AbstractIn recent years, long noncoding RNAs (lncRNAs) have been shown to have critical regulatory roles in cancer biology. However, the contributions of lncRNAs to hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) remain largely unknown. Differentially expressed lncRNAs between HBV-related HCC and paired peritumoral tissues were identified by microarray and validated using quantitative real-time polymerase chain reaction. Liver samples from patients with HBV-related HCC were analyzed for levels of a specific differentially expressed lncRNA High Expression In HCC (termed lncRNA-HEIH); data were compared with survival data using the Kaplan-Meier method and compared between groups by the log-rank test. The effects of lncRNA-HEIH were assessed by silencing and overexpressing the lncRNA in vitro and in vivo. The expression level of lncRNA-HEIH in HBV-related HCC is significantly associated with recurrence and is an independent prognostic factor for survival. We also found that lncRNA-HEIH plays a key role in G0/G1 arrest, and further demonstrated that lncRNA-HEIH was associated with enhancer of zeste homolog 2 (EZH2) and that this association was required for the repression of EZH2 target genes. Conclusions: Together, these results indicate that lncRNA-HEIH is an oncogenic lncRNA that promotes tumor progression and leads us to propose that lncRNAs may serve as key regulatory hubs in HCC progression. (HEPATOLOGY 2011 Hepatocellular carcinoma (HCC) is one of the most common human cancers worldwide, particularly in Southeast Asia and Africa.1 More than 70%-80% of HCC cases occur in high hepatitis B virus (HBV) endemic regions, and 50% of HCC cases worldwide are attributable to chronic infection with HBV. Unfortunately, the 5-year survival rate of HBV-related HCC patients remains poor, and approximately 600,000 HCC patients die each year, despite recent advances in surgical techniques and medical treatment.2 Although previous studies identified many aberrantly expressed protein-coding genes in HCC, novel molecular markers that can help in early diagnosis and risk assessment are still urgently needed.3 It is of paramount importance to understand the relationships between clinical symptoms and molecular changes in HCC for developing new diagnosis and treatment strategies for HCC and improving the prognosis of diagnosed patients. Abbreviations: CCK-8, Cell-Counting Kit-8 assay; ChIP, chromatin immunoprecipitation; cDNA, complementary DNA; 95% CI, 95% confidence interval; EZH2, enhancer of zeste homolog 2; FACS, fluorescence-activated cell sorting; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; HBV, hepatitis B virus; HCC, hepatocellular carcinoma; HR, hazard ratio; IgG, immunoglobulin; IP, immunoprecipitate; lncRNAs, long noncoding RNAs; lncRNA-HEIH, long noncoding RNA High Expression In HCC; mRNA, messenger RNA; miRNA, microRNA; nt, nucleotides; PCNA, proliferating cell nuclear antigen; PRC2, Polycomb Repressive Complex 2; RIP, RNA immunoprecipitation; qRT-PCR, quantitative real-time polymerase chain reaction; SD, standard deviation; shRNA, short-hairpin RNA; siRNA, small-interfering RNA. The human transcriptome comprises not only large numbers of protein-coding messenger RNAs (mRNAs), but also a large set of nonprotein coding transcripts that have structural, regulatory, or unknown functions.4 Although studies of small noncoding RNAs (18-200 nucleotides [nt]) have dominated the field of RNA biology in recent years,5, 6 a surprisingly wide array of cellular functions has also been associated with long noncoding RNAs (lncRNAs).7-9 lncRNAs, tentatively defined as noncoding RNAs more than 200 nt in length, are characterized by the complexity and diversity of their sequences and mechanisms of action. A handful of studies have implicated lncRNAs in a variety of disease states,10, 11 and altered lncRNA levels can result in aberrant expression of gene products that may contribute to cancer biology.12, 13 However, there are only preliminary studies on the role of lncRNAs in HCC,14, 15 and the overall pathophysiological contributions of lncRNAs to HCC remain largely unknown. In this study, we have identified nonoverlapping signatures of a small number of lncRNAs and mRNAs that are up- or down-regulated in HBV-related HCC, compared with paired peritumoral tissues. The effects of lncRNA-HEIH were