Silencing of LINC00221 Suppresses Glioblastoma Cell Migration and Invasion through miR-34c-5p/Snai1 and Regulation of Actin and Cytoskeletal Dynamics Proteins

Silencing of LINC00221 Suppresses Glioblastoma Cell Migration and Invasion through miR-34c-5p/Snai1 and Regulation of Actin and Cytoskeletal Dynamics Proteins | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Silencing of LINC00221 Suppresses Glioblastoma Cell Migration and Invasion through miR-34c-5p/Snai1 and Regulation of Actin and Cytoskeletal Dynamics Proteins Dexter Hoi Long Leung, Siti Ayuni Hassanudin, Mageswary Sivalingam, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3831522/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The role of long non-coding RNAs (lncRNAs) in regulating cell motility in glioblastoma (GBM) remains largely unexplored as compared to other cancers. Our bioinformatic analyses of the microarray data of upregulated lncRNAs predicted the oncogenic role of LINC00221 in GBM cell motility. Quantitative PCR (qPCR) analysis confirmed that LINC00221 was upregulated in different GBM cell lines. While the transient silencing of LINC00221 decreased the A172 cell viability, the cell scratch closure in LN18 and T98G was suppressed. This was followed by reduced cell migration in both LN18 and T98G, but only decreased cell invasion in the latter. Furthermore, Snail and N-cadherin were only decreased in the LINC00221 silenced T98G (T98G si − LINC00221 ) but not LN18. Subsequent bioinformatic analysis predicted miR-34c-5p as a potential miRNA target downstream of LINC00221 and upstream of Snai1, which was confirmed by luciferase reporter assays. To further elucidate the molecular mechanisms involved, we identified the differentially expressed proteins (DEPs) from the proteome profiling of T98G si − LINC00221 and miR-34c-5p mimic transfection (T98G miR − 34c−5p ). Further enrichment of the DEPs in both T98G si − LINC00221 and T98G miR − 34c−5p unveiled enriched pathways associated with the regulation of actin and cytoskeletal dynamics proteins. In summary, our findings establish the oncogenic role of LINC00221 in promoting both T98G and LN18 cell motility. Although LINC0221 exhibited the involvement of a Snai1-dependant mechanism, which is potentially modulated by miR-34c-5p in T98G, proteomic analysis further supported the regulation cell motility via the actin and cytoskeletal-related proteins following LINC00221 silencing in both GBM cells. Biological sciences/Biochemistry Biological sciences/Cancer Biological sciences/Cell biology Biological sciences/Molecular biology cell invasion cell migration miRNA long-ncRNA glioblastoma actin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1.0 Introduction Glioblastoma (GBM) is the most common adult malignant brain tumor, where complete surgical resection is impossible due to its highly aggressive nature 1 . The acquired resistance of the tumor to chemotherapeutic drugs, coupled with the high degree of invasiveness underlie this aggressive nature of GBM. These attributes lead to a low overall survival and high recurrence post-therapy in GBM patients. Several factors contribute to the aggressive phenotype of GBM that include the mesenchymal (MES) transition process, which induces the transition of GBM tumor cells to more aggressive and motile phenotypes. The induction of MES transition in GBM has similar key expression profiles to the classical non-neural epithelial-to-mesenchymal transition (EMT) setting. These involve an increase in the expression of mesenchymal markers (such as N-cadherin and vimentin) and transcription factors (such as Snai1, Slug, ZEB1). The complex interplays between various lncRNAs and the MES-transition transcription factors, EMT markers, and signaling pathways, which identified specific transcription factors regulating the MES transition process was identified in our recent systematic review 2 . With the advancement of sequencing technologies, non-coding RNA such as long non-coding RNAs (lncRNAs), and microRNAs (miRNAs), have been identified to regulate cell motility through regulation of the EMT process and its associated proteins 3 . In recent years, the non-coding RNAs have been reported to contribute to the aggressive nature of GBM 4 . The initial microarray analysis performed between LN18 and normal human astrocyte cells in this study has identified a substantial number of upregulated lncRNAs, many of which remain uncharacterized in the context of GBM. In the context of cancer, the upregulation of genes often signifies oncogenic potential, while downregulation is typically associated with tumor-suppressing activity. Additionally, it is well-documented that lncRNAs play a significant role in gene regulation, primarily through the widely reported lncRNA-miRNA-protein signaling axis. Building upon this, this study aims to identify the potential oncogenic lncRNA candidate capable of enhancing the mobility of GBM cells. We seek to elucidate the potential lncRNA/miRNA/protein axis involved for a deeper understanding of the intricate mechanisms regulated by the lncRNA in this context. Nevertheless. in GBM, there are limited lncRNA studies in contrast with other types of cancers, such as breast cancer. The scarcity of comparable research has impeded the current research of lncRNAs mechanisms in the GBM motility landscape. This challenge primarily stems from the relatively limited clinical data available for GBM datasets compared to other cancers, as well as the availability of lncRNAs information in the bioinformatics databases, which complicate their functional characterization in GBM. To address this challenge, we utilized a series of bioinformatics tools which predicted LINC00221 as the putative oncogenic lncRNAs with the potential to govern GBM cell motility by influencing specific cellular processes. Additionally, the cell motility processes influenced by MES transition were substantiated with the identification of miR-34c-5p as a potential miRNA, downstream of LINC00221 and upstream of Snai1 that regulate the N-cadherin expression. Using this information, the associated mechanisms through the lncRNA-miRNA-protein axis of the LINC00221/ miR-34c-5p/Snail was further investigated in this study. The ongoing discovery of novel lncRNAs in GBM highlights the necessity for continuous investigations to comprehensively elucidate their cellular and molecular functions. This will enable a deeper comprehension of the intricate biological regulatory networks in GBM that are modulated by lncRNAs and ultimately aiding in their characterization specific to the GBM context as prognostic and therapeutic targets. 2.0 Materials and Methods 2.1 Cell Culture, RNA extraction, and cDNA synthesis Normal human astrocyte cells (NHA, CC-2565, Lonza USA) were cultured using Astrocyte Growth Medium BulletKit (AGM, Lonza USA). The GBM cells consist of LN-18, A-172, and T98G cell lines were purchased from ATCC. The LN-18 cells (CRL-2610) were cultured in RPMI medium, while the A-172 cells (CRL-1620) were cultured in DMEM media (ATCC, USA), and the T98G cells (CRL-1690) were cultured in EMEM media (ATCC, USA). All complete media were supplemented with 10% Fetal Bovine Serum (FBS) (Gibco, USA) and 0.5% antibiotic-antimycotics (Gibco, USA). Total RNA was extracted using TRIzol reagent (Invitrogen, USA) according to the manufacturer’s instructions. cDNA was synthesized by a High-Capacity cDNA reverse transcription kit according to the manufacturer’s instruction (Applied Biosystems, USA). 2.2 Microarray analysis Total RNAs were subjected to in vitro amplification and labeled with Low Input Quick Amp Labeling Kit (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer's instruction. Labeled RNA was mixed with the control RNA and hybridized to SurePrint G3 Mouse GE 8X60K (Agilent Technologies). Microarray was performed by Hokkaido System Science (Hokkaido, Japan). The microarrays were scanned using SureScan Microarray Scanner (Agilent Technologies). The scanned images were quantitatively analyzed with Feature Extraction Software v10.7.3.1 (Agilent Technologies). The expression data from the microarray were normalized using Linear and Locally Weighted Scatterplot Smoothing (LOWESS) method for p -value estimation for each spot. The q -value (false discovery rate, FDR) was calculated based on the p -value, with a threshold of less than 0.01. 2.3 Bioinformatic analysis and prediction of lncRNA candidates The upregulated differentially expressed genes (DEGs) from microarray were selected for lncRNA, performed through biomart 5 . LNCipedia 6 was used to check for alternate names and other additional information used for these lncRNA transcripts. To validate that these genes are non-coding, the transcripts were analyzed for their protein-coding potential using the CPAT tool 7 . Functional enrichment based on gene ontology annotations and KEGG pathway were performed using Enrichr 8 . To predict lncRNA function based on their interacting targets, RAID database was utilized to obtain all relevant RNA interactions (lncRNA, miRNA, mRNA, proteins) 9 . TAM 2.0 database was utilized to obtain miRNAs that are associated with cellular processes leading to cell migration and invasion 10 . Cytoscape 11 , an open-source software platform, was used to visualize complex networks. LncRNAs specific lncRNA-protein interactions were obtained from the RAID database and the proteins were clustered based on the Gene Ontology (GO) biological process annotations containing keywords associated with cell motility. Only lncRNAs that interact with these proteins of interest were included in the subsequent analysis. For lncRNAs that were identified to interact with any of the proteins associated with the GO terms, the lncRNA sequence was first retrieved from Lncipedia, followed by retrieval of the sequence of all miRNAs associated with cell invasion processes from miRNameConverter 12 . The potential interactions of these miRNAs with the lncRNAs identified were predicted through LncTar 13 . Figure 1 illustrated the flow of the bioinformatic analyses carried out. 2.4 Quantitative Polymerase Chain Reaction (qPCR) to determine LINC00221 expression qPCR analysis was carried out using SensiFAST SYBR Hi-Rox mix (Bioline,UK) to measure the relative expression level of LINC00221 in three GBM cell lines (LN18, A172, and T98G) compared to NHA cells normalized to ARF1 housekeeping gene. The primer sequence used are: LIN000221 (F: GCAGTAACTGTTGGTTGGGATG, R: CAGGCTTACAAGTGTCTTAGTCCAG); ARF1 (F: GACCACGATCCTCTACAAGC, R: TCCCACACAGTGAAGCTGATG). The qPCR reaction mixture was ran using ABI 7500 Fast Real-time system (Applied Biosystems, USA) with initial denaturation at 95 o C for 10min, followed by 35 cycles of denaturation at 95 o C for 15s, and lastly annealed and extended at 60 o C for 1min. The relative expression levels were calculated using 2 −ΔΔCt method. 2.5 Transfection of siRNAs for LINC00221 silencing and miR-34c-5p mimics The T98G, A172, and LN18 GBM cells were seeded into 24-well plate overnight to 70–80% confluency at 30,000 cells/well and was starved before the start of transfection by replacing to base medium. Transfection efficiency of all cell lines used were first determined through transfecting TYE 563 Transfection Control DsiRNA (iDT), which is a fluorescence labelled transfection control. Fluorescence microscope (Nikon) was used to visualize fluorescence siRNA uptake by the cells following transfection to determine transfection efficiency. siRNAs or miRNA mimic were then used for transfection. The sequence for the siRNAs used are as follows: (i) siLINC00221_01 (5’-AUUGUUUCUUGGAUGAAUCUCUGGA-3’ 3’-UUUAACAAAGAACCUACUUAGAGACCU-5’); (ii) siLINC00221_02 (5’-GCUCUUAUUUAAGUAAUACAAACCA-3’ 3’-UUCGAGAAUAAAUUCAUUAUGUUUGGU-5’); (iii) siLINC00221_03 (5’-GAGCUCAGGUAUAGUCAAAAUUGTT-3’ 3’-GUCUCGAGUCCAUAUCAGUUUUAACAA-5’); miR-34c-5p mimic (AGGCAGUGUAGUUAGCUGAUUGC). For transfection reagent, Lipofectamine 3000 (Invitrogen) were first diluted with Opti-MEM (Gibco), the volume of lipofectamine used were based on the manufacturer’s recommended volume for the respective plates used (0.5uL for 96-wells; 1.5uL for 24-wells; and 7.5uL for 6-wells). Lipofectamine-DNA complexes were then prepared through adding 25nmol of either siRNA or miRNA mimics and incubated at 37 o C for 15min. The lipofectamine-DNA complex was then added dropwise into the cells and incubated at 37 o C in a CO 2 incubator for 24h. The cells were then recovered by replacing the media with medium supplied with 10% serum and incubated with until subsequent assay was carried out to these transfected cells. Transfection efficiency of siRNA in all three cell lines were first determined through qPCR analysis after 24h of cell recovery following transfection. 2.6 Cell viability For cell viability, A172, LN18, and T98G cells were seeded into 96-well plate at 5000 cells/well overnight until ~ 70% confluency and were transfected with siRNAs as previously described. Following transfection for 24h, cell-viability were determine using CCK-8 (Dojindo, Japan) according to manufacturer’s protocol. The CCK-8 reagent was added to transfected cells and incubated at 37 o C for 1 hr. Absorbance at 450 nm were then obtained by using a microplate reader (TECAN, Switzerland). Relative viability of cells was obtained by comparing the absorbance of the transfected cells with the absorbance of the control cells. 2.7 Cell scratch assay For the cell scratch assay, the T98G and LN18 cells were seeded into 24 well plate overnight at 30,000 cells/well to reach ~ 70% confluency. The seeded cells were then transfected with the respective siRNAs for 24 hr. Following cell recovery at 24 hr, a vertical scratch was performed using a sterile 100 µL pipette tip, and the cells were washed twice with PBS before serum-free media was added and the cells were incubated at 37 o C in a 5% CO 2 incubator. Photos were taken using a Nikon inverted microscope (Nikon, Japan) every 12 hr interval for a total of 48 hr. The photos were then analyzed using the ImageJ plugin developed by Suarez-Arnedo et al. (2020) to obtain area of the wound scratch. Percentage of wound closure in relative to T = 0 was then calculated for each group. Relative wound closure was then calculated by comparing percentage of wound closure for each group with the control group in that specific time point. 2.8 Cell migration and cell invasion assay Cell migration assay was performed using Cell Migration/Chemotaxis Assay Kit (catalogue no. ab235673) (Abcam, USA) according to manufacturer’s protocol. Briefly, 50,000 cells were seeded into each well and incubated for 24 hr before measuring for fluorescence signals at 530/590 nm. Relative migration was then calculated by comparing number of migrated cells between control and siLINC00221_03 transfected cells. Cell invasion assay was performed using QCM ECMatrix Cell-Invasion Assay (catalogue no. ECM555) (Merck, USA) according to manufacturer’s protocol. Again, 50,000 cells were seeded into each well and incubated for 24 hr before measuring for fluorescence signals at 480/520 nm. Relative invasion was then calculated by comparing number of invasive cells between control and siLINC00221_03 transfected cells. Fluorescence signals were obtained through microplate reader (TECAN, Switzerland) 2.9 Protein extraction and quantification Protein lysates was obtained through standard protein extraction protocol through RIPA buffer (Nacalai Tesque, Japan) supplemented with 1% protease inhibitor and 1% phosphatase inhibitor (Sigma, USA) as a form of extraction cocktail. Transfected cells from six-well plates were harvested, centrifuged, and washed with PBS twice prior to addition of the extraction cocktail and incubated for 15 min, and finally protein lysate was collected after centrifugation at 500 g for 10 min to remove cell debris. Concentration of protein lysate were quantified by using Pierce BCA Protein Assay Kit (ThermoFisher, USA) according to manufacturer’s protocol and the absorbance were measured using microplate reader (TECAN, Switzerland). 