MicroRNAs and Cell Cycle Regulation

[Cell Cycle 6:17, 2127-2132, 1 September 2007]; ©2007 Landes Bioscience

Perspective

MicroRNAs and Cell Cycle Regulation Michael Carleton* Michele A. Cleary Peter S. Linsley

Abstract

*Correspondence to: Michael Carleton; Rosetta Inpharmatics; 401 Terry Ave. N.; Seattle, Washington 98109 USA; Email: [email protected]

Previously published online as a Cell Cycle E-publication: http://www.landesbioscience.com/journals/cc/article/4641

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Original manuscript submitted: 06/26/07 Manuscript accepted: 06/26/07

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Rosetta Inpharmatics LLC, a wholly owned subsidiary of Merck and Co.; Seattle, Washington USA

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MicroRNAs (microRNAs) are abundant, ~21–25 nucleotide (nt) non-coding RNAs that mediate sequence‑specific, post‑transcriptional repression of mRNA targets. Emerging evidence suggests that several microRNAs target transcripts that encode proteins directly or indirectly invovled in cell cycle progression and cellular proliferation. Moreover, alteration of microRNA levels can contribute to pathological conditions, including tumorigenesis, that are associated with loss of cell cycle control. In this review we highlight recent data linking microRNAs to mammalian cell cycle regulation. We describe how specific miRNAs function within pathways that control cell cycle checkpoints. We discuss emerging evidence that support the idea that some microRNA activity may be cell cycle dependent, and we outline how the coordinate regulation of microRNA targets may influence cell cycle progression.

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microRNAs and Cellular Differentiation

Cellular differentiation is marked by the coordinate regulation of cell cycle exit, activation of lineage‑specific gene expression, and in some cases, cell cycle re-entry. Cell fate decisions can be regulated by tissue‑specific transcription factors that function as switches or modulators of lineage‑specific gene expression programs. Some microRNAs also exhibit tissue‑specific expression, and microRNAs may impact cell fate decisions by modulating lineage‑specific gene expression and cell cycle progression.1‑3 A more detailed description of microRNA function during differentiation has come from studies of erythropoiesis and myogenesis. Erythropoietin (Epo) and stem cell factor (Scf ) are growth factors required for the survival, proliferation and differentiation of erythroid progenitors (reviewed in ref. 4). Using an in vitro erythropoietic (E) differentiation culture system of cord blood CD34+ hematopoietic progenitor cells (HPCs), Peschle and colleagues demonstrated that the robust expression of miR‑221 and miR‑222 in HPCs is markedly reduced as cells differentiate into erythroblasts. E cultured cells undergoing exponential growth exhibited a reduction in miR‑221/222 expression that inversely correlated with an increase in protein but not mRNA expression for SCF receptor Kit, which is required for the survival, proliferation and differentiation of erythoid progenitors.5 Kit appears to be a direct target of miR‑221 and miR‑222 as its 3' UTR contains a sequence matching the miR‑221/222 seed region and miR‑221/222 overexpression caused repression of both a Kit 3' UTR‑containing luciferase reporter in miR‑221/222 negative K562 cells and endogenous Kit protein in the TF‑1 erythroleukemic cell line.5 While activation of signaling through both Kit and the Epo receptor (Epo‑R) synergizes to enhance proliferation of erythroid progenitors (reviewed by ref. 4), in late erythropoesis, the GATA‑1 transcription factor represses transcription from the Kit promoter, and Kit levels decline in terminal erythroblasts.6 Consistent with a role in negatively regulating Kit, over‑expression of miR‑221 or miR‑222 accelerated erythropoeisis and induced an early decrease in cell proliferation with an accompanying increase in the percent of late erythroblasts.5 Taken together, the results of these studies support a role for miR‑221 and miR‑222 in modulating erythropoeisis through regulation of Kit. It will be important to determine how miR‑221 and miR‑222 expression is regulated during erythropoiesis, whether miR‑221 and miR‑222 are required for HPC commitment to the erythroid lineage, and whether there are additional miR‑221/222 targets whose repression limits cell cycle progression and promotes differentiation.