assessed by silencing and overexpressing it in vitro and in vivo. Patients and MethodsMicroarray and Computational Analysis.Briefly, samples (five HBV-related HCC tissues and five corresponding nontumor tissues; Supporting Table 1) were used to synthesize double-stranded complementary DNA (cDNA), and double-stranded cDNA was labeled and hybridized to the 12×135K LncRNA Expression Microarray (Arraystar, Rockville, MD). After hybridization and washing, processed slides were scanned with the Axon GenePix 4000B microarray scanner (Molecular Devices, Sunnyvale, CA). Raw data were extracted as pair files using NimbleScan software (version 2.5; Roche NimbleGen, Inc., Madison, WI). NimbleScan software's implementation of RMA offers quantile normalization and background correction. Differentially expressed genes were identified through the random variance model.16 A P value was calculated using the paired t-test. The threshold set for up- and down-regulated genes was a fold change >= 2.0 and a P value <= 0.05. The microarray data discussed in this article have been deposited in National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) and are accessible through (GEO) Series accession number GSE27462 (http://www.ncbi.nlm./geo/query/acc.cgi?acc=GSE27462). Hierarchical clustering was performed based on differentially expressed mRNAs and lncRNAs using Cluster_Treeview software from Stanford University (Palo Alto, CA). Coexpression Network.We present gene-coexpression networks to identify interactions among genes.17 Gene-coexpression networks were built according to the normalized signal intensity of specific expressed genes. We constructed the network adjacency between two genes, i and j, defined as a power of the Pearson correlation between the corresponding gene-expression profiles, xi and xj. By computing them, we obtained the gene adjacency matrix, M (i,j).18 The adjacency matrix, M (i,j), was visualized as a graph, and the topological properties of this graph were examined. To make a visual representation, only the strongest correlations (0.99 or greater) were drawn in these renderings. In gene-coexpression networks, each gene corresponds to a node. Two genes are connected by an edge, indicating a strong correlation (i.e., either positive or negative). Within the network analysis, a degree is the simplest, most important measure of the centrality of a gene within a network and determines the relative importance. A degree is defined as the number of directly linked neighbors.19 RNA Immunoprecipitation.We performed RNA immunoprecipitation (RIP) experiments using the Magna RIP RNA-Binding Protein Immunoprecipitation Kit (Millipore, Bedford, MA), according to the manufacturer's instructions. The EZH2 antibodies used for RIP were clone AC22 (17-662; Millipore) and ab3748 (Abcam, Hong Kong, China). The coprecipitated RNAs were detected by reverse-transcription polymerase chain reaction (RT-PCR). Total RNAs (input controls) and isotype controls were assayed simultaneously to demonstrate that the detected signals were from RNAs specifically binding to enhancer of zeste homolog 2 (EZH2) (n = 3 for each experiment). The gene-specific primers used for detecting lncRNA-HEIH (lncRNA High Expression In HCC) are presented in Supporting Table 2. RNA Pull-Down Assay.RNA pull-down and deletion mapping were performed as described previously.20 Briefly, biotin-labeled RNAs were in vitro transcribed with the Biotin RNA Labeling Mix (Roche Diagnostics, Indianapolis, IN) and T7 RNA polymerase (Roche), treated with RNase-free DNase I (Roche), and purified with the RNeasy Mini Kit (Qiagen, Inc., Valencia, CA). Cell nuclear proteins were extracted using the ProteoJETTM Cytoplasmic and Nuclear Protein Extraction Kit (Fermentas, St. Leon-Rot, Germany). One milligram of Huh7 or HCCLM3 cell nuclear extract was then mixed with 50 pmol of biotinylated RNA biotin-labeled RNAs. Sixty microliters of washed streptavidin agarose beads (Invitrogen, Carlsbad, CA) were added to each binding reaction and further incubated at room temperature for 1 hour. Beads were washed briefly five times and boiled in sodium dodecyl sulfate buffer, and the retrieved protein was detected by the standard western blotting technique. Chromatin Immunoprecipitation.Chromatin immunoprecipitation (ChIP) was performed using the EZ ChIP? Chromatin Immunoprecipitation