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Molecular and Cellular Biology, July 2007, p. 4784-4795, Vol. 27, No. 13
0270-7306/07/$08.00+0 doi:10.1128/MCB.00494-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.

European Institute of Oncology, Department of Experimental Oncology, 20141 Milan, Italy,1 IFOM-IEO Campus, Via Adamello 16, 20139 Milan, Italy,2 Cancer Research, Merck Research Laboratories, Basic Research, 33 Avenue Louis Pasteur, Boston, Massachusetts 02115,3 Max F. Perutz Laboratories, Medical University of Vienna, Vienna Biocenter, Dr. Bohr-Gasse 9/2, A-1030 Vienna, Austria4
Received 21 March 2007/ Returned for modification 11 April 2007/ Accepted 18 April 2007
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HDAC inhibitors are a new class of drugs with anticancer potential. They have been shown to induce apoptosis effectively in cancer cells and are currently in clinical trials for a variety of cancers (4, 40). One example includes the HDAC inhibitor suberoylanilide hydroxamic acid, which recently has been shown to induce polyploidy in human cancer cell lines (55). As we learn more about HDACs and the biological processes they regulate, a strong idea that the identities of the relevant target deacetylases need to be determined to aid in the development of HDAC inhibitors as anticancer agents is emerging. One clear example is the demonstration of HDAC2 induction upon loss of the adenomatosis polyposis coli tumor suppressor in colorectal tumorigenesis, providing a reason for treating certain carcinomas with HDAC inhibitors (58). Interestingly, it has been demonstrated previously that the HDAC inhibitor valproic acid selectively induces polyubiquitination and proteasomal degradation of HDAC2 (35). Lately, HDAC3 was found to be required for normal mitotic progression and maximal phosphorylation of histone 3 (H3) on Ser 10 (S10) in mitosis (38). Phosphorylation of H3 on S10 is a well-characterized and evolutionary conserved mitotic event (6, 17, 22, 23, 45).
Recent experiments with small interfering RNA (siRNA) implicated HDAC1 and HDAC3 in the regulation of proliferation and survival of cancer cells (13). In particular, the idea that HDAC1 can also be a potential target for therapeutic intervention in certain cancers stems from a series of studies. HDAC1 has been shown to inhibit estrogen receptor alpha protein expression and transcriptional activity, suggesting that it can modulate breast cancer progression (32). Overexpression of HDAC1 at mRNA and protein levels was reported for human gastric and prostate tumors (5, 18, 34, 44), whereas overexpression of HDAC3 is seen with colon tumors (54). Furthermore, published data indicate a role of mouse HDAC1 in the regulation of proliferation and development. For instance, the expression of HDAC1 is induced upon growth factor activation of mouse T cells and fibroblasts (3, 19) and HDAC1 levels were found to be elevated in highly proliferative tissues, embryonic stem (ES) cells, and several transformed cell lines (3, 37), suggesting a link between HDAC1 function and proliferation. In accordance with this idea, disruption of the HDAC1 gene resulted in reduced proliferation of mouse embryos and ES cells (37), whereas overexpression of HDAC1 led to impaired cell proliferation of murine fibroblasts (3). Taken together, these results suggest that class I HDACs are crucial in controlling the proliferation state of mammalian cells.
HDAC1 and HDAC2 often heterodimerize and are generally found in large multiprotein complexes: the Sin3, NuRD, and CoREST complexes (16). Numerous transcription factors, including regulators of cell cycle, differentiation, and development, have been shown to associate directly with HDAC1 and HDAC2 or with HDAC1/HDAC2 complexes, thereby mediating the repression of specific target genes (1, 7, 42). Furthermore, the loss of Sds3, a component of the Sin3/HDAC1/HDAC2 complex and a putative recruiting factor, led to cell death due to missegregation of chromosomes during mitosis (8). Therefore, both HDAC1- and HDAC1/HDAC2-mediated chromatin modifications seem to be important for cell cycle control and development. In light of this evidence, we conducted a study to analyze the effect of depleting class I deacetylases in human tumor cells by RNA interference (RNAi). We show here that by ablating either HDAC1 or HDAC3 protein expression there is an inhibition of tumor cell proliferation. Clearly, HDAC1 knockdown abolishes the ability of tumor cells to proceed through mitosis. On the contrary, HDAC2 knockdown shows no effect, unless we concurrently knock down both HDAC1 and HDAC2. In addition, we also conducted an analysis of the changes in gene expression in U2OS cells in response to knockdown of deacetylases and demonstrated that a large number of HDAC target genes are involved in proliferation and apoptosis.
