MALAT1 predicts poor survival in osteosarcoma patients and promotes cell metastasis through associating with EZH2

Osteosarcoma is the most common type of bone cancer, especially in children and young adults. Recently, long noncoding RNAs (lncRNAs) have emerged as new prognostic markers and gene regulators in several cancers, including osteosarcoma. In this study, we investigated the contributions of the lncRNA MALAT1 in osteosarcoma with a specific focus on its transcriptional regulation and its interaction with EZH2. Our results showed that MALAT1 was significantly increased in osteosarcoma specimens and cell lines. ROC curve analysis showed that MALAT1 had a higher area under the curve than alkaline phosphatase, and Kaplan-Meier survival analysis indicated that patients with high serum levels of MALAT1 showed reduced survival rate. Knockdown of MALAT1 decreased osteosarcoma cell invasion and promoted E-cadherin expression. Mechanistic investigations showed that MALAT1 was transcriptionally activated by TGF-β. Additionally, EZH2 is highly expressed and associated with the 3’ end region of lncRNA MALAT1 in osteosarcoma, and this association finally suppressed the expression of E-cadherin. Subsequently, our gain and loss function assay showed that MALAT1 overexpression promoted cell metastasis and decreased E-cadherin level, however, this effect was partially reversed by EZH2 knockdown. In conclusion, our work illuminates that lncRNA MALAT1 is a potential diagnostic and prognostic factor in osteosarcoma and further demonstrates how MALAT1 confers an oncogenic function. Thus, lncRNA MALAT1 may serve as a promising prognostic and therapeutic target for osteosarcoma patients.


INTRODUCTION
Osteosarcoma, primarily affecting adolescents and young adults, is among the most frequently occurring primary bone tumors [1]. Approximately 80% of osteosarcoma patients have metastatic disease at the time of diagnosis, and metastasis is a consistent problem in tumor prognosis and treatment [2]. The 5-year overall survival is approximately 65% and the best predictor of long-term survival is the absence of metastatic disease at diagnosis [2]. While the molecular mechanism of osteosarcoma has gained considerable attention, the mechanisms underlying its initiation and progression remain unclear, the most likely candidates are the activation of oncogenes or silence of suppressor genes [3,4]. Currently, surgical resection with subsequent radiotherapy and chemotherapy has dramatically improved the clinical outcome of osteosarcoma patients. However, they finally become resistant and pulmonary metastasis. Further exploration of this area will help in the development of effective strategies in the diagnosis, treatment and prognosis of osteosarcoma.
Long noncoding RNAs (lncRNAs) are defined as transcripts > 200 nucleotides in length and are transcribed but non-translated noncoding RNAs in human genome [5]. Recent studies demonstrated that lncRNAs played important roles in carcinogenesis and cancer metastasis, and deregulated expression of lncRNAs has been found in cancers including osteosarcoma [6]. The discovery and www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 29), pp: 46993-47006 Research Paper study of lncRNAs is thus of major relevance to human biology and disease, as they represent an extensive, largely unexplored, and functional component of the genome [7,8].
Several lncRNAs (PVT1, UCA1, HOTTIP and LINC00161) have been reported to be involved in osteosarcoma progression [9][10][11][12]. The metastasisassociated lung adenocarcinoma transcript 1 (MALAT1), is located on the chromosome 11q13 and was firstly found as a predictive biomarker for metastasis in the early stage of non-small cell lung cancer and then in other cancers [13]. A variety of reports have found that MALAT1 was upregulated in different malignancies including breast cancer, bladder cancer and hepatocellular cancer [14][15][16]. For osteosarcoma, Luo et al revealed that MALAT1 can promote osteosarcoma development by targeting TGFA via MIR376A [17]. Dong et al demonstrated that MALAT1 promoted the proliferation and metastasis of osteosarcoma cells by activating the PI3K/Akt pathway [18]. However, it is still not well known why MALAT1 is deregulated and how MALAT1 participates in metastasis in osteosarcoma. Additionally, the transcription of MALAT1 is initiated from multiple promoters [17]. So far, it is still unclear which of these promoters is predominantly used and which factors regulate the selection or drive the expression.
Enhancer of Zeste Homolog 2 (EZH2), a critical component of polycomb repressive complex 2 (PRC2), functions as a histone H3 Lysine 27 (H3K27) methyltransferase in target gene promoters and inhibits specific gene expression [19]. EZH2 has frequently been found to be overexpressed in a variety of human cancers including osteosarcoma [20]. More importantly, studies demonstrated that MALAT1 interacted with EZH2 and facilitated its recruitment to gene promoter in renal and gastric cancer [21,22], but this was not reported in osteosarcoma. Thus, the study on the regulatory mode between lncRNA MALAT1 and EZH2 in osteosarcoma is a meaningful work.
In our study, we investigated the clinical and experimental function of MALAT1 in osteosarcoma. We determined the reason for MALAT1 overexpression in osteosarcoma, and further verified the downstream effects of MALAT1 in osteosarcoma. Our preliminary study found that MALAT1 is a diagnostic and prognostic factor and activated by the transcription factor TGF-β in osteosarcoma. Moreover, the functional assay indicates that MALAT1 promoted osteosarcoma metastasis through interacting with EZH2.

