Introduction
Alzheimer's disease (AD) is a common
neurodegenerative disease characterized by the deposition of
β-amyloid (Aβ) and hyperphosphorylated τ protein-induced
neurofibrillary tangles, presenting with progressive cognitive
dysfunction and memory loss (1,2).
There were approximately 54.9 million individuals worldwide who are
diagnosed Alzheimer's disease and other dementias in 2021 (3). Its pathogenesis primarily involves
neuroinflammation, synaptic damage and neuronal loss, and there is
no curative treatment at present (4,5).
In an aim to improve the prognosis of patients with AD, in-depth
investigations on the molecular mechanisms of AD and novel targets
have attracted increasing attention (6,7).
Imbalance in microglial M1/M2 polarization serves as
a key mechanism driving neuroinflammation and disease progression
of AD (8-12). Upon pathological stimuli such as
Aβ plaques, microglia primarily polarize into either the
classically activated pro-inflammatory M1 phenotype or the
alternatively activated anti-inflammatory/repair-oriented M2
phenotype (8). M1-type microglia
release tumor necrosis factor-α (TNF-α), IL-1β and nitric oxide
(NO), thereby exacerbating neurotoxicity and τ pathology;
conversely, M2-type microglia highly express arginase-1 (ARG1) and
IL-10, enhance Aβ phagocytosis and clearance and secrete
neurotrophic factors to exert neuroprotection (9,10). In early AD, the M2-type response
predominates to clear pathological proteins, however, as the
disease advances, microenvironmental changes drive microglial
transformation toward the M1 phenotype, leading to chronic
inflammation and neuronal injury (8,11). Thus, promoting microglial
polarization from M1 toward M2 represents a promising therapeutic
strategy to alleviate neuroinflammation in AD (12).
Mucosa-associated lymphoid tissue lymphoma
translocation protein 1 (MALT1) is a paracaspase enzyme serving as
a critical intracellular signaling molecule in both immune
responses and inflammation (13,14). Its primary role involves
mediating NF-κB activation downstream of immune receptors,
including the T and B cell receptor and Toll-like receptors,
thereby regulating immune cell activation and promoting the
expression of pro-inflammatory genes, such as TNF-α (14,15). MALT1 has been reported to be
aberrantly expressed and to participate in the pathogenesis of
various diseases, such as cancer, immune disease and infection
(16-18). Accordingly, targeting MALT1 has
been proposed as a potent treatment of diseases, although further
validation is required (19,20).
In neurological disease, MALT1 is upregulated and is
associated with higher levels of IFN-γ and IL-17 in patients who
have had an acute stroke (21),
and is one of the genes most commonly associated with the
initiation and progression of multiple sclerosis (22). Moreover, the overexpression of
MALT1 promotes NLRP3 inflammasome-mediated inflammation and neural
impairment in diabetes (23) and
the inhibition of MALT1 proteolytic activity by MALT1 inhibitor 2
(MI-2) mitigates spinal ischemia-reperfusion neural injury and
neuroinflammation by regulating glial endoplasmic reticulum stress
(24). MALT1 is able to promote
myocardial oxidative stress in doxorubicin-induced mice (25), and its degradation suppresses
reactive oxygen species (ROS) in the mitochondria of Jurkat cells
(26). As MALT1 promotes NF-κB
pathway activation (14), and
NF-κB signaling serves a crucial role in regulating inflammatory
responses and oxidative stress, MALT1 may contribute to disease
progression by modulating NF-κB-mediated pathological processes
(27), MALT1 may induce
oxidative stress via the activation of NF-κB pathway. A previous
study validated this hypothesis, revealing that MALT1 facilitated
oxidative stress, reflected by levels of NO, superoxide dismutase
and malondialdehyde in sepsis (28). In addition, the analysis based on
the public dataset GSE28146 reveals that MALT1 is upregulated in AD
hippocampus compared with control tissues and public dataset
GSE67835 reveals that MALT1 is abundantly expressed in microglia,
followed by neurons, endothelial and oligodendrocyte precursor
cells, and seldom expressed in other types of cell in human brain
(29,30). Based on the involvement of MALT1
in neurological disease (21-24), its modulation of NF-κB signaling
and inflammation (13-15,31) and the association of NF-κB and
inflammation with AD (32,33), it was hypothesized that targeting
MALT1 may attenuate AD microglial M1/M2 imbalance-mediated
neuroinflammation, neural injury and oxidative stress dependent of
the NF-κB pathway. Therefore, the present study aimed to
investigate the effects of MALT1 inhibition on neuroinflammation,
neuronal loss and oxidative stress based on in vitro AD
models.
Materials and methods
Cells and culture
Human microglia HMC3 (cat. no. iCell-h301) and
neuroblastoma SH-SY5Y (cat. no. iCell-h187) and mouse microglial
BV-2 (cat. no. iCell-m011) and mouse hippocampal neuronal HT-22
(cat. no. iCell-m020) cells were obtained from iCell Bioscience
Inc. HMC3 and SHSY5Y cells were maintained in MEM with Ham's F12
(MEM F12; Wuhan Servicebio Technology Co., Ltd.). BV-2 and HT-22
cells were grown in DMEM (Wuhan Servicebio Technology Co., Ltd.).
All cells were maintained in medium containing 10% FBS
(MilliporeSigma) and penicillin/streptomycin reagent (Wuhan
Servicebio Technology Co., Ltd.) at 37°C and 5% CO2. The
authentication for SH-SY5Y cell line was performed by short tandem
repeat profile.
Preparation of Aβ
Synthetic Aβ (25-35) peptide fragment (MedChemExpress)
was dissolved in sterile distilled water to prepare a 1 mM stock
solution. The peptide solution was incubated at 37°C for 7 days to
allow aggregation prior to use. The aggregated peptide was
aliquoted and stored at −20°C until use. For experiments, the stock
solution was diluted in culture medium immediately before
treatment.
Cell treatment
A co-culture system involving neuronal cells and
conditioned medium (CM) derived from microglia was conducted to
mimic AD pathology in vitro (Fig. 1) (34,35).
HMC3 and BV-2 cells were plated and divided into
blank, Aβ and Aβ + MI-2 groups: The cells in the blank group were
cultured without treatment; cells in the Aβ group were treated with
1 μM Aβ; cells in the Aβ + MI-2 group were treated with 1
μM Aβ and 200 nM MI-2 (MALT1 inhibitor; MedChemExpress),
simultaneously. Following 24 h treatment at 37°C, the supernatant
was harvested as the CM and adopted for ELISA. The HMC3 and BV-2
cells were collected for western blot analysis. For co-culture, the
SH-SY5Y and HT-22 cells were seeded and treated with the CM of HMC3
and BV-2 cells for 24 h at 37°C, respectively. The SH-SY5Y and
HT-22 cells were collected for Cell Counting kit-8 (CCK-8), EdU,
ROS and reduced glutathione (GSH) assay.
