The let-7 MicroRNA Represses Cell Proliferation Pathways in Human Cells (original) (raw)

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Cell, Tumor, and Stem Cell Biology| August 15 2007

Aurora Esquela-Kerscher;

3Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut

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Giovanni Stefani;

3Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut

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Mike Byrom;

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Xiaowei Wang;

2Ambion, Inc., Austin, Texas, and

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Lena Chin;

3Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut

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Frank J. Slack

3Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut

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Requests for reprints: Frank J. Slack, Department of Molecular, Cellular and Developmental Biology, P.O. Box 208103, Yale University, New Haven, CT 06520. Phone: 203-432-3492; Fax: 203-432-6161; E-mail: frank.slack@yale.edu or David Brown, Asuragen, Inc., 2150 Woodward St., Austin, TX 78744. E-mail: dbrown@asuragen.com.

Received: March 21 2007

Revision Received: May 17 2007

Accepted: June 18 2007

Online ISSN: 1538-7445

Print ISSN: 0008-5472

©2007 American Association for Cancer Research.

2007

Cancer Res (2007) 67 (16): 7713–7722.

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Citation

Charles D. Johnson, Aurora Esquela-Kerscher, Giovanni Stefani, Mike Byrom, Kevin Kelnar, Dmitriy Ovcharenko, Mike Wilson, Xiaowei Wang, Jeffrey Shelton, Jaclyn Shingara, Lena Chin, David Brown, Frank J. Slack; The let-7 MicroRNA Represses Cell Proliferation Pathways in Human Cells. _Cancer Res 15 August 2007; 67 (16): 7713–7722. https://doi.org/10.1158/0008-5472.CAN-07-1083

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Abstract

MicroRNAs play important roles in animal development, cell differentiation, and metabolism and have been implicated in human cancer. The let-7 microRNA controls the timing of cell cycle exit and terminal differentiation in Caenorhabditis elegans and is poorly expressed or deleted in human lung tumors. Here, we show that let-7 is highly expressed in normal lung tissue, and that inhibiting let-7 function leads to increased cell division in A549 lung cancer cells. Overexpression of let-7 in cancer cell lines alters cell cycle progression and reduces cell division, providing evidence that let-7 functions as a tumor suppressor in lung cells. let-7 was previously shown to regulate the expression of the RAS lung cancer oncogenes, and our work now shows that multiple genes involved in cell cycle and cell division functions are also directly or indirectly repressed by let-7. This work reveals the let-7 microRNA to be a master regulator of cell proliferation pathways. [Cancer Res 2007;67(16):7713–22]

Introduction

Hundreds of microRNAs (miRNA) are encoded in animal genomes, where they provide important regulatory functions in development, apoptosis, life span, and metabolism (1, 2). A number of miRNAs have also been linked to human cancer (3–8): we refer to this class of miRNAs as “oncomirs” (9). These are roughly divided into two groups, those miRNAs that are up-regulated or amplified in cancer and are likely to be acting as oncogenes, and those miRNAs deleted or down-regulated in cancer that are likely to be acting as tumor suppressors. Like most animal miRNAs, oncomirs act by binding to complementary sequences in the mRNAs of their target genes, e.g., oncogenes or tumor suppressors, to repress protein expression from the target mRNA (10), but miRNAs can also destabilize target mRNAs (11, 12).

The let-7 miRNA is a founding member of the miRNA family and is conserved in invertebrates and vertebrates, including humans, where the let-7 family consists of 11 very closely related genes (13–15). In Caenorhabditis elegans, let-7 is temporally regulated and controls the timing of terminal differentiation, acting as a master temporal regulator of multiple genes required for cell cycle exit in seam cells (5, 15–18). Many human let-7 genes map to regions altered or deleted in human tumors (3), indicating that these genes may function as tumor suppressors. In fact, let-7g maps to 3p21, which has been implicated in the initiation of lung cancers (19). Previous work has shown that let-7 may also play a role in lung cancer progression (4, 5, 20). For example, let-7 is expressed at lower levels in lung tumors than in normal tissue for patients with both adenocarcinoma and squamous cell carcinoma (4, 5, 20). Underscoring the potential importance of let-7 in lung cancer is the observation that postoperative survival time in lung cancer patients directly correlated with let-7 expression levels (4, 20): patients with lower let-7 expression survived for less time than those with higher let-7 expression. Our previous work showed that let-7 may directly control cellular proliferation by negatively regulating the human RAS genes (5), which are known lung cancer oncogenes (21). let-7 is complementary to multiple sequences in the 3′-untranslated regions (3′UTR) of human RAS genes, and let-7 represses the expression of KRAS and NRAS in tissue culture through their 3′UTRs (5). Moreover, in lung squamous cell carcinoma, low let-7 levels correlates with high RAS expression, consistent with let-7 negatively regulating RAS protein levels in vivo (5).

