Tetraspanin CD9 stabilizes gp130 by preventing its ubiquitin-dependent lysosomal degradation to promote STAT3 activation in glioma stem cells
Cell Death and Differentiation
Tetraspanin CD9 stabilizes gp130 by preventing its ubiquitin-dependent lysosomal degradation to promote STAT3 activation in glioma stem cells
Yu Shi 0 1 2
Wenchao Zhou 2
Lin Cheng 4
Cong Chen 0 1 2
Zhi Huang 2
Xiaoguang Fang 2
Qiulian Wu 2
Zhicheng He 0 1
Senlin Xu 0 1
Justin D Lathia 3
Yifang Ping 0 1
Jeremy N Rich 2
Xiu-Wu Bian 0 1
Shideng Bao 2
0 The Key Laboratory of Tumor Immunopathology, Ministry of Education of China , Chongqing 400038 , China
1 Institute of Pathology and Southwest Cancer Center, Southwest Hospital, The Third Military Medical University , Chongqing 400038 , China
2 Department of Stem Cell Biology and Regenerative Medicine, Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA
3 Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA
4 State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui Jin Hospital, Shanghai Jiao Tong University , Shanghai 200025 , China
Glioblastoma (GBM) is the most malignant and lethal brain tumor harboring glioma stem cells (GSCs) that promote tumor propagation and therapeutic resistance. GSCs preferentially express several critical cell surface molecules that regulate the prosurvival signaling for maintaining the stem cell-like phenotype. Tetraspanin CD9 has recently been reported as a GSC biomarker that is relevant to the GSC maintenance. However, the underlying molecular mechanisms of CD9 in maintaining GSC property remain elusive. Herein, we report that CD9 stabilizes the IL-6 receptor glycoprotein 130 (gp130) by preventing its ubiquitindependent lysosomal degradation to facilitate the STAT3 activation in GSCs. CD9 is preferentially expressed in GSCs of human GBM tumors. Mass spectrometry analysis identified gp130 as an interacting protein of CD9 in GSCs, which was confirmed by immunoprecipitation and immunofluorescent analyses. Disrupting CD9 or gp130 by shRNA significantly inhibited the self-renewal and promoted the differentiation of GSCs. Moreover, CD9 disruption markedly reduced gp130 protein levels and STAT3 activating phosphorylation in GSCs. CD9 stabilized gp130 by preventing its ubiquitin-dependent lysosomal degradation to promote the BMXSTAT3 signaling in GSCs. Importantly, targeting CD9 potently inhibited GSC tumor growth in vivo, while ectopic expression of the constitutively activated STAT3 (STAT3-C) restored the tumor growth impaired by CD9 disruption. Collectively, we uncovered a critical regulatory mechanism mediated by tetraspanin CD9 to maintain the stem cell-like property and tumorigenic potential of GSCs. Cell Death and Differentiation (2017) 24, 167-180; doi:10.1038/cdd.2016.110; published online 14 October 2016
Glioblastoma (GBM) is the most common and aggressive
primary brain tumor with dismal prognosis.1,2 Despite recent
advance in the treatment of other cancers, current therapies
for GBM remain palliative.2 GBM is featured by the remarkable
cellular heterogeneity and differential hierarchies of cancer
cells. Growing evidence supported that a subset of cancer
cells, referred to as glioma stem cells (GSCs) or tumor
initiating cells, are responsible for tumor propagation and
recurrence in GBMs.3–5 Although the cellular origin of GSCs
remains controversial,6 these cells have been demonstrated
to share several typical features of embryonic or somatic stem
cells (i.e., self-renewal capacity and multi-lineage
differentiation potential). GSCs are privileged to drive tumor initiation and
malignant progression.6,7 The potent capacity of GSCs in
promoting tumor progression may be a result of their extensive
potential to maintain cell proliferation and to support malignant
behaviors such as cancer invasion, tumor angiogenesis,
vascular pericyte generation and immune evasion.5,8
GSCs have been found to be enriched in GBMs after
radiation and chemotherapy, and contribute to therapeutic
resistance and tumor re-initiation.3,9 The pivotal role of GSCs
in promoting malignant progression and tumor recurrence in
GBMs indicate that targeting GSCs may significantly improve
GBM treatment and overcome the therapeutic resistance.