LncRNA MALAT1 is up-regulated in osteosarcoma specimens and cell lines
RT-qPCR was used to detect MALAT1 expression in 68 primary osteosarcoma tissues and paired adjacent noncancerous tissues, normalized to GAPDH. Our results showed that MALAT1 was up-regulated in primary osteosarcoma tissues compared to noncancerous tissues (P<0.001, Figure 1A). Additionally, the osteosarcoma tissues in 66.2% (45 of 68) of cases had at least 2-fold higher expression of MALAT1 than noncancerous tissues ( Figure 1B). We also detected the serum levels of MALAT1 in 46 osteosarcoma patients and 40 healthy individuals, and the results also indicated a significant higher MALAT1 expression in osteosarcoma patients than in healthy controls (P<0.001, Figure 1C). Subsequently, the MALAT1 expression in four osteosarcoma cell lines (MG-63, SAOS-2, U2OS, SW1353) and one osteoblastic cell line (hFOB) were also determined. As shown in Figure 1D, MALAT1 was up-regulated in all the four osteosarcoma cell lines compared with normal osteoblastic cells.

The diagnostic and prognostic value of MALAT1 in osteosarcoma patients
After having discovered the up-regulation of MALAT1 in osteosarcoma, we further investigated the diagnostic and prognostic role of cell-free MALAT1. Firstly, we analyzed the association of serum levels of MALAT1 with clincopathological factors. Serum level of MALAT1 was significantly correlated with tumor size and distant metastasis, but not correlated with other factors such as age, sex, differentiation, and TNM stage (Table 1). Subsequently, Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of MALAT1. The area under the ROC curve (AUC) for MALAT1 was 0.834 (95% confidence interval [CI] = 0.738-0.906) and the optimal cut-off value was 3.68, providing a sensitivity of 80.43 % and a specificity of 72.50 % (Figure 2A). We then compared the diagnostic performance of MALAT1 with alkaline phosphatase (ALP), a traditional serum biomarker for detecting bone tumors. The AUC of serum ALP was 0.747, with a diagnostic sensitivity of 70.43% and specificity of 57.5% ( Figure 2B). The AUC of MALAT1 was markedly higher than that of ALP (P<0.05). More importantly, combined detection of MALAT1 and ALP increased the diagnostic sensitivity (82.61%) and specificity (82.50%) ( Figure 2C).
The role of MALAT1 in prognosis of osteosarcoma patients was also investigated. We divided the patients into a high and a low expressing group by using the median value (4.43) of 46 serum samples. The 5-year overall survival rate of the osteosarcoma patients whose tumors expressed high levels of MALAT1 was 39.1% (18/46), which was significantly lower than that of the patients whose tumors expressed low levels of MALAT1 (56.5%, 26/46). More importantly, the Kaplan-Meier analysis indicated that patients with high expression of MALAT1 was associated with poor overall survival and progressive free survival compared with the low expressing patients ( Figure 2D and 2E). www.impactjournals.com/oncotarget