Taken together, this previous work (3–5) suggested that let-7 is a candidate tumor suppressor in lung, but little direct evidence existed to show this. Furthermore, little is known about the extent of the involvement of this miRNA in cancer or mechanisms by which this miRNA functions in cancer. In this new work, we show that let-7 is robustly expressed in the lung and directly affects the proliferation of A549 lung cancer cells. We also show that let-7 reduces cell cycle progression of a liver cancer cell line. Our studies indicate that let-7 directly regulates multiple cell cycle oncogenes in addition to RAS and, thus, directly represses cell proliferation pathways.

Materials and Methods

Plasmids. To generate the luciferase fusion to the human 3′UTRs, we subcloned the 3′UTR fragments downstream of firefly luciferase (luc) in pGL3 control (Promega). Details are shown in Supplementary Data. Transfections and luciferase assays are described in Supplementary Data.

Tissue culture, transfections, and cellular assays. HeLa, A549, and HepG2 cells were obtained from the American Type Culture Collection and grown in 90% DMEM with 10% fetal bovine serum (Invitrogen) at 37°C under 5% CO2. All cell lines were reverse transfected with either pre-miRs or anti-miRs (Ambion, Inc.) as indicated at 30 nmol/L final concentration using NeoFx (Ambion, Inc.) under manufacturer-recommended conditions.

Cell proliferation. To measure the effects on cellular proliferation rates, cells were incubated in 10% AlamarBlue diluted in normal culture media until visual color conversion appears. Proliferation rates were determined at 48 h post-transfection, and quantification was done on a BMG POLARstar Optima fluorescent plate reader under manufacturer-recommended protocol.

Cell cycle assay. Cells were reverse transfected in triplicate in six-well plate format by complexing 30 nmol/L small interfering RNA (siRNA) or miRNA and 4 μL of NeoFX transfection reagent (Ambion) in Opti-MEM serum-free medium (Invitrogen) in a total volume of 100 μL for 20 min. HepG2, or A549 cells (200,000 cells in 1.9 mL of complete growth medium per well), were plated by overlaying the transfection complexes. Seventy-two hours post-transfection, cells were harvested, and flow cytometry analysis was done using a GUAVA PCA-96 instrument following the manufacturer's recommended protocol. Data were collected and processed using the GUAVA Cell Cycle Analysis Software.

Western blots. HeLa cells growing in six-well plates were transfected with pre-miRs (Ambion) to a final concentration of 60 nmol/L with LipofectAMINE RNAiMAX (Invitrogen). Cells were harvested 24 h after transfection and lysated in radioimmunoprecipitation assay buffer [50 mmol/L Tris (pH, 7.4), 150 mmol/L NaCl, 1% Triton X-100, 0.5% deoxycholic acid, 0.1% SDS], containing complete proteases inhibitor mix (Roche). Proteins were analyzed by Western blot using antibodies against CDK6, CDC25a, and actin (DCS-90 from Sigma, DCS-120, 121 from Labvision, and C4 from MP Biomedicals). Bands were visualized by chemiluminescence using a Typhoon 8600 Imaging System (GE Healthcare). All values of CDC25a and CDK6 were normalized for the corresponding values of actin.

Reverse transcription-PCR detection of let-7 expression in cell lines. Details are found in Supplementary Data.

let-7 pathway analysis using GeneChip mRNA array analysis. HepG2 and HeLa cells were transfected with pre-miRs specific to let-7b, miR-124, negative control 1, and negative control 2 at 30 nmol/L final concentration using NeoFx (Ambion, Inc.) under the manufacturer's recommended conditions. At time points indicated in the figure legends, the samples were lysed, and total RNA was isolated using the RNAqueous RNA isolation system (Ambion).

All Affymetrix U133 plus 2 GeneChips used in the cell comparisons were processed according to the robust multichip analysis (RMA) background subtraction, normalization, and expression summary method (22). Irizarry et al. (22) showed that RMA has better precision for lower expression values and provides a greater than 5-fold reduction of the within-replicate variance as compared with other commonly used methods.

Assessment of statistically significant differential expression was carried out using a one-way ANOVA for each tissue type using Partek Genomic Solutions 6.2 (Partek Inc.). Given the nature of the data and the statistical tests selected, adjusting for multiple testing errors is critical. To account for the increased probability of type 1 error, a false discovery rates (FDR) P value adjustment was used (23). The FDR is defined to be the expected value of the ratio of the number of erroneously rejected true hypotheses over the number of rejected hypotheses. Benjamini and Hochberg (23) step-up procedure rejects H(1)… H(k) with k being the largest i for which P(i) ≤ q × i/m, and this procedure controls the FDR at level q when P(i) are independent.

We did pairwise comparison for the differentially expressed genes identified by ANOVA to determine the probe set that has significant differences between groups. For each pair of treatments, a two-sample t test was carried out for those genes that possessed a significant ANOVA main effect after FDR adjustment. This method is referred to as Fisher's protected least significant difference. We identified 50% of the same mir-124 repressed genes as previously published (12), suggesting that our microarray technology is accurate.

