Hindawi BioMed Research International Volume 2020, Article ID 9567846, 12 pages https://doi.org/10.1155/2020/9567846

Research Article lncRNA MRUL Suppressed Non-Small Cell Lung Cancer Cells Proliferation and Invasion by Targeting miR-17-5p/SRSF2 Axis

Ying Chen,1 Tianle Shen,2 Xuping Ding,3 Cui Ma,4 Lei Cheng,1 Liming Sheng,1 and Xianghui Du 1

1Department of Radiation Oncology, Zhejiang Key Laboratory of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital); Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, 1 Banshandong Road, 310022 hangzhou, Zhejiang, China 2Department of Radiation Oncology, Jiaotong University School of Medicine, 197 Ruijin Second Road, 200000 Shanghai, China 3Department of Respiratory Medicine, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, 310000 Zhejiang, China 4Department of Endocrinology and Metabolism, Zhejiang Greentown Cardiovascular Hospital, 409 Gudun Road, 310000 Zhejiang, China

Correspondence should be addressed to Xianghui Du; [email protected]

Received 19 June 2020; Revised 7 September 2020; Accepted 9 September 2020; Published 14 October 2020

Academic Editor: Tao Huang

Copyright © 2020 Ying Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The two broad histological subtypes of lung cancer are small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), which are the leading causes of cancer-related death in the world. Long noncoding RNAs (lncRNAs) have been verified to be critical in the regulation of cancer development. The present study identified and elucidated the regulatory roles of a novel lncRNA MRUL in NSCLC. The results showed that MRUL was overexpressed in NSCLC samples and correlated with the poor prognosis of patients who had NSCLC. Moreover, this research has for the first time demonstrated that MRUL acted as an oncogenetic lncRNA in NSCLC. Knockdown of MRUL considerably repressed NSCLC cell proliferation, invasion, and migration. The bioinformatics analysis showed that MRUL was involved in regulating multiple RNA splicing and proliferation- related biological processes, such as mRNA splicing, RNA splicing, mRNA processing, mRNA 3′-end processing, mRNA splice site selection, and DNA replication. By combining bioinformatics analysis and experimental validation, we found that MRUL regulated NSCLC progression through promoting SRSF2 by sponging miR-17 in NSCLC cells. The discoveries indicated that MRUL could be a therapeutic target and a potential diagnostic for NSCLC.

