Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer
Lingyan Xiang,
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Jiajun Yang,
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Jie Rao
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et al.
International Journal of Molecular Sciences,
Journal Year:
2025,
Volume and Issue:
26(8), P. 3682 - 3682
Published: April 13, 2025
Breast
cancer
(BRCA)
continues
to
pose
a
serious
risk
women’s
health
worldwide.
Neoadjuvant
chemotherapy
(NAC)
is
critical
treatment
strategy.
Nevertheless,
the
heterogeneity
in
outcomes
necessitates
identification
of
reliable
biomarkers
and
prognostic
models.
Programmed
cell
death
(PCD)
pathways
serve
as
factor
tumor
development
response.
However,
relationship
between
diverse
patterns
PCD
NAC
BRCA
remains
unclear.
We
integrated
machine
learning
multiple
bioinformatics
tools
explore
association
19
prognosis
within
cohort
921
patients
treated
with
from
seven
multicenter
cohorts.
A
model
based
on
PCD-related
genes
(PRGs)
was
constructed
evaluated
using
combination
117
algorithms.
Immune
infiltration
analysis,
mutation
pharmacological
single-cell
RNA
sequencing
(scRNA-seq)
were
conducted
genomic
profile
clinical
significance
these
BRCA.
Immunohistochemistry
(IHC)
employed
validate
expression
select
(UGCG,
BTG22,
TNFRSF21,
MYB)
tissues.
PRGs
by
signature
comprising
20
DEGs
forecast
patients.
The
demonstrated
excellent
predictive
accuracy,
high
concordance
index
(C-index)
0.772,
validated
across
independent
datasets.
Our
results
strong
developed
survival
prognosis,
pathological
features,
immune
infiltration,
microenvironment
(TME),
gene
mutations,
drug
sensitivity
for
Moreover,
IHC
studies
further
that
certain
tissues
significantly
associated
efficacy
emerged
an
autonomous
predictor
influencing
outcome
are
first
integrate
bulk
scRNA-seq
decode
various
mechanisms
unique
model,
PRGs,
provides
novel
comprehensive
strategy
predicting
This
not
only
aids
understanding
underlying
but
also
offers
insights
into
personalized
strategies,
potentially
improving
patient
outcomes.
Language: Английский
Identification of potential novel targets for treating inflammatory bowel disease using Mendelian randomization analysis
Ji‐Chang Fan,
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Yuan Lü,
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Jin‐Heng Gan
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et al.
International Journal of Colorectal Disease,
Journal Year:
2024,
Volume and Issue:
39(1)
Published: Oct. 16, 2024
Inflammatory
bowel
disease
(IBD)
is
a
complex
autoimmune
disorder,
although
some
medications
are
available
for
its
treatment.
However,
the
long-term
efficacy
of
these
drugs
remains
unsatisfactory.
Therefore,
there
need
to
develop
novel
drug
targets
IBD
Language: Английский