Aging and Disease,
Journal Year:
2024,
Volume and Issue:
unknown, P. 0 - 0
Published: Jan. 1, 2024
Angina
pectoris
(AP),
a
clinical
syndrome
characterized
by
paroxysmal
chest
pain,
is
caused
insufficient
blood
supply
to
the
coronary
arteries
and
sudden
temporary
myocardial
ischemia
hypoxia.
Long-term
AP
typically
induces
other
cardiovascular
events,
including
infarction
heart
failure,
posing
serious
threat
patient
safety.
However,
AP's
complex
pathological
mechanisms
developmental
processes
introduce
significant
challenges
in
rapid
diagnosis
accurate
treatment
of
its
different
subtypes,
stable
angina
(SAP),
unstable
(UAP),
variant
(VAP).
Omics
research
has
contributed
significantly
revealing
various
diseases
with
development
high-throughput
sequencing
approaches.
The
application
multi-omics
approaches
effectively
interprets
systematic
information
on
from
perspective
genes,
RNAs,
proteins,
metabolites.
Integrating
introduces
novel
avenues
for
identifying
biomarkers
distinguish
subtypes.
This
study
reviewed
articles
related
elaborate
progress
(including
genomics,
transcriptomics,
proteomics,
metabolomics),
summarized
their
applications
screening
employed
discriminate
multiple
delineated
integration
methods
Finally,
we
discussed
advantages
disadvantages
applying
single-omics
approach
distinguishing
diverse
Our
review
demonstrated
that
technologies
preferable
quick
precise
three
types,
namely
SAP,
UAP,
VAP.
Journal of Hematology & Oncology,
Journal Year:
2023,
Volume and Issue:
16(1)
Published: Nov. 27, 2023
Research
into
the
potential
benefits
of
artificial
intelligence
for
comprehending
intricate
biology
cancer
has
grown
as
a
result
widespread
use
deep
learning
and
machine
in
healthcare
sector
availability
highly
specialized
datasets.
Here,
we
review
new
approaches
how
they
are
being
used
oncology.
We
describe
might
be
detection,
prognosis,
administration
treatments
introduce
latest
large
language
models
such
ChatGPT
oncology
clinics.
highlight
applications
omics
data
types,
offer
perspectives
on
various
types
combined
to
create
decision-support
tools.
also
evaluate
present
constraints
challenges
applying
precision
Finally,
discuss
current
may
surmounted
make
useful
clinical
settings
future.
BMC Microbiology,
Journal Year:
2024,
Volume and Issue:
24(1)
Published: Jan. 5, 2024
Abstract
Studying
the
effects
of
microbiome
on
development
different
types
cancer
has
recently
received
increasing
research
attention.
In
this
context,
microbial
content
organs
gastrointestinal
tract
been
proposed
to
play
a
potential
role
in
pancreatic
(PC).
Proposed
mechanisms
for
pathogenesis
PC
include
persistent
inflammation
caused
by
microbiota
leading
an
impairment
antitumor
immune
surveillance
and
altered
cellular
processes
tumor
microenvironment.
The
limited
available
diagnostic
markers
that
can
currently
be
used
screening
suggest
importance
composition
as
non-invasive
biomarker
clinical
settings.
Samples
including
saliva,
stool,
blood
analyzed
16
s
rRNA
sequencing
determine
relative
abundance
specific
bacteria.
Studies
have
shown
potentially
beneficial
prebiotics,
probiotics,
antibiotics,
fecal
transplantation,
bacteriophage
therapy
altering
diversity,
subsequently
improving
treatment
outcomes.
review,
we
summarize
impact
PC,
these
microorganisms
might
biomarkers
diagnosis
determining
prognosis
patients.
We
also
discuss
novel
methods
being
minimize
or
prevent
progression
dysbiosis
modulating
composition.
Emerging
evidence
is
supportive
applying
findings
improve
current
therapeutic
strategies
employed
PC.
ACS Pharmacology & Translational Science,
Journal Year:
2024,
Volume and Issue:
7(4), P. 967 - 990
Published: March 19, 2024
Precision
medicine
is
transforming
colorectal
cancer
treatment
through
the
integration
of
advanced
technologies
and
biomarkers,
enhancing
personalized
effective
disease
management.
