Original Article | Published:

p27Kip1 represses transcription by direct interaction with p130/E2F4 at the promoters of target genes

Oncogene volume 31, pages 42074220 (20 September 2012) | Download Citation


The cyclin-cdk (cyclin-dependent kinase) inhibitor p27Kip1 (p27) has a crucial negative role on cell cycle progression. In addition to its classical role as a cyclin-cdk inhibitor, it also performs cyclin-cdk-independent functions as the regulation of cytoskeleton rearrangements and cell motility. p27 deficiency has been associated with tumor aggressiveness and poor clinical outcome, although the mechanisms underlying this participation still remain elusive. We report here a new cellular function of p27 as a transcriptional regulator in association with p130/E2F4 complexes that could be relevant for tumorigenesis. We observed that p27 associates with specific promoters of genes involved in important cellular functions as processing and splicing of RNA, mitochondrial organization and respiration, translation and cell cycle. On these promoters p27 co-localizes with p130, E2F4 and co-repressors as histone deacetylases (HDACs) and mSIN3A. p27 co-immunoprecipitates with these proteins and by affinity chromatography, we demonstrated a direct interaction of p27 with p130 and E2F4 through its carboxyl-half. We have also shown that p130 recruits p27 on the promoters, and there p27 is needed for the subsequent recruitment of HDACs and mSIN3A. Expression microarrays and luciferase assays revealed that p27 behaves as transcriptional repressor of these p27-target genes (p27-TGs). Finally, in human tumors, we established a correlation with overexpression of p27-TGs and poor survival. Thus, this new function of p27 as a transcriptional repressor could have a role in the major aggressiveness of tumors with low levels of p27.


The protein p27Kip1 (p27) is a cell cycle regulator whose main known function is the regulation of cyclin-dependent kinase (cdk) activities (Sherr and Roberts, 1999). The importance of p27 as a cell cycle regulator in vivo was revealed by the generation of p27−/− mice that display an increase in body size and multiple organ hyperplasia (Fero et al., 1996; Nakayama et al., 1996) (Kiyokawa et al., 1996). This protein was originally considered as a ‘universal’ inhibitor of cyclin-cdk complexes whose activity was exerted by the N-terminal half of the molecule (Russo et al., 1996). However, recent reports revealed a dual role of p27, behaving as an inhibitor or and activator of cyclin D-cdk4/6 and cyclin E-cdk2 on depending of specific tyrosine phosphorylation (Chu et al., 2007; Grimmler et al., 2007; Blain, 2008; James et al., 2008).

p27 deficiency is associated with tumorigenesis. Reduced p27 levels are frequently observed in human cancers in association with tumor aggressiveness and poor clinical outcome (Slingerland and Pagano, 2000). In most of the cases, low levels of p27 are the consequence of an increased protein degradation (Frescas and Pagano, 2008). In some tumors, cytoplasmic localization of p27 is also associated with increased motility, aggressiveness and poor prognosis (Viglietto et al., 2002).

Quiescent cells contain high levels of p27 mostly located in the nucleus. After mitogenic stimulation, it translocates to the cytoplasm where it is degraded via ubiquitin–proteasome (Shirane et al., 1999). In the cytoplasm, p27 performs several cdk-independent activities. It participates in both actin cytoskeleton rearrangement and cell motility through the modulation of RhoA activity, a role that relies in the C-terminal half of p27 (McAllister et al., 2003; Besson et al., 2004). p27 also interacts with stathmin, a microtubule-associated protein, thus regulating cell morphology and motility (Baldassarre et al., 2005). These regulatory roles of p27 on cell migration have been associated with the cdk-independent oncogenic functions of cytoplasmic p27 (Besson et al., 2008).

It is assumed that the main function of nuclear p27 during early G1 is to prevent premature entry into S phase by maintaining cyclin E/cdk2 complexes inactive (Chu et al., 2008). However, whether nuclear p27 in quiescent cells solely acts as a CDK inhibitor or may fulfill other nuclear functions remains unclear. It has been postulated that p27 may participate in the regulation of transcription independently of cyclin-cdk regulation. It has been shown that the interaction of p27 with neurogenin-2 leads to the differentiation of neural progenitors in the cortex. Specifically, p27 stabilizes neurogenin-2 by a mechanism that depends on the integrity of its N-terminal half but does not require interactions with cyclins and cdks (Nguyen et al., 2006). Moreover, the overexpression of p27 in C2C12 cells induces myogenic differentiation, whereas elimination of p27 prevents differentiation (Munoz-Alonso et al., 2005). In another example it has been shown that overexpression of p27 induces the expression of erythroid markers in the K562 cell line (Acosta et al., 2008). All these data suggested that the nuclear role of p27 in quiescence might rely not only on the inhibition of cyclin-cdk complexes but also on the transcriptional repression of specific target genes.

Thus, we hypothesize that p27 could interact with transcriptional regulators at specific gene promoters. We explored this possibility by chromatin immunoprecipitation (ChIP) analysis followed by promoter microarrays (chip). Results revealed that p27 associates with a number of promoters in quiescent cells. These p27 target genes (p27-TGs) are mainly involved in RNA processing, translation, cell cycle and respiration. We found that p27 has a role as a transcriptional repressor in coordination with p130 and E2F4. We have shown that p27-TGs are overexpressed in different tumors and this is associated with poor clinical outcome.


p27 binds to specific gene promoters

Quiescent cells contain high levels of p27 mostly in the nucleus (Supplementary Figure S1) (Shirane et al., 1999). Whether p27 has a role, aside from cyclin-cdk inhibition in the nucleus of quiescent cells still remains unclear. We therefore tested the possibility that p27 could associate with specific gene promoters to regulate transcription. ChIP on chip experiments performed in quiescent cells revealed that p27 significantly associates with a number of gene promoters (Figure 1a and web Supplementary dataset S1). The interaction of p27 with some of these promoters was validated by real time qPCR of immunoprecipitated chromatin fragments (Figure 1b). Gene ontology enrichment analysis indicates that p27 target genes (p27-TGs) are mostly involved in pre-mRNA processing and splicing, mitochondrial biogenesis and respiration, translation and cell cycle (Figure 1c).

