- Open Access
NF-κB induces miR-148a to sustain TGF-β/Smad signaling activation in glioblastoma
© Wang et al.; licensee BioMed Central. 2015
- Received: 6 August 2014
- Accepted: 2 December 2014
- Published: 11 February 2015
Inflammatory cytokines and transforming growth factor-β (TGF-β) are mutually inhibitory. However, hyperactivation of nuclear factor-κB (NF-κB) and TGF-β signaling both emerge in glioblastoma. Here, we report microRNA-148a (miR-148a) overexpression in glioblastoma and that miR-148a directly suppressed Quaking (QKI), a negative regulator of TGF-β signaling.
We determined NF-κB and TGF-β/Smad signaling activity using pNF-κB-luc, pSMAD-luc, and control plasmids. The association between an RNA-induced silencing complex and QKI, mitogen-inducible gene 6 (MIG6), S-phase kinase–associated protein 1 (SKP1), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA was tested with microribonucleoprotein immunoprecipitation and real-time PCR. Xenograft tumors were established in the brains of nude mice.
QKI suppression induced an aggressive phenotype of glioblastoma cells both in vitro and in vivo. Interestingly, we found that NF-κB induced miR-148a expression, leading to enhanced-strength and prolonged-duration TGF-β/Smad signaling. Notably, these findings were consistent with the significant correlation between miR-148a levels with NF-κB hyperactivation and activated TGF-β/Smad signaling in a cohort of human glioblastoma specimens.
These findings uncover a plausible mechanism for NF-κB–sustained TGF-β/Smad activation via miR-148a in glioblastoma, and may suggest a new target for clinical intervention in human cancer.
Glioblastoma multiforme (GBM) is the most common and lethal primary brain tumor in adults; it has a spectrum of aberrantly aggressive phenotypes . Although non-metastasizing, and the despite advances in treatments over the past decades, the extensive invasion of GBM limits patient survival to approximately 12–14 months [2, 3]. The extremely poor prognosis of patients with GBM is due to the ability of GBM to diffusely infiltrate the cerebral cortex, which limits the extent of surgical resection and high-dose radiotherapy for fear of unacceptable permanent neurological damage to the patient. Poor blood–brain barrier penetration, intrinsic GBM resistance, and nonselective toxicity restrict the value of traditional chemotherapy . Therefore, the development of improved therapies rests on further understanding of the molecular mechanism of the aggressive malignant phenotype of GBM. However, this remains largely unclear.
Transforming growth factor-β (TGF-β) is a multifunctional polypeptide that can switch from being a tumor suppressor in normal or dysplastic cells to a tumor promoter in advanced cancers [5–7]. Although TGF-β is a notable tumor suppressor in most cases, it promotes proliferation, invasion, metastasis, and intratumoral angiogenesis in non-epithelial cancer such as glioma [8–15]. Interestingly, TGF-β usually suppresses nuclear factor-κB (NF-κB) activity in normal cells, and NF-κB activation induces Smad7 expression, which in turn inhibits TGF-β signaling through Smads [16, 17]. However, NF-κB and TGF-β pathway activation both emerge in glioma . This indicates the possibility of cross-talk between NF-κB and TGF-β signaling in cancer, which remains poorly understood.
The RNA-binding protein Quaking (QKI) belongs to the signaling transduction and activation of RNA (STAR) protein family . The three QKI isoforms, QKI-5, QKI-6, and QKI-7, which share an RNA-binding hnRNPK homology (KH) domain, can dimerize with one another and shuttle between the cytoplasm and the nucleus [20, 21]. The QKI gene is implicated as being important in schizophrenia, and QKI controls the translation of many oligodendrocyte-related genes [22, 23]. QKI expression is also a characteristic of glial progenitors, and a high frequency of deletion of chromosome 6q26-27, containing QKI, was observed in anaplastic astrocytoma and GBM [24–27]. Chen and team validated the finding that QKI suppresses GBM by stabilizing microRNA-20a (miR-20a), which targets TGF-β receptor 2 (TGFβR2) . The potential importance of QKI in GBM pathogenesis is elevated further by its direct regulation by the tumor suppressor TP53 . However, the frequency of TP53 mutations is about 70% in GBM , which means that TP53 may not regulate QKI in most cases. Taken together, we suspect that there may be an alternative regulatory mechanism of QKI protein expression in GBM.
Being able to coordinately regulate target gene repertoires, miRNAs can potentially modulate multiple steps of cancer development and progression [31, 32]. From analysis using a published microarray-based high-throughput assessment, we found that miR-148a expression is significantly higher in GBM tissues than in normal brain tissue. Herein, we report that miR-148a was induced by NF-κB and directly targeted and suppressed the 3′ untranslated regions (3′ UTRs) of multiple genes that function as negative regulators of TGF-β, leading to TGF-β hyperactivation and GBM aggressiveness. These results identified a regulatory mechanism that results in sustained TGF-β activation in human GBM, thereby supporting the functional and clinical significance of epigenetic events in cancer progression.
