Recent data have linked hypoxia, a classic feature of the tumor microenvironment, to the function of specific microRNAs (miRNAs); however, whether hypoxia affects other types of noncoding transcripts is currently unknown. Starting from a genome-wide expression profiling, we demonstrate for the first time a functional link between oxygen deprivation and the modulation of long noncoding transcripts from ultraconserved regions, termed transcribed-ultraconserved regions (T-UCRs). Interestingly, several hypoxia-upregulated T-UCRs, henceforth named ‘hypoxia-induced noncoding ultraconserved transcripts’ (HINCUTs), are also overexpressed in clinical samples from colon cancer patients. We show that these T-UCRs are predominantly nuclear and that the hypoxia-inducible factor (HIF) is at least partly responsible for the induction of several members of this group. One specific HINCUT, uc.475 (or HINCUT-1) is part of a retained intron of the host protein-coding gene, O-linked N-acetylglucosamine transferase, which is overexpressed in epithelial cancer types. Consistent with the hypothesis that T-UCRs have important function in tumor formation, HINCUT-1 supports cell proliferation specifically under hypoxic conditions and may be critical for optimal O-GlcNAcylation of proteins when oxygen tension is limiting. Our data gives a first glimpse of a novel functional hypoxic network comprising protein-coding transcripts and noncoding RNAs (ncRNAs) from the T-UCRs category.
Hypoxia is one of the classic features of the neoplastic microenvironment and is causally associated with resistance to conventional anticancer therapy.1 Under hypoxic conditions, cells undergo a complex adaptive process involving genes regulating angiogenesis, cell invasion, metabolism and survival pathways. Novel insights into the pathways regulated by low oxygen concentration have shown that in addition to protein-encoding genes, the noncoding transcriptome is also affected by hypoxia. We and others previously reported that hypoxia regulates specific microRNAs (miRNAs), which in turn regulate signals of relevance for tumor biology,2, 3, 4, 5 including angiogenesis, cell cycle, DNA repair and energy metabolism.5, 6
During the past few years, it has become clear that long noncoding RNAs (ncRNAs) (>200 bp in length) also participate in complex genetic events in eukaryotes.7 One intriguing family of long ncRNAs8 is transcribed from regions that exhibit extremely high conservation between the orthologous regions of human, rat and mouse genomes,9, 10 hence the term ‘transcribed-ultraconserved regions’ (T-UCRs) or ultraconserved genes.8 Their striking evolutionary retention strongly suggests profound biological roles in a wide variety of physiologic responses. Recent studies have identified alterations in T-UCR-expression patterns that are associated with specific tumor phenotypes, pointing towards a mechanistic involvement of T-UCRs in cancer development. In particular, alterations in T-UCR expression have been described in adult chronic lymphocytic leukemia, colorectal cancer (CRC),8 hepatocellular carcinomas8, 11 and neuroblastomas.12, 13 In the human genome, T-UCRs are often found to overlap with exons of genes involved in RNA splicing or are located within host gene introns or in close proximity to genes that are involved in transcription and development regulation.9, 14 Whereas ultraconserved sequences appear to act as tissue-specific regulators of gene expression during development,7, 9, 15 very little, if anything, is currently understood about the mechanisms underlying the cancer-associated profile alterations of the T-UCR. To address this limitation, we hypothesized that decreased oxygenation contributes to the deregulation of specific T-UCRs in cancer, pursuing a similar rationale to our original work on hypoxia-regulated miRNAs.2 We initiated the search by exposing several cancer cell lines to low oxygen followed by quantification of changes in T-UCR expression versus normoxic controls using a genome-wide microarray profiling. Subsequently, we interrogated the contribution of hypoxia-inducible factor (HIF) activity to the upregulation of a set of hypoxia-induced noncoding ultraconserved transcripts (HINCUTs). Finally, the leading candidate of this group was functionally dissected in detail.
T-UCR-expression changes under hypoxic conditions in malignant cells
We re-interrogated our previous microarray data (Array Expression accession: E-TABM-184) obtained from CRC samples (78 CRCs compared with 21 normal colonic mucosas)8 to identify T-UCRs overexpressed in CRC that could be potentially induced by hypoxia (for a detailed workflow, see Figure 1a and Supplementary Figure 1). The same type of microarrays was used for the discovery of hypoxia-induced miRNAs.2 We identified 61 T-UCRs that had a significantly (P-value <0.05 Welch t-test with Benjamini–Hochberg correction) altered expression in CRC when compared with normal colon tissue (59 overexpressed and two with lower expression). Twenty-seven T-UCRs were upregulated compared with normal colonic mucosa at a more stringent P-value <0.005, and further analyzed (Supplementary Table 1).
In order to validate the microarray data, we exposed two cancer cell lines (HCT-116 CRC and MCF-7 breast cancer cells) to 1% oxygen or 500 μM DMOG (dimethyloxalylglycine) – a widely used hypoxia mimetic – for 24 and 48 h and measured T-UCR expressions using quantitative reverse transcriptase PCR (RT-qPCR). Comparisons were performed with normoxic controls (21% oxygen) or dimethyl sulfoxide (0.5% DMSO). We identified a set of T-UCRs (uc.63, uc.73, uc.106, uc.134 and uc.475) that was induced more than two-fold (P-value <0.05 by Student’s t-test) after 48 h both of hypoxia and DMOG exposures (Figure 1b and Table 1). All of these transcripts were predominantly present in the nucleus, as identified by nuclear and cytoplasmic fractionation experiments (Supplementary Figure 2). Robust activation of hypoxia signaling was confirmed by HIF-1α (or HIF-2α) protein overexpression (Figures 1b and c), carbonic anhydrase IX (CA9) (data not shown) and miR-210 (Supplementary Figure 3) gene expression levels, which are both well-established coding and noncoding HIF targets, respectively.2 Henceforth, these T-UCRs will be referred to as HINCUTs; their functional dissection under low-oxygen conditions is described below.
