Long Noncoding RNA MALAT1 Promotes Hepatocellular Carcinoma Development by SRSF1 Up-Regulation and Mtor Activation

Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Long noncoding RNA MALAT1 promotes hepatocellular carcinoma development by SRSF1 up-regulation and mTOR activation.

Pushkar Malakar1, Asaf Shilo1, Adi Mogilevsky1, Ilan Stein2, Eli Pikarsky2, Yuval Nevo3, Hadar Benyamini3, Sharona Elgavish3, Xinying Zong4, Kannanganattu V. Prasanth4 and Rotem Karni 1*.

1. Department of Biochemistry and Molecular Biology, 2. Department of Immunology and Cancer Research, 3. Bioinformatics unit, the Institute for Medical Research Israel-Canada, Hebrew University-Hadassah Medical School, Ein Karem, 91120, Jerusalem, Israel. 4. Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.

Keywords: MALAT1, Alternative splicing, SRSF1, Oncogene, S6K1

Running title: MALAT1 is a proto-oncogene in HCC development

*Correspondence should be addressed to R.K. e-mail: ([email protected]) The authors declare no potential conflicts of interest

This work was supported by the Israeli Science Foundation [ISF Grants no' 1290/12 to R. Karni.], P. Malakar. was funded by a postdoctoral fellowship of the Israel Higher Education Committee. Research in K.V. Prasanth's laboratory is supported by grants from American Cancer Society [RSG-11-174-01-RMC] and NIH [GM088252].

Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Abstract Several long noncoding RNAs (lncRNA) are abrogated in cancer but their precise contributions to oncogenesis are still emerging. Here we report that the lncRNA MALAT1 is upregulated in hepatocellular carcinoma (HCC) and acts as a proto-oncogene through Wnt pathway activation and induction of the oncogenic splicing factor SRSF1. Induction of SRSF1 by MALAT1 modulates SRSF1 splicing targets, enhancing the production of anti-apoptotic splicing isoforms and activating the mTOR pathway by modulating the alternative splicing of S6K1. Inhibition of SRSF1 expression or mTOR activity abolishes the oncogenic properties of MALAT1, suggesting that SRSF1 induction and mTOR activation are essential for MALAT1 induced transformation. Our results reveal a mechanism by which lncRNA MALAT1 acts as a proto-oncogene in HCC, modulating oncogenic alternative splicing through SRSF1 upregulation.

Introduction Recent estimations from transcriptome studies suggest that more than 75% of the human genome is transcribed, generating thousands of non-coding RNAs (ncRNAs), which are not translated into proteins (1). This large group of noncoding transcripts contains many small RNAs (2). However, the majority of ncRNAs are longer than 200 nucleotides and are designated as long ncRNAs (lncRNAs) (2). lncRNAs are involved in the regulation of almost every step of gene expression, ranging from chromatin remodelling, transcriptional control, regulation of splicing, mRNA stability, mRNA translation, microRNA processing and protein stability (3). Expression and function of lncRNAs is deregulated in several human diseases, including cancer (4). The first lncRNA discovered with an established role in cancer is Metastasis-Associated Lung Adenocarcinoma Transcript 1 (MALAT1), later referred to as Nuclear-Enriched Abundant Transcript 2 (NEAT2) (5). The MALAT1 transcript is greater than 6 kb in length and is highly abundant (6). MALAT1 sequence is highly conserved among mammals (7). MALAT1 is assumed to play an important role in regulation of gene expression due to its residence in nuclear speckles (8). Localization of MALAT1 in nuclear speckles is dependent on active transcription by RNA-Polymerase II (9).

MALAT1 was shown to modulate the positioning of a member of the SR family of pre-mRNA splicing factors to the transcription site of an inducible transgene array (9). SR proteins are a family of RNA binding proteins that regulate both general and alternative splicing (10). SRSF1, a classic example of a SR protein family member, has been shown to regulate the alternative splicing of various oncogenes and tumor suppressor genes important for tumor progression and maintenance (10). SRSF1 was shown to act as an oncogene by activating the mTORC1 pathway (11). MALAT1 was shown to bind active chromatin sites of many genes and to bind several splicing factors, among them SRSF1. This binding affects both its localization and phosphorylation by the kinase SRPK1, leading to changes in alternative splicing of its splicing targets (12,13). The process of alternative splicing is widely deregulated in various cancers and many tumors express cancer-specific splicing isoforms that are absent or are expressed at different levels in the corresponding normal tissues (14,15). Many of these transcripts encode for oncogenes and tumor suppressor genes (16-18).

In spite of its abundance, MALAT1 is dispensable for viability, and MALAT1 knockout mice do not present any obvious abnormal phenotype (19,20). One report using MALAT1 knockout mice suggested that MALAT1 is not necessary for development but has the potential to regulate the expression of nearby genes (21). In the past few years, studies have found that MALAT1 is up- regulated in several cancers, and its knockdown inhibited tumorigenesis (22,23). Several reports showed that MALAT1 regulates the Wnt-β-catenin pathway by enhancing nuclear β-catenin levels and elevating c-Myc expression (24,25). It was shown recently that MALAT1 regulates the differentiation and metastasis of mammary tumors (26). However, neither a direct causative role for MALAT1 in early steps of transformation and tumorigenesis, nor the mechanism by which MALAT1 causes cellular transformation has been shown to date.

In this study, we show that MALAT1 is up-regulated in hepatocellular carcinoma (HCC), and acts as a proto-oncogene to induce transformation and tumorigenesis of liver progenitor cells by Wnt pathway activation, SRSF1 up-regulation and mTORC1 activation.

Materials and Methods

Animal Care

All animal experiments were performed in accordance with the guidelines of the Hebrew University committee for the use of animals for research and under the approval of the Hebrew University Ethics committee. Veterinary care was provided to all animals by the Hebrew University animal care facility staff in accord with AAALAC standard procedures and as approved by the Hebrew University Ethics committee.

Cell Culture

Liver progenitor cells from embryonic day 18 fetal livers from TP53-/- mice were isolated and immortalized with MSCV-based retroviruses expressing MYC-IRES-GFP as previously described to generate TP53-/- hepatocytes overexpressing c-MYC (PHM-1) cells (27,28). PHM- 1, FLC4 and BWTG-3 cells were grown in DMEM supplemented with 10% FCS, 0.1mg/ml penicillin and 0.1mg/ml streptomycin. All cell lines have been tested and authenticated using

STR loci (TH01, TPOX, vWA, CSF1PO, D16S539, D7S820, D13S317 and D5S818) plus Amelogenin for gender identification for human cell line authentication by the biosynthesis DNA Identity Testing Centre.