Time course study GeneChip array analysis. Affymetrix U133 plus 2 GeneChips that were used in the time course study were processed using Affymetrix MAS 5.0 algorithm as the scaling (value set to 500) and summarization method (Affymetrix Statistical Algorithms Description Document Part Number 701137 Rev 3). Because the time course study was unreplicated, the Wilcoxon signed-rank test (24) as implemented in the Affymetrix GCOS 1.4 software, was used to determine those genes that were differentially expressed relative to time 0. Those genes that were calculated to be absent in 100% of time points were discarded.

Gene ontology analysis. Details are found in Supplementary Data.

Northern blot analysis. Approximately 20.0 μg of total RNA was obtained from various adult mouse organs for Northern blot analysis using methods described previously (15). A probe used to detect RNA levels of let-7c (5′-AACCATACAACCTACTACCTCA-3′) was made using the StarFire oligonucleotide labeling system (IDT). The Northern blot was subsequently stripped and reprobed with U6 to normalize lanes for loading. pU6 (5′-GCAGGGGCCATGCTAATCTTCTCTGTATTG-3′; ref. 15), was 5′-end labeled with γ-32P ATP.

In situ hybridization analysis. Mouse tissue was collected in PBS and fixed in 4% paraformaldehyde. Samples were then soaked in 0.5 mol/L sucrose/PBS, embedded in OCT compound (Tissue-Tek), frozen, and sectioned at 12 μm thickness with a microtome cryostat. In situ hybridization analysis was done using digoxigenin-labeled LNA probes (miRcury probes, Exiqon; UTP/DIG Oligo Tailing Kit, Roche) corresponding to let-7a (5′-ACTATACAACCTACTACCTCA-3′) and let-7c (5′-AACCATACAACCTACTACCTCA-3′) on frozen sections as described (25), with blocking and antibody incubation steps as described in ref. 26, except that miRNA probes were hybridized at 48°C. Slides were mounted in a water-based medium (Aquamount) and photographed.

Results

let-7 is highly expressed in normal lung tissue. Previous work strongly implicated let-7 as a tumor suppressor in lung tissue (3–5). In support of this notion, we now show that let-7 is highly expressed in the adult mouse lung as well as in the developing lung during mouse embryogenesis (Fig. 1A–D). Northern analysis showed that of all adult tissues, let-7 is expressed with the highest relative level in the lung (Fig. 1B) and lower levels in other adult tissues (Fig. 1A). In addition, we detected let-7 expression in multiple tissues in developing mouse embryos using in situ hybridization (Fig. 1C; Supplementary Fig. S1), with intense expression in the developing lung (Fig. 1D). In contrast, a control probe detected little signal (Supplementary Fig. S1). let-7a and let-7c probes revealed an almost identical expression pattern (Fig. 1, Supplementary Fig. S1), which could reflect the difficulty in specifically detecting individual let-7 family members that only differ by one nucleotide. We also detected let-7 expression in adult murine lung epithelium (Supplementary Fig. S2). Consistent with this, we detected expression of all human let-7 family members (let-7a, b, c, d, e, f, g, and i) in normal adult human lung samples (Supplementary Fig. S3).

Figure 1.

let-7 expression in lung tissue. A, Northern blot analysis of total RNA taken from adult mouse tissues was probed for let-7c. U6 RNA is shown as a loading control. B, quantification of normalized RNA expression of let-7c shown in (A). Note that let-7c is highly expressed in the murine lung and lowest in the testis. C, in situ hybridization analysis of an E12.5 mouse embryo for let-7a shows expression in a variety of organ systems. Boxed region shows intense staining in the embryonic lung. D, higher magnification of the boxed region in (C) shows that let-7c expression is prominent in the developing bronchial system of the mouse (black arrows). a, atrium of heart; drg, dorsal root ganglion; f, forebrain; fnp, frontal nasal prominence; h, hindbrain; k, kidney; liv, liver; m, midbrain; p, palate; s, stomach; v, heart ventricle.

Figure 1.

let-7 expression in lung tissue. A, Northern blot analysis of total RNA taken from adult mouse tissues was probed for let-7c. U6 RNA is shown as a loading control. B, quantification of normalized RNA expression of let-7c shown in (A). Note that let-7c is highly expressed in the murine lung and lowest in the testis. C, in situ hybridization analysis of an E12.5 mouse embryo for let-7a shows expression in a variety of organ systems. Boxed region shows intense staining in the embryonic lung. D, higher magnification of the boxed region in (C) shows that let-7c expression is prominent in the developing bronchial system of the mouse (black arrows). a, atrium of heart; drg, dorsal root ganglion; f, forebrain; fnp, frontal nasal prominence; h, hindbrain; k, kidney; liv, liver; m, midbrain; p, palate; s, stomach; v, heart ventricle.