2.10 JESS Simple Western JESS Simple Western was utilized to determine relative change in EMT protein expression following LINC00221 silencing based on recommended protocol from ProteinSimple using a 12–230 kDa JESS separation module (SM-W004). Protein lysates at 1.2 mg/mL were mixed with fluorescent 5x Master mix (Protein Simple) to achieve final concentration of 1.0 mg/mL, which was followed by denaturation at 95 o C for 5min, before loaded into each well. The samples were run on a capillary based system, where the protein separation will take place. Primary antibodies used for the analysis includes Vimentin (D21H3), N-Cadherin (D4R1H), β-catenin (D10A8), Snai1 (C15D3), Slug (C19G7), ZEB1 (D80D3), and E-cadherin (24E10) obtained from Cell Signalling Technology, USA. All primary antibodies listed were raised in rabbit. Dilution factor of 1:50 was utilized as the final concentration for all antibodies. Anti-Rabbit detection module (Biotechne, USA) was used as secondary antibody according to manufacturer’s instruction Total protein normalization was performed through protein normalization assay module (Biotechne, USA) to normalized proteins loaded into the well. Chemiluminescence were detected where the signals are captured in the JESS system. Compass software for Simple Western (Protein Simple), which calculated chemiluminescence intensity as peaks where the corrected area was used was used for data analysis. Results were expressed in terms of relative protein expression by comparing the corrected area between knockdown group and control group. 2.11 Prediction of potential miRNA target To predict the potential miRNA targets for LINC00221, a list of pre-computed potential miRNA for LINC00221 were obtained from RNA22 database 14 . GEO microarray dataset (GSE65626) was used to identify downregulated miRNAs from this list of pre-computed potential miRNA candidates. Following this, three separate databases (miRDB, TargetScan, and RAID) containing predicted miRNA-mRNA interactions were used to search for miRNA that was predicted to interact with SNAI1, CDH2, and VIM. Based on the outcome of the prediction analysis, miR-34c-5p were chosen as a miRNA candidate for further analysis. 2.12 Polymerase Chain Reaction (PCR) and luciferase reporter assay The PCR amplicons of the predicted miR-34c-5p interacting target sequence were obtained through standard PCR reaction using a thermocycler (AppliedBiosystems, USA) with initial denaturation at 95 o C for 10 min, followed by 35 cycles of denaturation at 95 o C for 15 s, and lastly annealed and extended at 60 o C for 1 min. The PCR amplicons were purified using the Wizard SV Gel and PCR clean-up system (Promega, USA). Dual luciferase reporter plasmid pmirGLO were obtained from Promega, USA. For construction of luciferase plasmid, luciferase plasmid pmirGLO (Promega, USA) were inserted with predicted binding site of miR-34c-5p with LINC00221 or Snai1-3’UTR to construct pmirGLO:LIN00221 or pmirGLO:Snai1-3’UTR. Wildtype pmirGLO were digested by the XhoI and XbaI restriction enzymes at room temperature for 15 min followed by heat inactivation at 60 o C for 20 min. Then, 25 ng of purified PCR amplicons obtained previously were ligated into 100 ng of RE-digested pmirGLO by T4 DNA ligase (ThermoScientific, USA) by incubating the reaction mixture in room temperature for 20 min, followed by heat inactivation at 60 o C for 20 min. The ligated plasmids were then propagated using the DH5α E. coli competent cells through heat-shock at 42 o C for 45 s and placed on ice for 2 min followed by 1 hr of recovery in SOC medium (Invitrogen) before plating in LB Agar supplemented with ampicillin and incubated at 37 o C overnight. Colonies were then subjected to colony PCR to confirm insertion of target sequence. Confirmed colonies containing correct inserts were propagated in LB broth (Oxoid, UK) overnight and plasmid extracted and purified by the Wizard Plus SV Minipreps DNA purification system (Promega). Concentration and quality of plasmid extracted were assessed through Nanodrop one spectrophotometer (Sigma). The workflow for luciferase plasmid construction were illustrated in Fig. 2 . To assess the interaction of miR-34c-5p mimic with LINC00221 and 3’UTR Snai1, the T98G cells were seeded into 24-well plate overnight to reach ~ 70% confluency at 30,000 cells/well. Following this, the seeded cells were then transfected with the luciferase plasmid with predicted miRNA binding sequences constructed as previously described to determine miRNA binding activity. 100 ng of pmirGLO:LINC00221 or pmirGLO:Snai1-3’UTR were transfected into the cells for 24 hr as the control group. For the experimental group, the cells were co-transfected with both the constructed plasmid and 25 ng of miR-34c-5p mimics. Negative control miRNA mimics and wild-type pmirGLO were also transfected as control. The cells were recovered in complete medium after transfection for 24 hr. Luciferase activity were then examined by using the Dual-Glo luciferase reporter assay (Promega). Luminescence of the transfected cells were quantified by using a microplate reader (TECAN) based on manufacturer’s protocol. Luminescence obtained from firefly luciferase in all samples were normalized with Renilla luciferase luminescence. Relative luciferase activity was then calculated based on the normalized luminescence value of control groups compared with the normalized luminescence of the experimental group where cells were co-transfected with both mutated plasmid and miR-34c-5p mimics. 2.13 Proteomics analysis of si-LINC00221 and miR-34c-5p mimics transfected cells For proteome profiling, LC-MS/MS analysis was performed on three experimental groups: (i) T98G cells transfected with si-LINC00221 versus control (T98G si − LINC00221 ), T98G cells transfected with miR-34c-5p mimic versus control (T98G miR − 34c−5p ), and LN18 cells transfected with si-LINC00221 versus control (LN18 si − LINC00221 ). Protein lysates were extracted as previously described and was processed for MS analysis using EasyPEP MS Sample Prep Kit (Thermofisher, USA). The purified digested peptides were then loaded onto an Agilent AdvancedBio Peptide Mapping (120 A, 2.1 x 150 mm, 2.7 µm) attached on Agilent 1290 ultra-high-performance liquid-chromatography system (UHPLC). The column was equilibrated with 0.1% formic acid in water (solution A). The peptides were then eluted from the column with increasing gradients of 90% acetonitrile (ACN) in 0.1% formic acid solution (solution B) with the following gradients: 5–75% solution B from 0 to 50 min and 75% solution B from 50 to 60 min, at a flow rate of 0.2 mL/min. The polarity of the Quadrupole-time of flight (Q-TOF) was set to positive, with capillary and fragmentor voltage being set at 1800 V and 360 V respectively along with 11 L/min of drying gas flow with a temperature of 280°C. MS acquisition by Data-dependent acquisition (DDA) mode was performed to analyze digested peptide spectrum in MS mode ranging from 110–3000 m/z (mass to charge ratio) for MS scan (in quadrupole mode) and 50–3000 m/z for MS/MS scan (in time-of-flight, TOF mode). Protein identification and LFQ were performed using PEAKS ® Studio software (Version 10.6, Bioinformatics Solutions Inc. (BSI), Waterloo, ON, Canada). The analysis was performed once on every biological sample (three biological repeats for every cell line/ type). The UniProt/ Swiss-Prot (Organism: Homo sapiens ) database (release 2018_03) was used for protein identification and homology search by comparing the de novo sequence tag. Label-free quantitation (LFQ) analysis was performed using the built-in quantification module in PEAKS Studio with the following parameters: Carbamidomethylation was set as fixed modification (+ 57.02 on C) with maximum mixed cleavages at 3. The mass tolerance of precursors was set at 20 ppm while the parent mass and fragment ion mass error tolerance were both set 0.1 Da with monoisotopic as the precursor mass search type while the maximum missed cleavages was set at 3 precursors. Trypsin was selected as the enzyme used for digestion. In order to filter out inaccurate proteins, the recommended PEAKS Q statistical analysis (a built- in statistical tool of the PEAKS Ⓡ software) settings are applied as follows: False discovery rate (FDR) threshold ≤ 1%, fold change ≥ 1, unique peptide ≥ 1, and significance score ≥ 20. A significance score of greater than 20 is relatively high in confidence as it targets very few decoy matches above the threshold and is equivalent to a significance p value of < 0.01. The relative amount of proteins per sample is determined according to their intensities in which the protein intensities are log transformed, normalized and compared between the samples. Normalization during quantitation was performed based on Total Ion Chromatogram (TIC). The default maximum number of variable posttranslational modifications per peptide was set at 3, while the De novo score threshold for SPIDER was set 15 and Peptide hit score threshold at 30. Retention time shift tolerance was 6 min. The analyses are exported into an Excel spreadsheet listing every protein identified, along with their corresponding − 10lgP scores, raw and normalized quantified values, percentage coverage and number of peptides and its unique peptide sequences. PEAKS Q indicated that a − 10 lgP > 20 was relatively high in confidence as it targeted very few decoys matches above that threshold. 2.14 Bioinformatic analyses of differentially expressed proteins (DEPs) The DEPs identified from proteomic analysis were inserted into STRING and was clustered through k-means clustering. STRING enrichment analysis with an interaction score of high confidence (0.700) was performed to identify enriched REACTOME pathways in both T98G si − LINC00221 and T98G miR − 34c−5p that is associated with Snai1 identified through STRING interactions 15 , 16 . 2.15 Statistical Analysis One-way analysis of variance (ANOVA) with Tukey's post hoc test and independent t-tests were employed to compare means among multiple groups. In addition, a two-way ANOVA was performed to assess the influence of two independent variables on a dependent variable. Subsequently, Bonferroni post hoc tests and independent t-tests were conducted to compare means between groups within each combination of the independent variables, where applicable. 3.0 Results 3.1 Microarray revealed 373 upregulated lncRNAs in LN18 GBM cells compared to NHA cells The comparative analyses of LN18 and NHA cell lines ( p 2) provided 372 upregulated lncRNA transcripts ( Fig. 3 A, Complete information available in Supplementary S1 ), The top-10 upregulated lncRNAs were listed in Table 1 . 3.2 Upregulated expression of LINC00221 is predicted with its oncogenic roles in GBM cell motility The functions of lncRNAs identified from microarray were predicted based on the functions of both miRNAs and proteins they interact with, which is available in RAID and TAM 2.0 bioinformatic database. From Gene set enrichment analysis (GSEA) of the upregulated lncRNAs, only one lncRNAs, SRGAP3 , was annotated with cell invasion and motility associated GO annotation. To further characterize lncRNAs which cannot be functionally enriched through GSEA, their function was predicted based on their interactions with both miRNAs and proteins which were obtained from the RAID bioinformatic database. Based on protein functions, among the 372 upregulated lncRNAs identified in LN18 cells, 35 lncRNAs are associated with angiogenesis; 32 with cell migration; 35 with epithelial-to-mesenchymal transition; 27 with hypoxia; and 10 lncRNAs were predicted to be involved in ECM. In addition, 65 lncRNAs are predicted to be involved in angiogenesis, 36 with cell migration, 51 with cell motility, and 70 with EMT based on miRNAs function ( Fig. 3 B ). Network analysis was performed to visualize the potential function(s) of the upregulated lncRNAs based on their interacting targets (Fig. 3 C). Based on this, four specific lncRNAs were identified to be associated with cell motility, which were i) LINC00221 associated with EMT, ii) LINC01564 and LINC00265 with angiogenesis, and iii) LOC100240735 with cell migration. Finally, lncTAR was utilized to predict the binding potential of miRNAs associated with cell motility with the four lncRNAs (LINC00221, LINC00265, LINC001564, and LOC100240735 (also known as lnc-SMUG1). Based on lncTAR prediction, 57 miRNAs were predicted to bind with LINC00221, 49 for both LINC001564 and LINC00265, and 21 for LOC100240735. To visualize the predicted lncRNA-miRNA-protein interacting network, potential mRNAs targets of these miRNAs were obtained from RAID miRNA-protein interaction database. These interactions were then analyzed using Cytoscape to visualize distinct signatures ( Fig. 3 D ) . Results through lncTAR predictions were able further to visualize the distinct and potential interacting pathways of these four lncRNAs. LINC00221 was predicted to bind with miRNAs which affects biological pathways at different axis/loci at TP53 , EGF, TERT, and MDM2; lncSMUG1 with miR-584 will interact with BRCA1, STAT1, PDGFRA, and MDM2; and both LINC01564 and LINC00265 with PTEN, PTG52, and EGFR. As LINC00221 were identified as the most differentially expressed lncRNA in LN18 when compared to NHA, alongside results from combined bioinformatic analysis which predicted a specific signaling axis in influencing cell motility, LINC00221 were chosen for further characterization. Following this, LINC00221 expressions were validated in A172, T98G, and LN18 GBM cell lines through qPCR (Fig. 4 A). Results shown that LINC00221 is significantly upregulated (P < 0.001) in LN18 by 177.91-fold, A172 by 38.59-fold, and T98G by 5.68-fold when compared with NHA cells. The observed trend is consistent with results from the LN18 vs. NHA microarray (127.40-fold increase). Table 1 Top-10 upregulated lncRNA gene in LN18 in relative to NHA Gene Name Fold Change P-value FDR P-value LINC00221 127.40 3.52 x 10 − 23 3.18 x 10 − 20 ENST00000446495 108.40 8.12 x 10 − 23 3.37 x 10 − 20 LOC340340 66.28 4.80 x 10 − 22 7.03 x 10 − 20 FENDRR 60.29 9.01 x 10 − 23 3.43 x 10 − 20 DSCR8 57.91 9.74 x 10 − 23 3.46 x 10 − 20 lnc-EIF3M-2 55.03 1.44 x 10 − 21 1.46 x 10 − 19 LINC00470 42.68 1.18 x 10 − 20 7.38 x 10 − 19 LINC00871 41.45 1.63 x 10 − 20 9.65 x 10 − 19 LINC01296 30.48 8.47 x 10 − 19 2.92 x 10 − 17 ERICH2 29.43 1.46 x 10 − 18 4.68 x 10 − 17 3.3 LINC00221 silencing decreased A172 cells viability To determine the knockdown efficiency of three siRNAs (siLINC00221_01, siLINC00221_02, and siLINC00221_03) in LINC0221 silencing in A172, T98G, and LN18 GBM cell lines, qPCR was performed following cell transfection to assess LINC00221 expression. Transfecting siLINC00221_01, siLINC00221_02, and siLINC00221_03 significantly decreased LINC00221 expression in GBM cells at T = 24h. For siLINC00221_01, significant reduction in expression of LINC00221 by 68% (p < 0.05), 75% (p < 0.05), and 58% (p < 0.05) were achieved for LN18, A172, and T98G cells, respectively. For siLINC00221_02, significant reduction in expression of LINC00221 by 90% (p < 0.05), 70% (p < 0.05), 78% (p < 0.05) were achieved in LN18, A172, and T98G cells, respectively. For siLINC00221_03, significant reduction in expression of LINC00221 by 84% (p < 0.05), 65% (p < 0.05), and 78% (p < 0.05) were observed in LN18, A172, and T98G cells, respectively (Fig. 4 B, 4 C, 4 D). Reduction of LINC00221 expression has observed significant reduction of cell viability in cells. A significant reduction (p < 0.05) in A172 viable cells at 24h were observed for cells transfected with siLINC00221_01 (20% reduction), siLINC00221_02 (39% reduction, p < 0.05), siLINC00221 (50% reduction, p < 0.05), and siHPRT (64% reduction, p 0.05) in cell viability were observed at T = 24h other than cells transfected with positive control siHPRT (43% reduction, p 0.05) on cell viability were observed across all siRNAs transfected at 24h ( Fig. 4 G ) . 3.4 LINC00221 silencing impeded cell scratch closure, migration, and invasion in T98G cells and reduced migration in LN18 cells As A172 cells exhibited reduced viability following LINC00221 silencing, the effect of LINC00221 in influencing A172 motility was not investigated further. For T98G cells, LINC00221 silencing has demonstrated a significant reduction in cell scratch closure for siLINC00221_02, siLINC00221_03, and siHPRT starting at 36h post-scratch (p < 0.05) when compared with both control and negative control group where at T = 36 both blank and negative control group has observed around 60% closure of cell scratch, while across the other three experimental groups mentioned had observed only 0.05) in cell scratch closure post-scratch were observed across all cell groups transfected with different siRNAs ( Fig. 4 J ) . Complete information for cell scratch assay performed are available in Supplementary S2. Based on the observation of siLINC00221_03 exhibiting a significant effect on both T98G cells viability and cell scratch closure at 36h and 48h respectively and was used for subsequent assays (from here referred as si-LINC00221). In cell migration assay, both LN18 and T98G cell lines exhibited a significant reduction (p < 0.05) in cell migration at approximately of 25% following si-LINC00221 transfection at 24h when compared with the control group (Fig. 4 K). Conversely, in cell invasion assay, T98G exhibited a significant reduction of 40% (p 0.05) in cell invasion following si-LINC00221 transfection at 24h (Fig. 4 L ) . 