Kit (Millipore), according to its manual. Briefly, cross-linked chromatin was sonicated into 200- to 1,000-bp fragments. The chromatin was immunoprecipitated using anti-Ezh2 (clone AC22), anti-H3K27me3 (Millipore), and anti-RNA Pol II antibodies. Normal mouse immunoglobulin G (IgG) was used as a negative control. Quantitative PCR was conducted using SYBR Green Mix (Takara Bio, Otsu, Japan). Primer sequences are listed in Supporting Table 2. Statistical Analysis.All the statistical analyses were performed using SPSS version 17.0 software (SPSS, Inc., Chicago, IL). For comparisons, one-way analyses of variance, Fisher's exact tests, chi-squared tests, and two-tailed Student's t-tests were performed, as appropriate. Multivariate logistic regression was performed to identify the independent factors related to HCC recurrence. Cumulative survival probability was evaluated using the Kaplan-Meier method, and differences were assessed using the log-rank test. To determine independent prognostic factors, Cox multivariate regression analysis was used. For a description of the patients and other methods used in this study, see the Supporting Information. ResultslncRNAs Expression Profile in HCC.Hierarchical clustering showed systematic variations in the expression of lncRNAs and protein-coding RNAs between HBV-related HCC and paired nontumor samples (Fig. 1A,B). To validate microarray analysis findings, we randomly selected five lncRNAs among the differential lncRNAs and analyzed their expression, using quantitative real-time polymerase chain reaction (qRT-PCR), in 50 pairs of HCC and corresponding nontumor liver tissues (Supporting Table 3, cohort 1; Fig. 1C). These data confirmed that AY129027, uc002pyc, and DQ786243 were overexpressed in HCC, whereas the expression of AK055007 and AK123790 was decreased (P < 0.05 for all). Thus, our data indicate that a set of lncRNAs is frequently aberrantly expressed in HBV-related HCC tissues. It is also interesting that the expression of DQ786243 in HCC is related to liver cirrhosis (Supporting Fig. 1A), and the expression of HOTAIR and AK055007 is up-regulated in paired nontumor samples, when compared to normal liver samples (Supporting Table 4; Supporting Fig. 1B).  Figure 1. Differential expression of lncRNAs in HCC. Hierarchical clustering analysis of 254 mRNAs (A) and 174 lncRNAs (B) that were differentially expressed between HCC samples (ca, cancer tissues) and nontumor samples (p, paired nontumor samples) (greater than 2.0-fold; P < 0.05). Expression values are represented in shades of red and green, indicating expression above and below the median expression value across all samples (log scale 2, from ?0.06 to +0.06), respectively. (C) We validated the differential expression of six lncRNAs in 50 paired HCC and nontumor samples using RT-PCR. (D) lncRNA-HEIH subnetwork in the HCC coexpression network. This subnetwork consists of lncRNA-HEIH (center) and its 18 direct neighbors. Genes colored in purple are protein-coding RNAs with unknown function. Genes colored in green are protein-coding RNAs involved in tumor growth and drug resistance. Genes colored in yellow are lncRNAs. Node size represents the node degrees. (E) RT-PCR analysis of lncRNA-HEIH expression in 50 paired HCC/nontumor tissue specimens, 20 HBV-infected liver cirrhosis tissues, and 20 healthy liver tissues. Horizontal lines in the box plots represent the median, the boxes represent the interquartile range, and whiskers represent the 2.5th and 97.5th percentiles. (F) Survival rates of 85 HCC patients who underwent liver surgery were compared between the lncRNA-HEIH high-expression and lncRNA-HEIH low-expression groups (log rank: P = 0.011). The median expression level was used as the cutoff. Low expression of lncRNA-HEIH in 42 patients was classified as values below the 50th percentile. High lncRNA-HEIH expression in 43 patients was classified as values at or above the 50th percentile. A Newly Identified lncRNA Could Be an Independent Prognostic Factor for HCC Patient Overall Survival.We used gene coexpression networks to cluster thousands of transcripts into phenotypically relevant coexpression modules.17, 21 The structure of the coexpression networks of HCC and nontumor samples were significantly different (Supporting Figs. 2 and 3), indicating that the coexpression patterns of