Reduced QKI levels in glioblastoma correlated with patient prognoses
MiR-148a targeted QKI
QKI is located on chromosome 6q26-27, which is frequently deleted in astrocytoma and glioblastoma. Interestingly, integrative analysis using the cBioPortal for Cancer Genomics (http://cbioportal.org) indicated that approximately 70% of the QKI gene is not deleted in glioblastoma (Additional file 1: Figure S1A). Given the QKI promoter hypomethylation (Additional file 1: Figure S1B), DNA methylation is unlikely to be the major mechanism responsible for the downregulation of QKI. Chen et al found that TP53 regulates QKI directly; however, most TP53 mutations in glioblastoma do not feature QKI deletion (Additional file 1: Figure S1C). Moreover, real-time PCR analysis revealed no appreciable alteration of QKI mRNA expression in glioblastoma tissue compared with normal brain tissue (Additional file 1: Figure S1D), which suggests that the reduction of QKI protein in glioblastoma is not due to transcriptional inhibition.
MiR-148a targeted SKP1 and activated TGF-β signaling
MiR-148a overexpression correlated with glioblastoma progression
MiR-148a upregulation augmented glioblastoma aggressiveness in vitroand in vivo
QKI and SKP1 played important roles in miR-148a–induced glioblastoma cell invasiveness and angiogenesis
NF-κB induced miR-148a in glioblastoma
MiR-148a expression correlated with NF-κB activity and TGF-β/Smad pathway hyperactivation in clinical glioblastoma
The key finding of the present study is that NF-κB increases miR-148a expression to sustain the TGF-β/Smad signaling pathway by downregulating QKI and SKP1. We demonstrate that NF-κB binds directly to the miR-148a promoter to regulate miR-148a expression. Furthermore, QKI and SKP1 are bona fide targets of miR-148a. QKI and SKP1 inhibition led to the induction of TGF-β/Smad signaling activity. Ectopic miR-148a expression dramatically promoted glioblastoma aggressiveness both in vitro and in vivo. Importantly, the significant correlation detected among miR-148a levels, NF-κB, and TGF-β/Smad signaling hyperactivation was confirmed in a cohort of human glioblastoma samples. Hence, the NF-κB/miR-148a/TGF-β pathway represents a critical mechanism for promoting glioblastoma aggressiveness.
QKI is a tumor suppressor in several cancers, including oral cancer, prostate cancer, colorectal cancer, gastric cancer, and brain cancer [28, 39–42]. However, the biological effect of QKI on cancer development and progression remains unclear. In the present study, statistical analysis of clinical specimens revealed, for the first time, that QKI is associated with shorter overall survival of patients with glioblastoma, supporting the notion that QKI functions as a tumor suppressor. In addition to the genome mutations or deletions that can lead to QKI downregulation , the loss of QKI expression can also be regulated at the transcriptional level. For example, TP53 regulated QKI expression in glioma cells by directly targeting its promoter . However, the present study found no appreciable alteration of QKI mRNA expression in glioblastoma tissues compared with normal brain tissues, which intimates that translational repression might regulate the loss of QKI expression in glioblastoma. Analyses using publicly available algorithms and the present results identified QKI as a direct target of miR-148a in glioblastoma.
Interestingly, we found that NF-κB activation increased the expression of miR-148a, whose promoter contains NF-κB target elements. From the above results, we conclude that NF-κB signaling is probably hyperactivated in glioblastoma, thereby inducing miR-148a expression but reducing QKI expression. In fact, hyperactive signaling correlates with glioma progression and poor prognosis of patients with malignant glioma [43–46]. Thus, the present study uncovers a novel mechanism that regulates QKI expression in glioblastoma.
Despite therapeutic advancements, treating malignant glioma remains a challenge due to ineffective targeting of infiltrating glioma cells and the formation of abnormal, dysfunctional tumor vasculature [11, 47, 48]. TGF-β signaling is highly active in glioblastoma, and elevated TGF-β activity has been associated with poor clinical outcome in this disease . The TGF-β/Smad pathway is considered a therapeutic target in glioma [50, 51]. QKI suppresses TGF-β signaling in glioblastoma, and SKP1 is an essential component of the E3 ubiquitin ligase complex ROC1-SCFFbw1a, which induces Smad3 ubiquitination. As both QKI and SKP1 are bona fide targets of miR-148a, we suspect that miR-148a is involved in TGF-β activation. We found that miR-148a enhances the strength and prolongs the duration of TGF-β/Smad signaling. Via TCGA database analysis, we found that miR-148a was significantly associated with shorter overall survival in patients with glioblastoma, and correlated positively with TGF-β/Smad signaling activity (P < 0.05). These findings suggest that miR-148a expression could be sufficient for activating TGF-β/Smad signaling.
