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. 2017 Dec 4;6:e30433. doi: 10.7554/eLife.30433

LAST, a c-Myc-inducible long noncoding RNA, cooperates with CNBP to promote CCND1 mRNA stability in human cells

Limian Cao 1,, Pengfei Zhang 1,, Jinming Li 2, Mian Wu 1,2,
Editor: Igor Ulitsky3
PMCID: PMC5739540  PMID: 29199958

Abstract

Cyclin D1 is a critical regulator of cell cycle progression and works at the G1 to S-phase transition. Here, we report the isolation and characterization of the novel c-Myc-regulated lncRNA LAST (LncRNA-Assisted Stabilization of Transcripts), which acts as a CCND1 mRNA stabilizer. Mechanistically, LAST was shown to cooperate with CNBP to bind to the 5′UTR of CCND1 mRNA to protect against possible nuclease targeting. In addition, data from CNBP RIP-seq and LAST RNA-seq showed that CCND1 mRNA might not be the only target of LAST and CNBP; three additional mRNAs were shown to be post-transcriptional targets of LAST and CNBP. In a xenograft model, depletion of LAST diminished and ectopic expression of LAST induced tumor formation, which are suggestive of its oncogenic function. We thus report a previously unknown lncRNA involved in the fine-tuned regulation of CCND1 mRNA stability, without which CCND1 exhibits, at most, partial expression.

Research organism: E. coli, Human

eLife digest

Cell division involves a series of steps in which the cell grows, duplicates its contents, and then divides into two. Together these steps are called the cell cycle, and the transition between each step must be controlled to make sure that events take place in the right order. Any loss of control can cause cells to divide in an unrestrained manner, which may lead to cancer.

Proteins called cyclins control progression through the cell cycle. As such, these proteins need to be produced in the correct amounts and at the correct times. Transcription factors are proteins that switch genes on or off to help regulate how much protein is made from those genes. A transcription factor known as c-Myc regulates the expression of the genes that encode the cyclins. Among these genes, one called CCND1 is particularly important because it encodes a protein that controls a crucial transition in the cell cycle: it marks a ‘point of no return’, beyond which cells are committed to dividing.

When a transcription factor switches on a gene, the gene gets copied into a molecule of messenger RNA, which is then translated into protein. But, cells also contain genes that do not code for proteins. Transcription factors can bind to such non-coding genes, leading to the production of so-called long non-coding RNAs (often abbreviated to lncRNAs).

Many lncRNAs can affect the expression of other genes. Cao, Zhang et al. have now asked whether any lncRNAs regulate CCND1 in human cells. The analysis revealed that the transcription factor c-Myc promotes the expression of a previously unidentified lncRNA. Cao, Zhang et al. name this lncRNA LAST, which is officially short for LncRNA-assisted stabilization of transcripts, and show thatit makes the CCND1 messenger RNA more stable. In other words, it makes the messenger RNAs ‘last’ longer in the cell. This in turn, ensures that the cell cycle progresses in the correct manner, allowing cells to complete their division. In the absence of LAST, the CCND1 messenger RNA becomes unstable and as a result the cell cycle does not progress.

Cao, Zhang et al. then explored the role of LAST in cancer cells. When human colon cancer cells that expressed LAST were implanted into mice, they formed tumors. Yet, reducing the expression of LAST in the colon cancer cells made the tumors grow slower.

Future challenges will be to understand how LAST makes messenger RNAs stable and further explore its role in cancer. A better understanding of this molecule could reveal whether it can be used to help doctors diagnose or treat cancers.

Introduction

The oncoprotein c-Myc plays a pivotal role in multiple cellular processes, such as cell cycle progression, malignant transformation, differentiation suppression and apoptosis induction, predominantly through its transcription activity (Seth et al., 1993; Drayton et al., 2003; Wei et al., 2003; Demeterco et al., 2002; Prendergast, 1999; Amati et al., 1992; Lee et al., 1996; Hoffman and Liebermann, 2008). Indeed, as a master transcriptional factor, c-Myc regulates the expression of approximately 10–15% of genes in the genome, including a variety of protein-coding genes (Lin et al., 2012; Nie et al., 2012; Fernandez et al., 2003), such as CDKN1A, CDKN2B, CCND1, CCND2, CDK4 and E2F2 (Adhikary and Eilers, 2005).

Among c-Myc target genes, CCND1 is of particular importance in cell cycle control and is characterized by the dramatic periodicity of the abundance of its protein product cyclin D1 throughout the cell cycle (Sherr, 1995). Cyclin D1 forms a complex with CDK4 or CDK6 and functions as a regulatory subunit whose activity is required for G1/S transition (Sherr, 1995; Resnitzky et al., 1994). Cyclin D1 also interacts with the tumor suppressor pRB1, which in turn positively regulates cyclin D1 expression (DeGregori, 2004). Mutation, amplification and overexpression of CCND1 are frequently observed in cancer and have been reported to contribute to tumorigenesis (Wiestner et al., 2007; Elsheikh et al., 2008; Musgrove et al., 2011). Cyclin D1 is a short-lived protein with a rapid turnover rate (~24 min) due to degradation by the ubiquitin-proteasome system (Diehl et al., 1998; Diehl et al., 1997). While early studies showed that the Skp2 F-box protein is involved in cyclin D1 degradation (Yu et al., 1998), a recent study has identified two additional F-box proteins that play important roles in targeting cyclin D1 for proteasome degradation (Lin et al., 2006; Okabe et al., 2006).

c-Myc can upregulate or downregulate expression of cyclin D1 in a context-dependent manner. On the one hand, c-Myc, together with Max, a co-transcription factor, activates CCND1 transcription through an E box located at −558 nt in its promoter (Kress et al., 2015; Yu et al., 2005; Guo et al., 2011). On the other hand, simultaneous overexpression of c-Myc and ZO-2 enhances repression of the CCND1 promoter through the E box in MDCK cells (Gonzalez-Mariscal et al., 2009). In addition, c-Myc has been reported to repress the cyclin DI promoter and antagonize USF-mediated transactivation in BALB/c-3T3, Rat6 and rat embryo fibroblasts (Philipp et al., 1994). In addition to c-Myc, multiple transcription factors, including AP-1, NF-κB, E2F and Oct-1, can bind to their respective CCND1 promoters and regulate its expression (Guo et al., 2011). CCND1 can also be regulated epigenetically through histone modifications; GATA3 cooperates with PARP1 to regulate CCND1 transcription by modulating histone H1 incorporation (Shan et al., 2014). Moreover, post-transcriptional mechanisms are also involved in the regulation of CCND1, as exemplified by MYF5-mediated enhancement in CCND1 mRNA translation, which contributes to early myogenesis (Panda et al., 2016). Mutations in CCND1 leading to stable truncated transcripts are associated with increased cell proliferation and shortened survival of cancer patients (Wiestner et al., 2007).

Long noncoding RNAs (lncRNAs), which are defined as transcripts that are longer than 200 nucleotides and lack protein coding capacity, are emerging as important regulators of biological processes, including regulation of gene expression at multiple levels, such as chromatin remodeling, transcription, and post-transcriptional modulation (Derrien et al., 2012; Iorio and Croce, 2012; Bonasio and Shiekhattar, 2014; Wilusz et al., 2008). Genome-wide studies have shown that c-Myc transcriptionally regulates many lncRNA genes, such as PVT1, the CCAT family, and MYCLos, whereas a number of lncRNAs have been demonstrated to be important components of the c-Myc-mediated signaling network (Colombo et al., 2015; Nissan et al., 2012; Ling et al., 2013; Kim et al., 2015a; Kim et al., 2015b). Nevertheless, whether lncRNAs participate in the regulation of CCND1 remains to be fully studied.

Here, we report the isolation and characterization of the novel c-Myc regulated LAST, which acts as a CCND1 mRNA stabilizer and without which CCND1 mRNA becomes unstable and cell cycle arrest occurs in the G1 phase. Mechanistically, LAST cooperates with CNBP, a single-stranded DNA/RNA-binding factor, to bind to the 5’ untranslated region of CCND1 messenger RNA, possibly to protect against nuclease degradation. This report describes a model by which lncRNA stabilizes mRNA post-transcriptionally via 5’-end protection.

Results

Identification of LAST, a c-Myc-responsive long noncoding RNA that promotes cell proliferation

To identify novel functions of c-Myc-regulated long non-coding RNAs, doxycycline-treated or untreated P493-6 cells carrying a c-Myc tet-off system (Kim et al., 2007) were used to analyze the lncRNA expression profile via long non-coding RNA microarray analysis (Supplementary file 1, GSE106916). We selected five significantly c-Myc-downregulated lncRNAs (fold change above 8, P-value below 0.01) that were identified by the lncRNA microarray. Two of the five lncRNAs, namely, lncRNA-51 and lncRNA-52, along with CDK4 (positive control) were found to be downregulated when c-Myc expression was suppressed by doxycycline treatment (Figure 1A). Of these two c-Myc responsive lncRNAs, lncRNA-52 (RP11-660L16.2, ENST00000529369) was chosen for further investigation because knockdown of this lncRNA (Figure 1B) showed a significant reduction in colony formation (Figure 1C and D). lncRNA-52 is located approximately 1.8 Mb downstream of the cyclin D1/CCND1 gene in a head-to-tail orientation (Figure 1—figure supplement 1A). As will be shown in the following sections, this lncRNA is able to promote the stability of mRNA transcripts, including CCND1 mRNA; we therefore named it LAST (LncRNA-Assisted Stabilization of Transcripts).

Figure 1. LAST is positively regulated by c-Myc.

(A) P493-6 cells carrying a c-Myc tet-off system were treated with doxycycline (1 μg/mL) for 24 hr. The levels of five lncRNAs (lncRNA-5639,–51, −52,–5630 and −5690) and the positive control CDK4 were assessed by real-time RT–PCR analysis. Data shown are the mean ± SD (n = 3; ***p<0.001, two-tailed t-test). Cell lysates were also analyzed by western blotting with the indicated antibodies to ensure that gene expression was controlled by c-Myc. (B) HCT116 cells were infected with lentiviruses expressing control shRNA (sh-ctrl), shRNA-1,–2 against lncRNA-52 or shRNA-1,–2 against lncRNA-51, as indicated. The lentivirus-mediated gene knockdown efficiencies for both lncRNA-52 and lncRNA-51 were analyzed by real-time RT–PCR. Data shown are the mean ± SD (n = 3; **p<0.01, ***p<0.001, two-tailed t-test). (C) Colonies of the above cells were stained with crystal violet and photographed after 14 days of incubation. (D) The number of colonies was counted and plotted in columns. (E) Total RNA from the indicated cell lines was subjected to northern blot analysis to determine the molecular size of LAST. (F) Single molecule RNA FISH detecting endogenous LAST molecules (green) in HCT116 and H1299. Chromosomal DNA (red) was stained with PI. (G) HCT116 and H1299 cells were fractionated into cytoplasmic and nuclear extracts. Total RNA extracted from each fraction was analyzed by real-time RT–PCR. Data shown are the mean ± SD (n = 3). Actin and U1 were used as markers for the cytoplasmic and nuclear fractions, respectively. (H) The LAST transcript copy numbers per cell in HAFF, IMR90, MCF10A, HCT116, MCF7 and H1299 cells were determined by absolute quantitative PCR (qPCR). Data shown are the mean ± SD (n = 3). (I) HCT116, H1299 and MCF10A cells were infected with lentiviruses expressing control shRNA or c-Myc shRNA. Ninety-six hours after infection, total RNA and cell lysates were analyzed by real-time RT-PCR and western blotting, respectively. Data shown are the mean ± SD (n = 3; **p<0.01, ***p<0.001, two-tailed t-test). (J) HCT116, H1299 and MCF10A cells were transfected with empty vector or FLAG-c-Myc. Twenty-four hours after transfection, total RNA was extracted from these cells and subjected to real-time RT-PCR analysis. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). Cell lysates were also analyzed by western blotting using the indicated antibodies. (K) Schematic representation of putative c-Myc binding sites around the LAST gene, predicted c-Myc binding fragments, qPCR-amplified fragments from the ChIP assay and fragments used in the luciferase reporter assay (upper panel). Lysates from HCT116 cells were subjected to the ChIP assay with a normal rabbit IgG or c-Myc antibody. ChIP products were amplified by qPCR with the indicated pairs of primers (Table 1). Data shown are the mean ± SD (n = 3; *p<0.05, two-tailed t-test) (lower panel). (L) Schematic diagram of the luciferase reporter systems constructed to assess LAST promoter activity. The indicated pGL3-based luciferase reporter constructs were generated to examine the transcriptional activities of two putative c-Myc binding sites, BS2 and BS3, in response to c-Myc induction. BS2M and BS3M indicate their corresponding mutant binding sites, which are written in black in the open boxes (upper panel). HCT116 cells were co-transfected with either FLAG-c-Myc or the control vector plus the indicated reporter constructs and Renilla luciferase plasmid. Twenty-four hours after transfection, reporter activity was measured and plotted after normalizing with respect to Renilla luciferase activity. Data shown are the mean ± SD (n = 3; *p<0.05, two-tailed t-test) (lower panel).

Figure 1—source data 1. Source data for Figure 1A, B, D, G, H, I, J, K and L.
DOI: 10.7554/eLife.30433.006

Figure 1.

Figure 1—figure supplement 1. LAST is positively regulated by c-Myc.

Figure 1—figure supplement 1.

