Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses
Frontiers in Immunology,
Год журнала:
2024,
Номер
15
Опубликована: Фев. 28, 2024
Background
Cervical
carcinoma
(CC)
represents
a
prevalent
gynecological
neoplasm,
with
discernible
rise
in
prevalence
among
younger
cohorts
observed
recent
years.
Nonetheless,
the
intrinsic
cellular
heterogeneity
of
CC
remains
inadequately
investigated.
Methods
We
utilized
single-cell
RNA
sequencing
(scRNA-seq)
transcriptomic
analysis
to
scrutinize
tumor
epithelial
cells
derived
from
four
specimens
cervical
patients.
This
method
enabled
identification
pivotal
subpopulations
and
elucidation
their
contributions
progression.
Subsequently,
we
assessed
influence
associated
molecules
bulk
(Bulk
RNA-seq)
performed
experiments
for
validation
purposes.
Results
Through
our
analysis,
have
discerned
C3
PLP2+
Tumor
Epithelial
Progenitor
Cells
as
noteworthy
subpopulation
(CC),
exerting
on
differentiation
progression
CC.
established
an
independent
prognostic
indicator—the
EPCs
score.
By
stratifying
patients
into
high
low
score
groups
based
median
score,
that
high-score
group
exhibits
diminished
survival
rates
compared
low-score
group.
The
correlations
between
these
immune
infiltration,
enriched
pathways,
single-nucleotide
polymorphisms
(SNPs),
drug
sensitivity,
other
factors,
further
underscore
impact
prognosis.
Cellular
validated
significant
ATF6
proliferation
migration
cell
lines.
Conclusion
study
enriches
comprehension
determinants
shaping
CC,
elevates
cognizance
microenvironment
offers
valuable
insights
prospective
therapies.
These
discoveries
contribute
refinement
diagnostics
formulation
optimal
therapeutic
approaches.
Язык: Английский
Comprehensive pan-cancer analysis reveals EPHB2 is a novel predictive biomarker for prognosis and immunotherapy response
BMC Cancer,
Год журнала:
2024,
Номер
24(1)
Опубликована: Авг. 28, 2024
Recent
studies
have
increasingly
linked
Ephrin
receptor
B2
(EPHB2)
to
cancer
progression.
However,
comprehensive
investigations
into
the
immunological
roles
and
prognostic
significance
of
EPHB2
across
various
cancers
remain
lacking.
Язык: Английский
Unraveling the role of ADAMs in clinical heterogeneity and the immune microenvironment of hepatocellular carcinoma: insights from single-cell, spatial transcriptomics, and bulk RNA sequencing
Frontiers in Immunology,
Год журнала:
2024,
Номер
15
Опубликована: Сен. 13, 2024
Hepatocellular
carcinoma
(HCC)
is
a
prevalent
and
heterogeneous
tumor
with
limited
treatment
options
unfavorable
prognosis.
The
crucial
role
of
disintegrin
metalloprotease
(ADAM)
gene
family
in
the
microenvironment
HCC
remains
unclear.
Язык: Английский
Characterization of NOD-like receptor-based molecular heterogeneity in glioma and its association with immune micro-environment and metabolism reprogramming
Frontiers in Immunology,
Год журнала:
2025,
Номер
15
Опубликована: Янв. 15, 2025
The
characteristics
and
role
of
NOD-like
receptor
(NLR)
signaling
pathway
in
high-grade
gliomas
were
still
unclear.
This
study
aimed
to
reveal
the
association
NLR
with
clinical
heterogeneity
glioblastoma
(GBM)
patients,
explore
hub
genes
occurrence
development
GBM.
Transcriptomic
data
from
496
GBM
patients
complete
prognostic
information
obtained
TCGA,
GEO,
CGGA
databases.
Using
NMF
clustering
algorithm
expression
profiles
genes,
these
classified
into
different
subtypes.
activity
immune
micro-environment
then
compared
between
A
novel
accurate
profile-based
marker
for
was
developed
using
LASSO
COX
regression
analysis.
Based
on
gene
profile,
accurately
divided
two
subtypes
(C1
C2)
outcomes.
groups
showed
microenvironment
metabolic
characteristics,
which
might
be
potential
reason
difference
prognosis.
