HOTAIR is a lncRNA overexpressed in several epithelial cancers and strongly correlated with invasion. This lncRNA was proven a pivotal element of the epithelial-to-mesenchymal transition (EMT), a transdifferentiation process triggering metastasis. Snail, master inducer of EMT, requires HOTAIR to recruit EZH2 on specific epithelial target genes (i.e., HNF4α, E-cadherin, and HNF1α) and cause their repression. Here, we designed a HOTAIR deletion mutant form, named HOTAIR-sbid, including the putative Snail-binding domain but depleted of the EZH2-binding domain. HOTAIR-sbid acted as a dominant negative of the endogenous HOTAIR. In both murine and human tumor cells, HOTAIR-sbid impaired the ability of HOTAIR to bind Snail and, in turn, trigger H3K27me3/EZH2-mediated repression of Snail epithelial target genes. Notably, HOTAIR-sbid expression was proven to reduce cellular motility, invasiveness, anchorage-independent growth, and responsiveness to TGFβ-induced EMT. These data provide evidence on a lncRNA-based strategy to effectively impair the function of a master EMT-transcriptional factor.
This study defines an innovative RNA-based strategy to interfere with a pivotal function of the tumor-related lncRNA HOTAIR, comprising a dominant negative mutant that was computationally designed and that impairs epithelial-to-mesenchymal transition.
Long noncoding (lnc) RNAs act as major players in physiologic regulatory circuitries of the cell and are largely deregulated in different instances of human diseases, such as tumors (1, 2). Specifically, HOTAIR (HOX transcript antisense intergenic RNA; ref. 3) is a well-known lncRNA characterized as a scaffold for the PRC2 subunit EZH2 and able to act in trans to allow the establishment of a repressed chromatin state (4, 5). This model of HOTAIR function was debated by considering promiscuous the specificity of the PRC2-RNA in vitro interactions (6, 7) and even dispensable PRC2 for the HOTAIR-mediated repression of a luciferase reporter (8). However, there is no doubt that HOTAIR is an in vivo hallmark of poor prognosis and it impacts epithelial tumor metastasis, by determining genome-wide PRC2 retargeting (4, 9, 10). Similarly, HOTAIR negative regulation significantly affects cancer cells' migratory and invasive properties (9, 11). HOTAIR-mediated recruitment of PRC2 to chromatin sites may imply more than direct RNA–DNA complementarity (4, 12) and may conceivably involve the interaction with other partners. Notably, evidence was recently provided that, in the epithelial-to-mesenchymal transition (EMT), HOTAIR bridges in specific chromatin sites the interaction between EZH2 and the “master” transcription factor (EMT-TF) Snail1 (Snail). In other words, Snail-repressive function depends on its capacity to convey EZH2 to target sites by means of a direct interaction with HOTAIR (11, 13).
Interestingly, these observations were validated for both murine and human HOTAIR. Of note, EZH2 and Snail proteins are highly conserved in mouse (92.8% and 99.3% sequence identity, respectively) and human HOTAIR shares significant sequence similarity with its mouse homologue (55% identity), which is higher than the average 20% of human lncRNAs conserved in mouse (13). Here, in line with the growing effectiveness of RNA-based therapeutic approaches (14, 15), an innovative anti-EMT strategy has been attempted. By means of an advanced computational tool, catRAPID (16), we estimated the binding potential of HOTAIR to Snail and EZH2 and an HOTAIR deletion mutant form (called HOTAIR-sbid, for Snail binding domain; nucleotides 620–845) was designed to correspond to the putative Snail-binding and depleted of the EZH2-binding domain. catRAPID method allows predictions of RNA–protein interactions through van der Waals, hydrogen bonding, and secondary structure propensities of both protein and RNA sequences and identifies binding partners with an accuracy of 0.78 or higher (16, 17).
HOTAIR-sbid has been functionally challenged in several model of tumoral and nontumoral, murine and human, liver cells; this allowed to test its capacity (i) to interfere with the endogenous HOTAIR in Snail-expressing cells (i.e., BW1J, Hep3B, and HepG2 cell lines) and (ii) to prevent EMT induction by the niche factor TGFβ in hepatocytes (i.e., D3 and E14 cell lines).