Thus, identifying key molecular regulators that control GSC
self-renewal and tumorigenic potential may provide useful
targets for the development of new therapeutic strategies to
effectively improve GBM treatment. Cell surface molecules
that are preferentially expressed in GSCs and regulate critical
signaling for GSC maintenance are particularly amenable to
specific targeting for the development of effective therapeutics
Tetraspanins are a family of cell surface glycoproteins,
which couple multiple trans membrane receptors to function
as key signal organizers or regulators.10,11 Tetraspanins are
featured by four transmembrane domains that form multimeric
complexes with other cell surface proteins to modulate
diverse cellular processes, including cell fusion, adhesion and
motility.10,12 To investigate the role of tetraspanins in the GSC
maintenance, we screened for the tetraspanins preferentially
expressed in GSCs relative to non-stem tumor cells (NSTCs)
and identified tetraspanin CD9 as a GSC-enriched protein. As
a key member of the tetraspanin family, CD9 is closely
associated with malignant progression in a context-dependent
manner. CD9 has a pro-tumorigenic role to promote cancer
invasion and tumor growth in cervical cancer, gastric cancer
and GBM.13–15 In addition, CD9 expression has potential
prognostic value to predict patient survival.16 Moreover, CD9
is associated with the stem cell phenotype in embryonic stem
cells (ES) and hematopoietic stem cells.17–19 Recently, CD9
has been shown to facilitate cell proliferation and tumorsphere
formation of GSCs.15 However, the molecular mechanisms
underlying the CD9 function in GSC maintenance have not
In this study, we used mass spectrometry (MS) analysis to
screen for the potential CD9-interacting proteins and identified
the interleukin-6 (IL-6) receptor subunit gp130 (glycoprotein
130) as a critical binding partner of CD9 in GSCs. Gp130 has a
critical role in mediating IL-6 signaling. Upon the binding
of IL-6 to IL-6Rα, gp130 dimerizes and triggers a signal
transduction to induce STAT3 (signal transducer and activator
of transcription 3) phosphorylation (p-Tyr705), resulting in
nuclear translocation of STAT3 and the active transcription of
the STAT3 downstream genes responsible for cancer cell
proliferation, invasion and tumor angiogenesis.20,21 The
crucial role of the STAT3 activation in maintaining GSC
property has been demonstrated by our laboratory and
others.21–24 We previously showed that the non-receptor
tyrosine kinase bone marrow X-linked non-receptor tyrosine
kinase (BMX) mediates STAT3 hyper-activation in GSCs and
demonstrated that the BMX-mediated STAT3 activation is
required for maintaining GSC self-renewal and tumorigenic
potential.22 However, how BMX kinase is activated by
upstream regulators in this pivotal pathway remains elusive.
Herein we demonstrate that CD9 stabilizes gp130 by blocking
its ubiquitin-dependent lysosomal degradation to promote the
IL6-gp130-BMX-STAT3 signaling for maintaining GSC
selfrenewal and tumorigenic capacity. Our study highlights CD9
as a crucial signal organizer for the gp130-mediated signal
transduction in GSCs, indicating that CD9 is a potential target
for the development of new therapeutics against GSCs to
improve GBM treatment.
Tetraspanin CD9 is preferentially expressed in GSCs. As
tetraspanins have been implicated in tumor malignant
progression,10,11 we sought to identify specific tetraspanins
that are preferentially expressed in GSCs and investigate
their functional significance in GSC maintenance and tumor
growth. We used the published microarray profiles to analyze
tetraspanin expressions between GSCs (n = 12) and
conventional glioma cell lines (CGCs) (n = 32) isolated from
human GBMs (Gene Expression Omnibus; GEO:
GDS3885).25 We found that 4 out of 31 members of the
tetraspanin family, CD9, TSPAN7, TSPAN11 and TSPAN33,
were significantly upregulated in GSCs relative to CGCs
(Po0.05) (Figure 1a). The expressions of these candidates
were further examined in 6 pairs of matched GSCs (CD15+/
CD133+) and NSTCs (CD15−/CD133−) isolated from
patientderived GBM xenografts. The quantitative real-time-PCR
(qRT-PCR) analyses demonstrated that only CD9, but not the
other tetraspanins, was consistently upregulated in all tested
GSCs relative to the matched NSTCs (Supplementary
Figures S1a–d). Consistently, elevated expression of CD9
in GSCs relative to NSTCs was confirmed by
immunofluorescent and immunoblot analyses of CD9 in CD133+/CD15+
GSCs and their matched CD133−/CD15− NSTCs isolated
from human GBMs or GBM xenografts (Figure 1b,
Supplementary Figures S1e and f). To interrogate the
correlation of CD9 and the established GSC markers SOX2
(SRY-related HMG-Box gene 2), OLIG2 (oligodendrocyte
lineage transcription factor 2) and CD133, we performed
immunofluorescent analyses and identified the
co-enrichment of CD9 with these GSC markers in
GSCderived tumorspheres (Figure 1c and Supplementary
Figure S1g). Flow cytometry analyses also confirmed that
CD9 partially overlapped with the established GSC markers
CD15, CD133, cell surface glycoprotein CD44 (CD44) and
integrin α6 in glioma cells isolated from patient-derived GBM
xenografts (Supplementary Figures S1h–o). As GSC
population decreased during the serum-induced differentiation, we
examined the expression of CD9 during GSC differentiation.
A gradual decline of CD9 and the GSC marker SOX2 was
observed during the serum-induced GSC differentiation,
which was accompanied by the increase of the neuronal
marker microtubule associated protein 2 (MAP2), indicating
that CD9 expression was closely associated with GSC status
(Figure 1d). These data demonstrate that tetraspanin CD9 is
preferentially expressed in GSCs in human GBMs and may
represent a new GSC marker.
CD9 is essential for the self-renewal and proliferation of
GSCs. Because CD9 is preferentially expressed in GSCs
relative to NSTCs, we next interrogated the functional
significance of CD9 in the GSC maintenance by disrupting
CD9 with short hairpin RNA (shRNA). The expressions of
endogenous CD9 in D456 and T4121 GSCs were disrupted
by two independent CD9 shRNAs (shCD9-1 and shCD9-2)
as confirmed by immunoblot analyses and flow cytometry
analyses (Supplementary Figures S2a and b). The in vitro
limiting dilution assay demonstrated that silencing CD9
expression significantly inhibited GSC self-renewal, as
demonstrated by the reduced primary tumorspheres and
secondary tumorspheres derived from GSCs expressing
shCD9 relative to those expressing shNT (Figure 1e,
Supplementary Figure S2c and Supplementary Table S1).
