE-compatible
workflow
(Chromium
Fixed
RNA
Profiling;
scFFPE-seq),
transcriptomics
(Visium
CytAssist),
automated
microscopy-based
situ
technology
313-plex
panel
(Xenium
In
Situ).
Whole
transcriptome
profiling
FFPE
scFFPE-seq
Visium
facilitated
identification
17
different
types.
Xenium
allowed
us
to
spatially
resolve
these
types
their
profiles
with
resolution.
Due
non-destructive
nature
workflow,
were
able
perform
H&E
staining
immunofluorescence
on
same
section
post-processing
which
register
protein,
histological,
data
together
into
image.
Integration
from
Chromium
scFFPE-seq,
Visium,
do
extensive
benchmarking
sensitivity
specificity
between
technologies.
Furthermore,
integration
inspired
interrogation
three
molecularly
distinct
tumor
subtypes
(low-grade
high-grade
ductal
carcinoma
(DCIS),
invasive
carcinoma).
We
used
cellular
composition
differentially
expressed
genes
within
subtypes.
This
analysis
draw
biological
insights
about
DCIS
progression
infiltrating
carcinoma,
as
myoepithelial
layer
degrades
cells
invade
surrounding
stroma.
also
further
predict
hormone
receptor
status
subtypes,
including
small
0.1
mm
2
region
was
triple
positive
for
ESR1
(estrogen
receptor),
PGR
(progesterone
ERBB2
(human
epidermal
growth
factor
2,
a.k.a.
HER2)
RNA.
order
derive
information
cells,
interpolate
spots,
discover
new
biomarkers
demonstrate
independently
provide
signatures
relevant
understanding
heterogeneity.
However,
it
is
leads
even
deeper
insights,
ushering
discoveries
will
progress
oncology
research
development
diagnostics
therapeutics.