TGF-β and inflammatory cytokines such as TNF-α and IL-1β are mutually inhibitory. Curiously, the NF-κB and TGF-β signaling pathways are both hyperactive in glioblastoma. Focusing on this issue, Song et al. reported that TGF-β induced miR-182 to sustain NF-κB activation in glioma subsets . However, they did not clarify the sustained activation of TGF-β. Sustained activation of regulatory programs requires orchestrated transcription and post-transcriptional regulation of gene expression. Due to their multi-targeting properties and the network effect, miRNAs are perfectly suited to the task. Here, we showed that miR-148a directly repressed QKI and SKP1, which inhibited the TGF-β pathway. Interestingly, we also found that NF-κB induced miR-148a expression. Thus, it is plausible that miR-148a modulates NF-κB–mediated TGF-β activation through multiple mechanisms. On the other hand, analysis of the TCGA datasets indicated that miR-148a promotes glioblastoma aggressiveness. These observations indicate that further investigation of the effect of miR-148a on the TGF-β pathway in glioblastoma is warranted.
In summary, the present study provides an important link between NF-κB and TGF-β signaling via miR-148a in glioblastoma. Our findings suggest an essential role of miR-148a in regulating GBM cell progression. Understanding the precise role played by miR-148a in GBM progression will not only increase our knowledge of the pathogenesis of gliomas, but also will enable the development of novel therapeutic strategies and the identification of an effective biomarker for predicting outcomes for patients with malignant gliomas.
Primary normal human astrocytes (NHAs) were purchased from ScienCell Research Laboratories (Carlsbad, CA, USA) and cultured according to the manufacturer’s instructions. Glioma cell lines A172, T98G, LN18, LN229, U138MG, U87, and U118MG were from ATCC (Manassas, VA, USA). The cells were grown in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum.
Plasmids, virus production, and target cell infection
The human MIR148A gene was PCR-amplified from genomic DNA and cloned into a pMSCV-puro retroviral vector. MiR-148a sponge was constructed by annealing, purifying, and cloning oligonucleotides containing six tandem “bulged” miR-148a–binding motifs into the pMSCV vector. Negative control 1(NC1) is a chemically synthesized double-stranded small RNA used as negative control for miR-148a mimic. NC2 is a chemically synthesized single-stranded RNA molecule used as negative control for miR-148a inhibitor. Both of these negative control molecules exhibit minimum homology to any human, mouse or rat miRNAs annotated in the current released of the miRBase database, and no significant homology to the genomes of those three species as established by sequence alignment. Human QKI and SKP1 (S-phase kinase–associated protein 1) were PCR-amplified from NHA complementary DNA (cDNA) and cloned into the pMSCV vector. The 3′ UTRs of the human QKI (QKI-3′UTR) and SKP1 (SKP1-3′UTR) genes, generated by PCR amplification from NHAs, were cloned into the SacI/XmaI sites of pGL3 luciferase reporter plasmid (Promega, Madison, WI, USA) and pEGFP-C3 vector (Clontech, Mountain View, CA USA). The pNF-κB-luc, pSMAD-luc, and control plasmids (Clontech) were used to determine NF-κB and TGF-β/Smad signaling activity. Plasmid transfection was performed using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. Stable cell lines expressing miR-148a and miR-148a sponge were generated via retroviral infection using HEK293T cells as described by Li et al.  and selected with 0.5 μg/mL puromycin for 10 days.
Tissue specimens and patient information
A total 167 paraffin-embedded, archived clinical glioma specimens comprising World Health Organization (WHO) grade I–IV tumors and 12 freshly snap-frozen glioma tissues were histopathologically diagnosed at the Third Affiliated Hospital of Sun Yat-sen University from 2000 to 2010. Normal brain tissues were obtained from individuals who had died in traffic accidents and who were confirmed to be free of any preexisting pathologically detectable conditions. Prior donor consent and approval from the Institutional Research Ethics Committee were obtained.