(A) Schematic representation of the gene locations of CCND1 and LAST on chromosome 11. (B) Single molecule RNA FISH was used to detect endogenous LAST molecules (green) in H1299 expressing control shRNA, LAST shRNA-1 or −2. Chromosomal DNA (red) was stained with PI. (C) HCT116 cells were treated as follows: mock (lane1); thymidine/TDR (2.5 mM) for 16 hr, then released for 9 hr, followed by nocodazole (50 ng/mL) for 16 hr (lane 2); mimosine (200 μM) for 24 hr (lane 3); TDR for 16 hr, then released for 9 hr, followed by TDR again for 16 hr (lane 4); and TDR for 16 hr, then released for 9 hr, followed by TDR again for 16 hr, then released for 3 hr (lane 5). Total RNA was subjected to real-time RT-PCR to detect the LAST levels in their respective cell cycle phase. Western blotting was used to analyze the indicated protein level. Data shown are the mean ± SD (n = 3).
Figure 1—figure supplement 2. Uncropped images of blots.

Figure 1—figure supplement 2.

Red boxes indicate the cropped regions.

To verify the existence of endogenousLAST and to determine its molecular size, northern blot analysis was performed. A band of approximately 700 nt in length was detected in both P493-6 and H1299 cells, but was absent in P493-6 cells treated with doxycycline, which suppresses c-Myc expression (Figure 1E). The apparent size of LAST was the same as predicted by the UCSC (University of California, Santa Cruz) Genome Browser, suggesting that LAST is a full-length transcript. To investigate the cellular compartment in which LAST is located, single molecule RNA fluorescent in situ hybridization (FISH) was performed in both HCT116 and H1299 cells. As shown in Figure 1F, LAST was predominantly localized in the cytosol. Cytosol localization of LAST was also confirmed by determining the levels of LAST in different sub-cellular fractions (Figure 1G). Moreover, the signal intensity of LAST was reduced in LAST-depleted cells (Figure 1—figure supplement 1B). It has been reported that lncRNAs are often present at relatively low copy numbers; hence, we measured the LAST transcript copy number per cell in various cell lines, including the normal cell lines HAFF, IMR90, and MCF10A and tumor cell lines HCT116, MCF7 and H1299. The LAST copy number was higher in tumor cells than in normal cells (Figure 1H).

Lentivirus-mediated gene knockdown of c-Myc decreased whereas ectopic expression of c-Myc increased LAST expression in HCT116, H1299 and MCF10A cells (Figure 1I and J). Furthermore, the levels of LAST and c-Myc appeared to be notably synchronous during cell cycle progression (Figure 1—figure supplement 1C). In particular, the c-Myc and LAST levels were decreased in G2/M (lane 2), followed by a rapid increase in the G1 phase (lane 3). These data suggest that LAST expression is positively regulated by c-Myc.

We next explored whether c-Myc regulates LAST expression at the transcriptional level. We first inspected the genomic sequence around the LAST gene using the JASPAR database (Mathelier et al., 2016). Six putative c-Myc binding sites (BS1, BS2, BS3, BS4, BS5 and BS6) were identified (Figure 1K, upper panel). Furthermore, we analyzed the genomic sequence around the LAST gene using the ENCODE database. Three fragments (F1, F2 and F3) were predicted to be recognized by c-Myc (Figure 1K, upper panel). The chromatin immunoprecipitation (ChIP) assay determined the association of c-Myc with chromatin fragments corresponding to the BS2 and BS3 sites (within F2 fragment) among all examined fragments (Figure 1K, lower panel). We further evaluated whether BS2 and BS3 conferred c-Myc-dependent transcriptional activity. DNA fragments containing wild-type BS2 and BS3 or their corresponding mutant binding sites were inserted into the promoter region of a firefly luciferase reporter plasmid (Figure 1L, upper panel). Luciferase expression from the reporter containing an individual BS2 or BS3 site was indeed induced by ectopic expression of c-Myc (Figure 1L, lower panel). By contrast, mutant BS2M and BS3M sites showed no response to c-Myc induction (Figure 1L, lower panel). These data demonstrate that c-Myc transactivates LAST.

LAST promotes G1/S transition and upregulates cyclin D1/CCND1

Knockdown of LAST results in reduced colony formation (Figure 1C), indicating that LAST normally promotes cell proliferation. To examine how LAST affects cell growth, the cell cycle phase distribution was analyzed by flow cytometric analysis. Knockdown of LAST caused a decrease in the percentage of cells in the S and G2/M phases and an increase in the percentage of cells in the G1 phase (Figure 2—figure supplement 1A and B), indicating that LAST knockdown prevents cell passage from the G1 phase into S phase. As a result, LAST was shown to promote G1/S phase transition.

Cell cycle regulation is controlled by many factors. To define which factor(s) were involved in LAST-mediated regulation, the mRNA levels of G1-related cyclins and CDKs genes were selected for comparison in HCT116 cells before and after LAST gene knockdown. Among all of the mRNAs examined, only the CCND1 mRNA level was significantly decreased (Figure 2A). Among all of the cyclins or CDKs examined, only cyclin D1 was shown to be downregulated when LAST was depleted (Figure 2B). The lncRNA PVT1 is known to be a c-Myc regulated lncRNA that is involved in c-Myc stability and activity (Colombo et al., 2015). However, unlike PVT1, we found that LAST, which is also regulated by c-Myc (Figure 1A), does not affect c-Myc stability since knockdown of LAST did not change c-Myc expression at either the mRNA or protein levels (Figure 2A and B). The effect of LAST on cyclin D1/CCND1 was further verified in normal HAFF cells and tumor H1299 and HCT116 cells. Depletion of LAST decreased whereas over-expression of LAST increased cyclin D1/CCND1 expression at both the mRNA and protein levels (Figure 2C and D).

Figure 2. LAST accelerates G1/S transition and upregulates cyclin D1/CCND1.

(A) HCT116 cells were infected with lentiviruses expressing control shRNA, LAST shRNA-1 or −2. Ninety-six hours after infection, total RNA was extracted and the transcript levels for LAST, CCND1, CCNE1, CDK2, CDK4 and c-Myc were analyzed by real-time RT-PCR. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, ***p<0.001, two-tailed t-test). (B) Cell lysates prepared as described above (Figure 2A) were analyzed by western blotting to examine GAPDH, cyclin D1, cyclin E1, Actin, CDK2, CDK4 and c-Myc expression. (C) HAFF and H1299 cells were infected with lentiviruses expressing control shRNA or LAST shRNA. Ninety-six hours after infection, total RNA was analyzed by real-time RT-PCR to detect the level of LAST to determine its knockdown efficiency (lower panel). Total RNA was also analyzed by real-time RT-PCR to detect the level of CCND1 mRNA and by western blotting to examine the cyclin D1 protein level (upper panel). Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01). (D) HCT116, H1299 and HAFF cells were infected with lentiviruses expressing control RNA or LAST. Ninety-six hours after infection, total RNA was analyzed by real-time RT-PCR to detect successful expression of LAST (lower panel). Total RNA was also analyzed by real-time RT-PCR to detect the level of CCND1 mRNA and by western blotting to examine the cyclin D1 protein level (upper panel). Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, ***p<0.001, two-tailed t-test).

Figure 2—source data 1. Source data for Figure 2A, C and D.
DOI: 10.7554/eLife.30433.010

Figure 2.

Figure 2—figure supplement 1. LAST knockdown prevents cell passage from the G1 phase into S phase.

Figure 2—figure supplement 1.

(A) HCT116 cells were individually infected with lentiviruses expressing LAST shRNA-1,–2 and non-targeting control shRNA. Ninety-six hours after infection, cells were stained with PI, followed by flow cytometric analysis of the cell cycle phase distribution. (B) The percentage numbers of cells from (A) in the G1, S or G2/M phase were analyzed by FlowJo 7.6 software. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). (C) HCT116 cells were infected with lentiviruses expressing control shRNA, LAST shRNA-1 or −2. Ninety-six hours after infection, total RNA was extracted and the transcript levels of DHCR7 and NADSYN1 were analyzed by real-time RT-PCR. Data shown are the mean ± SD (n = 3; two-tailed t-test). Cell lysates were analyzed by western blotting to examine actin, DHCR7 and NADSYN1 expression. (D) HCT116 cells expressing control shRNA or LAST shRNA-1 were separately transfected with either mock control or shRNA-resistant LAST. Twenty-four hours after transfection, total extracted RNA was subjected to real-time RT-PCR to analyze the mRNA level of CCND1. Data shown are the mean ± SD (n = 3; **p<0.01, two-tailed t-test). (E) Cell lysates from cells treated as described in Figure 2—figure supplement 1B were analyzed by western blotting to detect the cyclin D1 protein level.
Figure 2—figure supplement 2. Uncropped images of blots.

Figure 2—figure supplement 2.

Red boxes indicate the cropped regions.

To test if the function of LAST is mediated through an effect on the adjacent genes, we checked the shRNA-mediated LAST knockdown effect on the two adjacent genes DHCR7 and NADSYN1 (Figure 1—figure supplement 1A) and found that LAST showed no effect on either the mRNA or protein levels of those two genes (Figure 2—figure supplement 1C). Furthermore, we introduced shRNA-resistant LAST into LAST depleted cells, and as shown in Figure 2—figure supplement 1D and E, both the CCND1 mRNA and protein levels were rescued. This result excludes off-target effects of LAST shRNA knockdown.

LAST cooperates with CNBP to regulate CCND1 mRNA stability

To investigate how LAST affects the CCND1 mRNA level, we first examined whether LAST regulates the CCND1 mRNA transcription process. The levels of both CCND1 pre-mRNA and mature mRNA were examined by primers against CCND1 mRNA intron- or exon-specific regions in HCT116 cells treated with and without LAST knockdown. The levels of CCND1 pre-mRNA containing four intronic regions were found to remain unaltered between control and LAST knockdown cells, whereas the levels of mature spliced CCND1 mRNA containing 5’UTR, CDS (coding sequences) and 3’UTR regions were greatly reduced upon LAST depletion (Figure 3—figure supplement 1A and B). These results suggest that LAST may post-transcriptionally regulate CCND1 mRNA. To evaluate the effect of LAST on the stability of CCND1 mRNA, HCT116 cells were treated with actinomycin D, which measures the decay of pre-existing mRNA. Knockdown of LAST resulted in a decrease of the half-life of CCND1 mRNA from 5 hr to 3 hr (Figure 3A), whereas over-expression of LAST increased its half-life from 5 hr to 9 hr (Figure 3B), indicating that LAST stabilizes CCND1 mRNA. To determine whether LAST interacts with CCND1 mRNA, we performed a biotinylated oligonucleotide pull-down assay, and as shown in Figure 3C, endogenous CCND1 mRNA but not CCNB1 mRNA co-precipitated with LAST, indicating an association between LAST and CCND1 mRNA. However, by careful inspection, we found there was no complementary base pairing between LAST and CCND1 mRNA. We therefore hypothesized that some protein(s) may mediate this binding. Proteins pulled down by LAST were separated by SDS PAGE, and a unique band with a molecular weight of approximately 20 kDa was revealed and identified as CNBP by mass spectrometry (Figure 3—figure supplement 1C, left panel). CNBP has a preference for binding single-stranded DNA and RNA (Flink and Morkin, 1995) and has been reported to function in the translation of ornithine decarboxylase mRNA (Sammons et al., 2010). To validate the MS Spectro result, we performed a LAST pull-down assay. A biotin-labeled antisense DNA probe against LAST pulled down CNBP, but not cyclin D1 (Figure 3—figure supplement 1C, right panel). To further demonstrate that CNBP can bridge CCND1 mRNA and LAST, we first pulled down CCND1 mRNA using a biotinylated antisense DNA probe as bait; both CNBP and LAST were coprecipitated (Figure 3D). The RIP assay further concluded that CNBP interacts with both CCND1 mRNA and LAST (Figure 3E). These data demonstrate that CNBP acts as a mediator for LAST and CCND1 mRNA binding. As shown in Figure 3F, CNBP knockdown in HCT116 led to a decrease in both the mRNA and protein levels of cyclin D1/CCND1. The effect of CNBP on the stability of CCND1 mRNA was evaluated in HCT116 cells treated with actinomycin D. The half-life of CCND1 mRNA was reduced from 5 hr to 3 hr as CNBP was depleted (Figure 3G), further demonstrating that CNBP prolongs the CCND1 mRNA half-life. Because CNBP predominantly resides in the cytosol, we investigated whether the association of CCND1 mRNA with LAST via CNBP only occurs in the cytosol. Using a LAST and CCND1 mRNA pull-down assay, we found that CNBP was co-precipitated by either LAST or CCND1 mRNA in the cytoplasm, but not the nucleus (Figure 3—figure supplement 1D). HNRNPK was used as a nuclear marker. Moreover, knockdown of CNBP was shown to result in decreased levels of CCND1 mRNA (Figure 3F). Further investigation revealed that knockdown of CNBP affected the level of mature CCND1 mRNA, but not unspliced CCND1 pre-mRNA, indicating that the protective role of CNBP in mature CCND1 mRNA stability occurred in the cytosol since nuclear unspliced CCND1 pre-mRNA was not affected when CNBP was silenced (Figure 3—figure supplement 1E). To further confirm that LAST affects CCND1 mRNA stability through CNBP, we knocked down CNBP in HCT116 cells. As shown in Figure 3—figure supplement 1F, the increased expression of CCND1 mRNA caused by over-expression of LAST was diminished when CNBP was depleted (lanes 2 vs. 4). Thus, our hypothesis is that LAST affects CCND1 mRNA via CNBP. Knockdown of LAST resulted in no change in CNBP at either the RNA or protein levels (Figure 3H), which suggests that LAST affects CCND1 mRNA not according to the quantity of CNBP, but rather by the association of CNBP and CCND1 mRNA. It was therefore expected that knockdown of CNBP would reduce the association between LAST and CCND1 mRNA. This was indeed the case. An RNA pull-down experiment was performed starting with the same amount of CCND1 mRNA, and less LAST was co-precipitated as CNBP was depleted (Figure 3I). Similarly, when we pulled down the same amount of CCND1 mRNA, less co-precipitated CNBP was detected as LAST was silenced. As a negative control, the RNA-binding protein HuR remained unchanged after LAST was knocked down (Figure 3J). These data suggest that LAST cooperates with CNBP to regulate CCND1 mRNA stability.