Figure 1
Figure 1

p27 associates with specific gene promoters in quiescent NIH 3T3 cells. (a) DNA was immunoprecipitated with anti-p27 or IgG and then, labeled with Cy5 and Cy3, respectively, whereas input DNA remained unlabeled. Both samples were hybridized in two different arrays, one with p27 vs input and the other one with IgG vs input. This plot represents the log ratio of channels (Cy3 and Cy5) as M value (M=log2(Cy3)-log2(Cy5)) vs the intensity of each spot in the array (A=(log2(R)+log2(G))/2) as log of geometric average of the channels intensities for each spot (Cy3=red, Cy5=green). (b) ChIP was performed with anti-p27 and then real time qPCR was performed using specific primers for the 19 mentioned gene promoters. Results were normalized vs the values obtained with the IgG control and represented as the relative binding. (c) p27-TGs were analyzed for enrichment of GO terms using binomial distribution in Gitools. This test measures whether the proportion of genes with particular GO term is significantly higher than random expectations. P-values are shown in a color code scale; red color shows significant P-values after multiple testing correction, indicating enrichment for a particular GO term. Gray means no statistically significant difference.

p27 associates with specific transcription factors (TFs) on the p27-TG promoters

We then analyzed the promoter sequences of the p27-TGs for the presence of TF-binding sites. Using the TRANSFAC database, we found that target sequences of ETS1, E2F4 and GABP were significantly enriched in the promoters of these genes (Figure 2a). We subsequently analyzed whether p27-TGs were also targeted by these three mentioned TFs (Hollenhorst et al., 2007; Lopez-Bigas et al., 2008). Results revealed that p27 shared a significant number of target genes with these TFs and additionally also with ELF1 and RBP2 (Figure 2b and web Supplementary analysis S1).

Figure 2
Figure 2

p27 associates with E2F4-p130 complexes and with ETS1 on the promoters of p27-TGs. (a) Identification of the enrichment of predicted transcription factors-binding sites (TFBS) in p27-TG promoters. The P-values are shown in a color code scale; red shows significant P-values, whereas gray means no statistically significant difference. (b) Enrichment of experimentally validated target genes for several transcription factors among p27-TGs. In all cases, these analyses were performed by Poisson statistics as described under material and methods. (c) IP experiments were performed in NIH 3T3 quiescent cells using anti-p27 or non-specific IgGs (used as a control). The presence of p27 and E2F4 in the immunoprecipitates was detected by WB. (d) ChIP experiments using antibodies against E2F4 and p27 and a non-specific IgG were performed on four p27-TG promoters and on a control promoter (HoxB8). E2F consensus sites in these promoter sequences are shown in the Supplementary Figures S3 and S4. (e) IP experiments were performed using anti-p27 or non-specific IgGs (used as a control). Then, the immunoprecipitates were analyzed for the presence of p130, mSIN3A, HDAC1, 4 and 5 by WB. (f) ChIP experiments were performed to determine the presence of repressors mentioned in (e) on the promoters of the mentioned p27-TGs and on a control promoter (HoxB8). (g) IP experiments were performed using anti-p27 or non-specific IgGs (used as a control). The presence of p27 and ETS1 in the immunoprecipitates was detected by WB. (h) ChIP experiments using antibodies against ETS1, p27 and a non-specific IgG were performed on two p27-TG promoters and on a control promoter (HoxB8). ETS consensus sites in these promoter sequences are shown in the Supplementary Figure S5.

To analyze the putative interaction of p27 with E2F4, we performed immunoprecipitation (IP) experiments with anti-p27 and observed that E2F4 co-immunoprecipitated with p27 (Figure 2c). This interaction was confirmed by IPs with anti-E2F4 in mice embryo fibroblasts (MEFs) p27WT or p27−/− (Supplementary Figures S2a and b). Moreover, by ChIP, we demonstrated that p27 and E2F4 simultaneously associated with several p27-TG promoters enriched with E2Fs-binding sequences (Supplementary Figures S3 and S4) but not with the control (HoxB8) (Figure 2d). We subsequently studied whether p27 interacted with specific co-repressors known to be associated with E2F4. IP experiments revealed that p27 co-immunoprecipitated with endogenous p130, mSIN3A and histone deacetylases (HDACs) 1, 4 and 5, indicating that they form complexes in vivo (Figure 2e). The interaction of p27 with p130 was confirmed by IPs with anti-p130 (Supplementary Figure S2c). Finally, we checked whether all these repressors associated with p27 on p27-TG promoters. As observed in Figure 2f, in quiescent cells p27 associated with p130, mSIN3A and HDACs 1, 4 and 5 on several p27-TG promoters but not on the control gene promoter. We also observed that p27 co-immunoprecipitated with ETS1 (Figure 2g). Moreover, ChIP experiments revealed the simultaneous presence of p27 and ETS1 on some p27-TG promoters enriched with Ets-binding sites (Figure 2h and Supplementary Figure S5).

p130 directly interacts with p27 and recruits it on the p27-TG promoters

To analyze the functional relationship between p27 and p130/E2F4 in transcriptional regulation, we performed IP experiments using anti-p27 on extracts from p27wt, p27−/− and p130−/− MEFs and additionally on extracts from two MEF-lines harboring a p27 mutant containing a deletion of the first 51 aa (p27Δ51) or four punctual mutations that unable its interaction with cyclins and cdks (p27CK−; Supplementary Figure S6). Results revealed that p27wt, p27Δ51 and p27CK− interacted with p130 (Figure 3a), indicating that this association is cyclin-cdk independent. Then, we studied whether p130 was able to directly interact with p27. Thus, affinity chromatography experiments using two fragments of p27: the N-terminal half (aa 1–110) (p27-NT) and the C-terminal half (aa 110-198) (p27-CT), coupled to sepharose 4B were performed. Two different fragments of p130: p130NT (aa 1-417) and p130CT (aa 967-1082) were separately loaded onto both p27 columns. Results showed that fragment p130CT, but not p130NT, directly interacted with p27-CT on the column (Figure 3b). Similar experiments were performed by loading purified E2F4 on both p27 columns. Results revealed that p27-CT but not p27-NT was able to directly associate with E2F4 (Figure 3c).