Western blotting analysis
Cells and tissues were harvested in sampling buffer [62.5 mmol/L Tris-HCl (pH 6.8), 10% glycerol, 2% sodium dodecyl sulfate (SDS)] and heated for 5 minutes at 100°C. Protein concentration was determined with the Bradford assay using a commercial kit purchased from Bio-Rad Laboratories (Hercules, CA, USA). Equal quantities of protein were separated electrophoretically on 10% SDS/polyacrylamide gels and transferred onto polyvinylidene difluoride membranes (Roche, Basel, Switzerland). The membranes were probed with diluted antibody. The expression of target proteins was determined with horseradish peroxidase–conjugated anti-rabbit immunoglobulin G (IgG)/anti-mouse IgG (Sigma-Aldrich, St Louis, MO, USA) and enhanced chemiluminescence (Pierce, Rockford, IL, USA) according to the manufacturers’ suggested protocols. The membranes were stripped and reprobed with an anti–β-actin mouse monoclonal antibody (Sigma-Aldrich) as a loading control. The related antibodies were anti-Smad2/3, anti–NF-κB inhibitor (IκBα), anti–matrix metalloproteinase 9 (MMP9), anti–phosphorylated (p)-Smad2, anti–p-Smad3, anti-Smad2, anti–vascular endothelial growth factor (VEGF) (Cell Signaling Technology, Beverly, MA, USA), anti-QKI, and anti–green fluorescent protein (GFP) (Abcam, Cambridge, MA, USA).
Immunohistochemical (IHC) analysis was performed to study altered protein expression in 167 clinical glioma tissue sections. In brief, paraffin-embedded specimens were cut into 4-μm sections and baked at 65°C for 30 minutes. The sections were deparaffinized with xylenes and rehydrated. Sections were submerged in EDTA antigenic retrieval buffer and microwaved for antigen retrieval. The sections were treated with 3% hydrogen peroxide in methanol to quench the endogenous peroxidase activity, followed by incubation with 1% bovine serum albumin to block nonspecific binding. The sections were incubated with antibody overnight at 4°C. After washing, the tissue sections were treated with biotinylated anti-rabbit/mouse secondary antibody (Zymed, San Francisco, CA, USA), followed by incubation with streptavidin–horseradish peroxidase complex (Zymed). The tissue sections were immersed in 3-amino-9-ethyl carbazole and counterstained with 10% Mayer’s hematoxylin, dehydrated, and mounted in Crystal Mount (Biomeda, Foster City, CA, USA).
RNA extraction and real-time quantitative PCR
Total miRNA from cultured cells and fresh surgical glioblastoma tissues was extracted using a mirVana miRNA Isolation Kit (Ambion, Foster City, CA, USA) according to the manufacturer’s instructions. We synthesized cDNA using a TaqMan MicroRNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA) and quantified miR-148a expression using a miRNA-specific TaqMan MiRNA Assay Kit (Applied Biosystems). Real-time PCR was performed using the Applied Biosystems 7500 Sequence Detection System. MiRNA expression was defined based on the comparative threshold (Ct); relative expression levels were calculated as 2 - (Ct miR-148a - Ct U6) after normalization with reference to the quantification of U6 small nuclear RNA expression.
Microribonucleoprotein immunoprecipitation assay
Cells were cotransfected with a plasmid that encodes hemagglutinin-tagged (HA)-Ago1 and miR-148a (100 nM), followed by HA-Ago1 immunoprecipitation (IP) using an anti-HA antibody. Real-time PCR analysis of the IP material was used to test the association of QKI, mitogen-inducible gene 6 (MIG6), SKP1, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA with the RNA-induced silencing complex.
Cells (3 × 103) were seeded in triplicate in 48-well plates and allowed to settle for 24 hours. Luciferase reporter plasmids (100 ng) or 100 ng control luciferase plasmid plus 1 ng pRL-TK Renilla plasmid (Promega) were transfected into glioblastoma cells using Lipofectamine 2000 (Invitrogen). Luciferase and Renilla signals were determined 24 hours after transfection using a Dual Luciferase Reporter Assay Kit (Promega).
Cell invasion assay
Glioblastoma cells (2 × 104) were plated on the top side of a polycarbonate Transwell filter (with Matrigel) in the top chamber of a BioCoat Invasion Chamber (BD Biosciences, Bedford, MA, USA) and incubated at 37°C for 22 hours; cells in the top chamber were removed with cotton swabs. Cells that had migrated and invaded to the lower membrane surface were fixed in 1% paraformaldehyde, stained with hematoxylin, and counted under a microscope (10 random fields per well, ×100 magnification). The cell counts were expressed as the mean number of cells per field.
Human umbilical vein endothelial cell tubule formation assay
Matrigel (200 μL; BD Biosciences) was pipetted into each well of a 24-well plate and polymerized for 30 minutes at 37°C. Human umbilical vein endothelial cells (HUVECs) (2 × 104) in 200 μL conditioned medium were added to each well and incubated at 37°C in 5% CO2 for 20 hours. Photographs were captured under a × 100 bright-field microscope, and the capillary tubes were quantified by measuring the total lengths of the completed tubule structure. Each condition was assessed at least in triplicate.