Evidence for HIF as HINCUT’s regulator
The effect of DMOG on the expression of HINCUTs suggests a central role for HIFs as an upstream regulator. To further address the role of HIF, we used the renal cell carcinoma (RCC) cell line 786-O, which exhibits homozygous inactivation of the von Hippel–Lindau tumor suppressor gene (VHL), the well-established E3 ubiquitin ligase for all HIF family members. 786-O cells exhibit constitutive activation of the HIF pathway.16 We hypothesized that HIF-2α-induced T-UCR expression would have a similar pattern. To this end, when we compared normoxic 786-O cells expressing an empty vector with cells expressing wild-type VHL to restore the defects, and consistent with being bona fide HIF-2α targets, all HINCUTs were upregulated at least 1.5-fold in the VHL-deficient cell line (VHL−) compared with the VHL-restored (VHL+) cells (Figure 1c). Furthermore, time course experiments in hypoxic models revealed that uc.475 was the most consistently induced (Supplementary Figure 4).
As no T-UCR promoter has been characterized to date, we performed an in silico search for HIF-binding sites within the 15-kb genomic region surrounding HINCUTs. For uc.63, uc.73, uc.134 and uc.475, we found multiple putative HIF-binding sites per UCR (Supplementary Table 2). Then T-UCRs with yet unknown functional role and more than one binding sites identified were also included in these studies. In the uc.63 promoter region, we identified the following three candidate HIF-binding sites: Q3_uc.63A 5′-IndexTermGGCAACGTGCATG-3′ (63A.1), Q3_uc.63A 5′-IndexTermGAGTGCGTGCTCCT-3′ (63A.2) and Q6_uc.63A 5′-IndexTermCGCGTGTGC-3′ (63A.3), whereas for uc.475 the following three candidate sites were found: Q3_uc.475 5′-IndexTermGCTCGCATGCGCGG-3′ (475.1) and two in close proximity with each other, Q5_uc.475 5′-IndexTermCACACGTGCGCG-3′ and Q6_uc.475 5′-IndexTermCACGTGCGC-3′ (475.2) (Figure 2a).
To further substantiate the role of HIF in the regulation of uc.475 and uc.63, we performed chromatin-immunoprecipitation assay (ChIP) of HIF-1α in MCF-7 cells under normoxic conditions or following treatment with the hypoxia mimetic, DMOG. We confirmed direct recruitment of endogenous HIF-1α at the promoters of uc.63 (data not shown) and uc.475, which was more evident during hypoxic conditions (Figure 2a; genomic regions from The University of California, Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu/)17 NCBI36/hg18). For each ChIP reaction, we used the promoter of CA9, a well-characterized HIF target, as the positive control and hemoglobin beta (HBB) as the negative control.
We further confirmed the transcriptional activation of uc.475 by hypoxia and HIF-1α using promoter fragments subcloned into the pGL4-10 (luc2) basic expression vector. These constructs were co-expressed with the pRL-TK (Renilla) control vector and constitutively active HIF-1α constructs (pcDNA 3.1-HIF-1α P/A (proline/alanine mutant) and pcDNA 3.1-HIF-1α 3M (proline/alanine/asparagine mutant)18 in two CRC cell lines, HCT-116 and HT-29 cells (Figures 2b and c). We found that hypoxia and the active HIF-1αs induced an increase (up to five-fold) in luciferase activity (Figure 2b), which was correlated with the uc.475 expression in these cells (Supplementary Figure 5). In contrast, luciferase activity of the mutant clones that lack HIF-1α-binding sites (PT1 and PT2) was significantly reduced (Figure 2c) (P-value <0.005), suggesting that the two predicted binding sites are functional HIF-recognition sites that mediate hypoxia effects on uc.475 transcription.
Biological effects of uc.475 downregulation
To determine the biological significance of HINCUTs, we performed knockdown experiments for uc.63 and uc.475 using custom-designed siRNAs and found that these effected cell proliferation using the general strategy described initially for uc.73.8 siRNA-specific oligonucleotides for HINCUTs were designed after evaluating by strand-specific RT-qPCR if the sense or antisense transcript was transcribed at higher levels (Supplementary Figures 5 and 6). No major biological effect on the dynamics of COLO-205 culture was identified for uc.63 (Supplementary Figure 7) and henceforth, we focused our efforts on uc.475. Notably, the primary uc.475 transcript has the same orientation as its host gene, O-linked N-acetylglucosamine (GlcNAc) transferase (OGT) (Supplementary Figure 6). The effect of uc.475 downregulation on cell survival was tested in HT-29 cells under hypoxic and normoxic conditions. These cells were chosen based on their high endogenous uc.475 expression level (Supplementary Figure 5). We employed a custom-designed pool of siRNAs to knockdown uc.475; each of the three siRNAs tested to be efficient reduced the basal expression of uc.475 by more than 65% as confirmed by RT-qPCR (Supplementary Figures 7 and 8 and Supplementary Table 3).
