Long noncoding RNA plasmacytoma variant translocation gene 1 promotes epithelial‐mesenchymal transition in osteosarcoma

Abstract Objective Long noncoding RNAs (lncRNAs) are involved in the proliferation, migration, and invasion of tumors. In the current study, our aim was to explore the role of lncRNA plasmacytoma variant translocation gene 1 (PVT1) in osteosarcoma. Methods Quantitative real‐time reverse transcription‐polymerase chain reaction was used to detect the expression of lncRNA PVT1 in osteosarcoma tissues and cells. The relationship between lncRNA PVT1 expression status and the prognosis of patients with osteosarcoma was analyzed. The effect of lncRNA PVT1 on the malignant biological behavior of osteosarcoma cells in vitro was also analyzed. Results LncRNA PVT1 was upregulated in osteosarcoma. High lncRNA PVT1 expression indicated poor prognosis in patients with osteosarcoma. In vitro knockdown of lncRNA PVT1 inhibited the proliferation, migration, and invasion ability of osteosarcoma cells. In addition, we confirmed that lncRNA PVT1 affected the epithelial‐mesenchymal transition of osteosarcoma cells. Conclusion LncRNA PVT1 is a potential therapeutic target for osteosarcoma.


| INTRODUC TI ON
Osteosarcoma is a common type of malignant bone tumor in adolescents, accounting for 5%-10% of all malignancies among adolescents. Osteosarcoma is the sixth most common cause of cancer-related deaths in adolescents. 1 The main cause of death in osteosarcoma is lung metastasis. The 5-year survival rate of patients with osteosarcoma is below 20%, even after active treatment. 2 Targeted therapy and immunotherapy have improved the treatment of malignant tumors. However, there are limited effective therapeutic targets for osteosarcoma. Therefore, there is a need to elucidate the molecular mechanism underlying the progression of osteosarcoma and identify new therapeutic targets for osteosarcoma to enhance prognosis.
Long noncoding RNAs (lncRNAs) are involved in the proliferation, migration, and invasion of tumors. 3 Recent studies have revealed that some lncRNAs such as lncRNA BC040587, lncRNA TUSC7, and lncRNA MALAT1, which are differentially expressed in osteosarcoma, are involved in the progression of osteosarcoma. 4 LncRNA plasmacytoma variant translocation gene 1 (PVT1), which is localized on chromosome 8q24.21, 5 is reported to be a Myc activator in plasmacytoma. 6 Some studies have reported that the expression of lncRNA PVT1 is aberrant in different malignant tumors, including breast, gastric, and colorectal cancers. [7][8][9] LncRNA PVT1 can promote the malignant phenotype of tumor cells by regulating DNA rearrangement and interacting with other oncogenes. 10 However, the role of lncRNA PVT1 in osteosarcoma has been evaluated in only a limited number of studies.

Epithelial-mesenchymal transition (EMT) of cells is known to
play an indispensable role in the progression of tumors. EMT is a reversible cellular process that promotes invasiveness and is traditionally believed to be the prelude to the process of metastasis, wherein cells within a primary tumor lose their epithelial characteristics and acquire both the phenotype and a transcriptional program reminiscent of mesenchymal cells. 11,12 Multiple studies have shown that lncRNAs are involved in the regulation of EMT in osteosarcoma cells. The expression of lncRNA PGM5-AS1 is upregulated in osteosarcoma. It regulates the expression of miR-140-5p and FBN1 through sponge adsorption, thereby promoting tumor EMT, invasion, and metastasis. 13 LncRNA CCAT2, a marker of poor prognosis in patients with osteosarcoma, was found to promote EMT in osteosarcoma cells. 14 Therefore, we also studied the relationship between lncRNA PVT1 and EMT in osteosarcoma cells.
Here, we investigated the expression and molecular function of lncRNA PVT1 in osteosarcoma. The findings of this study suggest that lncRNA PVT1 is a potential therapeutic target for osteosarcoma.