Consistently, the tumorsphere formation ability of GSCs was
also impaired by CD9 disruption, resulting in the reduced
tumorsphere numbers and sizes in the GSCs expressing
shCD9 (Supplementary Figures S2d–f). We also examined
D456 T4121 T3359 T3691 T3028 T2297
GSCs + - + - + - + - + - +
Annexin V - FITC
the impact of CD9 disruption on GSC differentiation. GSCs
expressing shCD9 or shNT were cultured in serum-induced
differentiation medium for 5 days. Immunoblot analyses
showed that the levels of astrocytic marker glial fibrillary
acidic protein (GFAP) and neuronal marker MAP2
were significantly elevated in glioma cells expressing shCD9
relative to the control cells expressing shNT (Supplementary
Figure S2g). These results indicate that CD9 disruption could
accelerate GSC differentiation. As CD9 has been
demonstrated to regulate tumor cell viability,26,27 we investigated the
impact of CD9 on GSC proliferation and apoptosis, and found
that CD9 disruption apparently inhibited GSC proliferation
and significantly induced GSC apoptosis (Supplementary
Figure S2h and Figure 1f). Collectively, these data
demonstrate that CD9 is essential for maintaining the self-renewal
and proliferation of GSCs.
CD9 interacts with gp130 to mediate its function in
GSCs. Tetraspanins have been reported to function through
interaction with other membrane proteins, including
cytokine receptors, to regulate the downstream signaling
transduction,12,28 whereas the CD9-binding partner on cell
surface of GSCs has not been defined. To identify the
CD9-interacting proteins in GSCs, we transduced GSCs with
a Flag-tagged CD9, and the CD9 associated protein complex
was then immunoprecipitated with anti-Flag antibody followed
by MS analyses. To this end, we identified gp130, a
transmembrane IL-6 receptor subunit that regulates the activation
of STAT3 signaling, as the top candidate of CD9-interacting
proteins on cell surface (Figure 2a and Supplementary Table
S2). The interaction between CD9 and gp130 was confirmed
by the co-immunoprecipitation assay, as gp130 protein was
detected in the anti-CD9-Flag immunoprecipitated protein
complex and vice versa (Figure 2b and Supplementary
Figure S3a). Furthermore, immunofluorescent analyses
validated the co-localization of CD9 and gp130 in GSC
populations (D456 and T4121) (Figure 2c and d). These data
suggest that CD9 could be functionally associated with gp130
in regulating the GSC phenotype. To address the role of
gp130 on GSC viability and self-renewal property, we used
specific shRNAs against gp130 to disrupt endogenous
gp130 expression in GSCs, and confirmed the effective
disruption of gp130 by immunoblot analyses (Figure 2e and
Supplementary Figure S3b). The cell proliferation analyses
demonstrated that silencing gp130 expression potently
inhibited GSC growth (Figure 2f). Moreover, the
selfrenewal of GSCs was significantly impaired by gp130
disruption, as demonstrated by the reduced tumorspheres
derived from GSCs expressing shgp130 relative to those
expressing shNT (Figure 2g and Supplementary Table S3). In
addition, gp130 disruption promoted GSC differentiation, as
the levels of astrocytic marker GFAP and neuronal marker
MAP2 were elevated in glioma cells expressing shgp130
relative to those expressing shNT (Supplementary
Figure S3c). As CD9 binds to gp130 in GSCs, we next
examined whether the binding of CD9 to gp130 could impact
gp130 in GSCs. Immunoblot analyses showed that disrupting
CD9 by shRNAs markedly reduced gp130 protein levels in
GSCs (Figure 2h), indicating that CD9 may control GSC
maintenance through regulating gp130 protein stability
CD9 stabilizes gp130 by blocking its ubiquitin-dependent
lysosomal degradation. As CD9 bound to gp130 and
disrupting CD9 markedly reduced gp130 protein in GSCs,
we next investigated how CD9 maintained gp130
protein in GSCs. The qRT-PCR results showed that the
mRNA level of gp130 was not affected by CD9 disruption
(Figures 3a and b), thus it is possible that CD9 regulated
gp130 protein at the post-transcriptional level. As
ubiquitindependent degradation affects gp130 stability in multiple
normal and malignant cells,29 we investigated whether CD9
stabilized gp130 by preventing its ubiquitin-dependent
degradation in GSCs. The ubiquitination-dependent protein
degradation may be mediated by either proteasome or
lysosome.30,31 Although both pathways have been reported
in the regulation of gp130,29 only the lysosome inhibitor
chloroquine (CHL), but not the proteasome inhibitor MG132,
could significantly extend the turnover of gp130 protein in
GSCs (Figures 3c, d, Supplementary Figures S4a and b),
suggesting that the lysosome-mediated protein degradation
is the dominant mechanism controlling gp130 protein
stability in GSCs. The ubiquitination assay showed that
CD9 disruption markedly increased poly-ubiquitination of
gp130 protein in GSCs treated with lysosome inhibitor
CHL (Figure 3e). Consistently, whereas disruption of CD9
reduced the gp130 protein level in GSCs, treatment of the
lysosome inhibitor CHL partially restored gp130 protein level
(Figures 3f and g), indicating that CD9 may prevent gp130
from the lysosome-mediated degradation. Taken together,
our results indicate that CD9 stabilizes gp130 by coupling
gp130 and preventing the ubiquitin-dependent lysosomal
degradation of gp130 protein in GSCs.
