Background
Lymphoma is a type of malignant cancer that occurs worldwide, contributing 4% of the total number of new cancer cases diagnosed in 2018. Non-Hodgkin lymphoma (NHL) is the most common subtype of lymphoma and mainly includes diffuse large B-cell lymphoma (DLBCL). DLBCL is aggressive and heterogeneous, and approximately 75% of DLBCL patients are defined as Ann Arbor stage III or IV [
1,
2]. Emerging evidence indicates large roles for lncRNAs in malignant B cells; in these cells, lncRNAs can influence oncogenic signaling as well as the response to clinical treatments [
3‐
5]. For example, aberrant expression of lncRNA NEAT1 is found in DLBCL tissues and is often associated with disease progression and poor prognosis [
6].
The GLI1 oncogene has been implicated in the pathobiology of DLBCL [
7‐
9]. Agarwal et al. identified GLI1 as providing insights into the contribution of Hedgehog signaling in the pathobiology of malignant tumours [
7]. GLI1 contributes to the cell survival of DLBCL through the expression of AKT in DLBCL and likely in other malignant tumours. Active IKKβ promotes GLI1 expression, leading to the increased cell viability of DLBCL in vivo and in vitro [
8]. Sun et al. found that GLI1 inhibition repressed cell growth and cell cycle progression and promoted apoptosis as well as autophagy depending on ERK1/2 activity in human chondrosarcoma cells [
9].
MicroRNAs (miRNAs) are endogenous ∼ 22 nt RNAs that can play important regulatory roles in animals and plants by targeting mRNAs for translational repression [
10]. The targeting of miRNAs could be a novel therapeutic approach, as evidenced by tumour regression in mouse models and initial promising data from clinical trials [
11‐
14]. One recent study showed that miR-101, upregulated in DLBCL, suppressed DLBCL cell proliferation and facilitated apoptosis by inhibiting the expression of MEK1 [
15], while miR-155, which is downregulated in DLBCL, suppressed DLBCL cell proliferation and facilitated apoptosis by upregulating SOCS3 expression to suppress the JAK-STAT3 signaling pathway [
16]. Thus, miRNAs may play different roles through various signaling pathways. In our study, we observed that miR-34b-5p was downregulated in DLBCL and that a targeting relationship existed between miR-34b-5p and GLI1 according to TargetScan analysis. Moreover, the interaction between NEAT1 and miR-34b-5p was predicted by StarBase, indicating that the NEAT1-miR-34b-5p-GLI1 axis might function in DLBCL progression.
With the development of microarray technology and immunohistochemistry, DLBCL has been classified into germinal centre B cell-like (GCB) DLBCL and activated B cell-like (ABC) DLBCL based on gene expression profiling studies. The GCB DLBCL samples expressed genes that are characteristic of normal germinal centre B cells, but ABC DLBCL samples had genes characteristic of plasma cells [
17]. In addition to GCB DLBCL and ABC DLBCL subtypes, double-hit lymphomas that had concurrent chromosomal rearrangements of MYC plus BCL2 or BCL6 were considered aggressive DLBCL. MYC, BCL2 and BCL6 are the most common oncogenes in DLBCL. A study showed that MYC rearrangements were found in 12.2% of DLBCL, with 17.7% in GCB DLBCL and 6.5% in ABC DLBCL, and these rearrangements indicated a poor prognosis after standard combination chemotherapy [
18]. MYC rearrangements plus BCL2 rearrangements (4.8%) were observed in GCB DLBCL, and MYC rearrangements with BCL6 rearrangements (1.2%) were also detected. Although many studies have mainly focused on the effect of MYC and BCL2 rearrangements, it is also recognized that MYC and BCL2 can be induced in other ways. High expression of MYC and BCL2 or BCL6 was significantly associated with poor prognosis and survival [
19,
20].
MYC is a master transcriptional regulator that controls almost all cellular processes [
21‐
23]. To be exact, it can promote cell activation, growth and proliferation while concomitantly sensitizing cells to apoptosis [
24]. MYC-related microRNAs can regulate DLBCL progression via core cellular pathways [
25]. Recently, it was shown that the Smurf2-YY1 axis regulates MYC expression to reduce B cell proliferation [
26]. In addition, MYC can bind to NEAT1 and inhibit its expression to regulate cell apoptosis in chronic myeloid leukaemia (CML) [
27]. Thus, we predicted that MYC could bind to the promoter of NEAT1 by JASPAR analysis and modulate the expression of NEAT1. Taken together, we hypothesized that MYC may participate in the regulation of the NEAT1-miR-34b-5p-GLI1 axis, further investigating DLBCL pathogenesis.