Figure 3. LAST stabilizes CCND1 mRNA via CNBP.

(A) HCT116 cells expressing control shRNA, LAST shRNA-1 or −2 were treated with actinomycin D (1 μg/mL) for the indicated periods of time. Total RNA was purified and then analyzed by real-time RT-PCR to examine the mRNA half-life of CCND1. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, ***p<0.001, two-tailed t-test). (B) HCT116 cells expressing control RNA or LAST were treated with actinomycin D (1 μg/mL) for the indicated periods of time. Total RNA was extracted and then analyzed by real-time RT-PCR to examine the mRNA half-life of CCND1. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). (C) HCT116 cell lysates were incubated with in vitro synthesized biotin-labeled sense or antisense DNA probes against LAST for the biotinylated oligonucleotide pull-down assay. The precipitates from the pull-down were analyzed by real-time RT-PCR to detect the interacting mRNAs. Data shown are the mean ± SD (n = 3; **p<0.01, ***p<0.001, two-tailed t-test). (D) HCT116 cell lysates were incubated with in vitro synthesized biotin-labeled sense or antisense DNA probes against CCND1 mRNA for the biotin pull-down assay. The precipitates from the pull-down underwent real-time RT-PCR and western blot analyses to examine the levels of indicated RNAs and protein CNBP, respectively. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). (E) HCT116 cell lysates were immunoprecipitated with an antibody against CNBP or normal mouse IgG2a. Precipitated samples were analyzed by western blotting to ensure successful precipitation of CNBP and by real-time RT-PCR to detect the indicated coprecipitated RNAs. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). (F) HCT116 cells were infected with lentiviruses expressing control shRNA or CNBP shRNA. Ninety-six hours after infection, total RNA was subjected to real-time RT-PCR to compare the levels of CCND1 mRNA. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). Cell lysates were also analyzed by western blotting with the indicated antibodies. (G) HCT116 cells expressing control shRNA or CNBP shRNA were treated with actinomycin D (1 μg/mL) for the indicated periods of time. Total RNA was then analyzed by real-time RT-PCR to examine the mRNA half-life of CCND1. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). (H) HCT116 cells were infected with lentiviruses expressing control shRNA, LAST shRNA-1 or −2. Ninety-six hours after infection, total RNA was subjected to real-time RT-PCR to compare the levels of CNBP. Data shown are the mean ± SD (n = 3; **p<0.01, two-tailed t-test). Cell lysates were also analyzed by western blotting to examine actin and CNBP expression. (I) Cell lysates of HCT116 cells expressing control shRNA or CNBP shRNA were incubated separately with in vitro synthesized biotin-labeled sense or antisense DNA probes against CCND1 mRNA for the biotinylated oligonucleotide pull-down assay. The pull-down products were subjected to real-time RT-PCR analysis to examine the indicated RNA levels. Cell lysates from HCT116 treated with or without CNBP shRNA knockdown were subjected to western blotting to ensure knockdown of CNBP. Data shown are the mean ± SD (n = 3; *p<0.05, ***p<0.001, two-tailed t-test). (J) Cell lysates of HCT116 cells expressing control shRNA or LAST shRNA-1 were incubated with in vitro synthesized biotin-labeled sense or antisense DNA probes against CCND1 mRNA for the biotin pull-down assay, followed by real-time RT-PCR analysis to examine the indicated RNA levels. Pull-down products were also subjected to western blotting with the indicated antibodies and real-time RT-PCR. Data shown are the mean ± SD (n = 3; **p<0.01, two-tailed t-test).

Figure 3—source data 1. Source data for Figure 3A, B, C, D, E, F, G, H, I and J.
DOI: 10.7554/eLife.30433.014

Figure 3.

Figure 3—figure supplement 1. LAST stabilizes CCND1 mRNA via CNBP.

Figure 3—figure supplement 1.

(A) HCT116 cells were infected with lentiviruses expressing control shRNA, LAST shRNA-1 or −2. Ninety-six hours after infection, total RNA was analyzed by real-time RT-PCR with the indicated primers. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, ***p<0.001, two-tailed t-test). RT-PCR was performed using specific primer pairs against various regions of the CCND1 pre-mRNA transcript, including the 5’-UTR, coding region, 3’-UTR and intronic regions-1,–2, −3 and −4 (Figure 3—figure supplement 1B), to measure the level of the CCND1 transcript. (B) Schematic illustration showing the different parts of CCND1 mRNA, including the 5’UTR, 3’UTR, intron 1, intron 2, intron 3 and intron 4 regions. (C) HCT116 cell lysates were incubated with in vitro synthesized biotin-labeled sense or antisense DNA probes against LAST for the biotin-labeled RNA pull-down assay. Precipitated complexes from the pull-down assay were separated by SDS-PAGE and visualized by Coomassie brilliant blue staining. Gel-separated proteins were analyzed by MALDI mass spectrometry. A putative RNA-binding protein is indicated. Pull-down products were analyzed by western blotting with indicated antibodies. (D) Cytoplasmic and nuclear extracts from HCT116 cells were incubated with a LAST antisense DNA probe or CCND1 antisense DNA probe. Precipitated complexes from the pull-down assay were analyzed by western blotting with the indicated antibodies. (E) HCT116 cells were infected with lentiviruses expressing control shRNA or CNBP shRNA. Ninety-six hours after infection, total RNA was analyzed by real-time RT-PCR with the indicated primers against their respective regions. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). (F) HCT116 cells expressing control shRNA or CNBP shRNA were separately infected with lentiviruses expressing either mock control or LAST. Ninety-six hours after injection, the total RNA extracted was subjected to real-time RT-PCR to analyze the mRNA level of CCND1, and cell lysates were analyzed by western blotting to detect the CNBP protein level.
Figure 3—figure supplement 2. Uncropped images of blots.

Figure 3—figure supplement 2.

Red boxes indicate the cropped regions.

Both LAST and CCND1 mRNA bind to CNBP through their G-rich motifs

To describe a detailed CNBP, LAST and CCND1 mRNA binding mechanism, we mapped the LAST and CNBP binding sites on CCND1 mRNA by RNA pull-down using different in vitro biotin-labeled fragments (Figure 4A, upper panel). We found that the 5’UTR but not 3’UTR-1,–2 and −3 of CCND1 mRNA was able to bind LAST and CNBP (Figure 4A and B), indicating that LAST and CNBP bind to the 5’ region of CCND1 mRNA. To further determine whether LAST and CNBP bind to the CCND1 mRNA 5’UTR to enhance its stability, two CCND1 expression constructs were generated, as shown in Figure 4—figure supplement 1A and B. One construct contained the CCND1 coding region (CD) plus the 5’UTR and the other contained the CD alone. The expression plasmid plus LAST and CNBP or plasmid alone was individually transfected into 293T cells. Actinomycin D was added to measure the mRNA decay rate. The half-life of ectopically expressed CCND1 mRNA lacking the 5’UTR was not altered by the presence or absence of LAST and CNBP (Figure 4—figure supplement 1A). By contrast, the half-life of CCND1 mRNA bearing 5'-UTRs was extended from 4 hr in the absence of LAST and CNBP to 9 hr in the presence of LAST and CNBP, indicating that LAST and CNBP enhanced CCND1 mRNA stability via its 5’UTR (Figure 4—figure supplement 1B). In addition, we performed CNBP RIP sequencing, and an enrichment peak at the CCND1 5’UTR was observed (Figure 4—figure supplement 1C). This was consistent with the previous conclusion from Figure 4B. Thus, our hypothesis is that CNBP binds both CCND1 mRNA and LAST. We again examined whether LAST, the 5'-UTR of CCND1 mRNA and CNBP form a ternary complex by using a sequential immuno-precipitation assay (Figure 4—figure supplement 2A). By using an anti-FLAG antibody against FLAG–CNBP, both the biotin-labeled 5'-UTR of CCND1 mRNA and LAST were pulled down in an initial immunoprecipitation assay (Figure 4C, panel 1 and 3). The immunocomplexes were eluted and were subsequently precipitated by streptavidin sepharose beads against the biotin-labeled 5'-UTR of CCND1 mRNA. LAST and CNBP were present in the streptavidin-biotin precipitates (Figure 4C, panel 5 and 6), indicating that these three components indeed form a ternary complex.

Figure 4. CNBP binds to LAST and CCND1 mRNA via their G-rich motifs.

(A) Schematic illustration showing different parts, including the 5’UTR, CDS, 3’UTR-1, 3’UTR-2 and 3’UTR-3, in CCND1 mRNA (upper panel). HCT116 cell lysates were incubated with in vitro synthesized biotin-labeled CCND1 5’UTR as well as 3’UTR-1,–2, and −3 (upper panel), followed by RNA pull-down. Cell lysates incubated with no RNA were used as negative controls. Pull-down products were subjected to real-time RT-PCR. Data shown are the mean ± SD (n = 3; **p<0.01, two-tailed t-test) (lower panel). (B) The pull-down products from above were analyzed by western blotting with the indicated antibodies. (C) In-vitro synthetic biotin-labeled CCND1 5’UTR and unlabeled LAST plus Flag-CNBP were incubated for 3 hr at 4°C. The mixtures were first immunoprecipitated with M2 beads, followed by elution with 3 × FLAG peptides. Ten percent of the eluent was analyzed by western blotting or RT-PCR. The rest of the eluent was further immunoprecipitated with streptavidin beads. The immunoprecipitates were then washed. After elution, 10% of the eluent was analyzed by western blotting. Ninety percent of the eluent was used for real-time RT-PCR analysis. (D) A schematic illustration of two G-rich regions in the CCND1 5’UTR. Electrophoretic mobility shift assay (EMSA) was performed to detect the CNBP binding activity to its targeted G-rich region 1 and 2. (E) A schematic illustration of six G-rich regions in LAST. An electrophoretic mobility shift assay (EMSA) was performed to detect the CNBP binding activity to its targeted G-rich motif A, B, C, D, E and F. (F) HCT116 cells were infected with lentiviruses expressing either control RNA; wild-type LAST; LAST individually mutated at G-rich-A, G-rich-C, G-rich-D and G-rich-F sites; or LAST mutated at the four G-rich-A, C, D and F sites combined. Ninety-six hours after infection, total RNA was analyzed by real-time RT-PCR to detect the successful expression levels of LAST or mutant LAST. Data shown are the mean ± SD (n = 3; **p<0.01, two-tailed t-test). (G) Total RNA of HCT116 cells separately expressing exogenous control RNA; wild-type LAST; LAST with a single mutation at G-rich-A, G-rich-C, G-rich-D or G-rich-D; and LAST with four mutations combined were analyzed by real-time RT-PCR to detect the mRNA level of CCND1. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, ***p<0.001, two-tailed t-test).

Figure 4—source data 1. Source data for Figure 4A, F and G.
DOI: 10.7554/eLife.30433.019

Figure 4.

Figure 4—figure supplement 1. CNBP binds to CCND1 mRNA 5'UTR.

Figure 4—figure supplement 1.

(A) 293T cells were either transfected with PCDH-CCND1-CD alone or co-transfected with PCDH-CCND1-CD plus LAST and FLAG-CNBP. Twenty-four hours later, cells were treated with actinomycin D (1 μg/mL) for the indicated periods of time. Total RNA was purified and then analyzed by real-time RT-PCR to examine the mRNA half-life of CCND1. Data shown are the mean ± SD (n = 3). (B) 293T cells were either transfected with PCDH-CCND1-CD alone or co-transfected with PCDH-CCND1-5’UTR-CD plus LAST and FLAG-CNBP. Twenty-four hours later, cells were treated with actinomycin D (1 μg/mL) for the indicated periods of time. Total RNA was purified and then analyzed by real-time RT-PCR to examine the mRNA half-life of CCND1. Data shown are the mean ± SD (n = 3; *p<0.05, **p<0.01, two-tailed t-test). (C) Visualization analysis of the CNBP RIP-seq peaks of the CCND1 5’UTR was performed by IGV.
Figure 4—figure supplement 2. Both LAST and CCND1 mRNA bind to CNBP.

Figure 4—figure supplement 2.

(A) A schematic illustration of the two-step immunoprecipitation/pulldown assay to determine the interactive mode for CCND1, CNBP and LAST. (B) CNBP RIP sequencing enriched peaks were analyzed, and all those containing a series of G-rich motifs were selected. For a given G-rich motif, the average proportion of motif-containing sequences in 1000 randomly generated DNA sequence samples was used as a negative control. The proportions of G-rich motif-containing peaks in all RIP peak sequences and the average proportion of G-rich motif-containing sequences in 1000 random samples are shown in the bar graph (***p<0.001, U-test). (C) In vitro transcribed biotin-labeled LAST or the biotin-labeled CCND1 5’UTR was separately incubated with lysates extracted from HEK293T cells expressing full-length CNBP or the indicated CNBP deletion mutants for 3 hr. The biotin pull-down assay was then carried out.
Figure 4—figure supplement 3. Uncropped images of blots.