CD9 is required for the gp130-mediated BMX-STAT3
signaling in GSCs. Because CD9 binds to gp130 and
stabilizes gp130 protein in GSCs, we next investigated
whether CD9 regulates the downstream signaling of gp130
in GSCs. Gp130-mediated signaling is crucial for the
activation of STAT3 pathway in GSCs in response to multiple
cytokines, including IL-6.21 We thus sought to determine the
effect of CD9 disruption on the gp130-mediated IL-6-STAT3
pathway. Immunoblot analyses showed that IL-6 stimulation
activated STAT3 pathway in GSCs, as represented by the
elevated phosphorylations of the downstream signaling
transducer BMX (p-Tyr40) and STAT3 (p-Tyr705)
(Figures 4a and b). However, disrupting CD9 by shRNA
reduced gp130 protein and potently attenuated the
IL-6activated activating phosphorylations of BMX and STAT3 in
GSCs (Figures 4a and b). The association of CD9 expression
and STAT3 activation was also confirmed in human GBMs, as
demonstrated by positive correlation of CD9 level and
p-STAT3 (p-Tyr705) level in human GBMs from TCGA
database (Supplementary Figure S4c). Moreover, the
expressions of STAT3 downstream effectors related to cell
proliferation, including Bcl-xL and c-Myc were attenuated by CD9
disruption (Figures 4c and d). These data demonstrate that
CD9 is required for the gp130-mediated BMX-STAT3
signaling in GSCs.
Identification of gp130 as a CD9-interacting protein
GSCs D456 T4121 100
D456 - GSCs
CHL (100 μM)
to those expressing shCD9 only (Figures 5f and g), indicating
that STAT3-C compromised the suppressive effect of CD9
disruption on GSC maintenance. Collectively, these data
demonstrate that CD9 functions through mediating the
gp130-STAT3 signaling axis to maintain the GSC phenotype.
CD9 promotes GSC-driven tumor propagation through
the gp130-STAT3 signaling axis. Because STAT3
activation is crucial for GBM tumor progression and CD9 is required
for the STAT3 signaling in GSCs, CD9 may have a critical role
in maintaining GSC tumorigenic potential. To determine the
functional significance of CD9 in GSC-driven tumor growth,
T4121 or D456 GSCs expressing luciferase along with
shCD9 or shNT were implanted into mouse brains to examine
the impact of CD9 disruption on GSC tumor growth. The
in vivo bioluminescent imaging showed that silencing CD9
expression markedly impaired GSC-driven intracranial tumor
growth (Figures 6a, b, Supplementary Figures S5a
and b). The retarded tumor sizes of the shCD9-expressing
xenografts relative to the shNT-expressing xenografts were
confirmed by H&E staining (Figure 6c). Consequently, the
survivals of mice bearing the shCD9-expressing xenografts
were significantly extended relative to those bearing the
shNT-expressing xenografts (Figure 6d and Supplementary
Figure S5c). Immunofluorescent analyses confirmed a
significant reduction of CD9-positive tumor cells in the
xenografts expressing shCD9 relative to the control
xenografts (Supplementary Figures S5d and e). As activation of
STAT3 signaling is required for GSC-driven tumor
propagation, we examined the effect of CD9 disruption on the
activating phosphorylation of STAT3 (p-Tyr705) in the
GSCderived xenografts. Immunohistochemical analyses showed
STAT3-C - + - + - +
In vitro limiting dilution assay
GSC proliferation assay
T4121 GSC-derived xenografts
T4121-GSC derived xenografts
- - + + - - + +
much fewer p-STAT3-positive tumor cells in the
shCD9expressing xenografts than the shNT-expressing xenografts
(Figures 6e, f, Supplementary Figures S5f and g). Further
analyses indicated that the xenografts derived from the
shCD9-expressing GSCs contained much fewer
Ki67positive proliferative cells (Figures 6g and h) and much more
TUNEL-positive apoptotic cells relative to the control tumors
(Figures 6i and j), indicating that CD9 disruption significantly
reduced tumor cell proliferation and promoted cell apoptosis
in vivo. Taken together, these data demonstrate that CD9 is
critical for maintaining STAT3 signaling in vivo to support
GSC-driven tumor propagation.
As CD9 disruption inhibited STAT3 activation and
suppressed GSC tumor propagation, we examined whether
ectopic expression of the STAT3-C could rescue the tumor
growth impaired by CD9 disruption. GSCs expressing
luciferase were transduced with STAT3-C along with shCD9
or shNT, and then implanted into mouse brains.
Immunofluorescent analyses confirmed a significant reduction of
CD9positive tumor cells in the shCD9-expressing xenografts
relative to the shNT-expressing xenografts (Supplementary
Figures S6a and b). Bioluminescent analyses showed that
expression of the STAT3-C markedly restored the tumor
growth that was impaired by CD9 disruption (Figures 7a
and b). Restored activation of p-STAT3 (p-Tyr705) was also
detected in the xenografts expressing STAT3-C and shCD9
relative to the xenografts expressing shCD9 alone (Figure 7c).