Phorbol 12-myristate 13-acetate (PMA, NF-κB
activator; MedChemExpress) was administered to explore whether the
effects of MI-2 were mediated by the NF-κB pathway. The HMC3 and
BV-2 cells were assigned to Aβ, Aβ + MI-2, Aβ + PMA and Aβ + MI-2 +
PMA groups: The cells in the Aβ group were treated with 1 μM
Aβ; cells in the Aβ + MI-2 group were treated with 1 μM Aβ
and 200 nM MI-2, simultaneously; cells in the Aβ + PMA group were
exposed to 1 μM Aβ and 1 μM PMA, simultaneously;
cells in the Aβ + MI-2 + PMA group were treated with 1 μM
Aβ, 200 nM MI-2 and 1 μM PMA, simultaneously. Following 24 h
treatment at 37°C, the cells and CM were collected for further
experiments.
The concentrations of Aβ, MI-2 and PMA were
determined with reference to previous studies (36-38), together with preliminary
dose-response experiments.
Small interfering RNA (siRNA)-mediated
MALT1 knockdown
The HMC3 and BV-2 cells were transfected with 50
pmol siRNA targeting MALT1 or negative control siRNA (siNC) using
siRNA mate plus transfection reagent (all Shanghai GenePharma Co.,
Ltd.) according to the manufacturer's instructions at 37°C for 24
h. As HMC3 and BV-2 cells were of human and murine origin,
respectively, species-specific siRNA sequences were required. The
siMALT1 sequences for HMC3 cells were as follows: Forward), 5'
GAUCAUCUAUACAAGUAUATT 3' and anti-sense (reverse), 5'
UAUACUUGUAUAGAUGAUCTT 3'. The siMALT1 sequences for BV-2 cells were
sense (forward), 5'GCAGCAUGUUGUUGUUACATT 3' and reverse), 5'
UGUAACAACAACAUGCUGCTT 3'. siNC sequences for both cell lines were
as follows: 5' UUCUCCGAACGUGUCACGUTT 3' (forward) and 5'
ACGUGACACGUUCGGAGAATT 3' (reverse).
Following incubation for 24 h at 37°C, the cells
were collected and divided into four groups: The cells in the blank
group received neither siRNA transfection nor Aβ treatment; cells
in the Aβ group were exposed to 1 μM Aβ without siRNA
transfection; cells in the Aβ + siNC group were transfected with
siNC and treated with 1 μM Aβ; cells in the Aβ + siMALT1
group were transfected with siMALT1 and treated with 1 μM
Aβ. Following 24 h treatment at 37°C, the supernatant was harvested
for ELISA and the cells were collected for western blot
analysis.
Western blot analysis
The HMC3 and BV-2 cells were washed and lysed using
the RIPA Lysis kit (Wuhan Servicebio Technology Co., Ltd.) for 30
min. Protein was collected via centrifugation (10,000 × g) at 4°C
for 15 min and detected using the Protein Quantification kit (Wuhan
Servicebio Technology Co., Ltd.). Equal amounts of protein (30
μg/lane) were separated by 4-20% electrophoresis and
transferred onto PVDF membranes (Wuhan Servicebio Technology Co.,
Ltd.). Membranes were blocked via 5% non-fat milk (Wuhan Servicebio
Technology Co., Ltd.) for 1.5 h at room temperature and exposed to
primary antibodies for 1 h at 37°C, including anti-MALT1 (1:500;
cat no. 11660-1-AP), anti-cylindromatosis protein (CYLD) (1:1,000,
cat no. 11110-1-AP), anti-iNOS(both 1:1,000; cat no. 22226-1-AP),
anti-ARG1 (1:5,000; cat no. 16001-1-AP; all Proteintech Group,
Inc.), anti-phosphorylated (p-)p65 (cat no. GB15997), anti-p65
(both 1:1,000; both Wuhan Servicebio Technology Co., Ltd.) (cat no.
GB153882) and anti-GAPDH (1:10,000; cat no. AF7021; Affinity
Biosciences). The HRP conjugated secondary antibodies (1:10,000;
cat no. GB23303; Wuhan Servicebio Technology Co., Ltd.) were
incubated for 0.5 h at room temperature. The blots were visualized
with Super Sensitive ECL Luminescence kit (Meilunbio). Band
intensities were quantified using ImageJ software (Ver1.8; National
Institutes of Health). The integrated density of each target
protein band was normalized to GAPDH.
ELISA
The CM of HMC3 and BV-2 cells was collected and
centrifuged (10,000 × g) at 4°C for 15 min. The supernatant was
employed for ELISA detection using the human and mouse TNF-α (cat
no. ml106471 for human; cat no. ml002095 for mouse) and IL-1β ELISA
kits (cat no. ml058059 for human; cat no. ml106733 for mouse;
Shanghai Enzyme-linked Biotechnology Co., Ltd. according to the
manufacturer's protocols. In brief, the test samples and standard
samples were added to the pre-coated plates for 0.5 h. The plates
were then exposed to enzyme-labeled reagent for 0.5 h. Following
washing, chromogenic solutions were adopted for 15 min. The stop
solution was used and the optical density (OD) values at 450 nm
were read using a microplate reader. Finally, the concentrations of
TNF-α and IL-1β were calculated using the OD values according to
standard curves.
Aβ, MI-2, and PMA direct treatment of the
HT-22 and SH-SY5Y cells
The HT22 and SH-SY5Y cells were seeded and divided
into blank, Aβ, Aβ + MI-2 and Aβ + PMA groups: The cells in the
blank group were cultured without treatment; cells in the Aβ group
were treated with 1 μM Aβ; cells in the Aβ + MI-2 group were
treated with 1 μM Aβ and 200 nM MI-2; cells in the Aβ + PMA
group were exposed to 1 μM Aβ and 1 μM PMA. Following
24 h treatment at 4°C, the cell viability, ROS and GSH levels were
measured.
CCK-8 assay
The SH-SY5Y and HT-22 cells were harvested following
co-culture and re-plated to 96-well plates (3×103
cells/well). Following treatment for 24 h as aforementioned, the
cells were stained with CCK-8 reagent (Wuhan Servicebio Technology
Co., Ltd.) for 2 h. The OD values at 450 nm were measured via the
microplate reader.
EdU staining
The SH-SY5Y and HT-22 cells were washed by PBS
following co-culture, incubated with EdU incubation solution (Wuhan
Servicebio Technology Co., Ltd.) for 2 h at 37°C, blocked with 4%
paraformaldehyde at room temperature for 15 min and incubated with
Click-iT solution (Wuhan Servicebio Technology Co., Ltd.) at room
temperature for 30 min. DAPI (Beyotime Biotechnology) was employed
to stain the nuclei. The fluorescent images were captured using an
inverted fluorescence microscope (Motic Incorporation, Ltd.). The
EdU positive rate was calculated as the number of EdU-positive
cells divided by that of DAPI-positive cells.