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microRNA, cell cycle, differentiation, proliferation, tumorigenesis, apoptosis

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MicroRNAs and Cell Cycle Regulation

microRNAs and Tumorigenesis

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Cellular transformation and tumorigenesis are driven by activation of oncogenes and/or inactivation of tumor suppressors. These genetic alterations contribute to the loss of cell cycle control and increased proliferative capacity characteristic of transformed cells. Recent data indicate that microRNAs may impact cellular transformation by modulating oncogenic and tumor suppressor molecular networks (reviewed in refs. 19 and 20).21‑22 Tumors may exhibit global decrease in levels 23 of mature microRNAs, perhaps due in part to failure of Drosha processing of microRNA precursors.24 In addition, many studies have uncovered specific over‑ and underexpression of microRNAs in tumors (reviewed in ref. 20). These alterations in microRNA levels may reflect the less differentiated state of tumors or indicate that microRNAs causally affect the transformed phenotype. Evidence that a reduction in microRNA levels plays a causal role in tumorigenesis comes from recent studies by Jacks and colleagues. These investigators showed that shRNA‑mediated disruption of the microRNA processing machinery enhanced tumor cell proliferation in vitro.25 Enhanced cell proliferation was accompanied by overexpression of protein products of Myc and Kras oncogenes. Transcripts encoding Myc and Kras contain target sites for the let‑7 microRNA in their 3' UTR regions. This observation agreed with previous studies showing that let‑7 regulates levels of Ras family proteins.22 microRNA let‑7g overexpression reduced colony formation in tumor cells with impaired microRNA processing whereas overexpression of let‑7g anti‑miR elevated the growth rate of tumor cells whose microRNA processing had not been manipulated.25 Finally, conditional inactivation of Dicer in the LSL‑KrasG12D mouse model of lung cancer led to an increase in tumor growth in vivo. These data indicate that global repression of microRNA processing can promote tumorigenesis and cell cycle entry in part by relieving constraints on the activity of known oncogenes.

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Skeletal muscle development is marked by stages of differentiation and proliferation. The observation that muscle‑specific microRNAs miR‑1, miR‑133 and miR‑206 are induced by myogenic transcription factors has stimulated intense interest in the function of these microRNAs during myogenesis.7 Functional studies performed in cells undergoing myoblast‑myotube transition have begun to elucidate targets of these muscle‑specific microRNAs and mechanisms by which repression of specific genes impacts myogenesis. Specifically, overexpression of either miR‑1 or miR‑206 decreased C2C12 cell proliferation and induced myogenesis.1,8,9 miR‑1 and miR‑206 share extensive sequence identity and presumably regulate a similar spectrum of targets. In contrast, overexpression of miR‑133 enhanced proliferation and inhibited myogenesis.1 In addition, 2'‑O‑methyl antisense microRNAs (anti‑miRs) to miR‑1/miR‑206, or miR‑133 had opposite effects to their cognate miRs on C2C12 myoblast‑ myotube transition.1,9 The proliferation and developmental phenotypes associated with microRNA expression in C2C12 can be attributed in part to the repression of specific target genes that affect muscle cell differentiation. Targets of miR‑206 and/or miR‑1 include Pola1 (the largest subunit of DNA polymerase a,9 Gkb1 (connexin‑43), a gap junction protein that regulates myoblast proliferation and is repressed during myoblast fusion in vitro,10‑13 and Hdac4 (a repressor of muscle gene expression).1 Targets of miR‑133 include Srf (serum response factor), a regulator of muscle cell differentiation and proliferation,1 and Ptbp2 a splicing factor that may control alternative splicing of developmentally regulated transcripts during myoblast‑myotube transition.2 It is possible that whole genome approaches such as microarray analysis of overexpressed microRNAs may uncover additional cell cycle‑related targets for microRNAs that control muscle differentiation and development. Srivastava and colleagues used targeted deletion of miR‑1‑2 to investigate its function in mouse cardiogenesis.3 Deletion of miR‑1‑2 induced defects in cardiac morphogenesis, electrophysiology, and cell cycle control indicating a role for miR‑1 in these processes. Specifically, deletion of miR‑1‑2 triggered an increase in mitotic adult cardiomyocytes and cardiac hyperplasia that was linked to the de‑repression of Hand2, a transcription factor that promotes myocyte expansion.14 The electrophysiological defects in miR‑1‑2 deficient mice were linked to elevation in the expression of transcription factor Irx5, which controls cardiac repolarization by repressing the potassium (K+) channel Kcnd2.3 Notably, miR‑1 overexpression is observed in human coronary artery disease. Moreover, both miR‑1 and miR‑133 have been linked with additional electrophysiological cardiac phenotypes due to their repression of distinct K+ channels.15,16 While these studies did not address the effect modulation of K+ channel expression has on cardiomyocyte cell cycle progression, regulation of the resting membrane potential of myofibroblasts and other cell types by K+ channels is known to impact cellular proliferation.17,18 Together these developmental studies clearly indicate that microRNA‑mediated gene repression can modulate cell cycle progression and lineage‑specific gene expression necessary for differentiation. These reports underscore the complexity with which microRNAs can act to regulate the cell cycle through repression of a variety of targets involved in an assortment of cellular processes. The continued application of gene targeting approaches will expand our understanding of microRNA function, the biological context in which microRNAs are active, and the genes they repress.