Consequently, the survivals of mice bearing the xenografts
expressing shCD9 plus STAT3-C were significantly reduced
relative to those bearing the xenografts expressing shCD9
alone (Figure 7d). These results demonstrate that CD9
maintains GSC tumorigenic capacity through promoting
GBM is the most common and lethal primary brain tumor that
is highly resistant to current treatment.2 GSCs are critical
cancer cells that contribute to malignant progression,
therapeutic resistance and tumor recurrence in GBM.5,32 As
STAT3 signaling is commonly activated in GSCs, and the
BMX-mediated STAT3 activation is required for maintaining
the self-renewal and tumorigenic potential of GSCs,21,22,23
disrupting STAT3 signaling pathway may potently disrupt
GSCs and have therapeutic potential. However, targeting
STAT3 transcription factor itself is not clinically achievable, as
STAT3 is required for other functions in normal cells.20,22 Thus,
identification of unique upstream regulators controlling STAT3
activation in GSCs may offer new therapeutic targets for
developing GSC-specific therapeutics to improve GBM
treatment. In this study, we identify tetraspanin CD9 to be
preferentially expressed in GSCs and demonstrate that CD9
is crucial for maintaining STAT3 activation in GSCs. We
uncover that CD9 functions through stabilizing the IL-6
receptor subunit gp130, which in turn promotes the
BMXmediated activating phosphorylation of STAT3. Specifically,
CD9 couples gp130 to block the ubiquitination-dependent
lysosomal degradation of gp130 and promotes the
gp130BMX-STAT3 signaling in GSCs (Figure 8). Thus, tetraspanin
CD9 functions as a key molecular organizer for the
prosurvival STAT3 signaling in GSCs. As targeting CD9 potently
inhibited GSC tumorsphere formation, cell proliferation and
tumor growth, and CD9 is a cell surface protein preferentially
and commonly expressed in GSCs, CD9 represents a unique
molecular target for developing specific therapeutics against
GSCs. In addition, as CD9 expression positively correlates
with glioma tumor grades and predicts poor prognosis of GBM
patients (Supplementary Figure S7), CD9 can also serve as a
useful marker for diagnostic and prognostic determination
CD9 functions through regulating gp130 protein stability to
maintain the self-renewal and tumorigenic potential of GSCs.
Gp130 is a glycoprotein that mediates the activation of key
pro-survival pathways crucial for tumor cell proliferation,
invasion and angiogenesis.21,33,34 Amplification of gp130
gene and the abnormal stabilization of the gp130 protein have
been shown to be closely associated with tumor
progression.33,34 The protein level of gp130 in normal cells is
tightly regulated at the post-translational level by the
ubiquitindependent degradation, endocytosis and caspase-induced
proteolysis.29,35,36 It is highly possible that the abnormally
elevated gp130 protein level in tumor cells may be caused by
dysregulated post-translational processes. Our results
showed that CD9 coupled gp130 to reduce gp130
ubiquitination, thereby sustaining high level of gp130 in GSCs for
maintaining STAT3 activation. As the ubiquitin-dependent
degradation of gp130 in normal cells has been shown to be
mediated by the E3 ligase Cbl when triggered by the IL-6,29 we
speculate that CD9 coupling gp130 may block the Cbl binding
on gp130 to prevent its ubiquitination and lysosomal
degradation in GSCs and our preliminary data support this hypothesis
(Supplementary Figure S8). Of note, although multiple
posttranslational processes participate in the regulation of gp130
stability, it seems that lysosomal degradation is the dominant
mechanism controlling gp130 level in GSCs, because the
lysosome inhibitor CHL but not the proteasome inhibitor
MG132 could potently restore the gp130 protein level in GSCs
(Figures 3c, d, Supplementary Figures S4a and b). In addition,
gp130 can be activated by ligands such as IL-6 or leukemia
inhibitory factor (LIF), and is crucial for signal transductions in
multiple stem cells, including ES and cancer stem cells.37–39 In
GSCs, gp130 is critical for the maintenance of the stem
celllike phenotype of GSCs (Figures 2f and g). As our study
demonstrated that CD9 stabilized gp130 expression, we
speculate that CD9 could also affect LIF-stimulated gp130
downstream signal transduction, which warrants further
The activation of STAT3 pathway is a key downstream
signaling event of gp130. STAT3 signaling has been shown to
be crucial for the maintenance of the stem cell property in ES,
somatic stem cells and cancer stem cells, including
GSCs.22,40,41 As STAT3 has essential roles in several cellular
activities in normal cells and STAT3 is a transcription factor,
direct targeting of STAT3 may cause collateral damage on
normal cells, including somatic stem cells.22,40,41 Our study
demonstrated that disrupting CD9 markedly reduced gp130
protein thus inhibited the activation of STAT3 in GSCs.
Disrupting CD9 potently suppressed GSC tumor growth,
indicating that CD9 is an attractive therapeutic target to halt
STAT3 signaling in GSCs to diminish their tumorigenic
potential. Because CD9 is preferentially expressed in GSCs,
but it is rarely expressed in neural stem cells or other normal
brain cells,15 targeting CD9 may specifically disrupt
GSCdriven tumor progression with minimal impact on the
physiological function of brain. As a cell surface protein, the
tumor-supportive functions of CD9 have been reported to be
neutralized by antibody blockade.14 Thus, CD9 may represent
a potential therapeutic target to improve GBM treatment and
overcome therapeutic resistance. In conclusion, this study
revealed that CD9 stabilizes gp130 protein by blocking its
lysosomal degradation to promote STAT3 signaling and
support GSC tumor propagation and malignant progression.
Targeting CD9 to interrupt the gp130-STAT3 signaling axis
may have therapeutic potential to improve GBM treatment.