| Bioinformatics analysis
The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/ geo/geo2r/) was employed to examine five GeneChip expression microarrays of osteosarcoma (GSM954792, GSM954810, GSM954823, GSM954797, and GSM954825) to screen differentially expressed lncRNAs. The threshold for differentially expressed lncRNAs was set as follows: log 2 (fold change) >2; adjusted P-value < .05. The differentially expressed lncRNA results from the five datasets were visualized on a volcano plot. The Gene Expression Profiling Interactive Analysis (GEPIA) online tool (http://gepia.cance r-pku.cn) was utilized to determine the expression of differentially expressed genes in osteosarcoma and their correlation with patient prognosis.

| RNA extraction and qRT-PCR
Total RNA was extracted from the cells or tissues using TRIzol reagent (Invitrogen). The purity of the extracted RNA was measured using a spectrophotometer (Unico). Next, the extracted RNA was subjected to reverse transcription to obtain cDNA using the PrimeScript RT-PCR kit (TaKaRa). qRT-PCR analysis was performed using SYBR™ Premix Ex Taq™ (TaKaRa) in the 7500 Fast Real-Time System (Applied Biosystems). GAPDH was used as a loading control. The relative expression of lncRNA PVT1 was calculated by the 2 −△△Ct method. The following primers were used for qRT-PCR analysis: lncRNA PVT1 forward, 5ʹ-CAGCACTCTGGACGGAC-3ʹ; lncRNA PVT1 reverse, 5ʹ-CAACAGGAGAAGCAAACA-3ʹ. GAPDH forward, 5ʹ-ACTAGGCGCT CACTGTTCTC-3ʹ; GAPDH reverse, 5ʹ-ATCCGTTGACTCCGACCTTC-3ʹ.

| Western blotting
Total protein was extracted from the cells and tissues using radioimmunoprecipitation assay (RIPA) lysis buffer (Biosharp). The extracted protein was denatured using loading buffer (R&D Systems).
The protein sample was subjected to sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE) using a 10% gel.
The resolved proteins were transferred onto a polyvinyl difluoride (PVDF) membrane (Millipore). The membrane was incubated with the following primary antibodies (all from Abcam) at 4°C overnight: anti-GAPDH (ab181602), anti-E-cadherin (ab194982), antivimentin (ab92547), anti-N-cadherin (ab18203), and anti-Snail (ab229701). The membrane was washed three times with Trisbuffered saline containing Tween-20 (TBST). The membrane was then incubated with the secondary antibody at room temperature for 1 hour. The membrane was washed three times with TBST. The protein bands were visualized using enhanced chemiluminescence (ECL) solution.
Then, 10 μL of CCK-8 solution was added to each well. The absorbance of the solution was measured at 450 nm using a microplate reader (Bio-Rad).

| Colony formation assay
Briefly, the cells were inoculated in a 6-well plate (500 cells/well) and cultured in complete DMEM for 8-12 days. The cells were washed with phosphate buffered saline (PBS), fixed in methanol for 15 minutes, and stained with 0.1% crystal violet for 15 minutes.

| Transwell assay
Migration and invasion assays were performed using a Transwell chamber. For the invasion assay, the upper Transwell chamber was pre-coated with Matrigel (BD Biosciences). For the migration assay, Matrigel was not added. Briefly, the cells (1 × 10 5 ) were inoculated in the upper Transwell chamber in a serum-free medium. To the lower chamber, medium containing 10% FBS was added. The cells were incubated at 37°C and 5% CO 2 . The cells were fixed in methanol for 15 minutes, stained with 0.1% crystal violet for 15 minutes, and counted under a microscope.

| Wound healing assay
The wound healing assay was performed to evaluate the cell migration ability. Briefly, the cells were inoculated in a 6-well plate until they formed a monolayer. Next, a scratch wound was introduced in the monolayer using a 200-μL pipette tip. The cells were incubated in complete medium at 37°C and 5% CO 2 . The representative images were captured at 0 and 24 hours to evaluate wound healing.