TGF-β is involved in the regulation of MALAT1 expression
Since our data revealed an up-regulation of MALAT1 in the osteosarcoma patients, we then determine the underlying mechanism that may explain the clinical observations. Thus, we focused on transcription factors binding to the MALAT1 promoter. We selected TGF-β because Chen et al [24] found that TGF-β functioned as a potent stimulator of osteosarcoma cell epithelial-mesenchymal transition. As expected, TGF-β mRNA expression was significantly increased in osteosarcoma tissues compared with the paired noncancerous tissues ( Figure 3A). Additionally, a positive correlation between MALAT1 and TGF-β mRNA expression was found in primary osteosarcoma tissues. Subsequently, TGF-β over expressing plasmids, pTGF-β, was generated ( Figure 3C), and enhanced TGF-β significantly promoted MALAT1 expression level in both MG-63 and SAOS-2 cells ( Figure 3D). Subsequently, luciferase vector containing the TGF-β binding sites was then constructed to verify the direct interaction between TGF-β and MALAT1. Dual luciferase reporter assay showed that luciferase vector containing TGF-β binding sites had higher luciferase activity than negative control vector both cell lines. To conclude, we identified that overexpression of MALAT1 was at least partially due to the activation by TGF-β in osteosarcoma.

Knockdown of MALAT1 impairs migration and invasion of osteosarcoma cells
As lncRNA MALAT1 was identified as an oncogene associated with tumor metastasis in various cancers [13,17,18], we investigated the effect of MALAT1 on cell migration and invasion. Figure 4A indicated that the siMALAT1-2 showed a better knockdown effect compared with the siMALAT1-1 vector, and siMALAT1-1 was chosen for further experiments. The wound-healing assay and matrigel invasion assay indicated a significant decreased cell migratory and invasive capacity in osteosarcoma cells that transfected with siMALAT1-1 compared with the negative control ( Figure 4B and 4C). Subsequently, we also determined whether E-cadherin expression was regulated by MALAT1. As expected, western blot assay showed that E-cadherin protein was significantly up-regulated after siMALAT1 transfection ( Figure 4D).

EZH2 is highly expressed and interacts mostly with the 3' end region of MALAT1 in osteosarcoma
Various reports have indicated that the MALAT1 may exert its function through interaction with EZH2,   a subunit of PRC2 [21,22,25]. To verify the potential pathway, we firstly determined EZH2 expression in osteosarcoma specimens. Results showed that EZH2 mRNA was upregulated in primary osteosarcoma tissues and serums ( Figure 5A and 5B). Additionally, a significant up-regulation of EZH2 mRNA and protein was also found in four osteosarcoma cell lines compared to normal osteoblastic cells ( Figure 5C and 5D). Moreover, the spearman correlation testing indicated a significant positive association between EZH2 mRNA and MALAT1 expression levels in primary osteosarcoma tissues (r=0.6175, Figure 5E).
Subsequently, RIP assay was performed with an antibody against EZH2 from nuclear extracts of osteosarcoma cells. As MALAT1 contains more than 8000 bps, EZH2 protein can only precipitate the MALAT1 fragments that are responsible for the interaction. To achieve a more explicit understanding, 6 MALAT1 fragments (M1-M6), covering the whole sequence from 5' end to 3' end, were separately detected by RT-qPCR with an independent set of primers ( Figure 5F). The RIP results showed that MALAT1 can interact with EZH2 ( Figure 5G). Moreover, the region containing the nucleotides 7501-8708 at the 3' end of MALAT1 interacted most strongly with EZH2 ( Figure  5H), but there was no enrichment of β-actin or lncRNA control ( Figure 5I). These data indicate that MALAT1 directly interacts with the EZH2, and EZH2 interacts with the 3' end region of MALAT1.