Materials and Methods
Isolation and culture of glioma cells. GSCs and matched NSTCs were
isolated from GBM surgical specimens or patient-derived GBM xenografts using
Papain Dissociation System as previously reported.3,7,8,22,42 T4121 xenograft was
derived from an adult GBM tumor (WHO grade IV),22 and D456 (D456-MG)
xenograft was derived from a pediatric GBM.43 To isolate total glioma cells from
GBM tumors, subcutaneous xenografts were collected and cut into small pieces and
then were isolated using the Papain Dissociation System (Worthington Biochemical,
Lakewood, NJ, USA) according to the manufacturer’s instructions. The xenografts
were further mechanically dissociated and the suspension was filtered with a 70 μm
cell strainer (BD Biosciences, San Jose, CA, USA) to remove tissue pieces in the
xenografts. Cells were then cultured in Neurobasal medium (Invitrogen, Carlsbad,
CA, USA) with B27 supplement and growth factors for 6 h to recover surface
antigens, then passed through a 30 μm nylon mesh to obtain a single-cell
suspension. Human tumor cells were separated from host cells by using a Mouse
Cell Depletion Kit (Miltenyi, 130-104-694, San Diego, CA, USA) according to the
manufacturer’s instructions. To sort GSCs and matched NSTCs, glioma cells were
then labeled with the PE-conjugated anti-CD15 (130091375, Miltenyi) and the
APCconjugated anti-CD133 (130090854, Miltenyi) at 4 °C for 40 min followed by
fluorescence-activated cell sorting to isolate the GSCs (CD15+/CD133+) and NSTCs
(CD15−/CD133−). The cancer stem cell property of GSCs was confirmed by
functional analyses (including in vitro limiting dilution assay, cell differentiation assay
and in vivo tumorigenic assay) to assess the self-renewal potential, multi-lineage
differentiation potency and in vivo tumor formation capacity of GSCs as described
previously.3,7,8,22,42 Preferential expressions of GSC markers SOX2, OLIG2,
L1CAM, CD15 and CD133 in GSC populations were validated. The enriched
GSCs were constantly maintained as GBM xenografts and were only dissociated,
sorted and cultured in vitro for functional experiments. GSCs cultured in vitro were
maintained in Neurobasal medium (Invitrogen) with EGF (20 ng/ml, PeproTech,
Rocky Hill, NJ, USA), bFGF (20 ng/ml, PeproTech) and B27 Supplement (20 μl/ml,
Life Technologies, Carlsbad, CA, USA). All GBM cells used in this study have been
authenticated by STR analysis or karyotype analysis and were verified to be
mycoplasma-free. All procedures were performed with informed consents approved
by the institutional ethics committee of Cleveland Clinic and Southwest Hospital, and
were in accordance with the principles of the WMA Helsinki Declaration and the
Department of Health and Human Services Belmont Report.
Microarray analysis using GEO database. Microarray data of GEO
(GEO: GDS3885) were applied to determine the expressions of tetraspanins in 12
cases of GSC lines and 32 cases of CGCs.25 Gene cluster analyses were
performed and visualized using Cluster/Java Treeview (http://bonsai.hgc.jp/
~mdehoon/software/cluster/software.htm). Genes enriched in GSCs were identified
when the ratio of average target expression in GSCs to CGCs was of statistical
Microarray analyses of CD9 from the Rembrandt database and
TCGA database. Correlation of CD9 expression and glioma tumor grades was
analyzed using the Rembrandt database
(https://gdoc.georgetown.edu/gdoc/workflows/translationalResearch) and TCGA database (https://tcga-data.nci.nih.gov/
tcga). The expressions of CD9 and p-STAT3 (p-Tyr705) in human GBMs and
patient survival information were obtained from gene profiling data (Affymetrix
U133A platforms) and protein expression data (MDA_RPPA_Core) from TCGA
Co-immunoprecipitation and MS analyses. For co-immunoprecipitation
analyses of the CD9-binding proteins, GSC-transduced CD9-Flag or control vector
were lysed on ice for 20 min in 20 mM Tris-HCl, pH 7.4, 150 mM NaCl, 5 mM EDTA,
10% glycerol, 1% CHAPS, 1 mM PMSF, 1 mM sodium fluoride, 1 mM sodium
orthovanadate and a protease inhibitor cocktail (Roche, Pleasanton, CA, USA). The
supernatant proteins were incubated with 15 μl of anti-Flag M2 Affinity Gel (A2220,
Sigma, St. Louis, MO, USA) for 14 h at 4 °C with constant rotation. Protein
complexes were washed three times with 0.1% Triton X-100 in PBS and were
competitively eluted with the Flag peptide (Sigma). To detect the binding of gp130
with CD9 or Cbl, the indicated GSCs were lysed and the supernatant proteins were
incubated with 10 μl of anti-gp130 antibody (06-291, Millipore, Billerica, MA, USA)
or 5 μl of isotype IgG (SC-2027, Santa Cruz, Santa Cruz, CA, USA) together with
20 μl of Protein A/G PLUS-Agarose (SC-2003, Santa Cruz) for 14 h at 4 °C with
constant rotation. Protein complexes captured by agarose beads were washed for
three times with 0.1% Triton X-100 in PBS and eluted by boiling in Laemmli buffer.
Samples were subjected to SDS-PAGE followed by silver staining or immunoblot
analysis. For the liquid chromatography-MS analysis, the gel pieces with CD9
immunoprecipitated complex or control were dehydrated in acetonitrile, dried in a
speed vacuum and digested with trypsin. The peptides were extracted from the
polyacrylamide and were evaporated for MS analysis using LTQ-Orbitrap Elite Mass
Spectrometer System (Thermo Scientific, Waltham, MA, USA). The data were
analyzed by using all CID spectra collected in the experiment to search against the
human reference sequence database with the program Sequest, which was
integrated in Proteome Discoverer V1.4. (Thermo Scientific).