Differential
enrichment
analyzes
revealed
intrinsic
signature
differences
C1
C2
differential
C2,
molecular
markers
related
developed.
AUC
value
3-year
ROC
curve
ranged
0.601
0.846,
suggesting
its
significance.
Single-cell
sequencing
analysis
that
mainly
active
myeloid
cells
within
random
forest
identified
crucial
TRIP6
pathway.
Molecular
biology
experiments
confirmed
abnormally
overexpressed
Knockdown
can
significantly
inhibit
proliferation
migration
ability
cells.
plays
a
critical
regulating
metabolism
reprogramming
is
affects
malignant
biological
behavior
Язык: Английский
Anoikis resistance regulates immune infiltration and drug sensitivity in clear-cell renal cell carcinoma: insights from multi omics, single cell analysis and in vitro experiment
Frontiers in Immunology,
Год журнала:
2024,
Номер
15
Опубликована: Июнь 17, 2024
Background
Anoikis
is
a
form
of
programmed
cell
death
essential
for
preventing
cancer
metastasis.
In
some
solid
cancer,
anoikis
resistance
can
facilitate
tumor
progression.
However,
this
phenomenon
underexplored
in
clear-cell
renal
carcinoma
(ccRCC).
Methods
Using
SVM
machine
learning,
we
identified
core
anoikis-related
genes
(ARGs)
from
ccRCC
patient
transcriptomic
data.
A
LASSO
Cox
regression
model
stratified
patients
into
risk
groups,
informing
prognostic
model.
GSVA
and
ssGSEA
assessed
immune
infiltration,
single-cell
analysis
examined
ARG
expression
across
cells.
Quantitative
PCR
immunohistochemistry
validated
differences
between
therapy
responders
non-responders
ccRCC.
Results
ARGs
such
as
CCND1,
CDKN3,
PLK1,
BID
were
key
predicting
outcomes,
linking
higher
with
increased
Treg
infiltration
reduced
M1
macrophage
presence,
indicating
an
immunosuppressive
environment
facilitated
by
resistance.
Single-cell
insights
showed
enrichment
Tregs
dendritic
cells,
affecting
checkpoints.
Immunohistochemical
reveals
that
protein
markedly
elevated
tissues
responsive
to
immunotherapy.
Conclusion
This
study
establishes
novel
gene
signature
predicts
survival
immunotherapy
response
ccRCC,
suggesting
manipulating
the
through
these
could
improve
therapeutic
strategies
prognostication
Язык: Английский
Integrated single-cell sequencing, spatial transcriptome sequencing and bulk RNA sequencing highlights the molecular characteristics of parthanatos in gastric cancer
Aging,
Год журнала:
2024,
Номер
16(6), С. 5471 - 5500
Опубликована: Март 18, 2024
Background:
Parthanatos
is
a
novel
programmatic
form
of
cell
death
based
on
DNA
damage
and
PARP-1
dependency.
Nevertheless,
its
specific
role
in
the
context
gastric
cancer
(GC)
remains
uncertain.
Methods:
In
this
study,
we
integrated
multi-omics
algorithms
to
investigate
molecular
characteristics
parthanatos
GC.
A
series
bioinformatics
were
utilized
explore
clinical
heterogeneity
GC
further
predict
outcomes.
Results:
Firstly,
conducted
comprehensive
analysis
omics
features
various
human
tumors,
including
genomic
mutations,
transcriptome
expression,
prognostic
relevance.
We
successfully
identified
7
types
within
microenvironment:
myeloid
cell,
epithelial
T
stromal
proliferative
B
NK
cell.
When
compared
adjacent
non-tumor
tissues,
single-cell
sequencing
results
from
tissues
revealed
elevated
scores
for
pathway
across
multiple
types.
Spatial
transcriptomics,
first
time,
unveiled
spatial
distribution
signaling.
patients
with
different
signals
often
exhibited
distinct
immune
microenvironment
metabolic
reprogramming
features,
leading
The
integration
signaling
indicators
enabled
creation
survival
curves
that
accurately
assess
patients'
times
statuses.