Under normoxic conditions, downregulation of uc.475 had no significant impact on the total cell number versus control (siRNA-NEG) cells for up to 120 h (Figure 3a, left). In contrast, under hypoxic conditions (1% O2), uc.475 knockdown significantly decreased cell proliferation (Figure 3a, right). This effect was not the result of increased apoptosis, as poly ADP-ribose polymerase, a critical component of programmed cell death, remained uncleaved (data not shown). Instead, through the analysis of the cell cycle, using fluorescence-activated cell sorting (FACS), we observed that uc.475 knockdown under hypoxic condition enriched the G2/M fraction more than two-fold at 72 and 96 h (from 10.3 and 8.2% with the negative control to 21.7 and 18.8% with siRNA, respectively), suggesting a G2/M blockade. No similar consistent variations in the percentage of cells in the various phases of the cell cycle under normoxic conditions were identified (Figure 3b and Supplementary Figure 9). Cell cycle distribution was also checked after treatment with siRNA against OGT (Supplementary Table 3 and Supplementary Figure 8) under normoxia and hypoxia, and only minimal effects on cell cycle progression were observed (Supplementary Figure 9b). To exclude the possibility that siRNA against uc.475 downregulates pre-mRNA of OGT and leads to a phenotypic effect, we designed another siRNA targeting another intron of OGT. We selected intron 12 to knockdown the pre-mRNA, as this siRNA exhibited the highest efficiency among several siRNAs we have designed. As a result, although OGT protein expression was moderately downregulated by OGT-intron 12 knockdown, more significant reduction was observed with uc.475 knockdown (Figure 3c), and no proliferation inhibition or altered cell cycle distribution was observed after the knockdown of OGT-intron 12 (Supplementary Figure 11). These results indicate that the alteration of OGT expression and proliferation inhibition by uc.475 knockdown is a distinct effect of the OGT pre-mRNA knockdown.
OGT locus: a mix of OGT and HINCUT-1 transcripts
As mentioned previously, and in line with earlier reports,19, 20, 21 the uc.475 sequence (396 bp in length) is found inside the fourth intron of the OGT gene (UCSC Genome Browser; GRCh/hg19, Figure 4a). OGT has two known isoforms (OGT1 of 5497 bp and OGT2 of 5467 bp) because of a variant splice site, which is known to encode proteins of 1046 or 1036 amino acids (116 and 103 kDa), respectively, and that catalyze polypeptide glycosylation by the addition of N-acetylglucosamine (O-GlcNAc) to serine and threonine residues (O-GlcNAcylation) on many nuclear and cytosolic proteins.19 Recently, this modification was proposed to be a new link between glucose metabolism and cancer growth and invasion in breast,22 colon and lung cancer types.23 In addition, OGT was found to be highly expressed in prostate cancer compared with the normal epithelium.24 Taking into account the link between OGT and cancer, we hypothesized that this, at least in part, could be explained by the associated uc.475 transcript with a potential role as the regulator of its host gene expression during hypoxia.
By using a multiple-primer amplifications approach, we cloned a transcript of ∼2.7 kb that included the uc.475 region but excluded the flanking OGT exons (for details see Supplementary Figure 12). In contrast, amplification levels were much lower when primers in the ‘flanking’ OGT exons (Exons 4 and 5) and intron region containing uc.475 were used in combination; the OGT and uc.475 transcripts were 2–10 times more abundant than the amplicons obtained with the mixed combinations of primers between flanking sequences of uc.475 and exons of OGT (Figure 4b). These data support two possibilities: (a) the existence of an OGT-independent transcript that contains the fourth intron or (b) the existence of a primary transcript that contains both OGT and uc.475 but is further spliced into two transcripts, one noncoding (the intronic uc.475) and one coding (the OGT isoforms).
To further substantiate the tight link between OGT and uc.475, we performed experiments under stress conditions for which OGT function is relevant.25 As OGT-mediated O-GlcNAcylation is proportional to substrate (glucose) availability,26 we performed experiments under glucose- as well as oxygen-deprivation conditions (OGD experiments) – two tightly associated characteristics of the tumor microenvironment. In HT-29 cells, the expression levels of uc.475 and OGT mRNA significantly increased during 12 and 24 h of normoxia in glucose-free media. After 48-h exposure under these conditions, the expression of both decreased dramatically to the same or lower level observed under hypoxia in the presence or absence of glucose (Figure 4c). These data show that the responses of uc.475 and OGT mRNA expression to oxygen and glucose deprivation are similar.
In parallel, we attempted to visualize the sizes of the transcripts from this locus by using Northern blot analysis. This would allow us to determine whether uc.475 exists as an independent transcript, or only part of a hybrid transcript with OGT, or as both. We used RNA isolated from MCF-7 cells after exposure to hypoxia or normoxia for 24 h. Using a probe specific to uc.475, we identified two transcripts (∼8 and∼9.5 kb) with higher expression under hypoxia in MCF-7 cells, whereas the OGT-coding region transcripts (4.2 kb long) had barely detectable signal (Figure 5, left). Hybridization with an OGT-specific probe detected two transcripts (1.7 and 4.2 kb) with similar intensity under both normoxia and hypoxia conditions (Figure 5, right). Therefore, we believe that uc.475 is the part of a larger OGT primary transcript, which retains intron 4 and which is expressed in a hypoxia-dependent manner.
