bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 4, 2024
Immune
checkpoint
inhibitors
such
as
anti-PD-1
antibodies
(aPD1)
can
be
effective
in
treating
advanced
cancers.
However,
many
patients
do
not
respond
and
the
mechanisms
underlying
these
differences
remain
incompletely
understood.
In
this
study,
we
profile
a
cohort
of
with
locally-advanced
or
metastatic
basal
cell
carcinoma
undergoing
aPD-1
therapy
using
single-cell
RNA
sequencing,
high-definition
spatial
transcriptomics
tumors
draining
lymph
nodes,
immunoreceptor
profiling,
long-term
clinical
follow-up.
We
find
that
successful
responses
to
PD-1
inhibition
are
characterized
by
an
induction
B-cell
receptor
(BCR)
clonal
diversity
after
treatment
initiation.
These
induced
BCR
clones
spatially
co-localize
T-cell
clones,
facilitate
their
activation,
traffic
alongside
them
between
tumor
nodes
enhance
clearance.
Furthermore,
validated
aPD1-induced
predictor
response
larger
glioblastoma,
melanoma,
head
neck
squamous
patients,
suggesting
is
generalizable
across
types
discover
pre-treatment
harbor
characteristic
gene
expression
signature
portends
higher
probability
inducing
therapy,
develop
machine
learning
model
predicts
PD-1-induced
from
baseline
sequencing.
findings
underscore
dynamic
role
B
during
immunotherapy,
highlighting
its
importance
prognostic
marker
potential
target
for
intervention
non-responders.
Hepatology Communications,
Journal Year:
2025,
Volume and Issue:
9(5)
Published: April 21, 2025
Background:
HCC,
the
most
common
form
of
liver
cancer,
is
one
leading
causes
cancer-related
deaths
worldwide.
Although
immune
system
plays
a
crucial
role
in
cancer
pathogenesis,
landscape
within
metabolic
dysfunction–associated
steatohepatitis–driven
HCC
remains
poorly
understood.
Methods:
In
this
study,
we
used
high-fat,
high-carbohydrate
diet
fed
major
urinary
protein–urokinase-type
plasminogen
activator
mouse
model
HCC.
We
performed
single-cell
RNA
sequencing
on
intrahepatic
cells
to
characterize
their
heterogeneity
and
gene
expression
profiles.
Additionally,
examined
B
antitumor
immunity
by
depleting
μMT
mice
analyzing
effects
progression.
Results:
Our
analysis
revealed
significant
shifts
cell
populations,
including
cells,
T
macrophages
that
undergo
transcriptional
reprogramming,
suggesting
altered
roles
tumor
immunity.
Notably,
an
expanded
subset
activated
showed
signature
associated
with
increased
survival
patients
cancer.
Consistently,
cell-deficient
exacerbated
progression,
substantial
reduction
lymphocytes,
impaired
CD8
+
activation,
may
promote
enhancing
responses.
Conclusions:
findings
reveal
complex
reprogramming
microenvironment
underscore
protective
for
These
results
highlight
as
potential
targets
immunomodulatory
therapies
Frontiers in Immunology,
Journal Year:
2025,
Volume and Issue:
16
Published: April 28, 2025
Cancer
antigen
discovery
has
mostly
focused
on
T
cell
antigens,
while
antigens
driving
B
responses
have
been
largely
overlooked
despite
representing
another
important
branch
of
adaptive
immune
in
cancer.
Traditional
cancer
studied
using
serological
approaches
analyzing
polyclonal
antibodies
serum.
With
recent
technological
advances
single-cell
sequencing,
a
few
studies
begun
to
investigate
single
specificity
the
tumor
microenvironment
immunoglobulin
recombinant
monoclonal
antibody
production,
binding
screening,
and
identification.
In
this
review,
we
highlight
initial
insights
into
directed
categorize
them
cancer-associated
viral
non-viral
with
latter
featuring
autoantigens.
We
will
further
discuss
functions
cells
context
their
specificity,
effector
function,
activation,
secretion.
Lastly,
provide
perspectives
challenges
opportunities
identification
new
translational
potential.
Proceedings of the National Academy of Sciences,
Journal Year:
2025,
Volume and Issue:
122(18)
Published: May 2, 2025
Immune
checkpoint
inhibitors
such
as
anti-Programmed
Death-1
antibodies
(aPD-1)
can
be
effective
in
treating
advanced
cancers.
However,
many
patients
do
not
respond,
and
the
mechanisms
underlying
these
differences
remain
incompletely
understood.
In
this
study,
we
profile
a
cohort
of
with
locally
or
metastatic
basal
cell
carcinoma
undergoing
aPD-1
therapy
using
single-cell
RNA
sequencing,
high-definition
spatial
transcriptomics
tumors
draining
lymph
nodes,
immunoreceptor
profiling,
long-term
clinical
follow-up.
We
find
that
successful
responses
to
PD-1
inhibition
are
characterized
by
an
induction
B
receptor
(BCR)
clonal
diversity
after
treatment
initiation.
These
induced
BCR
clones
spatially
colocalize
T
clones,
facilitate
their
activation,
traffic
alongside
them
between
tumor
nodes
enhance
clearance.
Furthermore,
validated
aPD-1-induced
predictor
response
larger
glioblastoma,
melanoma,
head
neck
squamous
patients,
suggesting
is
generalizable
across
types
pretreatment
harbor
characteristic
gene
expression
signature
portends
higher
probability
inducing
therapy,
develop
machine
learning
model
predicts
PD-1-induced
from
baseline
sequencing.
findings
underscore
dynamic
role
during
immunotherapy,
highlighting
its
importance
prognostic
marker
potential
target
for
intervention
non-responders.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 4, 2024
Immune
checkpoint
inhibitors
such
as
anti-PD-1
antibodies
(aPD1)
can
be
effective
in
treating
advanced
cancers.
However,
many
patients
do
not
respond
and
the
mechanisms
underlying
these
differences
remain
incompletely
understood.
In
this
study,
we
profile
a
cohort
of
with
locally-advanced
or
metastatic
basal
cell
carcinoma
undergoing
aPD-1
therapy
using
single-cell
RNA
sequencing,
high-definition
spatial
transcriptomics
tumors
draining
lymph
nodes,
immunoreceptor
profiling,
long-term
clinical
follow-up.
We
find
that
successful
responses
to
PD-1
inhibition
are
characterized
by
an
induction
B-cell
receptor
(BCR)
clonal
diversity
after
treatment
initiation.
These
induced
BCR
clones
spatially
co-localize
T-cell
clones,
facilitate
their
activation,
traffic
alongside
them
between
tumor
nodes
enhance
clearance.
Furthermore,
validated
aPD1-induced
predictor
response
larger
glioblastoma,
melanoma,
head
neck
squamous
patients,
suggesting
is
generalizable
across
types
discover
pre-treatment
harbor
characteristic
gene
expression
signature
portends
higher
probability
inducing
therapy,
develop
machine
learning
model
predicts
PD-1-induced
from
baseline
sequencing.
findings
underscore
dynamic
role
B
during
immunotherapy,
highlighting
its
importance
prognostic
marker
potential
target
for
intervention
non-responders.