1. Introduction Long noncoding RNAs (lncRNAs) are a type of ncRNAs which have longer than 200 bps with no or limited - Lung cancer, which includes small cell lung cancer (SCLC) coding capacity [4]. Emerging studies demonstrated that [1] and non-small cell lung cancer (NSCLC) [2], has been lncRNAs participated in regulating cancer tumorigenesis playing the leading part in causing tumor-related death and progression through multiple cancer-related pathways, worldwide. NSCLC can then be classified into subcategories including Wnt signaling and PI3K signaling. lncRNAs could of squamous cell carcinoma, adenocarcinoma, and large cell affect cancer proliferation, differentiation, and metastasis. carcinoma [3]. Multiple causes, such as genetic factors, air For example, silencing of PVT1 enhances radiosensitivity in pollution, and smoking, were regarded to be related to NSCLC by sponging miR-195 [5]. The contribution to NSCLC progression. However, the mechanisms underlying NSCLC’s progression by lncRNA SNHG1 is made by activat- NSCLC remained to be further investigated. ing Wnt/β-catenin signaling pathway [6] and inhibiting 2 BioMed Research International miR-101-3p. And NSCLCAT1 enhanced NSCLC cell migra- vector (DingGuoChangSheng Biotechnology Co. Ltd., Bei- tion and invasion via the Hippo signaling pathway through jing, China), 50 to 100 nM small interfering RNA (siRNA) the interaction with CDH1 [7]. Therefore, understanding ( Pharma Co., Shanghai, China), Lipofectamine 2000 the roles of lncRNAs in NSCLC is of great significance for (Invitrogen Int., USA), and lentivirus vector-MRUL(−) exploring the underlying mechanisms of NSCLC progression (RiboBio Co., Guangzhou, China) were employed following and discovering new therapeutic strategies for NSCLC. the manufacturer’s recommendations as portrayed earlier lncRNA MRUL was a nonprotein coding transcript of (19). siRNA sequences are presented here: siRNA targeting DMTF1 [8]. Interestingly, a tumor suppressor as DMTF1 NR_024549 (MRUL), siMRUL-1, GGCCUUUGUUUGCA was regarded in human cancers, while MRUL was considered GUUUATT; siMRUL-2, AACACUUUCCUGUUUUGGG linked with the progression of human cancers. MRUL, for UC; siMRUL-3, AGUUUCUACUGUUACUGUGUC; siP- example, in gastric cancer samples, was upregulated, and it gp (targeting P-gp), GGGACAGGAAUAAUUAUAUTT; was involved in the regulation of multiple drug resistance and siNC (negative control), UUCUCCGAACGUGUCA [9]. Moreover, the functional roles of MRUL in NSCLC CGUTT. remain unknown. This study aimed at figuring out MRUL’s expression and role in NSCLC. This study found that in 2.5. Cell Growth and Invasion. To assay cell growth, the incu- NSCLC tissues, the MRUL expression level was upregulated. bation of the cells happened in the 96-well plate, and they Moreover, to explore the potential functions of MRUL in were stained with CCK-8 (Dojindo Chemical Laboratory, ff NSCLC, loss-of-function assays were carried out. Kumamoto, Japan) at di erent moments. The multilabel plate reader (PerkinElmer, MA) was employed to decide 2. Materials and Methods the absorbance at 450 nm. Matrigel-coated Transwell cham- bers (Millipore, MA, USA) helped to measure cell invasion. 2.1. The Protein Expression Level of DMTF1 in Lung Cancer On the upper chamber where no serum existed, those cells Tissues. The Human Protein Atlas (http://www.proteinatlas were cultured. In the bottom well, the medium with 10% .org) for the online query was used, DMTF1 was entered in FBS was added to make it the chemoattractant. One percent the search field, and the search button was clicked. The crystal violet was used to fix the invasive cells, and then, they option of the lung in the tissue group was selected to evaluate were counted. the expression level of DMTF1 protein in lung cancer tissues. 2.6. Statistical Analysis. All of the results were presented as 2.2. Quantitative Real-Time Polymerase Chain Reaction mean ± standard deviation (SD). All experiments were (qRT-PCR). TRIzol reagent (Invitrogen, USA) was employed repeated at least 3 times, and representative experiments to extract total RNAs from tissues or samples, and the syn- were shown. SPSS [10] statistical (SPSS, Chicago, USA) was thesis of cDNA was carried out based on the protocol of employed to conduct statistical analysis. Student’s t-test anal- the manufacturer. By using SYBR Green qPCR Mixes (Invi- ysis of variance was employed to measure the statistical dif- trogen, CA) based on the information given by the manufac- ference. If p is below 0.05, then the difference was turer, quantitative real-time PCR (qRT-PCR) was conducted considered statistically significant. to decide the expression of MRUL and E-cadherin, cyclin D1, N-cadherin, Vimentin, and Snail. Through the use of the IQ5 3. Result real-time PCR System machine, qRT-PCR was conducted. 3.1. The RNA Levels, Not Protein Levels of DMTF1 2.3. Western Blot Analysis. From cells or tissues, total protein Expression, Were Increased in NSCLC Samples. lncRNA lysates were extracted. By using 10% sodium dodecyl sulfate- MRUL was a nonprotein coding transcript of DMTF1. polyacrylamide gel electrophoresis (SDS-PAGE), equal DMTF1 was reported to be a tumor suppressor. Very inter- quantity of protein was separated, and they were transferred estingly, we found that DMTF1 RNA levels were significantly to polyvinylidene difluoride membranes (PVDF, Bio-Rad, upregulated in both types of NSCLC samples, including Hercules, CA). After blocking with nonfat milk, in the envi- LUAD and LUSC tissues by analyzing the TIMER database ronment of 1 : 3000 dilutions at 4°C overnight, the incubation (Figure 1(a)), suggesting that DMTF1 might serve as an of membrane with p-AKT and GAPDH antibodies (Bio- oncogene in NSCLC, and this did not go along with past world Biotechnology) took place. The incubation of the studies. membrane with secondary antibody (Pierce, IL, USA) was Furthermore, we analyzed the protein levels of DMTF1 in carried out subsequent to its being washed in TBST. The NSCLC using The Human Protein Atlas. The results showed employment of ECL reagents (Pierce, IL, USA) helped to that DMTF1 protein levels were not significantly dysregu- detect the protein band. lated in lung cancer samples compared to normal tissues. Thus, we hypothesized that DMTF1 played its roles in 2.4. Cell Lines, Cell Cultures, and Transfections. The Acad- NSCLC probably via its nonprotein coding transcripts. What emy of Military Medical Sciences (Beijing, China) provided is more, the association between lower expression levels of the human NSCLC cell line A549 and H1299. In a 5% CO2 lncRNA MRUL and advanced stage in patients who had fi ° humidi ed incubator at 37 C and RPMI 1640 medium NSCLC had been discovered (Figure 1(b)). (Thermo Scientific, USA) supplemented with 10% fetal calf serum (FCS) (Thermo Scientific), these cells were cultured. 3.2. High lncRNA MRUL Expression Correlates with Poor For transfections, pcDNA3.1(+)-MRUL and pcDNA3.1(+) Survival of LUAD but Not LUSC. To explore whether the BioMed Research International 3

