p53 is the most frequently mutated tumor suppressor gene in human neoplasia and encodes a transcriptional coactivator. Identification of p53 target genes is therefore key to understanding the role of p53 in tumorigenesis. To identify novel p53 target genes, we first used a comparative genomics approach to identify p53 binding sequences conserved in the human and mouse genome. We hypothesized that potential p53 binding sequences that are conserved are more likely to be functional. Using stringent filtering procedures, 32 genes were newly identified as putative p53 targets, and their responsiveness to p53 in human cancer cells was confirmed by reverse transcription-PCR and real-time PCR. Among them, we focused on the vitamin D receptor (VDR) gene because vitamin D3 has recently been used for chemoprevention of human tumors. VDR is induced by p53 as well as several other p53 family members, and analysis of chromatin immunoprecipitation showed that p53 protein binds to conserved intronic sequences of the VDR gene in vivo. Introduction of VDR into cells resulted in induction of several genes known to be p53 targets and suppression of colorectal cancer cell growth. In addition, p53 induced VDR target genes in a vitamin D3-dependent manner. Our in silico approach is a powerful method for identification of functional p53 binding sites and p53 target genes that are conserved among humans and other organisms and for further understanding the function of p53 in tumorigenesis. (Cancer Res 2006; 66(9): 4574-83)

The transcriptional coactivator p53 binds to DNA in a sequence-specific manner and induces transcription of a variety of genes involved in cell cycle regulation, apoptosis, inhibition of angiogenesis, and DNA repair (1, 2). Notably, the gene encoding p53 is the most frequently mutated tumor suppressor gene in neoplasms. Consequently, identification of the transcriptional targets of p53 is a potential key to understanding functions of p53 and its signaling pathways in tumorigenesis, and to exploiting their potential use as molecular targets for cancer chemotherapeutic drugs.

Several approaches have been used to successfully identify genes induced by p53 including differential display, representational difference analysis, cDNA microarrays, and serial analysis of gene expression (36). However, identification of p53-inducible targets by gene expression profiling is highly dependent on the expression level of the target gene, potentially overlooking genes of which the expression level is relatively low in the tissue analyzed. Alternatively, p53 target genes should be identifiable using an in silico analysis of p53 response elements (p53RE) as probes (7). However, a complete data set of functional p53REs in the human genome is not yet available. Comparison of orthologous genomic sequences has become a powerful tool for identifying functional elements within the genome (8, 9). Using a computational approach, coding regions, regulatory elements, and noncoding RNA conserved in different vertebrates have been identified (10). We hypothesized that both known and novel functional p53REs important for p53 function are likely to exhibit greater sequence conservation than nonfunctional sequences (11). A comparative genomic analysis of putative p53 binding sequences may thus be a way to identify the downstream mediators of p53 function.

Epidemiologic studies indicate that vitamin D3 and its most active analogue, 1,25-dihydroxyvitamin D3 [1,25(OH)2D3], have antitumor activity (12, 13). In vitro, vitamin D3 induces cell cycle arrest, differentiation, and apoptosis of cancer cells (1417). Clinical trials are under way to assess the activity of various vitamin D analogues against tumors. Vitamin D3 exerts its activity through binding to the vitamin D receptor (VDR). VDR is down-regulated during colorectal tumorigenesis, and absence or low levels of VDR expression correlate with poor prognosis (18, 19). However, the regulatory mechanism of VDR expression is not fully understood.

The aim here was to identify and compare p53 target genes in the human and mouse genomes using in silico genome scanning for sequence conservation of potential p53 binding sites. Our results indicate that this in silico approach is a powerful method for identification of p53 target genes conserved among humans and other organisms, and help determine new functions of p53 in tumorigenesis. Among the genes identified as a putative target of p53, we examined the induction of VDR by p53 family members. We also examined the role of VDR in the regulation of p53 target genes.

Construction of p53RE database and comparative analysis of p53 target genes. p53REs typically consist of two copies of a 10-bp motif (RRRCWWGYYY) separated by 0 to 12 bp. We first extracted all putative p53 binding sites in the entire human and mouse genomes. The sequence data were downloaded from the National Center for Biotechnology Information (NCBI) Human Assembly 33 (April 10, 2003) and the MGSC Mouse Assembly 3 (February 2003) and then input to the p53RE prediction system. We set the parameter conditions to include the following restrictions: (i) fewer than four mismatches in the 20-nucleotide consensus binding sequence, and (ii) the spacer between the 10-bp motifs has fewer than 12 bp. The output data, which consisted of p53 binding site IDs, chromosomal positions, nucleotide sequences, the number of mismatches, spacer length, and the 200-bp sequences surrounding the binding sites, were stored in the p53RE database.