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In contrast, let-7 levels are reduced in non–small cell lung tumors relative to normal adjacent tissue (4, 5) and in eight tested lung cancer cell lines relative to normal lung samples (Supplementary Fig. S3). We found that with a few rare exceptions, the lung cancer lines tested showed reduced expression of all human let-7 molecules. This analysis led us to pick A549 cells as a representative lung cancer cell line for the remainder of this study.

let-7 represses cell proliferation in lung cells. Consistently reduced let-7 expression in the tumors of lung cancer patients suggests that the miRNA is either being affected as a consequence of the disease or is itself contributing to the development of the tumor. To experimentally distinguish between these possibilities, we examined the role of let-7 on cellular growth and proliferation in mammalian cells by manipulating let-7 levels using exogenously transfected pre–let-7 RNAs (to overexpress let-7) and anti–let-7 2'OMe oligonucleotides (to reduce let-7 activity). We transfected cultured human A549 lung cancer cells and HepG2 liver cancer cells [which also consistently produce low levels of all endogenous let-7s_ (Supplementary Fig. S3); refs. 4, 5] with synthetic let-7 miRNAs to artificially increase the intracellular concentrations of the let-7a, let-7b, let-7c, let-7d, and let-7g forms of the miRNA (Figs. 2A and 3A). We then monitored the transfected cell lines for alterations in proliferation, apoptosis, and cell cycle. The effects of the let-7 family members were compared with the effects of a negative control miRNA (Ambion), and siRNAs targeting MYC or kinesin Eg5 (which are two powerful effectors of cell proliferation; ref. 27). All tested pre–_let-7 molecules consistently reduced the number of proliferating A549 and HepG2 cells by levels that approached the MYC siRNA (Figs. 2A and 3A). This suggests that one or more processes related to cell proliferation or death that are common between these cell types are affected by let-7. This work extends similar analyses in lung and colon cancer cells (4, 28) by showing that multiple different let-7 family members have similar effects on cell proliferation. Because we have not yet detected a difference with any particular let-7 family member, we use them interchangeably for the remainder of this work.

Figure 2.

Impact of let-7 on proliferation in lung cancer cells. A, all synthetic pre–let-7 molecules tested reduced cell number in transfected A549 lung cancer cells compared with a negative control miRNA (NC). A siRNA against MYC served as a positive control. B, inhibition of let-7 with an anti–let-7 molecule results in an ∼100% increase in the number of A549 cells, compared with a control transfection and other tested anti-miRNA (anti-oncomirs). gapAS is a control transfection with a siRNA against glyceraldehyde-3-phosphate dehydrogenase.

Figure 2.

Impact of let-7 on proliferation in lung cancer cells. A, all synthetic pre–let-7 molecules tested reduced cell number in transfected A549 lung cancer cells compared with a negative control miRNA (NC). A siRNA against MYC served as a positive control. B, inhibition of let-7 with an anti–let-7 molecule results in an ∼100% increase in the number of A549 cells, compared with a control transfection and other tested anti-miRNA (anti-oncomirs). gapAS is a control transfection with a siRNA against glyceraldehyde-3-phosphate dehydrogenase.

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Figure 3.

A, impact of let-7 on proliferation and cell cycle in HepG2 cells. A, all synthetic pre–let-7 molecules tested affected proliferation in transfected HepG2 liver cancer cells compared with a negative control miRNA (NC). A siRNA against MYC served as a positive control. B, all synthetic pre–let-7 miRNAs tested significantly affected the percentage of HepG2 cells arrested in the G0-S stage of cell cycle. NC1 and NC2, negative control miRNAs 1 and 2, respectively. EG5 is an siRNA directed against Eg5. G0-G1 P values: let-7a, <0.001; let-7b, 0.026; let-7c, <0.001; let-7d, 0.0013; let-7e, <0.001; Eg5, <0.001.

Figure 3.

A, impact of let-7 on proliferation and cell cycle in HepG2 cells. A, all synthetic pre–let-7 molecules tested affected proliferation in transfected HepG2 liver cancer cells compared with a negative control miRNA (NC). A siRNA against MYC served as a positive control. B, all synthetic pre–let-7 miRNAs tested significantly affected the percentage of HepG2 cells arrested in the G0-S stage of cell cycle. NC1 and NC2, negative control miRNAs 1 and 2, respectively. EG5 is an siRNA directed against Eg5. G0-G1 P values: let-7a, <0.001; let-7b, 0.026; let-7c, <0.001; let-7d, 0.0013; let-7e, <0.001; Eg5, <0.001.

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In contrast to the reduced proliferation defect observed with exogenously added pre–let-7, antisense molecules targeting let-7a delivered into A549 cells induced an approximately 2-fold increase in proliferation relative to A549 cells transfected with a negative control siRNA and antisense miRNAs to other tested oncomirs (Fig. 2B). The inverse correlation between active let-7 and cell proliferation suggests that the miRNA affects a cell process that is vital for cell division, cell survival, or another process that supports cell proliferation. We believe that we have eliminated apoptosis as the cause of cell loss because an enzymatic assay to detect active caspase-3 levels revealed no change in three cell lines examined (A549, HepG2, and HeLa; data not shown).

let-7 reduces progression through the cell cycle. To investigate the effects of let-7 on the cell cycle, we used a flow cytometry assay to measure cell cycle progression in cells overexpressing let-7 or scrambled control miRNAs. Because HepG2 liver cancer cells accumulate a barely detectable amount of native let-7 (Supplementary Fig. S3; ref. 5) and because we saw the most dramatic effect on cell proliferation here (Fig. 3A), we focused our attention on these cells. We transfected HepG2 cells with synthetic mimics for several different members of the let-7 family (pre–let-7) as well as negative control synthetic miRNAs (control pre-miRs). All tested synthetic let-7 miRNAs caused a cell cycle defect in HepG2 cells, with a significant increase in the percentage of cells in G0-G1 (P < 0.01; Fig. 3B). Our flow cytometry results suggest that the proliferation effects of let-7 result from reduced progression through the cell cycle, most likely due to a block or delay in the G1-S transition.