Figure 4—figure supplement 3.

Red boxes indicate the cropped regions.

CNBP prefers to bind G-rich motifs, especially the GGAG core (Armas et al., 2008; Benhalevy et al., 2017). We checked the proportion of G-rich motifs in all of the peak sequences from the CNBP RIP samples. Nearly sixty percent of the CNBP enriched sequences contained the GGAG motif, and more than ninety percent of the peak sequences contained a GGR motif (Figure 4—figure supplement 2B). To assess the possible CNBP binding sites on LAST and CCND1 mRNA, the bioinformatics software tool QGRS Mapper was utilized (Kikin et al., 2006). Two G-rich sequences containing a GGAG core in the 5’UTR of CCND1 mRNA were identified (Figure 4D, upper part). An electrophoretic mobility shift assay (EMSA) was performed, and the results showed that G-rich-1 and G-rich-2 in the CCND1 5’UTR were responsible for the binding of CNBP (Figure 4D, lower part). Among the six predicted G-rich sequences (G-rich-A to F) found in LAST (Figure 4E, upper part), four G-rich sequences (G-rich-A, C, D and F) were found to contain a GGAG core. G-rich-A, C, D and F from LAST were able to bind CNBP, whereas neither G-rich-B nor G-rich-E was able to bind CNBP (Figure 4E, lower part). Thus, CNBP only interacted with G-rich sequences that contained the GGAG core, but not those lacking the GGAG core. These data suggest that both CCND1 and LAST interact with CNBP via their G-rich motifs containing the GGAG core. Four G-rich regions (A, C, D and F) were mutated from GGAG to UUUU with either a single mutation or four combined mutations in LAST. We found that over-expression of LAST containing only one site mutation led to an increase in the CCND1 mRNA level, whereas over-expression of LAST containing four G-rich site mutations nullified its effect on the CCND1 mRNA level (Figure 4F and G). This result indicates that the effect of LAST on CCND1 stability requires at least one of the four functional G-rich motifs. To define which domain of CNBP is responsible for binding LAST and the CCND1 5’UTR, a biotin-labeled RNA pull-down assay and deletion mapping were performed. According to the web site InterPro (Hunter et al., 2009), CNBP can be divided into four structural domains based on its zinc-finger arrangement (Figure 4—figure supplement 2C). As shown in Figure 4—figure supplement 2C, we concluded that LAST binds to the CNBP fragment corresponding to amino acids 92–134 (domain 3), whereas the CCND1 5’UTR binds to the CNBP fragment corresponding to amino acids 29–134 (domain 2 + domain 3) (Figure 4—figure supplement 2C). Determination of the exact mechanism of these associations requires further investigation.

In addition to CCND1, LAST regulates the stability of other mRNAs

To globally identify transcripts that simultaneously meet the following requirements: (i) transcripts are downregulated by LAST knockdown and (ii) transcripts are able to bind to CNBP, we assembled two unbiased transcriptome profiles using LAST knockdown mRNA-seq and CNBP RIP-seq in HCT116 cells. The intersection of these two arrays is shown in Figure 5A, and 225 overlapping genes were found (Supplementary file 2). We further narrowed this list down to 75 genes (Supplementary file 2, bold part) based on the criteria that CNBP-enriched genes must be 4-fold above the input control level. Three mRNAs, namely, SOX9, NFE2L1 and PDF, were also likely to be regulated by LAST, as knockdown of LAST led to a decrease in their levels (Figure 5B). Experimental verification showed that knockdown of LAST decreased (Figure 5C) whereas over-expression of LAST increased their half-lives (Figure 5D). In addition, CNBP deletion led to a decrease in the mRNA levels of SOX9, NFE2L1 and PDF (Figure 5E and F). These data suggest that LAST, together with CNBP, can regulate the stabilization of additional mRNAs, such as SOX9, NFE2L1 and PDF.

Figure 5. The synergistic effect of LAST and CNBP on mRNA expression.

(A) Venn diagram represents 225 overlapping transcripts (Supplementary file 2) obtained from LAST RNA-seq (red) and CNBP RIP-seq (violet). (B) Heatmap showing that SOX9, NFE2L1, PDF and CCND1 are not only decreased upon LAST knockdown but also enriched by CNBP. (C) HCT116 cells expressing control shRNA or LAST shRNA-1 were treated with actinomycin D (1 μg/mL) for the indicated periods of time. Total RNAs were extracted and then analyzed by real-time RT-PCR to examine the mRNA half-life of SOX9, NFE2L1 and PDF. Data shown are the mean ± SD (n = 6; *p<0.05, **p<0.01, ***p<0.001, two-tailed t-test). (D) HCT116 cells expressing control RNA or LAST were treated with actinomycin D (1 μg/mL) for the indicated periods of time. Total RNAs were extracted and then analyzed by real-time RT-PCR to examine the mRNA half-life of SOX9, NFE2L1 and PDF. (E) HCT116 cells were infected with lentiviruses expressing control shRNA or CNBP shRNA. Ninety-six hours later, cell lysates were subjected to western blotting to detect the CNBP knockdown efficiency. (F) HCT116 cells were infected with lentiviruses expressing control shRNA or CNBP shRNA. Ninety-six hours after injection, total RNA was analyzed by real-time RT-PCR with the indicated primers. Data shown are the mean ± SD (n = 3; ***p<0.001, two-tailed t-test).

Figure 5—source data 1. Source data for Figure 5C, D and F.
DOI: 10.7554/eLife.30433.022

Figure 5.

Figure 5—figure supplement 1. Uncropped images of blots.

Figure 5—figure supplement 1.

Red boxes indicate the cropped regions.

LAST promotes tumorigenesis

To further determine whether LAST regulates tumorigenesis, we used a xenograft mouse model. HCT116 cells stably expressing exogenous LAST or LAST shRNA-1 were injected subcutaneously into the dorsal flanks of nude mice (left (control) and right (treated), n = 7 for each group). According to animal care and enforcement, mice were sacrificed when the largest subcutaneous tumor mass on one flank was close to one cubic centimeter. Tumors expressing control shRNA or LAST shRNA-1 were excised after 6 weeks, and tumors expressing control RNA or LAST were excised after 3 weeks. Mice were sacrificed and tumors were excised. Knockdown of LAST decreased the tumorigenicity of HCT116 cells (Figure 6A and B). By contrast, induction of LAST promoted HCT116 cell tumorigenicity (Figure 6C and D). Furthermore, based on the TCGA dataset (Weinstein et al., 2013), we found that the LAST expression levels were higher in tumor tissues than normal tissues, including the human bladder, breast, colorectal, esophagus, head and neck, kidney, liver, lung, prostate and stomach. In addition, the CCND1 expression levels were higher in tumor tissues than in normal tissues, including the human bladder, breast, cervix, bile duct, colorectal, esophagus, head and neck, kidney, pancreas, stomach and uterus. In conclusion, both the LAST and CCND1 expression levels were higher in most tumor tissues than in their normal counterparts (Figure 6E and F, Figure 6—figure supplements 1 and 2). The above results suggest that LAST promotes tumorigenesis.

Figure 6. LAST promotes tumorigenesis.

(A) A total of 3 × 106 HCT116 cells expressing either control shRNA or LAST shRNA-1 were individually injected subcutaneously into the flanks of nude mice (n = 7 for each group) as indicated. Representative photographs of xenograft tumors in situ were taken 6 weeks after injection. (B) Tumors of the above nude mice (Figure 6A) were also selected to be weighed. Data shown are the mean ± SD (n = 7; ***p<0.001, two-tailed t-test). (C) A total of 3 × 106 HCT116 cells expressing either control RNA or LAST were individually injected subcutaneously into the flanks of nude mice (n = 7 for each group) as indicated. Representative photographs of xenograft tumors in situ were taken 3 weeks after injection. (D) Tumors of the above nude mice (Figure 6C) were selected and weighed. Data shown are the mean ± SD (n = 7; ***p<0.001, two-tailed t-test). (E) Data for the LAST and CCND1 expression levels in COAD (colon adenocarcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing differential expression of LAST and CCND1 between normal (n = 41) and tumor (n = 454) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001). (F) Data for LAST and CCND1 expression levels in READ (rectum adenocarcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 10) and tumor (n = 165) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001). (G) Pathway analysis of differentially downregulated genes (log2 (fold change) below - 0.58 in RNA-seq) in HCT116 with and without LAST knockdown. The top 10 significant pathways with enrichment scores are shown. (H) A schematic illustration of the proposed model depicting the role of c-Myc-induced LAST in regulating CCND1 mRNA stability via CNBP. (I) Gene homology analysis of LAST in human, chimp, gorilla, rhesus, mouse, rabbit, dog, chicken and zebrafish.

Figure 6—source data 1. Source data for Figure 6B, D, E and F.
DOI: 10.7554/eLife.30433.026

Figure 6.

Figure 6—figure supplement 1. The expression levels of LAST and CCND1 are both higher in most tumor tissues than in their normal counterparts.

Figure 6—figure supplement 1.

(A) Summary table of the differential expression of LAST and CCND1 between 15 tumor tissue types and their corresponding normal tissues. Data were from the TCGA dataset. (B) Data for the LAST and CCND1 expression levels in BLCA (bladder urothelial carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing differential expression of LAST and CCND1 between normal (n = 19) and tumor (n = 408) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001). (C) Data for the LAST and CCND1 expression levels in BRCA (breast invasive carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing differential expression of LAST and CCND1 between normal (n = 113) and tumor (n = 1090) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001). (D) Data for the LAST and CCND1 expression levels in CESC (cervical squamous cell carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 3) and tumor (n = 304) samples. Statistical analysis was performed using the two-tailed t-test (*p<0.05). (E) Data for the LAST and CCND1 expression levels in CHOL (cholangiocarcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 9) and tumor (n = 36) samples. Statistical analysis was performed using the two-tailed t-test (**p<0.01). (F) Data for the LAST and CCND1 expression levels in ESCA (esophageal carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 11) and tumor (n = 161) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001). (G) Data for the LAST and CCND1 expression levels in HNSC (head and neck squamous carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 23) and tumor (n = 480) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001).
Figure 6—figure supplement 2. The expression levels of LAST and CCND1 are both higher in most tumor tissues than in their normal counterparts.

Figure 6—figure supplement 2.

(A) Data for the LAST and CCND1 expression levels in KIRC (kidney renal clear cell carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 72) and tumor (n = 530) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001). (B) Data for the LAST and CCND1 expression levels in LIHC (liver hepatocellular carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 50) and tumor (n = 371) samples. Statistical analysis was performed using the two-tailed t-test (*p<0.05). (C) Data for the LAST and CCND1 expression levels in LUAD (lung adenocarcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 57) and tumor (n = 513) samples. Statistical analysis was performed by the two-tailed t-test (***p<0.001). (D) Data for the LAST and CCND1 expression levels in PAAD (pancreatic adenocarcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 4) and tumor (n = 177) samples. Statistical analysis was performed using the two-tailed t-test (***p<0.001). (E) Data for the LAST and CCND1 expression levels in PRAD (prostate adenocarcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 52) and tumor (n = 495) samples. Statistical analysis was performed using the two-tailed t-test (*p<0.05, ***p<0.001). (F) Data for the LAST and CCND1 expression levels in STAD (stomach adenocarcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 32) and tumor (n = 375) samples. Statistical analysis was performed using the two-tailed t-test (**p<0.01, ***p<0.001). (G) Data for the LAST and CCND1 expression levels in UCEC (uterine corpus endometrial carcinoma) tumor and normal tissues were downloaded from the TCGA dataset. Box plots showing the differential expression of LAST and CCND1 between normal (n = 23) and tumor (n = 543) samples. Statistical analysis was performed using the two-tailed t-test (**p<0.01).

To assess the impact of LAST deficiency on gene expression in HTC116, we performed unbiased transcriptome profiling using RNA-seq in HCT116 cells. The absence of LAST downregulated expression of 667 genes (log2 (fold change) below - 0.58) (Supplementary file 3). We then performed pathway analysis in those genes and found the top 10 significant pathways that were significantly associated with 667 differentially expressed genes. Among these 10 pathways, the majority were associated with tumorigenesis (Figure 6G).

Discussion

Cyclin D1 is a critical regulator of CDK kinase, which regulates cell cycle progression at the G1 to S-phase transition. Pre- or mature CCND1 mRNA is regulated at different hierarchical levels bymultiple protein factors. Multiple classical transcriptional factors, such as c-Myc, E2F1, OCT1,RELA and c-Jun, have been reported to modulate CCND1 at the transcriptional level (Guo et al., 2011). Epigenetic and post-transcriptional mechanisms are also involved in the regulation of cyclin D1/CCND1 (16, 29, 30). Moreover, Pitx2 and HuR, which belong to the same ribonucleoprotein complex, also control the decay rate of CCND1 mRNA (Gherzi et al., 2010). However, whether lncRNA(s) is (are) involved in the regulation of CCND1 mRNA stability remains largely unaddressed. Very recently, NcRNACCND1 was reported to negatively regulate CCND1 transcription by recruiting TLS to the CCND1 promoter (Wang et al., 2008). In this study, we characterized an overlooked mechanism of CCND1 mRNA regulation. c-Myc induced-LAST cooperates with CNBP, by which LAST is guided to the 5’ untranslated region of CCND1 messenger RNA and thus stabilizes CCND1 mRNA (Figure 6H). The detailed mechanism underlying this 5’end protection requires further characterization.