Stable cell lines pCD513B1 empty (System Biosciences) and pCD513B1-hMALAT1 lentiviruses were prepared using the manufacturer's instructions. These viruses were used to infect PHM-1 cells. Cells were selected by the addition of puromycin (2µg/ml) for 72-96 hours.In the case of infection with MLP-puro-shRNA viruses, cells were selected with puromycin (2µg/ml) for 96 hours.

Growth Curve

PHM-1, FLC4 and BWTG-3 cells were infected with the indicated lentiviruses. After selection 500 cells (PHM-1) or 2000 cells (FLC4 and BWTG-3) were seeded in 96 well plates. Cells were stained with 1% methylene blue in 0.1M borate buffer and fixed. After treatment with 0.1N HCl the absorbance (655nM) of the acid extracted stain was measured using a plate reader (Bio-Rad)

siRNA treatment

Double stranded siRNAs (Sigma) were used to deplete MALAT1 from cells at specific concentrations. siRNA against Luciferase (Dharmacon Thermoscientific, USA) or siRNA universal negative control (Sigma) was used as a control at specified concentrations. Lipofectamine 2000 reagent was used for transfection as per the manufacturer’s instructions (Invitrogen, USA).

RT-PCR

Total RNA was extracted with TRI Reagent (Sigma) and 1 µg of total RNA was reverse transcribed using M-MLV reverse transcriptase (Promega). PCR was performed on 1/10 volume (2µl) of the cDNA using PCR Mix (Kapa Biosystem.)

Quantitative RT-PCR

Total RNA was extracted with TRI Reagent (Sigma), and 1 µg of total RNA was reverse transcribed using M-MLV reverse transcriptase (Promega) after DNASE treatment (Promega). qPCR was performed on the cDNA using SYBR green mix (Roche) and CFX96 (Bio-rad) real time PCR machine. Primer list is supplied in Table S1.

Immunoblotting

Cells were lysed in Laemmli buffer and analyzed for total protein concentration as described(10). 20 µg of total protein from each cell lysate was separated by SDS-PAGE and transferred on to a PVDF membrane.. Primary antibodies: TCF7L2 EP20334 (1:10000, Abcam), c-MYC Sc-40 (1:1000, Santa Cruz), SRSF1 (AK96 culture supernatant 1:300) (29),GAPDH (1:500, Santa Cruz), α-Tubulin (1:1000, Santa Cruz), β-Catenin (1:2000, Sigma), β-Actin (1:2000, Santa Cruz), total S6K1-anti-p70 (1:1000, BD Transduction Laboratories), (phospho-4E-BP1 Thr70 (1:1,000, Cell Signaling Technologies), (4E-BP1 (1:1,000, Cell Signaling Technologies). Secondary antibodies: HRP-conjugated goat anti-mouse, goat anti-rabbit, donkey anti-goat IgG (H+L) (1:10000, Jackson Laboratories).

Colony Formation Assay

Cells were seeded in 6 well plates (1000 cells/well) and grown for 10 days. . After fixation with 2.5% glutaraldehyde the plates were washed three times. Fixed cells were then stained with methylene blue solution (1% methylene blue in 0.1M borate buffer, pH 8.5) for 60 minutes at room temperature. Plates were photographed after extensive washing and air drying.

Anisomycin Mediated Cell Death Assay

Following transduction and selection, cells were seeded in six well plates (2 × 105 cells/well). 24 hours later, cells were incubated with 1 µM anisomycin in DMEM medium containing 0.1% serum for 24 hours. Medium and PBS washes were collected together with trypsinized cells from

each well into 15ml tubes and centrifuged at 1500 RPM for 5 min. Cells were washed with PBS and resuspended in 50 µl of HEPES Buffer. 10 µl of the cell suspension was mixed with 10 µl of 4% trypan blue solution and live/dead cells were counted using a Bio-Rad TC-10 automated cell counter.

Anchorage-independent growth

Colony formation in soft agar was assayed as described (10). After 14 to 21 days, colonies from 10 different fields in each of 2 wells were counted for each treatment and the average number of colonies per well was calculated. The colonies were stained as described (10) and photographed under a light microscope at ×10 magnification.

Tumorigenesis assays in nude mice

PHM-1 cells overexpressing MALAT1 or an empty vector, with and without SRSF1 shRNA expression, were injected (3 × 106 cells/ site in 200 μl of PBS) subcutaneously into each rear flank of NOD-SCID mice using a 26-gauge needle. Tumor growth was monitored twice a week. Tumor volume was calculated using the formula, tumor volume= (length x width2)/2 (10).

Nuclear and cytoplasmic extract preparation.

Cytoplasmic and nuclear extracts were prepared as described (30). After trypsinization the cells were washed in cold PBS and spun down. The pellet was resuspended in CE buffer (10 mM

HEPES pH7.9, 1.5 mM MgCl2, 10 mM KCl containing protease inhibitor) and incubated on ice for 5 minutes. An equal amount of CE buffer containing 0.2% NP40 was added to the cell suspension, incubated for 5 minutes on ice, and centrifuged for 3 minutes at 6500 rpm at 40C. The supernatant is the cytoplasmic extract. The pellet was resuspended in NE buffer (20 mM

HEPES pH7.9, 1.5 mM MgCl2, 0.42 M NaCl, 0.2 mM EDTA, 25% glycerol containing protease inhibitors) and vortexed at full speed for 1 minute. The nuclear extract suspension underwent three cycles of freeze (-800C for 15 minutes) and thaw (for 1 minute at 370C). Between each cycle of freeze /thaw the suspension was vortexed for 1 minute at full speed. The suspension was then spun at full speed for 15 minutes at 40C. The supernatant is the nuclear extract.

Oligonucleotide pull down assay. Oligonucleotide pull down assay was performed as described (30). In brief, 30 µl of 1:1 bead slurry was washed 3 times in 1ml of GFB 100, blocked for 30 minutes at 4 0C in 1 ml GFB 100 containing heparin and then washed in 1ml of GFB 100. The binding reaction mixture with 5 µl of 10pmol/ µl biotinylated SRSF1 ESE oligo derived from within the 3’UTR of SRSF1 transcript (see the sequence in Table S1) and 20 µl of nuclear extract was incubated at 30 0C for 30 minutes on a rotating shaker. The streptavidin bead suspension was added to the binding reaction mixture containing biotinylated RNA oligo and nuclear extracts and incubated for 2 hours with rotation at 4 0C. After incubation, the coupled beads and binding reaction mixture were washed

four times in 500µl of GFB100 containing 4mM MgCl2. The beads were then resuspended in 50 µl of 2X SDS sample buffer and run on SDS–PAGE.