Microarray analysis reveals genes whose expression changes in the presence of excess let-7. To determine the cellular pathways regulated by let-7, we did a microarray analysis of cells treated with let-7 miRNA. let-7 seems to regulate its target genes primarily at the level of translation (18, 29); however, recent evidence indicates that let-7 can also cause the instability of its target mRNAs (11, 15). In fact, in some cases, miRNAs have been reported to reduce mRNA levels of their direct targets sufficiently to be detected by standard microarray analysis (11, 12). We therefore predicted that exogenously applied let-7 miRNA might directly affect the mRNA levels of the genes that are naturally regulated by let-7 (with the exception of genes that let-7 regulates at the translational level only, e.g., KRAS) and indirectly affect the expression of genes that are downstream of these direct targets, leading to measurable changes in the global expression profiles of the treated cells. The identification of the affected pathways could reveal the mechanism by which let-7 inhibits cell division.

We transfected HepG2 and A549 cells in quadruplicate with synthetic miRNAs corresponding to let-7b, miR-124 (chosen as a positive control because its effects on global gene expression patterns have already been published; ref. 12), and two negative control miRs. Total RNA isolated from the cells 72 h after transfection was amplified, labeled, and hybridized to Affymetrix U133 arrays. Principal component analysis revealed that the two negative control miRNAs had very similar mRNA expression profiles in both cell types (Supplementary Fig. S4). In contrast, the mRNA profiles for the cells transfected with let-7b and miR-124 are clearly distinct from the cells transfected with the negative control miRNAs as well as from each other, indicating that the two miRNAs are uniquely affecting the global gene expression profiles of the two cell types. For both cell types, the number of genes determined to be altered by treatment was calculated by filtering all genes by fold change relative to both control transfections, and statistical significance was assessed by a t test after the omnibus F test was shown to be significant. In HepG2 liver cancer cells, we identified 1,334 (698 repressed and 636 up-regulated) genes whose expression varied by at least 1.93-fold and were statistically significant at a 0.05 FDR between the cells transfected with let-7 and the negative control miRNAs (Supplementary Table S1). In A549 lung cancer cells, we identified 629 (244 repressed and 385 up-regulated) altered genes, all of which were statistically significant at a 0.05 FDR (Supplementary Table S2). let-7 addition affected 200 genes in common between both cell types (Supplementary Tables S1 and S2). In both cell types, we identified NRAS and HMGA2, known downstream targets of let-7 (5, 30), indicating that our analysis could appropriately reveal let-7 downstream genes (Table 1).

Table 1.

Cell cycle, cell division, and cell proliferation genes that respond to excess let-7

*

Functional annotations were derived from the Human Proteome Survey Database (HumanPSD; ref. 45).

let-7 repressed multiple cell cycle associated genes. Genes found to be differentially expressed in either the HepG2 and A549 cell lines were grouped by their assigned biological functions using the Gene Ontology (GO) database (Fig. 4A; Supplementary Table S4). These results show that let-7 directly or indirectly affects the expression of many cell cycle–related genes. In fact, the primary GO classes associated with the differentially expressed genes in the HepG2 cells are linked with the cell cycle (Fig. 4A), which are consistent with our earlier observations (Figs. 2 and 3). Cell proliferation genes repressed directly or indirectly by excess let-7 in both cell types include the genes for cyclin A2, which promotes G1-S and G2-M phase transitions; CDC34, which promotes the degradation of cyclin-dependent kinase (CDK) inhibitor 1B; the ASK activator of S-phase kinase, required for the initiation of DNA replication at the G1 to S transition; the Aurora A and B kinases; the E2F5 transcription factor; CDK8; PLAGL2, the pleomorphic adenoma gene-like transcription factor; and Geminin, a regulator of DNA replication and proliferation (Table 1). Additional cell cycle genes repressed directly or indirectly by let-7 in HepG2 cells include the genes for various CDKs, cyclins, the CDC25A phosphatase, the S-phase kinase–associated protein 2, SKP2; the CDC28 kinase regulatory subunit 1B, and various cell division cycle–associated proteins (Table 1). let-7 also repressed genes coding for DNA synthesis and DNA replication functions (Table 1), e.g., ribonucleotide reductase subunits, multiple DNA replication initiation and origin recognition complex proteins, members of the Mini chromosome maintenance-deficient complex, and multiple members of the replication factor C complex (Table 1).