Immunoblot analyses. Immunoblot analyses were performed as previously
described.8,44 The primary antibodies used in this study include the following:
antiCD9 (sc-13118, 1:1000, Santa Cruz); anti-gp130 (sc-655, 1:1000, Santa Cruz);
antic-Myc (sc-40, 1:1000, Santa Cruz); anti-Cbl (sc-1651, 1:500, Santa Cruz);
anti-pSTAT3 (p-Tyr705, #9131, 1:1000, Cell Signaling, Danvers, MA, USA); anti-STAT3
(#9139, 1:2000, Cell Signaling); anti-Bcl-xL (#2764, 1:500, Cell Signaling);
anti-pBMX (p-Tyr40, #3211, 1:1000, Cell Signaling); anti-BMX (ab59360, 1:1000, Abcam,
Cambridge, UK); anti-Ubiquitin (646301, 1:500, Biolegend, San Diego, CA, USA);
anti-GFAP (644702, 1:1000, Biolegend); anti-MAP2 (SMI-52 R, 1:1000, Covance,
Princeton, NJ, USA); anti-Flag (637301, 1:1000, Biolegend); anti-GAPDH (#2118,
1:5000, Cell Signaling); and anti-tubulin (T9026, 1:10 000, Sigma).
Ubiquitination assay. Ubiquitination assay was performed as previously
described.45 D456 and T4121 GSCs expressing shCD9 or shNT were treated with
lysosome inhibitor CHL (100 μM) for 14 h, and collected for co-immunoprecipitation
with anti-gp130 antibody (Millipore) followed by immunoblot analyses of ubiquitin.
Precipitation with normal rabbit IgG was used as negative controls. Total cell
lysates (input) were also immunoblotted with antibodies against gp130 (sc-655,
1:1000, Santa Cruz), CD9 (sc-13118, 1:1000, Santa Cruz) and tubulin (T9026,
1:10 000, Sigma).
Immunofluorescent staining and terminal dUTP nick end
labeling staining. Immunofluorescent staining was performed as previously
described using frozen human GBM specimens or GBM xenografts.8,42 Primary
antibodies used in this study include the following: anti-CD9 (sc-13118, Santa Cruz);
FITC-conjugated anti-human CD9 (555371, BD Biosciences); anti-gp130 (sc-655,
Santa Cruz); anti-SOX2 (sc-17320, Santa Cruz); anti-OLIG2 (MABN50, Millipore);
anti-CD133 (PAB12663, Abnova, Walnut, CA, USA); and anti-Ki67 (9615580, Abcam).
Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining was
performed using an Apo-BrdU-Red In Situ DNA Fragmentation Assay Kit (Biovision,
Milpitas, CA, USA) according to the manufacturer’s instructions. Images were
captured using an AMG EVOS FL microscope (Thermo Scientific, Waltham, MA,
USA) or a Leica SP5 spectral confocal microscope (Leica, Buffalo Grove, IL, USA).
The co-localization rate of CD9 and SOX2, OLIG2 or gp130 in cultured GSCs was
determined with three or five randomly selected images using Leica LAS AF Lite
software (Leica, Buffalo Grove, IL, USA). The percentage of CD9+, Ki67+ and TUNEL+
cells in GBM xenografts was determined using Image J software (National Institutes of
Health, Bethesda, MD, USA) under five randomly selected microscopic fields at × 400.
Immunohistochemical staining. Immunohistochemical staining of
p-STAT3 (p-Tyr705) in GBM xenografts was performed using Dako REAL EnVision
Detection System and the anti-p-STAT3 antibody (p-Tyr705, #9145, Cell Signaling)
according to the manufacturer’s protocol (DAKO, Carpinteria, CA, USA). The
images were obtained under a Leica DM4000B microscope equipped with a
QImaging EXi Aqua camera (QImaging, Surrey, BC, Canada). The percentage of
p-STAT3+ cells was quantified in five randomly selected microscopic areas using
Image J software.
In vitro limiting dilution assay. GSCs were implanted into a 96-well plate
at a density of 0, 2, 4, 6, 8, 10 or 12 cells/well with 20 replicates for each
concentration. Seven days after implantation, the numbers of tumorspheres in each
well were determined and the sphere formation efficiency was calculated using
extreme limiting dilution analysis as mentioned previously46 (http://bioinf.wehi.edu.
Cell apoptosis assay. For cell apoptosis assay, GSCs expressing shCD9,
shNT and/or STAT3-C were used to determine apoptotic cell death using the
Annexin V–FITC Apoptosis Detection Kit (BD Pharmingen) according to the
manufacturer’s guidance. Signals of FITC-conjugated Annexin V and PI were
detected using a BD LSR II flow cytometer. Data were analyzed and presented
using FlowJo software (Tree Star).
Cell proliferation assay and tumorsphere formation assay. For cell
proliferation assay, GSCs expressing shCD9, shgp130, shNT and/or STAT3-C were
seeded in 96-well plates (1000 cells per well). The cell viability was determined at the 0,
2, 4 and 6 days after cell seeding using Cell Titer-Glo Luminescent Cell Viability Assay
kit (Promega, Madison, WI, USA) following the manufacturer’s protocol. For tumorsphere
formation assay, GSCs expressing shCD9, shgp130, shNT and/or STAT3-C were plated
in 96-well plates at a density of 1000 cells/well and cultured in Neurobasal medium with
B27 Supplement and growth factors. Tumorsphere numbers and sizes were calculated
at the seventh day after implantation as previously described.22,47
GSC differentiation assay. GSCs were induced to differentiate by
withdrawing growth factors and adding serum to cell culture medium as previously
described.22,47 Briefly, GSCs expressing shCD9, shgp130 or shNT were cultured in
DMEM with 10% FBS and were collected to examine the expressions of CD9, the
GSC marker SOX2, the astrocytic marker GFAP, or the neural marker MAP2 using
Flow cytometry analyses. Mouse FITC-conjugated anti-human CD9
(555371, BD Biosciences, San Jose, CA, USA) and isotype Mouse IgG1κ
(555748, BD Biosciences) were used to determine the percentage of CD9-postive
cells in GSCs expressing shCD9 and shNT. The above-mentioned CD9 flow
antibody and PE-conjugated anti-CD15 (130091375, Miltenyi), APC-conjugated
antiCD133 (130090854, Miltenyi), APC-conjugated anti-CD44 (130098110, Miltenyi),
APC-conjugated anti-Integrin α6 (130097250, Miltenyi) or the corresponding isotype
controls were used to determine the correlation between CD9, CD15, CD133 and
CD44 or Integrin α6. Cells were subjected to flow cytometry analyses using a BD
LSR II flow cytometer. Data were analyzed and presented using FlowJo software
(Tree Star, Ashland, OR, USA).