ROS staining
The SH-SY5Y and HT-22 cells were washed by PBS
following co-culture and 10 μM DCFH-DA (Beyotime
Biotechnology) was added for 20 min at 37°C. The cells were then
washed with serum-free MEM F12 or DMEM (Wuhan Servicebio Technology
Co., Ltd.). The fluorescent images were captured using an inverted
fluorescence microscope (Motic Incorporation, Ltd.) under identical
acquisition settings, and the fluorescence intensity values were
assessed using ImageJ software (Ver1.8; National Institutes of
Health). The relative ROS levels were calculated as the
fluorescence intensity of experimental groups divided by that of
the blank (MI-2 treatment) or Aβ group (PMA treatment).
GSH
The GSH levels were determined using the GSH Assay
kit (cat. No. E-BC-K030-M; Elabscience Bionovation Inc.). Briefly,
the SH-SY5Y and HT-22 cells were collected and 1×105
cells were lysed in PBS (Wuhan Servicebio Technology Co., Ltd.).
Total GSH detection reagent was added for 25 min at 25°C and OD
values were read at 412 nm. For oxidized GSH (GSSG) detection, GSH
scavenger auxiliary reagents were added before the reaction with
total GSH detection reagent at 25°C for 60 min. GSH levels were
determined via the formula: GSH=total GSH-2 × GSSG. The relative
GSH levels were calculated as the GSH concentrations of
experimental groups divided by that of the blank (MI-2 treatment)
or Aβ group (PMA treatment).
Statistical analysis
The experiments were performed with three
independent biological replicates. Data distribution normality was
assessed using the Shapiro-Wilk test and homogeneity of variances
was evaluated using the Brown-Forsythe test. Data are presented as
the mean ± SD. One-way ANOVA followed by Tukey's test was conducted
to compare differences using GraphPad 9 software (Dotmatics).
P<0.05 was considered to indicate a statistically significant
difference.
Results
MALT1 inhibition by MI-2 regulates the
microglial phenotype, neuroinflammation and NF-κB pathway
MALT1 expression was higher in the Aβ group compared
with the blank group [fold-change (FC)=2.3, P<0.01 in the HMC3
cells and FC=2.1, P<0.05 in the BV-2 cells], however, there was
no significant difference between the Aβ + MI-2 and Aβ groups
(P>0.05 in both the HMC3 and BV-2 cells); conversely, CYLD
expression was lower in the Aβ compared with the blank group
(FC=0.5, P<0.01 in the HMC3 cells and FC=0.4, P<0.05 in the
BV-2 cells), but higher in the Aβ + MI-2 vs. the Aβ group (FC=3.1,
P<0.001 in the HMC3 cells and FC=4.6, P<0.01 in the BV-2
cells; Fig. 2A), indicating that
MALT1 expression was elevated in microglia of AD cell models and
MI-2 treatment suppressed MALT1 proteinase activity.
 | Figure 2Effect of MALT1 inhibition on the
microglial phenotype switch and inflammation. Expression levels of
(A) MALT1 and CYLD, (B) microglial M1 phenotype marker iNOS and the
M2 phenotype marker ARG1 and (C) inflammatory cytokines TNF-α and
IL-1β in HMC3 and BV-2 cells. *P<0.05,
**P<0.01, ***P<0.001. ns, not
significant; MALT, mucosa-associated lymphoid tissue lymphoma
translocation protein; CYLD, CYLD lysine 63 deubiquitinase; iNOS,
inducible nitric oxide synthase; ARG, arginase; Aβ, amyloid-β;
MI-2, MALT1 inhibitor-2. |
iNOS expression was increased in the Aβ compared
with the blank group (FC=2.6, P<0.01 in the HMC3 and FC=2.0,
P<0.001 in the BV-2 cells), but decreased in the Aβ + MI-2 group
compared with the Aβ group (FC=0.7, P<0.05 in both the HMC3 and
BV-2 cells); moreover, ARG1 expression was decreased in the Aβ
group compared with the blank group (both FC= 0.3, P<0.01) in
the HMC3 and BV-2 cells; no significant difference was observed
between the Aβ + MI-2 and Aβ group in the HMC3 cells (P>0.05)
and ARG1 expression was elevated in the Aβ + MI-2 compared with Aβ
group in the BV-2 cells (FC=2.1, P<0.05; Fig. 2B); these findings suggested that
MALT1 inhibition suppressed the microglial M1 phenotype and might
enhance the M2 phenotype in AD cell models.
The TNF-α expression was higher in the Aβ group
compared with the blank group (FC=2.2, P<0.01 in the HMC3 and
FC=3.3, P<0.001 in the BV-2 cells), whereas it was lower in the
Aβ + MI-2 compared with the Aβ group (FC=0.6 in the HMC3 and 0.7 in
the BV-2 cells; both P<0.05). IL-1β expression was elevated in
the Aβ group vs. the blank group in the HMC3 and BV-2 cells
(FC=2.1, P<0.05 in the HMC3 and FC=2.7, P<0.001 in BV-2
cells), while it was only decreased in the Aβ + MI-2 group vs. the
Aβ group in BV-2 cells (FC=0.7, P<0.01), with no significant
difference in the HMC3 cells (FC=0.7, P>0.05; Fig. 2C), suggesting that MALT1
inhibition suppressed neuroinflammation in AD cell models.
p-p65 expression was elevated in the Aβ compared
with the blank group (FC=2.5 in the HMC3 and FC=3.7 in the BV-2
cells; both P<0.01), but was reduced in the Aβ + MI-2 group
compared with the Aβ group (FC=0.5, P<0.05 in the HMC3 cells,
and FC=0.4, P<0.01 in the BV-2 cells; Fig. 3A and B), indicating that MALT1
inhibition blocked the NF-κB pathway in AD cell models.
Microglial MALT1 inhibition by MI-2
regulates neuronal viability and oxidative stress
Cell viability was determined by both the CCK-8
assay OD value and EdU-positive cells; these were lower in the Aβ
compared with the blank group in the SH-SY5Y and HT-22 cells (CCK-8
assay: FC=0.8, P<0.05 in the SH-SY5Y cells, and FC=0.7,
P<0.01 in the HT-22 cells; EdU assay: both FC=0.5, P<0.01),
however, these values were higher in the Aβ + MI-2 group vs. the Aβ
group in the HT-22 cells (CCK-8 assay: FC=1.2; EdU assay: FC=1.6;
both P<0.05), but were not altered in the SH-SY5Y cells (CCK-8
assay: FC=1.1; EdU assay: FC=1.5; both P>0.05; Fig. 4A and B). These findings suggested
that microglial MALT1 inhibition may alleviate neuronal loss in AD
cell models.