When we screened for potential open reading frames (ORF) in the ‘retained intron’, we detected no ORF >100 bp. The 9-kb transcript was not predicted to encode for either of the two OGT isoforms, as the predicted ORF corresponds to 665 amino acids, potentially representing the smaller 78-kDa version of the OGT reported recently19, 20, 27 (Supplementary Figure 13). In addition, we have searched for miRNAs and other putative ncRNAs in the uc.475 region using the UCSC database, in which current integrated RNA deep-sequencing experiment data (RNA-seq and miRNA-seq) are available, and found no annotated miRNAs or other ncRNAs to be located within the uc.475 region.
Uc.475 inhibition has an impact on OGT expression and function
We first investigated whether OGT expression at RNA and protein levels was affected by uc.475 knockdown in HT-29 cells. Expression of OGT mRNA levels was decreased by knocking down uc.475 (Figure 6a), as well as OGT protein levels, which was more evident in hypoxia (Supplementary Figure 10). Silencing OGT with siRNAs (siRNA-OGT) resulted in decreased levels of uc.475 and OGT mRNAs (Figure 6b) and OGT protein expression (Figure 6c). Interestingly, and contrary to the mRNA, the OGT protein level does not increase in hypoxia, as evidenced by measurements performed in three different cell lines – HCT-116 colon cancer, MCF-7 breast cancer and U-87 glioblastoma cells (Supplementary Figure 14).
To provide functional support for the impact of uc.475 downregulation on OGT function, we quantitated the O-GlcNAcylation rate following siRNA-mediated knockdown of the transcript containing the ultraconserved sequence (Supplementary Figure 15). This was performed in HT-29 cells treated with PUGNAc (1,5-hydroximolactone), an inhibitor of the N-acetylhexosaminidases (OGA or MGEA5), in order to prevent the removal of O-GlcNAc from proteins.28 Downregulation of uc.475 led to a significant decrease in the global O-GlcNAcylation rate, an effect similar to treatment with OGT-siRNA (Figure 6d), whereas the inhibition of OGT protein and global O-GlcNAcylation was relatively modest after treatment with siRNA against OGT-intron 12, which targets OGT pre-mRNA.
The enhancer-like function of the DNA region containing uc.475 ncRNA
It has been reported that ultraconserved regions can act as developmental enhancers, so we determined whether, in addition to having a transcriptional activity, the uc.475 could also have an enhancer function.29 We used sequence-transcription stimulation by an adjacent heterologous promoter region as previously described.30 The 2.7-kb long region (−1 kb upstream and +1.3 kb downstream of uc.475) (Supplementary Figure 12) was subcloned into the pGL3-TK vector (Figure 7a). This cloned insert revealed 2-3 fold luciferase activity enhancement, under both normoxia and hypoxia, in U-87 cells (Figure 7b). These findings demonstrate that the uc.475 DNA region also has an enhancer activity both under hypoxic and normoxic conditions.
We aimed to investigate whether hypoxia induces the expression of noncoding ultraconserved transcripts in a similar manner to the conventional hypoxia-regulated genes or more recently studied miRNAs. To this end, we employed a strategy that integrates tumor data with a microarray-based screen.2 We identified in multiple cell types the following hypoxia-induced, noncoding ultraconserved transcripts: uc.63, uc.73, uc.106, uc.134, and uc.475, and termed these HINCUTs. Similar to the earlier work on miRNAs,2 we are providing evidence that HIF has a critical role for their hypoxic regulation, based on induction with chemical inactivators of the HIF prolyl hydroxylases, effect of the VHL tumor-suppressor inactivation and effect of exogenous HIF-1αs on luciferase reporters containing fragments from the candidate promoters of HINCUTs. We identified HIF-1α-binding sites upstream of uc.475. This region in fact overlaps the OGT gene promoter region; therefore, the transcriptional control of uc.475 is not considered to be completely distinct from OGT transcription. Our in silico prediction detects no putative binding site for HIF-1α very close to OGT intron 4, where uc.475 is located. Recent reports have demonstrated that many intronic miRNAs possess their own promoter, which is independent of the host gene transcription.31 Further investigation is required to reveal whether there is an additional transcriptional factor-binding site closer to the uc.475 region.
Our data suggest that uc.475 is part of a primary (potentially retained intron) transcript that also includes the coding sequences of its ‘host gene’ OGT. The role of OGT is to catalyze the addition of O-GlcNAc on proteins, which are involved in transcription, cellular signaling pathways and processes, and the cell cycle.27, 32 OGT was also recently reported to be overexpressed in breast cancer and primary and metastatic prostate cancer,22, 24 further supporting OGT as a therapeutic target in solid malignancies.
Our results may expand the understanding of the complexity of the OGT genomic locus, as it reveals the presence of a noncoding ultraconserved sequence, part of a retained intron, at the core of a hybrid nuclear transcript. We provide evidence that the OGT locus generates multiple coding and noncoding transcripts. The retained intron that contains uc.475 does not possess a coding ORF but does include a second start codon (ATG) or it could be part of a long 5′-untranslated region (3.27 kb).21
We also noticed a contrast between the hypoxia-inducible nature of OGT/uc.475 at RNA and protein levels. Indeed, measurements in multiple cell lines indicate that OGT is either unchanged (Supplementary Figure 14) or even decreased during oxygen deprivation (data not shown). This is likely part of the wide translational suppression consistently reported under hypoxia. Higher transcript levels may serve to compensate this decrease, and it is entirely conceivable that in the absence of mRNA induction the level of O-GlcNAcylation would be compromised below the level compatible with survival.
