A negative feedback loop between Insulin-like Growth Factor signaling and the lncRNA SNHG7 tightly regulates transcript levels and proliferation

Evidence suggests Insulin-like growth factor 1 (IGF1) signaling is involved in the initiation and progression of a subset of breast cancers by inducing cell proliferation and survival(1, 2). Although the signaling cascade following IGF1 receptor activation is well-studied(3, 4), the key elements of the transcriptional response governing IGF1’s actions are not well understood. Recent studies reveal that the majority of the genome is transcribed and that there are more long non-coding RNAs (lncRNAs) than protein coding genes(5), several of which are dysegulated in human cancer(6, 7). However, studies on the regulation and mechanism of action of these lncRNAs are in their infancy. Here we show that IGF1 alters the expression levels of a subset of lncRNAs. SNHG7, a member of the small nucleolar host gene family, is a highly-expressed lncRNA that is consistently and significantly down-regulated by IGF1 signaling by a post-transcriptional mechanism through the MAPK pathway. SNHG7 regulates proliferation of breast cancer cell lines in a dose-dependent manner, and silencing SNHG7 expression causes cell cycle arrest in G0/G1. Intriguingly, SNHG7 alters the expression of many IGF1 signaling intermediates and IGF1-regulated genes suggesting a feedback mechanism to tightly regulate the IGF1 response. Finally, we show with TCGA data that SNHG7 is overexpressed in tumors of a subset of breast cancer patients and that these patients have lower disease-free survival than patients without elevated SNHG7 expression. We propose that SNHG7 is a lncRNA oncogene that is controlled by growth factor signaling in a feedback mechanism to prevent hyperproliferation, and that this regulation can be lost in the development or progression of breast cancer. SIGNIFICANCE STATEMENT IGF1 signaling drives proliferation and survival and is important for the initiation and development of a subset of breast cancers. IGF1 is known to control the expression of thousands of protein coding genes, but it is unknown if it alters the expression of other gene types, such as long noncoding RNAs. Here we demonstrate that IGF regulates lncRNAs including the mostly unstudied SNHG7. We further show that SNHG7 is necessary for proliferation and modulates IGF1 signaling through a novel feedback mechanism that is required for fine-tuning of the transcriptional response to growth factor signaling and proliferation of breast cancer cells. SNHG7 is highly expressed in a subset of breast cancer patients with poor prognosis giving further credence that it is a novel oncogene.

Actinomycin D before addition of IGF1 or vehicle. The inhibition of transcription did not ablate 1 9 9 the reduction of SNHG7 expression by IGF1 (Fig. 2H) suggesting that IGF1 alters SNHG7 2 0 0 expression by reducing the stability of the transcript and not through transcriptional repression. Actinomycin/Ctl) demonstrates transcription was effectively inhibited. Combined, these results 2 0 3 suggest that the regulation of the mature transcript is not merely a mechanism to change the 2 0 4 expression of the snoRNAs in the introns, but rather a tight regulation of the levels of the mature 2 0 5 SNHG7 lncRNA. 2 0 6 SNHG7 is a 5'terminal oligopyrimidine (5'TOP) gene similar to Gas5. It is known that 2 0 7 Gas5 lncRNA levels and other 5'TOP genes are destabilized by translation (39). Given that IGF1 2 0 8 signaling regulates translation, we tested if IGF1 regulates SNHG7 levels through translation. 2 0 9 Surprisingly, we observed that inhibition of translation with cycloheximide did not prevent IGF1 2 1 0 from decreasing the levels of SNHG7 (Fig. 2I), so we examined the effects of signaling 2 1 1 intermediates. Two of the primary downstream signaling pathways of IGF1R are 2 1 2 PI3K/AKT/mTOR and MAPK. Small molecule inhibitors of PI3K, MEK, and mTOR were used to 2 1 3 examine how IGF1 alters the stability of SNHG7. Inhibition of PI3K and mTOR had little effect 2 1 4 on IGF1's control of SNHG7 levels, while inhibition of MEK fully prevented alterations of SNHG7 2 1 5 levels by IGF1 signaling in serum starved MCF7 cells (Fig. 2I) indicating MEK signaling in the 2 1 6 destabilization of SNHG7. Collectively, these results (Fig 2) suggest a novel mechanism 2 1 7 whereby IGF1 significantly down-regulates the expression of SNHG7 through posttranscriptional 2 1 8 alteration of SNHG7 mature RNA stability via the MAPK pathway. 2 1 9 2 2 0 SNHG7 is necessary and sufficient for breast cancer cell proliferation 2 2 1 IGF1 signaling regulates proliferation of breast cancer cells. To determine if SNHG7 has 2 2 2 similar effects, we examined the response of proliferation to altered SNHG7 levels. A pool of 2 2 3 independently designed siRNA duplexes significantly reduced mature SNHG7 expression 2 2 4 without altering the expression of the snoRNAs hosted in the introns (Fig. 3A). The proliferation 2 2 5 of MCF7 cells with reduced SNHG7 expression was drastically reduced as scored by both a 2 2 6 fluorometric assay measuring DNA content (Fig. 3B) and by counting cells with a 2 2 7 hemacytometer using trypan blue exclusion ( Fig. S4A RNAi targeting SNHG7. The inhibition of proliferation in these cells is due to the reduction of 2 3 0 SNHG7 levels and not an off-target effect as demonstrated by the ability of 3 different individual 2 3 1 siRNA duplexes (Fig. 3D) that target SNHG7 to all inhibit proliferation (Fig. 3E). Interestingly, 2 3 2 these data suggest that there is a dose-dependent response to SNHG7 levels as the individual 2 3 3 duplexes that were most efficient at inhibiting SNHG7 levels also inhibited proliferation the most 2 3 4 ( Fig. 3D-E). A live/dead assay demonstrated that the reduction in cell numbers by siSNHG7 2 3 5 treatment is due to a decrease in proliferation (Fig. S4E) and not an increase in cell death ( Fig.  2 3 6 S4F). While control treated cells continued to increase in number, siSNHG7 treated cells do not 2 3 7 (Fig. S4E); however, the number of dead cells is not significantly different between treatment 2 3 8 groups (Fig. S4F). Additionally, FACS analysis with propidium iodine staining indicates that by 3 2 3 9 days siSNHG7 treated MCF7 cells begin to arrest in G0/G1 (Fig. 3F). Reducing the expression 2 4 0 of SNHG7 had no effect on the sensitivity of MCF7 cells to the dual-kinase IGF1R/InsR inhibitor, 2 4 1 BMS-754807 ( Fig.S4G). However, once again it is obvious that reduced SNHG7 expression 2 4 2 decreases basal proliferation ( Fig. S4G siCtl vs siSNHG7 at 10 -9 M). Together these data 2 4 3 demonstrate that SNGH7 is necessary for full proliferation of breast cancer cell lines.