The ROS levels increased in the Aβ group compared
with the blank group (FC=5.5, P<0.001 in the SH-SY5Y and FC=4.0,
P<0.01 in the HT-22 cells), but decreased in the Aβ + MI-2 group
compared with the Aβ group (both FC=0.4, P<0.01; Fig. 4C); by contrast, the GSH level
decreased in the Aβ compared with the blank group (FC=0.46,
P<0.01 in the SH-SY5Y and FC=0.71, P<0.05 in HT-22 cells),
but increased in the Aβ + MI-2 group compared with the Aβ group
(FC=1.90, P<0.05 in the SH-SY5Y cells, and FC=1.30, P<0.05 in
the HT-22 cells; Fig. 4D),
suggesting that microglial MALT1 inhibition relieved neuronal
oxidative stress in AD cell models.
NF-κB activation by PMA attenuates the
effects of MALT1 inhibition in microglia
p-p65 expression was elevated in the Aβ + PMA
compared with the Aβ group (FC=2.8 in the HMC3 and FC=2.5 in the
BV-2 cells; both P<0.001), and was increased in the Aβ + MI-2 +
PMA compared with the Aβ + MI-2 group (FC=5.3, P<0.001 in the
HMC3 cells, and FC=5.1, P<0.01 in the BV-2 cells; Fig. 5A and B), indicating that PMA
effectively activated the NF-κB pathway and attenuated the effects
of MALT1 inhibition on the NF-κB pathway in AD cell models.
iNOS expression was higher in the Aβ + PMA compared
with the Aβ group (FC=1.6, P<0.05 in the HMC3 and FC=1.6,
P<0.01 in the BV-2 cells), and was also higher in the Aβ + MI-2
+ PMA compared with the Aβ + MI-2 group (FC=3.0 in the HMC3 cells,
and FC=1.9 in BV-2 cells; both P<0.05); on the contrary, ARG1
expression was lower in the Aβ + PMA compared with the Aβ group
(FC=0.3 in SH-SY5Y cells, and FC=0.4 in the HT-22 cells, both
P<0.05), and was also lower in the Aβ + MI-2 + PMA compared with
the Aβ + MI-2 group (both FC=0.5, both P<0.01 in the HMC3 cells
and BV-2 cells, Fig. 6A); these
findings suggested that NF-κB activation by PMA facilitated the
microglial M1 phenotype, suppressed the M2 phenotype and attenuated
the effects of MALT1 inhibition on the microglial phenotype in AD
cell models.
The levels of TNF-α and IL-1β were increased in the
Aβ + PMA vs. the Aβ group (TNF-α: FC=2.3 in the HMC3 and FC=2.0 in
the BV-2 cells, both P<0.001; IL-1β: FC=2.5, P<0.001 in the
HMC3 and FC=1.6, P<0.01 in the BV-2 cells), which were also
elevated in the Aβ + MI-2 + PMA vs. the Aβ + MI-2 group (TNF-α:
FC=3.3, P<0.01 in the HMC3 and FC=2.5, P<0.001 in the BV-2
cells, IL-1β: FC=3.1, P<0.001 in the HMC3 and FC=2.0, P<0.01
in the BV-2 cells; Fig. 6B),
suggesting that the activation of NF-κB by PMA promoted
neuroinflammation and attenuated the effects of MALT1 inhibition on
neuroinflammation in AD cell models.
Microglial NF-κB activation by PMA
attenuates the effects of microglial MALT1 inhibition on neuronal
viability and oxidative stress
Cell viability was decreased in the Aβ + PMA group
compared with the Aβ group (CCK-8 assay: FC=0.7, P<0.05 in the
SH-SY5Y cells, and FC=0.6, P<0.01 in the HT-22 cells; EdU assay:
both FC=0.4, both P<0.01) and was decreased in the Aβ + MI-2 +
PMA compared with the Aβ + MI-2 group (CCK-8 assay: FC=0.8,
P<0.05 in the SH-SY5Y and FC=0.7, P<0.01 in the HT-22 cells,
EdU assay: FC=0.7, P<0.05 in the SH-SY5Y and FC=0.6, P<0.01
in the HT-22 cells; Fig. 7A and
B), indicating that microglial NF-κB activation by PMA induced
neuronal loss and attenuated the effects of MALT1 inhibition on
neuronal loss in AD cell models.
The ROS levels were increased in the Aβ + PMA
compared with the Aβ group (FC=2.3, P<0.01 in the SH-SY5Y and
FC=1.5, P<0.05 in the HT-22 cells) and in the Aβ + MI-2 + PMA
compared with the Aβ + MI-2 group (FC=4.8, P<0.001 in the
SH-SY5Y cells, and FC=1.7, P<0.05 in the HT-22 cells; Fig. 7C); conversely, the GSH levels
were decreased in the Aβ + PMA compared with the Aβ group (FC=0.5
in SH-SY5Y cells, and FC=0.6 in the HT-22 cells, both P<0.05)
and in the Aβ + MI-2 + PMA compared with the Aβ + MI-2 group
(FC=0.5 in the SH-SY5Y cells, and FC=0.6 in the HT-22 cells, both
P<0.01, Fig. 7D), implying
that microglial NF-κB activation by PMA induced neuronal oxidative
stress and attenuated the effects of MALT1 inhibition on neuronal
oxidative stress in AD cell models.
Effect of direct treatment of MI-2 and
PMA on neuronal viability and oxidative stress
Direct effects of MI-2 and PMA treatments on the
SH-SY5Y and HT-22 cells, without CM or microglia, were determined.
Aβ direct treatment decreased viability (FC=0.9, P<0.01 in the
SH-SY5Y and FC=0.9, P<0.05 in the HT-22 cells) and elevated
oxidative stress (reflected by increased ROS and decreased GSH
levels (ROS level: FC=4.0 in the SH-SY5Y cells, and FC=3.0 in the
HT-22 cells, both P<0.01; GSH: FC=0.8, P<0.05 in the SH-SY5Y
cells, and FC=0.7, P<0.01 in the HT-22 cells), however, neither
MI-2 nor PMA direct treatment altered viability and oxidative
stress in the Aβ-stimulated SH-SY5Y and HT-22 cells (P>0.05;
Fig. S1A-C). In summary, MI-2
and PMA treatments affected the SH-SY5Y and HT-22 cell viability
and oxidative stress via microglia indirectly.
MALT1 knockdown by siMALT1 modifies the
microglial phenotype, neuroinflammation and NF-κB pathway
Considering the specificity of MI-2 and potential
off-target risk, siMALT1 was used to knockdown MALT1 for
validation. MALT1 expression was effectively knocked down following
siMALT1 transfection in both the HMC3 and BV-2 cells (both FC=0.2,
P<0.001; Fig. S2).
siMALT1 downregulated MALT1 expression (FC=0.2 in
the HMC3 cells, and FC=0.1 in the BV-2 cells; both P<0.001) and
iNOS expression (FC=0.5, P<0.01 in the HMC3 and FC=0.6,
P<0.05 in the BV-2 cells), while upregulating ARG1 expression
(FC=1.9 in the HMC3 cells, and FC=1.7 in the BV-2 cells; both
P<0.05) in the Aβ-stimulated HMC3 and BV-2 cells (Fig. S3A). Moreover, siMALT1 decreased
the levels of TNF-α (both FC=0.7, P<0.05 in the HMC3 and BV-2
cells) and IL-1β (FC=0.7, P<0.05 in the HMC3 and FC=0.6,
P<0.01 in the BV-2 cells) and decreased p-p65 expression
(FC=0.4, P<0.01 in the HMC3 cells, and FC=0.5, P<0.05 in the
BV-2 cells) in the Aβ-stimulated HMC3 and BV-2 cells (Fig. S3B and C).