lncRNAs and protein-coding RNAs in HCC and nontumor samples are different. Because coexpression modules may correspond to biological pathways22 and many functions of protein-coding RNAs could be found in NCBI RefSeq, we focused on coexpression modules that have a high rate of protein-coding RNAs in the HCC coexpression network. The role of lncRNA-HEIH in HCC can be characterized by this method. In the cancer coexpression network, lncRNA-HEIH is connected to two lncRNAs and 16 protein-coding genes that are enriched for gene products involved in tumor growth and drug resistance (Fig. 1D; Supporting Table 5). To investigate the roles of lncRNA-HEIH in HCC, we first examined a panel of 50 paired HCC/nontumor tissue specimens (Supporting Table 3, cohort 1), along with 20 HBV-infected cirrhotic liver tissues and 20 normal liver tissues (Supporting Table 4). The transcript levels of lncRNA-HEIH were higher in HCC tissues (P = 0.010), when compared with the corresponding nontumor liver tissues from the same donor (Fig. 1E). lncRNA-HEIH was also overexpressed in liver cirrhosis samples, compared with healthy liver tissue samples (P = 0.014), thus linking elevated expression of lncRNA-HEIH to pathological liver tissue. We further examined lncRNA-HEIH expression in 107 HCC tissues (Supporting Table 3, cohort 2) by RT-PCR. Though there was no significant correlation between lncRNA-HEIH expression and age, gender, tumor size, or HCC stage, aberrant lncRNA-HEIH expression was more frequently observed in tumors from patients with liver cirrhosis than in those from patients with no liver cirrhosis (P = 0.032). Furthermore, it was noteworthy that lncRNA-HEIH overexpression was significantly associated with tumor recurrence (P = 0.009) (Table 1). Logistic multivariate regression revealed that high levels of lncRNA-HEIH were independently associated with HCC recurrence (hazard ratio [HR] 2.83; 95% confidence interval [CI]: 1.29-6.21; P = 0.010). To explore whether lncRNA-HEIH could be an important factor in determining clinical outcomes of HCC patients, we examined the expression of lncRNA-HEIH in an additional 85 HCC samples (Supporting Table 3, cohort 3). As a result, we found that patients with high lncRNA-HEIH expression in HCC had a significantly worse prognosis than those with low lncRNA-HEIH expression (Fig. 1F; log rank: P = 0.011). Multivariate analyses revealed that the level of lncRNA-HEIH expression is an independent prognostic factor for overall survival (HR: 2.063; 95% CI: 1.160-3.670; P = 0.014). Taken together, these data suggest an important role for lncRNA-HEIH in hepatocarcinogenesis.
lncRNA-HEIH Regulates the Cell Cycle in HCC Cells.The transcription start and termination sites and sequence of full-length lncRNA-HEIH are presented in Supporting Fig. 4. Our results indicate that lncRNA-HEIH is polyadenylated, and RNA polymerase II catalyzes its transcription (Supporting Fig. 5A,B). The transcript of lncRNA-HEIH is located in the nucleus and cytoplasm of HCC cells (Supporting Fig. 5C). Analysis by RT-PCR revealed significantly higher expression of lncRNA-HEIH in Huh7 and HepG2 cell lines (Supporting Fig. 6A). We first ruled out the possibility that the lncRNA-HEIH was amplified in the HCC genome, because equal amounts were detected in genomic DNA extracted from HCC and paired nontumor tissues using RT-PCR (data not shown). Second, we did not find any changes in lncRNA-HEIH expression levels in HCC cells treated with histone deacetylase inhibitors or DNA methylation inhibitors (data not shown). These results indicate that histone acetylation and DNA methylation are less likely to regulate lncRNA-HEIH expression in HCC. Third, we performed a computational screen and found that SP1 localized within the lncRNA-HEIH gene transcriptional element. We addressed whether the overexpression of lncRNA-HEIH is mediated by SP1. The expression of SP1 in HepG2 and Huh7 cells was down-regulated by transfection with small-interfering RNAs (siRNAs) targeting the SP1 gene. siRNAs significantly decreased SP1 protein levels (Fig. 2A, up, and B, up). lncRNA-HEIH levels were significantly reduced in cells transfected with anti-SP1 siRNAs (Fig. 2A, down). Similar differential results were also observed in Huh7 cells transfected with anti-SP1 siRNAs, compared to those transfected with a scramble control (Fig. 2B, down). These results indicate the possibility that lncRNA-HEIH up-regulation in HCC is mediated by the transcription factor, SP1.  