Glioblastoma and brain connectivity: the need for a paradigm shift
The Lancet Neurology,
Год журнала:
2024,
Номер
23(7), С. 740 - 748
Опубликована: Июнь 13, 2024
Язык: Английский
Pigs: Large Animal Preclinical Cancer Models
World Journal of Oncology,
Год журнала:
2024,
Номер
15(2), С. 149 - 168
Опубликована: Март 21, 2024
Pigs
are
playing
an
increasingly
vital
role
as
translational
biomedical
models
for
studying
human
pathophysiology.
The
annotation
of
the
pig
genome
was
a
huge
step
forward
in
translatability
pigs
model
various
diseases.
Similarities
between
humans
and
terms
anatomy,
physiology,
genetics,
immunology
have
allowed
to
become
comprehensive
preclinical
With
diverse
range,
from
craniofacial
ophthalmology
reproduction,
wound
healing,
musculoskeletal,
cancer,
provided
seminal
understanding
This
review
focuses
on
current
research
using
cancer
highlights
strengths
opportunities
cancers.
Язык: Английский
Advancing Glioblastoma Therapy: Learning From the Past and Innovations for the Future
Mandeep Rana,
Ke-Chi Liou,
Amandeep Thakur
и другие.
Cancer Letters,
Год журнала:
2025,
Номер
unknown, С. 217601 - 217601
Опубликована: Март 1, 2025
Язык: Английский
Structural-functional fingerprinting for abnormalities investigation in glioma patients
Research Square (Research Square),
Год журнала:
2025,
Номер
unknown
Опубликована: Май 21, 2025
Gliomas
alter
brain
function
and
integrity,
but
these
disruptions
are
often
studied
separately.
This
study
utilised
a
novel
approach
that
integrated
functional,
structural
microstructural
connectivity
information
to
investigate
glioma-induced
network
changes
their
clinical
implications.
It
focused
on
the
impact
of
gliomas
key
networks,
with
particular
emphasis
relationship
between
tumour
topology
its
effect
homotopic
areal-level
parcellation.
The
investigation
was
grounded
in
unique
dataset
comprising
functional
diffusion
images
forty-one
newly
diagnosed
glioma
patients.
Connectivity
matrices
(functional,
structural,
microstructural)
were
generated
using
parcellations
combined
into
an
integration
matrix.
A
linear
regression
model
compared
patient
data
pseudo-healthy
references.
identified
affected
regions
as
those
falling
left
tail
distribution
across
patients
parcellations.
revealed
lateralized
affect
networks
both
hemispheres,
hemisphere
lesions
primarily
altering
homolateral
contralateral
healthy
tissues.
Abnormalities
more
easily
detected
distant
from
lesion
rather
than
measures.
highlighted
heterogeneity
alterations
emphasised
comprehensive
understanding
abnormalities
requires
integrating
multiple
modalities.
Язык: Английский
Indirect functional connectivity does not predict overall survival in glioblastoma
Neurobiology of Disease,
Год журнала:
2024,
Номер
196, С. 106521 - 106521
Опубликована: Апрель 30, 2024
Lesion
network
mapping
(LNM)
is
a
popular
framework
to
assess
clinical
syndromes
following
brain
injury.
The
classical
approach
involves
embedding
lesions
from
patients
into
normative
functional
connectome
and
using
the
corresponding
maps
as
proxies
for
disconnections.
However,
previous
studies
indicated
limited
predictive
power
of
this
in
behavioral
deficits.
We
hypothesized
similarly
low
predictiveness
overall
survival
(OS)
glioblastoma
(GBM).
A
retrospective
dataset
with
GBM
was
included
(n
=
99).
masks
were
registered
space
compute
disconnectivity
maps.
consisted
data
173
healthy
subjects
obtained
Human
Connectome
Project.
modified
version
LNM
then
applied
core
regions
masks.
Linear
regression,
classification,
principal
component
(PCA)
analyses
conducted
explore
relationship
between
OS.
OS
considered
both
continuous
categorical
(low,
intermediate,
high
survival)
variable.
results
revealed
no
significant
associations
disconnection
strength
when
analyzed
at
voxel-wise
classification
levels.
Moreover,
stratified
different
groups
did
not
exhibit
differences
connectivity
patterns.
spatial
similarity
among
first
PCA
each
group
suggested
lack
distinctive
patterns
associated
duration.
Compared
indirect
structural
measures,
does
provide
GBM.
These
findings
are
consistent
research
that
demonstrated
limitations
measures
predicting
outcomes,
underscoring
need
more
comprehensive
methodologies
deeper
understanding
factors
influencing
outcomes
challenging
disease.
Язык: Английский
Relationship between glioblastoma location and O6-methylguanine-DNA methyltransferase promoter methylation percentage
Brain Communications,
Год журнала:
2024,
Номер
6(6)
Опубликована: Янв. 1, 2024
Abstract
A
large
literature
assessed
the
relationships
between
O6-methylguanine-DNA
methyltransferase
(MGMT)
promoter
methylation
status
and
glioblastoma
location
with
inconsistent
results.
Studies
assessing
this
association
using
percentage
of
are
lacking.
This
cross-sectional
study
aimed
at
investigating
topology
MGMT
methylation,
both
as
categorical
(presence/absence)
continuous
(percentage)
status.
We
included
patients
diagnosis
isocitrate
dehydrogenase
wild-type
[World
Health
Organization
(WHO)
2021
classification],
available
pre-surgical
MRI,
known
Quantitative
assessment
was
obtained
through
pyrosequencing.
Several
analyses
were
performed
for
variables
(χ2,
t-tests,
ANOVA
Pearson’s
correlations),
in
cortex/white
matter/deep
grey
matter
nuclei,
lobes,
left/right
hemispheres
functional
white
network
templates.
Furthermore,
we
voxel-wise
level
differences
(i)
methylated
unmethylated
glioblastomas
(ii)
highly
lowly
glioblastomas.
Lastly,
investigated
linear
relationship
glioblastoma-voxel
percentage.
Ninety-three
(66
males;
mean
age:
62.3
±
11.3
years),
42
methylated.
The
33.9
18.3%.
No
volume
found
MGMT-methylated
MGMT-unmethylated
patients.
specific
anatomical
regions
associated
level.
positively
correlated
cortical
localization
(R
=
0.36,
P
0.021)
negatively
deep
nuclei
−0.35,
0.025).
To
summarize,
multiple
approaches,
including
analyses.
In
conclusion,
location,
while
no
Язык: Английский