Discussion
As a key paracaspase enzyme regulating immune
responses and inflammation (13-15), MALT1 is dysregulated in immune-
and inflammation-associated diseases (28,39,40). Notably, MALT1 is dysregulated in
neurological disease (21,22). However, the expression of MALT1
in AD remains unclear. The present study demonstrated that MALT1
was upregulated in the microglia of AD cell models, indicating its
key role in the development of AD. MALT1 regulates immunity and
inflammation, which are key contributors to the pathogenesis of AD,
therefore, MALT1 was upregulated in AD cellular models.
Targeting MALT1 through allosteric modulation has
emerged as the dominant strategy for suppressing its proteolytic
activity, with recent medicinal chemistry efforts primarily
directed toward optimizing compounds that bind and disrupt function
at regulatory sites distant from the catalytic center (20). Pharmacological strategies
targeting MALT1 are broadly categorized by their binding
modalities: Irreversible covalent inhibitors and reversible
non-covalent inhibitors (37,41-43). The prototypical covalent
inhibitors MI-2 and JNJ-67856633 exemplify the former class
(37,41,42), whereas MLT-827 represents the
latter approach through its non-covalent allosteric binding
mechanism (43). The
first-developed selective MALT1 inhibitor, MI-2 establishes a
covalent adduct with the nucleophilic Cys464 residue within the
protease catalytic triad, which has been demonstrated to
effectively inhibit MALT1 proteolytic activity and achieve a
sustained target engagement by previous studies (37,44,45). Therefore, the present study used
MI-2 for the inhibition of MALT1 and detected CYLD expression to
validate the suppressed MALT1 proteolytic activity; MI-2
effectively inhibited MALT1 proteolytic activity in AD cell
models.
MALT1 is known for its modification of the immune
cell phenotype and inflammation in multiple diseases, such as
sepsis, experimental colitis, ankylosing spondylitis and spinal
cord injury (28,46-48). However, its role in the
modification of the microglia and the progression of AD remains
unclear. The present study found that the inhibition of MALT1 by
MI-2 suppressed the microglial M1 phenotype and neuroinflammation,
whereas it enhanced the microglial M2 phenotype in AD cell models.
MALT1 promotes microglial differentiation towards the
pro-inflammatory type (M1 phenotype) due to its role in regulating
other immune cells, such as macrophages and CD4+ T cells
(28,46,48); moreover, MALT1 activates the
NF-κB pathway, which is key for the microglial M1 phenotype switch
(14,49), therefore, MALT1 inhibition
suppresses the microglial M1 phenotype, whereas it enhances the M2
phenotype in AD cell models. In addition, the microglial M1
phenotype is associated with exacerbated inflammatory cytokine
secretion and MALT1 directly modifies several inflammatory
pathways, such as NF-κB, JNK and mTOR (14,23,50), which facilitates inflammation;
therefore, MALT1 inhibition suppresses neuroinflammation in AD cell
models. Here, inhibition of MALT1 by MI-2 only increased ARG1
expression (the M2 phenotype marker) in the BV-2 cells, but did not
alter its expression in the HMC3 cells. This may be due to the
differences in response between human and mouse cell lines, or
because MI-2 in human cells affects other pathways that support the
M2 phenotype besides ARG1. The same phenomenon was observed
following MALT1 inhibition of IL-1β levels in BV-2 cells and HMC3
cells, which might result from the differences in response between
human and mouse cell lines.
Dysregulated microglial M1 phenotype polarization
and neuroinflammation exacerbate neuronal loss and oxidative stress
in AD (51,52). Under AD pathological conditions,
the accumulation of Aβ plaque and hyperphosphorylated τ proteins
drive persistent microglial activation toward a pro-inflammatory M1
phenotype, which results in the excessive release of
pro-inflammatory cytokines (IL-1β and TNF-α) and ROS, contributing
to synaptic dysfunction and neuronal apoptosis; concurrently,
microglial M1 phenotype polarization suppresses the neuroprotective
functions of the anti-inflammatory M2 phenotype, including the
diminished secretion of neurotrophic factors, further compromising
neuronal survival (51).
Additionally, neuroinflammation amplifies oxidative stress via
NADPH oxidase activation and other pathways, inducing mitochondrial
dysfunction and lipid peroxidation, that establishes a
self-perpetuating neuroinflammation-oxidative stress loop,
ultimately driving widespread neuronal loss (52). The present study further detected
the effects of microglial MALT1 inhibition by MI-2 on neuronal
viability and oxidative stress, which revealed that microglial
MALT1 inhibition attenuated neuronal loss and oxidative stress in
AD cell models. The potential reason for this is that MALT1
inhibition suppressed the microglial M1 phenotype and
neuroinflammation, and improved neuronal loss and oxidative stress
during AD (51,52).
As the resident innate immune cells of the central
nervous system, microglia exhibit M1 polarization that is
associated with the activation of the NF-κB pathway (53). Upon stimulation, NF-κB
upregulates pro-inflammatory cytokines, such as TNF-α, IL-1β, IL-6
and iNOS, while suppressing anti-inflammatory cytokines, such as
IL-10 and TGF-β, thereby establishing a self-perpetuating
inflammatory loop that exacerbates neuroinflammation during the
development and progression of AD (54,55). Aβ oligomers drive microglial
polarization toward the M1 phenotype via the NLRP3/NF-κB signaling
pathway, contributing to synaptic dysfunction and neuronal
apoptosis; conversely, NF-κB inhibition shifts microglial
polarization toward the M2 phenotype, characterized by the
increased expression of ARG1 and chitinase-like protein 3 and
enhances Aβ phagocytic clearance (56-58). Considering the key function of
MALT1 in regulating NF-κB (13,14), the present study detected whether
NF-κB activation attenuated the effects of MALT1 inhibition in AD
cell models; activation of NF-κB by PMA attenuated the effects of
MALT1 inhibition on microglial phenotype switches and
neuroinflammation, as well as neuronal loss and oxidative stress in
AD cell models. These findings suggested that the protective
effects of MALT1 inhibition were mediated, at least partly, through
modulation of the NF-κB pathway during AD progression.