The overall evidence therefore points to the idea that each individual class I HDAC plays a different role in regulating genes involved in various biological processes.
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Transfection of cells with siRNA, electrophoresis, and Western blotting. siRNAs were ordered from MWG BIOTECH and prepared according to the manufacturer's instructions (stock concentration of 20 µM in molecular-biology-grade water). Oligofectamine was used for all siRNA transfections (Invitrogen, San Diego, CA). The following siRNA sequences were used: 5'-CGUACGCGGAAUACUUCGATT-3' for siRNA LUC (control), 5'-CAGCGACUGUUUGAGAACCTT-3' and 5'-CUAAUGAGCUUCCAUACAATT-3' for siRNA HDAC1, 5'-UCCGUAAUGUUGCUCGAUGTT-3' for siRNA HDAC2, and 5'-GAUGCUGAACCAUGCACCUTT-3' for siRNA HDAC3.
Oligofectamine reagent was diluted and used according to the manufacturer's instructions. The amount of siRNA used was optimized and fixed for each knockdown experiment. A second cycle of siRNA transfection was performed 24 h later. Cells were harvested 72 h after the first cycle of transfection and stored at 80°C until lysis in urea buffer (8 M urea, 0.1 M NaH2PO4, 0.01 M Tris, pH 8).
After Western blotting, primary antibodies anti-HDAC1 (monoclonal mouse antibody; Upstate), anti-HDAC3 (ab 7030; Abcam), and anti-caspase-3 (H-277; Santa Cruz Biotechnology) were incubated with membrane overnight at 4°C; anti-HDAC2 (ab 7029; Abcam), anti-p21 (a kind gift from K. Helin's lab), anti-acetylated H3/H4 (in-house antibody), antitubulin (DM1A; Sigma), and anti-H3 (ab 1791; Abcam) were incubated for 2 h at room temperature. Proteins were visualized by chemiluminescence with ECL Western blotting detection reagents (Amersham Biosciences).
Growth curve. To determine the effects of siRNA knockdown on cell proliferation, 24 h after transfection, cells were collected by trypsinization, counted by use of a hemacytometer with trypan blue dye, and plated at 3,000 viable cells/well for U2OS and MCF7 or 2,000 viable cells/well for MCF10A into a 96-well tissue culture dish in a final volume of 200 µl. Every 24 h, a 96-well tissue culture dish was stained with crystal violet solution and left to dry. Then, crystal violet incorporated in the cellular membrane was solubilized with a solution of 10% acetic acid-phosphate-buffered saline (PBS) and the absorbance at 595 nm was measured with an MRX microplate reader (Dynatech). We calculated the increase (n-fold) of the absorbance as the ratio of absorbance at time i/absorbance at time zero (where time i is 48, 72, or 96 h after siRNA transfection and time zero is 48 h after transfection). Each experimental point is the average of three independent experiments, with the respective standard deviation.
Colony formation assay. Twenty-four hours after transfection, cells were collected by trypsinization, counted by use of a hemacytometer with trypan blue dye, and plated at 3,000 viable cells/well for U2OS and MCF7 or 2,000 viable cells/well for MCF10A into a six-well tissue culture dish. Six days after plating, cells were stained with crystal violet solution (1% crystal violet, 35% ethanol) and colonies were counted. We calculated the relative CFU as follows: number of colonies of each sample/number of colonies of the control. The average relative CFU of three plates was calculated, with the respective standard deviation.
