Abstract
Glioblastoma
is
the
most
common
aggressive
adult
brain
tumor.
Numerous
studies
have
reported
results
from
either
private
institutional
data
or
publicly
available
datasets.
However,
current
public
datasets
are
limited
in
terms
of:
a)
number
of
subjects,
b)
lack
consistent
acquisition
protocol,
c)
quality,
d)
accompanying
clinical,
demographic,
and
molecular
information.
Toward
alleviating
these
limitations,
we
contribute
“University
Pennsylvania
Imaging,
Genomics,
Radiomics”
(UPenn-GBM)
dataset,
which
describes
currently
largest
comprehensive
collection
630
patients
diagnosed
with
de
novo
glioblastoma.
The
UPenn-GBM
dataset
includes
(a)
advanced
multi-parametric
magnetic
resonance
imaging
scans
acquired
during
routine
clinical
practice,
at
University
Health
System,
(b)
information,
(d)
perfusion
diffusion
derivative
volumes,
(e)
computationally-derived
manually-revised
expert
annotations
tumor
sub-regions,
as
well
(f)
quantitative
(also
known
radiomic)
features
corresponding
to
each
regions.
This
our
contribution
towards
repeatable,
reproducible,
comparative
leading
new
predictive,
prognostic,
diagnostic
assessments.
CA A Cancer Journal for Clinicians,
Год журнала:
2019,
Номер
69(2), С. 127 - 157
Опубликована: Фев. 5, 2019
Abstract
Judgement,
as
one
of
the
core
tenets
medicine,
relies
upon
integration
multilayered
data
with
nuanced
decision
making.
Cancer
offers
a
unique
context
for
medical
decisions
given
not
only
its
variegated
forms
evolution
disease
but
also
need
to
take
into
account
individual
condition
patients,
their
ability
receive
treatment,
and
responses
treatment.
Challenges
remain
in
accurate
detection,
characterization,
monitoring
cancers
despite
improved
technologies.
Radiographic
assessment
most
commonly
visual
evaluations,
interpretations
which
may
be
augmented
by
advanced
computational
analyses.
In
particular,
artificial
intelligence
(AI)
promises
make
great
strides
qualitative
interpretation
cancer
imaging
expert
clinicians,
including
volumetric
delineation
tumors
over
time,
extrapolation
tumor
genotype
biological
course
from
radiographic
phenotype,
prediction
clinical
outcome,
impact
treatment
on
adjacent
organs.
AI
automate
processes
initial
images
shift
workflow
management
whether
or
administer
an
intervention,
subsequent
observation
yet
envisioned
paradigm.
Here,
authors
review
current
state
applied
describe
advances
4
types
(lung,
brain,
breast,
prostate)
illustrate
how
common
problems
are
being
addressed.
Although
studies
evaluating
applications
oncology
date
have
been
vigorously
validated
reproducibility
generalizability,
results
do
highlight
increasingly
concerted
efforts
pushing
technology
use
future
directions
care.
Nature Communications,
Год журнала:
2018,
Номер
9(1)
Опубликована: Окт. 22, 2018
Circular
RNAs
(circRNAs)
are
a
large
class
of
transcripts
in
the
mammalian
genome.
Although
translation
circRNAs
was
reported,
additional
coding
and
functions
their
translated
products
remain
elusive.
Here,
we
demonstrate
that
an
endogenous
circRNA
generated
from
long
noncoding
RNA
encodes
regulatory
peptides.
Through
ribosome
nascent-chain
complex-bound
sequencing
(RNC-seq),
discover
several
peptides
potentially
encoded
by
circRNAs.
We
identify
87-amino-acid
peptide
circular
form
intergenic
non-protein-coding
p53-induced
transcript
(LINC-PINT)
suppresses
glioblastoma
cell
proliferation
vitro
vivo.
This
directly
interacts
with
polymerase
associated
factor
complex
(PAF1c)
inhibits
transcriptional
elongation
multiple
oncogenes.
The
expression
this
its
corresponding
decreased
compared
levels
normal
tissues.
Our
results
establish
existence
potential
tumorigenesis.
Genes & Development,
Год журнала:
2019,
Номер
33(11-12), С. 591 - 609
Опубликована: Июнь 1, 2019
Glioblastoma
ranks
among
the
most
lethal
of
all
human
cancers.
Glioblastomas
display
striking
cellular
heterogeneity,
with
stem-like
glioblastoma
stem
cells
(GSCs)
at
apex.
Although
original
identification
GSCs
dates
back
more
than
a
decade,
purification
and
characterization
remains
challenging.
Despite
these
challenges,
evidence
that
play
important
roles
in
tumor
growth
response
to
therapy
has
grown.
Like
normal
cells,
are
functionally
defined
distinguished
from
their
differentiated
progeny
core
transcriptional,
epigenetic,
metabolic
regulatory
levels,
suggesting
no
single
therapeutic
modality
will
be
universally
effective
against
heterogenous
GSC
population.
induce
systemic
immunosuppression
mixed
responses
oncoimmunologic
modalities,
potential
for
augmentation
deeper
consideration
GSCs.
Unfortunately,
literature
been
complicated
by
frequent
use
inferior
cell
lines
lack
proper
functional
analyses.
Collectively,
offers
reliable
cancer
study
better
model
disease
inform
improved
biologic
understanding
design
novel
therapeutics.