4 4
To test if SNHG7 is sufficient to induce or enhance proliferation, the two main isoforms 2 4 5 of SNHG7 identified by RACE were cloned from cDNA of MCF7 cells. Two polyclonal MCF7 cell 2 4 6 lines stably expressing SNHG7 were generated for each isoform ( SNHG7 scores (indicative of high SNHG7 levels) have a significantly significant poorer disease-3 0 7 free survival (logrank test p-value=0.00079) than those with lower scores (Fig. S7). This further 3 0 8 argues that SNHG7 has an important biological and clinical role in breast cancer. 3 0 9 We leveraged the knowledge of IGF1 signaling and biology as a model system to identify a 3 1 2 lncRNA, SNHG7, that is important for proliferation and breast cancer biology. By doing so we 3 1 3 uncovered a novel fine-tuning feedback mechanism between IGF1 and SNHG7 that tightly 3 1 4 regulates RNA expression and cell proliferation. As summarized in a schematic in Figure 5, our 3 1 5 data shows that in addition to the regulation of many protein coding genes, IGF, which is 3 1 6 necessary for proliferation, downregulates the expression of SNHG7. Our results also implicate 3 1 7 SNHG7 in the regulation of expression of an enriched set of IGF1-regulated genes and of IGF1 3 1 8 signaling intermediates (Fig. 5 left). Additionally, there is a dose-response correlation between 3 1 9 SNHG7 levels and proliferation. Therefore, when IGF1 signaling is active it alters gene 3 2 0 expression (including downregulation of SNHG7) to increase proliferation (Fig. 5 middle).

2 1
However, by reducing SNHG7, which regulates a similar set of genes as IGF1, and also 3 2 2 numerous IGF1 signaling intermediates, the amplitude of IGF1-regulated genes is muted (Fig. 5  3  2  3 middle). When this feedback mechanism is overwhelmed, for example by the overexpression of 3 2 4 SNHG7 or the disruption of SNHG7 regulation by IGF1 (indicated by an x), it leads to enhanced 3 2 5 proliferation at least in part through differences in overall magnitude of IGF targets (Fig. 5 right -3 2 6 induced genes are expressed higher; repressed genes are repressed lower).

2 7
It is paradoxical that IGF1 would repress SNHG7, which controls the expression of many 3 2 8 of the same genes (in the same direction) and is necessary for proliferation, while 3 2 9 simultaneously inducing proliferation. However, our results and others(9) show that IGF1 3 3 0 signaling reduces the expression of IRS2, an immediate downstream signaling scaffold, and 3 3 1 increases the expression of numerous phosphatases (DUSPs) that dephosphorylate and 3 3 2 inactivate many of the kinases downstream of IGF1R. Thus, IGF1 regulation of SNHG7 3 3 3 expression is an example of a systems biology feedback mechanism to auto-attenuate IGF1 3 3 4 signaling. Further, our knock-down experiments that completely inhibit proliferation reduce 3 3 5 SNHG7 levels much lower than IGF1 signaling does (90% vs. 40%) suggesting there is a critical 3 3 6 amount of SNHG7 necessary for proliferation. Therefore, we propose that IGF1 regulates 3 3 7 SNHG7 levels as a feed-back mechanism to fine-tune the transcriptional response and 3 3 8 proliferation induced by IGF1 to prevent hyperproliferation or transformation/progression. If this 3 3 9 is true, we would predict that high levels of SNHG7 could lead to hyperproliferation. Accordingly, 3 4 0 SNHG7 is overexpressed or amplified in ~5% of TCGA breast cancer patients, and these 3 4 1 patients have worse disease-free survival than those without SNHG7 alterations.