We next added the gene annotation information into each of the binding site entries in the p53RE database. The public database RefFlat provided by the University of California Santa Cruz was used to determine the distance between the p53 binding sequences and their closest genes. This data set contained information from 15,824 human genes and 13,406 mouse genes; the data for each gene consisted of the chromosome number and the positions of the transcription start site, the first exon start position and the first intron start position. We calculated the distance between each p53RE and the corresponding transcription start site of the closest gene and retrieved only the p53 binding sites located within 10 kb of the transcription start site.

Cell lines, cell culture, and recombinant adenovirus. The human cancer cell lines used in this study were purchased from the American Type Culture Collection (Manassas, VA) or the Japanese Collection of Research Bioresources (Tokyo, Japan). All cell lines were cultured under conditions recommended by their individual depositors. The status of the endogenous p53 expressed in these lines was wild-type for RKO and HCT116, mutant for DLD-1, SW480, and MKN74, and p53-null for Saos-2 and H1299. The generation and purification of replication-deficient recombinant adenoviruses harboring p53, p73α, p73β, p63γ, and the bacterial LacZ gene (Ad-p53, Ad-p73α, Ad-p73β, Ad-p63, and Ad-LacZ, respectively) were previously described (20). To examine VDR expression induced by endogenous p53, cancer cells were treated with 0.2 to 0.5 μg/mL of Adriamycin for 12 to 24 hours and harvested.

Knockdown of VDR by short hairpin RNA. Two short hairpin RNA (shRNA) sequences (sh-VDR20 and sh-VDR32) were designed using siPRECISE software (B-bridge, Inc., Sunnyvale, CA). Oligonucleotides were annealed and ligated into pFIV-H1-Puro vector (SBI, Mountain View, CA). shRNA sequences for VDR are shown in Supplementary Table S1. HCT116 cells were transfected with 2 μg of sh-VDR20, sh-VDR32, or control pFIV-H1-Puro vector for 4 hours using Lipofectamine 2000 (Invitrogen Inc., Grand Island, NY) in 2 mL of Opti-MEM medium (Invitrogen). The culture medium was replaced with McCoy's medium containing 1 μg/mL puromycin and harvested after 48 hours.

Chromatin immunoprecipitation. Chromatin immunoprecipitation (ChIP) assays were carried out as previously described using a ChIP assay kit (Upstate Biotechnologies, Lake Placid, NY; ref. 21). Immunoprecipitation was carried out using mouse antihuman p53 monoclonal antibody (mAb; DO-1, Santa Cruz Biotechnology, Santa Cruz, CA). The primers used were ChIP-F and ChIP-R; their sequences are shown in Supplementary Table S1. The amplified products were subjected to agarose gel electrophoresis.

Luciferase assay. To construct luciferase reporter plasmids, oligonucleotide fragments corresponding to VDR-RE (wt) and VDR-RE (mut; Supplementary Table S1) were synthesized and inserted upstream of a basal SV40 promoter in the pGL3-promoter vector (Promega, Madison, WI); the resulting constructs were designated pGL3-VDR-RE (wt) and pGL3-VDR-RE (mut), respectively. H1299 cells at 50% confluence were transfected with a reporter and an effector plasmid (total, 100 ng DNA) using Lipofectin (Life Technologies, Inc., Gaithersburg, MD). After 48 hours, the cells were harvested for measurement of luciferase activity using a Luciferase Assay System (Promega). Cell extract was incubated with luciferin and light emission was measured using a Berthold Luminometer (Berthold Lumat LB9507, Belthold, Bad Wildbad, Germany).

Reverse-transcription PCR. Semiquantitative reverse transcription-PCR (RT-PCR) was carried out as previously described (6). Briefly, total RNA was extracted using TRIzol (Invitrogen); after which, a 5-μg sample was reverse transcribed using SuperscriptIII (Invitrogen). The primer sequences used are shown in Supplementary Table S1. The integrity of the cDNA was confirmed by amplifying glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as previously described (21). Samples of amplified product were then subjected to 2.5% Nusieve gel electrophoresis and stained with ethidium bromide.

Real-time PCR was carried out using a CYBR Green PCR or TaqMan PCR Master Mix (Applied Biosystems, Foster City, CA) on an ABI Prism 7000. Accumulation of PCR product was measured in real time as an increase in fluorescent signals and analyzed using ABI Prism 7000 SDS Software (Applied Biosystems). Standard curves relating initial template copy number to fluorescence and amplification cycle were generated using the amplified PCR product as a template, and were then used to calculate the mRNA copy number in each sample. The ratios of the intensities of the target genes to GAPDH signals were considered to be a relative measure of the target genes mRNA level in each specimen. The information for TaqMan primers/probe sets is available in Supplementary Materials and Methods.