HOTAIR-sbid delivery in epithelial cancer cells was challenged as a functional and innovative lncRNA-based strategy in impairing Snail activity. Provided molecular evidence demonstrated that HOTAIR-sbid localizes in the nucleus and competes with endogenous wild-type HOTAIR in Snail binding. This dominant negative function impairs the Snail-mediated recruitment of EZH2 to HNF4α, E-cadherin, and HNF1α promoters, thus preventing their H3K27me3-mediated repression. Functionally, HOTAIR-sbid was also demonstrated to cause a reduction of cell migration, invasion, anchorage-independent growth, and notably, to interfere with the responsiveness of nontumorigenic hepatocytes to the niche factor TGFβ, main inducer of EMT.
Materials and Methods
Protein–RNA interaction prediction
Interactions were predicted using Global Score (17) overall binding propensity and catRAPID fragments (18) identification of the binding sites. catRAPID estimates the binding propensity of protein–RNA pairs by combining secondary structure, hydrogen bonding and van der Waals contributions. As reported in a recent analysis of about half a million of experimentally validated interactions (19), the algorithm is able to separate interacting versus noninteracting pairs with an area under the ROC curve of 0.78. The Global Score and fragments calculations for the HOTAIR (NR_047528.1) and EZH2 (NP_031997.2) interaction are available at http://crg-webservice.s3.amazonaws.com/submissions/2019–12/234094/output/index.html?unlock=09cd6117fe; similarly, predictions for the interaction between HOTAIR and Snail (NP_035557.1) are at http://crg-webservice.s3.amazonaws.com/submissions/2019–12/233811/output/index.html?unlock=7d153ebbb3. The IgG control (BAX56602.1) interaction is calculated at http://crg-webservice.s3.amazonaws.com/submissions/2019–12/234361/output/index.html?unlock=45d56a80fd.
Comparison of human and mouse HOTAIR sequences was performed by the Cluster W algorithm (20). We used CROSSalign (21, 22), an algorithm based on Dynamic Time Warping (DTW), to check and evaluate the structural conservation between RNA molecules. The comparison between mouse (x-axis, NR_047528.1) and human (y-axis, NR_047517.1) HOTAIR structures are available at http://crg-webservice.s3.amazonaws.com/submissions/2019–12/233638/output/index.html?unlock=befdec937d. The lower the structural distance between the two RNAs, the closer is the line to the diagonal, as in the case of the 5′ (nucleotides 1–1000). The significance is assessed as in the original publications (21, 22). Secondary structure prediction of RNA structure and secondary structure propensity were performed by CROSS soft constrains (22, 23).
Nontumorigenic D3 and E14 hepatocytes were grown on collagen I–coated dishes in RPMI1640 supplemented with 10% FBS (Gibco Life Technology), 50 ng/mL epidermal growth factor, 30 ng/mL insulin-like growth factor II (PeproTech Inc.), 10 μg/mL Insulin (Roche), and antibiotics. Where reported, cells were treated with 2.5 ng/mL TGFβ1 (PeproTech Inc.) for 24 hours. Murine BW1J, human Hep3B, and HepG2 cells were grown in DMEM supplemented with 10% FBS (Gibco) and antibiotics. All cell lines were kindly provided by Dr. Alessandra Marchetti (BW1J, Hep3B, and HepG2) and Prof. Laura Amicone from Sapienza University of Rome (Rome, Italy) and used for the experiments three passages after thawing. All cell lines were tested for Mycoplasma using the DAPI staining and the LookOut Mycoplasma PCR Detection Kit (Merck MP0035). All cell lines were authenticated by morphology check, cell proliferation rate evaluation, and species verification by PCR. Bacteria contamination was excluded.
HOTAIR-sbid cloning and cell transfection
Murine HOTAIR sequence (NR_047528.1; nucleotides 620–845), obtained from NCBI (https://www.ncbi.nlm.nih.gov/), was artificially synthesized, verified by sequencing, and cloned (NheI-XbaI) in the pCDNA 3 vector.