RNA-seq analysis.

RNA from PHM-1 cells transduced with retroviruses encoding for empty vector or MALAT1 was extracted and subjected to RNA-seq using the Ilumina Hi-seq sequencer. ∼70×106 reads at length of 50 bases was generated from each sample.

Trimming and filtering of raw reads

Raw reads (fastq files) were inspected for quality issues with FastQC (v0.11.2, http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). According to the FastQC report, reads were quality-trimmed at both ends, using in-house Perl scripts, with a quality threshold of 32. In short, the scripts use a sliding window of 5 bases from the read's end and trim one base at a time until the average quality of the window passes the given threshold. Following quality- trimming, adapter sequences were removed with cutadapt (version 1.11, http://cutadapt.readthedocs.org/en/stable/), using a minimal overlap of 1 (-O parameter), allowing for read wildcards, and filtering out reads that became shorter than 15 nt (-m parameter). The remaining reads were further filtered to remove very low quality reads, using the fastq_quality_filter program of the FASTX package (version 0.0.14, http://hannonlab.cshl.edu/fastx_toolkit/), with a quality threshold of 20 at 90 percent or more of the read's positions.

Mapping and differential expression analysis

The processed fastq files were mapped to the mouse transcriptome and genome using TopHat (v2.0.14). The genome version was GRCm38, with the human MALAT1 gene added as an additional chromosome. Annotations were taken from Ensembl release 84. Mapping allowed up to 3 mismatches per read, a maximum gap of 5 bases, and a total edit distance of 8 (full command: tophat -G genes.gtf -N 3 --read-gap-length 5 --read-edit-dist 8 --segment-length 20 -- read-realign-edit-dist 3 --no-coverage-search genome processed.fastq). Quantification was done using htseq-count (version 0.6.0, http://www- huber.embl.de/users/anders/HTSeq/doc/count.html). Strand information was set to 'no', and an annotation file that lacked information for genes of type IG, TR, Mt, rRNA, tRNA, miRNA, misc_RNA, scRNA, snRNA, snoRNA, sRNA, scaRNA, piRNA, vaultRNA, ribozyme, artifact and LRG_gene, was used. Normalization and differential expression were done with the DESeq2 package (version 1.12.4). Genes with a sum of counts less than 2 over all samples were filtered out prior to normalization, then dispersion and size factors were calculated. Differential expression was calculated with default parameters. The significance threshold was taken as padj<0.1, testing for a log fold change greater than 0.3 (lfcThreshold parameter to the results method). Several quality control assays, such as counts distributions and principal component analysis, as well as differential expression results, were calculated and visualized in R (version 3.3.1, with packages 'RColorBrewer_1.1-2', 'pheatmap_1.0.8' and 'ggplot2_2.1.0'). Results were then combined with gene details (such as symbol, Entrez accession, etc.) taken from the results of a BioMart query (Ensembl, release 84) to produce the final Excel file.

Gene set enrichment analysis (whole data). Whole differential expression data was subjected to gene set enrichment analysis using GSEA (31) with the corresponding human ortholog gene symbols. Best human orthologs were extracted from Ensembl. GSEA uses all differential expression data (cut-off independent) to determine whether a-priori defined sets of genes show statistically significant, concordant differences between two biological states. Gene sets of the MSigDB database hallmark category were examined (v5.2, October 2016).

Enrichment analysis (top changed genes only). A list of 880 statistically significant differentially expressed genes was subjected to pathway enrichment analysis using QIAGEN’s Ingenuity Pathway Analysis (IPA, QIAGEN Redwood City, www.qiagen.com/ingenuity),

GeneAnalytics (32) and EnrichR (33) as well as functions/diseases enrichment analysis using IPAA list of 880 genes whose expression shown the most intensive change was subjected to enrichment analysis using IPA, GeneAnalytics (32) and EnrichR (33).

Network analysis. To build and visualize a functional network of the enriched functions in differentially expressed genes, the ClueGO application for Cytoscape was applied to genes that were significantly differentially expressed. ClueGO visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. Enrichments of pathways (released November 2016) were analysed.

Results lncRNA MALAT1 is up-regulated in hepatocellular carcinoma. To examine if MALAT1 plays a role in liver cancer development, we analyzed expression data from normal human livers and liver cancer samples (HCC and liver cell dysplasia) (https://www/oncomine.org). Comparison of normal liver samples to cancer liver samples showed elevated levels of MALAT1 transcripts in HCC and liver cell dysplasia samples (Fig. 1A-B). Next, we compared tumor liver samples and adjacent liver parenchyma from an inflammation–induced liver cancer mouse model, Mdr2-/- Mice (34,35). We found elevated levels of MALAT1 RNA in most of the liver tumor samples compared to the adjacent inflamed liver parenchyma from Mdr2-/- mice (Fig. 1C-D).

MALAT1 expression enhances proliferation and survival of hepatocytes.

In order to examine the oncogenic potential of MALAT1 in hepatocytes, we transduced TP53-/- mouse embryonic progenitor hepatocytes overexpressing c-MYC (PHM-1 cells) with lentiviruses encoding either hMALAT1 or an empty vector (Fig. 2A). We found that overexpression of MALAT1, increased the proliferative capacity of the transduced PHM-1 cells as determined by staining cells with methylene blue and measuring the absorbance of the extracted dye relative to that of the first day of the growth curve (Fig. 2B). Overexpression of MALAT1 also increased survival of PHM-1 cells seeded sparsely in a clonogenic assay, suggesting that MALAT1 protects cells subjected to low density stress conditions (Fig. 2C). To enumerate the possible role of MALAT1 in response to cellular stress, we treated transduced PHM-1 cells with anisomycin under low (0.1%) serum conditions. Overexpression of MALAT1 decreased apoptotic cell death in response to anisomycin treatment as measured by trypan blue

exclusion and Caspase-3 cleavage (Fig. 2D). To investigate the role of MALAT1 in tumor maintenance, we knocked down its expression using siRNAs in two HCC cell lines (to eliminate cell type specific effects): a human HCC cell line (FLC4), and mouse HCC cells (BWTG-3). MALAT1 knockdown in FLC4 cells (Fig. 2E) resulted in reduced proliferative capacity (Fig. 2F), reduced colony survival (Fig. 2G) and reduced anchorage-independent growth (Fig. 2H). Knockdown of MALAT1 also reduced proliferation capacity in the HCC cell line BWTG-3 and PHM-1 cells (Fig. S1A-D).

