CD44 Variant Expression in Follicular Cell-Derived Thyroid Cancers: Implications for Overcoming Multidrug Resistance
Molecules,
Journal Year:
2025,
Volume and Issue:
30(9), P. 1899 - 1899
Published: April 24, 2025
Thyroid
cancer
(TC)
is
a
significant
global
health
issue
that
exhibits
notable
heterogeneity
in
incidence
and
outcomes.
In
low-resource
settings
such
as
Africa,
delayed
diagnosis
limited
healthcare
access
exacerbate
mortality
rates.
Among
follicular
cell-derived
thyroid
cancers—including
papillary
(PTC),
(FTC),
anaplastic
(ATC),
poorly
differentiated
(PDTC)
subtypes—the
role
of
CD44
variants
has
emerged
critical
factor
influencing
tumor
progression
multidrug
resistance
(MDR).
CD44,
transmembrane
glycoprotein,
its
splice
(CD44v)
mediate
cell
adhesion,
migration,
survival,
contributing
to
stem
(CSC)
maintenance
therapy
resistance.
Differential
expression
patterns
isoforms
across
TC
subtypes
have
shown
diagnostic,
prognostic,
therapeutic
implications.
Specifically,
CD44v6
PTC
been
correlated
with
metastasis
aggressive
behavior,
while
FTC,
aids
distinguishing
malignant
from
benign
lesions.
Furthermore,
contributes
MDR
through
enhanced
drug
efflux
via
ABC
transporters,
apoptosis
evasion,
CSC
the
Wnt/β-catenin
PI3K/Akt
pathways.
Targeted
therapies
against
monoclonal
antibodies,
hyaluronic
acid-based
nanocarriers,
gene-editing
technologies
hold
promise
overcoming
MDR.
However,
despite
mounting
evidence
supporting
CD44-targeted
strategies
various
cancers,
research
on
this
potential
remains
limited.
This
review
synthesizes
existing
knowledge
variant
cancers
highlights
mitigate
MDR,
particularly
high-burden
regions,
thereby
improving
patient
outcomes
survival.
Language: Английский
Targeting cancer stem cells by TPA leads to inhibition of refractory sarcoma and extended overall survival.
Karina Galoian,
No information about this author
Daniel Bilbao,
No information about this author
Carina Denny
No information about this author
et al.
Deleted Journal,
Journal Year:
2024,
Volume and Issue:
32(4), P. 200905 - 200905
Published: Nov. 6, 2024
Refractory
cancer
recurrence
in
patients
is
a
serious
challenge
modern
medicine.
Tumor
regrowth
more
aggressive
and
invasive
drug-resistant
form
caused
by
specific
sub-population
of
tumor
cells
defined
as
stem
(CSCs).
While
the
role
CSCs
relapse
recognized,
signaling
pathways
CSCs-driven
chemoresistance
are
less
well
understood.
Moreover,
there
no
effective
therapeutic
strategies
that
involve
inhibition
responsible
for
drug
resistance.
There
clinical
need
to
develop
new
therapies
with
refractory
sarcomas,
particularly
fibrosarcoma.
These
tumors,
poor
overall
survival,
do
not
respond
conventional
therapies.
Standard
systemic
chemotherapy
these
tumors
includes
doxorubicin
(DOX).
A
Tyr
peptide
analog
(TPA),
developed
our
laboratory,
specifically
targets
drastically
reducing
expression
polycomb
group
protein
enhancer
zester
(EZH2)
its
downstream
targets,
ALDH1A1
Nanog.
Language: Английский
Single-cell expression and immune infiltration analysis of polyamine metabolism in breast cancer
Xiliang Zhang,
No information about this author
Hanjie Guo,
No information about this author
Xiao‐Long Li
No information about this author
et al.
Discover Oncology,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: Nov. 16, 2024
Breast
cancer
is
one
of
the
most
threatening
women
health
diseases
worldwide
and
its
molecular
heterogeneity
offers
a
range
response
to
therapy.
The
role
polyamine
metabolism
receiving
increasing
attention.
Polyamine
not
only
plays
an
important
in
occurrence
development
breast
cancer,
but
also
interacts
with
tumor
immune
microenvironment.
In
this
work,
we
applied
single-cell
RNA-sequencing
(scRNA-seq)
systems
immunological
approaches
interrogate
cell
infiltration
gene-to-gene
co-expressions
bulk
transcriptomes
cancer.
We
acquired
sample
data
from
Cancer
Genome
Atlas
(TCGA)
Gene
Expression
Omnibus
(GEO),
evaluated
status
22
types
using
CIBERSORTx
tool,
respectively.
By
leveraging
Retrospective
various
technologies
including
gene
expression
methylation,
identified
46
proliferation-associated
co-expression
modules
weighted
coexpression
network
analysis
(WGCNA)
approach
along
machine
learning
models
which
turn
delineated
single
level
expressions
features
that
these
selected
module
possessed.
observed
substantial
cellular
microenvironment,
where
lineage-specific
patterns
were
highly
associated
progression.
Moreover,
correlated
could
function
as
regulators
tumors
for
risk
scores
different
patient
groups
defined
by
high-
low-risk.
findings
study
shed
new
light
upon
classification
prognostic
assessment
personalized
treatment
Language: Английский