Fluorescence-activated cell sorter (FACS) analysis of cell cycle. To detect HDAC1, phosphorylated S10 at H3 (H3-P), and DNA or HDAC1, cyclin A, and DNA, 72 h after the first cycle of transfection, both attached cells and supernatant were collected and resuspended at 106 cells/ml in 1% formaldehyde for 15 min. After PBS washing, the pellet was resuspended in ice-cold 70% ethanol and stored at 4°C. For immunodetection, cells were washed twice in PBS and permeabilized in 0.1% Triton X-100 in PBS for 10 min. After being blocked in 5% normal goat serum for 20 min, cells were incubated with anti-HDAC1 mouse monoclonal antibody (Upstate), 1:250, and anti-H3-P rabbit polyclonal antibody (Upstate) or anti-cyclin A (Pharmingen), 1:100, in PBS plus 1% bovine serum albumin for 2 h at room temperature. Cells were rinsed in PBS and incubated for 1 h with Cy5-conjugated goat anti-mouse (1:50; Jackson Immunoresearch) and fluorescein isothiocyanate (FITC)-conjugated goat anti-rabbit antibodies. Cells were washed again and resuspended in 1 ml of a solution containing 2.5 µg/ml propidium iodide (PI) (Sigma) in PBS and 250 µg/ml RNase in PBS and incubated overnight at 4°C before acquisition.
Samples were acquired on a FACSCalibur (Becton Dickinson) flow cytometer. At least 10,000 events were acquired. Analysis was performed using CellQuest 3.3 (Becton Dickinson).
FACS analysis for activation of caspase-3. For active caspase-3 analysis, 96 h after the first cycle of transfection, both attached cells and supernatant were collected, fixed in 1% formaldehyde in PBS and then in 70% cold ethanol, and permeabilized in 0.1% Triton X-100 for 10 min. Prior to incubation with anti-caspase-3 polyclonal antibody (9661L; Cell Signaling), cells were incubated for 30 min with 10% goat serum in PBS. After being washed, cells were incubated with anti-rabbit FITC antibody (Sigma) for 1 h at room temperature (light protected). The labeled cells were stained overnight at 4°C in 2.5 µg/ml PI and RNase 250 µg/ml in PBS. The cellular suspension was passed through a FACSCalibur (Becton Dickinson) flow cytometer. At least 10,000 events were acquired, and analysis was performed using CellQuest 3.3 (Becton Dickinson) and ModFit LT 3.1 software.
Cell synchronization. Twenty-four hours after the first cycle of siRNA transfection (see above), cells were synchronized in the G1/S transition by treatment with 2 mM thymidine for 14 h, released for 8 h, and then treated again with thymidine for 14 h. After two washes with PBS, cells were cultured in fresh medium or in medium with 0.1 µg/ml nocodazole for different times (as indicated in each experiment) and harvested. Cells were synchronized in prometaphase by treatment with 0.1 µg/ml nocodazole for 16 h and then released from the drug-induced cell cycle block by being washed three times with PBS.
Time-lapse microscopy. Time-lapse microscopy was performed by use of a Cell R imaging station for live-cell microscopy (Olympus) mounted on an IX81 inverted microscope (Olympus) equipped with an incubation chamber (Evotec). The system includes a Hamamatsu ORCA-ER charge-coupled-device camera for image acquisition. A movie montage was performed using ImageJ image analysis software (W. Rasband, National Institutes of Health, Bethesda, MD).
Statistical immunofluorescence. Forty-eight hours after siRNA transfection, cells were plated on four-chamber slides pretreated with 15 µg/ml poly(D)lysine (Sigma) and treated with 0.1 µg/ml nocodazole for 16 h to enrich the mitotic population. Slides were fixed in 4% paraformaldehyde-1x PIPES [piperazine-N,N'-bis(2-ethanesulfonic acid)] for 10 min, permeabilized with 0.1% Triton X-100 and 0.2% bovine serum albumin in PBS, and processed using standard protocols. The primary antibodies used were anti-HDAC1 monoclonal (Upstate) at 1:250 and anti-H3-P rabbit polyclonal (Upstate) at 1:100, and the conjugated secondary antibodies were Cy3-conjugated goat anti-mouse (Jackson Laboratories) and FITC-conjugated goat anti-rabbit (Sigma). DAPI (4',6'-diamino-2-phenylindole) (Sigma) was used for nuclear counterstaining. Fluorescence microscopy images were acquired using a BX61 (Olympus) motorized fluorescence microscope. Acquired images were visualized using a browser developed with the ImageJ macro language. After acquisition of DAPI, Cy3, and FITC channels, DAPI staining was employed to identify cell nuclei and to build a mask for successive calculations. The mean nuclear levels of DAPI, HDAC1, and H3-P were stored in the memory to allow later statistical analysis. HDAC1 fluorescence distribution was evaluated in control- and HDAC1-interfered cells in order to establish an arbitrary threshold used to discriminate HDAC1-positive (gate II) and HDAC1-negative (gate I) cells. H3-P fluorescence distribution was evaluated in gate I and gate II to fix a value above which cells were H3-P positive and below which they were negative. We evaluated for both gate I and gate II the percentages of double positive cells.