3.5 LINC00221 silencing downregulates Snai1 and N-cadherin in T98G cells To determine if the observed decreased in migration and invasion following LINC00221 silencing are associated with EMT related factors, the expression of EMT transcription factors (EMT-TFs), ZEB1, Snai1, Slug; and EMT markers (N-cadherin, vimentin, E-cadherin, B-catenin) were assessed following si-LINC00221 transfection. In T98G cells, only Snai1 expression was significantly reduced (p < 0.05) by 50% compared to the control samples ( Fig. 5 A ) . In LN18 cells, no significant reduction was observed in all of the EMT-TFs investigated ( Fig. 5 B ) . For expression of EMT markers, relative expression of N-cadherin was observed to be significantly reduced (p < 0.05) by 52% in T98G cells following LINC00221 silencing ( Fig. 5 A ) . Changes in relative expression E-cadherin were also assessed. However, the results were not conclusive as the protein could not be detected in T98G cells. In LN18 cells, no significant changes (p > 0.05) were observed in relative expression of EMT markers following LINC00221 silencing ( Fig. 5 B ) ., The complete protein profiles for all three replicates for protein expression analysis obtained from protein normalization module of JESS Simple Western are available in Supplementary S3. 3.6 miR-34c-5p targets both LINC00221 and Snai1-3’UTR in regulation of cell motility As Snai1 and N-cadherin were observed as the potential target of LINC00221, the subsequent miRNA target of LINC00221 was predicted to investigate a complete lncRNA/miRNA/protein axis. As LINC00221 were found to be upregulated in GBM cells, we focus on downregulated miRNAs which can be obtained from several bioinformatic databases. From the RNA22 database, 1278 downregulated miRNAs which were pre-computed to interact with LINC00221 were obtained. Also, 245 downregulated miRNAs were found within the GEO microarray dataset (GSE65626). From these downregulated miRNAs which were pre-computed to interact with LINC00221, their potential interaction with downstream Snai1 and N-cadherin (CDH2) were searched from miRDB, RAID, and Targetscan databases ( Fig. 5 C & 5 D ) . The potential miRNA candidate was selected based on the fold-change observed from the microarray dataset alongside both interaction score and p-value from bioinformatic databases. These parameters show the probability if the miRNA candidate exhibits any bi-directional interaction with both upstream target LINC00221 and downstream target Snai1, mir-34c-5p with FC = 0.09, predicted with LINC00221 interaction from RNA22 (p = 0.05), and with Snai1/N-cadherin (with interaction score of 91 out of 100 from miRDB) was chosen for subsequent analysis. From the bioinformatic databases, miR-34c-5p was predicted to interact with LINC00221 at target site GGGATCAGTTAGAAAGCTCTT, and at the 3’UTR region of Snai1 with the target sequence CACTGCCA. Luciferase reporter assay was then used to assess the interaction between miR-34c-5p mimics with predicted sequences of both LINC00221 and Snai1 3’UTR. It was observed that the relative luciferase activity was significantly reduced (p < 0.05) when miR-34c-5p mimics were co-transfected with mutated luciferase plasmid inserted with predicted target sequence (Fig. 5 E & 5 F ) . As previously observed that si-LINC00221 transfection did not reduce Snai1 expression in LN18 cells, following the confirmation of miR-34c-5p interaction with both LINC00221 and Snai1, we investigated whether the miR-34c-5p mimics transfection would affect the Snail expression in LN18. Interestingly, results shown the significant reduction in Snai1 expression following miR-34c-5p mimic transfection in LN18 cells (P < 0.05) (Fig. 5 G ) . 3.7 Silencing of LINC00221 and transfecting miR-34c-5p mimics suggests regulation of actin and cytoskeletal specific pathways which mediates cell motility in T98G cells To identify the potential mechanisms that may be regulated through the potential axis of LINC00221/miR-34c-5p/Snai1 axis especially in T98G cells, LC-MS/MS analysis were first performed on both T98G and LN18 cells to identify differentially expressed proteins (DEPs) affiliated with si-LINC00221 transfection (T98G si − LINC00221 and LN18 si − LINC00221 ). Additionally, DEPs associated in T98G cells with miR-34c-5p mimic transfected was obtained as well (T98G miR − 34c−5p ). From T98G si − LINC00221 , 344 and 383 protein groups were identified from the control and transfected cells, where among these proteins 18 downregulated (FC 1.2) were identified (Complete Information Available In Supplementary S4 ). For T98G miR − 34c−5p , 434 and 411 protein groups were identified from control and transfected cells, respectively, where 79 downregulated DEPs (FC < 0.8) were identified (Complete Information Available In Supplementary S5 ). Six common DEPs (LAMP2, Protein 14-3-3B, TCPZ, H4, TEBP, TCPH) were observed between both T98G si − LINC00221 and T98G miR − 34c−5p . In contrast, for LN18 si − LINC00221 , 402 and 411 protein groups were identified for control and transfected group, respectively. Among these, 2 downregulated DEPs (TPT1 & HIST1H4J) and 4 upregulated DEPs (PMPCA, KRT10, RAB35, KRT9) were identified (Complete Information Available In Supplementary S6 ). There are no common DEPs shared between both T98G si − LINC00221/miR−34c−5p and LN18 si − LINC00221 . Following this, REACTOME pathways involved with Snai1 and DEPs identified in T98G si − LINC00221 and T98G miR − 34c−5p were then functionally enriched through STRING (Fig. 6 and Fig. 7 ), and enriched REACTOME pathways which is associated with Snai1 was tabulated (Table 2 and Table 3 ). Among the enriched pathways obtained, 4 common enriched REACTOME pathways were identified were namely: Folding of actin by CCT/TriC, Formation of tubulin folding intermediates by CCT/TriC, Prefoldin mediated transfer of substrate to CCT/TriC, and Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC). As there were only 6 DEPs identified in LN18 cells, functional enrichment was not possible. Finally, to identify possible mechanisms of the LINC00221/miR-34c-5p/Snai1 axis associated with T98G, Snai1 and all DEPs enriched alongside REACTOME pathways from T98G si − LINC00221 and T98G miR − 34c−5p were inserted into STRING to collectively look for the possible mechanisms governed by LINC00221/miR-34c-5p/Snai1 axis in T98G cells (Fig. 8 ). Table 2 Selected REACTOME pathways which were significantly enriched in the DEPs identified from si-LINC00221 transfection in T98G cells Term ID term description observed gene count background gene count strength false discovery rate matching proteins in network HSA-390450 Folding of actin by CCT/TriC 2 10 1.99 0.0054 CCT7,CCT6A HSA-264870 Caspase-mediated cleavage of cytoskeletal proteins 2 12 1.91 0.0072 GSN,VIM HSA-9613829 Chaperone Mediated Autophagy 2 22 1.65 0.0196 LAMP2,VIM HSA-389960 Formation of tubulin folding intermediates by CCT/TriC 2 25 1.6 0.0239 CCT7,CCT6A HSA-75153 Apoptotic execution phase 4 52 1.58 0.00011 KPNB1,H1-2,GSN,VIM HSA-389957 Prefoldin mediated transfer of substrate to CCT/TriC 2 27 1.56 0.0266 CCT7,CCT6A HSA-975956 Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC) 3 94 1.2 0.0183 RPL7,RPS3A,RPL30 HSA-194315 Signaling by Rho GTPases 15 672 1.04 1.14E-10 HSPE1,H4C6,CCT7,CCT6A,H2BC5,H2BC4,H2BC12,YWHAB,ACTN1,VIM,H2BC14,H2BC9,CLTC,H2BS1,H2BC15 Table 3 Selected REACTOME pathways which were significantly enriched in the DEPs identified from miR-34c-5p mimic transfection in T98G cells term ID term description observed gene count background gene count strength false discovery rate matching proteins in network HSA-390450 Folding of actin by CCT/TriC 3 10 1.88 6.80E-04 CCT7,CCT6A,CCT5 HSA-389960 Formation of tubulin folding intermediates by CCT/TriC 3 25 1.48 5.60E-03 CCT7,CCT6A,CCT5 HSA-389957 Prefoldin mediated transfer of substrate to CCT/TriC 3 27 1.45 6.80E-03 CCT7,CCT6A,CCT5 HSA-975956 Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC) 9 94 1.38 8.72E-08 RPL18A,RPL35,PABPC1,RPS24,RPL18,RPLP0,RPS5,RPS10,RPL9 HSA-6814122 Cooperation of PDCL (PhLP1) and TRiC/CCT in G-protein beta folding 3 38 1.3 1.61E-02 CCT7,CCT6A,CCT5 HSA-975957 Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC) 9 114 1.3 2.73E-07 RPL18A,RPL35,PABPC1,RPS24,RPL18,RPLP0,RPS5,RPS10,RPL9 HSA-390471 Association of TriC/CCT with target proteins during biosynthesis 3 39 1.29 1.71E-02 CCT7,CCT6A,CCT5 HSA-9010553 Regulation of expression of SLITs and ROBOs 10 169 1.17 3.02E-07 PSME2,RPL18A,RPL35,PABPC1,RPS24,RPL18,RPLP0,RPS5,RPS10,RPL9 4.0 Discussion Despite the growing recognition of the significance of lncRNAs, progress in studying lncRNAs in GBM remains bottlenecked in comparison with other cancer types. At present, the functional roles of lncRNAs, particularly in the context of GBM, remain largely uncharted at both the cellular and molecular levels. Comprehensive investigations focusing on specific lncRNAs that enable the utilization of Gene Ontology (GO)-annotated lncRNA databases for cluster analysis are scarce, especially in comparison to research conducted in other cancer types. To elucidate the functional relevance of lncRNAs in GBM motility, an analysis involved the acquisition of miRNAs and proteins known to interact with the identified lncRNAs in cell motility was conducted using bioinformatic databases. Subsequently, clustering was employed to predict either (i) the specific functions of the lncRNAs based on their miRNA associations or (ii) processes of the proteins they have reported interactions with. These functions include angiogenesis, hypoxia responses, extracellular matrix, and migration. Angiogenesis is a critical event in the progression of GBM since the tumors exhibit a high degree of vascular proliferation and endothelial cell hyperplasia 17 . Endothelial cells-associated with angiogenesis are among the critical inducers of cell invasion 18 . On the other hand, hypoxia can trigger the invasive phenotype of GBM by upregulating the levels of invasion proteins that drive the degradation and remodeling of the extracellular matrix and EMT in GBM 19 . Although the information of the four lncRNAs, LINC00221, LINC00265, LINC001564, and LOC100240735 is scarce, the current protocol successfully predicted their roles based on these cellular and molecular processes of cell motility. LINC00221 was reported to have multiple roles in other types of cancers which includes promotion of cisplastin resistance in non-small lung cancer 20 . Additionally, LINC00221 promoted the progression of hepatocellular carcinoma through the LINC00221/let-7a-5p/MMP11 axis 21 . Interestingly, LINC00221 demonstrated a tumor suppressive role in children acute lymphoblastic leukemia by influencing proliferation and apoptosis through the LINC00221/miR-152-3p/ATP2A2 axis 22 . However, the existing knowledge regarding LINC00221 in the context of GBM is lacking, necessitating an in-depth investigation and validation of its potential oncogenic roles, whether in promoting or inhibiting cell invasion. From the microarray, LINC00221 was identified as the most upregulated lncRNA in LN18 GBM cells as compared to NHA. Coupled with bioinformatic analyses which have predicted the involvement of LINC00221 in cell motility processes. The qPCR experiment performed also confirmed the upregulation of LINC00221 as an upregulated lncRNA in three GBM cell lines when compared to NHA. Based on all these observations, LINC00221 was chosen as the target lncRNA candidate to be further characterized in GBM cell motility. Our results demonstrated the transient silencing of LINC00221 reduced the A172 cell viability. Furthermore, LINC00221 silencing has impeded cell scratch closure in T98G cells, where the inhibition of motility potential was further evident by the decreased cell migration, and cell invasion in T98G cells. In LN18, however, LINC00221 silencing only reduced cell migration. These results have first demonstrated the oncogenic role of LINC00221 in GBM cells. The observed variation in the impact of LINC00221 silencing among the three GBM cell lines employed in this study suggests the possibility that LINC00221 may influence distinct biological pathways in a context-dependent manner. Our prior bioinformatics analysis has initially indicated the potential role of LINC00221 in EMT-related pathways. To validate this, we performed protein expression analysis, revealing a significant downregulation of the EMT transcription factor Snai1 and the EMT marker N-cadherin in T98G cells following LINC00221 silencing. This observation underscores the possibility of LINC00221 exerting distinct regulatory effects at the molecular level within the GBM cells used in this study. To further establish a potential lncRNA-miRNA-protein axis of LINC00221, the possible miRNA target candidates that can interact with LINC00221 which concomitantly reducing the regulatory effect towards Snai1 was predicted. Given its consistent presence in multiple predictive bioinformatic databases and the high confidence score indicating its interaction with both upstream LINC00221 and downstream Snai1-3’UTR, miR-34c-5p was chosen as the primary candidate miRNA for further investigation. MiR-34c-5p plays a role in suppressing both cell migration and invasion in both gastric cancer through targeting MAP2K1, and cervical cancer by targeting Notch1 23,24 . In the context of GBM, limited information has been available regarding miR-34c-5p. A previous investigation delved into the roles of miR-34c isoforms, specifically miR-34c-3p and miR-34c-5p, within GBM 25 . This study reported differential tumor-suppressive roles, contrasting the regulatory effects of miR-34c-3p and miR-34-5p, both of which were found to possess invasion-inhibiting capabilities. Notably, miR-34c-3p was observed to inhibit invasion by targeting Notch1, while the molecular target associated with miR-34c-5p-mediated invasion remained unexplored. In our investigation, we have observed a direct interaction between miR-34c-5p and both the upstream regulator LINC00221 and the downstream target Snai1. Based on JESS Simple western, Snai1 expression remained unchanged following the silencing of LINC00221 in LN18 cells. Considering the universality of the LINC00221/miR-34c-5p/Snai1 axis, the subsequent investigation delved into the effects of miR-34c-5p mimic transfection on Snai1 expression in LN18 cells. We observed a substantial decrease in Snai1 expression following transfection, confirming the validity of our study on lncRNA-miRNA-protein interactions. Collectively, based on our observations, LINC00221 targets miR-34c-5p, resulting in the upregulation of Snai1, which, in turn, suppresses T98G cell motility. The multifaceted target of lncRNA, particularly in the context of LINC00221, may underlie the lack of Snai1 expression modulation upon initial silencing of LINC00221 in LN18 cells. This observation supports the idea that LINC00221 exerts diverse oncogenic functions in different GBM cell lines, possibly attributed to variations in its preference for binding to distinct targets in each cell line. To identify alterations in mechanisms associated with LINC00221 and miR-34c-5p in T98G cells, we obtained proteome profiles after LINC00221 silencing (T98G si − LINC00221 ) and miR-34c-5p mimic transfection (T98G miR − 34c−5p ). We utilized Snai1 and the DEPs obtained to enrich pathways specifically through Snai1. Based on the pathway enriched, the dysregulation of Snai1 due to LINC00221 silencing resulted in the enrichment of pathways such as “Signaling by Rho-GTPases”. Rho GTPases are well known regulators of actin cytoskeleton which is involved in a wide range of actin related processes affiliated with cell migration, polarity and membrane trafficking that can be regulated by Snai1 26–28 . To further support this observation, pathways enriched from both T98G si − LINC00221 and T98G miR − 34c−5p also revealed several pathways specific to actin, cytoskeleton dynamics, and extracellular matrix. The actin cytoskeleton forms an integral part of cell motility whereby protrusive and contractile forces were initiated through the actin filaments leading to cell migration 29 . Studies has shown the upregulation of factors which signals for actin cytoskeleton remodeling to be upregulated in cancers 30 . The CCT group of proteins, which were among the DEPs to be enriched in pathways specific to folding of actin by CCT/TriC in T98G si − LINC00221 and T98G miR − 34c−5p , were reported as a dysregulated element in GBM extracellular vesicles and are all heavily implicated in cell migration 31 – 33 . In LN18 cells, silencing of LINC00221 resulted in the alteration of TPT1, RAB35, KRT9, and KRT10. TPT1 (also known as TCTP) has been reported to be involved in the cytoskeleton remodeling through affecting structural proteins such as actin and tubulins 34 . RAB35 is an oncogenic protein which were reported to be affiliated in invasion and metastasis in cancer and could facilitates actin depolymerization, which lead to change in cytoskeletal integrity 35 . Both KRT9 and KRT10 are intermediate filaments family of cytoskeletal proteins. These proteins are heavily implicated in cancer development and can directly impact cell proliferation, death, migration, and invasiveness 36 . While these DEPs could potentially account for the observed decrease in cell migration following LINC00221 silencing in LN18, further validation studies are required. 