What is therefore the role of uc.475-containing noncoding region in the context of OGT-hypoxic regulation? The luciferase experiments (Figure 7) suggest that on one hand this sequence may serve as an enhancer, which could cooperate with HIF for elevated transcription. The predominantly nuclear localization of the hypoxia-inducible hybrid transcript may point also to a role in RNA stability. To date, retained introns within several genes were found to enhance almost every step of gene expression and also affects mRNA stability. However, some studies showed that intron retention has little or no effects on mRNA half-life,33, 34, 35 whereas others confirmed that it is important for mRNA stability and has an effect on prolonged mRNA half-life.36, 37, 38 In addition, cells under hypoxia were even found to inhibit nonsense-mediated RNA decay (NMD) mechanisms to enable the expression of genes critical for cell adaptation and response to a cellular stress.39 Moreover, many studies found that constitutively spliced introns are required for optimal gene expression,33, 40, 41 and one possible way through which introns can affect transcription is by acting as repositories for transcriptional regulatory elements such as enhancers and repressors.41
Although further mechanistic studies as well as an understanding of the specific roles of the many transcripts at the OGT locus are needed, this is the first study that purposely investigates T-UCRs as a part of the hypoxic response and extends the knowledge of the interplay between coding and noncoding transcripts under stress conditions.
Materials and Methods
The complete version is included in the Supplementary Material.
Cell cultures and growth conditions
Colon cancer (HCT-116, HT-29 and COLO-205), breast cancer (MCF-7), bladder cancer (UC-2) and glioblastoma (U-87) cell lines were obtained from ATCC (Manassas, VA, USA). RCC cell lines42 were obtained from Dr. Maria Czyzyk-Krzeska (University of Cincinnati, Cincinnati, OH, USA). HCT-116 and HT-29 were maintained in McCoy’s 5A (enriched with L-glutamine and sodium bicarbonate; Thermo Scientific, Logan, UT, USA); UC-2 was maintained in minimum essential Eagle medium (MEM; Cellgro Mediatech, Manassas, VA, USA); MCF-7 was cultured in Dulbecco’s modified Eagle’s high-glucose medium (DMEM; Cellgro Mediatech); U-87 was cultured in special DMEM supplemented with F12 50/50 mix (Cellgro Mediatech); COLO-205 was maintained in RPMI 1640 (Cellgro Mediatech); and 786-O VEC (VHL −) and 786-O WT (VHL +)42 were cultured in DMEM : Ham’s F12 supplemented with G418 (200 μg/ml). All cell lines used were Mycoplasma-free, which was confirmed by using the MycoAlert mycoplasma detection kit (Lonza, Rockland, ME, USA).
Before being used, cell lines were validated by STR DNA fingerprinting using the AmpFℓSTR Identifier kit, according to the manufacturer’s instructions (Applied Biosystems, cat. no. 4322288). The STR profiles were compared with known ATCC fingerprints (ATCC.org), the Cell Line Integrated Molecular Authentication database version 0.1.200808 (http://bioinformatics.istge.it/clima/)43 and The University of Texas MD Anderson Cancer Center fingerprint database. The STR profiles of all the cell lines matched the known DNA fingerprints.
Clinical samples information is detailed in Supplementary Material.
Hypoxic experiments were performed in an InVivo2 200 hypoxia workstation (Ruskinn, Inc., Cincinnati, OH, USA), where oxygen concentration was maintained at 1 or 0.2% (in 5% CO2 and 95% N2) for 24, 48, 72 and 96 h. RNA and proteins were collected for further analysis using RT-qPCR and western blot, respectively.
Chemical induction of HIF-1α expression under normoxic conditions was performed using DMOG (Frontier Scientific, Logan, UT, USA). DMOG was added to the growth medium to a final concentration of 500 μM versus of 0.5% DMSO vehicle as control.
RNA extractions, RT-qPCR, real-time PCR controls and reference genes are detailed in Supplementary Material.
Data analysis for RT-qPCR
Data analysis was performed using the Bio-Rad CFX Manager Software (Bio-Rad, Hercules, CA, USA). Only samples with a single clear peak in melting temperature and no expression in nontargeted control cells were considered as positive and specific to be further analyzed. All RT-qPCR data of expressed genes were represented as Cq values for each sample of duplicates. Relative expression, as the fold change or difference,44 was calculated using the 2(−ΔΔCq) formula, in which ΔCq represents the difference in Cq values between the target gene and the mean Cq of the reference gene.45 Each sample, amplified using RT-qPCR, was tested in duplicate. Standard deviation (S.D.) of each target gene was calculated.
Western blot analysis, siRNA transfection and FACS are detailed in Supplementary Material.
HIF-1α-binding site predictions
We scanned the putative promoter sequence (−10 kb upstream and +10 kb downstream of the 5′ end of the annotated T-UCR) for predicted HIF-1α-binding sites generated using the MATCH program and the V$HIF1_Q3 (5′-IndexTermgnnkACGTGcggnn-3′), V$HIF1_Q5 (5′-IndexTermngtACGTGcngb-3′) and V$HIF1_Q6 (5′-IndexTermnRCGTGngn-3′) position weight matrices from the TRANSFAC database, version 9.146 (http://www.gene-regulation.com). The position weight matrices describe the position preferences of different nucleotides in the HIF-binding site.2
ChIP and the promoter reporter assays are detailed in Supplementary Material.