Conclusions:
parthanatos'
unicellular
transcriptomics
time.
Our
model
can
be
used
distinguish
individual
outcomes
Язык: Английский
Elucidating the multifaceted role of MGAT1 in hepatocellular carcinoma: integrative single-cell and spatial transcriptomics reveal novel therapeutic insights
Frontiers in Immunology,
Год журнала:
2024,
Номер
15
Опубликована: Июль 16, 2024
Glycosyltransferase-associated
genes
play
a
crucial
role
in
hepatocellular
carcinoma
(HCC)
pathogenesis.
This
study
investigates
their
impact
on
the
tumor
microenvironment
and
molecular
mechanisms,
offering
insights
into
innovative
immunotherapeutic
strategies
for
HCC.
Язык: Английский
Glutathione metabolism-related gene signature predicts prognosis and treatment response in low-grade glioma
Aging,
Год журнала:
2024,
Номер
16(11), С. 9518 - 9546
Опубликована: Май 30, 2024
Cancer
cells
can
induce
molecular
changes
that
reshape
cellular
metabolism,
creating
specific
vulnerabilities
for
targeted
therapeutic
interventions.
Given
the
importance
of
reactive
oxygen
species
(ROS)
in
tumor
development
and
drug
resistance,
abundance
reduced
glutathione
(GSH)
as
primary
antioxidant,
we
examined
an
integrated
panel
56
metabolism-related
genes
(GMRGs)
across
diverse
cancer
types.
This
analysis
revealed
a
remarkable
association
between
GMRGs
low-grade
glioma
(LGG)
survival.
Unsupervised
clustering
GMRGs-based
risk
score
(GS)
categorized
LGG
patients
into
two
groups,
linking
elevated
metabolism
to
poorer
prognosis
treatment
outcomes.
Our
GS
model
outperformed
established
clinical
prognostic
factors,
acting
independent
factor.
also
exhibited
correlations
with
pro-tumor
M2
macrophage
infiltration,
upregulated
immunosuppressive
genes,
diminished
responses
various
therapies.
Experimental
validation
cell
lines
confirmed
critical
role
proliferation
chemoresistance.
findings
highlight
presence
unique
metabolic
susceptibility
introduce
novel
system
highly
effective
tool
predicting
LGG.
Язык: Английский
Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma
Technology in Cancer Research & Treatment,
Год журнала:
2024,
Номер
23
Опубликована: Янв. 1, 2024
Clear
cell
renal
carcinoma
(ccRCC)
is
a
highly
lethal
urinary
malignancy
with
poor
overall
survival
(OS)
rates.
Integrating
computer
vision
and
machine
learning
in
pathomics
analysis
offers
potential
for
enhancing
classification,
prognosis,
treatment
strategies
ccRCC.
This
study
aims
to
create
model
predict
OS
ccRCC
patients.
In
this
study,
data
from
patients
the
TCGA
database
were
used
as
training
set,
clinical
serving
validation
set.
Pathological
features
extracted
H&E-stained
slides
using
PyRadiomics,
was
constructed
non-negative
matrix
factorization
(NMF)
algorithm.
The
model's
predictive
performance
assessed
through
Kaplan-Meier
(KM)
curves
Cox
regression
analysis.
Additionally,
differential
gene
expression,
ontology
(GO)
enrichment
analysis,
immune
infiltration,
mutational
conducted
investigate
underlying
biological
mechanisms.
A
total
of
368
patients,
comprising
two
subtypes
(Cluster
1
Cluster
2)
successfully
NMF
KM
revealed
that
2
associated
worse
OS.
76
genes
identified
between
subtypes,
primarily
involving
extracellular
organization
structure.
Immune-related
genes,
including
CTLA4,
CD80,
TIGIT,
expressed
2,
while
VHL
PBRM1
along
mutations
PI3K-Akt,
HIF-1,
MAPK
signaling
pathways,
exhibited
mutation
rates
exceeding
40%
both
subtypes.
learning-based
effectively
predicts
differentiates
critical
roles
immune-related
CTLA4
pathways
offer
new
insights
further
research
on
molecular
mechanisms,
diagnosis,
Язык: Английский