Figure 4.

Microarray analysis of _let-7_–treated human cancer cells. A, table of the most affected GO categories after let-7 overexpression in HepG2 cells for 72 h. mRNAs whose expression was affected by greater than 2-fold with P values below 0.05 were identified and classified using GO categories. *, P values were calculated with hypergeometric tests to determine whether there is a significant enrichment of affected genes in a GO category when compared with all genes represented on the arrays. B, cell cycle targets for let-7. Potential direct downstream targets of let-7. Right column, number of LCSs. Pink, first observed repression at 16 h; orange, first observed repression at 24 h; yellow, first observed repression at 36 h; blue, first observed repression after 36 h. Some of these genes, e.g., CDK6 and RRM2, were missed in PicTar because the rodent 3′UTRs are not complete. Known let-7 targets NRAS and HMGA2 are repressed after 36 h in our assay.

Figure 4.

Microarray analysis of _let-7_–treated human cancer cells. A, table of the most affected GO categories after let-7 overexpression in HepG2 cells for 72 h. mRNAs whose expression was affected by greater than 2-fold with P values below 0.05 were identified and classified using GO categories. *, P values were calculated with hypergeometric tests to determine whether there is a significant enrichment of affected genes in a GO category when compared with all genes represented on the arrays. B, cell cycle targets for let-7. Potential direct downstream targets of let-7. Right column, number of LCSs. Pink, first observed repression at 16 h; orange, first observed repression at 24 h; yellow, first observed repression at 36 h; blue, first observed repression after 36 h. Some of these genes, e.g., CDK6 and RRM2, were missed in PicTar because the rodent 3′UTRs are not complete. Known let-7 targets NRAS and HMGA2 are repressed after 36 h in our assay.

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Although the vast majority of altered cell cycle genes exhibited reduced expression following let-7 application, a few cell cycle genes were up-regulated under the same conditions. Because let-7 is currently only known to function as a repressor of gene expression, this likely indicates a 2° (or 3° or more) effect of let-7 application. These genes included those encoding CDK inhibitor 2B; the MAX-interacting protein 1, MXI1, a transcription regulator that antagonizes MYC; and cyclin G2, which is down-regulated in thyroid papillary carcinoma (31), showing that it has the propensity to act as a tumor antagonist (Table 1). In _let-7_–deficient tumor cells, these three genes would be predicted to be down-regulated, which might disable their tumor-suppressing functions.

Interestingly, we also found that let-7 addition repressed the expression of a number of known and putative tumor suppressor genes (Table 1) such as BRCA1, BRCA2, FANCD2, PLAGL1, E2F6, and E2F8 and the cell cycle checkpoint genes CHEK1, BUB1, BUB1B, MAD2L1, and CDC23. The significance of these findings remains to be determined, but may be relevant to the small number of recently identified tumors where let-7 is actually up-regulated (32, 33).

Identification of likely direct let-7 targets. To enrich for genes modulated directly by let-7, we reasoned that the expression of direct let-7 downstream genes might be affected earlier than indirect downstream genes. Therefore, in addition to analyzing the changes in global mRNA expression 72 h after let-7 transfection, we used a time course assay featuring microarray analysis of HepG2 cells harvested at 4, 8, 16, 24, 36, 48, 72, and 128 h after transfection (Fig. 4B; Supplementary Table S3). We found no change in gene expression at times 4 and 8 h after transfection, but detected the first changes 16 h post-transfection. We detected a total of 176 genes that were down-regulated within 36 h of let-7 addition: we denote these as early repressed genes (Supplementary Table S3; Fig. 4B). Like the original microarray analysis, these genes were enriched in GO categories for cell cycle and cell division (Supplementary Table S4). These included many of the same well-known cell cycle genes already mentioned (CCNA2, CDC25A, CDK8, SKP2, AURKA/STK6), but also included some that were missed in the 72-h experiment detailed above because their expression was presumably repressed early, and then their levels returned to normal by 72 h. These included the cell cycle genes CDC16 and CDK6. Other early repressed mRNAs include the DNA synthesis gene RRM2 and the cell proliferation regulator, MINA. Of these 176 early repressed genes, 127 genes first appeared down-regulated at time 16 h (Supplementary Table S3, pink; CDC16, CDK6, AURKA/STK6; RRM2, and MINA). An additional set of 37 genes was first observed down-regulated at 24 h (Supplementary Table S3, orange; including SKP2, CDCA7, and CDC25A), and another 12 were first detected as repressed at 36 h (Supplementary Table S3, yellow; including CCNA2 and E2F6). Interestingly, a number of other transcription factors besides E2F6, including ID2, CBFB, ZNF336, SMAD4, SOX9, NR1H4, ARID3A, PLAGL2, YAP1, and GTF2I, were among the early repressed genes, suggesting that they might also propagate the let-7 effects to their downstream targets.