Knockdown of MALAT1 increases E-cadherin level through the interaction with EZH2
To determine that E-cadherin is regulated by EZH2, we analyzed the effect of EZH2 on E-cadherin expression. Spearman correlation testing indicated that EZH2 mRNA expression was negatively correlated with E-cadherin mRNA expression. Then, we silenced EZH2 with siEZH2 in osteosarcoma cells ( Figure 6B). EZH2 knockdown significantly increased E-cadherin mRNA levels in osteosarcoma cells ( Figure 6C). Take a step further, we used ChIP analysis to determine that MALAT1-EZH2 complex had histone modification effect in E-cadherin promoter by using anti-EZH2 and anti-H3K27-me3 antibody in MG-63 cells. Specific primers were designed in three regions of E-cadherin promoter ( Figure 6D), and the enrichment levels by the anti-EZH2 and anti-H3K27-me3 were dramatically suppressed by si-MALAT1 ( Figure 6E and 6F), while binding level of IgG with E-cadherin promoter showed no significant change when MALAT1 was inhibited ( Figure 6G), indicating that the association between

MALAT1 promotes cell migration and invasion through EZH2 in osteosarcoma
We then determined the role of EZH2 in cell metastasis. As shown in Figure 7A and 7B, cell migratory and invasive ability were significantly impaired by transfection of siEZH2. Based on the above results, we further investigated whether EZH2 mediated MALAT1induced enhanced cell metastasis. Over expressing MALAT1 plasmid pMALAT1 was transfected into osteosarcoma cells, and the cell migration and invasion assay showed that pMALAT1 significantly promoted cell migration and invasion. However, this increased metastasis ability caused by MALAT1 was significantly reversed by siEZH2 co-transfection ( Figure 7C and 7D). Thus, we concluded that MALAT1 promoted cell metastasis through associating with EZH2.

DISCUSSION
Recent advances in the non-protein coding part of human genome analysis have discovered extensive transcription of large RNA transcripts that lack coding protein function, termed non-coding RNA [26,27]. It is becoming evident that lncRNAs may be an important class of pervasive genes involved in carcinogenesis and metastasis. Currently, pulmonary metastasis is a major reason of death for patients with osteosarcoma, revealing effective prognostic factor and therapeutic target could help improve treatment strategies to overcome metastatic osteosarcoma. The aim of this study is to investigate the clinical significance of MALAT1 expression in human osteosarcoma and further investigate the potential regulatory mechanism by which MALAT1 participate in osteosarcoma progression. The present study demonstrated that MALAT1 was significantly up-regulated in osteosarcoma. Additionally, MALAT1 expression was significantly correlated with tumor size