5.0 Conclusion In summary, silencing LINC00221 in T98G cells resulted in reduced cell migration and invasion, accompanied by the identification of DEPs enriched in actin and cytoskeletal-related pathways. Notably, this regulation of DEPs was found to be mediated by the interaction of LINC00221 with miR-34c-5p, which in turn regulated the expression of Snail. Meanwhile, LINC00221 silencing in LN18 cells led to decreased cell migration, with several DEPs associated with cellular structural elements. These findings underscore the differential molecular targets of LINC00221 silencing in T98G and LN18 cells, emphasizing the multifaceted and intricate oncogenic nature of LINC00221 and miR-34c-5p in GBM. To address the study's limitations, future investigations can explore additional miRNA targets, factors related to epithelial-mesenchymal transition (EMT), and proteins associated with migration and invasion governed by LINC00221. Declarations Acknowledgement We would like to thank Ms Aliaa Idrus from the Jeffrey Cheah School of Medicine and Health Sciences, Proteomics and Metabolomics Platform for assisting us with the LC-MS/MS run. Author Contributions DHLL:Conceptualization, bioinformatics protocol development, investigation, data collection and analysis, first draft writing and editing. SAH: Microarray and data analysis MS: Manuscript draft writing and critical editing, project supervision SAZA: LC-MS/MS and data analysis, draft writing and editing SNP: Manuscript draft writing and editing, microarray data authorization SO: Manuscript draft writing, luciferase analysis and critical editing, project supervision AKR: Manuscript draft writing and critical editing, project supervision MNAK: Project administration, funding acquisition, project conceptualization, critical data analysis, draft writing and critical editing and project supervision All authors read and approved the final manuscript. Data availability statement All data generated or analysed during this study are included in this published article and its supplementary information files. The long non-coding RNAs (lncRNAs) identified in this study through bioinformatic analysis were derived from a microarray dataset. It is important to note that the complete microarray data is not publicly accessible, as it is an integral component of a distinct research project supported by the National Institutes of Health (NIH)/IMR (grant number NMRR 17-1064-36200). This microarray data is however available from the SNP upon reasonable request. Conflict of Interest The authors declare that there are no competing interests. Funding This research was funded by High Impact Research Support Fund (HIRSF) grant (grant code STG-000145) from Monash University Malaysia References Brown, N. F. et al. Survival Outcomes and Prognostic Factors in Glioblastoma. Cancers (Basel) 14, doi: 10.3390/cancers14133161 (2022). Leung, D. H. L., Phon, B. W. S., Sivalingam, M., Radhakrishnan, A. K. & Kamarudin, M. N. A. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3831522","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":265581310,"identity":"09afa86e-d92a-40e0-a12c-463094f6edf3","order_by":0,"name":"Dexter Hoi Long Leung","email":"","orcid":"","institution":"Monash University Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Dexter","middleName":"Hoi Long","lastName":"Leung","suffix":""},{"id":265581311,"identity":"72075f03-7e50-4271-89d0-6d4fbf1fd2a2","order_by":1,"name":"Siti Ayuni Hassanudin","email":"","orcid":"","institution":"Monash University Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Siti","middleName":"Ayuni","lastName":"Hassanudin","suffix":""},{"id":265581312,"identity":"c7617b94-4458-4f10-8505-02878f82df97","order_by":2,"name":"Mageswary Sivalingam","email":"","orcid":"","institution":"Monash University Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Mageswary","middleName":"","lastName":"Sivalingam","suffix":""},{"id":265581313,"identity":"1b42cea3-7330-4696-9d8f-fbd229ce3599","order_by":3,"name":"Syafiq Anawi Zainal Abidin","email":"","orcid":"","institution":"Monash University Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Syafiq","middleName":"Anawi Zainal","lastName":"Abidin","suffix":""},{"id":265581314,"identity":"c17df069-4060-4686-b0c8-9a8a51157d42","order_by":4,"name":"Stephen Navendran Ponnampalam","email":"","orcid":"","institution":"UCSI Medical School","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"Navendran","lastName":"Ponnampalam","suffix":""},{"id":265581315,"identity":"47f6eded-d572-4a70-bbc8-e684e451b178","order_by":5,"name":"Satoshi Ogawa","email":"","orcid":"","institution":"Monash University Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Satoshi","middleName":"","lastName":"Ogawa","suffix":""},{"id":265581316,"identity":"79e85077-8d80-4417-95c8-f52351b5204f","order_by":6,"name":"Ammu K. Radhakrishnan","email":"","orcid":"","institution":"Monash University Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Ammu","middleName":"K.","lastName":"Radhakrishnan","suffix":""},{"id":265581317,"identity":"15a61243-92f9-43fa-89ea-37c11e1d20fe","order_by":7,"name":"Muhamad Noor Alfarizal Kamarudin","email":"data:image/png;base64,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","orcid":"","institution":"Monash University Malaysia","correspondingAuthor":true,"prefix":"","firstName":"Muhamad","middleName":"Noor Alfarizal","lastName":"Kamarudin","suffix":""}],"badges":[],"createdAt":"2024-01-03 09:59:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3831522/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3831522/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49353003,"identity":"dbac3440-64db-44f5-bd2d-bbc0f5229508","added_by":"auto","created_at":"2024-01-09 07:05:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":650685,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow for the bioinformatic prediction of potential lncRNA candidates from microarray dataset by utilizing various bioinformatic databases containing RNA-RNA interactions.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/54fe691cafe6b7e376d7912e.png"},{"id":49353203,"identity":"f92bfca4-502d-4a6e-b1f8-4fb15141a3db","added_by":"auto","created_at":"2024-01-09 07:13:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":122465,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted binding target sequence of miR-34c-5p with LINC00221 and Snai1 3’UTR obtained from bioinformatic database. Luciferase reporter plasmid were then inserted with these specific binding sequence which assessed the direct interaction of miR-34c-5p mimic.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/33e37829d4f42a8de5ab47e3.png"},{"id":49352601,"identity":"1a067ef6-03ca-440f-9fe4-0ec89ad30dec","added_by":"auto","created_at":"2024-01-09 06:57:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":128209,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Dot-plot illustrating 373 upregulated lncRNAs identified from microarray. Top-5 lncRNA with highest fold-change were annotated. (B) Prediction of lncRNA function based on function of target miRNA or proteins. (C) Network analysis of lncRNAs clustered based on selected GO annotations of interest associated with cell invasion and migration processes. (D) Network analysis of lncRNA-miRNA-protein interacting axis through lncTAR bioinformatic tool.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/0630ec0cf45901681e07ca65.png"},{"id":49352608,"identity":"f7ba862a-88f5-479c-809b-73e3309031de","added_by":"auto","created_at":"2024-01-09 06:57:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":219195,"visible":true,"origin":"","legend":"\u003cp\u003e(A) qPCR analysis. LINC00221 expression was assessed in NHA and three GBM cells (LN18, A172, T98G) and results demonstrated that LINC00221 is highly upregulated in the GBM cell lines. LINC00221 was silenced through siRNA transfection to allow cellular studies of LINC00221 function in (B) LN18, (C) T98G, and (D) A172 GBM cell lines. Effect of LINC00221 knockdown on T98G, A172, and LN18 cells were assessed through CCK- 8 assay. Results demonstrated that LINC00221 knockdown has significantly reduced viability of A172 at T=24 (E), while LINC00221 silencing has no effect on cell viability in T98G (F) and LN18 (G). Cell scratch assay was performed on T98G (H\u0026amp;I) and LN18 (J) following siLINC00221 transfections. Significant reduction in cell scratch closure were observed in T98G at T=36h following LINC00221 silencing, where no effect was observed in LN18 cells. Cell migration assay and cell invasion assay was performed on both LN18 and T98G cell lines. Results shown that LINC00221 silencing has decreased cell-migration in both cell lines (K), where only significant reduction in cell invasion were observed in T98G cells following LINC00221 silencing (L). All experiments were carried out at least for three individual replicates. ***P\u0026lt;0.001 **P\u0026lt;0.02 *P\u0026lt;0.033\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/ef1b4a7e159d8dfaf3f435aa.png"},{"id":49352602,"identity":"d0ec2a13-8bcb-4b1e-a9fe-0ab733f5e239","added_by":"auto","created_at":"2024-01-09 06:57:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":223590,"visible":true,"origin":"","legend":"\u003cp\u003eInvestigation of the LINC00221/miR-34c-5p/Snai1 axis. JESS Simple Western were first carried out to assess the effect of si-LINC00221 transfection on expression of EMT related proteins. Significant reductions in Snai1 and N-cadherin were recorded in T98G following transfection (A \u0026amp; B), where no reduction in EMT proteins were observed in LN18 cells following LINC00221 knockdown (C \u0026amp; D). Protein normalization module of JESS SimpleWestern was used for protein normalization. Results were presented in virtual bands obtained from COMPASS software, corrected area under the curve obtained and were used to calculate relative expressions between control groups and transfected groups. Potential miRNA candidates were then obtained from bioinformatic databases based on the reduction in expression of Snai1 and N-cadherin (CDH2) in T98G cells for further analysis. Luciferase reporter assay has assessed the direct interaction of miR-34c-5p with both upstream LINC00221 (G) and downstream Snai1 3’UTR region (H) which confirmed the LINC00221/miR-34c-5p/Snai1 3’UTR axis. JESS Simple western was then performed on LN18 cells transfected with miR-34c-5p mimic where significant reduction in Snai1 expression were recorded. All experiments were carried out for at least a minimum of three biological replicates. ***P\u0026lt;0.001, ** P\u0026lt;0.02, *P\u0026lt;0.033.\u003c/p\u003e","description":"","filename":"FIgure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/1d339fd2b71eb6fa74570bb9.png"},{"id":49353000,"identity":"91214e7a-24f3-489b-8f40-7da8e09bb05c","added_by":"auto","created_at":"2024-01-09 07:05:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":401490,"visible":true,"origin":"","legend":"\u003cp\u003eSTRING analysis of Snai1 and DEPs identified in si-LINC00221 transfected T98G cells to identify potential pathways affected by LINC00221 silencing through enrichment of pathways specific to LINC00221-Snai1 axis\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/4268686e6a120a7b5125d482.png"},{"id":49352606,"identity":"d0bed425-2b3c-483b-b41a-7edcd870f95c","added_by":"auto","created_at":"2024-01-09 06:57:45","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":912677,"visible":true,"origin":"","legend":"\u003cp\u003eSTRING analysis of Snai1 and DEPs identified in miR-34c-5p mimics transfected T98G cells to identify potential pathways affected by the miR-34c-5p/Snai1 axis in T98G cells\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/49400b54211a877482a1c331.png"},{"id":49353638,"identity":"8efc7262-8d09-4e3c-9a77-d32818438413","added_by":"auto","created_at":"2024-01-09 07:21:44","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":593279,"visible":true,"origin":"","legend":"\u003cp\u003eSTRING analysis of Snai1 and specific DEPs enriched in the specific pathways obtained in both T98G groups with si-LINC00221 and miR-34c-5p mimics trasnsfection.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/9568f644e022a240aa1448b1.png"},{"id":51526495,"identity":"d5d74aa2-d943-4ff7-b1e6-bb830c108064","added_by":"auto","created_at":"2024-02-23 05:51:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3349024,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/ba1687f9-21b3-420c-9018-a6943daf0453.pdf"},{"id":49352609,"identity":"a36f2c3f-4ae2-4257-86dd-7f12889f8f7e","added_by":"auto","created_at":"2024-01-09 06:57:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3037018,"visible":true,"origin":"","legend":"","description":"","filename":"SISCIREP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3831522/v1/a8ad251e03816e56a825cfb2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Silencing of LINC00221 Suppresses Glioblastoma Cell Migration and Invasion through miR-34c-5p/Snai1 and Regulation of Actin and Cytoskeletal Dynamics Proteins","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eGlioblastoma (GBM) is the most common adult malignant brain tumor, where complete surgical resection is impossible due to its highly aggressive nature\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The acquired resistance of the tumor to chemotherapeutic drugs, coupled with the high degree of invasiveness underlie this aggressive nature of GBM. These attributes lead to a low overall survival and high recurrence post-therapy in GBM patients. Several factors contribute to the aggressive phenotype of GBM that include the mesenchymal (MES) transition process, which induces the transition of GBM tumor cells to more aggressive and motile phenotypes. The induction of MES transition in GBM has similar key expression profiles to the classical non-neural epithelial-to-mesenchymal transition (EMT) setting. These involve an increase in the expression of mesenchymal markers (such as N-cadherin and vimentin) and transcription factors (such as Snai1, Slug, ZEB1).\u003c/p\u003e \u003cp\u003eThe complex interplays between various lncRNAs and the MES-transition transcription factors, EMT markers, and signaling pathways, which identified specific transcription factors regulating the MES transition process was identified in our recent systematic review\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWith the advancement of sequencing technologies, non-coding RNA such as long non-coding RNAs (lncRNAs), and microRNAs (miRNAs), have been identified to regulate cell motility through regulation of the EMT process and its associated proteins\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In recent years, the non-coding RNAs have been reported to contribute to the aggressive nature of GBM\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The initial microarray analysis performed between LN18 and normal human astrocyte cells in this study has identified a substantial number of upregulated lncRNAs, many of which remain uncharacterized in the context of GBM. In the context of cancer, the upregulation of genes often signifies oncogenic potential, while downregulation is typically associated with tumor-suppressing activity. Additionally, it is well-documented that lncRNAs play a significant role in gene regulation, primarily through the widely reported lncRNA-miRNA-protein signaling axis. Building upon this, this study aims to identify the potential oncogenic lncRNA candidate capable of enhancing the mobility of GBM cells. We seek to elucidate the potential lncRNA/miRNA/protein axis involved for a deeper understanding of the intricate mechanisms regulated by the lncRNA in this context.