MALAT1 expression transforms hepatocytes and is essential for HCC tumor maintenance.

To determine whether MALAT1 is required for tumor maintenance, we examined the effect of knockdown of MALAT1 on transformation of HCC cells. We found that MALAT1 knockdown by siRNA inhibited colony formation in soft agar of mouse HCC cells (BWTG-3) (Fig. 3A-B) and PHM-1 cells (Figs. S1A, 3C). Overexpression of MALAT1 was able to transform mouse PHM-1 cells enabling them to form colonies on soft agar (Figs. 2A, 3D). To further investigate whether MALAT1 overexpression can render cells tumorigenic in vivo, we injected PHM-1 cells expressing either MALAT1 or the empty vector subcutaneously into NOD-SCID mice. We found that PHM-1 cells overexpressing MALAT1 formed large tumors in mice when compared to cells expressing empty vector (Fig. 3E-F). These results suggest that MALAT1 is a cellular proto-oncogene in hepatocytes and can act as an oncogenic driver in HCC development.

MALAT1 regulates the expression of the oncogenic splicing factor SRSF1

One of the proteins known to bind MALAT1 is the splicing factor SRSF1. Splicing factor SRSF1 is upregulated in various types of cancer, acts as a proto-oncogene in HCC (36) and transforms liver progenitor cells when up-regulated (28). Overexpression of MALAT1 in PHM-1 cells up- regulated the expression of SRSF1. SRSF1 up-regulation occurred at both the mRNA and protein level (Fig. 4A-C). Knockdown of MALAT1, in PHM-1 cells, resulted in the reduction of SRSF1 protein (Fig. 4D-E). In order to examine the functional activity of SRSF1 in MALAT1 overexpressing cells, we measured binding of nuclear SRSF1 to an RNA oligonucleotide containing the consensus ESE motif taken from the SRSF1 3’UTR region (37), through direct RNA affinity purification (Fig. 4F). Cytoplasmic and nuclear extracts were prepared from PHM- 1 empty and PHM-1 MALAT1 cells overexpressing SRSF1. The purity of the extracts was examined with known cytoplasmic and nuclear protein (Fig. S1E). Nuclear extracts of PHM-1

cells overexpressing MALAT1 and transfected with T7-SRSF1 had more binding of SRSF1 as compared to PHM-1 cells with empty vector transfected with T7-SRSF1 (Fig. 4G). This result suggests that there are higher amounts of active SRSF1 in the nucleus of PHM-1 cell overexpressing MALAT1.

MALAT1 upregulation induces oncogenic alternative splicing events regulated by SRSF1

In order to establish if SRSF1 up-regulation induced by MALAT1 overexpression affects alternative splicing events known to be regulated by SRSF1, we examined splicing patterns of genes with roles in transformation and apoptosis. We focused on the splicing pattern of three previously reported SRSF1 target genes: Pro-apoptotic Bcl-2 family member BIM, tumor suppressor BIN1, and the transcription factor TEAD-1 (TEF-1) (38-40). We found that PHM-1 cells overexpressing MALAT1 increased expression of the ES (extra short) isoform of BIM (Figs. 5A, S2A), which lacks exon 4, the BH3 domain. The ES isoform of BIM has been shown to behave in a similar fashion to that of the γ1 isoform, as an anti-apoptotic protein (28). Transient MALAT1 knockdown by siRNAs in PHM-1 MALAT1 cells resulted in reduced expression of the ES isoform of BIM (Figs. 5B, S2A). The BIN1 protein interacts with c-MYC and suppresses its oncogenic activity (39). Inclusion of exon 12A in the BIN1 transcript abolishes its tumor suppressor activity while inclusion of exon 13 is required for the tumor suppressor activity of BIN1 (39). It was shown previously that SRSF1 overexpression results in increased inclusion of exon12A of BIN1 in human, mouse and rat cells (10,28). In agreement with these findings, we found that in PHM-1 cells overexpressing MALAT1, inclusion of exon 12A was increased compared to cells containing empty vector control (Figs. 5A, S2A). Alternatively, transient MALAT1 knockdown by siRNA in PHM-1 MALAT1 cells induced skipping of exon 12A (Figs. 5B, S2A). Finally, we examined the alternative splicing of TEAD1. SRSF1 affects the alternative splicing of the pre-mRNA of the transcription factor TEAD1 by promoting the inclusion of exon 5, resulting in more proliferative activity (10,28). Consistent with this, we found increased inclusion of exon 5 of TEAD1 in PHM-1 cells overexpressing MALAT1 (Figs. 5A, S2A). In contrast, transient MALAT1 knockdown by siRNA in PHM-1 cells overexpressing MALAT1 induced skipping of exon 5 of TEAD1 (Figs. 5B, S2A).

MALAT1 up-regulation activates the mTOR pathway

We have shown previously that SRSF1 regulates alternative splicing of RPS6KB1, increasing the expression of a shorter spliced variant of S6K1, called Iso-2 (10). Iso-2 possesses oncogenic activity, binds mTOR and activates the mTOR complex 1 (mTORC1) (10,41). However, SRSF1 can activates mTOR and protein translation also by alternative splicing-independent mechanisms (42,43). We therefore examined splicing pattern of S6K1 in MALAT1-overexpressing cells. PHM-1 cells overexpressing MALAT1 showed increased Iso-2/Iso-1 ratios at the mRNA level (Fig. 5C) and elevated levels of the Iso-2 isoform at the protein level (Fig. S2B). Transient knockdown of MALAT1 by siRNA in PHM-1 and PHM-1 overexpressing MALAT1 cells resulted in a decreased ratio of Iso2/Iso1 at the mRNA and protein levels (Figs. 5D, S2B). The S6K1 short isoform has been shown to bind and activate mTORC1, resulting in enhanced 4E- BP1 phosphorylation (41). We therefore examined the phosphorylation status of 4E-BP1 in PHM-1 cells overexpressing MALAT1. These cells had increased phosphorylation of 4E-BP1 (Fig. 5E). Knockdown of MALAT1 resulted in decreased phosphorylation of 4E-BP1 in PHM-1 overexpressing MALAT1 cells (Fig. 5F). Cumulatively, these findings suggest that MALAT1 can activate the mTORC1 pathway.