To assess how many of the early _let-7_–repressed genes might constitute direct target genes, we examine the 3′UTRs of this group for let-7 complementary sites (LCS) that displayed features of LCSs in validated let-7 target genes (5, 15–18, 29, 34) and also used a published miRNA prediction program, PicTar, to predict let-7 targets (35). We found that at least 25 of the early repressed genes contained LCSs in their 3′UTRs (Fig. 4B), and we propose that these constitute direct let-7 targets. This set includes the cell cycle regulators CDK6, CDC25A, AURKB/STK6, CDCA7, and the DNA synthesis regulator RRM2. CDK6 interacts with D-type cyclins and phosphorylates RB1 to activate the G1 phase of the cell cycle (36). CDK6 is also overexpressed or amplified in numerous cancers including non–small cell lung cancer. CDC25A is a serine-tyrosine phosphatase that activates CDKs by removing inhibitory phosphate groups. Like CDK6, CDC25A is up-regulated in multiple cancers, including lung cancers (37). Aurora kinase B regulates chromosome segregation and cytokinesis during mitosis. CDCA7 encodes a novel protein up-regulated in multiple cancers, including lung cancer, which, like CDC25A, is a downstream target of MYC, and participates in the cell proliferation effects of MYC (38). The list of likely direct let-7 targets also includes eight transcription factors CBFB, PLAGL2, E2F6, SOX9, ZNF336, YAP1, GTF2I, and ARID3A, consistent with the enrichment for transcription factors seen as let-7 targets in C. elegans (16). We conclude that the non–LCS-containing genes with altered expression upon let-7 addition are likely to be downstream genes indirectly affected by let-7 expression, perhaps as downstream targets of the transcription factors affected directly by let-7. For example, we found that multiple members of the MCM and RFC DNA synthesis complexes were repressed only at later time points and could therefore be targets of these transcription factors.

let-7 negatively regulates the protein levels of CDK6 and CDC25A. We analyzed the native expression of our two top scoring cell cycle regulators (Fig. 5), CDK6 and CDC25A, in cells transfected with pre-miRs. Consistent with the microarray analysis, we found that protein levels of both CDK6 and CDC25A decrease in cells transfected with pre–let-7 compared with cells transfected with a control pre-miRNA (Fig. 5A). When quantified, we found that pre–let-7 transfection resulted in approximately a 50% reduction of protein compared with the normal levels of CDK6 and CDC25A (P < 0.001, CDC25A; P < 0.002, CDK6; Fig. 5B).

Figure 5.

Native and reporter gene validation of let-7 target genes. A, Western analysis of the indicated proteins following pre–let-7b or pre-control miR transfection of HeLa cells. Three independent transfections are shown for each pre-miR. B, quantification of relative levels of CDK6 and CDC25A proteins normalized to actin and the negative control pre-miR. C, schematic representations of the 3′UTR fragments cloned downstream of a luciferase reporter 3′UTR (gray, 3′UTR; wide gray, subcloned fragments). Arrows, positions of LCSs. D, relative fold induction of reporter gene expression in HeLa cells transfected with an anti-let7b oligonucleotide compared with a transfection with a negative control miRNA. Triplicate repeats of this experiment were done. Each value of luciferase activity in the samples treated with let-7b anti-miR was normalized by the average luciferase activity value of the samples treated with negative control anti-miR (value = 1). NRAS is the NRAS long 3′UTR shown here as a positive control.

Figure 5.

Native and reporter gene validation of let-7 target genes. A, Western analysis of the indicated proteins following pre–let-7b or pre-control miR transfection of HeLa cells. Three independent transfections are shown for each pre-miR. B, quantification of relative levels of CDK6 and CDC25A proteins normalized to actin and the negative control pre-miR. C, schematic representations of the 3′UTR fragments cloned downstream of a luciferase reporter 3′UTR (gray, 3′UTR; wide gray, subcloned fragments). Arrows, positions of LCSs. D, relative fold induction of reporter gene expression in HeLa cells transfected with an anti-let7b oligonucleotide compared with a transfection with a negative control miRNA. Triplicate repeats of this experiment were done. Each value of luciferase activity in the samples treated with let-7b anti-miR was normalized by the average luciferase activity value of the samples treated with negative control anti-miR (value = 1). NRAS is the NRAS long 3′UTR shown here as a positive control.

Close modal

To provide further validation for these cell cycle genes as direct let-7 targets, we did reporter assays where we independently fused the 3′UTRs of CDK6 and CDC25A downstream of firefly luciferase (Fig. 5C). In luciferase assays, both 3′UTRs conferred let-7_–dependent repression of the reporter gene (Fig. 5D) compared with a negative control anti-miR. The effect on the CDC25a and CDK6 3′UTRs caused by the anti–_let-7 was similar to a known let-7 target gene, NRAS (Fig. 5D). Thus, like NRAS, these results show that these genes are also likely to be directly regulated by the let-7 miRNA. Given the close working relationship between CDK6 and cyclin D (36, 39) in promoting the G1 to S transition, and the fact that CCND2 (encoding cyclin D2) is the highest scoring cell cycle gene predicted as a let-7 target by PicTar (35), we also tested the CCND2 3′UTR in the same assay. We found a similar result to CDK6 (Fig. 5D), suggesting that CCND2 is also a direct target of let-7.

