BMC Cancer,
Journal Year:
2025,
Volume and Issue:
25(1)
Published: Jan. 15, 2025
Primary
pulmonary
lymphoepithelial
carcinoma
(pLEC)
is
a
subtype
of
non-small
cell
lung
cancer
(NSCLC)
characterized
by
Epstein-Barr
virus
(EBV)
infection.
However,
the
molecular
pathogenesis
pLEC
remains
poorly
understood.
In
this
study,
we
explored
using
whole-exome
sequencing
(WES)
and
RNA-whole-transcriptome
(RNA-seq)
technologies.
Datasets
normal
tissue,
other
types
NSCLC,
EBV-positive
nasopharyngeal
(EBV+-NPC)
were
obtained
from
public
databases.
Furthermore,
described
gene
signatures,
viral
integration,
quantification,
death
immune
infiltration
pLEC.
Compared
with
NSCLC
EBV+-NPC,
patients
exhibited
lower
somatic
mutation
burden
extensive
copy
number
deletions,
including
1p36.23,
3p21.1,
7q11.23,
11q23.3.
Integration
EBV
associated
dysregulation
expression,
CNV-altered
regions
coinciding
integration
sites.
Specifically,
ZBTB16
ERRFI1
downregulated
CNV
loss,
FOXD
family
genes
overexpressed
gain.
Decreased
expression
might
be
favorable
prognosis
in
patients,
these
enhanced
cytotoxicity.
NPC,
has
distinct
characteristics.
aberrant
genes,
as
well
loss
CNVs,
may
play
crucial
role
further
research
needed
to
assess
potential
biomarker.
PLoS Medicine,
Journal Year:
2019,
Volume and Issue:
16(1), P. e1002730 - e1002730
Published: Jan. 24, 2019
Background
For
virtually
every
patient
with
colorectal
cancer
(CRC),
hematoxylin–eosin
(HE)–stained
tissue
slides
are
available.
These
images
contain
quantitative
information,
which
is
not
routinely
used
to
objectively
extract
prognostic
biomarkers.
In
the
present
study,
we
investigated
whether
deep
convolutional
neural
networks
(CNNs)
can
prognosticators
directly
from
these
widely
available
images.
Methods
and
findings
We
hand-delineated
single-tissue
regions
in
86
CRC
slides,
yielding
more
than
100,000
HE
image
patches,
train
a
CNN
by
transfer
learning,
reaching
nine-class
accuracy
of
>94%
an
independent
data
set
7,180
25
patients.
With
this
tool,
performed
automated
decomposition
representative
multitissue
862
500
stage
I–IV
patients
The
Cancer
Genome
Atlas
(TCGA)
cohort,
large
international
multicenter
collection
tissue.
Based
on
output
neuron
activations
CNN,
calculated
"deep
stroma
score,"
was
factor
for
overall
survival
(OS)
multivariable
Cox
proportional
hazard
model
(hazard
ratio
[HR]
95%
confidence
interval
[CI]:
1.99
[1.27–3.12],
p
=
0.0028),
while
same
manual
quantification
stromal
areas
gene
expression
signature
cancer-associated
fibroblasts
(CAFs)
were
only
specific
tumor
stages.
validated
cohort
409
"Darmkrebs:
Chancen
der
Verhütung
durch
Screening"
(DACHS)
study
who
recruited
between
2003
2007
multiple
institutions
Germany.
Again,
score
OS
(HR
1.63
[1.14–2.33],
0.008),
CRC-specific
2.29
[1.5–3.48],
0.0004),
relapse-free
(RFS;
HR
1.92
[1.34–2.76],
0.0004).
A
prospective
validation
required
before
biomarker
be
implemented
clinical
workflows.
Conclusions
our
retrospective
show
that
assess
human
microenvironment
predict
prognosis
histopathological
Proceedings of the National Academy of Sciences,
Journal Year:
2019,
Volume and Issue:
116(18), P. 9020 - 9029
Published: April 17, 2019
Significance
The
exclusion
of
immune
cells
from
the
tumor
microenvironment
has
been
associated
with
poor
prognosis
in
majority
cancers.
We
report
that
when
considering
21
solid
cancer
types,
cell
is
widely
presence
a
stem
cell-like
phenotype
tumors
(“stemness”).
Stemness
positively
correlates
higher
intratumoral
heterogeneity,
possibly
by
protecting
antigenic
clones
elimination
system.
activation
stemness
program
appears
to
limit
antitumor
responses
via
cell-intrinsic
silencing
endogenous
retrovirus
expression,
repression
type
I
interferon
signaling,
and
up-regulation
immunosuppressive
checkpoints.
Our
work
suggests
targeting
will
promote
T
infiltration
render
more
responsive
control.
Health Information & Libraries Journal,
Journal Year:
2020,
Volume and Issue:
38(2), P. 125 - 138
Published: Jan. 29, 2020
Abstract
Background
The
application
of
bibliometrics
in
medicine
enables
one
to
analyse
vast
amounts
publications
and
their
production
patterns
on
macroscopic
microscopic
levels.
Objectives
aim
the
study
was
historical
perspective
research
literature
regarding
medicine.
Methods
Publications
related
from
1970
2018
were
harvested
Scopus
bibliographic
database.
Reference
Publication
Year
Spectroscopy
triangulated
with
VOSViewer
identify
roots
evolution
topics
clinical
areas.
Results
search
resulted
6557
publications.
trend
positive.
Historical
analysis
identified
33
16
areas
where
applied.
Discussion
increase
productivity
might
be
attributed
increased
use
quantitative
metrics
evaluation,
publish
or
perish
phenomenon
evidence‐based
Conclusion
Medicine
forefront
knowledge
development
bibliometrics.
reference
publication
year
spectroscopy
proved
an
accurate
method
which
able
most
roots.