Several limitations of the present study should be
noted. First, the primary findings are from a limited set of assays
in immortalized cell lines, lacking primary cell validation, human
induced pluripotent stem cell (iPSC)-based models and in
vivo evidence. Future studies incorporating these models are
warranted to validate the proposed mechanism of MALT1 inhibition in
AD. Second, PMA is commonly applied to activate the NF-κB pathway
(38,59); moreover, p-p65 is the key
component implicated in the NF-κB pathway (60,61). However, the causal involvement of
the NF-κB pathway remains to be established, as pathway activation
was mainly assessed by p-p65 expression and PMA may exert effects
beyond NF-κB activation. Further studies using more specific NF-κB
pathway modulators are required to confirm this mechanism. Third,
iNOS and ARG1 are key markers for microglial M1 and M2 types,
respectively, and the inflammatory cytokines including TNF-α and
IL-1β also partially reflect the microglial M1 type (62). Nevertheless, the assessment of
microglial polarization was based on a limited number of M1/M2
markers, which may not fully represent the complex phenotypic
states of microglia. In addition, cell viability assays alone are
insufficient to evaluate neurodegeneration or neuronal loss.
Fourth, although PMA-mediated NF-κB activation attenuated the
effects of MI-2 in the present study, this does not definitively
establish NF-κB as the exclusive downstream mediator of MALT1.
Exploration of alternative pathways (such as JNK, mTOR and
inflammasome-related signaling) is necessary to provide a more
nuanced mechanistic interpretation. Fifth, the blood-brain barrier
permeability, long-term safety and potential immune suppression of
MALT1 inhibition were not assessed in the present study, which are
important for the evaluation of MALT1 as a target for AD.
Future studies are warranted to translate the
present in vitro findings into in vivo contexts.
Specifically, the therapeutic efficacy of MI-2 or genetic MALT1
ablation should be evaluated in amyloid precursor
protein/presenilin 1 transgenic mouse models or Aβ-injected AD
mouse models, with assessments encompassing cognitive behavior,
microglial M1/M2 polarization profiles, amyloid plaque burden,
neuronal survival and oxidative stress markers in brain tissue.
Mechanistically, complementary approaches such as NF-κB-specific
inhibitors (BAY 11-7082), co-immunoprecipitation of the MALT1-B
cell lymphoma/leukemia 10-containing membrane-associated guanylate
kinase protein 1 signaling complex and MALT1 proteolytic activity
probes in vivo may delineate whether NF-κB serves as the
predominant downstream effector or if parallel pathways (JNK and
mTOR) also contribute to phenotypes. Additionally, the
incorporation of microglia-neuron 3D cerebral organoid models may
offer a more physiologically relevant platform to validate the
neuroprotective effects of MALT1 inhibition. These investigations
may inform the translational potential of targeting MALT1 as a
disease-modifying strategy for AD.
In conclusion, the present study demonstrated that
MALT1 inhibition suppressed the microglial M1 phenotype,
neuroinflammation, neuronal loss and oxidative stress in AD, which
may be associated with inactivation of the NF-κB pathway. These
findings suggested its potential as a candidate therapeutic target
of AD.
Supplementary Data
Availability of data and materials
The data generated in the present study may be
requested from the corresponding author.
Authors' contributions
JS and YL conceived and designed the study. XHou and
HX contributed to data analysis. HF, XHan, MN, YS and LZ performed
the data interpretation. JS and YL confirm the authenticity of all
the raw data. All authors have read and approved the final
manuscript.
Ethics approval and consent to
participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing
interests.
Acknowledgements
Not applicable.
Funding
The present study was supported by the 23456 Talent Project of
Henan Provincial People's Hospital (grant nos. ZC23456043 and
ZC2020259).
References
|
1
|
Scheltens P, De Strooper B, Kivipelto M,
Holstege H, Chételat G, Teunissen CE, Cummings J and van der Flier
WM: Alzheimer's disease. Lancet. 397:1577–1590. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Vejandla B, Savani S, Appalaneni R,
Veeravalli RS and Gude SS: Alzheimer's disease: The past, present,
and future of a globally progressive disease. Cureus.
16:e517052024.PubMed/NCBI
|
|
3
|
Zhang Q, Deng Y, Xue M, Ni Z, Luo G and
Tian K: Global trends in Alzheimer's disease and other dementias in
adults aged 55 and above (1992-2021): An age-period-cohort analysis
based on the GBD 2021. PLoS One. 20:e03312042025. View Article : Google Scholar :
|
|
4
|
Nasb M, Tao W and Chen N: Alzheimer's
disease puzzle: Delving into pathogenesis hypotheses. Aging Dis.
15:43–73. 2024.
|
|
5
|
Varadharajan A, Davis AD, Ghosh A, Jagtap
T, Xavier A, Menon AJ, Roy D, Gandhi S and Gregor T: Guidelines for
pharmacotherapy in Alzheimer's disease-a primer on FDA-approved
drugs. J Neurosci Rural Pract. 14:566–573. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Verma A, Kumar Waiker D, Bhardwaj B, Saraf
P and Shrivastava SK: The molecular mechanism, targets, and novel
molecules in the treatment of Alzheimer's disease. Bioorg Chem.
119:1055622022. View Article : Google Scholar
|
|
7
|
Cummings JL, Osse AML and Kinney JW:
Alzheimer's disease: Novel targets and investigational drugs for
disease modification. Drugs. 83:1387–1408. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Guo S, Wang H and Yin Y: Microglia
polarization from M1 to M2 in neurodegenerative diseases. Front
Aging Neurosci. 14:8153472022. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Cai Y, Liu J, Wang B, Sun M and Yang H:
Microglia in the Neuroinflammatory pathogenesis of Alzheimer's
disease and related therapeutic targets. Front Immunol.
13:8563762022. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Li S, Wang Y, Li J, Deng L and Dong Y:
Effect of galectin-1 on classical microglial activation,
neuroinflammation, and neuronal damage in rats exposed to amyloid-β
peptide. Basic Clin Neurosci J. 17:275–284. 2026. View Article : Google Scholar
|
|
11
|
Ahremenko E, Andreev A, Apushkin D and
Korkotian E: Glial cells in the early stages of neurodegeneration:
Pathogenesis and therapeutic targets. Int J Mol Sci. 26:119952025.
View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Yang X, Wang J, Jia X, Yang Y, Fang Y,
Ying X, Li H, Zhang M, Wei J and Pan Y: Microglial polarization in
Alzheimer's disease: Mechanisms, implications, and therapeutic
opportunities. J Alzheimers Dis. 104:3–13. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Hachmann J and Salvesen GS: The
paracaspase MALT1. Biochimie. 122:324–338. 2016. View Article : Google Scholar
|
|
14
|
Afonina IS, Elton L, Carpentier I and
Beyaert R: MALT1-a universal soldier: Multiple strategies to ensure
NF-κB activation and target gene expression. FEBS J. 282:3286–3297.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Zhang YY, Peng J and Luo XJ:
Post-translational modification of MALT1 and its role in B cell-
and T cell-related diseases. Biochem Pharmacol. 198:1149772022.