Detection of global O-GlcNAc cellular-protein modifications
To detect O-GlcNAc-modified proteins, we chemically (PUGNAc as a 1,5-hydroximolactone is an inhibitor of various N-acetylhexosaminidases) prevented the removal of O-GlcNAc modifications by the glycosidase MGEA5 (meningioma-expressed antigen 5 (hyaluronidase)).47 PUGNAc treatment was initiated 24 h after siRNA transfection. Fresh complete media containing PUGNAc was added to final concentrations of 0, 40 and 80 μM, respectively, and in duplicate wells. The stock PUGNAc solution (SIGMA; cat. no. 132489-69-1) was prepared following the manufacturer’s instructions and stored at −20 °C. After 72 h under normoxic or hypoxic condition, cells were washed with phosphate-buffered saline (PBS) and later harvested for RNA and protein extractions to determine siRNA knockdown efficiency and to detect changes in O-GlcNAc, respectively. Primary and mouse-specific secondary antibodies for detecting O-GlcNAc were reported by Caldwell et al.22
OGT isoforms 1 and 2, and the retained intron sequence (intron 4) of the OGT gene were all tested for ORF using the NCBI ORF finder (http://www.ncbi.nlm.nih.gov/gorf/gorf.html).
Cells (HCT-116, 2 × 106) were pelleted, and cytoplasmic and nuclear fractions were obtained using the PARIS kit following the manufacturer’s protocol (Ambion RNA, Life Technologies, Carlsbad, CA, USA). Oxygen and Glucose deprivation assays are described in Supplementary Materials.
ncRNA array data analyses
Microarray chips were developed with a total of 481 human UCR sequences as in http://www.soe.ucsc.edu/Bjill/ultra.htm. For each UCR, two 40-mer probes were designed, one corresponding to the sense genomic sequence (named ‘+’) and the other to the complementary sequence (named ‘A+’). The design criteria were as described48 and the detailed array description is in Calin et al.8 Images were quantified using the GenePix Pro 6.0 (Axon Instruments). Raw data were normalized and analyzed in GeneSpring GX 7.3 (Agilent Technologies, Santa Clara, CA, USA). Tumors were normalized using the on-chip and on-gene median normalization of the GeneSpring (Agilent Technologies). Statistical comparisons of tumors and normal tissues were performed by filtering on fold change and then by using the Welch t-test with Benjamini–Hochberg correction for reduction of false-positives. All data were submitted to the ArrayExpress database (accession number E-TABM-184).
All results are based on at least two independent experimental replicates, with error bars representing the standard error of the mean unless stated otherwise. Unpaired two-tailed Student’s t-tests were used to address differences between groups. Additionally, where indicated R-statistic was used (version 2.14.2).
polymerase chain reaction
quantitative reverse transcription PCR
carbonic anhydrase IX
O-linked N-acetylglucosamine (GlcNAc) transferase
hypoxia-induced noncoding ultraconserved transcripts
Von Hippel–Lindau tumor suppressor
fluorescence activated cell sorting
Harris AL . Hypoxia--a key regulatory factor in tumour growth. Nat Rev Cancer 2002; 2: 38–47.
Kulshreshtha R, Ferracin M, Wojcik SE, Garzon R, Alder H, Agosto-Perez FJ et al. A microRNA signature of hypoxia. Mol Cell Biol 2007; 27: 1859–1867.
Chan SY, Zhang YY, Hemann C, Mahoney CE, Zweier JL, Loscalzo J . MicroRNA-210 controls mitochondrial metabolism during hypoxia by repressing the iron-sulfur cluster assembly proteins ISCU1/2. Cell Metab 2009; 10: 273–284.
Favaro E, Ramachandran A, McCormick R, Gee H, Blancher C, Crosby M et al. MicroRNA-210 regulates mitochondrial free radical response to hypoxia and krebs cycle in cancer cells by targeting iron sulfur cluster protein ISCU. PloS One 2010; 5: e10345.
Devlin C, Greco S, Martelli F, Ivan M . miR-210: more than a silent player in hypoxia. IUBMB Life 2011; 63: 94–100.
Huang X, Le QT, Giaccia AJ . MiR-210--micromanager of the hypoxia pathway. Trends Mol Med 2010; 16: 230–237.
Mattick JS . The genetic signatures of noncoding RNAs. PLoS Genet 2009; 5: e1000459.
Calin G, Liu C, Ferracin M, Hyslop T, Spizzo R, Sevignani C et al. Ultraconserved regions encoding ncRNAs are altered in human leukemias and carcinomas. Cancer Cell 2007; 12: 215–229.
Bejerano G, Pheasant M, Makunin I, Stephen S, Kent WJ, Mattick JS et al. Ultraconserved elements in the human genome. Science 2004; 304: 1321–1325.
Bejerano G, Haussler D, Blanchette M . Into the heart of darkness: large-scale clustering of human non-coding DNA. Bioinformatics 2004; 20 (Suppl 1): i40–i48.
Braconi C, Valeri N, Kogure T, Gasparini P, Huang N, Nuovo GJ et al. Expression and functional role of a transcribed noncoding RNA with an ultraconserved element in hepatocellular carcinoma. Proc Natl Acad Sci USA 2011; 108: 786–791.
Scaruffi P, Stigliani S, Coco S, Valdora F, De Vecchi C, Bonassi S et al. Transcribed-ultra conserved region expression profiling from low-input total RNA. BMC Genomics 2010; 11: 149.
