Frontiers in Bioscience-Landmark,
Journal Year:
2023,
Volume and Issue:
28(11), P. 287 - 287
Published: Nov. 8, 2023
Background:
Cervical
cancer
has
high
morbidity
and
intratumor
heterogeneity.
Anoikis,
a
form
of
programmed
cell
death
preventing
detached
cells
from
readhering,
may
serve
as
potential
prognostic
signature
for
cervical
cancer.
This
study
aimed
to
assess
the
predictive
performance
anoikis
patterns
in
prognosis.
Methods:
Differentially
expressed
anoikis-related
genes
(DEARGs)
were
identified
between
normal
samples
using
data
Gene
Expression
Omnibus
database
with
elucidation
mutation
status
bio-function.
Novel
molecular
subtypes
defined
The
Cancer
Genome
Atlas
(TCGA)
cohort
consensus
clustering
analysis.
A
multigene
was
constructed
through
least
absolute
shrinkage
selection
operator
(LASSO)
Cox
analysis
internal
external
validation.
nomogram-based
survival
probability
over
3
5
years
predicted
assessed
calibration,
receiver
operating
characteristic,
decision
curve
analysis,
Kaplan-Meier
curves.
Additionally,
mutation,
function,
immune
conducted
among
different
risk
groups.
Results:
We
77
DEARGs
tissues
explored
their
functions.
TCGA
could
be
categorized
into
two
based
on
these
genes.
Furthermore,
seven
constructed,
nomogram
involving
clinicopathological
characteristics
showed
satisfactory
performance.
Functional
indicated
that
immune-related
enriched,
status,
well
sensitivity
chemotherapies
targeting
drugs,
correlated
model.
Conclusions:
Anoikis
play
important
roles
tumor
immunity
can
used
predict
prognosis
cancers.
Environmental Toxicology,
Journal Year:
2024,
Volume and Issue:
39(10), P. 4776 - 4790
Published: Aug. 20, 2024
Abstract
Osteosarcoma,
known
for
its
rapid
progression
and
high
metastatic
potential,
poses
significant
challenges
in
adolescent
oncology.
This
study
delves
into
the
roles
of
lipid
metabolism
acetylation
genes
disease's
pathogenesis.
Utilizing
gene
set
variation
analysis,
we
examined
14
metabolism‐related
pathways
osteosarcoma
patients,
identifying
variances
three
between
primary
cases.
Additionally,
differences
four
these
groups
were
observed.
A
comprehensive
analysis
pinpointed
62
genes,
with
39
exhibiting
correlations
termed
(LMA)
genes.
Employing
machine
learning
techniques
like
Lasso+RSF
GBM,
developed
a
predictive
model
overall
survival
based
on
LMA
model,
an
average
c‐index
0.771,
focuses
key
genes:
CYP2C8,
PAFAH2,
ACOX3,
whose
prognostic
value
was
confirmed
through
receiver
operating
characteristic
curve
analyses.
Quantitative
RT‐PCR
results
indicated
higher
expression
levels
ACOX3
PAFAH2
OS
cells
(143B,
HOS,
MG63)
than
osteoblasts
(hFOB1.19),
while
CYP2C8
lower
cells.
Furthermore,
drug
sensitivity
pRRophetic
algorithm
suggested
potential
targeted
therapies,
revealing
drugs
differential
scores
varied
treatment
responses
related
to
core
not
only
highlights
crucial
role
but
also
offers
foundation
personalized
strategies,
marking
notable
advancement
combating
this
severe
form
cancer.
Advanced Therapeutics,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 10, 2024
Abstract
Osteosarcoma
(OS)
is
a
rare
primary
malignant
bone
cancer
affecting
mainly
young
individuals.
Treatment
typically
consists
of
chemotherapy
and
surgical
tumor
resection,
which
has
undergone
few
improvements
since
the
1970s.
This
therapeutic
approach
encounters
several
limitations
attributed
to
tumor's
inherent
chemoresistance,
marked
heterogeneity
metastatic
potential.
Therefore,
development
in
vitro
platforms
that
closely
mimic
OS
pathophysiology
crucial
understand
progression
discover
effective
anticancer
therapeutics.