Figure 2. Overexpression of lncRNA-HEIH. HepG2 (A) and Huh7 (B) cells were transfected with the transfection agent, but no siRNA (Mock), siRNA against SP1 (siRNA), or scramble-control siRNA (negative control) for 48 hours. Reduced SP1 expression by siRNAs was shown by western blotting analysis and normalized to β-actin. Expression of lncRNA-HEIH transcripts was quantified by RT-PCR. Data shown are the mean ± standard deviation (SD) of three independent experiments. Huh7 cells stably transfected with lentivirus encoding shRNA against lncRNA-HEIH (C) and Hep3B cells stably transfected with pcDNA3.1 encoding lncRNA-HEIH cDNA (D) were seeded in 96-well plates, and cell proliferation was assessed daily for 3 days using the Cell Counting Kit-8 (CCK-8) assay (Dojindo Molecular Technologies, Inc., Rockville, MD). Changes in the proliferation marker, PCNA, were shown by western blotting analysis and normalized to β-actin. To evaluate the effects of lncRNA-HEIH on cell biological behaviors, we constructed cell lines with lncRNA-HEIH stable overexpression and downexpression (Supporting Fig. 6B-E). Cell-counting kit-8 assays indicated that cell proliferation was reduced in Huh7 (Fig. 2C, up) and HepG2 (Supporting Fig. 7A, up) cells when lncRNA-HEIH expression was knocked down. Consistent with decreased cell proliferation, Huh7 and HepG2 cells in which lncRNA-HEIH was attenuated had significantly lower levels of proliferating cell nuclear antigen (PCNA) expression, compared with control cells (Fig. 2C, down; Supporting Fig. 7A, down). In contrast, exogenous expression of lncRNA-HEIH promoted proliferation and PCNA expression in Hep3B (Fig. 2D) and SMMC-7721 cells (Supporting Fig. 7B). These results suggest that lncRNA-HEIH plays a physiological role in regulating cell proliferation. Next, we examined whether the cell cycle would be affected by the knockdown of lncRNA-HEIH, using fluorescence-activated cell sorting (FACS) analysis of propidium-iodide–stained cells. Knockdown of lncRNA-HEIH resulted in a significant decrease in the percentages of cells in the G2 phases (Fig. 3A). To investigate the fact that lncRNA-HEIH plays a role in G0/G1 arrest, we investigated the cyclin-dependent protein kinase inhibitors by western blotting, and the results showed that the p16, p27, and p21 proteins were increased with the knockdown of lncRNA-HEIH (Fig. 3B, up) and decreased with the overexpression of lncRNA-HEIH (Fig. 3B, down). These results suggest that lncRNA-HEIH may contribute to cell-cycle arrest.  Figure 3. lncRNA-HEIH regulates the cell cycle of HCC cells. Cell line construction and tumor establishment were performed as described in the Supporting Information. (A) FACS determined the relative cell numbers in each cell-cycle phase after propidium iodide staining of lncRNA-HEIH-down-regulated Huh7 cells. Numbers inside bars represent percentages of cells in each phase. (B) Huh7 (up) and Hep3B (down) cells, treated as described in Fig. 2C,D were collected for western blotting analysis of the G0/G1 arrest markers, p16, p21, and p27. Relative protein expression was identified (n = 3). The in vivo models used were xenograft-transplanted nude mouse tumor models of human HCC growth established with lncRNA-HEIH-down-regulated Huh7 cells (Huh7 shRNA-1; model A) or with lncRNA-HEIH-up-regulated SMMC-7721 cells (SMMC-7721 clone 10 and SMMC-7721 clone 16; model B). (C) Photographs of tumors that developed in model A by imaging with the IVIS Imaging System (Caliper Life Sciences, Hopkinton, MA). A representative luciferase signal was captured in each group at 6 weeks after cell injection (left). A photograph of the tumors is also presented (right). (D-F) Effect of lncRNA-HEIH on HCC tumor growth in model B. Asterisk indicates a significant change (P < 0.05). Data are the mean ± SD. To probe the effects of lncRNA-HEIH on cancer cell dynamics in vivo, lncRNA-HEIH-down-regulated (firefly luciferase-labeled Huh7 shRNA-1 cells), lncRNA-HEIH-up-regulated (SMMC-7721 clone 10 and SMMC-7721 clone 16 cells), or respective control cells were injected into the bilateral armpit of nude mice. Our results showed that the growth of tumors from lncRNA-HEIH-down-regulated xenografts was significantly inhibited, compared