\u003c/p\u003e \u003cp\u003eNevertheless. in GBM, there are limited lncRNA studies in contrast with other types of cancers, such as breast cancer. The scarcity of comparable research has impeded the current research of lncRNAs mechanisms in the GBM motility landscape. This challenge primarily stems from the relatively limited clinical data available for GBM datasets compared to other cancers, as well as the availability of lncRNAs information in the bioinformatics databases, which complicate their functional characterization in GBM. To address this challenge, we utilized a series of bioinformatics tools which predicted LINC00221 as the putative oncogenic lncRNAs with the potential to govern GBM cell motility by influencing specific cellular processes. Additionally, the cell motility processes influenced by MES transition were substantiated with the identification of miR-34c-5p as a potential miRNA, downstream of LINC00221 and upstream of Snai1 that regulate the N-cadherin expression. Using this information, the associated mechanisms through the lncRNA-miRNA-protein axis of the LINC00221/ miR-34c-5p/Snail was further investigated in this study. The ongoing discovery of novel lncRNAs in GBM highlights the necessity for continuous investigations to comprehensively elucidate their cellular and molecular functions. This will enable a deeper comprehension of the intricate biological regulatory networks in GBM that are modulated by lncRNAs and ultimately aiding in their characterization specific to the GBM context as prognostic and therapeutic targets.\u003c/p\u003e"},{"header":"2.0 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Cell Culture, RNA extraction, and cDNA synthesis\u003c/h2\u003e \u003cp\u003eNormal human astrocyte cells (NHA, CC-2565, Lonza USA) were cultured using Astrocyte Growth Medium BulletKit (AGM, Lonza USA). The GBM cells consist of LN-18, A-172, and T98G cell lines were purchased from ATCC. The LN-18 cells (CRL-2610) were cultured in RPMI medium, while the A-172 cells (CRL-1620) were cultured in DMEM media (ATCC, USA), and the T98G cells (CRL-1690) were cultured in EMEM media (ATCC, USA). All complete media were supplemented with 10% Fetal Bovine Serum (FBS) (Gibco, USA) and 0.5% antibiotic-antimycotics (Gibco, USA). Total RNA was extracted using TRIzol reagent (Invitrogen, USA) according to the manufacturer\u0026rsquo;s instructions. cDNA was synthesized by a High-Capacity cDNA reverse transcription kit according to the manufacturer\u0026rsquo;s instruction (Applied Biosystems, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Microarray analysis\u003c/h2\u003e \u003cp\u003eTotal RNAs were subjected to \u003cem\u003ein vitro\u003c/em\u003e amplification and labeled with Low Input Quick Amp Labeling Kit (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer's instruction. Labeled RNA was mixed with the control RNA and hybridized to SurePrint G3 Mouse GE 8X60K (Agilent Technologies). Microarray was performed by Hokkaido System Science (Hokkaido, Japan). The microarrays were scanned using SureScan Microarray Scanner (Agilent Technologies). The scanned images were quantitatively analyzed with Feature Extraction Software v10.7.3.1 (Agilent Technologies). The expression data from the microarray were normalized using Linear and Locally Weighted Scatterplot Smoothing (LOWESS) method for \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ep\u003c/span\u003e-value estimation for each spot. The \u003cem\u003eq\u003c/em\u003e-value (false discovery rate, FDR) was calculated based on the \u003cem\u003ep\u003c/em\u003e-value, with a threshold of less than 0.01.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Bioinformatic analysis and prediction of lncRNA candidates\u003c/h2\u003e \u003cp\u003eThe upregulated differentially expressed genes (DEGs) from microarray were selected for lncRNA, performed through biomart\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. LNCipedia\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e was used to check for alternate names and other additional information used for these lncRNA transcripts. To validate that these genes are non-coding, the transcripts were analyzed for their protein-coding potential using the CPAT tool\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Functional enrichment based on gene ontology annotations and KEGG pathway were performed using Enrichr\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. To predict lncRNA function based on their interacting targets, RAID database was utilized to obtain all relevant RNA interactions (lncRNA, miRNA, mRNA, proteins)\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. TAM 2.0 database was utilized to obtain miRNAs that are associated with cellular processes leading to cell migration and invasion\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Cytoscape\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, an open-source software platform, was used to visualize complex networks.\u003c/p\u003e \u003cp\u003eLncRNAs specific lncRNA-protein interactions were obtained from the RAID database and the proteins were clustered based on the Gene Ontology (GO) biological process annotations containing keywords associated with cell motility. Only lncRNAs that interact with these proteins of interest were included in the subsequent analysis. For lncRNAs that were identified to interact with any of the proteins associated with the GO terms, the lncRNA sequence was first retrieved from Lncipedia, followed by retrieval of the sequence of all miRNAs associated with cell invasion processes from miRNameConverter\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The potential interactions of these miRNAs with the lncRNAs identified were predicted through LncTar\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrated the flow of the bioinformatic analyses carried out.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Quantitative Polymerase Chain Reaction (qPCR) to determine LINC00221 expression\u003c/h2\u003e \u003cp\u003eqPCR analysis was carried out using SensiFAST SYBR Hi-Rox mix (Bioline,UK) to measure the relative expression level of LINC00221 in three GBM cell lines (LN18, A172, and T98G) compared to NHA cells normalized to \u003cem\u003eARF1\u003c/em\u003e housekeeping gene. The primer sequence used are: LIN000221 (F: GCAGTAACTGTTGGTTGGGATG, R: CAGGCTTACAAGTGTCTTAGTCCAG); ARF1 (F: GACCACGATCCTCTACAAGC, R: TCCCACACAGTGAAGCTGATG). The qPCR reaction mixture was ran using ABI 7500 Fast Real-time system (Applied Biosystems, USA) with initial denaturation at 95\u003csup\u003eo\u003c/sup\u003eC for 10min, followed by 35 cycles of denaturation at 95\u003csup\u003eo\u003c/sup\u003eC for 15s, and lastly annealed and extended at 60\u003csup\u003eo\u003c/sup\u003eC for 1min. The relative expression levels were calculated using 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Transfection of siRNAs for LINC00221 silencing and miR-34c-5p mimics\u003c/h2\u003e \u003cp\u003eThe T98G, A172, and LN18 GBM cells were seeded into 24-well plate overnight to 70\u0026ndash;80% confluency at 30,000 cells/well and was starved before the start of transfection by replacing to base medium. Transfection efficiency of all cell lines used were first determined through transfecting TYE 563 Transfection Control DsiRNA (iDT), which is a fluorescence labelled transfection control. Fluorescence microscope (Nikon) was used to visualize fluorescence siRNA uptake by the cells following transfection to determine transfection efficiency. siRNAs or miRNA mimic were then used for transfection. The sequence for the siRNAs used are as follows: (i) siLINC00221_01 (5\u0026rsquo;-AUUGUUUCUUGGAUGAAUCUCUGGA-3\u0026rsquo; 3\u0026rsquo;-UUUAACAAAGAACCUACUUAGAGACCU-5\u0026rsquo;); (ii) siLINC00221_02 (5\u0026rsquo;-GCUCUUAUUUAAGUAAUACAAACCA-3\u0026rsquo; 3\u0026rsquo;-UUCGAGAAUAAAUUCAUUAUGUUUGGU-5\u0026rsquo;); (iii) siLINC00221_03 (5\u0026rsquo;-GAGCUCAGGUAUAGUCAAAAUUGTT-3\u0026rsquo; 3\u0026rsquo;-GUCUCGAGUCCAUAUCAGUUUUAACAA-5\u0026rsquo;); miR-34c-5p mimic (AGGCAGUGUAGUUAGCUGAUUGC).\u003c/p\u003e \u003cp\u003eFor transfection reagent, Lipofectamine 3000 (Invitrogen) were first diluted with Opti-MEM (Gibco), the volume of lipofectamine used were based on the manufacturer\u0026rsquo;s recommended volume for the respective plates used (0.5uL for 96-wells; 1.5uL for 24-wells; and 7.5uL for 6-wells). Lipofectamine-DNA complexes were then prepared through adding 25nmol of either siRNA or miRNA mimics and incubated at 37\u003csup\u003eo\u003c/sup\u003eC for 15min. The lipofectamine-DNA complex was then added dropwise into the cells and incubated at 37\u003csup\u003eo\u003c/sup\u003eC in a CO\u003csub\u003e2\u003c/sub\u003e incubator for 24h. The cells were then recovered by replacing the media with medium supplied with 10% serum and incubated with until subsequent assay was carried out to these transfected cells. Transfection efficiency of siRNA in all three cell lines were first determined through qPCR analysis after 24h of cell recovery following transfection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Cell viability\u003c/h2\u003e \u003cp\u003eFor cell viability, A172, LN18, and T98G cells were seeded into 96-well plate at 5000 cells/well overnight until ~\u0026thinsp;70% confluency and were transfected with siRNAs as previously described. Following transfection for 24h, cell-viability were determine using CCK-8 (Dojindo, Japan) according to manufacturer\u0026rsquo;s protocol. The CCK-8 reagent was added to transfected cells and incubated at 37\u003csup\u003eo\u003c/sup\u003eC for 1 hr. Absorbance at 450 nm were then obtained by using a microplate reader (TECAN, Switzerland). Relative viability of cells was obtained by comparing the absorbance of the transfected cells with the absorbance of the control cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Cell scratch assay\u003c/h2\u003e \u003cp\u003eFor the cell scratch assay, the T98G and LN18 cells were seeded into 24 well plate overnight at 30,000 cells/well to reach\u0026thinsp;~\u0026thinsp;70% confluency. The seeded cells were then transfected with the respective siRNAs for 24 hr. Following cell recovery at 24 hr, a vertical scratch was performed using a sterile 100 \u0026micro;L pipette tip, and the cells were washed twice with PBS before serum-free media was added and the cells were incubated at 37\u003csup\u003eo\u003c/sup\u003eC in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator. Photos were taken using a Nikon inverted microscope (Nikon, Japan) every 12 hr interval for a total of 48 hr. The photos were then analyzed using the ImageJ plugin developed by Suarez-Arnedo et al. (2020) to obtain area of the wound scratch. Percentage of wound closure in relative to T\u0026thinsp;=\u0026thinsp;0 was then calculated for each group. Relative wound closure was then calculated by comparing percentage of wound closure for each group with the control group in that specific time point.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Cell migration and cell invasion assay\u003c/h2\u003e \u003cp\u003eCell migration assay was performed using Cell Migration/Chemotaxis Assay Kit (catalogue no. ab235673) (Abcam, USA) according to manufacturer\u0026rsquo;s protocol. Briefly, 50,000 cells were seeded into each well and incubated for 24 hr before measuring for fluorescence signals at 530/590 nm. Relative migration was then calculated by comparing number of migrated cells between control and siLINC00221_03 transfected cells. Cell invasion assay was performed using QCM ECMatrix Cell-Invasion Assay (catalogue no. ECM555) (Merck, USA) according to manufacturer\u0026rsquo;s protocol. Again, 50,000 cells were seeded into each well and incubated for 24 hr before measuring for fluorescence signals at 480/520 nm. Relative invasion was then calculated by comparing number of invasive cells between control and siLINC00221_03 transfected cells. Fluorescence signals were obtained through microplate reader (TECAN, Switzerland)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Protein extraction and quantification\u003c/h2\u003e \u003cp\u003eProtein lysates was obtained through standard protein extraction protocol through RIPA buffer (Nacalai Tesque, Japan) supplemented with 1% protease inhibitor and 1% phosphatase inhibitor (Sigma, USA) as a form of extraction cocktail. Transfected cells from six-well plates were harvested, centrifuged, and washed with PBS twice prior to addition of the extraction cocktail and incubated for 15 min, and finally protein lysate was collected after centrifugation at \u003cem\u003e500 g\u003c/em\u003e for 10 min to remove cell debris. Concentration of protein lysate were quantified by using Pierce BCA Protein Assay Kit (ThermoFisher, USA) according to manufacturer\u0026rsquo;s protocol and the absorbance were measured using microplate reader (TECAN, Switzerland).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 JESS Simple Western\u003c/h2\u003e \u003cp\u003eJESS Simple Western was utilized to determine relative change in EMT protein expression following LINC00221 silencing based on recommended protocol from ProteinSimple using a 12\u0026ndash;230 kDa JESS separation module (SM-W004). Protein lysates at 1.2 mg/mL were mixed with fluorescent 5x Master mix (Protein Simple) to achieve final concentration of 1.0 mg/mL, which was followed by denaturation at 95\u003csup\u003eo\u003c/sup\u003eC for 5min, before loaded into each well. The samples were run on a capillary based system, where the protein separation will take place. Primary antibodies used for the analysis includes Vimentin (D21H3), N-Cadherin (D4R1H), β-catenin (D10A8), Snai1 (C15D3), Slug (C19G7), ZEB1 (D80D3), and E-cadherin (24E10) obtained from Cell Signalling Technology, USA. All primary antibodies listed were raised in rabbit. Dilution factor of 1:50 was utilized as the final concentration for all antibodies. Anti-Rabbit detection module (Biotechne, USA) was used as secondary antibody according to manufacturer\u0026rsquo;s instruction Total protein normalization was performed through protein normalization assay module (Biotechne, USA) to normalized proteins loaded into the well. Chemiluminescence were detected where the signals are captured in the JESS system. Compass software for Simple Western (Protein Simple), which calculated chemiluminescence intensity as peaks where the corrected area was used was used for data analysis. Results were expressed in terms of relative protein expression by comparing the corrected area between knockdown group and control group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Prediction of potential miRNA target\u003c/h2\u003e \u003cp\u003eTo predict the potential miRNA targets for LINC00221, a list of pre-computed potential miRNA for LINC00221 were obtained from RNA22 database\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. GEO microarray dataset (GSE65626) was used to identify downregulated miRNAs from this list of pre-computed potential miRNA candidates. Following this, three separate databases (miRDB, TargetScan, and RAID) containing predicted miRNA-mRNA interactions were used to search for miRNA that was predicted to interact with SNAI1, CDH2, and VIM. Based on the outcome of the prediction analysis, miR-34c-5p were chosen as a miRNA candidate for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Polymerase Chain Reaction (PCR) and luciferase reporter assay\u003c/h2\u003e \u003cp\u003eThe PCR amplicons of the predicted miR-34c-5p interacting target sequence were obtained through standard PCR reaction using a thermocycler (AppliedBiosystems, USA) with initial denaturation at 95\u003csup\u003eo\u003c/sup\u003eC for 10 min, followed by 35 cycles of denaturation at 95\u003csup\u003eo\u003c/sup\u003eC for 15 s, and lastly annealed and extended at 60\u003csup\u003eo\u003c/sup\u003eC for 1 min. The PCR amplicons were purified using the Wizard SV Gel and PCR clean-up system (Promega, USA). Dual luciferase reporter plasmid pmirGLO were obtained from Promega, USA. For construction of luciferase plasmid, luciferase plasmid pmirGLO (Promega, USA) were inserted with predicted binding site of miR-34c-5p with LINC00221 or Snai1-3\u0026rsquo;UTR to construct pmirGLO:LIN00221 or pmirGLO:Snai1-3\u0026rsquo;UTR. Wildtype pmirGLO were digested by the XhoI and XbaI restriction enzymes at room temperature for 15 min followed by heat inactivation at 60\u003csup\u003eo\u003c/sup\u003eC for 20 min. Then, 25 ng of purified PCR amplicons obtained previously were ligated into 100 ng of RE-digested pmirGLO by T4 DNA ligase (ThermoScientific, USA) by incubating the reaction mixture in room temperature for 20 min, followed by heat inactivation at 60\u003csup\u003eo\u003c/sup\u003eC for 20 min. The ligated plasmids were then propagated using the DH5α \u003cem\u003eE. coli\u003c/em\u003e competent cells through heat-shock at 42\u003csup\u003eo\u003c/sup\u003eC for 45 s and placed on ice for 2 min followed by 1 hr of recovery in SOC medium (Invitrogen) before plating in LB Agar supplemented with ampicillin and incubated at 37\u003csup\u003eo\u003c/sup\u003eC overnight. Colonies were then subjected to colony PCR to confirm insertion of target sequence. Confirmed colonies containing correct inserts were propagated in LB broth (Oxoid, UK) overnight and plasmid extracted and purified by the Wizard Plus SV Minipreps DNA purification system (Promega). Concentration and quality of plasmid extracted were assessed through Nanodrop one spectrophotometer (Sigma). The workflow for luciferase plasmid construction were illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo assess the interaction of miR-34c-5p mimic with LINC00221 and 3\u0026rsquo;UTR Snai1, the T98G cells were seeded into 24-well plate overnight to reach\u0026thinsp;~\u0026thinsp;70% confluency at 30,000 cells/well. Following this, the seeded cells were then transfected with the luciferase plasmid with predicted miRNA binding sequences constructed as previously described to determine miRNA binding activity. 