View Article : Google Scholar : PubMed/NCBI
|
|
16
|
O'Neill TJ, Tofaute MJ and Krappmann D:
Function and targeting of MALT1 paracaspase in cancer. Cancer Treat
Rev. 117:1025682023. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Hailfinger S and Schulze-Osthoff K: The
paracaspase MALT1 in psoriasis. Biol Chem. 402:1583–1589. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Lu HY and Turvey SE: Human MALT1
deficiency and predisposition to infections. Curr Opin Immunol.
72:1–12. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Mempel TR and Krappmann D: Combining
precision oncology and immunotherapy by targeting the MALT1
protease. J Immunother Cancer. 10:e0054422022. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Brvar M, O'Neill TJ, Plettenburg O and
Krappmann D: An updated patent review of MALT1 inhibitors
(2021-present). Expert Opin Ther Pat. 35:639–656. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Chen X, Zhang X, Lan L, Xu G, Li Y and
Huang S: MALT1 positively correlates with Th1 cells, Th17 cells,
and their secreted cytokines and also relates to disease risk,
severity, and prognosis of acute ischemic stroke. J Clin Lab Anal.
35:e239032021. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Rang X, Liu Y, Wang J, Wang Y, Xu C and Fu
J: Identification of multiple sclerosis-related genes regulated by
EBV-encoded microRNAs in B cells. Mult Scler Relat Disord.
59:1035632022. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Ruan Z, Li Y and Chen Y: HECTD3 promotes
NLRP3 inflammasome and pyroptosis to exacerbate diabetes-related
cognitive impairment by stabilising MALT1 to regulate JNK pathway.
Arch Physiol Biochem. 130:373–384. 2024. View Article : Google Scholar
|
|
24
|
Zhang S, Yan Y, Wang Y, Sun Z, Han C, Qian
X, Ren X, Feng Y, Cai J and Xia C: Inhibition of MALT1 alleviates
spinal ischemia/reperfusion injury-induced neuroinflammation by
modulating glial endoplasmic reticulum stress in rats. J Inflamm
Res. 14:4329–4345. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Lu LQ, Li MR, Liu XY, Peng D, Liu HR,
Zhang XJ, Luo XJ and Peng J: CARD11-BCL10-MALT1 complex-dependent
MALT1 activation facilitates myocardial oxidative stress in
doxorubicin-treated mice via enhancing k48-linked ubiquitination of
Nrf2. Antioxid Redox Signal. 42:115–132. 2025. View Article : Google Scholar
|
|
26
|
Lee JE, Bo F, Thuy NTT, Hong J, Lee JS,
Cho N and Yoo HM: Anticancer activity of lesbicoumestan in jurkat
cells via inhibition of oxidative stress-mediated apoptosis and
MALT1 protease. Molecules. 26:1852021. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Oriquat G, Hamed Ahmed M, Al-Hasnaawei S,
Malathi H, Mishra S, Nanda A, Arora V and Chauhan AS: Bridging
neuroinflammation, oxidative stress, and neurogenesis: Aromatic
turmerone as a multifunctional modulator via NF-κB and Nrf2
pathways. Inflammopharmacology. 34:3973–3989. 2026. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Wang Y, Liu Z, Zhang M, Yu B and Ai F:
Mucosa-associated lymphoid tissue lymphoma translocation protein 1
exaggerates multiple organ injury, inflammation, and immune cell
imbalance by activating the NF-κB pathway in sepsis. Front
Microbiol. 14:11172852023. View Article : Google Scholar
|
|
29
|
Blalock EM, Geddes JW, Chen KC, Porter NM,
Markesbery WR and Landfield PW: Incipient Alzheimer's disease:
Microarray correlation analyses reveal major transcriptional and
tumor suppressor responses. Proc Natl Acad Sci USA. 101:2173–2178.
2004. View Article : Google Scholar :
|
|
30
|
Mathys H, Davila-Velderrain J, Peng Z, Gao
F, Mohammadi S, Young JZ, Menon M, He L, Abdurrob F, Jiang X, et
al: Single-cell transcriptomic analysis of Alzheimer's disease.
Nature. 570:332–337. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Demeyer A, Staal J and Beyaert R:
Targeting MALT1 proteolytic activity in immunity, inflammation and
disease: Good or bad? Trends Mol Med. 22:135–150. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Sun E, Motolani A, Campos L and Lu T: The
pivotal role of NF-kB in the pathogenesis and therapeutics of
Alzheimer's disease. Int J Mol Sci. 23:89722022. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Verma Y, Sachdeva H, Kalra S, Kumar P and
Singh G: Unveiling the complex role of NF-κB in Alzheimer's
disease: Insights into brain inflammation and potential therapeutic
targets. Georgian Med News. 133–141. 2023.
|
|
34
|
Zhao KP, Wang XY, Shao MQ, He CY and Yuan
FQ: Silencing of long noncoding RNA X-inactive specific transcript
alleviates Aβ1-42-induced microglia-mediated neurotoxicity by
shifting microglial M1/M2 polarization. Int J Immunopathol
Pharmacol. 37:39463202311849882023. View Article : Google Scholar
|
|
35
|
Cui ZQ, Hu XY, Yang T, Guan JW, Gu Y, Li
HY, Zhang HY, Xiao QH and Sun XH: TMEM16F may be a new therapeutic
target for Alzheimer's disease. Neural Regen Res. 18:643–651. 2023.
View Article : Google Scholar
|
|
36
|
Polini B, Ricardi C, Bertolini A,
Carnicelli V, Rutigliano G, Saponaro F, Zucchi R and Chiellini G:
T1AM/TAAR1 system reduces inflammatory response and β-amyloid
toxicity in human microglial HMC3 cell line. Int J Mol Sci.
24:115692023. View Article : Google Scholar
|
|
37
|
Fontan L, Yang C, Kabaleeswaran V, Volpon
L, Osborne MJ, Beltran E, Garcia M, Cerchietti L, Shaknovich R,
Yang SN, et al: MALT1 small molecule inhibitors specifically
suppress ABC-DLBCL in vitro and in vivo. Cancer Cell. 22:812–824.
2012. View Article : Google Scholar
|
|
38
|
Ding J, Zhang Y and Xu M: Circular RNA
DLGAP4 inhibits ischemic stroke-induced microglia M1 polarization
and proinflammatory cytokine production, possibly through the NF-κB
pathway. Tohoku J Exp Med. 263:277–285. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Zhang L, Li J, Yang Z, Wang S, Liu J, Luan
S and Tian G: Linkage of blood MALT1 with CD4+ T cell subset,
inflammation, lipid, and its potency as a biomarker for predicting
major adverse cardiovascular events in coronary heart disease
patients. Ann Clin Lab Sci. 53:507–515. 2023.PubMed/NCBI
|
|
40
|
Wang M, Huang L, Peng L, Yang Y, Mao J,
Zhu N and Wu B: MALT1 serves as a biomarker for estimating disease
risk of lupus nephritis: A prospective case-control study. Ann
Transl Med. 10:8742022. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Jiang VC, Liu Y, Lian J, Huang S, Jordan
A, Cai Q, Lin R, Yan F, McIntosh J, Li Y, et al: Cotargeting of BTK
and MALT1 overcomes resistance to BTK inhibitors in mantle cell
lymphoma. J Clin Invest. 133:e1656942023. View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Lu T, Connolly PJ, Philippar U, Sun W,
Cummings MD, Barbay K, Gys L, Van Nuffel L, Austin N, Bekkers M, et
al: Discovery and optimization of a series of small-molecule
allosteric inhibitors of MALT1 protease. Bioorg Med Chem Lett.