with that of tumors formed from control xenografts (Fig. 3C), and the growth of tumors from lncRNA-HEIH-overexpressing xenografts was significantly promoted, compared with that of tumors formed from control xenografts (Fig. 3D-F). Association of LncRNA-HEIH and Polycomb Repressive Complex 2.Recent studies have reported that lncRNAs recruit polycomb-group proteins to target genes.12, 20 Twenty percent of all human lncRNAs have been shown to physically associate with Polycomb Repressive Complex 2 (PRC2 complex),23 suggesting that lncRNAs may have a general role in recruiting polycomb-group proteins to their target genes. Thus, we hypothesized that lncRNA-HEIH might affect gene expression in such a manner. To test this, we performed RIP with an antibody against enhancer of zeste homolog 2 (EZH2; an important subunit of the PRC2 complex) from nuclear extracts of Huh7 and HCCLM3 cells. We observed a significant enrichment of lncRNA-HEIH with the EZH2 antibody (Fig. 4A, up, and B, up), but no enrichment of beta-actin (β-actin) or lncRNA AK055007 (Fig. 4C), compared with the nonspecific IgG control antibody. These results were confirmed using a different antibody against EZH2 and another primer pair for lncRNA-HEIH to exclude potential nonspecific association (Fig. 4A, down, and B, down). We next performed in vitro RNA pulldown (Fig. 4D), to validate the association between lncRNA-HEIH and EZH2, and performed deletion-mapping experiments (Fig. 4E) to determine whether EZH2 would associate within a specific region of lncRNA-HEIH. These analyses identified a 799-nt region at the 5′ end of lncRNA-HEIH required for the association with EZH2 (Fig. 4E). Together, the RIP, RNA pull-down, and deletion mapping results demonstrate a specific association between EZH2 and lncRNA-HEIH.  Figure 4. lncRNA-HEIH physically associates with EZH2. (A) RIP experiments were performed using the EZH2 antibody to immunoprecipitate (IP) and a primer to detect lncRNA-HEIH (up, antibody clone AC22 [Ab-1] and primer 1; down, antibody ab3748 [Ab-2] and primer 2). (B) RIP enrichment was determined as RNA associated with EZH2 IP relative to an input control. (C) RIP experiments were performed using Ab-1 (clone AC22) for IP and a primer to detect AK055007 and β-actin. (D) Biotinylated lncRNA-HEIH or antisense RNA were incubated with nuclear extracts (Huh7 and HCCLM3 cells), targeted with streptavidin beads, and washed, and associated proteins were resolved in a gel. Western blotting analysis of the specific association of EZH2 and lncRNA-HEIH (n = 3). A nonspecific protein (NONO) is shown as a control. (E) RNAs corresponding to different fragments of lncRNA-HEIH or its antisense sequence (dotted line) were treated as in (D), and associated EZH2 was detected by western blotting (n = 3). We then sought to determine the functional relevance of the association between lncRNA-HEIH and EZH2. The effectiveness of EZH2 siRNA is presented in Fig. 5A,B. Analysis with RT-PCR and western blotting confirmed that the expression of PRC2 target genes, such as the cell-cycle regulation genes, p15,24 p16,25, 26 p21,27 and p57,28 were diminished when lncRNA-HEIH was overexpressed (Fig. 5C,D) and up-regulated when lncRNA-HEIH was knocked down (Fig. 5E,F). Furthermore, the suppression of genes by lncRNA-HEIH was reversed when EZH2 expression was simultaneously down-regulated (Fig. 5C,D). To address whether lncRNA-HEIH is involved in transcriptional repression through enrichment of EZH2 to target gene promoters, we conducted ChIP analysis in lncRNA-HEIH-overexpressing SMMC-7721 cells (SMMC-7721 clone 10 and clone 16). ChIP arrays demonstrated that lncRNA-HEIH increased the binding of EZH2 and H3K27me3 levels across the p16 promoters (Fig. 6B,C). Interestingly, we observed that lncRNA-HEIH increased the binding of EZH2 (Fig. 6B), but there was no increase in H3K27me3 levels (Fig. 6C) across the p21 promoters. This indicates that EZH2 may silence this gene expression in other ways.27 More important, we did not detect any increase of EZH2 binding or H3K27me3 level cross the Foxc1 promoters, a target of polycomb29 (Fig. 6).  