Figure 3
Figure 3

p130 targets p27 to the promoters. (a) Immunoprecipitation of p27 in p27wt, p27CK−, p27Δ51, p130−/− and p27−/− MEFs were performed to evaluate the interaction of cyclin D1, CDK4 and p130 with the different variants of p27. The presence of these proteins in the immunoprecipitates was determined by WB. (b, c) Affinity chromatography columns containing p27-NT (aa 1-110) or p27-CT (aa 110-198) were loaded with purified p130NT and p130CT (b) or E2F4 (c). After extensive washing the unbound protein (UB), the last wash (W) and the bound protein was measured by WB. (d, e) Graphical representation of chromatin enrichment obtained in ChIP experiments using p27 (d) or p130 (e) antibodies and performed in p27wt, p27CK−, p27Δ51, p130−/− and p27−/− MEFs. (f) IP experiments on p130−/− MEFs were performed using anti-p27 or non-specific IgGs (used as a control). The presence of p27, p130 and E2F4 in the immunoprecipitates was detected by WB.

Next, we studied whether p27 needs p130 to be recruited on the promoters. Thus, ChIP experiments using anti-p27 were performed on p27wt, p27CK−, p27Δ51, p27−/− and p130−/− MEFs. Results revealed that all these forms of p27 (p27wt, p27CK− and p27Δ51) significantly associated with p27-TGs promoters when p130 was present in the cells supporting the cyclin-cdk-independent interaction of p27 with promoters. In contrast, p27 did not associate with the promoters in p130−/− MEFs, indicating that p27 needs p130 to be recruited on the promoters (Figure 3d). Interestingly, ChIP experiments using anti-p130 showed that this protein interacted with promoters independently of p27 (Figure 3e). Finally, we aimed to study the p27-E2F4 interaction in p130−/− MEFs. IP experiments indicate that p130 is needed to form the p27-E2F4 complexes in the cells (Figure 3f).

p27 is necessary to recruit different co-repressors on p27-TG promoters

We next explored whether p27 is needed on the promoters to recruit co-repressors as mSIN3A or HDAC1. Thus, ChIP was performed with anti-p27, anti-HDAC1 and anti-mSIN3A on p27wt and p27−/− MEFs. Then, the association of these proteins with the Heatr1 and RBl2 promoters was analyzed by qPCR. Results showed that in the p27−/− MEFs the association of HDAC1 and mSIN3A with the Heatr1 promoters (Figure 4a and Supplementary Figure S7) and with the RBl2 promoter (Figure 4b and Supplementary Figure S7) was strongly reduced, indicating that p27 is necessary to recruit these co-repressors. Interestingly, the levels of the proteins encoded by these two genes are clearly increased in p27−/− cells (Figures 4c and d), suggesting that p27 could act as a transcriptional co-repressor. Figures 4e and f show that in p27−/− cells p130 and E2F4 still remain associated with these promoters. Finally, we observed that in the absence of p130, p27 still retains the ability to interact with both HDAC1 and mSIN3A co-repressors (Figure 4g).

Figure 4
Figure 4

p27 recruits co-repressors as HDAC1 and mSIN3A on the promoters. (a, b) Graphical representation of chromatin enrichment obtained in ChIP experiments using p27, HDAC1 or mSIN3A antibodies in quiescent p27WT and p27−/− MEFs on Heatr1 (a) and Rbl2 (b) promoters. Data are represented as the mean value±s.d. of three independent experiments. (c, d) Protein levels of Heatr1 (c) and Rbl2 (d) in p27WT and p27−/− MEFs as determined by WB. Levels of actin were used as a loading control. (e, f) Graphical representation of chromatin enrichment obtained in ChIP experiments using p130, E2F4 or ETS1 antibodies in quiescent p27WT and p27−/− MEFs on Heatr1 (e) and Rbl2 (f) promoters. Data are represented as the mean value±s.d. of three independent experiments. (g) IP experiments on p130−/− MEFs were performed using anti-p27 or non-specific IgGs (used as a control). The presence of p130, p27, HDAC1 and mSIN3A in the immunoprecipitates was detected by WB.

p27 is a transcriptional co-repressor

To analyze the role of p27 as a transcriptional regulator, we performed expression microarray analysis on quiescent p27wt and p27−/− MEFs. Results showed that a significant number of genes were differentially expressed in p27−/− vs p27wt cells. Among them, a significant group of p27-TGs showed an increased expression in p27−/− vs p27wt cells, indicating that p27 represses the expression of these genes (Figure 5a and web Supplementary datasets S2 and S3).