Chorioallantoic membrane assay
Chorioallantoic membrane (CAM) assay was performed using fertilized, day 6 chicken eggs (Yueqin Breeding Co. Ltd., Guangdong, China). A 1-cm wide window was opened on the egg shell and the surface of the dermic sheet on the floor of the air sac was removed to expose the CAM. A 0.5-cm wide filter paper was first placed on top of the CAM, and 100 μL conditioned medium was added to the center of the paper. After closing the window with sterile adhesive tape, the eggs were incubated at 37°C in 80–90% relative humidity for four days. Following fixation with stationary solution (methanol:acetone = 1:1) for 15 minutes, the CAMs were cut and harvested and gross photos of each CAM were taken with a digital camera. The effect of conditioned media harvested from different cultured cells was evaluated based on the number of second- and third-order vessels.
Intracranial brain tumor xenografts, IHC, and hematoxylin–eosin staining
Glioblastoma cells (5 × 105) were stereotactically implanted into the brains of nude mice (n = 5 per group). The mice were monitored daily and euthanized when moribund. Whole brains were removed, paraffin-embedded, sectioned into 4-μm thick slides, and stained with hematoxylin–eosin (H&E) or with anti-QKI (Abcam), anti-MMP9 (Cell Signaling Technology), or anti-VEGF (Cell Signaling Technology) antibodies. Images were captured using an AxioVision Rel. 4.6 computerized image analysis system (Zeiss, Jena, Germany).
Cells (2 × 106) in a 100-mm culture dish were treated with 1% formaldehyde to cross-link proteins to DNA. The cell lysates were sonicated to shear DNA to 300–1000-bp fragments. Equal aliquots of chromatin supernatant were separated and incubated with 1 μg anti–NF-κB (Cell Signaling Technology) or anti-IgG antibody (negative control; Millipore, Billerica, MA, USA) overnight at 4°C with rotation. After reverse cross-linking of protein/DNA complexes to free the DNA, PCR was performed using specific primers.
Electrophoresis mobility shift assay
Electrophoresis mobility shift assay (EMSA) was performed using a LightShift Chemiluminescent EMSA Kit (Pierce). The following DNA probes containing specific binding sites were used: NF-κB sense, 5′-AGTTGAGGGGACTTTCCCAGGC-3′; NF-κB anti-sense, 5′-GCCTGGGAAAGTCCCCTCAAC-3′.
Microarray data processing and visualization
Microarray data were downloaded from The Cancer Genome Atlas (TCGA) database (http://cancergenome.nih.gov/). Gene Set Enrichment Analysis (GSEA) was performed using GSEA 2.0.9 (http://www.broadinstitute.org/gsea/).
All statistical analyses were carried out using the SPSS 16.0 statistical software package (SPSS Inc., Chicago, IL, USA). The χ2 test was used to analyze the relationship between QKI expression and clinicopathological characteristics. Bivariate correlations between study variables were calculated by Spearman’s rank correlation coefficients. P < 0.05 was considered statistically significant.
The Ethical Committee of the Third Affiliated Hospital of Sun Yat-sen University evaluated and approved the use of human glioma tissue specimens, and written informed consent was obtained from all participants or their appropriate representatives. All animal studies were conducted with the approval of the Sun Yat-sen University Institutional Animal Care and Use Committee and were performed in accordance with established guidelines.
This study was supported by grants from the Chinese Ministry of Education for young teacher training of Sun Yat-Sen University (12ykpy44); Science and Technology Project from Guangzhou City (12c002061756); Science and Technology Project from Guangdong Province (20120314); National Natural Science Foundation of China(81272794).