Journal of Hematology & Oncology,
Journal Year:
2021,
Volume and Issue:
14(1)
Published: June 25, 2021
Tumors
are
not
only
aggregates
of
malignant
cells
but
also
well-organized
complex
ecosystems.
The
immunological
components
within
tumors,
termed
the
tumor
immune
microenvironment
(TIME),
have
long
been
shown
to
be
strongly
related
development,
recurrence
and
metastasis.
However,
conventional
studies
that
underestimate
potential
value
spatial
architecture
TIME
unable
completely
elucidate
its
complexity.
As
innovative
high-flux
high-dimensional
technologies
emerge,
researchers
can
more
feasibly
accurately
detect
depict
TIME.
These
findings
improved
our
understanding
complexity
role
in
biology.
In
this
review,
we
first
epitomized
some
representative
emerging
study
categorized
description
methods
used
characterize
these
structures.
Then,
determined
functions
biology
effects
gradient
extracellular
nonspecific
chemicals
(ENSCs)
on
We
discussed
clinical
architectures
TIME,
as
well
current
limitations
future
prospects
novel
field.
This
review
will
bring
an
dimension
ecosystem
research,
attention
promote
application
research
practice.
Journal of Personalized Medicine,
Journal Year:
2023,
Volume and Issue:
13(8), P. 1214 - 1214
Published: July 31, 2023
Artificial
Intelligence
(AI)
has
emerged
as
a
transformative
technology
with
immense
potential
in
the
field
of
medicine.
By
leveraging
machine
learning
and
deep
learning,
AI
can
assist
diagnosis,
treatment
selection,
patient
monitoring,
enabling
more
accurate
efficient
healthcare
delivery.
The
widespread
implementation
role
to
revolutionize
patients'
outcomes
transform
way
is
practiced,
leading
improved
accessibility,
affordability,
quality
care.
This
article
explores
diverse
applications
reviews
current
state
adoption
healthcare.
It
concludes
by
emphasizing
need
for
collaboration
between
physicians
experts
harness
full
AI.
Frontiers in Immunology,
Journal Year:
2023,
Volume and Issue:
13
Published: Jan. 17, 2023
Cuproptosis,
a
newly
identified
form
of
programmed
cell
death,
plays
vital
roles
in
tumorigenesis.
However,
the
interconnectivity
cuproptosis
and
ferroptosis
is
poorly
understood.
In
our
study,
we
explored
genomic
alterations
1162
lung
adenocarcinoma
(LUAD)
samples
from
The
Cancer
Genome
Atlas
(TCGA)
Gene
Expression
Omnibus
(GEO)
cohort
to
comprehensively
evaluate
regulators.
We
systematically
performed
pancancer
analysis
by
depicting
molecular
correlations
between
regulators
33
cancer
types,
indicating
cross-talk
at
multiomic
level.
successfully
three
distinct
clusters
based
on
regulators,
termed
CuFeclusters,
as
well
cuproptosis/ferroptosis
gene
subsets.
tumor
microenvironment
cell-infiltrating
characteristics
CuFeclusters
were
highly
consistent
with
immune
phenotypes
tumors.
Furthermore,
CuFescore
was
constructed
validated
predict
pathways
individuals
response
chemotherapeutic
drugs
immunotherapy.
significantly
associated
expression
miRNA
regulation
post-transcription.
Thus,
research
established
an
applied
scoring
scheme,
identify
LUAD
patients
who
are
candidates
for
immunotherapy
patient
sensitivity
drugs.
Advanced Science,
Journal Year:
2024,
Volume and Issue:
11(23)
Published: April 3, 2024
Abstract
The
heterogeneity
of
macrophages
influences
the
response
to
immune
checkpoint
inhibitor
(ICI)
therapy.
However,
few
studies
explore
impact
APOE
+
on
ICI
therapy
using
single‐cell
RNA
sequencing
(scRNA‐seq)
and
machine
learning
methods.
scRNA‐seq
bulk
RNA‐seq
data
are
Integrated
construct
an
M.Sig
model
for
predicting
based
distinct
molecular
signatures
macrophage
algorithms.
Comprehensive
analysis
as
well
in
vivo
vitro
experiments
applied
potential
mechanisms
affecting
response.
shows
clear
advantages
efficacy
prognosis
pan‐cancer
patients.
proportion
is
higher
non‐responders
triple‐negative
breast
cancer
compared
with
responders,
interaction
longer
distance
between
CD8
exhausted
T
(Tex)
cells
confirmed
by
multiplex
immunohistochemistry.
In
a
4T1
tumor‐bearing
mice
model,
combined
treatment
best
efficacy.
real‐world
immunotherapy
accurately
predicts
pan‐cancer,
which
may
be
associated
Tex
cells.
Histopathology,
Journal Year:
2018,
Volume and Issue:
74(3), P. 372 - 376
Published: Oct. 1, 2018
Histopathology
has
undergone
major
changes
firstly
with
the
introduction
of
Immunohistochemistry,
and
latterly
Genomic
Medicine.We
argue
that
a
third
revolution
is
underway:
Artificial
Intelligence
(AI).Coming
on
back
Digital
Pathology
(DP),
AI
potential
to
both
challenge
traditional
practice
provide
totally
new
realm
for
pathology
diagnostics.Hereby
we
stress
importance
certified
pathologists
having
learned
from
experience
previous
revolutions
be
willing
accept
such
disruptive
technologies,
ready
innovate
actively
engage
in
creation,
application
validation
technologies
oversee
safe
into
diagnostic
practice.