Normal growth control depends on the architecture of precise cell cycle control, and disturbing any component of this network could result in neoplastic growth and tumorigenesis. The G1/S transition is a major checkpoint in cell cycle progression, as it is a ‘point of no return’ beyond which cells are committed to dividing. Cyclin D1, along with its catalytically active partner CDK4, is a positive cell cycle regulator that advances the cell cycle from G1 to S phase (McKay et al., 2002). Instead of protein factors, in this study, we found a novel long noncoding RNA, LAST, that ensures normal cell cycle progression. Lacking this lncRNA causes cell cycle arrest at the G1/S stage due to decreased cyclin D1 and attenuates tumor growth. Both the LAST and CCND1 expression levels are higher in most tumor tissues than in their corresponding normal tissues (Figure 6—figure supplement 1A). Conceivably, LAST could be a potential target for new cancer therapeutics. However, a correlation between the expression levels of CCND1 and LAST in the 15 tumor types examined was not found (Supplementary file 4). In addition, there was no difference in survival when tumors were divided into those expressing high versus low CCND1 or LAST. These results imply that the regulation of CCND1 is more complicated than we had anticipated, and new functions of LAST need to be characterized.

CNBP encodes a nucleic-acid binding protein that has seven zinc-finger domains and a preference for binding single-stranded DNA and RNA (Flink and Morkin, 1995). Previous studies have shown that CNBP acts on cap-independent translation of ornithine decarboxylase mRNA (Sammons et al., 2010) and also functions in sterol-mediated transcriptional regulation as well as c-Myc transcription (Rajavashisth et al., 1989; Murphy et al., 2009). In this study, we found that CNBP possesses a new function. CNBP is able to guide lncRNA to bind to the 5’UTR of CCND1 mRNA, acting as a mediator between LAST and CCND1 mRNA.

lncRNAs are able to regulate their genomic neighborhoods in cis (Quinn and Chang, 2016). Examples of cis-acting lncRNAs include enhancer RNAs (eRNAs) (De Santa et al., 2010), imprinted lncRNAs (Mancini-Dinardo et al., 2006; Sleutels et al., 2002) and dosage compensation lncRNAs (Lee, 2012; Conrad and Akhtar, 2012). Homo sapiens cyclin D1/CCND1 and LAST are both located on chromosome 11, and the two genes are 1.8 Mb apart and in the same transcriptional direction (+strand). It is interesting to note that although CCND1 and LAST are both subjected to positive transcriptional regulation by c-Myc, they do not share the same promoter. Rather, CCND1 and LAST are transcribed separately by c-Myc via their respective promoters (Figures 1K and 6H). The relatively long distance between the CCND1 and LAST genes may preclude their direct interaction. Moreover, LAST was shown to borrow a trans-acting factor, CNBP, as a mediator to connect the 5’UTR of CCND1 mRNA and itself, thus affecting CCND1/cyclin D1 expression in trans. Without CNBP, LAST shows no effect on CCND1 (Figure 3—figure supplement 1F), further supporting the concept that LAST does not regulate CCND1 in cis. Therefore, co-location of CCND1 and LAST on the same chromosome appears to be a random event.

In summary, our findings from this investigation have uncovered a novel, c-Myc-induced, long non-coding RNA, LAST. The LAST gene is encoded physically on the same chromosome as CCND1. Normally, LAST interacts with CNBP, a RNA binding protein, by which it is guided towards the 5’UTR of CCND1 mRNA, leading to the stabilization of CCND1 mRNA, which in turn ensures orderly cell cycle progression. In the case of LAST dysregulation, CCND1 mRNA becomes unstable, resulting in decreased cyclin D1, inevitably causing cell cycle arrest and stoppage of cell division (Figure 6H). This is a novel mechanism for CCND1 mRNA regulation. Based on the importance of cyclin D1 in proliferative control and its ability to promote oncogenic transformation, this finding provides new insight into the complexity of the regulatory network underlying the mechanistic regulation of cyclin D1/CCND1. Moreover, this LAST/CNBP regulatory mode can be applied to other genes; three different mRNAs, SOX9, NFE2L1 and PDF, were identified with half-lives that were prolonged by LAST/CNBP. The lack of similarity between human LAST and transcripts of Mus musculus also precludes using mouse c-Myc-driven tumor models to further clarify the significance of the LAST in c-Myc-mediated cell cycle regulation and tumor growth in vivo (Figure 6I).

Materials and methods

Antibodies and reagents

The following antibodies were used for western blot analysis in this study: anti-c-Myc (Cell Signaling Technology); anti-GAPDH and anti-β-Actin (CMC-TAG); normal rabbit IgG, normal mouse IgG2a, anti-HUR, anti-cyclin D1, anti-CNBP and anti-NADSYN1 (Santa Cruz); anti-FLAG (Sigma-Aldrich); anti-cyclin E1, anti-CDK2, and anti-CDK4 (ImmunoWay Biotechnology Company); anti-HNRNPK (ABclonal); anti-DHCR7 (ABCAM). Anti-c-Myc used for ChIP assay was from Santa Cruz. Thymidine, Nocodazole, Mimosine, EGF, hydrocortisone, Cholera Toxin, insulin and Doxycycline was from Sigma-Aldrich. Actinomycin D was from Solarbio. Strepavidin beads for RNA pull-down assay was from Invitrogen.

Cell culture

H1299, HCT116, IMR90, 293T and HAFF cell lines were cultured in DMEM (Dulbecco's modified Eagle's medium) medium containing 10% fetal bovine serum. P493-6 and MCF7 cell lines were cultured in RPMI medium 1640 containing 10% fetal bovine serum. MCF10A cell line were cultured in DMEM/F12 medium containing 5% horse serum, 20 μg/mL EGF, 0.5 μg/mL hydrocortisone, 100 ng/mL Cholera Toxin and 10 μg/mL insulin. P493-6 cells carrying a c-Myc tet-off system were provided by professor Ping Gao. All other cell lines were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA). All cells were tested by STR profiling (GenePrint 10 System kit from Promega and AuthentiFiler PCR Amplification Kit from ThermoFisher) to authenticate the identity. All cells were tested for mycoplasma contamination by Cell Culture Contamination Detection Kit (ThermoFisher).

Western blotting, northern blotting and real-time RT-PCR

Western blotting, Northern blotting and real-time RT-PCR were performed as described previously (Zhang et al., 2016).

Colony-formation assay

HCT116 cells (1 × 103) expressing control shRNA, lncRNA-52 shRNA-1,–2, lncRNA-51 shRNA-1 or −2 were cultured in a six-well plate. Ten days later, cells were fixed, stained with crystal violet and photographed.

Quantitationfor the expression levels of LAST

The exact copy numbers of LAST transcripts per HAFF, IMR90, MCF10A, HCT116, MCF7 or H1299 cell were quantified by using quantitative real-time RT-PCR assay. In this assay, serially diluted RT-PCR products of LAST were used as templates to formulate standard curves, and the exact copies of LAST per cell were calculated accordingly.

ChIP assay

HCT116 cells were crosslinked with 1% formaldehyde for 10 min. The ChIP assay was performed by using anti-c-Myc antibody and the Pierce Agarose ChIP kit (ThermoScientific, USA) according to the manufacturer's instructions. Anti-Rabbit immunoglobulin G was used as a negative control. The bound DNA fragments were subjected to real-time PCR using the specific primers (Table 1).

Table 1. Oligomers used in this study.