13 ⁎⁎⁎ ⁎⁎⁎ ⁎⁎⁎⁎⁎ ⁎⁎⁎⁎ ⁎⁎⁎ ⁎⁎⁎⁎⁎⁎ ⁎⁎⁎ ⁎ ⁎⁎⁎ ⁎ ⁎⁎⁎ ⁎⁎⁎ ⁎⁎⁎

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7 DMTF1 expression level (log2 RESM) OV.tumor UCS.tumor LGG.tumor ACC.tumor GBM.tumor KIRP.tumor KIRC.tumor LIHC.tumor UVM.tumor CESC.tumor ESCA.tumor LUSC.tumor KICH.tumor SARC.tumor BLCA.tumor PCPG.tumor STAD.tumor DLBC.tumor BRCA.tumor KIRP.normal PRAD.tumor TGCT.tumor READ.tumor UCEC.tumor HNSC.tumor LAML.tumor MESO.tumor PAAD.tumor LUAD.tumor KIRC.normal SKCM.tumor LIHC.normal CHOL.tumor THCA.tumor ESCA.normal LUSC.normal COAD.tumor KICH.normal BLCA.normal THYM.tumor STAD.normal BRCA.normal PRAD.normal READ.normal UCEC.normal HNSC.normal LUAD.normal CHOL.normal THCA.normal COAD.normal SKCM.metastasis BRCA-Her2.tumor BRCA-Basal.tumor BRCA-Luminal.tumor HNSC-HPVpos.tumor HNSC-HPVneg.tumor (a)

(b)

Figure 1: Long noncoding RNA MRUL was upregulated in NSCLC. (a) MRUL expression levels were downregulated in LUAD and LUSC samples compared with normal tissues. (b) The protein levels of DMTF1 were not significantly dysregulated in NSCLC samples compared to normal lung tissues. Significance was defined as p <0:05 (∗p <0:05; ∗∗p <0:01; ∗∗∗ p <0:001). relation between lncRNA MRUL and the survival of This study showed that higher lncRNA MRUL expres- patients who had lung cancer existed, we performed the sion was associated with shorter first progression survival Kaplan-Meier curve analysis by using the TCGA database. time and overall survival time in LUAD, but not with LUSC As presented in Figure 2, it was found the positive corre- (Figures 2(c)–2(e)). Similar results were also observed by lation existed between higher lncRNA MRUL expression analyzing an independent GEO dataset, GSE50081 and shorter disease-free survival time in patients who (Figures 2(f)–2(h)). had LUAD (Figure 2(a)), but not LUSC (Figure 2(b)), indicating that lncRNA MRUL might be a biomarker of 3.3. Knockdown of lncRNA MRUL Suppressed NSCLC Cell poor survival. Furthermore, the Kaplan-Meier plotter data- Proliferation and Cell Cycle. This study further teased out base was employed to analyze the association between the subcellular localization of MRUL in NSCLC cells, includ- lncRNA MRUL expression and the prognosis. An amount ing A549 and H1299 cells. The RT-PCR assay results made it of 1926 cases of NSCLC together with available data for clear that compared with the MRUL level in nuclear in both lncRNA MRUL expression and the general rate of survival H1299 and A549 cell lines, it was higher in the cytoplasm were included in the database. (Figures 3(a) and 3(b)), suggesting that MRUL was a 4 BioMed Research International

TCGA-LUAD TCGA-LUSC 1.0 1.0 HR = 1.49 (0.95 – 2.33) HR = 1.24 (0.74 – 2.1) Logrank p = 0.42 0.8 Logrank p = 0.077 0.8

0.6 0.6

0.4 0.4 Probability Probability 0.2 0.2

0.0 0.0 0 50 100 150 200 250 0 50 100 150 Time (months) Time (months) Expression Expression Low Low High High (a) (b) NSCLC LUAD LUSC 1.0 1.0 HR = 1.8 (1.26 – 2.58) 1.0 HR = 1.53 (1.26 – 1.85) HR = 1.71 (1.01 – 2.9) Logrank p = 0.0011 0.8 Logrank p = 1.5e–05 0.8 0.8 Logrank p = 0.052