Discussion

During mouse embryogenesis, let-7 is first detected around the time of initiation of lung development (40), and expression then persists into adulthood (Fig. 1A; Supplementary Fig. S3). These expression studies suggest that let-7 may control a variety of processes both during development and in the maintenance of adult tissue homeostasis. In contrast to robust let-7 expression in normal human lung tissue (14), let-7 is poorly expressed in lung tumors and lung cancer cell lines (Supplementary Fig. S3; refs. 4, 5). Poor let-7 expression may thus be a powerful diagnostic marker for lung tumors (20).

let-7 in control of cell proliferation. Proliferation and survival pathways are frequently altered in tumors (41). We have shown that let-7 overexpression causes human cancer cells to decrease cell cycle progression (Figs. 2 and 3). In addition, our microarray data show that let-7 directly or indirectly regulates multiple cell proliferation genes and strongly suggest that let-7 is a key regulator of cell cycle progression, consistent with the cell cycle assay results described earlier. We show that let-7 directly regulates a few key cell cycle proto-oncogenes, e.g., RAS, CDC25a, CDK6, and cyclin D (Fig. 5), thus controlling cell proliferation by reducing flux through the pathways promoting the G1 to S transition. Because many of these _let-7_–responsive genes are known oncogenes or are overexpressed in tumors, one prediction is that in cancer cells with let-7 deletions or poor let-7 expression, many of these genes would be up-regulated, which is likely to stimulate cell cycle and DNA synthesis and, hence, cell division.

The class of let-7 target genes that are solely repressed at the level of translation will not be identified via microarray analysis, but rather will need to be identified via proteomic or other means. For example, let-7 does not affect KRAS mRNA levels (42), and consequently, the human let-7 target gene KRAS (5) did not emerge from our microarray analysis. This shows that our analysis did not provide a complete picture of all let-7 targets and implies that let-7 might confer varying degrees of translational inhibition versus mRNA instability depending on specific target genes. In addition, CCND2 was also missed in our microarray analysis, but confirmed as a target by luciferase assays (Fig. 5D).

Nevertheless, our microarray analysis seems to have enriched for potential direct let-7 targets. Just over 14% (25 out of 176 total repressed) of our early misregulated genes are likely to be directly regulated by the let-7 miRNA, better than the ∼1% of all PicTar predicted let-7a targets as a function of the whole genome (243:25,000; enrichment P value = 5.4E−22 by hypergeometric test).

Our data strongly support the assertion that let-7 is a tumor suppressor miRNA. Although this role is most likely in lung cells where there is normally high let-7 expression and a strong correlation between let-7 loss and lung cancer, our studies find that let-7 causes cell cycle defects in a non–lung cancer cell line as well, implying that let-7 may function as a tumor suppressor in other tissues. This idea is supported by the observation that let-7 genes map to loci deleted in multiple types of cancers, such as breast, ovary, urothelial, and cervical cancers (3).

Our work reveals a miRNA to be a master regulator of proto-oncogene expression and cancer pathways. This important role in the control of a fundamental process such as cell cycle may provide an explanation for why let-7 has been 100% conserved more than 600 million years of evolution (14). These experiments also suggest that let-7 may prove to be a valuable tool in interventions aimed at treating and diagnosing many cancers.

let-7 affects expression of homologues of C. elegans heterochronic genes. In C. elegans, let-7 is a member of the heterochronic pathway, which regulates the timing of cell fate determination during development (43, 44) and requires dcr-1 and alg-1/alg-2 for this role (45). Interestingly, we identified three human homologues of C. elegans heterochronic genes as _let-7_–responsive genes in both A549 and HepG2 cells (Table 1), including LIN28B, DICER1, and EIF2C2/AGO2. In addition, EIF2C4/AGO4 was also affected in HepG2 cells overexpressing let-7. EIF2C2, EIF2C4, and alg-1/2 encode Argonaute proteins (46), which function with miRNAs in the RNAi-induced silencing complex (RISC) to mediate target-specific gene silencing. DICER1 processes let-7 (and other miRNAs) and our microarray data suggest that let-7 may negatively feedback on its own expression by modulating DICER1 expression. LIN28B is altered in human hepatocellular carcinoma and, like the C. elegans lin-28, has LCSs in its 3′UTR (47). It is therefore possible that conserved pathways function to control the timing of cell proliferation during the development of nematodes and mammals.

C. Johnson, A. Esquela-Kerscher, and G. Stefani contributed equally to this work.

Acknowledgments

Grant support: G. Stefani was supported by a Yale postdoctoral fellowship and the Anna Fuller Fund. F.J. Slack was supported by NIH grant GM62594 and National Science Foundation grant IBN-03444429. A.E. Kerscher was supported by a NIH/National Research Service Award postdoctoral fellowship (F32GM071157).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank Drs. Joanne Weidhaas and Iain Dawson for critical reading of this manuscript.

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