Name Application Sequence
qrt-lncRNA-5639-F qRT-PCR GACCTTGGGCTAGTTATTTTGTG
qrt-lncRNA-5639-R qRT-PCR TCCTCTCTCCTTTCCTGTCTG
qrt-lncRNA-51-F qRT-PCR ACCACAGATCCAGTAGCCTAG
qrt-lncRNA-51-R qRT-PCR CCTAACCACACTCCAAGACAC
qrt-lncRNA-5630-F qRT-PCR CTCCAACATCACCAAAACCAC
qrt-lncRNA-5630-R qRT-PCR TCTTGGCATGTGGTATCTGTC
qrt-lncRNA-5690-F qRT-PCR TCGACATGAAACTTGGGTGG
qrt-lncRNA-5690-R qRT-PCR GGCCAAATTCACTTGATGCTC
qrt-LAST-F qRT-PCR GGATCCTCCATAAACGATCAG
qrt-LAST-R qRT-PCR AGCTGGTCGGTGGTCTCTTA
qrt-CNBP-F qRT-PCR CCTCGGATAGAGGTTTCCAG
qrt-CNBP -R qRT-PCR ACCGCAGTTATAGCAGGCTT
qrt-CDK4-F qRT-PCR CTGGTGTTTGAGCATGTAGACC
qrt-CDK4-R qRT-PCR AAACTGGCGCATCAGATCCTT
qrt-CDK2-F RT-PCR GCTAGCAGACTTTGGACTAGCCAG
 qrt-CDK2-R qRT-PCR AGCTCGGTACCACAGGGTCA
qrt-CCNB1-F qRT-PCR AAGAGCTTTAAACTTTGGTCTGGG
qrt-CCNB1-R qRT-PCR CTTTGTAAGTCCTTGATTTACCATG
qrt-CCNE1-F qRT-PCR ATCAGCACTTTCTTGAGCAACA
qrt-CCNE1-R qRT-PCR TTGTGCCAAGTAAAAGGTCTCC
qrt-CCND1-CDS-F qRT-PCR ACGAAGGTCTGCGCGTGTT
qrt-CCND1-CDS-R qRT-PCR CCGCTGGCCATGAACTACCT
qrt-CCND1-5’UTR-F qRT-PCR CTGGAGCCTCCAGAGGGCTGT
qrt-CCND1-5’UTR-R qRT-PCR GCGCTCCCTCGCGCTCTTC
qrt-CCND1-3’UTR-1-F qRT-PCR GGAAAGCTTCATTCTCCTTGTTG
qrt-CCND1-3’UTR-1-R qRT-PCR TTCTTTTGCTTAAGTCAGAGATGGAA
qrt-CCND1-3’UTR-2-F RT-PCR CATTGATTCAGCCTGTTTGG
qrt-CCND1-3’UTR-2-R qRT-PCR GAATTCATCGGAACCGAACT
qrt-CCND1-3’UTR-3-F RT-PCR TCTCAATGAAGCCAGCTCACA
qrt-CCND1-3’UTR-3-R RT-PCR TTTTGGTTCGGCAGCTTG
qrt-CCND1-intron-1-F qRT-PCR CTTTGTTCAAGCAGCGAGTC
qrt-CCND1-intron-1-R qRT-PCR AAGGTCCTCCAAGCCGATA
qrt-CCND1-intron-2-F qRT-PCR CCCAGCTCCCTTGAGTCC
qrt-CCND1-intron-2-R qRT-PCR CGGTCCTGGATGTTGGAG
qrt-CCND1-intron-3-F qRT-PCR TTTGTCATCGGCCAGAAATA
qrt-CCND1-intron-3-R qRT-PCR GACCTTCAGAGCACAGACCA
qrt-CCND1-intron-4-F qRT-PCR ATGTGCGTGGCCAATAAATA
qrt-CCND1-intron-4-R qRT-PCR ATCCCAGGGTTTAACAGCAG
qrt-c-Myc-F qRT-PCR AGCGACTCTGAGGAGGAAC
qrt-c-Myc-R qRT-PCR TGTGAGGAGGTTTGCTGTG
qrt-PDF-F qRT-PCR GCTGCGGCGCTCCTATT
qrt-PDF-R qRT-PCR TTGGCACACGTGCGAGAAC
qrt-NFE2L1-F qRT-PCR TGGCTATGGTATCCACCCCA
qrt-NFE2L1-R qRT-PCR ACCAGCCAGGCATTTACCTC
qrt-SOX9-F qRT-PCR GCGAGCCCGATCTGAAGAAG
qrt-SOX9-R qRT-PCR GTTCTTGCTGGAGCCGTTGA
qrt-DHCR7-F qRT-PCR ATCTGCCATGACCACTTCGG
qrt-DHCR7-R qRT-PCR CAGACCCTGCAGCGTGTAAA
qrt-NADSYN1-F qRT-PCR GCCGTGAGGAGTGGAAATGA
qrt-NADSYN1-R qRT-PCR GTGGTCAGTATGCGTCCACA
qrt-TOMM6-F qRT-PCR TGCTGGCTCGGCTAATGAAA
qrt-TOMM6-R qRT-PCR TCCTATCAGTGGCAAAGCGG
qrt-CEBPG-F qRT-PCR GAGCATGCACACAACCTTGC
qrt-CEBPG-R qRT-PCR CATTGTCGCCATCTGCTGTC
qrt-PRNP-F qRT-PCR GGAGAACTTCACCGAGACCG
qrt-PRNP-R qRT-PCR AGGACCATGCTCGATCCTCT
qrt-CHMP1B-F qRT-PCR GTTCAACCTGAAGTTCGCGG
qrt-CHMP1B-R qRT-PCR GGCATTTTCGGCGTGTATCC
qrt-MSX1-F qRT-PCR CCACTCGGTGTCAAAGTGGA
qrt-MSX1-R qRT-PCR GAAGGGGACACTTTGGGCTT
qrt-THAP11-F qRT-PCR AACCTGGTATCTGCTTCCGC
qrt-THAP11-R qRT-PCR TGAGATCGATGGGCTTCACG
qrt-C16orf91-F qRT-PCR ATGGGAAAGGGACATCAGCG
qrt-C16orf91-R qRT-PCR CTCCCCACACCTGTCTCAAC
qrt-VMA21-F qRT-PCR CATCTGCACAGCACCTTACAGTTTGC
qrt-VMA21-R qRT-PCR GAAATGCAGCACATCCAAATCCTCCC
qrt-PLEC-F qRT-PCR CCGGGCAGTCTCTGAAGATG
qrt-PLEC-R qRT-PCR GCGTTTTCCCAAGGTTCCAG
qrt-DLG5-F qRT-PCR GATGACCCGGGAGAGAAACG
qrt-DLG5-R qRT-PCR GGATTCAGCCTGTGGTAGGG
qrt-EPPK1-F qRT-PCR GTGTGTGATGAGTGGCCACACC
qrt-EPPK1-R qRT-PCR CTCTGGGTACACTGGCCTGCTCT
qrt-HIST2H4A-F qRT-PCR GGCGGAAAAGGCTTAGGCAA
qrt-HIST2H4A-R qRT-PCR CCAGAGATCCGCTTAACGCC
qrt-MYH9-F qRT-PCR ATCTCGTGCTATCCGCCAAG
qrt-MYH9-R qRT-PCR GTTGTACGGCTCCAACAGGA
qrt-PPL-F qRT-PCR AGGCAAATACAGCCCCACTG
qrt-PPL-R qRT-PCR AGGTCACTCTGCATCTTGGC
qrt-PRKDC-F qRT-PCR GGACCTATAGCGTTGTGCCC
qrt-PRKDC-R qRT-PCR GATCACTCAGGTAAGCCGCC
qrt-GDF15-F qRT-PCR TCCAGATTCCGAGAGTTGCG
qrt-GDF15-R qRT-PCR CGAGGTCGGTGTTCGAATCT
qrt-Actin-F qRT-PCR GACCTGACTGACTACCTCATGAAGAT
qrt-Actin-R qRT-PCR GTCACACTTCATGATGGAGTTGAAGG
qrt-U6-F qRT-PCR GCTTCGGCAGCACATATACTAAAAT
qrt-U6-R qRT-PCR CGCTTCACGAATTTGCGTGTCAT
qrt-U1-F qRT-PCR GGCGAGGCTTATCCATTG
qrt-U1-R qRT-PCR CCCACTACCACAAATTATGC
sh-LAST-F-1 plasmid construction ccggAAGAGGATCCTCCATAAACGActcgagTCGTTTATGGAGGATCCTCTTtttttg
sh-LAST-R-1 plasmid construction aattcaaaaaAAGAGGATCCTCCATAAACGActcgagTCGTTTATGGAGGATCCTCTT
sh-LAST-F-2 plasmid construction ccggTCAGCCATAGCAGCTGTGATTctcgagAATCACAGCTGCTATGGCTGAtttttg
sh-LAST-R-2 plasmid construction aattcaaaaaTCAGCCATAGCAGCTGTGATTctcgagAATCACAGCTGCTATGGCTGA
sh-lncRNA-51-F-1 plasmid construction ccggAAGCAGATGGAGGGAAGTTggatcc AACTTCCCTCCATCTGCTTtttttg
sh-lncRNA-51-R-1 plasmid construction aattcaaaaaAAGCAGATGGAGGGAAGTTggatccAACTTCCCTCCATCTGCTT
sh-lncRNA-51-F-2 plasmid construction ccggGGAAGCAGAGTAAGCAAGTGAGGATCCTCACTTGCTTACTCTGCTTCCtttttg
sh-lncRNA-51-R-2 plasmid construction aattcaaaaaGGAAGCAGAGTAAGCAAGTGAGGATCCTCACTTGCTTACTCTGCTTCC
LAST-DNA-1-sense lncRNA pull down (biotin-)TAAACGATCAGCCATAGCA
LAST-DNA-1-antisense lncRNA pull down (biotin-)TGCTATGGCTGATCGTTTA
LAST-DNA-2-sense lncRNA pull down (biotin-)TCATCGTGCCTCAGTTTCC
LAST-DNA-2-antisense lncRNA pull down (biotin-)GGAAACTGAGGCACGATGA
LAST-DNA-3-sense lncRNA pull down (biotin-)ACAGACACAGTTCTTGGTC
LAST-DNA-3-antisense lncRNA pull down (biotin-)GACCAAGAACTGTGTCTGT
LAST-DNA-4-sense lncRNA pull down (biotin-)ATGGGTCATATATTACATG
LAST-DNA-4-antisense lncRNA pull down (biotin-)CATGTAATATATGACCCAT
LAST-DNA-5-sense lncRNA pull down (biotin-)GTTGAATATGTATGTTTAG
LAST-DNA-5-antisense lncRNA pull down (biotin-)CTAAACATACATATTCAAC
LAST-DNA-6-sense lncRNA pull down (biotin-)CCAGCCTCAGACAGATGGC
LAST-DNA-6-antisense lncRNA pull down (biotin-)GCCATCTGTCTGAGGCTGG
CCND1-DNA-1-sense mRNA pull down (biotin-)GCGCAGTAGCAGCGAGCAGCA
CCND1-DNA-1-antisense mRNA pull down (biotin-)TGCTGCTCGCTGCTACTGCGC
CCND1-DNA-2-sense mRNA pull down (biotin-)CCGCTGGCCATGAACTACCTG
CCND1-DNA-2-antisense mRNA pull down (biotin-)CAGGTAGTTCATGGCCAGCGG
CCND1-DNA-3-sense mRNA pull down (biotin-)AACACGCGCAGACCTTCGTTG
CCND1-DNA-3-antisense mRNA pull down (biotin-)CAACGAAGGTCTGCGCGTGTT
CCND1-DNA-4-sense mRNA pull down (biotin-)CGTAGGTAGATGTGTAACCTCT
CCND1-DNA-4-antisense mRNA pull down (biotin-)AGAGGTTACACATCTACCTACG
CCND1-DNA-5-sense mRNA pull down (biotin-)AGAGTCATCTGATTGGACAGGC
CCND1-DNA-5-antisense mRNA pull down (biotin-GCCTGTCCAATCAGATGACTCT
CCND1-DNA-6-sense mRNA pull down (biotin-)AATGAAGCCAGCTCACAGTGCT
CCND1-DNA-6-antisense mRNA pull down (biotin-)AGCACTGTGAGCTGGCTTCATT
ChIP-LAST-a-F qRT-PCR for ChIP TTCCTGACAGCAGATTCCAG
ChIP-LAST-a-R qRT-PCR for ChIP TCTGCCATGTTTGGAGAATG
ChIP-LAST-b-F qRT-PCR for ChIP ACCTGCTCACCTGGGCAAGC
ChIP-LAST-b-R qRT-PCR for ChIP GGCAATCGCTGACATCATCCGGG
ChIP-LAST-c-F qRT-PCR for ChIP GGGATCCCAGCTGACCAGCTG
ChIP-LAST-c-R qRT-PCR for ChIP GAGGCACGATGATCCAGGTGATGAG
ChIP-LAST-d-F qRT-PCR for ChIP CTGAGCCACAGTGCGAGCCG
ChIP-LAST-d-R qRT-PCR for ChIP GACAGTAAGGCCTGTTACCCGAGC
ChIP-LAST-e-F qRT-PCR for ChIP AAGTCAAACAGCACGAACCC
ChIP-LAST-e-R qRT-PCR for ChIP CGGATGGGCATTGACGTTAT
ChIP-LAST-f-F qRT-PCR for ChIP TCAAGTGCAGTTCCTGTAGTTTC
ChIP-LAST-f-R qRT-PCR for ChIP GATGGCGCTGAATTCTTGGGAACC
ChIP-LAST-g-F qRT-PCR for ChIP TCCCTTCTTGTCCCTTCAAA
ChIP-LAST-g-R qRT-PCR for ChIP CCTAAAGACCAACGGGAAAC
ChIP-LAST-h-F qRT-PCR for ChIP TCTAGGGTTCTGGGCTGTCT
ChIP-LAST-h-R qRT-PCR for ChIP GTCAGGCTCACGAGACGAT

Luciferase reporter assay

To determine the effect of c-Myc on LAST promoter, either p3xflag-Myc-CMV-24 or p3xflag-Myc-CMV-24-c-Myc was co-transfected into HCT116 cells together with individual pGL3, pGL3-BS2, pGL3-BS2M, pGL3-BS3 or pGL3-BS3M construct plus Renilla luciferase reporter plasmid. Twenty-four hours after transfection, firefly and Renilla luciferase activity were measured by a Dual-Luciferase Reporter Assay System (Promega, Madison, WI, USA). The data are represented as mean ± SD of three independent experiments.

Cell cycle analysis

HCT116 cells were infected with lentiviruses and screened by puromycin, followed by plating into 6 mm dishes. During the proliferative exponential phase (50% confluency), cells were fixed in 70% ethanol overnight. Cells were then stained with propidium iodide and analyzed by flow cytometry.

RNA in situ hybridization

To detect LAST, RNA FISH was carried out as previously described with in vitro transcribed antisense probes labeled by Nucleic Acid Labeling Kits (Life technologies, USA) with Alexa Fluor 488 (Yin et al., 2012). The sequence of RNA probe was CGUCUUUUCAGGACACAAAGGCAUGCAGGUGCAUCAUCUCUCUCUAUUAACGGGUCAGCUGGUCGGCAUGGUCAGCUGGUCGGUGGUCUCUUAUUAGGAGAAAGUCACUGAAAUCAGUCUCUUGUCCAAUCACAGCUGCUAUGGCUGAUCGUUUAUGGAGGAUCCUCUUCGCCCCGGGACGUGAGCCCUAGGACCAAGAACUGUGUCUGUUUUGCUCCUUGCGGUGCACCGGCGCCUGGACAUACGCUCCAUCAAUGUGCGUCGCGAGCCGCUGAAGCCCCAUUUGCCGAGGGGGAAACUGAGGCACGAUG. The nuclei were counterstained with PI.

Cytosolic/nuclear fractionation

HCT116 cells (1 × 107) were incubated with hypotonic buffer (25 mM Tris-HCl, PH 7.4, 1 mM MgCl2, 5 mM KCl) on ice for 5 min. An equal volume of hypotonic buffer containing 1% NP-40 was then added, and each sample was left on ice for another 5 min. After centrifugation at 5000 g for 5 min, the supernatant was collected as the cytosolic fraction. The pellets were re-suspended in nucleus resuspension buffer (20 mM HEPES, PH 7.9, 400 mM NaCl2, 1 mM EDTA, 1 mM EGTA, 1 mM DTT, 1 mM PMSF), and incubated at 4°C for 30 min. Nuclear fraction was collected after removing insoluble membrane debris by centrifugation at 12000 g for 10 min.

RNA immunoprecipitation RT-PCR

RNA immunoprecipitation (RIP) was performed as described previously (Yang et al., 2014). 1 × 107 cells were lysed in RIP buffer supplemented with RNase A inhibitor and DNase I before centrifugation. Cell lysates were precleared with protein A/G beads (Pierce) before they were incubated with protein A/G beads coated with the indicated antibodies at 4°C for 3 hr. After extensive washing, the bead-bound immunocomplexes were eluted using elution buffer (50 mM Tris [pH 8.0], 1% SDS, and 10 mM EDTA) at 65°C for 10 min. To isolate protein-associated RNAs from the eluted immunocomplexes, samples were treated with proteinase K, and RNAs were extracted by phenol/chloroform. Purified RNAs were then subjected to RT-PCR analysis.

RIP-seq (RIP sequencing)

RIP was performed as described previously (Xiang et al., 2014). Briefly, two 10 cm2 dishes of HCT116 cells were washed three times with cold PBS and irradiated at 200 mJ/cm2 at 254 nm in HL-2000 HybriLinkerTM UV Crosslinker. Cells were collected and resuspended in 1 ml RIP buffer. Cells were then homogenized and followed by 3 rounds of sonication on ice. Cell lysates were precleared with protein A/G beads (Pierce) before they were incubated with protein A/G beads coated with the indicated antibodies at 4°C for 3 hr. After extensive washing, the bead-bound immunocomplexes were eluted using elution buffer (50 mM Tris [pH 8.0], 1% SDS, and 10 mM EDTA) at 65°C for 10 min. To isolate protein-associated RNAs from the eluted immunocomplexes, samples were treated with proteinase K, and RNAs were extracted by phenol/chloroform. The sequencing was performed and analyzed by KangChen Bio-tech, Shanghai, China. The sequencing data were deposited in the National Center for Biotechnology Information Gene Expression Omnibus database (GSE106918).

mRNA-seq (mRNA sequencing)

Total RNA from HCT116 cells expressing either control shRNA or LAST shRNA-1 was extracted by phenol/chloroform. The mRNA-seq was performed and analyzed by KangChen Bio-tech, Shanghai, China. The sequencing data were deposited in the National Center for Biotechnology Information Gene Expression Omnibus database (GSE106917).