BW1J, D3, and E14 cells were transfected with Lipofectamine LTX Reagent (Invitrogen), according to the manufacturer's protocol. Equal amounts of DNA (pCDNA3 empty vector or pCDNA3/HOTAIR-sbid) were used. BW1J cells were analyzed 48 hours posttransfection; D3 and E14 cells were diluted 24 hours posttransfection, treated with TGFβ 30 hours posttransfection, and collected after 24 hours (13). Hep3B and HepG2 cells were transfected with FuGENE HD Transfection Reagent (Promega), according to the manufacturer's protocol, diluted 24 hours posttransfection, and collected at 48 hours posttransfection.
RNA immunoprecipitation (RIP) was performed (24) starting from 1 mg of cleared lysate. Immunoprecipitated RNA was reverse transcribed for reverse transcription and qRT-PCR amplifications. List of primers is reported in Supplementary Table S1. Primary antibodies for IP were: anti-EZH2 39901 (Active motif), anti-Snail AF3639 (R&D Systems), and as negative control Normal Rabbit IgG 12370 (Millipore) or Normal Goat IgG AB-108-C (R&D Systems).
Cells were lysed in 50 mmol/L Tris-HCl (pH 8.0), 150 mmol/L NaCl, 5 mmol/L EGTA (pH 8.0), 50 mM NaF (pH 8.0), 10% glycerol, 1.5 mmol/L MgCl2, 1% Triton X-100 containing protease and phosphatase inhibitors (complete EDTA-free; Roche Applied Science) and protein concentrations determined by Bradford method. One milligram of cell lysates, after preclearing with protein A-sepharose (GE Healthcare), was incubated with 5 μg of anti-EZH2 39901 (Active motif), anti-Snail AF3639 (R&D Systems), and as negative control Normal Rabbit IgG 12370 (Millipore) or Normal Goat IgG AB-108-C (R&D Systems). The complexes were incubated for 3 hours with protein A-sepharose. Immune complexes were washed, eluted, and denatured in Laemmli buffer. Proteins from either cell lysates or immunoprecipitation were resolved on SDS-PAGE and transferred to nitrocellulose membrane (162–0115; Bio-Rad Laboratories). Blots were probed with primary anti-EZH2 05–1319 (Millipore Corp.) or anti-Snail L70G2 (Cell Signaling Technology), and immune complexes were detected with horseradish peroxidase–conjugated species-specific secondary antiserum (Bio-Rad Laboratories), followed by enhanced chemiluminescence reaction (Bio-Rad Laboratories).
RNA extraction, reverse transcription, qPCR
RNAs were extracted by ReliaPrep RNA Tissue Miniprep System (Promega) and reverse transcribed with iScriptTM c-DNA Synthesis Kit (Bio-Rad Laboratories). qRT-PCR analyses were performed according to MIQE guidelines (25). cDNAs were amplified by qPCR reaction using GoTaq qPCR Master Mix (Promega). Relative amounts, obtained with 2(−ΔCt) method, were normalized with respect to the housekeeping gene 18S rRNA (mouse) or L32 (human). For primer details, see Supplementary Table S1.
Protein extraction and Western blot analysis
Cells were lysed in Laemmli buffer; subsequently, the proteins were resolved on SDS-PAGE and transferred to nitrocellulose membrane 0.45 μm (162–0115; Bio-Rad Laboratories). The following primary antibodies were used for immunoblotting: α-HNF4α (SC-6556 Santa Cruz Biotechnology), α-HNF1α (NBP1–33596 Novus Biological), α-E-CADHERIN (610182 BD Transduction Laboratories), α-SNAIL (L70G2, Cell Signaling Technology), α-FIBRONECTIN (F0916 Sigma), α-VIMENTIN (V6389 Sigma), and α-GAPDH (MAB-374 Millipore Corp), used as a loading control. The immune complexes were detected with horseradish peroxidase–conjugated species-specific secondary antiserum α-Rabbit 172–1019 and α-Mouse 170–6516 (Bio-Rad Laboratories), α-Goat 705–036–147 (Jackson ImmunoResearch), then by enhanced chemiluminescence reaction (Bio-Rad Laboratories). Densitometric analysis of protein expression was performed by using the Fiji Image J image processing package.