0.6 0.6 0.6

0.4 0.4 0.4 Probability Probability Probability 0.2 0.2 0.2

0.0 0.0 0.0 0 50 100 150 200 0 20406080100120 0 20 40 60 80 100 120 140 Time (months) Time (months) Time (months) Expression Expression Expression Low Low Low High High High (c) (d) (e) GSE50081-NSCLC GSE50081-LUAD GSE50081-LUSC 1.0 1.0 1.0 HR = 2 (1.15 – 3.49) HR = 2.19 (1.14 – 4.21) HR = 1.81 (0.52 – 6.29) p Logrank p = 0.016 Logrank p = 0.34 0.8 Logrank = 0.012 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4 Probability Probability Probability 0.2 0.2 0.2

0.0 0.0 0.0 0 20 40 60 80 100 120 140 0 20406080100 0 20 40 60 80 100 120 140 Time (months) Time (months) Time (months) Expression Expression Expression Low Low Low High High High (f) (g) (h)

Figure 2: High lncRNA MRUL expression correlates with poor survival of LUAD, but not LUSC. (a, b) TCGA dataset analysis revealed that high lncRNA MRUL expression correlates with poor survival of LUAD, but not LUSC. (c–e) The Kaplan-Meier plotter database analysis revealed high lncRNA MRUL expression correlated with poor survival of NSCLC and LUAD, but not LUSC. (f–g) GSE50081 dataset analysis revealed that high lncRNA MRUL expression correlated with poor survival of NSCLC and LUAD, but not LUSC. Significance was defined as p <0:05 (∗p <0:05; ∗∗p <0:01; ∗∗∗ p <0:001). BioMed Research International 5

2.5 1.5 A549 1.5 H1299 2.0 1.5 1.0 1.0 1.5 1.0 1.0 0.5 0.5 0.5 Relative MRUL levels MRUL Relative 0.5 levels MRUL Relative Relative MRUL levels MRUL Relative 0.0 levels MRUL Relative 0.0 0.0 0.0 A549- A549- H1299- H1299- NC cytoplasm nuclear cytoplasm nuclear NC siMRUL-1 siMRUL-1 siMRUL-1 siMRUL-1 (a) (b) (c) (d) A549 ⁎⁎⁎ 3 4 H1299 ⁎⁎⁎

3 2 ⁎⁎⁎ ⁎⁎⁎ 2

OD450 nM OD450 1 OD450 nM OD450 1

0 0 Day1 Day2 Day3 Day4 Day5 Day1 Day2 Day3 Day4 Day5

NC NC siMRUL-1 siMRUL-1 siMRUL-2 siMRUL-2 (e) (f)

Figure 3: Knockdown of lncRNA MRUL suppressed NSCLC proliferation. (a, b) RT-PCR assay showed MRUL was located in the cytoplasm in both A549 and H1299 cells. (c, d) RT-PCR assay showed MRUL expression levels in A549 and H1299 cells after transfecting with siRNA-1 and siRNA-2. (e, f) Knockdown of MRUL induced cell proliferation in A549 and H1299. Significance was defined as p <0:05 (∗p <0:05; ∗∗p <0:01; ∗∗∗ p <0:001). cytoplasm located in lncRNA. In order to work out MRUL’s invading cells decreased by 36 and 41.3 percentage in siM- functional effect on NSCLC cell, 2 siRNAs reported by previ- RUL-1- and siMRUL-2-transfected A549 cells, compared ous studies were used to knockdown the expression levels of with control groups (Figures 5(a) and 5(b)). The results MRUL in H1299 and A549 cells. The knockdown efficiency obtained by using H1299 cells were also similar was presented in (Figures 3(c) and 3(d)). (Figures 4(c), 4(d), 5(c), and 5(d)). In an effort to detect MRUL’seffect on cell proliferation, the CCK-8 assays were applied (Figures 3(e)–3(h)). We 3.5. Functional Analysis of lncRNA MRUL in NSCLC. The noticed that compared with siNC transfected cells, the cell detailed mechanisms of MRUL regulating NSCLC progres- viability decreased considerably in siMRUL-1- and sion remained largely unclear. Here, we conducted a coex- siMRUL-2-transfected cells. The flow cytometric analysis pression analysis of MRUL in NSCLC using the cBioPortal made it clear that the knockdown of MRUL significantly database [11] (https://www.cbioportal.org/). After selection, increased the proportion of G1 phase cells by 30% and the potential targets of MRUL in NSCLC were the top 1000 reduced the proportion of S phase cells by 30%. These results coexpressing . GO analysis of the 1000 target genes suggested MRUL played as an oncogene in NSCLC. revealed that some of the biological processes were involved, such as transcription, mRNA splicing, RNA splicing, mRNA 3.4. Knockdown of lncRNA MRUL Suppressed NSCLC Cell processing, mRNA 3′-end processing, RNA processing, reg- Migration and Invasion. This study then looked at ulation of protein kinase activity, cilium morphogenesis, whether NSCLC cell invasion and migration abilities were mRNA splice site selection, regulation of RNA splicing, affected by MRUL. Through the performance of Transwell DNA replication, cilium-dependent cell motility, cilium assay, we found the migrating cells in siMRUL-1- and assembly, RNA export from the nucleus, and mismatch siMRUL-2-transfected A549 cells decreased by about 62 repair (Figure 6(a)). and 56 percentage compared to control groups Furthermore, the PPI [12] network revealed interactions (Figures 4(a) and 4(b)). By adding Matrigel in a Transwell between target genes (Figure 7(a)). The use of the MCODE chamber, this study further detected the influence on the plugin (the nodes with edges ≥ 2 − core and degree cut − off invasive ability of NSCLC produced by MRUL knock- ≥ 2) helped perform module analysis, and we identified four down. The results suggested that MRUL knockdown sig- hub networks regulated by MRUL in NSCLC. Figures 6(b)– nificantly inhibited A549 cell invasion. The numbers of 6(e) show that there are 68 edges and 19 nodes in hub 6 BioMed Research International