- Kotliarova S, Fine HA: SnapShot: glioblastoma multiforme. Cancer Cell 2012,21(710–710):e711.Google Scholar
- Wen PY, Kesari S: Malignant gliomas in adults. N Engl J Med 2008, 359:492–507. 10.1056/NEJMra0708126View ArticlePubMedGoogle Scholar
- Johnson DR, Leeper HE, Uhm JH: Glioblastoma survival in the United States improved after Food and Drug Administration approval of bevacizumab: a population-based analysis. Cancer 2013, 119:3489–3495.View ArticlePubMedGoogle Scholar
- Lacroix M, Abi-Said D, Fourney DR, Gokaslan ZL, Shi W, DeMonte F, et al.: A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J Neurosurg 2001, 95:190–198. 10.3171/jns.2001.95.2.0190View ArticlePubMedGoogle Scholar
- Markowitz SD, Roberts AB: Tumor suppressor activity of the TGF-beta pathway in human cancers. Cytokine Growth Factor Rev 1996, 7:93–102. 10.1016/1359-6101(96)00001-9View ArticlePubMedGoogle Scholar
- Reiss M: TGF-beta and cancer. Microbes Infect 1999, 1:1327–1347. 10.1016/S1286-4579(99)00251-8View ArticlePubMedGoogle Scholar
- Akhurst RJ, Balmain A: Genetic events and the role of TGF beta in epithelial tumour progression. J Pathol 1999, 187:82–90. 10.1002/(SICI)1096-9896(199901)187:1<82::AID-PATH248>3.0.CO;2-8View ArticlePubMedGoogle Scholar
- Siegel PM, Massague J: Cytostatic and apoptotic actions of TGF-beta in homeostasis and cancer. Nat Rev Cancer 2003, 3:807–821. 10.1038/nrc1208View ArticlePubMedGoogle Scholar
- Pardali K, Moustakas A: Actions of TGF-beta as tumor suppressor and pro-metastatic factor in human cancer. Biochim Biophys Acta 2007, 1775:21–62.PubMedGoogle Scholar
- Bierie B, Moses HL: TGF-beta and cancer. Cytokine Growth Factor Rev 2006, 17:29–40. 10.1016/j.cytogfr.2005.09.006View ArticlePubMedGoogle Scholar
- Furnari FB, Fenton T, Bachoo RM, Mukasa A, Stommel JM, Stegh A, et al.: Malignant astrocytic glioma: genetics, biology, and paths to treatment. Genes Dev 2007, 21:2683–2710. 10.1101/gad.1596707View ArticlePubMedGoogle Scholar
- Seoane J, Le HV, Shen L, Anderson SA, Massague J: Integration of Smad and forkhead pathways in the control of neuroepithelial and glioblastoma cell proliferation. Cell 2004, 117:211–223. 10.1016/S0092-8674(04)00298-3View ArticlePubMedGoogle Scholar
- Bruna A, Darken RS, Rojo F, Ocana A, Penuelas S, Arias A, et al.: High TGFbeta-Smad activity confers poor prognosis in glioma patients and promotes cell proliferation depending on the methylation of the PDGF-B gene. Cancer Cell 2007, 11:147–160. 10.1016/j.ccr.2006.11.023View ArticlePubMedGoogle Scholar
- Ikushima H, Todo T, Ino Y, Takahashi M, Miyazawa K, Miyazono K: Autocrine TGF-beta signaling maintains tumorigenicity of glioma-initiating cells through Sry-related HMG-box factors. Cell Stem Cell 2009, 5:504–514. 10.1016/j.stem.2009.08.018View ArticlePubMedGoogle Scholar
- Penuelas S, Anido J, Prieto-Sanchez RM, Folch G, Barba I, Cuartas I, et al.: TGF-beta increases glioma-initiating cell self-renewal through the induction of LIF in human glioblastoma. Cancer Cell 2009, 15:315–327. 10.1016/j.ccr.2009.02.011View ArticlePubMedGoogle Scholar
- Hong S, Lim S, Li AG, Lee C, Lee YS, Lee EK, et al.: Smad7 binds to the adaptors TAB2 and TAB3 to block recruitment of the kinase TAK1 to the adaptor TRAF2. Nat Immunol 2007, 8:504–513. 10.1038/ni1451View ArticlePubMedGoogle Scholar
- Lee YS, Kim JH, Kim ST, Kwon JY, Hong S, Kim SJ, et al.: Smad7 and Smad6 bind to discrete regions of Pellino-1 via their MH2 domains to mediate TGF-beta1-induced negative regulation of IL-1R/TLR signaling. Biochem Biophys Res Commun 2010, 393:836–843. 10.1016/j.bbrc.2010.02.094View ArticlePubMedGoogle Scholar
- Song L, Liu L, Wu Z, Li Y, Ying Z, Lin C, et al.: TGF-beta induces miR-182 to sustain NF-kappaB activation in glioma subsets. J Clin Invest 2012, 122:3563–3578. 10.1172/JCI62339View ArticlePubMed CentralPubMedGoogle Scholar
- Vernet C, Artzt K: STAR, a gene family involved in signal transduction and activation of RNA. Trends Genet 1997, 13:479–484. 10.1016/S0168-9525(97)01269-9View ArticlePubMedGoogle Scholar