Contrary
2D
monolayer
cultures
animal
models,
3D
show
promise
replicating
macrostructure,
cell‐cell
cell‐extracellular
matrix
interactions.
review
provides
an
overview
biomanufacturing
strategies
employed
developing
highlighting
their
role
different
aspects
improving
research
drug
screening.
A
variety
models
are
explored,
including
both
scaffold‐free
scaffold‐based
encompassing
cell
spheroids,
hydrogels,
innovative
approaches
like
electrospun
nanofibers,
microfluidic
devices
bioprinted
constructs.
By
examining
distinctive
features
each
model
type,
this
offers
insights
into
potential
transformative
impact
on
landscape
innovation,
addressing
challenges
future
directions
modeling.
Journal Of Big Data,
Journal Year:
2023,
Volume and Issue:
10(1)
Published: Aug. 16, 2023
Abstract
Hepatocellular
carcinoma
(HCC)
represents
a
formidable
malignancy
with
high
lethality.
Nonetheless,
the
development
of
vaccine
and
establishment
prognostic
models
for
precise
personalized
treatment
HCC
still
encounter
big
challenges.
Thus,
aim
this
study
was
to
develop
vaccines
explore
anoikis-based
based
on
RNA
sequencing
data
in
GEO
datasets
(GSE10143,
GSE76427)
TCGA-LIHC
cohort.
Potential
antigens
were
identified
using
GEPIA2,
cBioPortal,
TIMER2.
Anoikis-related
subtypes
gene
clusters
defined
by
consensus
clustering
566
liver
cancer
samples
28
anoikis
regulators,
we
further
analyzed
their
relationship
immune
microenvironment
HCC.
A
predictive
model
anoikis-related
long
noncoding
RNAs
(lncRNAs)
developed
accurately
predict
prognosis.
Seven
overexpressed
genes
associated
prognosis
tumor-infiltrating
antigen-presenting
cells
as
potential
tumor
mRNA
vaccines.
Two
(ARGs)
two
different
characteristics
validated
cohorts.
The
between
showed
cell
infiltration
molecular
characteristics.
Furthermore,
score
seven
lncRNAs
LASSO
regression
constructed,
low-risk
group
having
favorable
prognosis,
“hot”
microenvironment,
better
response
immunotherapy.
CCNB1,
CDK1,
DNASE1L3,
KPNA2,
PRC1,
PTTG,
UBE2S
first
promising
Besides,
innovatively
propose
subtypes,
which
not
only
enable
stratification
patients
but
also
provide
blueprint
identifying
optimal
candidates
vaccines,
enhancing
immunotherapeutic
strategies.
Frontiers in Bioscience-Landmark,
Journal Year:
2023,
Volume and Issue:
28(11), P. 287 - 287
Published: Nov. 8, 2023
Background:
Cervical
cancer
has
high
morbidity
and
intratumor
heterogeneity.
Anoikis,
a
form
of
programmed
cell
death
preventing
detached
cells
from
readhering,
may
serve
as
potential
prognostic
signature
for
cervical
cancer.
This
study
aimed
to
assess
the
predictive
performance
anoikis
patterns
in
prognosis.
Methods:
Differentially
expressed
anoikis-related
genes
(DEARGs)
were
identified
between
normal
samples
using
data
Gene
Expression
Omnibus
database
with
elucidation
mutation
status
bio-function.
Novel
molecular
subtypes
defined
The
Cancer
Genome
Atlas
(TCGA)
cohort
consensus
clustering
analysis.
A
multigene
was
constructed
through
least
absolute
shrinkage
selection
operator
(LASSO)
Cox
analysis
internal
external
validation.
nomogram-based
survival
probability
over
3
5
years
predicted
assessed
calibration,
receiver
operating
characteristic,
decision
curve
analysis,
Kaplan-Meier
curves.
Additionally,
mutation,
function,
immune
conducted
among
different
risk
groups.
Results:
We
77
DEARGs
tissues
explored
their
functions.
TCGA
could
be
categorized
into
two
based
on
these
genes.
Furthermore,
seven
constructed,
nomogram
involving
clinicopathological
characteristics
showed
satisfactory
performance.
Functional
indicated
that
immune-related
enriched,
status,
well
sensitivity
chemotherapies
targeting
drugs,
correlated
model.
Conclusions:
Anoikis
play
important
roles
tumor
immunity
can
used
predict
prognosis
cancers.