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microRNAs and Tumor Suppression: Regulation of Checkpoint Control and Apoptosis Deregulated microRNA expression can result from impaired microRNA processing, copy number alterations of microRNA encoding loci, or the methylation of microRNA promoter regions. Many microRNAs are located in chromosomal regions subject to chromosomal abnormalities in human cancer.26,27 Tumor suppressors maintain cell cycle checkpoint integrity and regulate apoptotic responses, so copy number loss at these loci can enhance tumorigenesis and contribute to poor clinical outcome. Deletion of certain microRNA loci in distinct tumor types, and correlation of microRNA deletion with poor clinical prognosis has led to the prediction that microRNAs may act as tumor suppressors (reviewed in ref. 20). Croce and colleagues provided some of the first evidence that specific microRNA loci may act as human tumor suppressors. For years, it has been known that deletions at chromosome 13q14 are common in chronic lymphocyte leukemia (CLL). However, despite intensive efforts, no loss of protein encoding transcript could be linked to these deletions. More recently, Calin et al. showed that the chromosomal region deleted in CLL contains the microRNA cluster encoding miR‑15a and miR‑16‑1.28 Reduced expression of miR‑15a and miR‑16 was observed in 75% of CLL cases harboring this deletion. Subsequent studies showed that over‑expression of the

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exhibits the characteristics of a tumor suppressor in NB. The miR‑34 microRNA family comprises three highly conserved microRNAs (miR‑34a, miR‑34b and miR‑34c). Recently, miR‑34 family members were shown to be directly regulated by the tumor suppressor, TP53.35‑38 miR‑34a may play a role in regulating the apoptotic36‑38 and/or G1 checkpoint functions of TP53.35 Over‑expression of each of the miR‑34 family members caused cell cycle arrest at G1 and down‑regulation of a significant number of cell cycle genes.35 Genes both down and upregulated by miR‑34a, ‑b and ‑c overlapped significantly with genes regulated by DNA damage. These observations suggest that the miR‑34 family plays a role in the TP53‑mediated DNA damage checkpoint by downregulating cell cycle genes and eliciting G1 arrest. Downregulation of cell cycle genes by miR‑34 family miRNAs may be a direct or indirect effect of cell cycle arrest. Arguing that cell cycle genes are direct targets of miR‑34 family microRNAs is the finding that several predicted miR‑34 targets show decreases in transcript levels as early as six hours after microRNA transfection.35 He et al. validated several of the downregulated genes as direct targets by showing miR‑34 regulation of reporters engineered to contain the 3' UTRs of the respective targets. These target genes included CDK4 (a cyclin‑dependent kinase), CCNE2 (cyclin E2,) and MET (a receptor tyrosine kinase). Like CDK6, CDK4 is activated by D‑type cyclins (reviewed in ref. 39) leading to the RB phosphorylation. CCNE2 regulates the initiation of DNA synthesis by activating CDK2.40‑42 MET is the receptor for hepatocyte growth factor and several studies have shown that suppression of c‑MET results in cell cycle arrest.43,44 While efficient repression of any one of these targets elicits cell cycle arrest reminiscent of introduction of miR‑34 family members, the actual knockdown of these targets by mir‑34 microRNAs is minimal (~40%–50%) and not sufficient to induce the observed phenotype. It is more plausible that the robust cell cycle phenotype caused by miR‑34 family members is the result of the cumulative effect of weak inhibition of multiple cell cycle genes. Thus, as with miR‑16 family microRNAs,31 miR‑34 microRNAs may initiate G1 checkpoint activation by regulating a cellular program (cell cycle) through the modulation of multiple targets, rather than a single key target.35