4 2
In this report, we also describe a novel posttranscriptional mechanism of regulation of 3 4 3 SNHG7 through alterations in stability via the MAPK pathway. SNHG7 is a 5'TOP gene like 3 4 4 Gas5, which are regulated by nonsense mediated decay (NMD) through translation(43). While 3 4 5 SNHG7 levels are altered by mTOR and translational inhibition (data not shown), it is clear that 3 4 6 IGF1/MAPK regulation of SNHG7 levels is independent of translation induced by IGF1 because 3 4 7 inhibition of translation, mTOR, and PI3K/AKT did not prevent IGF1 mediated downregulation of 3 4 8 SNHG7. This suggests an additional mechanism of regulation of 5'TOP genes that requires 3 4 9 further investigation.

5 0
Our results that IGF-regulated lncRNAs, including SNHG7 and SNHG15, are important 3 5 1 for biology, enriched in breast cancer subtypes, and correlate with survival are consistent with 3 5 2 recent studies. A large number of functionally important lncRNAs were shown to be regulated by 3 5 3 estrogen signaling(25), but ours is the first study that examined regulation of lncRNAs by IGF.

5 4
Additionally, through reanalysis of TCGA data, others have demonstrated that certain lncRNAs 3 5 5 are enriched in specific breast cancer subtypes and lncRNAs alone can accurately stratify 3 5 6 patients into molecular subtypes (44)(45)(46). In fact, lncRNAs were shown to be more subtype 3 5 7 specific than protein coding genes and some correspond to patient survival, suggesting their 3 5 8 utility as biomarkers (45). It is still unclear if SNHG7 or other IGF-regulated lncRNAs can be 3 5 9 used as biomarkers or targeted for therapy. However, further understanding of the IGF1/SNHG7 3 6 0 system, the mechanisms of SNHG7 functions, and the characterization of other IGF1-regulated 3 6 1 lncRNAs clearly will impact our understanding of both basic and breast cancer biology. pipeline used to identify persistently IGF1 regulated known lncRNAs. The Tuxedo package was 3 6 5 used to determine differentially expressed (DE) genes after IGF1 treatment. Novel gene 3 6 6 discovery was allowed, but for a conservative estimate only genes with Gencode V21 lncRNA 0 (H-I) MCF7 cells were plated in triplicate for each treatment group, starved overnight, pretreated 4 0 1 with the indicated drug for 1-2hrs before stimulation with IGF1 or vehicle control for 8hrs. Cells 4 0 2 were harvested, RNA was isolated, cDNA was generated, and qPCR was performed and is 4 0 3 presented as described above. (H) 10ug/ml of actinomycin was used to inhibit transcription and 4 0 4 all results are normalized to the DMSO/Ctl group (I) 50uM of U0126 was used to inhibit MEK; 4 0 5 500nM of Wortmanin was used to inhibit PI3K; 1ug/ml of rapamycin was used to inhibit mTOR; 4 0 6 50 ug/ml of cycloheximide was used to inhibit translation; and, ctl was DMSO. Reported is the 4 0 7 mean +/-SD normalized to the respective Ctl. H) The two isoforms of SNHG7 (see Fig. 2A) were cloned into pcdna3.1, transfected into MCF7 4 2 7 cells individually, and multiple polyclonal cell lines were generated by selection with G418. The 4 2 8 number after p indicates the clone number. (G) qPCR was performed and mean +/-SEM are 4 2 9 reported of biological triplicates to verify that SNHG7 was expressed higher than clones 4 3 0 generated by transfection of vector alone (all significant; ttest p<0.05). (H) The proliferation of 0 proliferation was scored with the FluoReporter (ThermoFisher) assay by quantitation of dsDNA 5 4 1 according to manufacturers' instructions on the Victor X4 (PerkinElmer). Proliferation was also 5 4 2 scored via counting cells with a hemocytometer (Fig. S4A) using Trypan Blue exclusion in 5 4 3 triplicate plated MCF7 cells in 6-well dishes.

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Cell Cycle Assay: MCF7 cells were reverse transfected with siSNHG7, nontargeting control, or 5 4 5 nothing in biological triplicates. After 3 days, the cells were collected, fixed in 70% ethanol for 5 4 6 1hr, stained with 100ug/mL propidium iodide for 1hr, and then analyzed by flow cytometry. The 5 4 7 percentage of cells in each phase of the cell cycle was calculated according to protocol.