Northern blot analysis. Ten micrograms of total RNA were separated by electrophoresis on a 1% agarose gel containing 2.2 mol/L formaldehyde. The integrity and equal loading of the RNA in each lane were confirmed by ethidium bromide staining. The RNA was then transferred onto a nitrocellulose transfer membrane (Protran, Schleicher and Schuell, Inc., Keene, NH) by capillary blotting in 20× SSC; after which, hybridization was done using radiolabeled probes in 50% formamide, 5× Denhardt solution, 3× SSC, 0.1% SDS, and 100 μg/mL salmon sperm DNA overnight at 42°C. After hybridization, the membranes were washed first in 1× SSC/0.1% SDS at room temperature and then in 0.25× SSC/0.1% SDS at 60°C. The intensities of hybridization bands were quantitated using a BAS2000 Bioimage Analyzer (Fuji, Tokyo, Japan).

Western blot analysis. Twenty micrograms of cell lysate were subjected to electrophoresis in a 10% SDS-PAGE; after which, the proteins were transferred to Immobilon-P membranes (Millipore, Bedford, MA). The membranes were then blocked with 5% nonfat milk and 0.1% Tween 20 in TBS and probed with anti-VDR (Lab Vision, Fremont, CA) and antiactin mouse mAbs (Chemicon, Temecula, CA); after which, the hybridization was visualized using enhanced chemiluminescence (Amersham, Piscataway, NJ).

Immunofluorescent staining. Cells grown on coverslips were infected with Ad-lacZ, Ad-p53, Ad-p63, or Ad-p73. After 48 hours, the cells were fixed with 4% paraformaldehyde and then incubated for 16 hours at 4°C with anti-VDR rat mAb (Lab Vision). FITC-conjugated goat anti-rat antibody (Molecular Probes, Eugene, OR) was used as the secondary antibody. Finally, the nucleus was stained with 4′,6-diamidino-2-phenylindole (DAPI; Vector Laboratories, Inc., Burlingame, CA) and the cells were examined under a fluorescence microscope (Olympus, Tokyo, Japan).

Geneticin-resistant colony formation assay. Cells were plated in 60-mm culture dishes to a density of 1 × 105 per plate and incubated for 24 hours; after which, they were transfected with pCMV-VDR or empty pCMV vector (5 μg each) using Lipofectamine Plus reagent (Invitrogen). Following transfection, cells were selected for 14 days in medium containing 0.6 mg/mL G418 and stained with Giemsa. The colonies were then counted in triplicate cultures using NIH Image software.

Pathway analysis. p53 and VDR target genes were analyzed using Ingenuity Pathway Analysis software (Ingenuity, Mountain View, CA). To infer coassociation of common p53 and VDR target genes, this method uses the gene identities in conjunction with controlled, vocabulary data mining of literature associations, protein-protein interaction databases, and a metabolism pathway database. We then combined the two pathways manually by connecting the genes up-regulated by both p53 and VDR.

In silico identification of p53 target genes. To identify novel p53 target genes within the human genome, we used a computational approach focusing on p53 binding sites (Fig. 1). The consensus p53 binding sequence consists of two copies of a 10-bp motif (RRRCWWGYYY) separated by 0 to 12 bases. Because several of the nucleotides comprising the motif are ambiguous (R, adenine or guanine; W, adenine or thymine; Y, cytosine or thymine), this sequence has up to 28 × 28 (= 65,536) possible patterns, making generation of comparison patterns a heavy task that requires considerable computer resources and takes much time to complete the general pattern matching. We therefore focused on developing a new algorithm to effectively deal with the highly degenerate consensus p53 binding sequence and the variable spacer length. Instead of performing a genome-wide pattern matching with all possible p53 patterns [patterns = 28 × 28 × 13 (spacer) = 851,968], we broke down this consensus sequence into three units, two 10-bp motifs, and a spacer, making it possible for us to design a strategy to pick up all possible 10-bp motifs and then to search for integrated p53 binding sites with a specific spacer length. We first extracted the entire set of putative p53 binding sequences in the genome. The total numbers of candidate sequences for putative p53 binding sites in the human and mouse genomes are summarized in Supplementary Tables S2 and S3. If candidate p53REs are defined as sequences that have four or less mismatches to the consensus p53 binding sequence along with a 0- to 12-bp spacer, there would be 4,834,075 putative p53REs in the human genome, and a putative p53RE would be present every 620 bp, on average. From these, we selected candidate p53REs located within 10 kb of the transcription start site of a gene; 87,659 putative p53REs were estimated to be present in or around the known genes in the human genome. This suggests that the vast majority of the p53 binding sequences, defined only by sequence and proximity to genes, may not be biologically functional.