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miR‑15a/miR‑16‑1 cluster in a leukemia‑derived cell line repressed levels of the anti‑apoptotic protein, Bcl2, and induced apoptosis.29 These observations were extended in the New Zealand Black (NZB) spontaneous mouse model for human CLL.30 Marti and colleagues identified a point mutation in the 3' flanking sequence of miR‑16‑1 not present in other mouse strains and determined that miR‑16 expression was reduced in NZB lymphoid tissue compared with controls. Over‑expression of miR‑16 in the NZB‑derived B cell lymphoma, LNC, caused a reduction in S‑phase cells, an accumulation of the G0/G1 fraction, and induction of apoptosis not observed in the non-NZB B cell line control.30 Another recent study suggested that miR‑16 family microRNAs may directly regulate cell cycle progression and proliferation by controlling the G1 checkpoint. Over‑expression of miR‑16 family microRNAs led to induction of G0/G1 arrest in cultured human tumor cells.31 Many miR‑16 targets were identified whose repression could induce G0/G1 accumulation. One of these targets was CDK6,31 a cell cycle kinase activated when it binds D‑type cyclins in early G1 phase. CDK6/cyclin D complexes participate in the sequential hyper‑phosphorylation of RB1 by CDK4/6 and CDK2 to repress RB inhibition of E2F, which positively regulates G1 to S-phase progression. CDK6 enhances leukemogenesis by promoting cellular proliferation. Hayette and colleagues reported finding three B‑CLL patients in which aberrant gene recombination caused CDK6 overexpression due to the juxtaposition of the CDK6 gene to the Ig gene enhancer.32 One of the three patients identified contained a deletion at 13q14. While the patient numbers are small, these data raise the interesting possibility that CDK6 overexpression induced by aberrant gene recombination, de‑repression of CDK6 due to deletion of 13q14 and loss of miR‑16, or a combination of the two may contribute to leukemogenesis. Additional analysis of lymphoma patient samples with deletions at 13q14 will be required to define any connection between miR‑16 loss, CDK6 overexpression, loss of cell cycle control, and leukemogenesis. Accumulating evidence suggests that other microRNAs may also directly regulate cell cycle checkpoints and cellular proliferation. Neuroblastoma (NB) is a common pediatric cancer that can be subdivided into several genetic subtypes. Profiles of microRNA expression were obtained from a panel of NB tumors segregated into three groups by histopathology.33 Using this data set, MYCN‑amplified (MNA) tumors, the most clinically aggressive subtype of NB, could be segregated from the other tumor types by 2D hierarchical clustering.33 microRNAs that exhibited differential expression between the three NB groups were identified, including miR‑184 whose expression was significantly reduced in MNA tumors relative to the other subtypes. Furthermore, overexpression of miR‑184 in several NB lines induced cell cycle arrest at G1, followed by apoptosis.33 microRNA miR‑34a loss has also been associated with NB. Hemizygous deletion of chromosome 1p is associated with NB poor prognosis, predominately in the MNA subtype. Comparative genomic hybridization demonstrated that miR‑34a is located in the minimal region of 1p loss in NB tumors with 1p deletions.34 In addition, expression of miR‑34a was reduced in NB cell lines and advanced stage primary NB tumors relative to normal tissue.34 Overexpression of miR‑34a in several NB cell lines induced growth arrest followed by apoptosis.34 E2F3 was identified as a putative miR‑34a target, and both the activity of a luciferase‑based reporter construct containing the E2F3 miR‑34 target site in its 3' UTR and levels of endogenous E2F3 protein were reduced by miR‑34a overexpression.34 These data were interpreted to indicate that miR‑34a www.landesbioscience.com