Figure 6: Knockdown of MALAT1 increases E-cadherin expression by associating with EZH2. (A) A negative correlation
was found between EZH2 mRNA and E-cadherin mRNA expression; (B) EZH2 expression was significantly suppressed by si-EZH2 transfection; (C) E-cadherin mRNA was significantly upregulated after EZH2 was silenced; (D-G) ChIP analysis of SW620 treated with si-MALAT1 was conducted on E-cadherin promoter (primer a-c) and GAPDH promoter (primer d-e) regions using the indicated antibodies. Enrichment was determined relative to input controls. These results show data from at least three independent experiments. *, P < 0.05; **, P < 0.01; ***, P < 0.001. and distant metastasis, and was an independent prognostic factor of overall survival for osteosarcoma patients. More importantly, we further uncovered that MALAT1 was activated by TGF-β, and promoted cell migration and invasion through associated with EZH2 in osteosarcoma.
In this study, we firstly investigated the role of MALAT1 in diagnosing and predicting osteosarcoma patients. Previous studies have demonstrated the prognostic value of MALAT1 in human cancer, and patients with enhanced level of MALAT1 had a higher risk of poor outcome in gastric cancer, esophageal squamous cell carcinoma, colorectal cancer and osteosarcoma [28][29][30][31]. Our results are partially consistent with previous studies and further revealed the value of cell-free MALAT1 in osteosarcoma patients. Utilizing lncRNA expression level in peripheral blood to diagnose tumors early may be effective strategy and deserved to be explored further because lncRNA is very stable in blood plasma and serum. More importantly, serum testing is more convenient and noninvasive. Therefore, it is important to identify serum markers that predict the initiation and progression of osteosarcoma, which may allow for the improvement of early detection rate. With this purpose, our ROC analysis and Kaplan-Meier survival analysis identified that serum lncRNA MALAT1 expression has considerable diagnostic and prognostic significance in discriminating osteosarcoma patients and non-tumor patients.
We attempted to unravel the molecular switch of MALAT1 in controlling this malignant phenotype of osteosarcoma. Previous reports indicated that several transcription factors are upregulated in malignancies and induce activation of lncRNAs [32][33][34]. To verify the underlying regulatory mechanism by which MALAT1 was activated in osteosarcoma patients, we concentrated on TGF-β, since TGF-β functioned as a potent stimulator of epithelial-to-mesenchymal transition in osteosarcoma cell. TGF-β is reported to diversely participate in the function of cancer cells through promoting migration, invasion and cell EMT process [24]. We found that TGF-β expression was significantly increased, and positive correlated with the expression of MALAT1 in primary osteosarcoma tissues. More importantly, luciferase assay indicated a direct interaction between TGF-β and MALAT1 in osteosarcoma cells, suggesting that TGF-β activated MALAT1 in osteosarcoma.
It is well known that MALAT1 regulates tumor cell migration, invasion and the metastasis in various cancer entities, particularly lung cancer [13]. However, the role of MALAT1 in osteosarcoma metastasis is largely unknown. Thus, we evaluated the role of MALAT1 in osteosarcoma cell migration and invasion. Our date indicated that MALAT1 silencing dramatically suppressed the cell metastasis and promoted E-cadherin expression in osteosarcoma. On this basis, we further investigated the potential regulatory pathway by which MALAT1 exerted its function. Recent studies reported that many lncRNAs including MALAT1 can interact with PRC2 in various cancers [35,36]. EZH2, working with EED and SUZ12, the other two essential components of the PRC2, functions primarily as a methyltransferase catalyzing H3K27me3 and promoting gene silencing [37]. Thus, the association between MALAT1 and EZH2 may be an important regulatory pattern in human cancers. Previously, Gupta and colleagues reported that HOTAIR induced genome-wide retargeting of PRC2, leading to H3K27me3, and promoted metastasis of breast cancer by silencing multiple metastasis suppressor genes [35]. On the other hand, Sun et al demonstrated that long non-coding RNA EBIC promotes tumor cell invasion by binding to EZH2 and repressing E-Cadherin in cervical cancer [38]. For osteosarcoma, previous study found that overexpression of EZH2 is associated with the poor prognosis in osteosarcoma and function analysis indicates a therapeutic potential [20]. However, there is no direct evidence about the role of interaction between specific lncRNAs and EZH2 in osteosarcoma. In our work, we validated the upregulation of EZH2 in osteosarcoma specimens and cell lines. The RIP results showed that MALAT1 specifically interacted with EZH2, and EZH2 was mostly associated with the 3' end of the MALAT1 region.
As a core catalytic subunit of PRC2, EZH2 has an essential role in the epigenetic maintenance of the H3K27me3 repressive chromatin mark [39]. EMT is a process initially observed in embryonic development in which cells lose epithelial characteristics and gain mesenchymal properties to increase motility and invasion including osteosarcoma [40]. E-cadherin is a key cellcell adhesion molecular associated with EMT of tumor cell. Thus, we investigated the effect of EZH2 on E-cadherin expression. EZH2 knockdown significantly increased E-cadherin levels in osteosarcoma cells. Furthermore, ChIP analysis indicated that MALAT1 decreases E-cadherin expression through EZH2-mediating H3K27me3 formation. The gain and loss function assay also showed that EZH2 reversed the MALAT1-induced enhanced cell metastasis and suppression of E-cadherin expression in osteosarcoma. Collectively, we demonstrated that MALAT1 promotes osteosarcoma cell metastasis through EZH2-induced suppression of E-cadherin.
In conclusion, our integrated approach demonstrates that lncRNA MALAT1 is a potential diagnostic biomarker and associated with prognosis in osteosarcoma patients. MALAT1 is activated by transcription factor TGF-β, and the enhanced expression of MALAT1 further promotes metastasis and suppresses E-cadherin expression through EZH2. Thus, lncRNA MALAT1 may be a potential prognostic and therapeutic target in osteosarcoma. Suppression of MALAT1 could be a future direction to promote the clinical outcome of osteosarcoma patients.  The si-Negative Control_05815(siN05815122147) was obtained from Ribo Bio (Guangzhou China). www.impactjournals.com/oncotarget