Figure 5
Figure 5

Deregulation of gene expression in p27-deficient and p27-mutated MEFs. (a) Comparative expression microarray analysis was performed in p27wt- and p27−/− MEFs. The Venn diagram shows the genes that are upregulated (red) or downregulated (dark blue) in the p27−/− MEFs (KO) vs p27wt cells. The expression of some p27-TGs was unmodified (yellow), whereas some others were overexpressed (orange) or downregulated (pale blue). P-values are shown in a color code scale; red color shows significant P-values, whereas gray means no statistically significant difference. (b, c) Venn diagrams representing the comparative expression analysis in p27CK vs p27wt cells (b) and p27CK−- vs p27−/− MEFs (c). (d) Diagrams showing the overlap of upregulated (upper panel) or downregulated (bottom panel) p27-TGs in p27CK− and p27−/− MEFs. (e) Venn diagrams of comparative expression analysis obtained in p27Δ51 vs p27wt MEFs. (f) Diagrams showing the overlap of upregulated p27-TGs in p27Δ51 and p27CK− MEFs. (g) Differentially expressed genes in p27CK−, p27Δ51 and p27−/− were analyzed for enrichment of GO terms using binomial statistics in Gitools. This test measures whether the proportion of genes with a particular GO term differs statistically from random expectations. P-values are shown in a color code scale; red color shows significant P-values after multiple testing correction, indicating enrichment for a particular GO term. Gray means no statistically significant difference.

We also studied the cdk dependence of the p27-mediated transcriptional repression, by expression microarrays using p27CK− MEFs (Besson et al., 2007). Results showed that similar to that observed in p27−/− cells, a significant number of p27-TGs genes was upregulated in p27CK− cells (Figures 5b and c), indicating that a group of genes is repressed by p27 in a cyclin-cdk-dependent manner. Consistent with the idea that cyclin-cdk complex inhibition is needed to repress the expression of this specific subset of p27-TGs, a significant number of these genes were overexpressed in both, p27CK− and p27−/− MEFs (Figure 5d, upper panel). Interestingly, we also observed that a significant number of p27-TGs were downregulated in p27CK− MEFs, indicating that p27 could also repress transcription in a cdk-independent manner (Figure 5b and web Supplementary datasets S4 and S5). The ability of p27CK− to repress transcription is highlighted when expression data from p27CK− versus p27−/− MEFs were compared (Figure 5c and web Supplementary datasets S6 and S7). Although a group of p27-TGs were downregulated in both p27CK− and p27−/− MEFs, this was not statistically significant (Figure 5d, bottom panel).

Altogether these results reveal a transcriptional repressor activity of p27 that is performed either in a cdk-independent or in a cdk-dependent manner depending on the subset of genes regulated.

To analyze the domains of p27 involved in transcriptional regulation, expression microarray analysis on p27Δ51 versus p27WT MEFs was performed. The protein p27Δ51 lacks the 51 N-terminal amino acid, a region that contains the interacting domains of p27 with cyclins and cdks (Kiyokawa et al., 1996). Similarly to p27−/− and p27CK− MEFs, a significant number of p27-TGs were upregulated in these cells (Figure 5e and web Supplementary datasets S8 and S9), as being a significant number of them also overexpressed in p27CK− MEFs (Figure 5f). These data support that inhibition of cdk activity is needed for repression of these genes. However, in contrast to results observed in p27CK− cells no significant repression of p27-TGs was observed in p27Δ51 cells (Figure 5e). These results indicate that p27Δ51 is not as efficient as p27CK− as a repressor, and suggest that a domain in the first 51 aa of p27 is also needed for the cdk-independent gene repression.

We also performed enrichment analysis with targets of p130, E2F4 and members of the Ets family of TFs. Interestingly, the p27-TGs upregulated in p27−/− cells were also targets of the Ets-TFs but not of p130 and E2F4 (Figure 5g lane 8). These results suggest that p27 collaborates with Ets family in the transcriptional repression of this particular set of p27-TGs.

Moreover, the p27-TGs upregulated in p27CK− and p27Δ51 cells are also targets of Ets-TFs but they are additionally enriched among targets of p130 and E2F4 (Figure 5g, lanes 5 and 6). Finally, results also revealed that the p27-TGs repressed in p27CK− MEFs were targets of Ets-TFs (Figure 5g lane 2). Collectively, these data suggest that p27 participates in transcriptional regulation through at least two different complexes one containing Ets-TFs and another one containing p130/E2F4.

To further confirm the role of p27 as a transcriptional co-repressor, we analyzed the effect of re-introduction of p27 in p27−/− MEFs on the expression of two p27-TGs upregulated in these cells. We observed that tranfection of p27 repressed the expression of both genes (Figures 6a and b and Supplementary Figure S7). Similar experiments were carried out in NIH 3T3 cells, in which endogenous p27 was knocked down with a specific shRNA. In these cells both genes were upregulated, but the overexpression of a non-degradable form of p27 clearly blocked the expression of both genes (Figures 6c and d).

Figure 6
Figure 6

p27 represses transcription of p27-TGs. (a) The levels of mRNA for two specific p27-TGs (Heatr1 and Rbl2) were measured by qPCR in quiescent MEFs with p27WT (black bar), p27KO (white bar) and p27KO infected with empty vector (vertical lines bar) or p27WT (gray bar). Data are represented as the mean value±s.d. of three independent experiments. (b) WB of p27 levels in cells used in (a). (c) Expression levels of Heatr1 and Rbl2 were measured by qPCR in quiescent NIH 3T3 transfected with control shRNA (black bar), p27 shRNA (white bar) and NIH 3T3 with p27 shRNA plus CFP (vertical lines bar) and p27 shRNA plus CFP-p27 (gray bar). Data are represented as the mean value±s.d. of three independent experiments. (d) WB of p27 levels in cells used in (c). (e) Quiescent control and p27-knocked down NIH 3T3 cells were transfected with specific reporter constructs. Results show the luciferase activity in p27-knocked down cells (grey bars) relative to the activity in control cells (black bars) for p27-TGs promoters and for the control promoter Noxa. Data are represented as the mean value±s.d. of three independent experiments. (f) p27 levels in cells of experiments in (e) as determined by WB.