- Chen T, Richard S: Structure-function analysis of Qk1: a lethal point mutation in mouse quaking prevents homodimerization. Mol Cell Biol 1998, 18:4863–4871.PubMed CentralPubMedGoogle Scholar
- Wu J, Zhou L, Tonissen K, Tee R, Artzt K: The quaking I-5 protein (QKI-5) has a novel nuclear localization signal and shuttles between the nucleus and the cytoplasm. J Biol Chem 1999, 274:29202–29210. 10.1074/jbc.274.41.29202View ArticlePubMedGoogle Scholar
- Aberg K, Saetre P, Jareborg N, Jazin E: Human QKI, a potential regulator of mRNA expression of human oligodendrocyte-related genes involved in schizophrenia. Proc Natl Acad Sci U S A 2006, 103:7482–7487. 10.1073/pnas.0601213103View ArticlePubMed CentralPubMedGoogle Scholar
- Haroutunian V, Katsel P, Dracheva S, Davis KL: The human homolog of the QKI gene affected in the severe dysmyelination "quaking" mouse phenotype: downregulated in multiple brain regions in schizophrenia. Am J Psychiatry 2006, 163:1834–1837. 10.1176/ajp.2006.163.10.1834View ArticlePubMedGoogle Scholar
- Cesari R, Martin ES, Calin GA, Pentimalli F, Bichi R, McAdams H, et al.: Parkin, a gene implicated in autosomal recessive juvenile parkinsonism, is a candidate tumor suppressor gene on chromosome 6q25-q27. Proc Natl Acad Sci U S A 2003, 100:5956–5961. 10.1073/pnas.0931262100View ArticlePubMed CentralPubMedGoogle Scholar
- Smith DI, Zhu Y, McAvoy S, Kuhn R: Common fragile sites, extremely large genes, neural development and cancer. Cancer Lett 2006, 232:48–57. 10.1016/j.canlet.2005.06.049View ArticlePubMedGoogle Scholar
- Mulholland PJ, Fiegler H, Mazzanti C, Gorman P, Sasieni P, Adams J, et al.: Genomic profiling identifies discrete deletions associated with translocations in glioblastoma multiforme. Cell Cycle 2006, 5:783–791. 10.4161/cc.5.7.2631View ArticlePubMedGoogle Scholar
- Ichimura K, Mungall AJ, Fiegler H, Pearson DM, Dunham I, Carter NP, et al.: Small regions of overlapping deletions on 6q26 in human astrocytic tumours identified using chromosome 6 tile path array-CGH. Oncogene 2006, 25:1261–1271. 10.1038/sj.onc.1209156View ArticlePubMed CentralPubMedGoogle Scholar
- Chen AJ, Paik JH, Zhang H, Shukla SA, Mortensen R, Hu J, et al.: STAR RNA-binding protein Quaking suppresses cancer via stabilization of specific miRNA. Genes Dev 2012, 26:1459–1472. 10.1101/gad.189001.112View ArticlePubMed CentralPubMedGoogle Scholar
- Gavino C, Richard S: Loss of p53 in quaking viable mice leads to Purkinje cell defects and reduced survival. Sci Rep 2011, 1:84.View ArticlePubMed CentralPubMedGoogle Scholar
- Ishii N, Maier D, Merlo A, Tada M, Sawamura Y, Diserens AC, et al.: Frequent co-alterations of TP53, p16/CDKN2A, p14ARF, PTEN tumor suppressor genes in human glioma cell lines. Brain Pathol 1999, 9:469–479. 10.1111/j.1750-3639.1999.tb00536.xView ArticlePubMedGoogle Scholar
- Valastyan S, Reinhardt F, Benaich N, Calogrias D, Szasz AM, Wang ZC, et al.: A pleiotropically acting microRNA, miR-31, inhibits breast cancer metastasis. Cell 2009, 137:1032–1046. 10.1016/j.cell.2009.03.047View ArticlePubMed CentralPubMedGoogle Scholar
- Subramanyam D, Lamouille S, Judson RL, Liu JY, Bucay N, Derynck R, et al.: Multiple targets of miR-302 and miR-372 promote reprogramming of human fibroblasts to induced pluripotent stem cells. Nat Biotechnol 2011, 29:443–448. 10.1038/nbt.1862View ArticlePubMed CentralPubMedGoogle Scholar
- Wang Y, Vogel G, Yu Z, Richard S: The QKI-5 and QKI-6 RNA binding proteins regulate the expression of microRNA 7 in glial cells. Mol Cell Biol 2013, 33:1233–1243. 10.1128/MCB.01604-12View ArticlePubMed CentralPubMedGoogle Scholar
- Kim J, Zhang Y, Skalski M, Hayes J, Kefas B, Schiff D, et al.: MicroRNA-148a is a prognostic oncomiR that targets MIG6 and BIM to regulate EGFR and apoptosis in glioblastoma. Cancer Res 2014, 74:1541–1553. 10.1158/0008-5472.CAN-13-1449View ArticlePubMed CentralPubMedGoogle Scholar