Extraction of RNA and reverse transcription-PCR. For validation of the microarray results, we employed independent RNA preparations of the samples described above. Total RNA was isolated by using a QIAGEN RNeasy Protect mini kit as described by the manufacturer. cDNA was generated by reverse transcription-PCR with PE Applied Biosystem TaqMan reverse transcription reagents. Relative levels of specific mRNA were determined with a 5' nuclease assay (TaqMan) chemistry system. All PCRs were performed with an ABI 7900HT sequence detection system. The GAPDH (glyceraldehyde-3-phosphate dehydrogenase) gene was used as a control gene for normalization.
Microarray analysis. Biotin-labeled cRNA targets were obtained from 5 µg of total RNA derived from samples as described above. cDNA synthesis was performed with a Gibco SuperScript custom cDNA synthesis kit, and biotin-labeled antisense RNA was transcribed using an in vitro transcription system (Ambion, Inc., Austin, TX) including Bio-11-UTP and Bio-11-CTP in the reaction (NEN Life Sciences, Boston, MA). GeneChip hybridization, washing, staining, and scanning were performed according to Affymetrix protocols (Santa Clara, CA). Two copies of the HG-U133Plus GeneChip were hybridized with each target. Full details of microarray methods are described in the supplementary data posted at http://bio.ifom-ieo-campus.it/supplementary/MCB49407/.
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FIG. 1. siRNA-mediated knockdown of HDAC1, HDAC2, and HDAC3 in U2OS, MCF7, and MCF10A cells. The loss of both HDAC1 and HDAC2 produced a hyperacetylation of histones H3 and H4. (A to C) Relative (rel.) expression levels of the indicated mRNAs were determined by real-time PCR, as described in Materials and Methods. Averages of three independent experiments are shown, and standard deviations are indicated by the error bars. (D to F) Western blots of U2OS whole-cell extracts after transfection of siRNA HDAC1, HDAC2, HDAC3, and HDAC1 plus HDAC2. Cells were transfected and processed as described in Materials and Methods, and 30 µg was loaded per lane. As a control (CTRL), we used transfection of antiluciferase siRNA.
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FIG. 2. Absence of either HDAC1 or HDAC3 causes a defective proliferation. (A to C) Growth curves of U2OS, MCF7, and MCF10A transfected with HDAC siRNAs. The increase of absorbance at 595 nm is directly correlated with cell proliferation, as described in Materials and Methods. Each curve represents the average of three independent experiments, and the standard deviation is indicated by the error bars. (D to F) CFU assay of U2OS, MCF7, and MCF10A cells transfected with HDAC siRNAs. The ratio of the CFU number of each sample/CFU number of the control was calculated. Each column represents the average of three independent experiments, with the respective standard deviations. CTRL, control.