In this study, we mainly focused on clarifying the mechanism by which MYC regulates the cell proliferation of DLBCL via the NEAT1-miR-34b-5p-GLI1 signaling axis, which might provide novel targets for DLBCL therapies.
Methods
Cell lines and cell transfection
The DLBCL cell lines OCI-Ly1, OCI-Ly8, OCI-Ly10 and SUDHL-4 were obtained from the Cell Bank of Type Culture Collection, Chinese Academy of Science (Shanghai, China). OCI-Ly1 was established from the bone marrow of a 44-year-old male with stage 4B B-cell non-Hodgkin lymphoma (B-NHL; diffuse large cell) at relapse in 1983. OCI-Ly8 was established from a 58-year-old male with diffuse large B-cell lymphoma. OCI-Ly10 was established from a 66-year-old female with DLBCL. SUDHL-4 was established from a 38-year-old male with DLBCL.
OCI-Ly1, OCI-Ly8, and OCI-Ly10 cells were grown in 90% Iscove’s medium with 10% foetal bovine serum (FBS) and supplemented with penicillin G and streptomycin, while SUDHL-4 cells were grown in 90% RPMI-1640 medium with 10% FBS and supplemented with penicillin G and streptomycin, l-glutamine, and HEPES. We performed Mycoplasma sp. and other contaminant tests every 3 months.
Cells were transfected with shRNAs targeting NEAT1 or GLI1, expression vectors containing full-length NEAT1 or MYC, or miR-34b-5p mimic, which were purchased from GenePharma Co., Ltd. (Shanghai, China) using Lipofectamine 2000 (Invitrogen, Carlsbad, USA) according to the manufacturer’s instructions. Cells were harvested 48 h after transfection.
Human samples
Sixty samples (healthy control, n = 30; DLBCL, n = 30) were provided by the Department of Hematology, The First Affiliated Hospital of Soochow University. Patient organization and case access were in line with the “Guidelines for the Diagnosis and Treatment of Diffuse Large B-Cell Lymphoma in China” (2013 Edition). All DLBCL patients were newly diagnosed, patients with other tumours were excluded, and patients had no serious impairment of heart, lung, brain, liver or kidney function. There were 12 males and 18 females with an average age of 54.26 ± 6.24 years. In terms of Ann Arbor staging, 17 cases were stage I–II (early stage) and 13 cases were stage III–IV (progressive stage). All samples were approved by the Ethics Committee of the First Affiliated Hospital of Soochow University. Written informed consent was signed by all enrolled patients.
3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay
Cells were seeded in 96-well plates at 5 × 103 cells/well. After the indicated number of days (0–3 days), cell viability was determined by MTT (Sigma, USA). The cell viability in each well was measured in terms of optical density (OD) at wavelength 490 nm by the use of a microplate reader (Bio-Rad Laboratories, Hercules, CA, USA). Every sample was measured in triplicate.
Flow cytometry
Apoptotic cells were analyzed by an annexin V staining kit (Thermo Fisher Scientific). Briefly, the cells were harvested and washed twice with cold PBS. The cells were resuspended in 1× binding buffer and stained with annexin V-FITC reagent for 15 min at room temperature. Then, the cells were washed with 1× binding buffer and incubated with propidium iodide (PI) for 5 min on ice. The stained cells were analysed by flow cytometry with a BD FACSCalibur cytometer (BD Biosciences, San Diego, CA, USA).
Cells were seeded at a low density (0.4 × 103 cells/well) in 6-well plates and cultured for 6 days. After 6 days of culture, colonies were washed with PBS, fixed with 10% formaldehyde for 5 min and stained with 1% crystal violet for 30 s. The images of each well were captured, and the number of colonies containing at least 50 cells in each well was counted.
Terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL) staining assay
Apoptotic cells were evaluated using the In Situ Cell Death Detection Kit (Roche, Basel, Switzerland, Germany) according to the manufacturer’s instructions. Nuclei were stained with DAPI. The images were captured by fluorescence microscopy (Leica Microsystems GmbH, Wetzlar, Germany). The percentage of apoptotic cells in each view was counted.
Reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR)
Total RNA was extracted from cells using TRIzol reagent (Invitrogen, Thermo Fisher Scientific) following the manufacturer’s instructions. cDNA synthesis was performed with the Prime-Script RT-PCR master mix (Takara). SYBR Green Premix Ex Taq (Takara) was used for quantitative RT-PCR analysis. The primers for genes of interest are listed: NEAT1 (forward: 5′-GAGTTAAGGCGCCATCCTCA-3′ and reverse: 5′-AGCACTGCCACCTGGAAAAT-3′), GLI1 (forward: 5′-GCCAATC ACAAATCAGTCTCC-3′ and reverse: 5′-TGCTCCTAACCT GCCCAC-3′), GAPDH (forward: 5′-CCAGGTGGTCTCCTCTGA-3′ and reverse: 5′-GCTGTAGCCAAATCGTTGT-3′), miR-34b-5p (forward: 5′-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGAC CAATCA-3′ and reverse: 5′-GCCTAGGCAGTGTCATTAGC-3′), U6 (forward: 5′-CTCGCTTCGGCAGCACA-3′ and reverse: 5′-AACGCTTCACGAATTTGCGT-3′), and MYC (forward: 5′-CGACGAGACCTTCATCAAAAAC-3′ and reverse: 5′-CTTCTC TGAGACGAGCTTGG-3′). Each sample was measured in duplicate, and each experiment was repeated three times.
Western blot analysis
DLBCL cells were collected, washed with cold PBS buffer, and lysed on ice for 30 min using lysis buffer (RIPA buffer, 89900, Thermo Fisher). Proteins were harvested from the lysates, and protein concentrations were quantified. Then, equal amounts of proteins from each sample were loaded into SDS–polyacrylamide gels and transferred to a polyvinylidene difluoride (PVDF) membrane. The membrane was blocked with 5% skim milk for 1 h at room temperature (RT). Next, the membrane was incubated with primary antibodies at 4 °C overnight. Primary antibodies against GLI1 (ab151796), cyclin D1 (ab226977), CDK4 (137675), p27 (ab45872), MYC (ab39688) and β-actin (ab8227) were purchased from Abcam. Antibodies against GAPDH were purchased from ProteinTech (Chicago, USA). The membrane was then incubated with horseradish peroxidase (HRP)-conjugated secondary antibody for 1 h at RT. The bands were detected with ECL reagent purchased from Millipore Corp.
Dual-luciferase reporter assay
The wild-type or mutant 3′-UTR region of NEAT1 or GLI1 predicted to bind to miR-34b-5p was cloned downstream of a firefly luciferase reporter in the pmirGLO vector. The mixture of reporter vector, control vector and miR-34b-5p was transfected into DLBCL cell lines OCI-Ly1 or SUDHL-4. The luciferase activity was assessed using a Dual-Glo® Luciferase kit according to the manufacturer’s instructions.
RNA immunoprecipitation (RIP) assay
RIP experiments were performed using the Magna RIP™ RNA-Binding Protein Immunoprecipitation Kit (Millipore, USA) according to the manufacturer’s protocol. Lysates from DLBCL cell lines OCI-Ly1 or SUDHL-4 were incubated with anti-NEAT1 or anti-GLI1 antibody for 4 h at 4 °C. Co-precipitated RNAs were analysed by qRT-PCR.
Chromatin immunoprecipitation (ChIP) assay
ChIP experiments were performed with the EZ-Magna ChIP™ Chromatin immunoprecipitation kit (Millipore, USA). Briefly, DLBCL cell lines OCI-Ly1 or SUDHL-4 were cross-linked with 1% formaldehyde for 10 min at room temperature. Cells were then lysed and sonicated in lysis buffer to obtain chromatin fragments. Next, the resulting fragments were extracted by incubation with anti-MYC antibody (anti-IgG antibody as a negative control) based on the manufacturer’s protocol. Co-precipitated DNAs were analysed by RT-qPCR.