To finally corroborate the transcriptional repressor role of p27, we generated different constructs containing a luciferase reporter gene under the control of p27-TG promoters including Aurka, Coq5 and Sfrs8. The promoter of Noxa (a non-p27-TG) was used as a control. Luciferase assays revealed that knockdown of p27 induced a transcriptional activation of the p27-TGs but not that of the control gene (Figures 6e and f).

Overexpression of p27-TGs in tumors correlates with a poor survival

It is known that tumors with reduced p27 levels display a worse outcome (Slingerland and Pagano, 2000). Thus, we can speculate that the higher malignancy of these tumors could be due to increased expression of some of the hereby-identified p27-TGs. To test this possibility, we analyzed the expression status of p27-TGs in a collation of oncogenomic experiments from IntOGen, a publicly available cancer resource that contains information on the pattern of different alterations in diverse types of cancer (Gundem et al., 2010). As shown in Table 1 and web Supplementary analysis S2, a significant number of p27-TGs were overexpressed in different types of human tumors. We next analyzed the relationship between reduced p27 expression with clinical parameters, using a breast cancer tissue microarray containing tumors of different origins and grades. Reduction of p27 levels correlated with an increased grade of the tumors (Figure 7A). Next, we tested the correlation between the levels of Aurka and Fancd2 (two of the most commonly represented p27-TGs among different samples in the IntOGen database) and the expression of p27. We observed that reduced levels of p27 were significantly linked to increased nuclear expression of Fancd2 and Aurka (Figures 7B and C). Of note, normal breast samples included in the array showed clear nuclear presence of p27 (Figure 7B-a) concomitant with almost undetectable Fancd2 and Aurka (Figure 7B-b and 7B-c). A multivariate analysis revealed that low levels of p27 correlate with tumor grade and with increased levels of Aurka and Fancd2 but not with the expression of PCNA, a proliferation marker (Supplementary Table S1). Finally, we searched for possible overlapping between p27-TGs overexpressed in human tumors with patient prognosis in the Oncomine gene expression database (Rhodes et al., 2004). One study of breast cancer (Pawitan et al., 2005) and one study of astrocytoma (Phillips et al., 2006) with very significant association (P-value<10−4) were selected for further Kaplan–Meier analysis. In addition, a large study of lung adenocarcinomas, including samples from four different clinical research centers, was analyzed (Shedden et al., 2008). In all these cases, a significant association between p27-TGs overexpression and poor survival was observed (Figure 7D), suggesting that the functional loss of p27 repression of p27-TGs could be associated with higher metastatic capacity of primary tumors.

Table 1: p27-TGs are over-expressed in many types of cancer
Figure 7
Figure 7

Overexpression of p27-TGs correlates with poor survival in human cancers. (A) Score of p27 staining in correlation with the histopathological grade of a tissue microarray of breast cancer. (B) Representative staining of p27 (a, d, g, j), Fancd2 (b, e, h, k) and Aurka (c, f, i, l). Samples were: normal breast tissue (a, b, c), ductal breast carcinoma Grade II (d, e, f), grade III (g, h, i) and lymph node metastasis (j, k, l). Bar=150 μm. (C) Graphic representation of the correlation between the expression of p27 and that of Aurka and Fancd2 in tissue microarrays. (D) Kaplan–Meier analyses were performed on a number on tumors from breast, astrocytoma and lung adenocarcinoma.


Compelling evidence unveiled a dual role for p27 during tumorigenesis: as a tumor suppressor presumably by virtue of its cdk regulatory function and as an oncogene through cdk-independent functions (Sicinski et al., 2007). However, the specific mechanisms underlying this participation still remain elusive. We report here a new function of p27 as a transcriptional regulator that can have a role during oncogenesis. We observed that p27 associates with promoters of genes involved in cellular functions as processing and splicing of RNA, mitochondrial organization and respiration, translation and cell cycle. The expression of a group of these p27-TGs is regulated by members of the Ets family of TFs, whereas another group of p27-TGs is regulated by p130/E2F4 complexes.

The p130/E2F4 complexes are crucial in the regulation of G1/S transition. They are the major transcriptional repressors of genes necessary for DNA replication during G0/G1 (Macaluso et al., 2006). At late G1 cyclin D-Cdk4/6 and subsequently cyclin E-Cdk2, phosphorylate p130 disrupting these complexes and allowing transcriptional activators, E2F1, to induce the expression of these genes (Malumbres and Barbacid, 2005). We investigated the functional relationship between p27 and p130/E2F4 complexes, and we have shown that p27 associates with most of the proteins of these complexes and that they co-localize on p27-TG promoters in quiescent cells. The observation that p27 directly interacts with p130 and E2F4 through its carboxyl-half corroborates that p27 forms part of these repressor complexes. It is known that p130 is essential to transport E2F4 to these promoters (Rayman et al., 2002). Our results indicate that p130 is necessary also for the recruitment of p27 on the promoters and that this is a cyclin-cdk-independent process. Interestingly, we also observed that p27 is critical for the subsequent assembly of HDAC1 and mSIN3A in these complexes. Thus, a model appears in which p130 drives p27 and E2F4 to the promoters and there, p27 is responsible for the recruitment of the other co-repressors (Figure 8).

Figure 8
Figure 8

Model illustrating the participation of p27 on the organization of p130/E2F4 repressor complexes. p130 first drives E2F4 to the promoters (1), then p27 is subsequently loaded by directly interacting by its carboxyl-domain with both p130 and E2F4 (2), finally, p27 recruits the co-repressors HDAC1 and mSIN3A on these promoters (3).