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siRNA-mediated knockdown of HDAC1 and HDAC3 diminishes cellular viability and proliferation. It is known that HDAC inhibitors lead to p21 induction. They also induce cell cycle arrest in either G1 or G2/M and apoptosis, killing tumor cells (4, 29, 48). The pathway leading to tumor cell death is still unknown, but it is very unlikely that a single molecular pathway will be identified in all cell types for all HDAC inhibitors. We decided to investigate cellular viability and proliferation of U2OS, MCF7, and MCF10A cells after HDAC knockdown. Clearly, the absence of HDAC1, HDAC3, and HDAC1 plus HDAC2 generated a remarkable defect in proliferation in both U2OS and MCF7 cell lines (Fig. 2A and B) but had an almost unnoticeable effect in the MCF10A cell line (Fig. 2C). The lack of HDAC2 had a much less pronounced effect on all cells (Fig. 2A to C). This is inconsistent with published data but is probably due to the different cell lines used (24). We then analyzed the effect of the absence of all three HDACs on the life spans of all three cell lines. In correlation with the results in Fig. 2A to C, cells lacking HDAC1, HDAC3, or the combination HDAC1 plus HDAC2 had a diminished capacity to form colonies when plated at a low density (Fig. 2D to F). These data suggest that both HDAC1 (either alone or in combination with HDAC2) and HDAC3 have important roles in the proliferation of tumor cells, in agreement with published data indicating a relevant role of murine HDAC1 for the regulation of proliferation and development (37). An HDAC3-AKAP95/HA95-Aurora B pathway regulating mitosis has been demonstrated recently, explaining the mitotic defect observed after HDAC3 siRNA (38). It is interesting to note that in the cell line MCF10A, the untransformed counterpart of MCF7, the absence of all three HDACs had less effect on cellular proliferation.
HDAC1 knockdown cells have a marked reduction of H3 S10 phosphorylation. H3-P is a mitotic marker. To explore whether the defect in proliferation of HDAC1 knockdown cells was due to a mitotic defect, we applied single-cell statistical analysis to both control-interfered and HDAC1-interfered cells by using an anti-HDAC1 antibody and an anti-H3-P antibody (see Materials and Methods). We analyzed all three cell lines for mitotic cells in the presence and absence of HDAC1 (Fig. 3). Figure 3A, B, and C show histograms reporting the distributions of HDAC1 levels in control-interfered populations and HDAC1-interfered populations, as described in Materials and Methods. As shown in the upper panels, we were able to discriminate between HDAC1-positive cells (gate II) and HDAC1-negative cells (gate I). The middle panels represent the distributions of H3-P levels in the two gates in order to define the basal level of H3-P-positive cells. In the lower panels, the correlation between HDAC1 and H3-P levels in the two gates is represented. Interestingly, knockdown of HDAC1 led to a clear reduction in the number of H3-P-positive cells, suggesting that HDAC1 could be important for proper cell cycle progression. Again, the effect was not as drastic in the MCF10A cell line (Fig. 3C).
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FIG. 3. Absence of the mitotic marker H3-P in HDAC1-deficient cells. U2OS, MCF-7, and MCF10A cells were analyzed for the presence of H3-P. (Top) Distribution of the HDAC1 signal over the siRNA-control (CTRL)-transfected and siRNA-HDAC1-transfected populations. The dashed line represents the arbitrary threshold used to distinguish HDAC1-negative (gate I) from HDAC1-positive (gate II) cells. (Middle) Distribution of H3-P signals in gate I and gate II. The dashed line represents the arbitrary threshold used to distinguish between positive and negative H3-P cells. (Bottom) Scatter plot of HDAC1 signal versus H3-P signal. The percentages inside the plot indicate the percentages of double positive cells.
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FIG. 4. HDAC1-deficient cells arrest in G1 or die during G2/M transition. (A) Asynchronous (As) siRNA-control (CTRL)-transfected (black) and siRNA-HDAC1-transfected (gray) U2OS cells were blocked in G1/S transition by use of thymidine and then released in fresh medium. (Top) DNA content was analyzed by FACS analysis of PI-stained cells at different time points after the release in fresh medium. (Bottom) Biparametric FACS analysis using anti-H3-P and PI staining was performed to calculate the percentages of cells in G1, S, G2, and M phases at each time point. (B) U2OS control- and HDAC1-interfered cells were blocked in G1/S transition by use of thymidine and then released in medium containing nocodazole. (Top) DNA content was analyzed by FACS analysis of PI-stained cells at different time points. (Middle) Biparametric FACS analysis using anti-cyclin A (CYCA) and PI staining was performed to calculate the percentages of cells in G1/S, G2, and M phases at each time point. (Bottom) DNA content was analyzed by FACS analysis to evaluate the percentages of sub-G1 cells. (C) U2OS control- and HDAC1-interfered cells were blocked in G2/M transition by use of nocodazole and then released in fresh medium. (Top) DNA content was analyzed by FACS analysis on PI-stained cells at different time points. (Bottom) DNA content was analyzed by FACS analysis to evaluate the percentages of sub-G1 cells. (D) (Top) Percentages of cells in the control- and HDAC1-interfered population able to undergo mitosis at least once in 30 h. (Bottom) Images of time-lapse experiments with U2OS siRNA-CTRL-transfected and siRNA-HDAC1-transfected cells. Control cells experience normal mitosis (white arrowheads), while HDAC1 knockdown cells cannot enter in mitosis and they die (yellow and black/white arrowheads).