A549 NC siMRUL-1 siMRUL-2

A549 1.5

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Fold changed over negative control 0.0 NC siMRUL-1 siMRUL-2 (a) (b) H1299 NC siMRUL-1 siMRUL-2

H1299 1.5

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Fold changed over negative control 0.0 NC siMRUL-1 siMRUL-2 (c) (d)

Figure 4: Knockdown of MRUL induced cell migration in NSCLC. (a, b) Knockdown of MRUL suppressed cell migration ability in A549 cells. (c, d) Knockdown of MRUL suppressed cell migration ability in H1299 cells. Significance was defined as p <0:05 (∗p <0:05; ∗∗p < 0:01; ∗∗∗ p <0:001). network 1, 37 edges and 13 nodes in hub network 2, 16 edges RNA splicing and cell cycle. In order to validate these find- and 10 nodes in hub network 3, and 13 edges and 9 nodes in ings, we knocked down lncRNA MRUL expression and hub network 4. detected RNA splicing regulators expression in NSCLC cell, Next, the potential functions of these hub networks in including RBM25, RBM39, RBM5, RNPC3, SUGP2, NSCLC were disclosed through the application of the THOC1, ACIN1, PRPF3, PRPF38B, PRPF4B, SRSF11, and ClueGO [13] analysis. These results showed the involvement SRSF2 (Figure 8(a)). The results showed that knockdown of of hub network 1 in regulating the termination of RNA poly- MRUL significantly suppressed SRSF11, SRSF2, RBM25, merase II transcription, spliceosome, and mRNA splicing. RBM39, and RBM5 expression in A549 and H1299 cells. Hub network 2 was involved in regulating centriole. These Among these regulators, the inhibition of SRSF2 expression results were consistent with the above analysis that lncRNA was the most significant; we focused on SRSF2, which was MRUL was associated with the regulation of RNA splicing taken as an oncogene in human cancers and involved in reg- Figures 7(a) and 7(b). ulating cell cycle and metastasis. By detecting the protein levels of SRSF2 after silencing of MRUL, the results showed 3.6. MRUL Regulated SRSF2 Expression. The bioinformatics knockdown of MRUL inhibited SRSF2 protein levels analysis showed the involvement of MRUL in regulating (Figures 8(b) and 8(c)). BioMed Research International 7

A549 invasion NC siMRUL-1 siMRUL-2

A549 invasion 1.5

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Fold changed over negative control 0.0 NC siMRUL-1 siMRUL-2 (a) (b) H1299 invasion NC siMRUL-1 siMRUL-2

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Fold changed over negative control 0.0 NC siMRUL-1 siMRUL-2 (c) (d)

Figure 5: Knockdown of MRUL induced cell invasion in NSCLC. (a, b) Knockdown of MRUL suppressed cell invasion ability in A549 cells. (c, d) Knockdown of MRUL suppressed cell invasion ability in H1299 cells. Significance was defined as p <0:05 (∗p <0:05; ∗∗p < 0:01; ∗∗∗ p <0:001).