100 ng of pmirGLO:LINC00221 or pmirGLO:Snai1-3\u0026rsquo;UTR were transfected into the cells for 24 hr as the control group. For the experimental group, the cells were co-transfected with both the constructed plasmid and 25 ng of miR-34c-5p mimics. Negative control miRNA mimics and wild-type pmirGLO were also transfected as control. The cells were recovered in complete medium after transfection for 24 hr. Luciferase activity were then examined by using the Dual-Glo luciferase reporter assay (Promega). Luminescence of the transfected cells were quantified by using a microplate reader (TECAN) based on manufacturer\u0026rsquo;s protocol. Luminescence obtained from firefly luciferase in all samples were normalized with Renilla luciferase luminescence. Relative luciferase activity was then calculated based on the normalized luminescence value of control groups compared with the normalized luminescence of the experimental group where cells were co-transfected with both mutated plasmid and miR-34c-5p mimics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.13 Proteomics analysis of si-LINC00221 and miR-34c-5p mimics transfected cells\u003c/h2\u003e \u003cp\u003eFor proteome profiling, LC-MS/MS analysis was performed on three experimental groups: (i) T98G cells transfected with si-LINC00221 versus control (T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e), T98G cells transfected with miR-34c-5p mimic versus control (T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e), and LN18 cells transfected with si-LINC00221 versus control (LN18\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e). Protein lysates were extracted as previously described and was processed for MS analysis using EasyPEP MS Sample Prep Kit (Thermofisher, USA). The purified digested peptides were then loaded onto an Agilent AdvancedBio Peptide Mapping (120 A, 2.1 x 150 mm, 2.7 \u0026micro;m) attached on Agilent 1290 ultra-high-performance liquid-chromatography system (UHPLC). The column was equilibrated with 0.1% formic acid in water (solution A). The peptides were then eluted from the column with increasing gradients of 90% acetonitrile (ACN) in 0.1% formic acid solution (solution B) with the following gradients: 5\u0026ndash;75% solution B from 0 to 50 min and 75% solution B from 50 to 60 min, at a flow rate of 0.2 mL/min. The polarity of the Quadrupole-time of flight (Q-TOF) was set to positive, with capillary and fragmentor voltage being set at 1800 V and 360 V respectively along with 11 L/min of drying gas flow with a temperature of 280\u0026deg;C. MS acquisition by Data-dependent acquisition (DDA) mode was performed to analyze digested peptide spectrum in MS mode ranging from 110\u0026ndash;3000 \u003cem\u003em/z\u003c/em\u003e (mass to charge ratio) for MS scan (in quadrupole mode) and 50\u0026ndash;3000 \u003cem\u003em/z\u003c/em\u003e for MS/MS scan (in time-of-flight, TOF mode). Protein identification and LFQ were performed using PEAKS\u003csup\u003e\u0026reg;\u003c/sup\u003e Studio software (Version 10.6, Bioinformatics Solutions Inc. (BSI), Waterloo, ON, Canada). The analysis was performed once on every biological sample (three biological repeats for every cell line/ type). The UniProt/ Swiss-Prot (Organism: \u003cem\u003eHomo sapiens\u003c/em\u003e) database (release 2018_03) was used for protein identification and homology search by comparing the de \u003cem\u003enovo\u003c/em\u003e sequence tag. Label-free quantitation (LFQ) analysis was performed using the built-in quantification module in PEAKS Studio with the following parameters: Carbamidomethylation was set as fixed modification (+\u0026thinsp;57.02 on C) with maximum mixed cleavages at 3. The mass tolerance of precursors was set at 20 ppm while the parent mass and fragment ion mass error tolerance were both set 0.1 Da with monoisotopic as the precursor mass search type while the maximum missed cleavages was set at 3 precursors. Trypsin was selected as the enzyme used for digestion. In order to filter out inaccurate proteins, the recommended PEAKS Q statistical analysis (a built- in statistical tool of the PEAKS\u003csup\u003eⓇ\u003c/sup\u003e software) settings are applied as follows: False discovery rate (FDR) threshold\u0026thinsp;\u0026le;\u0026thinsp;1%, fold change\u0026thinsp;\u0026ge;\u0026thinsp;1, unique peptide\u0026thinsp;\u0026ge;\u0026thinsp;1, and significance score\u0026thinsp;\u0026ge;\u0026thinsp;20. A significance score of greater than 20 is relatively high in confidence as it targets very few decoy matches above the threshold and is equivalent to a significance p value of \u0026lt;\u0026thinsp;0.01. The relative amount of proteins per sample is determined according to their intensities in which the protein intensities are log transformed, normalized and compared between the samples. Normalization during quantitation was performed based on Total Ion Chromatogram (TIC). The default maximum number of variable posttranslational modifications per peptide was set at 3, while the \u003cem\u003eDe novo\u003c/em\u003e score threshold for SPIDER was set 15 and Peptide hit score threshold at 30. Retention time shift tolerance was 6 min. The analyses are exported into an Excel spreadsheet listing every protein identified, along with their corresponding \u0026minus;\u0026thinsp;10lgP scores, raw and normalized quantified values, percentage coverage and number of peptides and its unique peptide sequences. PEAKS Q indicated that a \u0026minus;\u0026thinsp;10 lgP\u0026thinsp;\u0026gt;\u0026thinsp;20 was relatively high in confidence as it targeted very few decoys matches above that threshold.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e2.14 Bioinformatic analyses of differentially expressed proteins (DEPs)\u003c/h2\u003e \u003cp\u003eThe DEPs identified from proteomic analysis were inserted into STRING and was clustered through k-means clustering. STRING enrichment analysis with an interaction score of high confidence (0.700) was performed to identify enriched REACTOME pathways in both T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e that is associated with Snai1 identified through STRING interactions\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e2.15 Statistical Analysis\u003c/h2\u003e \u003cp\u003eOne-way analysis of variance (ANOVA) with Tukey's post hoc test and independent t-tests were employed to compare means among multiple groups. In addition, a two-way ANOVA was performed to assess the influence of two independent variables on a dependent variable. Subsequently, Bonferroni post hoc tests and independent t-tests were conducted to compare means between groups within each combination of the independent variables, where applicable.\u003c/p\u003e \u003c/div\u003e"},{"header":"3.0 Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Microarray revealed 373 upregulated lncRNAs in LN18 GBM cells compared to NHA cells\u003c/h2\u003e \u003cp\u003eThe comparative analyses of LN18 and NHA cell lines (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, FC\u0026thinsp;\u0026gt;\u0026thinsp;2) provided 372 upregulated lncRNA transcripts \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, \u003cem\u003eComplete information available in Supplementary S1\u003c/em\u003e), The top-10 upregulated lncRNAs were listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Upregulated expression of LINC00221 is predicted with its oncogenic roles in GBM cell motility\u003c/h2\u003e \u003cp\u003eThe functions of lncRNAs identified from microarray were predicted based on the functions of both miRNAs and proteins they interact with, which is available in RAID and TAM 2.0 bioinformatic database. From Gene set enrichment analysis (GSEA) of the upregulated lncRNAs, only one lncRNAs, \u003cem\u003eSRGAP3\u003c/em\u003e, was annotated with cell invasion and motility associated GO annotation. To further characterize lncRNAs which cannot be functionally enriched through GSEA, their function was predicted based on their interactions with both miRNAs and proteins which were obtained from the RAID bioinformatic database. Based on protein functions, among the 372 upregulated lncRNAs identified in LN18 cells, 35 lncRNAs are associated with angiogenesis; 32 with cell migration; 35 with epithelial-to-mesenchymal transition; 27 with hypoxia; and 10 lncRNAs were predicted to be involved in ECM. In addition, 65 lncRNAs are predicted to be involved in angiogenesis, 36 with cell migration, 51 with cell motility, and 70 with EMT based on miRNAs function \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e Network analysis was performed to visualize the potential function(s) of the upregulated lncRNAs based on their interacting targets (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Based on this, four specific lncRNAs were identified to be associated with cell motility, which were i) LINC00221 associated with EMT, ii) LINC01564 and LINC00265 with angiogenesis, and iii) LOC100240735 with cell migration. Finally, lncTAR was utilized to predict the binding potential of miRNAs associated with cell motility with the four lncRNAs (LINC00221, LINC00265, LINC001564, and LOC100240735 (also known as lnc-SMUG1). Based on lncTAR prediction, 57 miRNAs were predicted to bind with LINC00221, 49 for both LINC001564 and LINC00265, and 21 for LOC100240735.\u003c/p\u003e \u003cp\u003eTo visualize the predicted lncRNA-miRNA-protein interacting network, potential mRNAs targets of these miRNAs were obtained from RAID miRNA-protein interaction database. These interactions were then analyzed using Cytoscape to visualize distinct signatures \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Results through lncTAR predictions were able further to visualize the distinct and potential interacting pathways of these four lncRNAs. LINC00221 was predicted to bind with miRNAs which affects biological pathways at different axis/loci at \u003cem\u003eTP53\u003c/em\u003e, EGF, TERT, and MDM2; lncSMUG1 with miR-584 will interact with BRCA1, STAT1, PDGFRA, and MDM2; and both LINC01564 and LINC00265 with PTEN, PTG52, and EGFR. As LINC00221 were identified as the most differentially expressed lncRNA in LN18 when compared to NHA, alongside results from combined bioinformatic analysis which predicted a specific signaling axis in influencing cell motility, LINC00221 were chosen for further characterization. Following this, LINC00221 expressions were validated in A172, T98G, and LN18 GBM cell lines through qPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Results shown that LINC00221 is significantly upregulated (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in LN18 by 177.91-fold, A172 by 38.59-fold, and T98G by 5.68-fold when compared with NHA cells. The observed trend is consistent with results from the LN18 vs. NHA microarray (127.40-fold increase).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop-10 upregulated lncRNA gene in LN18 in relative to NHA\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFold Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFDR P-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLINC00221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.52 x 10\u003csup\u003e\u0026minus;\u0026thinsp;23\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.18 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENST00000446495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.12 x 10\u003csup\u003e\u0026minus;\u0026thinsp;23\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.37 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOC340340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.80 x 10\u003csup\u003e\u0026minus;\u0026thinsp;22\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.03 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFENDRR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.01 x 10\u003csup\u003e\u0026minus;\u0026thinsp;23\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.43 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDSCR8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.74 x 10\u003csup\u003e\u0026minus;\u0026thinsp;23\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.46 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnc-EIF3M-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.44 x 10\u003csup\u003e\u0026minus;\u0026thinsp;21\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.46 x 10\u003csup\u003e\u0026minus;\u0026thinsp;19\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLINC00470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.38 x 10\u003csup\u003e\u0026minus;\u0026thinsp;19\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLINC00871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.63 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.65 x 10\u003csup\u003e\u0026minus;\u0026thinsp;19\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLINC01296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.47 x 10\u003csup\u003e\u0026minus;\u0026thinsp;19\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.92 x 10\u003csup\u003e\u0026minus;\u0026thinsp;17\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERICH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.46 x 10\u003csup\u003e\u0026minus;\u0026thinsp;18\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.68 x 10\u003csup\u003e\u0026minus;\u0026thinsp;17\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.3 LINC00221 silencing decreased A172 cells viability\u003c/h2\u003e \u003cp\u003eTo determine the knockdown efficiency of three siRNAs (siLINC00221_01, siLINC00221_02, and siLINC00221_03) in LINC0221 silencing in A172, T98G, and LN18 GBM cell lines, qPCR was performed following cell transfection to assess LINC00221 expression. Transfecting siLINC00221_01, siLINC00221_02, and siLINC00221_03 significantly decreased LINC00221 expression in GBM cells at T\u0026thinsp;=\u0026thinsp;24h. For siLINC00221_01, significant reduction in expression of LINC00221 by 68% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), 75% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and 58% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were achieved for LN18, A172, and T98G cells, respectively. For siLINC00221_02, significant reduction in expression of LINC00221 by 90% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), 70% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), 78% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were