Paired t test and GraphPad Prism version 8.00 (GraphPad Software; http://www.graphpad.com) were used. A P < 0.05 was considered statistically significant (*, P < 0.05; **, P < 0.01; ***, P < 0.001). Data were obtained from independent experiments and expressed as mean ± SEM
Chromatin immunoprecipitation analysis
Chromatin immunoprecipitation (ChIP) analysis was performed as reported previously (13) by using 5 μg rabbit α-SNAIL (R&D Systems), α-EZH2 (Active motif) or the negative control normal rabbit immunoglobulin (IgG; Millipore), or normal goat immunoglobulin (IgG; R&D Systems). Five nanograms of immunoprecipitated DNA and the relative controls were used as templates for qRT-PCR analysis, performed in triplicate. qPCR analysis of the immunoprecipitated samples and of the negative controls (IgG) were both normalized to total chromatin input and expressed as percentage of Input (% Input). Histone ChIP analysis was performed by using 5 μg of the specific antibody (H3K27me3; 07–449; Millipore) or of the negative control normal rabbit IgG (Millipore), as reported previously (13). The DNA was extracted with phenol–chloroform, precipitated with ethanol, and resuspended in 50 μL of water, then used in the downstream qPCR analyses (primer pairs details are listed in Supplementary Table S2).
Cell lines were maintained in culture medium (as above) until reaching 100% confluence, then shifted to serum-depleted culture medium to inhibit cell proliferation, as in (26); a scratch wound was created on the cell layer using a micropipette tip. Micrographs were taken at time 0, 24, or 48 hours after the scratch. Cell-devoid areas at time 0 and 24 or 48 hours after the scratch were quantified through Fiji Image J image processing package.
For transwell invasion assays, 8-μm pore 24-well cell-culture plates (Corning Inc), coated with type I collagen (0.1 mg/mL; Upstate Biotechnology) were used. Equal numbers of cells were plated in the upper chamber in serum-free medium; in the lower chamber, DMEM medium was supplemented with 20% FBS as a chemoattractant. Cells were fixed with 100% MetOH, stained with Giemsa solution, and manually counted in three random microscopic fields. Three independent experiments for each cell line were performed.
Anchorage-independent growth assay
For colony formation assay, the same number of cells were plated on 6-cm cell-culture dishes in 7.5 mL of soft-agar plating medium. Colonies were evaluated after 2 weeks. The experiments were performed three times.
Bioinformatic prediction of HOTAIR functional domains
A direct interaction between HOTAIR and EZH2 was recently reported (13), in accordance with previous studies indicating the binding between the D1 domain of HOTAIR and PRC2 components (4, 27). In agreement with this evidence, catRAPID Global Score (17) predicts an interaction between murine HOTAIR and EZH2, propensity of 0.98, on a scale ranging from 0 to 1, where 0 indicates no RNA-binding ability and 1 is strong affinity for the interaction. Interestingly, similar binding scores were found for the interaction between murine HOTAIR and Snail, propensity of 0.91, while the negative control (Ig gamma chain C region, IgG) does not show significant interaction propensity. The interactions of EZH2 and Snail are both predicted in the 5′ of HOTAIR, with the EZH2 binding (nucleotides 1–500) slightly upstream Snail (nucleotides 500–1000). Then, by using catRAPID fragments (18), we further investigated on the Snail-binding site of HOTAIR. The algorithm identifies a region (henceforth called HOTAIR-sbid), located at nucleotides 620–845, where the interaction is predicted to occur with high specificity (Fig. 1A). The human HOTAIR lncRNA shares significant sequence similarity (55% identity) with its mouse homologue, which is higher than the average similarity between human and mouse lncRNAs (28). Interestingly, nucleotides 620–845, predicted by catRAPID to interact with Snail, show the highest sequence conservation between human and mouse HOTAIR (Fig. 1B and C).
