Cystic Fluid Total Proteins, Low-Density Lipoprotein Cholesterol, Lipid Metabolites, and Lymphocytes: Worrisome Biomarkers for Intraductal Papillary Mucinous Neoplasms
Cancers,
Год журнала:
2025,
Номер
17(4), С. 643 - 643
Опубликована: Фев. 14, 2025
Objectives:
Pancreatic
cystic
neoplasms
(PCNs),
particularly
intraductal
papillary
mucinous
(IPMNs),
present
a
challenge
for
their
potential
malignancy.
Despite
promising
biomarkers
like
CEA,
amylase,
and
glucose,
our
study
investigates
whether
metabolic
indices
in
blood
fluids
(CFs),
addition
to
lymphocyte
subsets
hematopoietic
stem/progenitor
cells
(HSPCs),
can
effectively
differentiate
between
high-
low-risk
PCNs.
Materials
Methods:
A
total
of
26
patients
(11
males,
mean
age
69.5
±
9
years)
undergoing
Endoscopic
Ultrasound-guided
Fine
Needle
Aspiration
were
consecutively
enrolled.
Analyses
included
blood,
serum,
CF,
assessing
cholesterol
(total,
HDL,
LDL),
proteins.
Flow
cytometry
examined
immunophenotyping
peripheral
fluids.
Mass
spectrometry
was
used
the
metabolomic
analysis
CF.
Sensitivity,
specificity,
ROC
analyses
evaluated
discriminatory
power.
Results:
25
out
had
IPMN.
Patients
categorized
as
low
or
high
risk
based
on
multidisciplinary
evaluation
clinical,
radiological,
endoscopic
data.
High-risk
showed
lower
CF
proteins
LDL
(p
=
0.005
p
0.031),
with
marked
reduction
lymphocytes
0.005).
HSCPs
absent
In
high-risk
increased
non-MHC-restricted
cytotoxic
T
0.019).
The
revealed
significantly
reduced
middle
long-chain
acyl
carnitines
(AcCa)
tryptophan
metabolites
patients.
curves
indicated
comparable
discriminant
abilities
(AUC
0.868),
0.859),
0.795).
highest
performance
achieved
by
AcCa
14:2
16:0
(AUC:
0.9221
0.8857,
respectively).
Conclusions:
levels
cholesterol,
together
counts
are
easy
translational
that
may
support
stratification
PCNs
IPMN
might
be
endorsed
analysis.
Further
studies
required
clinical
integration.
Язык: Английский
Integrating omics data and machine learning techniques for precision detection of oral squamous cell carcinoma: evaluating single biomarkers
Frontiers in Immunology,
Год журнала:
2024,
Номер
15
Опубликована: Дек. 3, 2024
Early
detection
of
oral
squamous
cell
carcinoma
(OSCC)
is
critical
for
improving
clinical
outcomes.
Precision
diagnostics
integrating
metabolomics
and
machine
learning
offer
promising
non-invasive
solutions
identifying
tumor-derived
biomarkers.
Язык: Английский
Transcriptomic and metabolomic analyses reveal the spatial role of carnitine metabolism in the progression of hepatitis B virus cirrhosis to hepatocellular carcinoma
Frontiers in Microbiology,
Год журнала:
2024,
Номер
15
Опубликована: Дек. 13, 2024
Introduction
Liver
cirrhosis
(LC)
and
hepatocellular
carcinoma
(HCC)
resulting
from
chronic
hepatitis
B
virus
(HBV)
infection
are
major
health
concerns.
Identifying
critical
biomarkers
molecular
targets
is
needed
for
early
diagnosis,
prognosis,
therapy
of
these
diseases.
Methods
In
this
study,
we
explored
the
gene
expression
metabolism
in
liver
tissues
LC,
HCC,
healthy
controls,
to
analyse
identify
potential
disease
progression.
Mass
spectrometry
imaging
was
used
evaluate
spatial
distribution
key
metabolites.
Results
discussion
The
results
revealed
significant
changes
metabolic
pathways
along
with
upregulated
genes
were
associated
extracellular
matrix
remodeling
cancer
pathways,
including
LAMC1-3,
COL9A2,
COL1A1,
MYL9,
MYH11,
KAT2A.
downregulated
linked
immune
response
fatty
acid
metabolism.
Metabolomic
analysis
showed
lipid
choline
Consistent
specific
metabolites
correlated
clinical
data.
Notably,
such
as
L-acetylcarnitine,
histamine,
4-trimethylammoniobutanoic
demonstrated
high
accuracy
(AUC
>
0.85)
distinguishing
between
healthy,
HCC
groups.
This
study
identifies
metabolite
HBV
related
LC
highlighting
involved
Biomarkers
like
L-acetylcarnitine
KAT2A
show
promise
diagnosis
potentially
improving
outcomes
patients.
Язык: Английский