achieved in LN18, A172, and T98G cells, respectively. For siLINC00221_03, significant reduction in expression of LINC00221 by 84% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), 65% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and 78% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were observed in LN18, A172, and T98G cells, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eReduction of LINC00221 expression has observed significant reduction of cell viability in cells. A significant reduction (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in A172 viable cells at 24h were observed for cells transfected with siLINC00221_01 (20% reduction), siLINC00221_02 (39% reduction, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), siLINC00221 (50% reduction, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and siHPRT (64% reduction, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. For T98G cells, no significant reduction (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in cell viability were observed at T\u0026thinsp;=\u0026thinsp;24h other than cells transfected with positive control siHPRT (43% reduction, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). For LN18 cells, no significant reduction (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) on cell viability were observed across all siRNAs transfected at 24h \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.4 LINC00221 silencing impeded cell scratch closure, migration, and invasion in T98G cells and reduced migration in LN18 cells\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAs A172 cells exhibited reduced viability following LINC00221 silencing, the effect of LINC00221 in influencing A172 motility was not investigated further. For T98G cells, LINC00221 silencing has demonstrated a significant reduction in cell scratch closure for siLINC00221_02, siLINC00221_03, and siHPRT starting at 36h post-scratch (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) when compared with both control and negative control group where at T\u0026thinsp;=\u0026thinsp;36 both blank and negative control group has observed around 60% closure of cell scratch, while across the other three experimental groups mentioned had observed only\u0026thinsp;\u0026lt;\u0026thinsp;20% closure of cell scratch (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH\u0026amp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI\u003cb\u003e)\u003c/b\u003e. For LN18 cells, no significant changes (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in cell scratch closure post-scratch were observed across all cell groups transfected with different siRNAs \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ\u003cb\u003e)\u003c/b\u003e. Complete information for cell scratch assay performed are available in \u003cb\u003eSupplementary S2.\u003c/b\u003e Based on the observation of siLINC00221_03 exhibiting a significant effect on both T98G cells viability and cell scratch closure at 36h and 48h respectively and was used for subsequent assays (from here referred as si-LINC00221).\u003c/p\u003e \u003cp\u003eIn cell migration assay, both LN18 and T98G cell lines exhibited a significant reduction (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in cell migration at approximately of 25% following si-LINC00221 transfection at 24h when compared with the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK). Conversely, in cell invasion assay, T98G exhibited a significant reduction of 40% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in cell invasion following si-LINC00221 transfection, while LN18 did not show any significant changes (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in cell invasion following si-LINC00221 transfection at 24h (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eL\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.5 LINC00221 silencing downregulates Snai1 and N-cadherin in T98G cells\u003c/h2\u003e \u003cp\u003eTo determine if the observed decreased in migration and invasion following LINC00221 silencing are associated with EMT related factors, the expression of EMT transcription factors (EMT-TFs), ZEB1, Snai1, Slug; and EMT markers (N-cadherin, vimentin, E-cadherin, B-catenin) were assessed following si-LINC00221 transfection. In T98G cells, only Snai1 expression was significantly reduced (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) by 50% compared to the control samples \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. In LN18 cells, no significant reduction was observed in all of the EMT-TFs investigated \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor expression of EMT markers, relative expression of N-cadherin was observed to be significantly reduced (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) by 52% in T98G cells following LINC00221 silencing \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Changes in relative expression E-cadherin were also assessed. However, the results were not conclusive as the protein could not be detected in T98G cells. In LN18 cells, no significant changes (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) were observed in relative expression of EMT markers following LINC00221 silencing \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e., The complete protein profiles for all three replicates for protein expression analysis obtained from protein normalization module of JESS Simple Western are available in \u003cb\u003eSupplementary S3.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.6 miR-34c-5p targets both LINC00221 and Snai1-3\u0026rsquo;UTR in regulation of cell motility\u003c/h2\u003e \u003cp\u003eAs Snai1 and N-cadherin were observed as the potential target of LINC00221, the subsequent miRNA target of LINC00221 was predicted to investigate a complete lncRNA/miRNA/protein axis. As LINC00221 were found to be upregulated in GBM cells, we focus on downregulated miRNAs which can be obtained from several bioinformatic databases. From the RNA22 database, 1278 downregulated miRNAs which were pre-computed to interact with LINC00221 were obtained. Also, 245 downregulated miRNAs were found within the GEO microarray dataset (GSE65626). From these downregulated miRNAs which were pre-computed to interact with LINC00221, their potential interaction with downstream Snai1 and N-cadherin (CDH2) were searched from miRDB, RAID, and Targetscan databases \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eC \u0026amp; \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. The potential miRNA candidate was selected based on the fold-change observed from the microarray dataset alongside both interaction score and p-value from bioinformatic databases. These parameters show the probability if the miRNA candidate exhibits any bi-directional interaction with both upstream target LINC00221 and downstream target Snai1, mir-34c-5p with FC\u0026thinsp;=\u0026thinsp;0.09, predicted with LINC00221 interaction from RNA22 (p\u0026thinsp;=\u0026thinsp;0.05), and with Snai1/N-cadherin (with interaction score of 91 out of 100 from miRDB) was chosen for subsequent analysis.\u003c/p\u003e \u003cp\u003eFrom the bioinformatic databases, miR-34c-5p was predicted to interact with LINC00221 at target site GGGATCAGTTAGAAAGCTCTT, and at the 3\u0026rsquo;UTR region of Snai1 with the target sequence CACTGCCA. Luciferase reporter assay was then used to assess the interaction between miR-34c-5p mimics with predicted sequences of both LINC00221 and Snai1 3\u0026rsquo;UTR. It was observed that the relative luciferase activity was significantly reduced (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) when miR-34c-5p mimics were co-transfected with mutated luciferase plasmid inserted with predicted target sequence (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eE \u0026amp; \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. As previously observed that si-LINC00221 transfection did not reduce Snai1 expression in LN18 cells, following the confirmation of miR-34c-5p interaction with both LINC00221 and Snai1, we investigated whether the miR-34c-5p mimics transfection would affect the Snail expression in LN18. Interestingly, results shown the significant reduction in Snai1 expression following miR-34c-5p mimic transfection in LN18 cells (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e3.7 Silencing of LINC00221 and transfecting miR-34c-5p mimics suggests regulation of actin and cytoskeletal specific pathways which mediates cell motility in T98G cells\u003c/em\u003e \u003c/p\u003e \u003cp\u003eTo identify the potential mechanisms that may be regulated through the potential axis of LINC00221/miR-34c-5p/Snai1 axis especially in T98G cells, LC-MS/MS analysis were first performed on both T98G and LN18 cells to identify differentially expressed proteins (DEPs) affiliated with si-LINC00221 transfection (T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and LN18\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e). Additionally, DEPs associated in T98G cells with miR-34c-5p mimic transfected was obtained as well (T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eFrom T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e, 344 and 383 protein groups were identified from the control and transfected cells, where among these proteins 18 downregulated (FC\u0026thinsp;\u0026lt;\u0026thinsp;0.8) and 21 upregulated DEPs (FC\u0026thinsp;\u0026gt;\u0026thinsp;1.2) were identified (Complete Information Available In \u003cb\u003eSupplementary S4\u003c/b\u003e). For T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e, 434 and 411 protein groups were identified from control and transfected cells, respectively, where 79 downregulated DEPs (FC\u0026thinsp;\u0026lt;\u0026thinsp;0.8) were identified (Complete Information Available In \u003cb\u003eSupplementary S5\u003c/b\u003e). Six common DEPs (LAMP2, Protein 14-3-3B, TCPZ, H4, TEBP, TCPH) were observed between both T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e. In contrast, for LN18\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e, 402 and 411 protein groups were identified for control and transfected group, respectively. Among these, 2 downregulated DEPs (TPT1 \u0026amp; HIST1H4J) and 4 upregulated DEPs (PMPCA, KRT10, RAB35, KRT9) were identified (Complete Information Available In \u003cb\u003eSupplementary S6\u003c/b\u003e). There are no common DEPs shared between both T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221/miR\u0026minus;34c\u0026minus;5p\u003c/sup\u003e and LN18\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFollowing this, REACTOME pathways involved with Snai1 and DEPs identified in T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e were then functionally enriched through STRING (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e7\u003c/span\u003e), and enriched REACTOME pathways which is associated with Snai1 was tabulated (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the enriched pathways obtained, 4 common enriched REACTOME pathways were identified were namely: Folding of actin by CCT/TriC, Formation of tubulin folding intermediates by CCT/TriC, Prefoldin mediated transfer of substrate to CCT/TriC, and Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC). As there were only 6 DEPs identified in LN18 cells, functional enrichment was not possible. Finally, to identify possible mechanisms of the LINC00221/miR-34c-5p/Snai1 axis associated with T98G, Snai1 and all DEPs enriched alongside REACTOME pathways from T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e were inserted into STRING to collectively look for the possible mechanisms governed by LINC00221/miR-34c-5p/Snai1 axis in T98G cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelected REACTOME pathways which were significantly enriched in the DEPs identified from si-LINC00221 transfection in T98G cells\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerm ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eterm description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eobserved gene count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ebackground gene count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003estrength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003efalse discovery rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ematching proteins in network\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-390450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFolding of actin by CCT/TriC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-264870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaspase-mediated cleavage of cytoskeletal proteins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGSN,VIM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-9613829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChaperone Mediated Autophagy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLAMP2,VIM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-389960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormation of tubulin folding intermediates by CCT/TriC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-75153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApoptotic execution phase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eKPNB1,H1-2,GSN,VIM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-389957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrefoldin mediated transfer of substrate to CCT/TriC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-975956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRPL7,RPS3A,RPL30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-194315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignaling by Rho GTPases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.14E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHSPE1,H4C6,CCT7,CCT6A,H2BC5,H2BC4,H2BC12,YWHAB,ACTN1,VIM,H2BC14,H2BC9,CLTC,H2BS1,H2BC15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelected REACTOME pathways which were significantly enriched in the DEPs identified from miR-34c-5p mimic transfection in T98G cells\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eterm ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eterm description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eobserved gene count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ebackground gene count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003estrength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003efalse discovery rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ematching proteins in network\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-390450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFolding of actin by CCT/TriC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.80E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A,CCT5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-389960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormation of tubulin folding intermediates by CCT/TriC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.60E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A,CCT5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-389957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrefoldin mediated transfer of substrate to CCT/TriC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.80E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A,CCT5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-975956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.72E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRPL18A,RPL35,PABPC1,RPS24,RPL18,RPLP0,RPS5,RPS10,RPL9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-6814122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCooperation of PDCL (PhLP1) and TRiC/CCT in G-protein beta folding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.61E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A,CCT5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-975957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.73E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRPL18A,RPL35,PABPC1,RPS24,RPL18,RPLP0,RPS5,RPS10,RPL9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-390471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociation of TriC/CCT with target proteins during biosynthesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.71E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCCT7,CCT6A,CCT5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSA-9010553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegulation of expression of SLITs and ROBOs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.02E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePSME2,RPL18A,RPL35,PABPC1,RPS24,RPL18,RPLP0,RPS5,RPS10,RPL9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4.0 Discussion","content":"\u003cp\u003eDespite the growing recognition of the significance of lncRNAs, progress in studying lncRNAs in GBM remains bottlenecked in comparison with other cancer types. At present, the functional roles of lncRNAs, particularly in the context of GBM, remain largely uncharted at both the cellular and molecular levels. Comprehensive investigations focusing on specific lncRNAs that enable the utilization of Gene Ontology (GO)-annotated lncRNA databases for cluster analysis are scarce, especially in comparison to research conducted in other cancer types. To elucidate the functional relevance of lncRNAs in GBM motility, an analysis involved the acquisition of miRNAs and proteins known to interact with the identified lncRNAs in cell motility was conducted using bioinformatic databases. Subsequently, clustering was employed to predict either (i) the specific functions of the lncRNAs based on their miRNA associations or (ii) processes of the proteins they have reported interactions with. These functions include angiogenesis, hypoxia responses, extracellular matrix, and migration. Angiogenesis is a critical event in the progression of GBM since the tumors exhibit a high degree of vascular proliferation and endothelial cell hyperplasia\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Endothelial cells-associated with angiogenesis are among the critical inducers of cell invasion\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. On the other hand, hypoxia can trigger the invasive phenotype of GBM by upregulating the levels of invasion proteins that drive the degradation and remodeling of the extracellular matrix and EMT in GBM\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Although the information of the four lncRNAs, LINC00221, LINC00265, LINC001564, and LOC100240735 is scarce, the current protocol successfully predicted their roles based on these cellular and molecular processes of cell motility.