Statistical analysis
All data are presented as the mean of at least triplicate samples ± standard deviation. The data were analysed with GraphPad Prism (GraphPad Software, San Diego, CA). Statistical analysis was performed with SPSS 22.0 (SPSS Inc., Chicago, USA). Student’s t-test was used to evaluate differences between two groups. P values smaller than 0.05 (*P < 0.05, **P < 0.01, ***P < 0.001) were considered statistically significant.
Discussion
It is now widely understood that mutations within noncoding regions of the genome are major determinants of human diseases such as cancers [
29‐
31]. Long noncoding RNAs (lncRNAs) are functionally defined as transcripts containing > 200 nucleotides in length that have no protein coding potential, and many lncRNAs are uniquely expressed in specific cancer types [
32‐
34]. For example, lncRNA NEAT1 was identified as a potential prognostic predictor in glioma [
35]. Aberrant lncRNA NEAT1 expression was also found in DLBCL tissues and was associated with disease progression and poor prognosis [
6]. However, the underlying mechanisms remain largely unclear. In this study, we examined the expression of NEAT1, miR-34b-5p and GLI1 in DLBCL cell lines. The results revealed significantly higher levels of NEAT1 and GLI1 and lower levels of miR-34b-5p in DLBCL cell lines than in normal B cells. These data suggested that NEAT1, miR-34b-5p and GLI1 might be jointly involved in DLBCL growth. There are two major subtypes of DLBCL: activated B-cell (ABC) and germinal centre B-cell (GCB) [
36]. The ABC subtype is clearly associated with poor survival when treated with standard chemoimmunotherapy. However, the associations between ABC/GCB and NEAT1 or GLI1 need to be investigated further.
Next, we performed MTT and colony formation assays and found that knockdown of NEAT1 or overexpression of miR-34b-5p suppressed cell proliferation. Moreover, an increase in cell apoptosis was observed after knockdown of NEAT1 or overexpression of miR-34b-5p in DLBCL cell lines by annexin-V staining and TUNEL assay. In addition, overexpression of NEAT1 rescued the GLI1 knockdown-induced attenuation of cell proliferation, indicating that NEAT1 functioned as an oncogene via GLI1 in DLBCL. The binding sites of NEAT1 and miR-34b-5p were predicted by StarBase, and those of miR-34b-5p and GLI1 were predicted by TargetScan. The results were also validated by dual-luciferase reporter and RIP assays, indicating that the NEAT1-miR-34b-5p-GLI1 axis exerted a vital effect on DLBCL progression.
MYC has been shown to bind to the promoter of NEAT1, and suppression of NEAT1 expression regulates cell apoptosis in chronic myeloid leukaemia (CML) [
27]. GLI1 inhibition has been reported to repress cell growth and cell cycle progression and promote apoptosis in human chondrosarcoma cells [
9]. The proteins p27, CDK4, and cyclin D1 are associated with the cell cycle and proliferation [
37‐
39]. Thus, we first determined the correlation between GLI1 and p27/CDK4/cyclin D1. Here, we also found that overexpression of MYC could repress DLBCL cell proliferation and promote cell apoptosis. Moreover, MYC inhibited NEAT1 transcription in DLBCL cell lines via the direct binding of MYC to the NEAT1 promoter. Considering the complexity of MYC, these results seem to be contradictory to the results of some studies, but they are also reasonable because the outcome depends on the level of MYC overexpression. A high level of MYC overexpression could induce apoptosis despite the promotion of cell proliferation, but a low level of MYC induced lymphomagenesis, suggesting that apoptosis antagonizes MYC oncogenic activity. It is not surprising that MYC overexpression negatively regulated NEAT1 expression, while low MYC positively modulated NEAT1, which facilitated the proliferation of DLBCL, which agreed with a previous study by others. However, the dual regulation MYC could occur through many different mechanisms to affect proliferation and apoptosis. MYC deregulation has been linked to the activation of tumour suppressor p53, and p53 mutations are one of most frequently detected mutations in DLBCL. Moreover, the consequence of MYC-induced apoptosis was rescued either by overexpression of anti-apoptotic BCL-2 family proteins or by a lack of pro-apoptotic proteins promoting MYC-induced lymphomagenesis.
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