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We next analyzed the proportion of sub-G1 cells after release from the nocodazole block. As shown in Fig. 4C, we observed massive apoptosis in HDAC1-negative U2OS cells. Taken together, these data demonstrate that the proliferative defect of HDAC1 knockdown cells is due to both partial G1 arrest and cell death either at the G2/M transition or at the very beginning of mitosis. Alternatively, HDAC1-deficient cells could become insensitive to nocodazole and grow to be G1 tetraploids. However, when we followed living cells by time-lapse microscopy, we observed the inability of HDAC1-negative cells to condense and enter mitosis, suggesting that these cells die during G2/M transition (Fig. 4D). Our data confirm and extend published findings showing that HDAC inhibitors induce G1 and/or G2/M arrest and/or apoptosis (4).
Induction of apoptosis in HDAC1-deficient U2OS cells. The observation that there were differences in the numbers of apoptotic cells after HDAC1 knockdown prompted us to confirm apoptotic cell death by examining caspase-3 activation, both by FACS analysis (Fig. 5A) and by Western blot analysis (Fig. 5B) (see Materials and Methods). Our results indicate that caspase-3 activation is involved in apoptosis after HDAC1 knockdown.
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FIG. 5. HDAC1 knockdown cells undergo apoptosis. (A) Effect of siRNA HDAC1 on caspase-3 activation by FACS analysis. The bars represent the percentages of cleaved caspase-3-positive cells in control (CTRL) and siRNA-HDAC1-transfected U2OS cells after 96 h. The values correspond to the averages of three independent experiments, and the error bars indicate the associated standard deviations. (B) Western blots of U2OS whole-cell extracts after transfection of control or siRNA HDAC1. Cells were collected 120 h after transfection, and 50 µg of lysates was loaded per lane. As a control, we used an injection of antiluciferase siRNA. The anti-caspase-3 antibody used was able to recognize both full-length inactive and cleaved active forms.
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Ablation of HDAC1, HDAC2, HDAC3, or HDAC1 plus HDAC2 resulted in the altered expression of 987, 283, 1,317, or 601 genes, respectively (see supplementary Table 1 posted at http://bio.ifom-ieo-campus.it/supplementary/MCB49407/). There is a large degree of overlap between the lists of genes regulated by siRNA of HDAC1 and those regulated by siRNA of HDAC1 plus HDAC2. Ablation of HDAC2 results in a mild phenotype and, compared to the other conditions, is associated with the deregulated expression of few genes, 86% of which are also deregulated under one of the two above-mentioned conditions. Only 31% of genes deregulated by HDAC3 siRNA are in common with those regulated by siRNA of HDAC1 or HDAC1 plus HDAC2 (see the supplementary data and supplementary Table 1 posted at the URL mentioned above). Hierarchical clustering using any of the lists of regulated genes confirms there is a higher degree of similarity in the gene expression profiles resulting from ablation of HDAC1, HDAC2, or HDAC1 plus HDAC2 than in those resulting from ablation of HDAC3 (Fig. 6).
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FIG. 6. Gene expression profiles. Supervised hierarchical clustering (according to Pearson's correlation) was performed using comparative expression values of the gene lists indicated above each dendrogram (for gene lists, see supplementary Table 1 posted at http://bio.ifom-ieo-campus.it/supplementary/MCB49407/). In all cases, the expression value for the control cells was used as the baseline (value of 1).