Our results also revealed that p27 behaves as a transcriptional repressor. This was demonstrated by expression microarray analysis performed on p27−/− MEFs that allowed us the identification of p27-TGs that were upregulated in these cells. This upregulated expression could be repressed by the re-introduction of p27 in these knockout MEFs but also in NIH 3T3 cells knocked down for p27. The transcriptional repressor role of p27 was also supported by assays carried out on cells containing a luciferase reporter gene under the control of p27-TG promoters. Finally, expression microarray analysis performed on p27CK− MEFs revealed that p27CK− is a good transcriptional repressor and indicated that p27 mediates the transcriptional repression in a cdk-independent manner.

Interestingly, as shown in Figure 5e lane 2, the p27-TGs repressed in p27CK− MEFs were only those regulated by Ets-TFs. This is concordance with data shown in Figure 5e lane 8, indicating that the p27-TGs upregulated in p27−/− MEFs are also those regulated by Ets-TFs. Collectively, these data indicate that p27 is clearly a transcriptional repressor of genes under the regulation of Ets-TFs.

In contrast to what observed in p27−/− MEFs, a significant number of p27-TGs repressed by p130/E2F4 complexes are upregulated in p27CK− MEFs (Figure 5e lane 6). These data indicate that the presence of p27 is needed for the transcriptional activation of these genes. Interestingly, the upregulation of these genes did not occur in p27WT MEFs, indicating that for the transcriptional activation of the p130/E2F4 regulated genes the presence of p27 on the promoters, but also of active cyclin-cdk complexes, are concomitantly needed. All these data lead us to postulate a model in which in quiescent cells p27 participates in the organization of the p130/E2F4 complexes to repress the genes needed for DNA replication. At mid-late G1 when the expression of these genes is needed, the p27 associated with p130/E2F4 on the promoters would recruit cyclin-cdk complexes by its N-terminal domain. This model is compatible with our data showing that p27 directly binds to p130 and E2F4 through its carboxyl-half; thus, under these conditions, the NH2-half of p27 is ‘free’ to interact when necessary with cyclin and cdk molecules. The model also postulates that these cyclin-cdk complexes bound to p27 on the promoters would be subsequently activated and then they could phosphorylate p130 and thus disrupting the repressor complexes. So, our model postulates that the binding of p27 to promoters, in addition to participate in the transcriptional repression, could help to recruit cyclin-cdk complexes needed for p130 phosphorylation. Work trying to validate this model is currently performed in our laboratory.

A corollary of these data is the existence of overlapping functions for p130 and p27. Indeed, the inactivation of p107 and p27Δ51 in vivo (Yeh et al., 2007) is highly reminiscent of that of p130 and p107 (Cobrinik et al., 1996). However, in vivo unique functions for p27 and p130 also exist (Soeiro et al., 2006). Whether these unique functions can be related to cdk-independent p27 transcriptional repression remains unclear. Future work will be delineated to clarify these possibilities.

The observation that in p27−/− cells a significant number of p27-TGs are upregulated suggested that tumors with low levels of p27 could also upregulate a number of these genes. In fact, we observed that p27-TGs are overexpressed in a broad spectrum of cancers. The high correlation between the p27-TGs overexpressed in a several sets of breast tumors and those overexpressed in p27−/− MEFs, also supports the idea that the decrease of p27 in tumors can lead to the increased expression of specific p27-TGs. For instance, two p27-TGs Aurka, encoding the protein kinase Aurora A, and Kif11, encoding a kinesin-related motor protein, are overexpressed in tumors and are considered as therapeutic targets for cancer, and a number of inhibitors are in clinical trials (Carter et al., 2006; Saijo et al., 2006; Malumbres and Barbacid, 2007; Huszar et al., 2009; Lapenna and Giordano, 2009). The finding that both proteins are overexpressed in p27−/− cells supports a link between a decrease in p27, overexpression of these proteins and cancer. This is also supported by our observation of a clear correlation between p27 decrease and the increased expression of Aurka and Fancd2 proteins in breast cancer. Of special relevance are results showing that overexpression of p27-TGs is associated with poor survival in a number of tumors. Overall, these data supports the link among p27-deficiency with overexpression of p27-TGs and poor survival in cancer.

In light of the new data presented here, the role of nuclear p27 as a tumor suppressor should be re-evaluated as it may also be linked to its new role as a transcriptional repressor through mechanisms that are cdk-independent. An additional role of p27 in the organization of the p130/E2F4 repressor complexes and in the activation of G1/S genes has also been taken under consideration.

Materials and methods

Cell culture and transfection

NIH 3T3 cells were cultured in Dulbecco's modified Eagle Medium supplemented with 10% donor bovine serum. p27WT, p27CK−, p27Δ51, p27−/− and p130−/− MEFs were cultured in Dulbecco's modified Eagle Medium supplemented with 10% fetal bovine serum. All cultures were maintained at 37 °C and 5% CO2. Plasmids and shRNAs were transfected in NIH 3T3 cells using lipofectamine 2000 (Invitrogen, Karlsruhe, Germany) following manufacturer's instructions.


Polyclonal antibodies against p27 (C-19), p130 (C-20 and KAB40), E2F4 (C-20), ETS1 (C-20), mSIN3A (K-20), HDAC1 (H-51), HDAC4 (H-92), HDAC5 (H-74), Heatr1 (sc-134699), cdk4 (C-20), cyclin D1 (DCS-6) or actin (C-2) were purchased from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Monoclonal p27Kip1 and p130 antibodies were obtained from Transduction labs, BD Biosciences (Franklin Lakes, NJ, USA); monoclonal E2F4 (4E2F04) and polyclonal p27 (ab7961) were purchased from Abcam (Cambridge, UK); and anti-Rabbit IgG whole molecule (R5506) was from Sigma-Aldrich (Madrid, Spain).