Clinical samples
Forty-six serum samples (male/female: 26/20, range of age: 13-45), 68 cancer tissues and paired adjacent noncancerous tissues (male/female: 41/27, range of age: 15-48) from primary osteosarcoma patients were collected at The Second Hospital of Shandong University between 2010 and 2012. Meanwhile, serum samples from 40 healthy volunteers (male/female: 23/17, range of age:  were also collected in this study. All the patients were pathologically confirmed and the tissues were collected immediately after they were obtained during the surgical operation, and then stored at -80 °C to prevent RNA loss. They were classified according to the WHO criteria and staged according to the tumor-node-metastasis (TNM) classification. Written informed consent was obtained from all patients according to the guidelines approved by the Ethics Committee of The Second Hospital of Shandong University.

RNA oligoribonucleotides and cell transfection
The small interfering RNAs (siRNAs) that specifically target lncRNA MALAT1 and EZH2 mRNA were designated as siMALAT1 and siEZH2, respectively (Genechem corporation, Shanghai, China). The MALAT1 overexpression plasmid (pMALAT1) was purchased from Addgene (Cambridge, MA, USA). To construct TGF-β over expressing plasmids (pTGF-β), the gene was amplified with total RNA from human adult normal osteogenic tissues by RT-PCR as described previously [23]. Osteosarcoma cells were plated in a 6-well plate in DMEM supplemented with 10% FBS and cultured until 50-70% confluent. SiRNAs were mixed with Lipofectamine 2000 (Invitrogen) in reduced serum medium (Opti-MEM, Gibco, USA) according to the manufacturer's instructions and final concentration of siRNAs was 100 nM. Knock down effect was examined by RT-qPCR using RNA extracted 48 hours after transfection. The siRNA sequences of lncRNA MALAT1, EZH2 and negative control used in this study are listed in Table 2.

Dual-luciferase reporter assay
Using MG-63 DNA, the identified MALAT1 promoter DNA region was amplified, and the PCR products were cloned into the pGEM-T easy vector System (Promega, Madison, WI, USA). Then the MALAT1 promoter DNA region was incorporated into the pGL4 luciferase expression vector (Promega). Luciferase activity was assessed using the Dual-Luciferase Reporter Assay System (Promega) 48 h after transfection, and the ratio of Firefly/ Renilla luciferase activity was determined.

Quantitative real-time PCR (RT-qPCR)
Total RNA was isolated from osteosarcoma specimens or osteosarcoma cell lines using TRIzol reagent (Invitrogen), and serum samples by using Trizol and acid phenol according to the manufacturer's instructions. And then, the cDNA was synthesized from 200 ng extracted total RNA using the PrimeScript RT reagent Kit (Takara Bio Company, Shiga, Japan) and amplified by RT-qPCR with an SYBR Green Kit (Takara Bio Company) on an ABI PRISM 7500 Sequence Detection System (Applied Biosystems) with the housekeeping gene GAPDH as an internal control. The 2 -ΔΔCt method was used to determine the relative quantification of gene expression levels. All the premier sequences were synthesized by RiboBio (Guangzhou, China), and their sequences are shown inTable 2. Each experiment was performed in triplicate.