MALAT1 activates a transcriptional program resulting in activation of the Wnt and ERBB3-4 signaling pathways and increased expression of c-MYC and cyclin D1

The results presented above suggest that MALAT1 regulates the expression and activity of SRSF1. SRSF1 was shown to be a direct transcriptional target of c-MYC (44). c-MYC is the direct transcriptional target of the Wnt-β-catenin pathway. To better understand the transcriptional program induced by MALAT1 in hepatocytes, we performed RNA-seq analysis on PHM-1 cells overexpressing MALAT1 compared to cells with empty vector (Fig. S3, Table S2). We identified by two different bioinformatic tools (IPA and GeneAnalytics)(31-33) activation of the Wnt pathway (Figs. S4-S6, Table S3). We identified up-regulation of several activators upstream of the Wnt pathway (e.g. both ligands - Wnt2, Wnt10a - as well as the receptor - Frizzled - that activate the pathway) (Figs S4-S6). In addition, several suppressors of the pathway were down-regulated (e.g. DKK, TGFβ, TGFβR) (Fig. S4B). Both c-Myc, and Cyclin D1 are known transcriptional targets of the Wnt pathway and contribute to proliferation and oncogenesis. Moreover, c-Myc is a transcriptional activator of SRSF1 (44). Thus, we examined the expression of c-MYC and Cyclin D1 upon MALAT1 overexpression. In PHM-1 cells, overexpression of MALAT1 resulted in increased expression of c-MYC and Cyclin D1, at

both the mRNA and protein levels while MALAT1 knockdown reduced their levels (Figs. 6A-B, S7). A hallmark of Wnt pathway activation is translocation of β-catenin into the nucleus (45,46). Overexpression of MALAT1 was shown to increase the nuclear localization of β-catenin in LoVo cells (24). We therefore examined β-catenin levels in cytoplasmic and nuclear extracts upon MALAT1 overexpression. Overexpression of MALAT1 in PHM-1 cells resulted in increased nuclear β-catenin (Fig. 6C). These result suggests that TCF/LEF/β-catenin transcriptional activity is enhanced in these cells. Knockdown of MALAT1 by siRNA, in PHM- 1, BWTG-3, FLC4 and PHM-1 MALAT1 cells, resulted in reduced expression of c-MYC protein (Figs. S7A) as well as cyclin D1 expression (Fig. 6D-E). Since SRSF1 is a transcriptional target of c-Myc, these results can explain SRSF1 up-regulation in cells overexpressing MALAT1. Another transcriptional target of the Wnt pathway is the receptor tyrosine kinase ERBB3 (47). Indeed, the RNA-seq analysis showed increased expression of ERBB3 in cells expressing MALAT1, which was also validated by Q-RT-PCR (Figs. S4B, S5B, S6A). In addition, ERBB4, another member of the EGFR family was induced by MALAT1 (Figs. S4B, S5B) suggesting that the ERBB3-ERBB4 signaling pathway is activated by MALAT1. Cells overexpressing MALAT1 also showed hallmarks of mTOR pathway activation based on gene expression patterns (Fig. S6C).

SRSF1 up-regulation and mTOR activation are essential for MALAT1 transformation and tumorigenesis

To assess the importance of mTOR activation for MALAT1 mediated transformation, we used the mTOR inhibitor rapamycin. Rapamycin blocks mTORC1 activity (48). The oncogenic properties of PHM-1 expressing MALAT1 cells were abolished in the presence of rapamycin as seen by decreased survival in colony survival assay (Fig. 7A), reduced formation of colonies on soft agar (Fig. 7B) and reduced proliferative capacity (Fig. 7C). These results demonstrate that cells overexpressing MALAT1 are highly sensitive to rapamycin and mTOR activation is essential for MALAT1-induced transformation.

To examine whether SRSF1 up-regulation mediates MALAT1-induced transformation, we knocked down the expression of SRSF1 in PHM-1 cells overexpressing human MALAT1 (Fig. 7D). Stable knockdown of SRSF1 in these cells resulted in reduced proliferative capacity (Fig.

7E) and decreased survival when sparsely seeded for colony survival (Fig. S8A). To test whether MALAT1 induced tumorigenesis can be inhibited by SRSF1 knockdown in vivo, we injected NOD-SCID mice with PHM-1 cells overexpressing MALAT1 with or without SRSF1 knockdown. Knockdown of SRSF1 greatly inhibited tumor growth in vivo (Fig. 7F,G). The above observations suggest that SRSF1 is required for the tumorigenic effects induced by MALAT1 and functions downstream to MALAT1. To examine if MALAT1 oncogenic activity is specifically sensitive to SRSF1 down-regulation, we transformed PHM-1 cells by oncogenic Ras and silenced SRSF1. We found that while SRSF1 knockdown did not affect colony survival and proliferation (Fig. S8B), it did inhibit, to some extent, colony formation in soft agar (Fig. S8C-D). These results suggest that MALAT1 oncogenic activity is highly sensitive to inhibition of SRSF1, more so than other oncogenes (such as Ras), and that SRSF1 is essential to some of the oncogenic properties of MALAT1 (e.g. proliferation/survival as determined by the clonogenic assay) while other properties (motility/invasiveness) might also be mediated by additional targets. In order to determine if SRSF1 regulation of alternative splicing also functions downstream to MALAT1, we knocked down MALAT1 by siRNA in PHM-1 cells overexpressing SRSF1 (Fig. S8E). We did not observe any significant change in the splicing patterns of BIM, BIN-1 or TEAD-1, suggesting that SRSF1 regulates splicing downstream to MALAT1 and not vice versa (Fig. S8F).

Discussion

In this study we show that up-regulation of the lncRNA MALAT1 can act as an oncogenic driver in HCC, and that this activity is mediated by the induction of the oncogenic splicing factor SRSF1. SRSF1 is known to affect alternative splicing of genes involved in transformation and apoptosis and to activate the mTOR pathway. Here, we present evidence that SRSF1 up- regulation and mTOR activation are essential for MALAT1 induced transformation and tumorigenesis, suggesting a mechanism by which lncRNA alters alternative splicing leading to activation of a pro-oncogenic signal transduction pathway.

MALAT1 is up-regulated and acts as a proto-oncogene in hepatocellular carcinoma.

Here, we show that not only is MALAT1 mRNA expression high in different forms of human liver cancer, but also in liver tumors from a mouse model of hepatic carcinogenesis (Fig. 1). We

further show that overexpression of MALAT1 in PHM-1 cells resulted in transformation of these cells in vitro and in vivo (Figs. 2A-D, 3D-F). In contrast, knockdown of MALAT1 in cells resulted in reduced proliferative capacity and decreased capacity to form colonies on soft agar (Figs. 2E-H, S1, 3A-C). Our results suggest that MALAT1 acts as an oncogene. Indeed, recent results show that the MALAT1 gene is mutated in liver and breast cancers, and functions as an oncogene in breast cancer as well (49-51)

MALAT1 induces SRSF1 up-regulation activating a pro-oncogenic alternative splicing program.