3.7. MRUL Regulated SRSF2 Expression via Physically in both A549 and H1299 cells were suppressed by overex- Binding to miR-17-5p. Next, we predicted the miRNAs tar- pression of miR-17-5p (Figures 9(f) and 9(i)). Enhanced geting MRUL regulated SRSF2 using the miRDB database expression of miR-17-5p suppressed SRSF2 protein levels in (http://mirdb.org/). A total of 20 candidate miRNAs were both A549 and H1299 cells, which was displayed by Western identified to target both MRUL and SRSF2 (Figure 9(a)). blot assays (Figures 9(d) and 9(e)). Then, we compared them based on their predicted scores and free energy. These miRNAs were prioritized, and miR- 4. Discussion 17-5p was selected for subsequent analysis. This study was centered on miR-17-5p, which was reported as a tumor sup- Recently, emerging evidences demonstrated that lncRNAs pressor. The correlation analysis showed the expression were deregulated and played crucial roles in tumor tumori- levels were negatively correlated to the expression levels of genesis and pathogenesis. In NSCLC, a series of lncRNAs MRUL (Figures 9(g) and 9(h)) and SRSF2 (Figures 9(b) and were reported to be related to cancer progression. For exam- 9(c)). Enhanced expression of miR-17-5p considerably sup- ple, via suppressing autophagy, the chemosensitivity of pressed the luciferase activity of constructed reporter con- NSCLC cells is enhanced by silencing lncRNA-XIST, and taining MRUL and SRSF2, but not the empty reporter, through regulating the WNT pathway in NSCLC and repres- which has been displayed by the dual-luciferase reporter sing E-cadherin, epithelial-mesenchymal transition (EMT) is assays. RT-PCR assays showed that SRSF2 and MRUL levels enhanced by the overexpression of FEZF1-AS1 [14]. The 8 BioMed Research International

Qvalue Transcription, DNA-templated mRNA splicing, via spliceosome 0.04 RNA splicing mRNA processing DNA replication 0.03 Cilium morphogenesis Cilium assembly RNA processing 0.02 mRNA 3′-end processing RNA export from nucleus Regulation of protein kinase activity Regulation of RNA splicing 0.01 Mismatch repair mRNA splice site selection Cilium-dependent cell motility 0.00 0.05 0.10 0.15 0.20

Count 30 90 60 120 (a)

PABPN1 CWC25 SRRT AHI1 CEP152 HAUS3 HNRNPU SRSF11 CPSF7 DDX5 CEP83 SFI1 PPWD1 CEP290 SRRM2 SNRNP70 SRSF5 FBF1 SRSF6 HAUS5 PCF11 RBM5 CEP162 PRPF3 CNTRL SF3B1 SRSF2 AKAP9 U2AF1L4 HNRNPH1 IQCB1 OFD1

(b) (c)

ASB16 ADCY6 ANAPC4 TAS2R20

PCP2 UBE2G2 ASB14 GNB3

FBXO44 KLHL3 TAS2R14 GABBR1 KCTD7

TAS2R10 UNKL WSB1 TAS2R5 ARIH2 TAS2R4

(d) (e)

Figure 6: Bioinformatics analysis of MRUL in NSCLC. (a) Bioinformatics analysis of MRUL in NSCLC. (b–e) Construction of hub networks regulated by MRUL in NSCLC, including hub network 1 (b), hub network 2 (c), hub network 3 (d), and hub network 4 (e). BioMed Research International 9

SRSF11

mRNA export from nucleus mRNA 3′-end processing SRSF2 CPSF7 U2AF1L4 Termination of RNA mRNA splicing, via PCF11 polymerase II spliceosome SRRM2 PRPF3 transcription SRSF5 PABPN1 PPWD1 SRSF6 Spliceosome CWC25 SF3B1

SRRT HNRNPU Regulation of mRNA processing

DDX5 Regulation of mRNA SNRNP70 HNRNPH1 Spliceosomal complex assembly splicing

RBM5 (a)

CEP83 AHI1

FBF1 Recruitment of NuMA tomitoticCilium basal body docking centrosomes IQCB1 Centriole Loss of NIp from Organic biogenesis and AKAP9 maintenance AURKA activation by TPX2mitoticHAUS5 CEP290 CEP162 centrosomes Cilium assembly HAUS3 OFD1 G2/M transition CNTRL SFI1 Anchoring of the basal body to the Loss of resulted for CEP152 plasma membrane interphase microtubuls organization from the centrosome Recruitment of mitotic centrosome proteins and complexes Centrosome maturation Mitotic G2-G2/M phases Mitotic prometaphase Regulation of PLK1 activity at G2/M Transition (b)

