Endometrial
cancer
(EC)
presents
significant
clinical
challenges
due
to
its
heterogeneity
and
complex
pathophysiology.
SAMHD1,
known
for
role
as
a
deoxynucleotide
triphosphate
triphosphohydrolase,
has
been
implicated
in
the
progression
of
various
cancers,
including
EC.
This
study
focuses
on
elucidating
SAMHD1
EC
through
impact
TRIM27-mediated
PTEN
ubiquitination.
Nature Metabolism,
Год журнала:
2023,
Номер
5(4), С. 642 - 659
Опубликована: Апрель 3, 2023
Abstract
Cancer
cells
fuel
their
increased
need
for
nucleotide
supply
by
upregulating
one-carbon
(1C)
metabolism,
including
the
enzymes
methylenetetrahydrofolate
dehydrogenase–cyclohydrolase
1
and
2
(MTHFD1
MTHFD2).
TH9619
is
a
potent
inhibitor
of
dehydrogenase
cyclohydrolase
activities
in
both
MTHFD1
MTHFD2,
selectively
kills
cancer
cells.
Here,
we
reveal
that,
cells,
targets
nuclear
MTHFD2
but
does
not
inhibit
mitochondrial
MTHFD2.
Hence,
overflow
formate
from
mitochondria
continues
presence
TH9619.
inhibits
activity
occurring
downstream
release,
leading
to
accumulation
10-formyl-tetrahydrofolate,
which
term
‘folate
trap’.
This
results
thymidylate
depletion
death
MTHFD2-expressing
previously
uncharacterized
folate
trapping
mechanism
exacerbated
physiological
hypoxanthine
levels
that
block
de
novo
purine
synthesis
pathway,
additionally
prevent
10-formyl-tetrahydrofolate
consumption
synthesis.
The
described
here
differs
other
MTHFD1/2
inhibitors
antifolates.
Thus,
our
findings
uncover
an
approach
attack
regulatory
1C
metabolism.
Metabolites,
Год журнала:
2025,
Номер
15(3), С. 201 - 201
Опубликована: Март 13, 2025
Background:
Tumor
cells
engage
in
continuous
self-replication
by
utilizing
a
large
number
of
resources
and
capabilities,
typically
within
an
aberrant
metabolic
regulatory
network
to
meet
their
own
demands.
This
dysregulation
leads
the
formation
tumor
microenvironment
(TME)
most
solid
tumors.
Nanomedicines,
due
unique
physicochemical
properties,
can
achieve
passive
targeting
certain
tumors
through
enhanced
permeability
retention
(EPR)
effect,
or
active
deliberate
design
optimization,
resulting
accumulation
TME.
The
use
nanomedicines
target
critical
pathways
holds
significant
promise.
However,
requires
careful
selection
relevant
drugs
materials,
taking
into
account
multiple
factors.
traditional
trial-and-error
process
is
relatively
inefficient.
Artificial
intelligence
(AI)
integrate
big
data
evaluate
delivery
efficiency
nanomedicines,
thereby
assisting
nanodrugs.
Methods:
We
have
conducted
detailed
review
key
papers
from
databases,
such
as
ScienceDirect,
Scopus,
Wiley,
Web
Science,
PubMed,
focusing
on
reprogramming,
mechanisms
action
development
metabolism,
application
AI
empowering
nanomedicines.
integrated
content
present
current
status
research
metabolism
potential
future
directions
this
field.
Results:
Nanomedicines
possess
excellent
TME
which
be
utilized
disrupt
cells,
including
glycolysis,
lipid
amino
acid
nucleotide
metabolism.
disruption
selective
killing
disturbance
Extensive
has
demonstrated
that
AI-driven
methodologies
revolutionized
nanomedicine
development,
while
concurrently
enabling
precise
identification
molecular
regulators
involved
oncogenic
reprogramming
pathways,
catalyzing
transformative
innovations
targeted
cancer
therapeutics.
Conclusions:
great
Additionally,
will
accelerate
discovery
metabolism-related
targets,
empower
optimization
help
minimize
toxicity,
providing
new
paradigm
for
development.
Redox Biology,
Год журнала:
2024,
Номер
77, С. 103394 - 103394
Опубликована: Окт. 11, 2024
Cancer
cells
maintain
high
levels
of
reactive
oxygen
species
(ROS)
to
drive
their
growth,
but
ROS
can
trigger
cell
death
through
oxidative
stress
and
DNA
damage.
To
survive
enhanced
levels,
cancer
activate
antioxidant
defenses.
One
such
defense
is
MTH1,
an
enzyme
that
prevents
the
incorporation
oxidized
nucleotides
into
DNA,
thus
preventing
damage
allowing
proliferate.
MTH1
are
often
elevated
in
many
cancers,
thus,
inhibiting
attractive
strategy
for
suppressing
tumor
growth
metastasis.
Targeted
inhibition
induce
cells,
exploiting
vulnerability
selectively
targeting
them
destruction.
Targeting
promising
treatment
because
normal
have
lower
less
dependent
on
these
pathways,
making
approach
both
effective
specific
cancer.
This
review
aims
investigate
potential
as
a
therapeutic
target,
especially
treatment,
offering
detailed
insights
its
structure,
function,
role
disease
progression.
We
also
discussed
various
inhibitors
been
developed
though
effectiveness
varies.
In
addition,
this
provide
deeper
mechanistic
prevention
management
diseases.