Our results suggest that the oncogenic potential of MALAT1 could be in part attributed to increased activity of the oncogenic splicing factor SRSF1 (Fig. 4). The role of SRSF1 as an alternative splicing factor strongly suggests that MALAT1 oncogenic activity might be mediated by SRSF1 dependent alternative splicing changes. We expect that it is not a single splicing event, but rather the cumulative effect of a set of isoforms, which drives the transformation process. We therefore investigated the effects of MALAT1 overexpression or knockdown on alternative splicing of some of the well-established SRSF1 targets that are known to be involved in transformation and apoptosis. Our results suggest that MALAT1 activates an alternative splicing program that enhances the anti-apoptotic isoforms of genes, such as BIM, as well as the oncogenic isoforms of genes, such as S6K1 and TEAD-1, which contribute to transformation (Fig. 5A-B).

The Ras-MAPK and PI3K-mTOR pathways are deregulated in many cancers, contributing to the establishment and maintenance of the transformed phenotype (52,53). We investigated whether MALAT1 can modulate the mTOR-signalling pathway. We found that alternative splicing of S6K1, a downstream component of this pathway, is deregulated upon MALAT1 overexpression, leading to more expression of the short S6K1 isoform, Iso2 (41) (Figs. 5C, S2B). It was also shown that the short S6K1 isoform binds and activates mTORC1 resulting in increased phosphorylation of 4E-BP1 (11,41). SRSF1 was shown to be present in a complex with mTOR and to increase 4E-BP1 phosphorylation in translational extracts (42). SRSF1 also affects RNA processing steps other than splicing that can attribute to its oncogenic activity. It enhances mRNA transport (54), and also directly affects translation of approximately 1,500 transcripts, some of which belong to tumor suppressors and oncogenes regulating cell cycle and correct

chromosomal segregation (43). We observed more phosphorylation of 4EBP1 in MALAT1 overexpressing cells, suggesting activation of the mTOR pathway (Fig. 5E). Moreover, the RNA-seq analysis we performed showed a gene expression pattern which suggests mTOR pathway activation (Fig. S5C). Taken together, these results point to the deregulation of the mTOR pathway, as a result of increased SRSF1 activity, to be one of the major mechanisms by which MALAT1 exerts its oncogenic properties.

MALAT1 activates SRSF1 and mTOR through a transcriptional program leading to Wnt and ERBB3-4 pathway activation.

SRSF1 was shown to be a direct transcriptional target of c-MYC (44). c-MYC is the direct transcriptional target of the Wnt-β-catenin pathway. To better understand the transcriptional program induced by MALAT1 in hepatocytes, we performed RNA-seq analysis on PHM-1 cells overexpressing MALAT1. Our analysis revealed that MALAT1 induced upstream activators of the Wnt pathway (e.g. both ligands - Wnt2, Wnt10a - as well as the receptor - Frizzled - that activates the pathway). In addition, several suppressors of the pathway were down-regulated (e.g. DKK, TGFb, TGFbR) (Figs. S4-S6). These findings can explain why beta catenin translocated to the nucleus and activated c-myc and cyclin D1 upon MALAT1 overexpression (Fig. 6). The increased expression of c-MYC by MALAT1 overexpressing PHM-1 cells is in agreement with earlier studies (24,25). Interestingly, one of the transcriptional targets of the Wnt pathway is the tyrosine kinase receptor ERBB3 (47). Both ERBB3 and ERBB4 expression was induced by MALAT1 (Figs. S4B, S5B, S6) suggesting that MALAT1 oncogenic activity might also be attributed to enhanced EGFR family signaling. Consistent with this, ERBB3 expression is up- regulated in a subset of HCC tumors correlating with poor prognosis (55).

SRSF1 up-regulation and activation of the mTOR pathway is essential for MALAT1- mediated transformation

To examine the importance of mTOR activation for MALAT1 mediated transformation, we blocked mTOR activity using the mTOR specific inhibitor rapamycin. Indeed, we found that rapamycin fully inhibited the oncogenic properties of MALAT1 overexpressing cells (Fig. 7A- C). This result suggests that mTOR activation is essential for MALAT1-mediated transformation. Activation of the mTOR pathway in various tumors has been reported in many studies (52). Rapamycin and its analogs are extremely selective for mTOR and are already in

clinical use for treating cancers and have been shown to have antitumor activity (48). MALAT1 transformed cells proved to be extremely sensitive to mTOR inhibition raising the possibility that clinical tumors with MALAT1 upregulation can be targeted with mTOR inhibitors. This finding may pave the way for better diagnosis and treatment of cancers with MALAT1 overexpression.

Summary

Taken together, our data suggests that MALAT1 acts as an oncogene in the context of hepatocellular carcinoma. Our proposed model of how MALAT1 acts as an oncogene is presented in a scheme (Fig. 7H). Overexpression of MALAT1 activates the Wnt pathway, inducing c-myc and cyclin D1. c-Myc activates the transcription of SRSF1 resulting in the modulation of alternative splicing of key target genes known to play an important role in cancer progression and maintenance. Modulation of the alternative splicing of S6K1, generates the oncogenic splicing isoform Iso2, promotes activation of the mTOR pathway, leading to enhanced 4E-BP1 phosphorylation. Alternatively, SRSF1 directly activates mTOR. Our data suggests that the mTOR pathway is necessary for the oncogenic potential of MALAT1 with SRSF1 being an important mediator. These results suggest that downregulation of MALAT1 levels or inhibition of mTOR, in tumors where MALAT1 is up-regulated, should be considered as a new strategy for HCC therapy.

Acknowledgements

The authors wish to acknowledge Drs. Zahava Kluger, and Rami Aqeilan for comments on the manuscript. References

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FIGURE LEGENDS

Figure 1. Elevated MALAT1 expression in hepatocellular carcinoma, liver cell dysplasia and mouse liver tumors.

A, Box plot representation of MALAT1 RNA levels in normal liver (n=10) and hepatocellular carcinoma (n=35) samples. P=1.38 E-6. T-test=6.279. Fold change=3.233. B, Box blot representation of MALAT1 RNA levels in normal liver (n=10), and liver cell dysplasia (n=17) samples. P=2.59 E-6. T-test=6.284. Fold change=3.170. Analysis is based on RNA-Seq data from Oncomine database (https: www.oncomine.org).