- Piek E, Heldin CH, Ten Dijke P: Specificity, diversity, and regulation in TGF-beta superfamily signaling. FASEB J 1999, 13:2105–2124.PubMedGoogle Scholar
- Massague J, Chen YG: Controlling TGF-beta signaling. Genes Dev 2000, 14:627–644.PubMedGoogle Scholar
- Heldin CH, Miyazono K, ten Dijke P: TGF-beta signalling from cell membrane to nucleus through SMAD proteins. Nature 1997, 390:465–471. 10.1038/37284View ArticlePubMedGoogle Scholar
- Fukuchi M, Imamura T, Chiba T, Ebisawa T, Kawabata M, Tanaka K, et al.: Ligand-dependent degradation of Smad3 by a ubiquitin ligase complex of ROC1 and associated proteins. Mol Biol Cell 2001, 12:1431–1443. 10.1091/mbc.12.5.1431View ArticlePubMed CentralPubMedGoogle Scholar
- Lu W, Feng F, Xu J, Lu X, Wang S, Wang L, et al.: QKI impairs self-renewal and tumorigenicity of oral cancer cells via repression of SOX2. Cancer Biol Ther 2014,15(9):1174–84. 10.4161/cbt.29502View ArticlePubMedGoogle Scholar
- Zhao Y, Zhang G, Wei M, Lu X, Fu H, Feng F, et al.: The tumor suppressing effects of QKI-5 in prostate cancer: a novel diagnostic and prognostic protein. Cancer Biol Ther 2014, 15:108–118. 10.4161/cbt.26722View ArticlePubMed CentralPubMedGoogle Scholar
- Bian Y, Wang L, Lu H, Yang G, Zhang Z, Fu H, et al.: Downregulation of tumor suppressor QKI in gastric cancer and its implication in cancer prognosis. Biochem Biophys Res Commun 2012, 422:187–193. 10.1016/j.bbrc.2012.04.138View ArticlePubMedGoogle Scholar
- Ji S, Ye G, Zhang J, Wang L, Wang T, Wang Z, et al.: miR-574–5p negatively regulates Qki6/7 to impact beta-catenin/Wnt signalling and the development of colorectal cancer. Gut 2013, 62:716–726. 10.1136/gutjnl-2011-301083View ArticlePubMed CentralPubMedGoogle Scholar
- Galardi S, Mercatelli N, Farace MG, Ciafre SA: NF-kB and c-Jun induce the expression of the oncogenic miR-221 and miR-222 in prostate carcinoma and glioblastoma cells. Nucleic Acids Res 2011, 39:3892–3902. 10.1093/nar/gkr006View ArticlePubMed CentralPubMedGoogle Scholar
- Song L, Lin C, Gong H, Wang C, Liu L, Wu J, et al.: miR-486 sustains NF-kappaB activity by disrupting multiple NF-kappaB-negative feedback loops. Cell Res 2013, 23:274–289. 10.1038/cr.2012.174View ArticlePubMed CentralPubMedGoogle Scholar
- Jiang L, Wu J, Yang Y, Liu L, Song L, Li J, et al.: Bmi-1 promotes the aggressiveness of glioma via activating the NF-kappaB/MMP-9 signaling pathway. BMC Cancer 2012, 12:406. 10.1186/1471-2407-12-406View ArticlePubMed CentralPubMedGoogle Scholar
- Liang F, Zhang S, Wang B, Qiu J, Wang Y: Overexpression of integrin-linked kinase (ILK) promotes glioma cell invasion and migration and down-regulates E-cadherin via the NF-kappaB pathway. J Mol Histol 2014, 45:141–151. 10.1007/s10735-013-9540-5View ArticlePubMedGoogle Scholar
- Holland EC: Gliomagenesis: genetic alterations and mouse models. Nat Rev Genet 2001, 2:120–129. 10.1038/35052535View ArticlePubMedGoogle Scholar
- Zhu Y, Parada LF: The molecular and genetic basis of neurological tumours. Nat Rev Cancer 2002, 2:616–626. 10.1038/nrc866View ArticlePubMedGoogle Scholar
- Joseph JV, Balasubramaniyan V, Walenkamp A, Kruyt FA: TGF-beta as a therapeutic target in high grade gliomas - promises and challenges. Biochem Pharmacol 2013, 85:478–485. 10.1016/j.bcp.2012.11.005View ArticlePubMedGoogle Scholar
- Seoane J: The TGFBeta pathway as a therapeutic target in cancer. Clin Transl Oncol 2008, 10:14–19. 10.1007/s12094-008-0148-2View ArticlePubMedGoogle Scholar
- Yingling JM, Blanchard KL, Sawyer JS: Development of TGF-beta signalling inhibitors for cancer therapy. Nat Rev Drug Discov 2004, 3:1011–1022. 10.1038/nrd1580View ArticlePubMedGoogle Scholar
- Li J, Zhang N, Song LB, Liao WT, Jiang LL, Gong LY, et al.: Astrocyte elevated gene-1 is a novel prognostic marker for breast cancer progression and overall patient survival. Clin Cancer Res 2008, 14:3319–3326. 10.1158/1078-0432.CCR-07-4054View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.