In agreement with the sequence conservation, CROSSalign (21, 22) predicts that the secondary structures of both human and mouse HOTAIR are highly similar in the region at nucleotides 620–845 (Supplementary Fig. S1), thus providing additional evidence that HOTAIR-sbid has a potential functional role. Indeed, the structure contains several double-stranded regions, which are indicative of protein interactions (Fig. 1D and E; ref, 29).
Overall, these analyses predict the existence of a Snail-interacting HOTAIR domain conserved in mouse and human.
HOTAIR-sbid displays a biochemical dominant negative function on human HOTAIR
On the basis of the above described bioinformatics analysis, a HOTAIR-sbid mutant (nucleotides 620–845), including the putative highly specific Snail-binding sequence and depleted of the EZH2-binding region, was designed, cloned in a plasmid vector (see Materials and Methods), and expressed in the various experimental cell models described below. First, the cellular distribution of HOTAIR-sbid was explored, taking into account that the nuclear localization would be the primary determinant for the expected functions of this mutant, and the cellular fractionation assay provided evidence about the HOTAIR-sbid nuclear enrichment (Supplementary Fig. S2A and S2B). Then, its capacity to form a complex (i) with Snail, (ii) EZH2, and (iii) to compete with endogenous HOTAIR was tested. To discriminate between the endogenous HOTAIR and HOTAIR-sbid, this analysis was performed in human Hep3B sparse cultures. Note that low confluency in vitro may act as a stressful condition triggering hepatoma cells dedifferentiation. Hep3B, indeed, when grown at low density, express both HOTAIR and Snail and, in turn, repress the Snail target genes HNF4α, HNF1α, and E-cadherin, mimicking in vivo mesenchymal, invasive tumor cells. On the other hand, dense hepatoma cultures, as differentiated tumor cells, maintain epithelial markers and repress Snail as well as HOTAIR (Supplementary Fig. S3; ref. 30). Thus, different confluence of this in vitro cell model allows to mimic different steps of epithelial tumorigenesis.
RIP assays, performed on Hep3B extracts from sparse cultures, highlighted that (i) Snail interacts with both endogenous HOTAIR and HOTAIR-sbid (Fig. 2A); (ii) EZH2 interacts with endogenous HOTAIR and not with HOTAIR-sbid (Fig. 2B); and most importantly, (iii) HOTAIR-sbid impairs the interaction of endogenous HOTAIR with Snail (while HOTAIR binding to EZH2 is retained; Fig. 2A and B). Finally, as shown by reciprocal Snail and EZH2 coimmunoprecipitation experiments (Fig. 2C), HOTAIR-sbid impairs the interaction between Snail and EZH2.
Overall, these results indicate as HOTAIR-sbid displays a biochemical dominant negative function on human endogenous HOTAIR.
HOTAIR-sbid displays an in vivo dominant negative function on endogenous HOTAIR
We then aimed at investigating the HOTAIR-sbid functional role in Snail-expressing human and murine cells in which the Snail/HOTAIR/EZH2 complex mediates the repression of HNF4α, HNF1α, and E-cadherin (13). In murine BW1J (Fig. 3A; Supplementary Fig. S4), human Hep3B (Fig. 3B; Supplementary Fig. S4), and HepG2 hepatoma cell lines (Supplementary Fig. S5), HOTAIR-sbid impaired HOTAIR-mediated (i) repression at both RNA and protein levels of epithelial genes previously characterized as Snail-targets (31–33), (ii) both migration ability and (iii) invasion properties (see also Supplementary Fig. S6; assays performed in absence of cellular proliferation; see also, Supplementary Fig. S7), and (iv) anchorage-independent growth. However, the expression of mesenchymal genes (i.e., Snail, Fibronectin and Vimentin) was not significantly modulated nor at RNA or at protein level (Fig. 3A and B; Supplementary Fig. S4).