Figure 5. lncRNA-HEIH induced alterations in cell-cycle–related genes require EZH2. Hep3B cells were transfected with EZH2 siRNAs for 48 hours, and EZH2 mRNA (A) and protein (B) levels were detected. RT-PCR (C) and western blotting (D) analysis of a representative panel of cell-cycle–related genes in lncRNA-HEIH-overexpressing Hep3B cells (Hep3B clone 1) and Hep3B clone 1 cells simultaneously transfected with EZH2 siRNA. RT-PCR (E) and western blotting (F) analysis of cell-cycle–related genes in lncRNA-HEIH-down-regulated Huh7 cells (Huh7 shRNA-1 and 2).  Figure 6. ChIP analysis. (A-D) ChIP analyses of lncRNA-HEIH-overexpressing SMMC-7721 cells (SMMC-7721 clone 10 and SMMC-7721 clone 16) were conducted on p16 (primer set a-c), p21 (primer set d-e), Foxc1 (primer f), and GAPDH (primer g) promoter regions using the indicated antibodies. Enrichment was determined relative to input controls. Asterisk indicates a significant change (P < 0.05). Data are the mean ± SD of three independent biological replicates. DiscussionIn this study, we have identified nonoverlapping signatures of a small number of lncRNAs that are aberrantly expressed in human HBV-related HCC, compared to paired peritumoral tissues. Applying loss-of-function and gain-of-function approaches, we identified that lncRNA-HEIH plays a key role in cell-cycle regulation. Furthermore, it was shown that lncRNA-HEIH associates with EZH2 and that this association is required for the expression of EZH2-regulated target genes. For HCC, deregulated expression of both protein-coding genes and microRNAs (miRNAs) have been suggested to have considerable potential in predicting the prognosis of HCC patients.30, 31 We found that patients with tumors with high lncRNA-HEIH expression had an increased risk of recurrence and significantly reduced overall postoperative survival. Previous reports showed that de-regulated lncRNA highly up-regulated in liver cancer,14, 15 and H1932 expression in HCC tissues could also be used as prognostic biomarkers of HCC. Detecting the expression level of these lncRNAs, in combination with lncRNA-HEIH and even protein-coding genes or miRNAs, may be valuable to predict the prognosis of HCC patients more accurately. Additionally, because several other lncRNAs, such as AK055007, DQ786243, AY12927, uc002pyc, and AK123790, are also suggested to be differentially expressed in HCC tissues, we will next determine whether deregulation of this panel of lncRNA also correlates with the survival of HCC patients and whether detecting these lncRNAs together is more precise in identifying the prognosis of HCC patients. Some previous studies showed that the overexpression of EZH2 is associated with the malignant progression of HCC and the aggressive biological features of HCC.25, 33 We showed that short-hairpin RNA (shRNA)-mediated depletion of lncRNA-HEIH leads to up-regulation of genes that are normally silenced by PRC2 (Fig. 5C,D). The association of lncRNA-HEIH with EZH2 could provide a hint to the complicated regulation mechanism of EZH2 in HCC. It is particularly interesting that SMMC-7721 clone 16 contains much greater lncRNA-HEIH than SMMC-7721 clone 10, or the control (Supporting Fig.6E), yet the proliferation ability of these clones behaves the same (Supporting Fig. 7B, up). This result indicates that lncRNA-HEIH expression level is not the only factor determining the association of lncRNA-HEIH and EZH2 for cell-proliferation regulation. Overall, we propose a model in which some lncRNAs associate with chromatin-modifying complexes to regulate gene expression in HCC. Unfortunately, because there is no mouse homolog of lncRNA-HEIH, there are currently no in vivo models available to study this mechanism in more detail. However, the association of lncRNA-HEIH with the EZH2 and our knock-down data suggest a role of lncRNA-HEIH in the transcriptional control of gene expression. More important, our data indicate that 174 lncRNAs were either overexpressed or underexpressed in HCC. Although these data suggest that the observed changes are likely to have a biological effect, this possibility needs to be confirmed by specific, hypothesis-driven studies. Understanding the precise molecular mechanisms by which lncRNAs function in HCC will be critical for exploring these potential new strategies for early diagnosis and therapy of HCC. References
Supporting InformationAdditional Supporting Information may be found in the online version of this article.
Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. |
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