Cancer Research,
Год журнала:
2023,
Номер
83(5), С. 657 - 666
Опубликована: Янв. 18, 2023
Abstract
Therapy
resistance
is
imposing
a
daunting
challenge
on
effective
clinical
management
of
breast
cancer.
Although
the
development
to
drugs
multifaceted,
reprogramming
energy
metabolism
pathways
emerging
as
central
but
heterogenous
regulator
this
therapeutic
challenge.
Metabolic
heterogeneity
in
cancer
cells
intricately
associated
with
alterations
different
signaling
networks
and
activation
DNA
damage
response
pathways.
Here
we
consider
how
dynamic
metabolic
milieu
regulates
their
repair
ability
ultimately
contribute
therapy
resistance.
Diverse
epigenetic
regulators
are
crucial
remodeling
landscape
This
epigenetic–metabolic
interplay
profoundly
affects
genomic
stability
well
genotoxic
therapies.
These
observations
identify
defining
mechanisms
epigenetics–metabolism–DNA
axis
that
can
be
critical
for
devising
novel,
targeted
approaches
could
sensitize
conventional
treatment
strategies.
Disease Models & Mechanisms,
Год журнала:
2024,
Номер
17(8)
Опубликована: Авг. 1, 2024
ABSTRACT
The
size
and
composition
of
the
intracellular
DNA
precursor
pool
is
integral
to
maintenance
genome
stability,
this
relationship
fundamental
our
understanding
cancer.
Key
aspects
carcinogenesis,
including
elevated
mutation
rates
induction
certain
types
damage
in
cancer
cells,
can
be
linked
disturbances
deoxynucleoside
triphosphate
(dNTP)
pools.
Furthermore,
approaches
treat
heavily
exploit
metabolic
interplay
between
dNTP
pool,
with
a
long-standing
example
being
use
antimetabolite-based
therapies,
strategy
continues
show
promise
development
new
targeted
therapies.
In
Review,
we
compile
current
knowledge
on
both
causes
consequences
perturbations
together
their
impact
stability.
We
outline
several
outstanding
questions
remaining
field,
such
as
role
catabolism
stability
expansion.
Importantly,
detail
how
mechanistic
these
processes
utilised
aim
providing
better
informed
treatment
options
patients
Frontiers in Genetics,
Год журнала:
2025,
Номер
15
Опубликована: Янв. 8, 2025
Lung
adenocarcinoma
(LUAD)
is
a
highly
aggressive
tumor
with
one
of
the
highest
morbidity
and
mortality
rates
in
world.
Nucleotide
metabolic
processes
are
critical
for
cancer
development,
progression,
alteration
microenvironment.
However,
effect
nucleotide
metabolism
on
LUAD
remains
to
be
thoroughly
investigated.
Transcriptomic
clinical
data
were
downloaded
organized
from
TCGA
GEO
databases.
Genes
related
Msigdb
database.
associated
prognosis
identified
using
univariate
COX
analysis,
prognostic
risk
model
was
constructed
machine
learning
combination
Lasso
+
Stepcox.
The
model's
predictive
validity
evaluated
KM
survival
timeROC
curves.
Based
model,
patients
classified
into
different
subtypes,
differences
between
subtypes
explored
terms
genomic
mutations,
functional
enrichment,
immune
characteristics,
immunotherapy
responses.
Finally,
key
gene
SNRPA
screened,
series
vitro
experiments
performed
cell
lines
explore
role
LUAD.
could
accurately
categorized
based
metabolism-related
score
(NMBRS).
There
significant
NMBRS
showed
high
accuracy
predicting
patients.
In
addition,
mutation
enrichment
exhibited
anti-tumor
profiles.
Importantly,
can
used
predict
responsiveness
immunotherapy.
results
cellular
indicate
that
plays
an
important
development
progression
lung
adenocarcinoma.
This
study
comprehensively
reveals
value
application
A
signature
genes
predicted
patients,
this
as
guide
Frontiers in Immunology,
Год журнала:
2025,
Номер
16
Опубликована: Март 26, 2025
Background
Ischemic
stroke
(IS)
is
a
major
global
cause
of
death
and
disability,
linked
to
nucleotide
metabolism
imbalances.
This
study
aimed
identify
metabolism-related
genes
associated
with
IS
explore
their
roles
in
disease
mechanisms
for
new
diagnostic
therapeutic
strategies.
Methods
gene
expression
data
were
sourced
from
the
GEO
database.
Differential
analysis
weighted
co-expression
network
(WGCNA)
conducted
R,
intersecting
results
genes.
Functional
enrichment
connectivity
map
(cMAP)
analyses
identified
key
potential
agents.
Core
immune-related
determined
using
LASSO
regression,
SVM-RFE,
Random
Forest
algorithms.
Immune
cell
infiltration
levels
correlations
analyzed
via
CIBERSORT.
Single-cell
RNA
sequencing
(scRNA-seq)
molecular
docking
assessed
expression,
localization,
gene-drug
binding.
In
vivo
experiments
validated
core
expression.
Results
Thirty-three
candidate
identified,
mainly
involved
immune
inflammatory
responses.
CFL1,
HMCES
,
GIMAP1
emerged
as
genes,
showing
high
potential.
cMAP
indicated
these
drug
targets.
scRNA-seq
clarified
confirmed
strong
significant
IS.
Conclusion
underscores
role
IS,
identifying
biomarkers
targets,
providing
insights
diagnosis
therapy
development.