C, Q-RT-PCR of MALAT1 expression using RNA isolated from 5 adjacent inflamed liver parenchyma and 20 tumor liver samples from Mdr2-/- mice. All samples were normalized to tubulin mRNA levels. Error bars represents SD of three technical repeats. Number indicates sample number. D, Average value of MALAT1 expression level from (C). Tubulin was used for normalization. ** P=0.0084.

Figure 2. Modulation of MALAT1 expression affects proliferation, survival and anchorage- independent growth.

A, Q-RT-PCR of MALAT1 expression using RNA from PHM-1 cells transduced with lentiviruses encoding either full length human MALAT1 or an empty vector. Relative expression was normalized to actin. B, Proliferation assay of cells described in (A). The error bars represents the SD from 6 repeats. C, Colony survival assay of cells described in (A). D, Trypan blue exclusion assay of cells described in (A). Bottom panel: Western blot of cleaved Caspase-3 in lysates from cells described in (A), as a marker for apoptosis. E, Q-RT-PCR of MALAT1 RNA levels after knockdown of MALAT1 in FLC4 cells by siRNA (siMALAT1). siRNA against luciferase was used as control. Relative expression was normalized to tubulin. F, Proliferation assay of cells described in (E). G, Colony survival assay of cells described in (E). H. Growth in soft agar assay on cells described (E). Graph represents the average and SD of number of colonies /well. n=3.

Figure 3: MALAT1 overexpression induced transformation and tumorigenesis in PHM-1 cells. A, Q-RT-PCR of MALAT1 expression using RNA from mouse HCC cells and BWTG-3 cells after knockdown of MALAT1 by siRNAs (siMALAT1-1,2). siRNA against luciferase was used as control. B, Colony formation in soft agar assay of cells described in (A) Graph shows the average number of colonies/well and SD. n=3. C, Growth in soft agar assay using PHM-1 cells transfected with siRNAs specific for mouse MALAT1 (siMALAT1-1,2) or a control siRNA. Graph represents the average and SD of number of colonies/well. n=3. D, Growth in soft agar assay using PHM-1 cells transduced with the lentiviruses encoding either MALAT1 or an empty vector. Graph represents the average and SD of number of colonies /well. n=3. E, Growth of

tumors after subcutaneously injection of cells (3x106 /site) described in (D) into NOD-SCID mice (n=8). Tumor volume was measured and calculated as described in materials and methods. F, Pictures of representative tumors described in (E).

Figure 4: MALAT1 regulates the expression and function of SRSF1. A, Detection of SRSF1 pre-mRNA by Q-RT-PCR in PHM-1 cells transduced with lentiviruses encoding either MALAT1 or an empty vector. PCR primers were designed to amplify an intron and neighboring exon sequences. B, Detection of SRSF1 protein by Western blotting in cells described in (A). Total β-catenin was used as a loading control. C. Quantification of the average SRSF1 protein levels upon MALAT1 overexpression (B) from three experiments. Empty vector was set as 1. D, Detection of SRSF1 protein in PHM-1 cells transfected with either siControl or siMALAT1 (-1,2) by Western blot. Total β-catenin and β-tubulin were used as loading controls. E. Quantification of the average SRSF1 protein levels upon MALAT1 knockdown (D) from three experiments. Empty vector was set as 1. F, Scheme illustrating pulldown assay using either ESE or SCR biotinylated RNA oligonucleotides. G. Top panel: Input of nuclear extracts of PHM-1 cells transduced with lentiviruses encoding either empty vector or MALAT1 transiently transfected with either pCDNA3 or T7 tagged SRSF1. SRSF1 expression in nuclear extracts was detected by Western blot using anti T7 antibodies. Bottom panel: Western blot of proteins pulled down using a biotinylated RNA oligo containing an ESE motif (described in materials and methods) from nuclear extracts of cells described in (F). Biotinylated SCR oligo was used as a control.

Figure 5: Effect of MALAT1 expression on alternative splicing of endogenous targets of SRSF1. A, RT-PCR of SRSF1 target genes (BIM, BIN-1 and TEAD-1) from RNA extracted from PHM- 1 cells transduced with lentiviruses encoding either MALAT1 or an empty vector. Isoform specific primers were used for RT-PCR. GAPDH was used as a control. B, RT-PCR of SRSF1 target genes from RNA extracted from MALAT1 overexpressing PHM-1 cells transfected with either siLUC or siMALAT1. Splicing patterns were determined using isoform specific primers. Tubulin was used as control. C, Q-RT-PCR of RPSKB1 isoforms in RNA extracted from cells described in (A). Results are expressed as a ratio of Iso2/Iso1 isoform. Expression was normalized to actin. D, Q-RT-PCR of RPS6KB1 isoforms in RNA extracted from cells described in (B). Results are expressed as a ratio of Iso2/Iso1 isoform. Actin was used for normalization.

E, Western blot of phosphorylated and total 4E-BP1 protein in extracts from cells described in (A). GAPDH was used as a loading control. F, Western blot of phosphorylated and total 4E-BP1 protein in extracts from cells described in (B). Tubulin was used as a loading control.

Figure 6: MALAT1 increases nuclear β-catenin and up-regulates the expression of c-MYC and cyclin D1.

A, Q-RT-PCR of c-Myc and cyclin D1 mRNA levels in PHM-1 cells transduced with lentiviruses encoding either MALAT1 or an empty vector. B, Western blot of c-Myc and cyclin D1 in cells described in (A). Tubulin was used as a loading control. C, Western blot of β-catenin in cytoplasmic and nuclear fractions isolated from cells described in (A). Sam68 was used as nuclear specific marker, tubulin as a cytoplasmic specific marker and GAPDH as a loading control. D, Q-RT-PCR of c-Myc and cyclin D1 mRNA levels in BWTG-3 cells following MALAT1 knockdown by siRNAs. E. Western blot of c-Myc and cyclin D1 in cells described in (D). Tubulin and GAPDH were used as a loading controls.