G-rich motifs analysis in RIP sequencing data

The peak-calling tool MACS2 (Zhang et al., 2008) (https://github.com/taoliu/MACS/) with default parameter settings was used to call enriched peaks with RIP.bed as input and input.bed as control. A PERL script was written to calculate the proportion of the peaks containing each of the five given motifs (TGGAGNW, TGGAG, GGAGNW, GGAG and GGR) in all the RIP peaks. To test the significance of G-rich motif enrichment, another PERL script was used to perform statistical simulations by generating 1000 random samples of DNA sequences with the same size and the same length distribution as that of the RIP peaks. For each given motif, the average proportion (with standard deviation) of motif-containing sequences in random samples was calculated. A U-test was performed for each G-rich motif to test the significance of the difference between the proportion of the motif-containing sequences in RIP peaks and that in random DNA samples.

Biotin pull-down assay

All processes were performed in the RNase-free conditions. For antisense oligomer affinity pull-down assay, sense or antisense biotin-labeled DNA oligomers corresponding to LAST or CCND1 mRNA (1 μM) were incubated with lysates from HCT116 cells (1 × 107) or the cytosolic/nuclear extracts. One hour after incubation, streptavidin-coupled agarose beads (Invitrogen) were added to isolate the RNA-protein complex or RNA-RNA complex. For in vitro RNA pull-down assay, 5 μg in vitro-synthesized biotin-labeled RNA was incubated with lysates from HCT116 cells (1 × 107) for 3 hr. Streptavidin-coupled agarose beads (Invitrogen) were then added to the reaction mix to isolate the RNA-protein complex or RNA-RNA complex. Immunocomplexes were then analyzed by real-time RT-PCR or western blotting.

Electrophoretic mobility shift assay

The electrophoretic mobility shift assay (EMSA) was performed by using an EMSA/gel shift kit (Beyotime, China). Flag-CNBP protein was purified from 293T cells expressing Flag-CNBP. The biotin-labeled RNA fragments (as shown in Figure 4D and E) in vitro transcribed by T7 Transcription Kit (Epicentre, USA) were used in EMSA.

Xenograft mouse model

HCT116 cells expressing control RNA or LAST (3 × 106) were subcutaneously injected into the dorsal flank of 4-week-old male athymic nude mice (Shanghai SLAC Laboratory Animal Co. Ltd.) (n = 7 mice per group). After 3 weeks, mice were sacrificed, and tumors were excised and weighed. HCT116 cells expressing control shRNA or LAST shRNA-1 (3 × 106) were subcutaneously injected into the dorsal flank of 4-week-old male athymic nude mice (Shanghai SLAC Laboratory Animal Co. Ltd.) (n = 7 mice per group). After 6 weeks, mice were sacrificed, and tumors were excised and weighed. Mice were randomly assigned to different experimental groups. During testing the tumors' weight, the experimentalists were blinded to the information and shape of tumor tissue masses. Studies on animals were conducted with approval from the Animal Research Ethics Committee of the University of Science and Technology of China (Permit Number: USTCACUC1701003).

Acknowledgements

The results shown in Figure 6E and F, Figure 6—figure supplements 1 and 2 are based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/. We would like to thank Professor Ping Gao for providing P493-6 cells carrying a c-Myc tet-off system. This work was supported by grants from the National Key R and D Program of China (2016YFC1302302) and National Natural Science Foundation of China (81430065 and 31371388).

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Mian Wu, Email: wumian@ustc.edu.cn.

Igor Ulitsky, The Weizmann Institute of Science, Israel.

Funding Information

This paper was supported by the following grants:

  • Ministry of Science and Technology of the People's Republic of China 2016YFC1302302 to Mian Wu.

  • National Natural Science Foundation of China 81430065 to Mian Wu.

  • National Natural Science Foundation of China 31371388 to Mian Wu.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing.

Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Writing—original draft, Writing—review and editing.

Formal analysis, Visualization, Methodology.

Conceptualization, Resources, Supervision, Funding acquisition, Writing—original draft, Project administration, Writing—review and editing.

Ethics

Animal experimentation: Studies on animals in this paper were conducted with approval from the Animal Research Ethics Committee of the University of Science and Technology of China (Permit Number: USTCACUC1701003).

Additional files

Supplementary file 1. lncRNA expression microarray data.

Information of the selected lncRNAs is colored.

elife-30433-supp1.doc (330.5KB, doc)
DOI: 10.7554/eLife.30433.028
Supplementary file 2. Overlap of the CNBP RIP sequencing dataset and LAST knockdown mRNA sequencing dataset (downregulation).

Information of SOX9, PDF, NFE2L1 and CCND1 is colored.

elife-30433-supp2.doc (328.5KB, doc)
DOI: 10.7554/eLife.30433.029
Supplementary file 3. LAST knockdown mRNA sequencing dataset (downregulation).
elife-30433-supp3.doc (911KB, doc)
DOI: 10.7554/eLife.30433.030
Supplementary file 4. Correlation between LAST and CCND1 expression levels in fifteen TCGA tumor types.
elife-30433-supp4.doc (35.5KB, doc)
DOI: 10.7554/eLife.30433.031
Transparent reporting form
DOI: 10.7554/eLife.30433.032

Major datasets

The following datasets were generated:

Wu M, author; Zhang P, author; Cao L, author. Myc regulates gene expression in P493-6 cell lines which carry a Myc tet-off system. 2017 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106916 Publicly available at the NCBI Gene Expression Omnibus (accession no: GSE106916)

Wu M, author; Cao L, author; Zhang P, author. The impact of lncRNA LAST knockdown on gene expression profile in HCT116 cells. 2017 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106917 Publicly available at the NCBI Gene Expression Omnibus (accession no: GSE106917)

Wu M, author; Cao L, author; Zhang P, author. Identification of CNBP binding mRNA and the binding sites/motifs in HCT116 cells. 2017 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106918 Publicly available at the NCBI Gene Expression Omnibus (accession no: GSE106918)

The following previously published datasets were used:

The Cancer Genome Atlas Research Network, author; Weinstein JN, author; Collisson EA, author; Mills GB, author; Mills Shaw KR, author; Ozenberger BA, author; Ellrott K, author; Shmulevich I, author; Sander C, author; Stuart JM, author. The Cancer Genome Atlas. 2013 https://cancergenome.nih.gov/ The National Cancer Institute (NCI) provides access to all individuals seeking information on www.cancer.gov, including individuals who are disabled. To provide this information, the NCI website complies with Section 508 of the Rehabilitation Act (as amended).

Mathelier A, author; Fornes O, author; Arenillas DJ, author; Chen C, author; Denay G, author; Lees J, author; Shai W, author; Shyr C, author; Tan G, author; Worsley-Hunt R, author; Zhang AW, author; Parcy F, author; Lenhard B, author; Sandelin A, author; Wasserman WW, author. The high-quality transcription factor binding profile database (JASPAR) 2016 http://jaspar.genereg.net/ The database is ready to be deployed quickly for genome-wide studies through the JASPAR API.

Finn RD, author; Attwood TK, author; Babbitt PC, author; Bateman A, author; Bork P, author; Bridge AJ, author; Chang H, author; Dosztanyi Z, author; El-Gebali S, author; Fraser M, author; Gough J, author; Haft D, author; Holliday GL, author; Huang H, author; Huang X, author; Letunic I, author; Lopez R, author; Lu S, author; Marchler-Bauer A, author; Mi H, author; Mistry J, author; Natale DA, author; Necci M, author; Nuka G, author; Orengo CA, author; Park Y, author; Pesseat S, author; Piovesan D, author; Potter SC, author; Rawlings ND, author; Redaschi N, author; Richardson L, author; Rivoire C, author; Sangrador-Vegas A, author; Sigrist C, author; Sillitoe I, author; Smithers B, author; Squizzato S, author; Sutton G, author; Thanki N, author; Thomas PD, author; Tosatto SCE, author; Wu CH, author; Xenarios I, author; Yeh L, author; Young S, author; Mitchell AL, author. InterPro: protein sequence analysis & classification. 2009 http://www.ebi.ac.uk/interpro/ New SOAP-based Web Services have been added to complement the existing InterProScan Web Service. These allow users to programmatically retrieve InterPro entry data such as the abstract, integrated signature lists or GO terms. Users can download a range of clients from http://www.ebi.ac.uk/Tools/webservices/clients/dbfetch, including PERL, C#.NET and Java clients, to access this data.

ENCODE Project Consortium, author. Encyclopedia of DNA Elements. 2004 https://www.encodeproject.org/ Publicly available at ENCODE.

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Decision letter

Editor: Igor Ulitsky1

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "LncRNA-CCND1, a c-Myc-inducible long noncoding RNA, cooperates with CNBP to promote CCND1 mRNA stability" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors and the evaluation has been overseen by Naama Barkai as the Senior Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

In this manuscript Cao and colleagues describe the function of a lncRNA that they name lncRNA-CCDN1. It is transcriptionally regulated by c-Myc and necessary for cell cycle progression. The authors found that lncRNA-CCDN1 promotes the stability of CCDN1 mRNA by binding to it through the protein CNBP. They finally show that lncRNA-CCDN1 is upregulated in some cancers, and its downregulation inhibits tumor growth in xenografts.

The authors make a quite convincing case for the claim that lncRNA-CCND1 post-transcriptionally regulates the accumulation in the cytoplasm of the CCND1 RNA. The experiments are performed overall to a high standard, and since there are few convincing reports of lncRNAs regulating mRNA stability in the cytoplasm, this study is of high interest to the lncRNA community and the broader audience interested in gene regulation. However, some aspects need clarification and improvement prior to decision on publication.

Essential revisions:

1) The name of the lncRNA is not appropriate. Since the authors show that exogenous over-expression of lncRNA-CCND1 is sufficient for regulation of CCND1, and a rescue experiment with shRNA-insensitive lncRNA-CCND1, this lncRNA appears to act in trans. Therefore, the localization of lncRNA-CCND1 and CCND1 on the same chromosome is inconsequential, and since there is no evidence for direct pairing between the two RNA molecules, it’s also not clear that CCND1 is the main target of lncRNA-CCND1. There is no justification for the lncRNA-CCND1 name and the authors should choose a more appropriate one.

2) The authors should check the effect of the shRNA knockdown of lncRNA-CCND1 on the two adjacent genes DHCR7 and NADSYN1.

3) Because the sequence of the lncRNA is composed mostly of transposable elements, there is a concern about the specificity of the FISH probe, which does not appear to be listed in the supplementary materials. The authors should provide the sequence and show specificity of the signal using their shRNA KD cells, and to also show that the RNA is cytoplasmic in their subcellular fractionation data.

4) The TCGA analysis is lacking – its currently showing data from just two tumor types. They authors should show a comparison of normal and tumor expression levels for lncRNA-CCND1 in all the solid tumors in which TCGA has data (~15 tumor types), and show the same comparison for CCND1 levels, as well as the correlation between CCND1, MYC and lncRNA-CCND1 expression levels in each tumor type. If tumors are divided into those expressing high versus low cyclin D1 or lncRNA-CCND1, is there a difference in survival (Kaplan Meier plots).

5) The authors show some CLIP-seq data in Figure 5, but it’s not described at all and not used in the rest of the study. They should describe in detail how these data were obtained and what is their quality. Do they see CLIP peaks on CCND1 and lncRNA-CCND1? Do they see G-rich motifs in the CLIP peaks when considering the whole transcriptome? If the data is not of proper quality, it is best to leave it out of the manuscript.

6) The analysis of the transcripts that are both bound by CNBP and changed upon lincRNA KD should be part of the results and not the discussion. This part of the analysis is incomplete and the conclusions are not fully supported by the data. Is the overlap significantly higher than expected by chance? How many of the 10 mRNAs have different half-lifes following lincRNA-CCND1 KD and overexpression? Without these data the claim that this lincRNA can regulate other transcripts in the same way is not supported.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "LAST, a c-Myc-inducible long noncoding RNA, cooperates with CNBP to promote CCND1 mRNA stability in human cells" for further consideration at eLife. Your revised article has been favorably evaluated by Naama Barkai (Senior editor), a Reviewing editor, and two reviewers.

The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:

Major comments:

1) It is not clear how the RIP-seq experiment was done – the authors refer to Yang et al., (2014), but it has RIP qRT-PCR and not RIP-seq. It is not clear if any digestion of the RNA following IP is performed. If there is no digestion – how can the authors conclude from it where CNBP is binding the CCND1 mRNA? If there is no digestion, then the peaks merely correspond to regions that are resistant to degradation, and it’s not surprising that they G/C-rich.

2) The manuscript still needs very extensive language editing. Sentences like "In addition, c-Myc has been reported to repress transcription of CCND1 mediated by core elements of the CCND1 promoter but not MAX when expression of human Myc in BALB/c-3T3 cells, Rat6 cells and rat embryo fibroblasts." (from the Introduction) are not comprehendible. Other examples: "was particularly attracted our attention", "G1-relevant cyclins and CDKs genes", "To further confirm that LAST affect CCND1 mRNA stability is through CNBP", "It is therefore expected that knockdown of CNBP will reduced the association between LAST and CCND1 mRNA", "The exact reason for LAST or 5-'UTR involved in choosing the CNBP domain(s) for association is not clear at this moment", "Three mRNAs namely SOX9, NFE2L1 and PDF as the same as CCND1", "Six weeks after cells expressing shRNA injection or three weeks after cells expressing lncRNA injection, Due to the humane care for experimental animals,". These are just some of the examples. In present form, the article cannot be published in eLife without editing.