29:1267432019. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Quancard J, Klein T, Fung SY, Renatus M,
Hughes N, Israël L, Priatel JJ, Kang S, Blank MA, Viner RI, et al:
An allosteric MALT1 inhibitor is a molecular corrector rescuing
function in an immunodeficient patient. Nat Chem Biol. 15:304–313.
2019. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Wu G, Wang H, Zhou W, Zeng B, Mo W, Zhu K,
Liu R, Zhou J, Chen C and Chen H: Synthesis and structure-activity
relationship studies of MI-2 analogues as MALT1 inhibitors. Bioorg
Med Chem. 26:3321–3344. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Wu C, Ge W and Wu Y: Mucosa-associated
lymphoid tissue lymphoma translocation protein 1 inhibitor, MI-2,
attenuates non-small cell lung cancer cell proliferation, migration
and invasion, and promotes apoptosis by suppressing the JNK/c-JUN
pathway. Oncol Lett. 28:4652024. View Article : Google Scholar
|
|
46
|
Nakamura Y, Igaki K, Komoike Y, Yokoyama K
and Tsuchimori N: Malt1 inactivation attenuates experimental
colitis through the regulation of Th17 and Th1/17 cells. Inflamm
Res. 68:223–230. 2019. View Article : Google Scholar
|
|
47
|
Qin H, Wu T, Liu J, Wang G, Fan L, Wang B
and Shen Y: MALT-1 inhibition attenuates the inflammatory response
of ankylosing spondylitis by targeting NF-κB activation. Injury.
52:1287–1293. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
48
|
Zhang H, Sun G, Li X, Fu Z, Guo C, Cao G,
Wang B, Wang Q, Yang S, Li D, et al: Inhibition of MALT1
paracaspase activity improves lesion recovery following spinal cord
injury. Sci Bull (Beijing). 64:1179–1194. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Si W, Li X, Jing B, Chang S, Zheng Y, Chen
Z, Zhao G and Zhang D: Stigmasterol regulates microglial M1/M2
polarization via the TLR4/NF-κB pathway to alleviate neuropathic
pain. Phytother Res. 38:265–279. 2024. View Article : Google Scholar
|
|
50
|
Wang XF, Wang F and Zhou G: MALT1 protease
regulates T-cell immunity via the mTOR pathway in oral lichen
planus. Inflammation. 47:939–957. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Bhardwaj V, Kumari S, Dhapola R, Sharma P,
Beura SK, Singh SK, Vellingiri B and HariKrishnaReddy D: Shedding
light on microglial dysregulation in Alzheimer's disease: Exploring
molecular mechanisms and therapeutic avenues. Inflammopharmacology.
33:679–702. 2025. View Article : Google Scholar
|
|
52
|
Jurcău MC, Andronie-Cioara FL, Jurcău A,
Marcu F, Ţiț DM, Pașcalău N and Nistor-Cseppentö DC: The Link
between oxidative stress, mitochondrial dysfunction and
neuroinflammation in the pathophysiology of Alzheimer's disease:
Therapeutic implications and future perspectives. Antioxidants
(Basel). 11:21672022. View Article : Google Scholar
|
|
53
|
Li R, Jia H, Si M, Li X, Ma Z, Zhu Y, Sun
W, Zhu F and Luo S: Loureirin B protects against cerebral
ischemia/reperfusion injury through modulating M1/M2 microglial
polarization via STAT6/NF-kappaB signaling pathway. Eur J
Pharmacol. 953:1758602023. View Article : Google Scholar
|
|
54
|
Yao K and Zu HB: Microglial polarization:
Novel therapeutic mechanism against Alzheimer's disease.
Inflammopharmacology. 28:95–110. 2020. View Article : Google Scholar
|
|
55
|
Uddin MS, Hasana S, Ahmad J, Hossain MF,
Rahman MM, Behl T, Rauf A, Ahmad A, Hafeez A, Perveen A and Ashraf
GM: Anti-neuroinflammatory potential of polyphenols by inhibiting
NF-κB to halt Alzheimer's disease. Curr Pharm Des. 27:402–414.
2021. View Article : Google Scholar
|
|
56
|
Jin X, Liu MY, Zhang DF, Zhong X, Du K,
Qian P, Yao WF, Gao H and Wei MJ: Baicalin mitigates cognitive
impairment and protects neurons from microglia-mediated
neuroinflammation via suppressing NLRP3 inflammasomes and
TLR4/NF-κB signaling pathway. CNS Neurosci Ther. 25:575–590. 2019.
View Article : Google Scholar : PubMed/NCBI
|
|
57
|
Li P, He Y, Yang Q, Guo H, Li N and Zhang
D: NEK7 inhibition attenuates Aβ42-induced cognitive
impairment by regulating TLR4/NF-κB and the NLRP3 inflammasome in
mice. J Clin Biochem Nutr. 73:145–153. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
58
|
Zhang F, Zhong R, Li S, Fu Z, Cheng C, Cai
H and Le W: Acute hypoxia induced an imbalanced M1/M2 activation of
microglia through NF-κB signaling in Alzheimer's disease mice and
wild-type littermates. Front Aging Neurosci. 9:2822017. View Article : Google Scholar
|
|
59
|
Lei P, Li Z, Hua Q, Song P, Gao L, Zhou L
and Cai Q: Ursolic acid alleviates neuroinflammation after
intracerebral hemorrhage by mediating microglial pyroptosis via the
NF-κB/NLRP3/GSDMD pathway. Int J Mol Sci. 24:147712023. View Article : Google Scholar
|
|
60
|
Giridharan S and Srinivasan M: Mechanisms
of NF-κB p65 and strategies for therapeutic manipulation. J Inflamm
Res. 11:407–419. 2018. View Article : Google Scholar
|
|
61
|
Wang R, Qian Y, Zhou X, Xu H, Wang Y, Geng
Y, Wang T and Sha B: Single-cell sequencing and transcriptomic data
reveal that P65 activation significantly promotes
microglia-mediated neuroinflammation after ischemic stroke. Sci
Rep. 15:177602025. View Article : Google Scholar :
|
|
62
|
Atta AA, Ibrahim WW, Mohamed AF and
Abdelkader NF: Microglia polarization in nociplastic pain:
Mechanisms and perspectives. Inflammopharmacology. 31:1053–1067.
2023. View Article : Google Scholar : PubMed/NCBI
|