| Statistical analysis
All statistical analyses were performed using SPSS 20.0 software (SPSS Inc) and GraphPad Prism 7 (GraphPad Software Inc). The nominal data were analyzed by the chi-scuare test, whereas the enumeration data were analyzed by the t test. Moreover, the Chi-square test was used to analyze the relationship between lncRNA PVT1 expression and clinicopathological features of patients. Kaplan-Meier and log-rank tests were used to analyze the effects of clinicopathological characteristics on patient prognosis. In this study, the overall survival (OS) was used as the main endpoint. The difference was considered statistically significant when the P-value was <.05.

| Bioinformatic prediction
We analyzed the five GeneChip microarrays of osteosarcoma and constructed a volcano plot of the differentially expressed lncRNAs ( Figure 1A). In total, 237 differentially expressed lncRNAs were identified, including 57 downregulated lncRNAs and 180 upregulated lncRNAs. The expression of lncRNA PVT1 was markedly upregulated in osteosarcoma tissue. The GEPIA online analysis revealed that the osteosarcoma samples exhibited significantly higher expression of lncRNA PVT1 than that of the normal samples ( Figure 1B). The survival analysis revealed that high lncRNA PVT1 expression was associated with poorer prognosis of osteosarcoma ( Figure 1C,D).

| Upregulated expression of lncRNA PVT1 in osteosarcoma cells and tissues
The results of the bioinformatics analysis were validated by qRT-PCR.
The expression of lncRNA PVT1 was analyzed in 78 pairs of osteosarcoma tissues and adjacent non-tumorous tissues. The osteosarcoma tissues exhibited significantly higher lncRNA PVT1 expression than that of the adjacent non-tumorous tissues (Figure 2A). The expression of lncRNA PVT1 was also determined in osteosarcoma cell lines. As shown in Figure 2B

| Correlation of lncRNA PVT1 expression with prognosis in patients with osteosarcoma
To investigate the correlation between lncRNA PVT1 expression and clinicopathological features of patients with osteosarcoma, 78 patients were categorized into the high lncRNA PVT1 (n = 48) and low lncRNA PVT1 (n = 30) expression groups using the average expression of lncRNA PVT1 as a cutoff value. The enhanced expression of lncRNA PVT1 was strongly correlated with the degree of tumor differentiation, distant metastasis, and disease stage in patients with osteosarcoma (P < .05; Table 1). However, lncRNA PVT1 expression was not correlated with age, sex, tumor location, tumor size, or pathological grade ( Table 1). The OS of patients with osteosarcoma after follow-up was plotted. The log-rank test analysis revealed that the high lncRNA PVT1 expression group had a poorer OS than that of the low lncRNA PVT1 expression group ( Figure 3A). In addition, the main factors affecting the OS of patients with osteosarcoma were differentiation, distant metastasis, and disease stage ( Figure 3B-D). Cox regression analysis model was constructed to examine the effect of lncRNA PVT1 on the prognosis of patients with osteosarcoma. Univariate regression analysis revealed that tumor size, differentiation, historical grade, distant metastasis, and disease stage were highly correlated with OS in patients with osteosarcoma (Table 2). Multivariate regression analysis revealed that high expression of lncRNA PVT1 was an independent risk factor for the prognosis of patients with osteosarcoma (Table 2).  Figure 4B). The effect of lncRNA PVT1 knockdown on the migration of osteosarcoma cells was evaluated by wound healing assay. As shown in Figure 4D, the migration of shPVT1-transfected cells was significantly suppressed compared with that of shNC-transfected cells.

| Role of lncRNA PVT1 in the EMT of osteosarcoma cells
The EMT is a key step in tumor cell metastasis. Thus, the potential

| D ISCUSS I ON
LncRNA PVT1 is reported to be a common retrovirus integration site in mouse leukemia. 15 The integration site is located in the sense

| CON CLUS ION
This study demonstrated the upregulation of lncRNA PVT1 expression in osteosarcoma cells and tissues and that lncRNA PVT1 is a potential therapeutic target for osteosarcoma. However, further studies are needed to elucidate the molecular mechanism by which lncRNA PVT1 promotes the progression of osteosarcoma.