Figure 7: Bioinformatics analysis of MRUL regulated hub networks 1 and 2 in NSCLC. (a, b) Bioinformatics analysis of MRUL regulated hub networks 1 (a) and 2 (b) in NSCLC. present study identified and elucidated the regulatory roles of samples, the DMTF1 gene was deleted [17]. However, for a novel lncRNA MRUL in NSCLC. The results showed that tumor suppression in Kras-mediated lung carcinogenesis MRUL was overexpressed in NSCLC samples and correlated mouse models, DMTF1 is haplo-insufficient [18]. Very inter- with the poor prognosis of NSCLC patients. Moreover, this estingly, through the analysis of public datasets, which research for the first time demonstrated MRUL played as include the LUAD, TCGA [19], and LUSC databases, this an oncogenetic lncRNA in NSCLC. NSCLC cell proliferation, study found that compared with normal tissues, DMTF1 invasion, and migration were considerably suppressed by the RNA levels were significantly overexpressed in NSCLC sam- knockdown of MRUL. By combining bioinformatics analysis ples. Importantly, protein levels of DMTF1 in NSCLC were and experimental validation, we found that MRUL regulated not remarkably dysregulated. These results suggested NSCLC progression through promoting SRSF2 by sponging DMTF1 might play its roles in NSCLC via its nonprotein miR-17 in NSCLC cells. These results suggested the potential coding transcripts. lncRNA MRUL was a nonprotein coding of MRUL to be a diagnostic and therapeutic target of NSCLC. transcript of DMTF1. A previous study revealed that MRUL DMTF1 was regarded as a tumor suppressor in human was involved in regulating multidrug-resistance in gastric cancers [15]. DMTF1 was regulated by Ras-Raf signaling cancer (GC) cell via ABCB1 [20]. Compared with normal tis- and involved in activating the Arf-p53 pathway [16]. Previ- sues, MRUL was considerably overexpressed in GC. MRUL ous studies reported that in roughly 40% of human NSCLC knockdown in GC cells promoted cell apoptosis [21]. 10 BioMed Research International

2.0

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0.5 Relative expression levels

0 SRRT SF3B1 SRSF5 SRSF2 SRSF6 RBM5 DDX5 CPSF7 PCF11 PRPF3 SRSF11 SRRM2 CWC25 PPWD1 PABPN1 U2AF1L4 SNRNP70 HNRNPU HNRNPH1

NC siMRUL-1 siMRUL-2 (a) NC siMRUL-1 siMRUL-2 NC siMRUL-1 siMRUL-2

SRSF2 SRSF2

ACTB ACTB

(b) (c)

Figure 8: Validation of downstream targets of MRUL. (a) RT-PCR assay showed the expression levels of downstream targets after transfecting with siMRULs. (b, c) Western blot assay revealed the protein levels of SRSF2 after transfecting with siMRULs in A549 (b) and H1299 (c).

Nevertheless, MRUL’s roles in NSCLC remain to be classi- some protein and a key regulator of RNA splicing disorders fied. This study made it clear that compared with early- in cancer. Related reports have shown that SRSF2 is essential stage NSCLC samples, lncRNA MRUL was overexpressed for the pathogenesis and progression of liver cancer cells and in advanced stage NSCLC samples. Higher expression levels can be used as a prognostic factor for HCC patients. In clear of MRUL were significantly correlated with shorter disease- cell renal cell carcinoma, decreased expression of SRSF2 con- free survival time in patients with LUAD, but not LUSC, tributes to the protection of cancer cell viability. By using bio- which has been shown in the Kaplan-Meier curve analysis. informatics analysis, we predicted that lncRNA’seffect upon Moreover, knockdown of lncRNA MRUL decreased NSCLC MRUL expression was mediated by miR-17-5p. Further val- cell cycle, cell growth, invasion, and migration. In sum, the idation showed that MRUL and SRSF2 were miR-17-5p’s data indicated that lncRNA MRUL was probably an onco- direct targets. Being a member of miR-17-92 cluster, miR- gene in NSCLC. 17-5p played as a key regulator of cancer proliferation, cell Aiming to investigate the detailed mechanisms of MRUL cycle, apoptosis, and autophagy. The expression of miR-17- in NSCLC, we applied the GO and KEGG pathway analysis 5p is upregulated in pancreatic adenocarcinoma, and high and coexpression analysis for MRUL. The bioinformatics levels of miR-17-5p are associated with poor prognosis. It analysis showed that MRUL was involved in regulating mul- was found in colon cancer that miR-17-5p reduced the tiple RNA splicing and proliferation-related biological pro- expression of tumor suppressor B cell junction (BLNK), lead- cesses, such as mRNA splicing, RNA splicing, mRNA ing to increased migration and invasion of cancer cells. In processing, mRNA 3′-end processing, mRNA splice site NSCLC, emerging evidences demonstrated miR-17-5p func- selection, and DNA replication. By constructing PPI net- tioned as a potential biomarker for cancer prognosis and a works, we identified the critical role of SRSF2 in MRUL reg- tumor suppressor. It was found that miR-17-5p was down- ulating networks and its involvement in regulating RNA regulated in NSCLC, and the negative relation between splicing in cancer progression. Furthermore, we found that serum miR-17-5p levels and the survival of NSCLC patients knockdown of MRUL significantly suppressed SRSF2 expres- was also discovered. Mechanically, miR-17-5p suppressed sion in NSCLC cells. SRSF2 is a gene encoding a key spliceo- multiple targets in NSCLC, including BECN1, RAD21, BioMed Research International 11