3) The lack of any anti-correlation between CCND1 and LAST across tumor samples, which should be discussed in the manuscript. It’s negative data, but important negative data, and so cannot be left out.

4) We cannot find the accession number for the mRNA-seq, microarray and RIP-seq results in the manuscript. Was the raw data deposited?

eLife. 2017 Dec 4;6:e30433. doi: 10.7554/eLife.30433.050

Author response


Essential revisions:

1) The name of the lncRNA is not appropriate. Since the authors show that exogenous over-expression of lncRNA-CCND1 is sufficient for regulation of CCND1, and a rescue experiment with shRNA-insensitive lncRNA-CCND1, this lncRNA appears to act in trans. Therefore, the localization of lncRNA-CCND1 and CCND1 on the same chromosome is inconsequential, and since there is no evidence for direct pairing between the two RNA molecules, it’s also not clear that CCND1 is the main target of lncRNA-CCND1. There is no justification for the lncRNA-CCND1 name and the authors should choose a more appropriate one.

We agree that name of this lncRNA in previous manuscript is not very appropriate. Besides CCND1 mRNA, we showed in this revised manuscript that this lncRNA is able to stabilize at least three additional mRNA transcripts, including SOX9, NFE2L1 and PDF (Figure 5C and 5D). We therefore renamed this lncRNA as LAST (LncRNA-Assisted Stabilization of Transcript). Literally, it means this lncRNA makes transcript last longer. Accordingly, sentences have been added in text to state this (subsection “Identification of LAST, a c-Myc responsive long noncoding RNA that promotes cell proliferation”).

2) The authors should check the effect of the shRNA knockdown of lncRNA-CCND1 on the two adjacent genes DHCR7 and NADSYN1.

We have checked the effect of LAST knockdown on its two adjacent genes DHCR7 and NADSYN1, and found that LAST showed no effect on either mRNA or protein level of those two genes (Figure 2—figure supplement 1C). This also implies that the decrease inCCND1 mRNA by knockdown of LAST is not an off-target effect. We have added sentences in text (subsection “LAST promotes G1/S transition and upregulates cyclin D1/CCND1”).

3) Because the sequence of the lncRNA is composed mostly of transposable elements, there is a concern about the specificity of the FISH probe, which does not appear to be listed in the supplementary materials. The authors should provide the sequence and show specificity of the signal using their shRNA KD cells, and to also show that the RNA is cytoplasmic in their subcellular fractionation data.

According to the reviewers’ suggestion, we have listed the FISH probe against LAST in the Materials and methods section (RNA in situ hybridization). Additionally, we performed a FISH experiment in H1299 cells expressing control shRNA, LAST shRNA-1 or -2 and found that the LAST signal intensity was markedly reduced in LAST depleted cells (Figure 1—figure supplement 1B). These data showed that this probe we used is specific for LAST. Furthermore, the cytosolic localization of LAST was also confirmed by a new sub-cellular fractionation experiment shown in Figure 1G. Sentences have been added in text to state this (subsection “Identification of LAST, a c-Myc responsive long noncoding RNA that promotes cell proliferation”).

4) The TCGA analysis is lacking – its currently showing data from just two tumor types. They authors should show a comparison of normal and tumor expression levels for lncRNA-CCND1 in all the solid tumors in which TCGA has data (~15 tumor types), and show the same comparison for CCND1 levels, as well as the correlation between CCND1, MYC and lncRNA-CCND1 expression levels in each tumor type. If tumors are divided into those expressing high versus low cyclin D1 or lncRNA-CCND1, is there a difference in survival (Kaplan Meier plots).

We have analyzed the LAST and CCND1expressionlevels in 15 types of normal and tumor tissues from TCGA. Both LAST and CCND1 expression levels were higher in the majority of tumor tissues relative to normal tissues (Figure 6E, 6F, Figure 6—figure supplement 1 and Figure 6—figure supplement 2). Sentences have been added in text to state this (subsection “LASTpromotes tumorigenesis”). However, the correlation between CCND1, Myc and LAST expression levels in 15 types of tumor examined was not found (Data are shown in below Table R1). In addition, there is no difference in survival when tumors are divided into those expressing high versus low cyclin D1 or LAST. As these results do not add significantly to the main message, we have not included them in the revised manuscript.

TCGA Tumor Types Pearson Correlation Coefficient (LAST-CCND1) P value Pearson Correlation Coefficient (LAST-Myc) P value Pearson Correlation Coefficient (CCND1- Myc) P value Sample Size
BLCA 0.028 0.567 -0.105 0.034 -0.08 0.107 408
BRCA 0.119 0 0.118 0 -0.069 0.023 1090
CESC 0.089 0.122 -0.005 0.93 -0.044 0.445 304
CHOL -0.088 0.61 0.025 0.884 -0.187 0.274 36
COAD -0.162 0.001 0.188 0 0.073 0.119 454
ESCA 0.337 0 -0.132 0.094 0.021 0.788 161
HNSC 0.034 0.442 -0.068 0.131 -0.031 0.496 499
KIRC 0.008 0.845 0.037 0.399 0.091 0.037 530
LIHC -0.047 0.366 -0.014 0.783 0.003 0.949 371
LUAD -0.037 0.402 -0.061 0.169 -0.033 0.454 513
PAAD -0.025 0.745 0.022 0.772 0.154 0.041 177
PRAD -0.061 0.174 -0.048 0.29 -0.016 0.715 495
READ -0.277 0 0.072 0.357 0.063 0.422 165
STAD 0.167 0.001 0.073 0.159 0.045 0.384 375
UCEC 0.024 0.58 -0.024 0.584 -0.049 0.25 543

BLCA (bladder urothelial carcinoma); BRCA (breast invasive carcinoma); CESC (cervical squamous cell carcinoma); CHOL (cholangiocarcinoma); COAD (colon adenocarcinoma); ESCA (esophageal carcinoma); HNSC (head and neck squamous carcinoma); KIRC (kidney renal clear cell carcinoma); LIHC (liver hepatocellular carcinoma); LUAD (lung adenocarcinoma); PAAD (pancreatic adenocarcinoma); PRAD (prostate adenocarcinoma); READ (rectum adenocarcinoma); STAD (stomach adenocarcinoma); UCEC (uterine corpus endometrial carcinoma).

5) The authors show some CLIP-seq data in Figure 5, but it’s not described at all and not used in the rest of the study. They should describe in detail how these data were obtained and what is their quality. Do they see CLIP peaks on CCND1 and lncRNA-CCND1? Do they see G-rich motifs in the CLIP peaks when considering the whole transcriptome? If the data is not of proper quality, it is best to leave it out of the manuscript.

We appreciate very much for referees’ comment. We have analyzed the CNBP RIP-seq enrichment peaks and a prominent peak on CCND1 5’UTR was observed (Figure 4—figure supplement 1C). This is consistent with the conclusion from Figure 4B. Because the sequencing depth of CNBP RIP-seq is 6 G, it is not enough to analyze the peaks on noncoding RNA. However, we have evaluated the enrichment efficiency of LAST and CCND1 in the RIP-seq samples. Both LAST and CCND1 were significantly enriched by CNBP antibody (Author response image 1). Furthermore, we checked the proportion of G-rich motifs in all peak sequences from CNBP RIP samples and found that nearly 60% of the CNBP enriched sequences contained GGAG core (Figure 4—figure supplement 2B), which is in good agreement with what had been previously reported (1, 2). These results prove that CNBP RIP-seq data are reliable. Sentences have been added in text to indicate these results (subsection “Both LAST and CCND1 mRNA bind to CNBP through their G-rich motifs”).

Author response image 1.

Author response image 1.

6) The analysis of the transcripts that are both bound by CNBP and changed upon lincRNA KD should be part of the results and not the discussion. This part of the analysis is incomplete and the conclusions are not fully supported by the data. Is the overlap significantly higher than expected by chance? How many of the 10 mRNAs have different half-lifes following lincRNA-CCND1 KD and overexpression? Without these data the claim that this lincRNA can regulate other transcripts in the same way is not supported.

In order to further analyze the data of mRNA-seq and RIP-seq, we examined half-lives of 75 genes in the overlap (CNBP enriched 4-fold above the control levels) in HCT116 cells expressing control shRNA or LAST shRNA-1. In addition to CCND1 mRNA, at least three additional mRNAs were identified to be regulated by LAST. Their half-lives are indeed changed following lincRNA-CCND1 KD and overexpression (Figure 5C and 5D). It suggests that CCND1 mRNA is not the only target regulated by LAST and CNBP. These data are now a part of the result in this revision (subsection “In addition to CCND1, LAST regulates the stabilization of some other mRNAs.”).

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Major comments:

1) It is not clear how the RIP-seq experiment was done – the authors refer to Yang et al., (2014), but it has RIP qRT-PCR and not RIP-seq. It is not clear if any digestion of the RNA following IP is performed. If there is no digestion – how can the authors conclude from it where CNBP is binding the CCND1 mRNA? If there is no digestion, then the peaks merely correspond to regions that are resistant to degradation, and it’s not surprising that they G/C-rich.

Reviewer is right, we performed RIP qRT-PCR as described in Yang et al., 2014, and RIP-seq was performed as described in Xiang et al.,(2014). The detailed method for RIP-seq has been added in the text (subsection “RIP-seq (RIP sequencing)”). In the RIP-seq experiment, cells were homogenized and then underwent 3 rounds of sonication on ice to remove the fragments that were not bound to CNBP. This information has been described in the method of RIP-seq.

2) The manuscript still needs very extensive language editing. Sentences like "In addition, c-Myc has been reported to repress transcription of CCND1 mediated by core elements of the CCND1 promoter but not MAX when expression of human Myc in BALB/c-3T3 cells, Rat6 cells and rat embryo fibroblasts." (from the Introduction) are not comprehendible. Other examples: "was particularly attracted our attention", "G1-relevant cyclins and CDKs genes", "To further confirm that LAST affect CCND1 mRNA stability is through CNBP", "It is therefore expected that knockdown of CNBP will reduced the association between LAST and CCND1 mRNA", "The exact reason for LAST or 5-'UTR involved in choosing the CNBP domain(s) for association is not clear at this moment", "Three mRNAs namely SOX9, NFE2L1 and PDF as the same as CCND1", "Six weeks after cells expressing shRNA injection or three weeks after cells expressing lncRNA injection, Due to the humane care for experimental animals,". These are just some of the examples. In present form, the article cannot be published in eLife without editing.

Sentences mentioned by the reviewer as some of the examples have been corrected (Introduction; subsection “Identification of LAST, a c-Myc-responsive long noncoding RNA that promotes cell proliferation”; subsection “LAST promotes G1/S transition and upregulates cyclin D1/CCND1”; subsection “LAST cooperates with CNBP to regulate CCND1mRNA stability”; subsection “Both LAST and CCND1 mRNA bind to CNBP through their G-rich motifs”; subsection “In addition to CCND1, LAST regulates the stability of other mRNAs.”; subsection “LAST promotes tumorigenesis). Furthermore, we had our whole manuscript to be edited by English language editing service.

3) The lack of any anti-correlation between CCND1 and LAST across tumor samples, which should be discussed in the manuscript. Its negative data, but important negative data, and so cannot be left out.

We have added these data in Supplementary file 4, and the description has been included in the Discussion section.

4) We cannot find the accession number for the mRNA-seq, microarray and RIP-seq results in the manuscript. Was the raw data deposited?

We have uploaded the mRNA-seq, microarray and RIP-seq raw data to Gene Expression Omnibus (GEO). The accession numbers are provided in the text (subsections “Identification of LAST, a c-Myc-responsive long noncoding RNA that promotes cell proliferation”, “RIP-seq (RIP sequencing)” and “mRNA-seq (mRNA sequencing)”).

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Figure 1—source data 1. Source data for Figure 1A, B, D, G, H, I, J, K and L.
    DOI: 10.7554/eLife.30433.006
    Figure 2—source data 1. Source data for Figure 2A, C and D.
    DOI: 10.7554/eLife.30433.010
    Figure 3—source data 1. Source data for Figure 3A, B, C, D, E, F, G, H, I and J.
    DOI: 10.7554/eLife.30433.014
    Figure 4—source data 1. Source data for Figure 4A, F and G.
    DOI: 10.7554/eLife.30433.019
    Figure 5—source data 1. Source data for Figure 5C, D and F.
    DOI: 10.7554/eLife.30433.022
    Figure 6—source data 1. Source data for Figure 6B, D, E and F.
    DOI: 10.7554/eLife.30433.026
    Supplementary file 1. lncRNA expression microarray data.

    Information of the selected lncRNAs is colored.

    elife-30433-supp1.doc (330.5KB, doc)
    DOI: 10.7554/eLife.30433.028
    Supplementary file 2. Overlap of the CNBP RIP sequencing dataset and LAST knockdown mRNA sequencing dataset (downregulation).

    Information of SOX9, PDF, NFE2L1 and CCND1 is colored.

    elife-30433-supp2.doc (328.5KB, doc)
    DOI: 10.7554/eLife.30433.029
    Supplementary file 3. LAST knockdown mRNA sequencing dataset (downregulation).
    elife-30433-supp3.doc (911KB, doc)
    DOI: 10.7554/eLife.30433.030
    Supplementary file 4. Correlation between LAST and CCND1 expression levels in fifteen TCGA tumor types.
    elife-30433-supp4.doc (35.5KB, doc)
    DOI: 10.7554/eLife.30433.031
    Transparent reporting form
    DOI: 10.7554/eLife.30433.032

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