Cell synchronization

NIH 3T3 cells were maintained in serum-free medium for 48 h, whereas MEFs were maintained for 72 h. Cells were then activated by serum addition. At different time points after serum re-stimulation, samples were taken and used for western blot and immunocytochemistry experiments.


Cells were grown onto glass coverslips, fixed with 4% paraformaldehyde, then permeabilized and blocked with 0.1%. Triton X-100 and 1% bovine serum albumin in phosphate-buffered saline (PBS) solution. After three washes with PBS, cells were incubated with primary antibody in blocking buffer (1% bovine serum albumin in PBS solution) for 1 h at 37 °C and then with secondary antibodies labeled with Alexa fluor 488 (Invitrogen) (dilution 1:500). After a 10 min washing, incubation with 46-diamidino-2-phenyl indole (dilution 1:10.000) was made. Stained coverslips were mounted using Mowiol (Calbiochem, Merck Chemicals Ltd., Nothingham, UK) and visualized using confocal microscope (TCS SL; Leica microsystems, Wetzlar, Germany).


Serum starved NIH 3T3 or MEFs were scraped and washed twice with PBS. Pellets were lysed in 1 ml of IP buffer (PBS containing 0.5% Triton X-100, 1 mM EDTA, 100 μM sodium orthovanadate, 0.25 mM PMSF, complete protease inhibitor mixture by Roche Applied Science (Penzberg, Germany), and 1/25 volume of DNAse I (Sigma). After centrifugation, samples were sonicated, and the protein was subsequently quantified using Lowry method (Lowry et al., 1951). The supernatants (1 mg protein) were incubated for 1 h at 4 °C with 7 μg of anti-p27 antibody (C-19) crosslinked to protein A-Dynabeads following manufacturer's instructions. The immunocomplexes were extensively washed with IP buffer and immunoprecipitates were subsequently eluted with 0.1 M citrate, pH 2.5, and boiled at 100 °C in Laemmli buffer for western blot analysis. As a control, lysates were incubated with irrelevant crosslinked rabbit IgG.

Affinity chromatography

Two affinity chromatography columns were generated with the p27 fragments p27-NT (aa 1-110) and p27-CT (aa 110–198) that were linked to sepharose 4B beads (Sigma-Aldrich), as previously described (Vera et al., 2007). Columns (1 ml) were loaded with 50 μg of purified recombinant E2F4 or p130 fragments (p130NT, aa 1-417 and p130CT, 967-1082). After extensive washing the bound proteins were eluted with 300 mM of NaCl and eluates analyzed by western blot.

Chromatin immunoprecipitation

ChIP assay was performed as previously described (Aguilera et al., 2004). Briefly, chromatin from cross-linked cells was sonicated, incubated overnight with rabbit anti-p27, p130, E2F4, mSIN3A, HDAC1, 4, 5 and anti-IgG antibodies in RIPA buffer, and precipitated with protein G/A-Sepharose. Cross-linkage of the co-precipitated DNA-protein complexes was reversed, and DNA was used as a template for qPCR.


Agilent G5590A mouse promoter microarray was used to analyze p27-target genes in quiescent NIH 3T3 cells. After scanning, raw data was extracted using Feature Extraction (Agilent Technologies, Basel, Switzerland). The data analysis was performed using LIMMA package from R of bioconductor, while the intrachip normalization was obtained with LOESS method. Only probes with a P-value <0.02 in both experiments were considered as bound.

ChIP validation

ChIP samples (2 μl) were used for the real time qPCR reaction using Brilliant SybrGreen master mix from Agilent Technologies. The primers used in the experiments are listed in the Supplementary Information (experimental procedures).

Expression microarrays

Cells were collected by trypsinization and then washed with PBS. Total RNA was extracted using the RNeasy Kit (Qiagen Iberia, Madrid, Spain). RNAs from quiescent p27WT, p27CK−, p27Δ51 and p27−/− MEFs cells were analyzed using a Bioanalyzer (Agilent). Only samples with RIN number greater than nine and a ratio A260/280 more than two were further used in microarray analysis. Retrotranscription was made followed by labeling with biotin. Fragmented samples were then hybridized with Affymetrix 430 2.0 and 1.0 ST murine arrays, and analyzed with dChip Affymetrix software and tools. The normalization of the arrays was performed using the robust multi-array average (RMA) method as implemented in the Affymetrix package of R bioconductor. Quality control measurements were obtained with ArrayQualityMetrics, while the statistical analysis of significant hits with Limma (Smyth, 2004).

shRNA experiments

NIH 3T3 cells were transfected with MISSION shRNA control vector and a specific p27 shRNA with the following sequence:


Both were purchased from Sigma-Aldrich (Madrid, Spain). After 24 h of transfection, serum-free medium and puromycin were added to the cells during additional 24 h, until collection of the samples. Total RNA was extracted using the RNeasy Kit (Qiagen). RNA (1 μg) was reverse transcribed using High Capacity cDNA Archive Kit from Applied Biosystems (Life Technologies, Madrid, Spain) following the manufacturer's protocol. Then, 2 μl of cDNA were used for each real time PCR using Brilliant SybrGreen qPCR master mix from Stratagene. All the primers used are listed in the Supplementary Information (experimental procedures).

Luciferase assay

Luciferase vectors were obtained by cloning specific regions from Aurka, Coq5 and Sfrs8 promoter sequences into a pGL2 basic vector. Primers for the selected genes were designed adding XhoI and SacI target sequences at 5′ and 3′, respectively. The primers used for this amplification were:







Amplification of promoter sequences was made by qPCR using genomic DNA and cloning the PCR products into pGEMt vectors (Promega, Madison, WI, USA). After transformation into JMJ109 bacteria and double digestion with the selected restriction enzymes, the promoter fragments were finally inserted into the pGL2B vector. NIH 3T3 cells were co-transfected with CMV-bGal vector and a pGL2b vector, empty or containing part of the promoters of Aurka, Coq5 and Sfrs8 representing p27 targets and Noxa as a control promoter. Luciferase assays (Luciferase Assay System; Promega) were performed at 48 h after transfection, as previously described (Aguilera et al., 2004).