\u003c/p\u003e \u003cp\u003eLINC00221 was reported to have multiple roles in other types of cancers which includes promotion of cisplastin resistance in non-small lung cancer \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Additionally, LINC00221 promoted the progression of hepatocellular carcinoma through the LINC00221/let-7a-5p/MMP11 axis\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Interestingly, LINC00221 demonstrated a tumor suppressive role in children acute lymphoblastic leukemia by influencing proliferation and apoptosis through the LINC00221/miR-152-3p/ATP2A2 axis\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, the existing knowledge regarding LINC00221 in the context of GBM is lacking, necessitating an in-depth investigation and validation of its potential oncogenic roles, whether in promoting or inhibiting cell invasion. From the microarray, LINC00221 was identified as the most upregulated lncRNA in LN18 GBM cells as compared to NHA. Coupled with bioinformatic analyses which have predicted the involvement of LINC00221 in cell motility processes. The qPCR experiment performed also confirmed the upregulation of LINC00221 as an upregulated lncRNA in three GBM cell lines when compared to NHA. Based on all these observations, LINC00221 was chosen as the target lncRNA candidate to be further characterized in GBM cell motility.\u003c/p\u003e \u003cp\u003eOur results demonstrated the transient silencing of LINC00221 reduced the A172 cell viability. Furthermore, LINC00221 silencing has impeded cell scratch closure in T98G cells, where the inhibition of motility potential was further evident by the decreased cell migration, and cell invasion in T98G cells. In LN18, however, LINC00221 silencing only reduced cell migration. These results have first demonstrated the oncogenic role of LINC00221 in GBM cells. The observed variation in the impact of LINC00221 silencing among the three GBM cell lines employed in this study suggests the possibility that LINC00221 may influence distinct biological pathways in a context-dependent manner. Our prior bioinformatics analysis has initially indicated the potential role of LINC00221 in EMT-related pathways. To validate this, we performed protein expression analysis, revealing a significant downregulation of the EMT transcription factor Snai1 and the EMT marker N-cadherin in T98G cells following LINC00221 silencing. This observation underscores the possibility of LINC00221 exerting distinct regulatory effects at the molecular level within the GBM cells used in this study.\u003c/p\u003e \u003cp\u003eTo further establish a potential lncRNA-miRNA-protein axis of LINC00221, the possible miRNA target candidates that can interact with LINC00221 which concomitantly reducing the regulatory effect towards Snai1 was predicted. Given its consistent presence in multiple predictive bioinformatic databases and the high confidence score indicating its interaction with both upstream LINC00221 and downstream Snai1-3\u0026rsquo;UTR, miR-34c-5p was chosen as the primary candidate miRNA for further investigation. MiR-34c-5p plays a role in suppressing both cell migration and invasion in both gastric cancer through targeting MAP2K1, and cervical cancer by targeting Notch1\u003csup\u003e23,24\u003c/sup\u003e. In the context of GBM, limited information has been available regarding miR-34c-5p. A previous investigation delved into the roles of miR-34c isoforms, specifically miR-34c-3p and miR-34c-5p, within GBM \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. This study reported differential tumor-suppressive roles, contrasting the regulatory effects of miR-34c-3p and miR-34-5p, both of which were found to possess invasion-inhibiting capabilities. Notably, miR-34c-3p was observed to inhibit invasion by targeting Notch1, while the molecular target associated with miR-34c-5p-mediated invasion remained unexplored. In our investigation, we have observed a direct interaction between miR-34c-5p and both the upstream regulator LINC00221 and the downstream target Snai1.\u003c/p\u003e \u003cp\u003eBased on JESS Simple western, Snai1 expression remained unchanged following the silencing of LINC00221 in LN18 cells. Considering the universality of the LINC00221/miR-34c-5p/Snai1 axis, the subsequent investigation delved into the effects of miR-34c-5p mimic transfection on Snai1 expression in LN18 cells. We observed a substantial decrease in Snai1 expression following transfection, confirming the validity of our study on lncRNA-miRNA-protein interactions. Collectively, based on our observations, LINC00221 targets miR-34c-5p, resulting in the upregulation of Snai1, which, in turn, suppresses T98G cell motility. The multifaceted target of lncRNA, particularly in the context of LINC00221, may underlie the lack of Snai1 expression modulation upon initial silencing of LINC00221 in LN18 cells. This observation supports the idea that LINC00221 exerts diverse oncogenic functions in different GBM cell lines, possibly attributed to variations in its preference for binding to distinct targets in each cell line.\u003c/p\u003e \u003cp\u003eTo identify alterations in mechanisms associated with LINC00221 and miR-34c-5p in T98G cells, we obtained proteome profiles after LINC00221 silencing (T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e) and miR-34c-5p mimic transfection (T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e). We utilized Snai1 and the DEPs obtained to enrich pathways specifically through Snai1. Based on the pathway enriched, the dysregulation of Snai1 due to LINC00221 silencing resulted in the enrichment of pathways such as \u0026ldquo;Signaling by Rho-GTPases\u0026rdquo;. Rho GTPases are well known regulators of actin cytoskeleton which is involved in a wide range of actin related processes affiliated with cell migration, polarity and membrane trafficking that can be regulated by Snai1\u003csup\u003e26\u0026ndash;28\u003c/sup\u003e. To further support this observation, pathways enriched from both T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e also revealed several pathways specific to actin, cytoskeleton dynamics, and extracellular matrix. The actin cytoskeleton forms an integral part of cell motility whereby protrusive and contractile forces were initiated through the actin filaments leading to cell migration\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Studies has shown the upregulation of factors which signals for actin cytoskeleton remodeling to be upregulated in cancers\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The CCT group of proteins, which were among the DEPs to be enriched in pathways specific to folding of actin by CCT/TriC in T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e, were reported as a dysregulated element in GBM extracellular vesicles and are all heavily implicated in cell migration\u003csup\u003e\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn LN18 cells, silencing of LINC00221 resulted in the alteration of TPT1, RAB35, KRT9, and KRT10. TPT1 (also known as TCTP) has been reported to be involved in the cytoskeleton remodeling through affecting structural proteins such as actin and tubulins\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. RAB35 is an oncogenic protein which were reported to be affiliated in invasion and metastasis in cancer and could facilitates actin depolymerization, which lead to change in cytoskeletal integrity\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Both KRT9 and KRT10 are intermediate filaments family of cytoskeletal proteins. These proteins are heavily implicated in cancer development and can directly impact cell proliferation, death, migration, and invasiveness\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. While these DEPs could potentially account for the observed decrease in cell migration following LINC00221 silencing in LN18, further validation studies are required.\u003c/p\u003e"},{"header":"5.0 Conclusion","content":"\u003cp\u003eIn summary, silencing LINC00221 in T98G cells resulted in reduced cell migration and invasion, accompanied by the identification of DEPs enriched in actin and cytoskeletal-related pathways. Notably, this regulation of DEPs was found to be mediated by the interaction of LINC00221 with miR-34c-5p, which in turn regulated the expression of Snail. Meanwhile, LINC00221 silencing in LN18 cells led to decreased cell migration, with several DEPs associated with cellular structural elements. These findings underscore the differential molecular targets of LINC00221 silencing in T98G and LN18 cells, emphasizing the multifaceted and intricate oncogenic nature of LINC00221 and miR-34c-5p in GBM. To address the study's limitations, future investigations can explore additional miRNA targets, factors related to epithelial-mesenchymal transition (EMT), and proteins associated with migration and invasion governed by LINC00221.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Ms Aliaa Idrus from the Jeffrey Cheah School of Medicine and Health Sciences, Proteomics and Metabolomics Platform for assisting us with the LC-MS/MS run.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDHLL:Conceptualization, bioinformatics protocol development, investigation, data collection and analysis, first draft writing and editing.\u003c/p\u003e\n\u003cp\u003eSAH: Microarray and data analysis\u003c/p\u003e\n\u003cp\u003eMS: Manuscript draft writing and critical editing, project supervision\u003c/p\u003e\n\u003cp\u003eSAZA: LC-MS/MS and data analysis, draft writing and editing\u003c/p\u003e\n\u003cp\u003eSNP: Manuscript draft writing and editing, microarray data authorization\u003c/p\u003e\n\u003cp\u003eSO: Manuscript draft writing, luciferase analysis and critical editing, project supervision\u003c/p\u003e\n\u003cp\u003eAKR: Manuscript draft writing and critical editing, project supervision\u003c/p\u003e\n\u003cp\u003eMNAK: Project administration, funding acquisition, project conceptualization, critical data analysis, draft writing and critical editing and\u0026nbsp;project supervision\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files. The long non-coding RNAs (lncRNAs) identified in this study through bioinformatic analysis were derived from a microarray dataset. It is important to note that the complete microarray data is not publicly accessible, as it is an integral component of a distinct research project supported by the National Institutes of Health (NIH)/IMR (grant number NMRR 17-1064-36200). This microarray data is however available from the SNP upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by High Impact Research Support Fund (HIRSF) grant (grant code STG-000145) from Monash University Malaysia\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBrown, N. 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Cells 8, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cells8050497\u003c/span\u003e\u003cspan address=\"10.3390/cells8050497\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cell invasion, cell migration, miRNA, long-ncRNA, glioblastoma, actin","lastPublishedDoi":"10.21203/rs.3.rs-3831522/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3831522/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe role of long non-coding RNAs (lncRNAs) in regulating cell motility in glioblastoma (GBM) remains largely unexplored as compared to other cancers. Our bioinformatic analyses of the microarray data of upregulated lncRNAs predicted the oncogenic role of LINC00221 in GBM cell motility. Quantitative PCR (qPCR) analysis confirmed that LINC00221 was upregulated in different GBM cell lines. While the transient silencing of LINC00221 decreased the A172 cell viability, the cell scratch closure in LN18 and T98G was suppressed. This was followed by reduced cell migration in both LN18 and T98G, but only decreased cell invasion in the latter. Furthermore, Snail and N-cadherin were only decreased in the LINC00221 silenced T98G (T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e) but not LN18. Subsequent bioinformatic analysis predicted miR-34c-5p as a potential miRNA target downstream of LINC00221 and upstream of Snai1, which was confirmed by luciferase reporter assays. To further elucidate the molecular mechanisms involved, we identified the differentially expressed proteins (DEPs) from the proteome profiling of T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and miR-34c-5p mimic transfection (T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e). Further enrichment of the DEPs in both T98G\u003csup\u003esi\u0026thinsp;\u0026minus;\u0026thinsp;LINC00221\u003c/sup\u003e and T98G\u003csup\u003emiR\u0026thinsp;\u0026minus;\u0026thinsp;34c\u0026minus;5p\u003c/sup\u003e unveiled enriched pathways associated with the regulation of actin and cytoskeletal dynamics proteins. In summary, our findings establish the oncogenic role of LINC00221 in promoting both T98G and LN18 cell motility. Although LINC0221 exhibited the involvement of a Snai1-dependant mechanism, which is potentially modulated by miR-34c-5p in T98G, proteomic analysis further supported the regulation cell motility via the actin and cytoskeletal-related proteins following LINC00221 silencing in both GBM cells.\u003c/p\u003e","manuscriptTitle":"Silencing of LINC00221 Suppresses Glioblastoma Cell Migration and Invasion through miR-34c-5p/Snai1 and Regulation of Actin and Cytoskeletal Dynamics Proteins","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-09 06:57:40","doi":"10.21203/rs.3.rs-3831522/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a9aa8db-c1a7-4c4e-ac42-bfed450f4905","owner":[],"postedDate":"January 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":27989359,"name":"Biological sciences/Biochemistry"},{"id":27989360,"name":"Biological sciences/Cancer"},{"id":27989361,"name":"Biological sciences/Cell biology"},{"id":27989362,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2024-02-23T05:50:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-09 06:57:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3831522","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3831522","identity":"rs-3831522","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}