SRSF2 1.5 A549 1.5 H1299

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0.5 0.5 Relative expression of SRSF2 Relative expression of SRSF2 0.0 0.0 MRUL NC miR-17-5p NC miR-17-5p (a) (b) (c)

1.5 A549

A549 H1299 1.0 NC miR-17-5p NC miR-17-5p

SRSF2 SRSF2 0.5

ACTB ACTB activity luciferase Relative 0.0 NC miR-17-5pNC miR-17-5p (d) (e) (f) 1.5 A549 1.5 H1299 1.5 H1299

1.0 1.0 1.0

0.5 0.5 0.5 Relative luciferase activity luciferase Relative Relative expression of MRUL Relative expression of MRUL of expression Relative 0.0 0.0 0.0 NC miR-17-5p NC miR-17-5p NC miR-17-5pNC miR-17-5p (g) (h) (i)

Figure 9: MRUL regulated SRSF2 expression via physically binding to miR-17-5p. (a) Venn diagrams for SRSF2-binding miRNAs and MRUL-binding miRNAs. (b, c) RT-PCR analysis of SRSF2 expression levels in A549 and H1299 after transfecting with miR-17-5p mimics. (d, e) Western blot analysis of SRSF2 protein levels in A549 and H1299 after transfecting with miR-17-5p mimics. (f) Luciferase assay detects the direct binding of miR-17-5p on the 3-UTR of SRSF2. (g, h) RT-PCR analysis of MRUL expression levels in A549 and H1299 after transfecting with miR-17-5p mimics. (i) Luciferase assay detects the direct binding of miR-17-5p on the MRUL.

STAT3, and lncRNA H19. SRSF2 was reported to regulate inhibits the expression levels of SRSF2 and MRUL, and gene splicing and [22]. SRSF2 acted as enhanced expression of miR-17-5p inhibits the level of an oncogene and regulated transcriptional extension and SRSF2 protein in cells. These data indicate that there may activation, and by interacting with E2F1 [23], it stimulated be a regulatory mechanism in lung cancer tissues. MRUL gene-regulated cell cycle activity. In NSCLC, SRSF2 could competitively sponges miR-17-5p to regulate the expression enhance cancer proliferation by regulating VEGFR1 pre- of SRSF2 mRNA, and miR-17-5p mediates between MRUL mRNA alternative splicing [24]. and SRSF2. Overexpression of MRUL in lung tumors can More and more evidence show that lncRNAs can be used absorb more miR-17-5p, which leads to miR17-5p reducing as ceRNAs and can regulate the expression of mRNAs by miRNA-mediated SRSF2 mRNA attenuation, thereby pro- binding to miRNAs. The function of lncRNA is closely moting the aggressive growth of tumors and ultimately related to its subcellular location. In this study, we deter- affecting patient survival. mined that MRUL is mainly located in the cytoplasm of lung In conclusion, lncRNA MRUL expression was upregu- cancer cells, suggesting that MRUL may be an endogenous lated in NSCLC tissues. We have demonstrated for the first miRNA sponge. Bioinformatics analysis and luciferase report time that MRUL acts as an oncogenic regulator in NSCLC analysis indicate that MRUL and SRSF2 are direct targets of and promotes cell proliferation and metastasis. Partly miR-17-5p. In addition, overexpression of miR-17-5p through regulating the miR-17-5p/SRSF2 pathway in 12 BioMed Research International

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