Functional enrichment analysis

Functional annotation of genes based on Gene Ontology (GO) (Consortium, 2006) were extracted from Ensembl v.47. (Flicek et al., 2008). Enrichment of the genes from different gene ontology categories was done using GiTools (Perez-Llamas and Lopez-Bigas, 2011). The probability of the overlap between two gene sets was assessed comparing the observed number of shared genes with the expected number estimated using the binomial distribution using the following formula,

n=number of genes in the category in question (for example, with a particular gene ontology term).

x=total number of genes in the category in question targeted by p27 or with mis-regulated expression in p27−/− (observed).

p=frequency of p27 target genes or with mis-regulated expression in p27−/− (success rate).

The resulting P-value is corrected for multiple testing using Benjamini–Hochberg procedure (Benjamini and Hochberg, 1995). Results are displayed in color-coded matrices in which P-value is represented by a color-coded scale. Colors towards red show significant P-values (corrected P-value <0.05), indicating strong deviation from random expectations. Grey indicates P-value is not significant after multiple testing corrections.

Promoter analysis

TF-binding sites in promoter sequences (1 kb upstream of the transcription start site) were predicted with MatScan software (Blanco et al., 2006), using position weight matrices from TRANSFAC database (Matys et al., 2003). To test whether there was a significant deviation from random expectation for distribution of TF-binding sites, we compared the observed number of motifs in p27 target promoters with the expected according to binomial Poisson distribution.

IntOGen analysis

To study the expression status of p27-TGs in cancer samples, we used a collation of oncogenomic experiments from IntOGen (Gundem et al., 2010). We tested whether p27-TGs were enriched by genes mis-regulated in those experiments using binomial test, as described above.

Cancer survival analysis

Overlapping between p27-TGs and genes overexpressed in human tumors with poor prognosis was done using the Oncomine gene expression database (Rhodes et al., 2004). Studies of breast cancer, astrocytoma and lung adenocarcinoma with very significant association (P-value<10−4) were selected for further Kaplan–Meier analysis. Genes with significant overexpression in the more malignant samples were selected to group the samples using hierarchical clustering analysis. In all studies, patient samples were divided in two groups, and each group was analyzed in Kaplan–Meier curves in order to assess their clinical behavior.

Tissue microarrays

Commercially available tissue microarrays (CC08-21, Cybrdi Inc., Rockville, MD, USA) containing normal breast tissue and samples from 96 individual patients of breast ductal carcinoma of grade I, II, III and lymph node metastasis was de-waxed and treated by microwave boiling in citrate buffer, blocked by incubation in 10% non-immune horse serum and incubated with the primary antibodies overnight at 4 °C. Antibodies used were a mAb against p27 (Clon 57; # 610242 BD Biosciences) diluted 1/200, rabbit polyclonal Ab against FancD2 (Abcam ab2187) diluted 1/500 and mAb against Aurka (Clon 35C1 Abcam ab13824) diluted 1/500. After exhaustive washing in PBST, sections were incubated with appropriate biotin-coupled secondary antibodies (all 1/1000 in PBST) followed by avidin-peroxidase (ABC elite kit Vector, Vector Laboratories, Burlingame, CA, USA). Positive staining was determined using diaminobenzidine as a substrate (DAB kit Vector, Vector laboratories) following manufacturer's recommendations. Sections were then counterstained with hematoxylin and mounted. Statistical analyses were carried out with the SSPS program, version 11. 5. (SSPS, Chicago, IL, USA). Frequencies were compared by the χ2-contingency test.


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We thank Dr Anxo Vidal for p27Δ51- MEF cells; Dr Antonio Giordano for p130 pGEX plasmids; Dr Xavier Mayol for GST-E2F4 vector; and Dr Alan Cassady for the pGL2b plasmid. This work was supported by the Ministerio de Ciencia y Tecnología of Spain (grants SAF2006-05212 and SAF2009-07769 to OB and SAF2009-06954 to NL-B; the Fondo de Investigación Sanitaria (grant PI070778 to LE), the Instituto de Salud Carlos III (RETICS RD06/0020/0010 to OB, RD06/0020/0029 to JP and RD06/0020/0098 to A. Bigas), the Comunidad Autonoma de Madrid (Oncocycle Program grant S2006/BIO-0232 to JP) and the Generalitat de Catalunya (grant SGR 09-1382 to OB). GG is supported by a fellowship from AGAUR of the Catalonian Government. AB is supported by grants from the Association pour la recherché sur le Cancer, Ligue Nationale Contre le Cancer and Institue National du Cancer.

Author information


  1. Department of Cell Biology, Immunology and Neurosciences, University of Barcelona, IDIBAPS, Barcelona, Spain

    • R Pippa
    • , A Dominguez
    • , S Orlando
    • , E Gallastegui
    • , M J Pujol
    •  & O Bachs
  2. Institut Municipal d’Investigacions Mèdiques-Hospital del Mar, Barcelona, Spain

    • L Espinosa
    •  & A Bigas
  3. Department of Experimental and Health Science, Research Unit on Biomedical Informatics, Universitat Pompeu Fabra, Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain

    • G Gundem
    •  & N López-Bigas
  4. Molecular Oncology Unit, Division of Biomedicine, CIEMAT, Madrid, Spain

    • R García-Escudero
    • , C Saiz
    •  & J M Paramio
  5. INSERM–UMR1037, Cancer Research Center of Toulouse, Toulouse, France

    • A Besson


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Correspondence to O Bachs.

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