Mestdagh P, Fredlund E, Pattyn F, Rihani A, Van Maerken T, Vermeulen J et al. An integrative genomics screen uncovers ncRNA T-UCR functions in neuroblastoma tumours. Oncogene 2010; 29: 3583–3592.
Bejerano G, Lowe CB, Ahituv N, King B, Siepel A, Salama SR et al. A distal enhancer and an ultraconserved exon are derived from a novel retroposon. Nature 2006; 441: 87–90.
Pennacchio LA, Ahituv N, Moses AM, Prabhakar S, Nobrega MA, Shoukry M et al. In vivo enhancer analysis of human conserved non-coding sequences. Nature 2006; 444: 499–502.
Xu J, Wang B, Xu Y, Sun L, Tian W, Shukla D et al. Epigenetic regulation of HIF-1alpha in renal cancer cells involves HIF-1alpha/2alpha binding to a reverse hypoxia-response element. Oncogene 2012; 31: 1065–1072.
Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM et al. The human genome browser at UCSC. Genome Res 2002; 12: 996–1006.
Ivan M, Kondo K, Yang H, Kim W, Valiando J, Ohh M et al. HIFalpha targeted for VHL-mediated destruction by proline hydroxylation: implications for O2 sensing. Science 2001; 292: 464–468.
Nolte D, Muller U . Human O-GlcNAc transferase (OGT): genomic structure, analysis of splice variants, fine mapping in Xq13.1. Mamm Genome 2002; 13: 62–64.
Kreppel LK, Blomberg MA, Hart GW . Dynamic glycosylation of nuclear and cytosolic proteins. Cloning and characterization of a unique O-GlcNAc transferase with multiple tetratricopeptide repeats. J Biol Chem 1997; 272: 9308–9315.
Lubas WA, Frank DW, Krause M, Hanover JA . O-Linked GlcNAc transferase is a conserved nucleocytoplasmic protein containing tetratricopeptide repeats. J Biol Chem 1997; 272: 9316–9324.
Caldwell SA, Jackson SR, Shahriari KS, Lynch TP, Sethi G, Walker S et al. Nutrient sensor O-GlcNAc transferase regulates breast cancer tumorigenesis through targeting of the oncogenic transcription factor FoxM1. Oncogene 2010; 29: 2831–2842.
Mi W, Gu Y, Han C, Liu H, Fan Q, Zhang X et al. O-GlcNAcylation is a novel regulator of lung and colon cancer malignancy. Biochim Biophys Acta 2011; 1812: 514–519.
Lynch TP, Ferrer CM, Jackson SR, Shahriari KS, Vosseller K, Reginato MJ . Critical role of O-GlcNAc transferase in prostate cancer invasion, angiogenesis and metastasis. J Biol Chem 2012; 287: 11070–11081.
Taylor RP, Parker GJ, Hazel MW, Soesanto Y, Fuller W, Yazzie MJ et al. Glucose deprivation stimulates O-GlcNAc modification of proteins through up-regulation of O-linked N-acetylglucosaminyltransferase. J Biol Chem 2008; 283: 6050–6057.
Robinson KA, Weinstein ML, Lindenmayer GE, Buse MG . Effects of diabetes and hyperglycemia on the hexosamine synthesis pathway in rat muscle and liver. Diabetes 1995; 44: 1438–1446.
Butkinaree C, Park K, Hart GW . O-linked beta-N-acetylglucosamine (O-GlcNAc): extensive crosstalk with phosphorylation to regulate signaling and transcription in response to nutrients and stress. Biochim Biophys Acta 2010; 1800: 96–106.
Dong DL, Hart GW . Purification and characterization of an O-GlcNAc selective N-acetyl-beta-D-glucosaminidase from rat spleen cytosol. J Biol Chem 1994; 269: 19321–19330.
Visel A, Prabhakar S, Akiyama JA, Shoukry M, Lewis KD, Holt A et al. Ultraconservation identifies a small subset of extremely constrained developmental enhancers. Nat Genet 2008; 40: 158–160.
Orom UA, Derrien T, Beringer M, Gumireddy K, Gardini A, Bussotti G et al. Long noncoding RNAs with enhancer-like function in human cells. Cell 2010; 143: 46–58.
Ozsolak F, Poling LL, Wang Z, Liu H, Liu XS, Roeder RG et al. Chromatin structure analyses identify miRNA promoters. Genes Develop 2008; 22: 3172–3183.
Love DC, Ghosh S, Mondoux MA, Fukushige T, Wang P, Wilson MA et al. Dynamic O-GlcNAc cycling at promoters of Caenorhabditis elegans genes regulating longevity, stress, and immunity. Proc Natl Acad Sci USA 2010; 107: 7413–7418.
Nott A, Meislin SH, Moore MJ . A quantitative analysis of intron effects on mammalian gene expression. RNA 2003; 9: 607–617.
Ryu WS, Mertz JE . Simian virus 40 late transcripts lacking excisable intervening sequences are defective in both stability in the nucleus and transport to the cytoplasm. J Virol 1989; 63: 4386–4394.
Chang CY, Hong WW, Chong P, Wu SC . Influence of intron and exon splicing enhancers on mammalian cell expression of a truncated spike protein of SARS-CoV and its implication for subunit vaccine development. Vaccine 2006; 24: 1132–1141.
Zhao C, Hamilton T . Introns regulate the rate of unstable mRNA decay. J Biol Chem 2007; 282: 20230–20237.
Wang HF, Feng L, Niu DK . Relationship between mRNA stability and intron presence. Biochem Biophys Res Commun 2007; 354: 203–208.