Wound-healing assays
For cell motility assays, transfected cells were seeded in 6-well plates and cultured to near confluence. Then, a linear wound was carefully made using a sterile 10 μl pipette tip across the confluent cell monolayer, and the cell debris was removed by washing with phosphatebuffered saline. The cells were incubated in DMEM without FBS, and the wounded monolayers were then photographed at 48 h after wounding. Percent of wound closure was calculated with Image J 1.47 software. Each experiment was performed in triplicate.

Matrigel invasion assays
Matrigel invasion assays were performed using Transwell permeable supports (Corning, USA) according to manufacturer's protocol. Briefly, cells were transfected with siMALAT1, siEZH2 or negative control for 48 h, followed by plating onto a Matrigel-coated membrane in the upper chamber of a 24-well insert (8 mm pore size) containing serum-free medium. The bottom chamber contained DMEM medium with 10% FBS. Cells were incubated at 37 °C with 5% CO 2 for 48 h after plating. Then, the bottom of the chamber insert was fixed with methanol and stained with crystal violet. Cells that remained in the upper chamber were removed with a cotton swab. The number of cells that invaded through the membrane was determined from digital images captured on an inverted microscope and calculated with Image J 1.47 software. Each experiment was performed in triplicate.

RNA immunoprecipitation (RIP)
RIP experiment was performed to investigate whether ribonucleoprotein (RNP) complex contained lncRNA MALAT1 and its potential binding protein (EZH2) in osteosarcoma cells. The Magna RIP RNA-Binding Protein Immunoprecipitation Kit (Millipore, Bedford, MA, USA) was used according to the manufacturer's instructions. The RNAs were immunoprecipitated using anti-EZH2 (catalog#4905S, Cell Signaling Technology, Beverly, MA, USA) antibody. Total RNA and controls were also assayed to demonstrate that the detected signals were from RNAs specifically binding to EZH2. The final analysis was performed using RT-qPCR and shown as the fold enrichment of MALAT1. The RIP RNA fraction Ct value was normalized to the input RNA fraction Ct value. Primers are listed in Table 2. Each experiment was performed in triplicate.

Chromatin immunoprecipitation (ChIP)
ChIP was performed using the EZ ChIP TM Chromatin Immunoprecipitation Kit (Millipore) according to the manufacturer's protocol. Briefly, cross-linked chromatin was sonicated into 200-1000 bp fragments. The chromatin was immunoprecipitated using anti-EZH2 (#4905S, Cell Signaling Technology) and anti-H3K27me3 (#07-449, Millipore) antibodies. Normal human immunoglobulin G (IgG) was used as a negative control. RT-qPCR was conducted to detect the relative enrichment according to the method described above. Primers are listed in Table 2. Each experiment was performed in triplicate.

Statistical analysis
Kolmogorov-Smirnov test was used to determine the normality of the distribution of data in each group. Data were presented as median (interquartile range). Mann-Whitney U test or Kruskal-Wallis test was employed to compare differences of MALAT1 among different groups. ROC curves were established to discriminate osteosarcoma responding patients from non-responding patients. AUC was used as an accuracy index for evaluating the predictive performance of MALAT1. Survival curves were estimated with Kaplan-Meier method and comparisons were conducted using log-rank test. Correlation testing was analysed using Spearman test. MedCalc 9.3.9.0 (MedCalc, Mariakerke, Belgium) was used for ROC analysis, and other analyses were performed with SPSS version 19.0 software (SPSS, Chicago, IL, USA). Error bars in figures represent SD (Standard Deviation), and statistical significance was defined as two-sided P value < 0.05.