Identification
key
driver
mutations
molecular
profiling
have
deepened
our
comprehension
genetic
alterations
in
cancer,
facilitating
targeted
therapy
immunotherapy
selection.
Biomarkers
such
as
microsatellite
instability
(MSI)
DNA
mismatch
repair
deficiency
(dMMR)
guide
decisions,
opening
avenues
for
immunotherapy.
Emerging
liquid
biopsies,
artificial
intelligence,
machine
learning
promise
to
revolutionize
early
detection,
monitoring,
selection
precision
medicine.
Despite
these
advancements,
ethical
regulatory
challenges,
including
equitable
access
data
privacy,
emphasize
importance
responsible
implementation.
The
dynamic
nature
with
its
tumor
heterogeneity
clonal
evolution,
underscores
necessity
adaptive
strategies.
future
lies
potential
enhance
patient
care,
clinical
outcomes,
understanding
this
intricate
disease,
marked
by
ongoing
evolution
field.
current
reviews
focus
on
providing
in-depth
knowledge
various
diverse
approaches
utilized
against
at
both
biochemical
levels.
Pharmacia,
Journal Year:
2025,
Volume and Issue:
72, P. 1 - 13
Published: Jan. 13, 2025
Colorectal
cancer
(CRC)
is
the
third
most
prevalent
tumor
in
men,
second
common
women,
and
fourth
leading
cause
of
mortality
worldwide.
Statins
reduce
cholesterol
levels
by
hampering
function
3-hydroxy-3-methyl-glutaryl-CoA
reductase
enzymes
synthesis.
Strains
have
shown
anticancer
effects
against
CRC.
However,
statins’
mechanism
yet
unknown.
Liquid
chromatography–mass
spectrometry
(LC–MS)-based
untargeted
metabolomics
proteomics
were
employed
to
study
on
CRC
using
cell
line
HCT-116.
These
approaches
utilized
identify
potential
underlying
metabolic
pathways
proteins
altered
atorvastatin
(a
statin)-treated
HCT-116
cells.
Compared
control,
significantly
numerous
metabolites
cells,
including
a
reduction
decanoylcarnitine
octanoyl-L-carnitine
biosynthesis
metabolism
amino
acids
like
alanine
citrate
cycle.
Proteomic
showed
that
atorvastatin-treated
cells
expressed
127
differently
from
controls.
Novel
findings
among
them,
such
as
centromere-associated
protein
E,
cytochrome
c
oxidase
subunit
6A1
mitochondrial,
hyaluronan
synthase
1.
The
indicate
may
characteristics
highlight
essential
role
understand
complex
relevant
develop
novel
treatment
targets.
International Journal of Molecular Sciences,
Journal Year:
2025,
Volume and Issue:
26(4), P. 1648 - 1648
Published: Feb. 14, 2025
Colorectal
cancer
(CRC)
is
a
leading
cause
of
cancer-related
deaths
worldwide,
characterized
by
high
incidence
and
poor
survival
rates.
Glycosylation,
fundamental
post-translational
modification,
influences
protein
stability,
signaling,
tumor
progression,
with
aberrations
implicated
in
immune
evasion
metastasis.
This
study
investigates
the
role
glycosylation-related
genes
(Glycosylation-RGs)
CRC
using
machine
learning
bioinformatics.
Data
from
The
Cancer
Genome
Atlas
(TCGA)
Molecular
Signatures
Database
(MSigDB)
were
analyzed
to
identify
67
differentially
expressed
Glycosylation-RGs.
These
used
classify
patients
into
two
subgroups
distinct
outcomes,
highlighting
their
prognostic
value.
Weighted
gene
coexpression
network
analysis
(WGCNA)
revealed
key
modules
associated
traits,
including
pathways
like
glycan
biosynthesis
PI3K-Akt
signaling.
A
machine-learning-based
model
demonstrated
strong
predictive
performance,
stratifying
high-
low-risk
groups
significant
differences.
Additionally,
correlations
between
risk
scores
cell
infiltration,
providing
insights
microenvironment.
Drug
sensitivity
identified
potential
therapeutic
agents,
Trametinib,
SCH772984,
Oxaliplatin,
showing
differential
efficacy
groups.
findings
enhance
our
understanding
glycosylation
CRC,
identifying
it
as
critical
factor
disease
progression
promising
target
for
future
strategies.