IEEE Transactions on Medical Imaging,
Год журнала:
2020,
Номер
41(4), С. 757 - 770
Опубликована: Сен. 3, 2020
Cancer
diagnosis,
prognosis,
mymargin
and
therapeutic
response
predictions
are
based
on
morphological
information
from
histology
slides
molecular
profiles
genomic
data.
However,
most
deep
learning-based
objective
outcome
prediction
grading
paradigms
or
genomics
alone
do
not
make
use
of
the
complementary
in
an
intuitive
manner.
In
this
work,
we
propose
Pathomic
Fusion,
interpretable
strategy
for
end-to-end
multimodal
fusion
image
(mutations,
CNV,
RNA-Seq)
features
survival
prediction.
Our
approach
models
pairwise
feature
interactions
across
modalities
by
taking
Kronecker
product
unimodal
representations,
controls
expressiveness
each
representation
via
a
gating-based
attention
mechanism.
Following
supervised
learning,
able
to
interpret
saliently
localize
modality,
understand
how
importance
shifts
when
conditioning
input.
We
validate
our
using
glioma
clear
cell
renal
carcinoma
datasets
Genome
Atlas
(TCGA),
which
contains
paired
whole-slide
image,
genotype,
transcriptome
data
with
ground
truth
histologic
grade
labels.
15-fold
cross-validation,
results
demonstrate
that
proposed
paradigm
improves
prognostic
determinations
subtyping,
as
well
networks
trained
alone.
The
method
establishes
insight
theory
train
biomedical
manner,
will
be
useful
other
problems
medicine
seek
combine
heterogeneous
streams
understanding
diseases
predicting
resistance
treatment.
Code
made
available
at:
https://github.com/mahmoodlab/PathomicFusion.
Nature Communications,
Год журнала:
2020,
Номер
11(1)
Опубликована: Окт. 27, 2020
Abstract
Tumor
necrosis
commonly
exists
and
predicts
poor
prognoses
in
many
cancers.
Although
it
is
thought
to
result
from
chronic
ischemia,
the
underlying
nature
mechanisms
driving
involved
cell
death
remain
obscure.
Here,
we
show
that
glioblastoma
(GBM)
involves
neutrophil-triggered
ferroptosis.
In
a
hyperactivated
transcriptional
coactivator
with
PDZ-binding
motif-driven
GBM
mouse
model,
neutrophils
coincide
temporally
spatially.
Neutrophil
depletion
dampens
necrosis.
Neutrophils
isolated
brain
tumors
kill
cocultured
tumor
cells.
Mechanistically,
induce
iron-dependent
accumulation
of
lipid
peroxides
within
cells
by
transferring
myeloperoxidase-containing
granules
into
Inhibition
or
myeloperoxidase
suppresses
neutrophil-induced
cytotoxicity.
Intratumoral
glutathione
peroxidase
4
overexpression
acyl-CoA
synthetase
long
chain
family
member
diminishes
aggressiveness
tumors.
Furthermore,
analyses
human
GBMs
support
ferroptosis
are
associated
predict
survival.
Thus,
our
study
identifies
as
reveals
pro-tumorigenic
role
Together,
propose
certain
damage(s)
occurring
during
early
progression
(i.e.
ischemia)
recruits
site
tissue
damage
thereby
results
positive
feedback
loop,
amplifying
development
its
fullest
extent.
Cell stem cell,
Год журнала:
2020,
Номер
26(1), С. 48 - 63.e6
Опубликована: Янв. 1, 2020
Glioblastoma
is
a
devastating
form
of
brain
cancer.
To
identify
aspects
tumor
heterogeneity
that
may
illuminate
drivers
invasion,
we
created
glioblastoma
cell
atlas
with
single-cell
transcriptomics
cancer
cells
mapped
onto
reference
framework
the
developing
and
adult
human
brain.
We
find
multiple
GSC
subtypes
exist
within
single
tumor.
Within
these
GSCs,
an
invasive
population
similar
to
outer
radial
glia
(oRG),
fetal
type
expands
stem
niche
in
normal
cortex.
Using
live
time-lapse
imaging
primary
resected
tumors,
discover
tumor-derived
oRG-like
undergo
characteristic
mitotic
somal
translocation
behavior
previously
only
observed
development,
suggesting
reactivation
developmental
programs.
In
addition,
show
PTPRZ1
mediates
both
invasion.
These
data
suggest
presence
heterogeneous
GSCs
underlie
glioblastoma's
rapid
progression
Nature Cancer,
Год журнала:
2022,
Номер
3(4), С. 505 - 517
Опубликована: Апрель 25, 2022
Inferring
single-cell
compositions
and
their
contributions
to
global
gene
expression
changes
from
bulk
RNA
sequencing
(RNA-seq)
datasets
is
a
major
challenge
in
oncology.
Here
we
develop
Bayesian
cell
proportion
reconstruction
inferred
using
statistical
marginalization
(BayesPrism),
method
predict
cellular
composition
individual
types
RNA-seq,
patient-derived,
scRNA-seq
as
prior
information.
We
conduct
integrative
analyses
primary
glioblastoma,
head
neck
squamous
carcinoma
skin
cutaneous
melanoma
correlate
type
with
clinical
outcomes
across
tumor
types,
explore
spatial
heterogeneity
malignant
nonmalignant
states.
refine
current
cancer
subtypes
annotation
after
exclusion
of
confounding
cells.
Finally,
identify
genes
whose
cells
correlates
macrophage
infiltration,
T
cells,
fibroblasts
endothelial
multiple
types.
Our
work
introduces
new
lens
accurately
infer
large
cohorts
RNA-seq
data.