Cell Cycle Regulation of microRNA Activity The activity of many genes known to control cellular proliferation is regulated by cell cycle‑dependent oscillation of gene transcription, stability (of transcripts and proteins), and protein sequestration (proteins).45 Studies in model organisms have shown that certain cell cycle‑regulated genes may be targets of microRNAs. For example, Hatfield et al46 described a role for microRNAs in control of germline stem cell (GSC) division in Drosophila melanogaster. GSCs mutant for dicer‑1 (dcr‑1) showed a reduced rate of germline cyst production, and were defective in cell cycle control. This GSC division defect was dependent on Dacapo, a homologue of the p21/p27 family of cyclin‑dependent kinase (CDK) inhibitors. In another example, RNA interference‑related pathways were shown to cooperate with retinoblastoma in transcriptional repression of endogenous genes, including cyclin E, to control nuclear divisions in the intestine of Caenorhabditis elegans.47 If microRNAs control the highly orchestrated patterns of gene expression that occur during cell cycle progression, it seems likely that the cell will employ mechanisms to control microRNA activity during the cell cycle. It is possible that expression of some

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microRNAs oscillates during the cell cycle, although at the time of this review we were not aware of any reports describing this possibility. Alternatively, cell cycle progression may be regulated by microRNAs induced by environmental agents. A clear example of this is the induction of miR‑34 family members by DNA damaging agents during activation of the G1 checkpoint.35 Cell cycle‑dependent changes in microRNA stability have been reported. Mendell and colleagues described how miR‑29b is rapidly degraded in cycling cells only to be stabilized when cells enter or are arrested in mitosis.48 They also demonstrated that nuclear localization of miR‑29b depends on Figure 1. Diagramatic comparison of a single target repression model and a cooperative a hexanucleotide terminal motif that serves as a repression model for microRNA induced phenotypic effects. cis‑acting nuclear localization sequence.48 While the function of miR‑29b and any role it may have in regulating cell cycle progression remains uncharacterized, these data of higher animals. microRNA target interactions may also depend raise the interesting possibility that cell cycle‑dependent regulation of on target 3' UTR contexts, which may impose some restrictions microRNA stability may serve to control microRNA function. These on the inclusion of some genes with seed region complementary as data also underscore that cis‑acting regulatory sequences may impart true microRNA targets.3,60 While relatively few microRNA‑target distinct functions to select microRNAs by regulating their cellular interactions have been confirmed experimentally, much effort has gone into their computational prediction.61 It is now generally localization. Sequestration of microRNAs may also regulate their activity during accepted that each animal microRNA can recognize many, perhaps the cell cycle. Small, dynamic cytoplasmic foci called P‑bodies, first hundreds, of targets (reviewed in ref. 62).63 This seems to present a identified in yeast, were initially thought to be a location for mRNA dilemma for the gene‑centric view of the early microRNA studies: storage and degradation. However, P‑bodies also appear to serve as why are so many targets regulated when so few are needed? An alternative view of microRNA target regulation is that sites for RNA‑induced silencing complex (RISC) activity. AGO2, a component of RISC, siRNAs, and microRNAs have been shown to multiple targets regulated by an individual microRNA act coordilocalize to P‑bodies.49 In addition, actively proliferating mammalian nately to regulate biological processes (Fig. 1). This model has several cells contain elevated numbers of P‑bodies that are larger in size attractive features. First, it is less “wasteful” than models predicting compared with quiescent cells. The increase in P‑body number and limited numbers of key targets. The “coordinate‑regulation” model size in proliferating cells occurred during the progression from late S also fits with how microRNAs actually regulate their targets, where, into G2 and was followed by disassembly of P‑bodies prior to mitosis typically, only partial target regulation is achieved. This makes with reassembly occurring in early G1.50 Disruption of P‑bodies it difficult to quantitatively compare phenotypes triggered by impaired siRNA and microRNA‑mediated gene silencing, although microRNAs with those elicited by disruption of single targets, where effects on cell cycle progression were not reported.51‑53 These data more complete gene disruption may be produced. The strength of raise the possibility that cell cycle dependent regulation of P‑body microRNA‑induced phenotypes may be better explained by coordynamics may play a role in modulating the activity of specific dinate or cooperative regulation of many targets. Of course, the microRNAs in proliferating cells. Given the stabilization of miR‑29b models shown in Figure 1 are not mutually exclusive. Even in cases during mitosis when P‑bodies have been disassembled, it will be where there is strong genetic evidence for a single key target, other important to determine whether disruption of P‑bodies in cycling microRNA‑regulated targets may modify resulting phenotypes. Cooperativity between different microRNA targets in regulating cells can alter the nuclear localization and stability of miR‑29b and cell cycle control and division was described in a study using cultured other microRNAs. human cells.31 miR‑16 transfection partially down‑regulated many targets that when silenced in isolation disrupted the transition from microRNAs and Target Recognition G0/G1 to S and triggered arrest in G0/G1. Known cell cycle reguAnimal microRNAs were first discovered during genetic studies of lators that did not induce G /G accumulation when selectively 0 1 development in C. elegans.54 Early studies showed that non-coding silenced were also identified as miR‑16 targets. These genes may serve microRNAs negatively regulated levels of specific protein‑coding to modify the effects of other miR‑16 targets (i.e., E2F7, CDC25A, targets and generally supported the view that microRNAs have CHEK1, WEE1 and CCNE1). There may also be microRNA targets limited numbers of key targets55‑58 (Fig. 1). However, emerging that induce G /G accumulation but escape detection because they 0 1 genome‑scale studies of microRNA target regulation suggest that are not regulated at the mRNA level. Thus, these experiments likely the “limited key target” view of microRNA target recognition is underestimate the number of miR‑16 targets that regulate cell cycle incomplete. progression. Taken together, these findings argued that miR‑16 microRNA target recognition in animal cells generally occurs targets act in concert, rather than individually, to regulate G /G 0 1 through regions of limited sequence complementarity between the progression. microRNA ‘seed region’ and 3' UTR regions of targets (reviewed in ref. 59). The limited sequence complementarity required for target recognition expands the potential target sites in the transcriptome 2130