Gencheva M, Lin TY, Wu X, Yang L, Richard C, Jones M et al. Nuclear retention of unspliced pre-mRNAs by mutant DHX16/hPRP2, a spliceosomal DEAH-box protein. J Biol Chem 2010; 285: 35624–35632.
Gardner LB . Hypoxic inhibition of nonsense-mediated RNA decay regulates gene expression and the integrated stress response. Mol Cell Biol 2008; 28: 3729–3741.
Buchman AR, Berg P . Comparison of intron-dependent and intron-independent gene expression. Mol Cell Biol 1988; 8: 4395–4405.
Le Hir H, Nott A, Moore MJ . How introns influence and enhance eukaryotic gene expression. Trends Biochem Sci 2003; 28: 215–220.
Kibel A, Iliopoulos O, DeCaprio JA, Kaelin WG Jr . Binding of the von Hippel-Lindau tumor suppressor protein to Elongin B and C. Science 1995; 269: 1444–1446.
Romano P, Manniello A, Aresu O, Armento M, Cesaro M, Parodi B . Cell Line Data Base: structure and recent improvements towards molecular authentication of human cell lines. Nucleic Acids Res 2009; 37 Database issue D925–D932.
Safdar A, Abadi A, Akhtar M, Hettinga BP, Tarnopolsky MA . miRNA in the regulation of skeletal muscle adaptation to acute endurance exercise in C57Bl/6J male mice. PLoS One 2009; 4: e5610.
Livak KJ, Schmittgen TD . Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001; 25: 402–408.
Matys V, Fricke E, Geffers R, Gossling E, Haubrock M, Hehl R et al. TRANSFAC: transcriptional regulation, from patterns to profiles. Nucleic Acids Res 2003; 31: 374–378.
Gao Y, Wells L, Comer FI, Parker GJ, Hart GW . Dynamic O-glycosylation of nuclear and cytosolic proteins: cloning and characterization of a neutral, cytosolic beta-N-acetylglucosaminidase from human brain. J Biol Chem 2001; 276: 9838–9845.
Liu CG, Calin GA, Meloon B, Gamliel N, Sevignani C, Ferracin M et al. An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues. Proc Natl Acad Sci USA 2004; 101: 9740–9744.
Dr. Calin is The Alan M. Gewirtz Leukemia and Lymphoma Society Scholar. He is supported also as a Fellow at The University of Texas, MD Anderson Research Trust, as a University of Texas System Regents Research Scholar and by the CLL Global Research Foundation. Work in Dr. Calin’s laboratory is supported in part by the NIH/NCI (CA135444), a Department of Defense Breast Cancer Idea Award, Developmental Research Awards in Breast Cancer, Ovarian Cancer, Brain Cancer, Prostate Cancer, Multiple Myeloma, Leukemia (P50 CA100632) and Head and Neck (P50 CA097007) SPOREs, a SINF MDACC_DKFZ grant in CLL, the Laura and John Arnold Foundation, the RGK Foundation and the Estate of CG Johnson, Jr. Dr. Ling is an Odyssey Fellow, and his work is supported in part by the Odyssey Program and The Estate of CG Johnson, JR at The University of Texas, MD Anderson Cancer Center. Additional support for the research was provided by the Slovenian Research Agency (ARRS) through the Research program P4-0220 to TK and project 30767 to JF. Dr. Ivan is an American Cancer Society Research Scholar (RSG-09-244-01-TBG). Work in Dr. Ivan’s laboratory is also supported by the NIH/NCI (R01 CA155332-01A1). We thank Mei Koh for assistance with the hypoxia experiments. We thank Ashley R. Heath (Sigma-Aldrich, Woodlands, TX, USA) for the siRNA design. STR DNA fingerprinting was performed by the Cancer Center Support grant-funded Characterized Cell Line core, NCI no. CA16672. We thank Ann Sutton (Department of Scientific Publications, MD Anderson Cancer Center) for her help with the editing of this manuscript.
The authors declare no conflict of interest.
Edited by G Melino
Study concept and design: Calin, Ivan and Kunej; development of methodology: Calin, Ivan, Kunej and Davuluri; acquisition of data: Ferdin, Wu, Nishida, Nicoloso, Shah, Devlin, Ling, Shimizu, Kumar, Cortez and Schmittgen; analysis and interpretation of data: Ferdin, Nishida, Voorhoeve, Reginato, Negrini, Davuluri, Kunej, Ivan and Calin; statistical analysis: Ferracin, Bi, Yang, Czerniak, Zhang and Davuluri; administrative, technical or material support: Shimizu, Schmittgen and Reginato; drafting of the manuscript: Ferdin, Nishida, Kunej, Ivan and Calin. All authors critically reviewed the manuscript and approved the final version.
Supplementary Information accompanies this paper on Cell Death and Differentiation website
About this article
Cite this article
Ferdin, J., Nishida, N., Wu, X. et al. HINCUTs in cancer: hypoxia-induced noncoding ultraconserved transcripts. Cell Death Differ 20, 1675–1687 (2013) doi:10.1038/cdd.2013.119
- ultraconserved genes
- colorectal cancer
Wiley Interdisciplinary Reviews: RNA (2019)
Journal of Cellular and Molecular Medicine (2019)
Genome Research (2019)
Rise of Systems Glycobiology and Personalized Glycomedicine: Why and How to Integrate Glycomics with Multiomics Science?
OMICS: A Journal of Integrative Biology (2019)