Mechanistically, ChIP assays on HNF4α, E-cadherin, and HNF1α promoters' Snail-binding sites highlighted a significant decrease of H3K27me3 (Fig. 4A and B). Furthermore, the direct recruitment of both Snail and EZH2 on the same promoter regions was assessed (Fig. 5A and B). While Snail recruitment appeared not affected, EZH2 binding was impaired by HOTAIR-sbid.
Finally, HOTAIR-sbid functional role was tested in two hepatocyte cell models (D3 and E14 cell lines; refs. 34, 35) suitable to study the TGFβ-mediated EMT (in both cellular systems Snail and HOTAIR are induced in response to this niche factor; ref. 13). In both cell lines, HOTAIR-sbid impaired the TGFβ-induced (i) acquisition of the mesenchymal morphology, (ii) repression of epithelial genes (i.e., HNF4α, E-cadherin, and HNF1α), and (iii) acquisition of migratory properties (Fig. 6A–D; Supplementary Fig. S8A–S8D). On the other hand, in line with previous findings achieved by HOTAIR silencing (13), mesenchymal genes (i.e., Snail, Fibronectin, and Vimentin) were found upregulated (Fig. 6B and C; Supplementary Fig. S8B and S8C).
Overall, these results indicate that HOTAIR-sbid (i) displays a dominant negative activity on Snail repressive function and (ii) significantly affects cellular EMT outcome, both in terms of epithelial program repression and migratory abilities (Fig. 7).
The main result of this research was the design and the validation of an RNA molecule with dominant negative function on the HOTAIR-mediated Snail repressive activity (on pivotal epithelial genes, i.e., HNF4α, HNF1α, and E-cadherin), thus allowing the rescue of a more differentiated phenotype of hepatocellular carcinoma cells and the protection from the TGFβ-induced EMT of nontumorigenic hepatocytes. Specifically, we designed the deletion mutant HOTAIR-sbid that competes with the wild-type endogenous HOTAIR form. Our computational approach, previously applied to other lncRNAs, such as SAMMSON (36) and XIST (17), was instrumental in defining the precise binding region for Snail. The mutant was found to impair the assembly of the Snail/HOTAIR/EZH2 functional complex that controls the execution of the Snail-mediated EMT (13).
The EMT reversible transdifferentiation program is essential for the dissemination of malignant epithelial tumors by conferring stem properties, motility, and finally, the ability to metastasize (for review, see ref. 37). HOTAIR acts as a “mesenchymal” gene positively regulated in TGFβ-induced EMT and is epistatic with respect to the EMT-TF Snail by controlling its repressive function in the chromatin context (13). Consistently, this lncRNA promotes tumorigenesis and metastasis formation in different epithelial cancers, including HCC: its increased expression causes the acquisition of metastatic properties while its knockdown impairs migration, invasion ability, and EMT in carcinoma cells (4, 9, 10, 38, 39). Coherently, HOTAIR repression is required in the maintenance of the epithelial differentiated state (11). In HCC, HOTAIR was shown to act also at posttranscriptional level (for review, see ref. 40) by sponging several miRs [e.g., miR-29b, thus enhancing DNMT3b (41) involved in EMT/MET dynamics (42), or miR-23p-3p, targeting the EMT-TF ZEB1 (39, 43)]. All this body of evidence identifies this lncRNA as a suitable candidate in therapies counteracting epithelial tumor progression.
Over the past years, much effort has been concentrated on the setting of RNA-based therapeutics, mimicking, or antagonizing endogenous RNA functions (e.g., the delivery of antisense oligonucleotides for mRNAs, interfering RNAs, in vitro transcribed mRNAs or oligonucleotides aptamers; refs. 14, 15). In particular for the liver, one of the more achievable organs, several siRNA-based approaches, with lower off-target effects than conventional therapies, have been attempted (44); for example, approaches have been challenged by using molecules chemically modified or loaded into lipid particles and nanoparticles (45). Nevertheless, because miRNA-mimics may present drawbacks as multiple targets (summarized in ref. 46), lncRNA-based strategies appear promising.