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We view the accumulating evidence as consistent with microRNAs modulating cell cycle progression by the coordinate and partial repression of multiple genes (Fig. 1). We propose that such a model allows enhanced “fine tune” control over cell cycle progression. Mechanisms of cell cycle control involving transcriptional repression/ activation and post‑translation modification of key regulatory molecules are well known. However, these mechanisms of cell cycle regulation rely upon secondary effects that delay both the intended change in cell cycle progression and its reversal. By regulating an entire cellular program through the cooperative repression of target genes, microRNAs may serve as buffers to limit the accumulation of many gene products that impact cell cycle progression under a variety of contexts. Coordinate regulation of many targets may also allow for rapid reversal of microRNA‑induced cell cycle regulation upon changes in microRNA synthesis, stability or localization. While many details remain unclear, the association of microRNAs with both cell cycle progression and cellular differentiation reinforces their importance as key regulators of transitions between these processes. It is our view that cooperative interactions between many partially regulated microRNA targets are key to cell cycle progression. With hundreds of human microRNAs now identified, the task of detailing microRNA function mimics the challenges presented in the study of transcription factor function. A more global understanding of microRNAs and the biological processes they impact will require more complete knowledge of gene(s) targeted by specific microRNAs, factors that regulate microRNA activity, and pathways that control the spatio‑temporal regulation of microRNA expression (reviewed in ref. 64). For a growing number of microRNAs, there has been progress in addressing several of these questions. However, optimal understanding of the role of microRNAs in the cell cycle may rely on development of more precise methods for studying functional interactions between microRNAs and their targets.

13. Gorbe A, Krenacs T, Cook JE, Becker DL. Myoblast proliferation and syncytial fusion both depend on connexin43 function in transfected skeletal muscle primary cultures. Exp Cell Res 2007; 313:1135‑48. 14. Zhao Y, Samal E, Srivastava D. Serum response factor regulates a muscle‑specific microRNA that targets Hand2 during cardiogenesis. Nature 2005; 436:214‑20. 15. Yang B, Lin H, Xiao J, Lu Y, Luo X, Li B, Zhang Y, Xu C, Bai Y, Wang H, Chen G, Wang Z. The muscle‑specific microRNA miR‑1 regulates cardiac arrhythmogenic potential by targeting GJA1 and KCNJ2. Nat Med 2007; 13:486‑91. 16. Xiao J, Luo X, Lin H, Zhang Y, Lu Y, Wang N, Yang B, Wang Z. MicroRNA miR‑133 represses HERG K+ channel expression contributing to QT prolongation in diabetic hearts. J Biol Chem 2007; 282:12363-7. 17. Chilton L, Ohya S, Freed D, George E, Drobic V, Shibukawa Y, Maccannell KA, Imaizumi Y, Clark RB, Dixon IM, Giles WR. 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