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FIG. 7. Gene expression profiles and quantitative real-time PCR. (A) Graphic representation of the expression patterns of genes functionally involved in apoptosis and proliferation regulated by ablation of HDAC1 or HDAC1 plus HDAC2 in U2OS cells. (B) Validation of microarray data by TaqMan quantitative real-time PCR. The error bars indicate the standard deviations from three independent experiments. CTRL, control.
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Based on our microarray results, the analysis of global gene expression profiles of U2OS cells in the absence of HDAC1, HDAC2, HDAC3, or HDAC1 plus HDAC2 yielded a large number of genes that present altered expression levels (see the supplementary data posted at http://bio.ifom-ieo-campus.it/supplementary/MCB49407/). HDAC1 and HDAC1 plus HDAC2 knockdown regulated a largely overlapping set of genes, including most of those regulated by HDAC2 knockdown. HDAC3 knockdown caused the deregulation of a vast number of genes. Interestingly, 50% of genes induced by HDAC3 knockdown were also induced by ablation of HDAC1 or HDAC1 plus HDAC2 expression, whereas only 21% of genes repressed by HDAC3 knockdown were in common with the other conditions. These results could be a consequence of the protein reduction of HDAC1 and HDAC2 we observed after HDAC3 knockdown (Fig. 1).
Again, we analyzed in greater detail the genes regulated by HDAC1. In accordance with the proposed role of HDAC1 as a transcriptional repressor, more HDAC1 target genes were upregulated than downregulated in the absence of HDAC1. Interestingly, this result evened out when both HDAC1 and HDAC2 were ablated. This is in line with several reports that have demonstrated the independent recruitment of HDAC1 and HDAC2 to target genes (26, 49).
Because of the phenotype observed in the absence of HDAC1 (and HDAC1 plus HDAC2), we validated genes involved in apoptosis and proliferation. Notably, a number of cyclins, cyclin-dependent kinases, and the cyclin-dependent kinase inhibitor p21, whose expression is tightly coordinated to regulate appropriate cell cycle progression, were induced after RNAi treatment against HDAC1. p21 has been regarded as an attractive therapeutic target in human cancer. Although a plethora of data regarding the role of this multifunctional protein in many cellular pathways has emerged, the precise mechanism by which p21 regulates cell cycle progression is still unknown, partly because p21 can act in both a positive and a negative fashion toward cell proliferation (53). Given that p21 expression is increased upon HDAC1 knockdown in U2OS cells but not in MCF7 cells, we would argue that the mitotic phenotype observed in these two tumor cell lines is not linked to p21. Our microarray data also showed repression of CDC25C and septin 6. In Saccharomyces cerevisiae, the septins are a family of cell division cycle regulatory proteins and have been associated with actin stress fibers in interphase cells, the cleavage furrow of dividing cells, and the bud neck of budding yeast (reviewed in reference 31). The human homologue of septin 6 has been found to be fused to MLL in a few cases of infant acute myeloid leukemia (43). Cdc25C phosphatase is a major cell cycle regulator in mammals. Its C-terminal catalytic phosphatase domain dephosphorylates Cdc2 to promote G2/M transition (27), whereas the N-terminal regulatory domain contains multiple phosphorylation sites. Multisite phosphorylation of Cdc25C by different kinases recruits specific proteins, controlling the normal cellular mitotic progression (reviewed in reference 56). Clearly, both Septin6 and Cdc25C have important roles in mitosis. Finally, the activation of many interleukins after HDAC ablation could be because of a postapoptotic activation of an inflammation response.
In summary, we have defined a role for HDAC1 in the proliferation of human tumor cells and, most importantly, identified a mitotic defect in human tumoral cells after knockdown of HDAC1. These results confirm once again the importance of characterizing the biological function of HDAC1, also in light of its potential significance as a target for cancer therapy.
This work was supported by grants from the Associazione Italiana per la Ricerca sul Cancro (AIRC) to S.C., from the GEN-AU program of the Austrian Ministry of Science to C.S., and from the Italian Ministry of Health.
Published ahead of print on 30 April 2007. ![]()
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