We validated for the first time, to our knowledge, a dominant negative-based RNA strategy to interfere with a pivotal function of a lncRNA. Specifically, HOTAIR-sbid function was proven dominant-negative against that of the endogenous HOTAIR, in chromatin context of both murine and human cell lines; following our computational design, HOTAIR-sbid was shown to interact with Snail but not with the general chromatin modifier EZH2. More interestingly, the endogenous HOTAIR was shown to maintain the capacity to interact with EZH2, while its ability to bind to Snail was hampered by HOTAIR-sbid; in turn, as highlighted by coimmunoprecipitation analysis, the interaction between Snail and EZH2 was impaired. At the epigenetic level, competition between endogenous HOTAIR and exogenous HOTAIR-sbid, inhibiting the formation of the tripartite complex Snail/HOTAIR/EZH2, causes the decrease of H3K27me3 levels on E-cadherin, HNF1α, and HNF4α promoter regions, and consequently, the rescue of their expression. It should be remembered that HNF1α and HNF4α in hepatic cells control cell differentiation and maintenance of the epithelial phenotype, acting on thousands of target genes, also by repression of the mesenchymal program (33).
Further effort should be made to extend current analysis to a broader number of genes known to be target of HOTAIR (47). Functionally, HOTAIR-sbid alters mouse and human HCC cells behavior: it significantly impairs the migratory capacity, the invasion abilities, and anchorage-independent growth of both cell lines. Most importantly, in two nontumorigenic cellular models, previously validated to respond to TGFβ with an EMT/MET dynamic (i.e., D3 and E14 cell lines; refs. 13, 48), HOTAIR-sbid affects cellular morphology, migration, and repression of master epithelial genes (see Fig. 6; Supplementary Fig. S8). However, HOTAIR-sbid does not impair the TGFβ-mediated mesenchymal gene expression, further suggesting the relevance of the previously reported Snail-independent TGFβ-induced response (49).
Collectively, these data represent an early promise in the control of tumor progression and in the rescue of the epithelial phenotype of cancer cells. Moreover, they open new perspectives for the future analysis of the effectiveness of this strategy also in vivo where HOTAIR-sbid could counteract different aspects of tumor progression. Overall, this innovative approach, based on the use of a dominant negative form of a lncRNA normally expressed in tumor cells, could represent one additional step in the use of highly specific RNA therapeutics.
No disclosures were reported.
C. Battistelli: Conceptualization, data curation, formal analysis, supervision, validation, investigation, visualization, methodology, writing-original draft, writing-review and editing. S. Garbo: Data curation, formal analysis, validation, investigation, methodology. V. Riccioni: Validation, investigation. C. Montaldo: Investigation. L. Santangelo: Conceptualization, formal analysis, investigation. A. Vandelli: Resources, software, formal analysis, methodology. R. Strippoli: Formal analysis, visualization. G.G. Tartaglia: Resources, data curation, software, visualization, methodology, writing-original draft, writing-review and editing. M. Tripodi: Conceptualization, resources, supervision, funding acquisition, visualization, writing-original draft, project administration, writing-review and editing. C. Cicchini: Conceptualization, resources, supervision, funding acquisition, writing-original draft, writing-review and editing.
The authors thank Prof. Andres Ramos (UCL) for critical reading and suggestions. The research leading to these results has been supported by European Research Council (RIBOMYLOME_309545 and ASTRA_855923), the H2020 projects IASIS_727658 and INFORE_825080, the Spanish Ministry of Economy and Competitiveness BFU2017-86970-P as well as the collaboration with Peter St. George-Hyslop financed by the Wellcome Trust (to G.G. Tartgalia); by Associazione Italiana per la Ricerca sul Cancro (AIRC) IG 18843, FFO2019 grant from CIB (Consorzio Italiano per le Biotecnologie), and Sapienza University of Rome RG11916B6A9C42C7 (to M. Tripodi); by Sapienza University of Rome RM116154BE5E14B2 and RM11916B6A80C2CF (to C. Cicchini).
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