Figure 7: mTOR activity and SRSF1 are required for MALAT1 transformation activity. A, Colony survival assay of PHM-1 cells transduced with lentiviruses encoding either MALAT1 or an empty vector in the presence or absence (DMSO) of rapamycin. B, Quantification of growth in soft agar assay of cells described in (A). Results are presented as relative to PHM-1 cells transduced with empty vector. C, Proliferation assay on cells described in (A). The error bars represent the SD from 6 experimental repeats. D, Western blot of PHM-1 cells transduced with MALAT1 lentivirus co-transduced with lentiviruses containing shRNAs against SRSF1 or an empty vector. β-Actin was used as loading control. E, Proliferation assay of cells described in (D). F, Cells described in (D) were injected (3x106 cells/site) subcutaneously into NOD-SCID mice (n=10). Pictures of representative tumors. G, Tumor volume was measured and calculated as described in materials and methods. H, Scheme summarizing the role of MALAT1 as a potential oncogene in hepatocellular carcinoma. Red lines represent changes or targets through which MALAT1 acts as an oncogene in hepatocellular carcinoma in our experimental studies. Black lines represent alternative pathways or targets through which MALAT1 can function as an oncogene.

A B

Normal liver HCC Normal liver Liver cell dysplasia

C D 60 8

** MALAT1 7

50 6 40 5

30 4

3 20 Relative Expression 2 Relative Expression 10 1

0 0 N1 N3 N5 T2 T4 T6 T8 T10 T12 T14 T16 T18 T20 Normal HCC Liver Samples Livers tumors

Figure 1. Malakar et al. Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

A E 1.2

300 1 250 0.8 200 0.6 150 100 0.4 50 0.2 Relative Expression Relative 0 Relative Expression 0 Empty MALAT1 siLuc siMALAT1

B 60 F 9

50 Empty 8 siLuc 7 Abs. Abs. 40 MALAT 1 6 siMALAT1 30 5 4 20 Relative 3 10 2 1 0 0 0 50 100 Absorbance Relative Time (Hrs) 0 24 48 72 96 C G Time (hrs) # of cells seeded: MALAT1 siRNA:

Empty

D 80 60

40 1000 H 20 750

% % Cell death 0 Empty MALAT1 500

Cl. Casp3 Colonies/well 250

0 β-Catenin siLuc siMALAT1 Figure 2. Malakar et al. Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

A B 1.2

1 1.2

1 0.8 0.8 0.6 0.6 0.4

Colonies/Well 0.4

Relative Expression 0.2 0.2

0 0 siLuc siMALAT1-1 siMALAT1-2 siLuc siMALAT1-1 siMALAT1-2

C D 1000 1.2

800 1 0.8 600 0.6 400 0.4 Colonies/Well Colonies/Well Colonies/well 0.2 200

0 0 siCont. siMALAT1-1siMALAT1-2 Empty MALAT1

E F

1400 ) 3 Empty * 1200 MALAT1 1000 ** MALAT1 800 600 400 ** Empty Tumor Volume (mm Volume Tumor 200 * 0 0 8 16 24 32 40 Days after injection Figure 3. Malakar et al. Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

pre-mRNA of SRSF1 A 5 B C

3 4 2.5

3 SRSF1 2

2 β-Catenin intensity 1.5 1 1 PHM-1 Relative Relative

Relative Expression 0.5

0 0 Empty MALAT1 Empty MALAT1 E D 1.2 1 0.8 SRSF1 0.6 Intensuty 0.4 β-Tubulin 0.2

β-Catenin Relative 0

PHM-1 F G Input Nuc. Extract: Empty MALAT1 Empty MALAT1

SRSF1 +Oligo T7 ESE/SCR Biotin Pulldown Pull down Avidin Oligo: SCR ESE

N.E: Immunoblot T7-SRSF1

Figure 4. Malakar et al. Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

A B

EL EL BIM L S L ES BIM S

+12A+13A ES BIN1 +12A -12A-13 +12A+13A +12A +E5 BIN1 +13 TEAD1 -E5 -12A-13 GAPDH TEAD1 +E5 PHM-1 -E5 Tubulin 2 PHM-1 MALAT1 C RPS6KB1 D 1.2

RPS6KB1 1.5 1

0.8 1 0.6

Short/Long 0.4 0.5 Short/Long 0.2 0 0 Empty MALAT1

E F

p-4EBP1 p-4EBP1

Total 4EBP1 Total 4EBP1

GAPDH Tubulin

Figure 5. Malakar et al. Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

A 2.5 D

1.2 2 c-MYC 1 1.5 0.8 c-MYC 1 0.6 0.5 0.4

Relative Expression 0 0.2 Empty MALAT1 Relative Expression

0 10 Cyclin D1 7.5

5 1.2 1 Cyclin D1 2.5 0.8

Relative Expression 0 0.6 Empty MALAT1 0.4 0.2 0 B Relative Expression

Cyclin D1

c-MYC E β-Catenin c-MYC PHM-1 cells Cyclin D1 Cytoplasm Nucleus Tubulin

C GAPDH

Sam68

β-Catenin

Tubulin

GAPDH

Downloaded from cancerres.aacrjournals.org on SeptemberFigure 30, 2021. ©6 2016. Malakar American Association et al. for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

A B C

3 30

Empty Empty 2.5 25 MALAT1

+DMSO 2 Abs. 20 MALAT1+ Rapa 1.5 15 MALAT1 +DMSO 1 10

0.5 Relative 5 MALAT1 0 +Rapamycin 0

relative # of colonies relative 0 24 48 72 Time (Hrs)

D E 30 Vector F 25 SRSF1 Sh1 Vector SRSF1 20 SRSF1 Sh2 15 β-Actin 10 SRSF1 Sh1

Relative Abs. Abs. Relative 5 SRSF1 sh2 PHM-1 MALAT1 0 0 24 48 72 Time(hrs) G H MALAT1

) 2000 3 Vector Wnt pathway c-MYC SRSF1Sh1 * 1500 activation SRSF1Sh2 ERBB3-4 SRSF1 Signaling, 1000 * Other Cyclin D1 Splicing Targets 500 * Changes

Tumor Volume (mm Volume Tumor 0 RPS6KB1 0 20 40 Apoptosis Days after Injection TEAD1 (BIM, BIN1) mTORC1

Proliferation, survival, tumorigenesis

Figure 7. Malakar et al. Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 19, 2016; DOI: 10.1158/0008-5472.CAN-16-1508 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Long noncoding RNA MALAT1 promotes hepatocellular carcinoma development by SRSF1 up-regulation and mTOR activation

Pushkar Malakar, Asaf Shilo, Adi Mogilavsky, et al.

Cancer Res Published OnlineFirst December 19, 2016.

Updated version Access the most recent version of this article at: doi:10.1158/0008-5472.CAN-16-1508

Supplementary Access the most recent supplemental material at: Material http://cancerres.aacrjournals.org/content/suppl/2016/12/17/0008-5472.CAN-16-1508.DC1

Author Author manuscripts have been peer reviewed and accepted for publication but have not yet been Manuscript edited.

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