Lentiviral vectors construction. CD9-shRNA and gp130-shRNA lentiviral
vectors and a non-targeting control shRNA (shNT, SHC002) vector were purchased
from Sigma. The sequences of the shRNAs are listed in Supplementary Table S5.
Lentiviral plasmids expressing Flag-tagged CD9 or Flag-tagged STAT3-C were
constructed by cloning CD9-Flag or STAT3-C-Flag into a
pCDH-MCS-T2a-PuroMSCV vector (System Bioscience, Palo Alto, CA, USA). Lentivirus packaging and
transduction were conducted as described previously.22,42 Cells stably expressing
shCD9, shgp130, CD9-Flag or STAT3-C-Flag were enriched by puromycin selection
for positive clones.
qRT-PCR. qRT-PCR was performed using a Bio-Rad CFX96 Real-Time PCR
Detection System (Bio-rad, Hercules, CA, USA) or an ABI 7900HT Sequence
Detection System (Applied Biosystems, Foster City, CA, USA) as previously
described.8,44 The primer sequences were listed in Supplementary Table S6.
Expression of GAPDH was used for the normalization.
Establishment of orthotopic GBM xenograft. Orthotopic GBM
xenografts were established through intracranial implantation of GBM cells as
previous described.8,42,48 Female C57BL/6 athymic/nude mice or NOG
(NOD/Shiscid/IL-2Rgnull) immunocompromised mice of 4–6 weeks were purchased from
Charles River Laboratories and were housed with no more than five animals per
cage in a vivarium of Lerner Research Institute, Cleveland Clinic. Briefly, GSCs
expressing luciferase were transduced with shCD9 and/or STAT3-C expressing
vector or control vector, and then GSCs (D456 or T4121; 5 × 103 cells per mouse)
were transplanted into the right frontal lobes of each mouse through intracranial
injection (1 mm anterior, 2.5 mm lateral to the bregma and at a depth of 3.5 mm).
Bioluminescence imaging was applied to monitor the tumor growth using IVIS
Spectrum system (PerkinElmer, Waltham, MA, USA) and data were quantified by
Living Image Software (PerkinElmer, Waltham, MA, USA). Animals were maintained
until manifestation of neurological signs. All in vivo experiments were carried out in
accordance with the ARRIVE guidelines and the Guide for the Care and Use of
Laboratory Animals and approved by the Institutional Animal Care and Use
Committee of Cleveland Clinic.
Statistical analysis. Statistical analyses were performed using PASW
Statistics 18 (SPSS Inc., Chicago, IL, USA) and GraphPad Prism 6 (GraphPad,
La Jolla, CA, USA). Kolmogorov–Smirnov test was used to assess the normal
distribution of data. Levene’s test of homogeneity of variances was used to assess
the variation within each group and the variance was similar among groups.
Twotailed unpaired t-test or one-way ANOVA were used to determine the level of
significance, with Po0.05 (*) and Po0.01 (**) being considered with statistical
significance. Bivariate correlation analysis (Pearson r test) was used to examine the
correlation of two variables in human specimens. All data used in this study met the
assumptions of statistical tests. No actions were taken to minimize the effects of
subjective bias. The investigators were not blinded to allocation during experiments
and outcome assessment. The in vitro and in vivo experiments included standard
sample size based on prior studies.8,22,42,45 Neither samples nor animals were
excluded from the analyses. Survival analyses were carried out using Kaplan–Meier
method, with the log-rank test used for comparison. All quantitative data were
presented as mean ± S.D. or mean ± S.E.M. as indicated.
Conflict of Interest
The authors declare no conflict of interest.
Acknowledgements. We thank the Department of Neurosurgery at Southwest
Hospital and the Brain Tumor and Neuro-Oncology Center at Cleveland Clinic for
providing GBM surgical specimens. We appreciate the technical support from
Dr Sage O’Bryant of the Flow Cytometry Core, Drs Judith A Drazba and Eric Diskin of
the Image Core, and Drs Belinda Willard and Ling Li of the Proteomics Laboratory at
Lerner Research Institute, Cleveland Clinic. This research was supported by a China
National Science and Technology Major Project (2016YFA0101203) to Xiu-Wu Bian
and NIH R01 grants (CA184090 and NS091080) to Shideng Bao.
YS, X-WB and SB developed the hypothesis; YS, WZ, LC, X-WB and SB designed
experiments and developed the methodology; YS, WZ, LC, CC, ZH, XF and ZH
performed the experiments, collected and analyzed the data; QW, SX, JDL and YP
provided reagents and technical assistance; YS wrote the manuscript; WZ, JNR,
X-WB and SB revised the manuscript; SB and X-WB supervised the project.
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