Figure 1.

Strategy for identifying putative p53 binding sequences conserved between human and mouse using an in silico approach. The algorithm presented here was implemented in a computer program written in the C programming language.

Figure 1.

Strategy for identifying putative p53 binding sequences conserved between human and mouse using an in silico approach. The algorithm presented here was implemented in a computer program written in the C programming language.

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To further refine the set of potentially functional p53REs, we used a comparative sequence analysis of the human and mouse genome, as the p53REs of several known p53 target genes are conserved in multiple species, including human, mouse, and rat (11), which was confirmed by our computational analysis (Supplementary Fig. S1; Supplementary Table S4). We systematically selected p53REs conserved in orthologous genes between human and mouse and eliminated repetitive elements. To search for p53 binding sites that are conserved in orthologous genes between human and mouse, we developed a simple algorithm composed of several steps. As a first step, 7,444 genes homologous between human and mouse were obtained from the NCBI database. By simple pattern matching, we compared the pair of p53 binding sites located within each pair of orthologous genes. We then extracted 7,530 pairs of putative p53 binding sites with sequence similarity (≥70% identity) between the orthologous genes. As a second step, we eliminated the p53 binding sites that were part of repetitive elements. The data on the 200-bp sequence around the p53 binding sites in the p53RE database were scanned using RepeatMasker Open 3.0,6

and any conserved segment that contained known human repeat motifs within the p53REs was excluded from further analysis.

Using this approach, we narrowed the number of candidates for novel p53 target genes to those having conserved p53 binding sites near their transcription start sites (Fig. 1; Supplementary Table S5).7

Figure 2 shows six representative p53 binding sequences that were predicted in this study and that are also conserved across multiple mammalian species.

Figure 2.

Representative p53 binding sites identified in this study and conserved across multiple species. The consensus p53 binding sequences are indicated by uppercase letters: R, purines; Y, pyrimidines; W, A or T. Asterisks, sequences conserved across multiple species. Numbers, nucleotide position relative to the transcription start site. Numbers of mismatched nucleotides in the consensus sequence (p53), those conserved between human and mouse sequences (human-mouse), and those conserved across multiple species (human-other species) are shown below the column.

Figure 2.

Representative p53 binding sites identified in this study and conserved across multiple species. The consensus p53 binding sequences are indicated by uppercase letters: R, purines; Y, pyrimidines; W, A or T. Asterisks, sequences conserved across multiple species. Numbers, nucleotide position relative to the transcription start site. Numbers of mismatched nucleotides in the consensus sequence (p53), those conserved between human and mouse sequences (human-mouse), and those conserved across multiple species (human-other species) are shown below the column.

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Validation of p53 target genes. To assess the validity of the p53 target genes predicted by the in silico analysis described above, their responsiveness to p53 was examined using semiquantitative RT-PCR and real-time PCR (Supplementary Fig. S2; Table 1). In 17 genes, the p53 binding sites contained two mismatches in the consensus p53 binding sequences and absence of a spacer whereas 20 genes contained two mismatches and a 1-bp spacer. In 64 genes, the p53 binding sites contained three mismatches and a 0-bp spacer. When Saos-2 human osteogenic sarcoma cells, which do not express endogenous p53 (22), and DLD-1 colorectal cancer cells, which express a mutant form of p53 (23), were infected with Ad-p53, Ad-p63, Ad-p73α, Ad-p73β, or Ad-LacZ, subsequent semiquantitative RT-PCR showed that, of 101 genes analyzed, 32 were up-regulated and 2 were down-regulated by introduction of p53, p63, or p73 (Supplementary Table S6). Sixteen genes were not expressed at all in Saos-2 or DLD-1 cells and the expression of 51 was not significantly affected. The p53 target genes with p53REs containing two mismatches and no spacer tended to show p53 responsiveness more frequently than those with p53REs containing three mismatches and no spacer or two mismatches and a 1-bp spacer (58.8% versus 28.6%, P < 0.05).

Table 1.

Summary of p53 and p53 family target genes identified by in silico analysis

Gene nameFold induction
p53p63p73αp73β
GAS6 425.0 561.1 112.3 61.6 
GEM 8.1 25.2 69.3 9.1 
VDR 12.1 17.5 10.3 20.2 
EFNB1 9.1 3.1 5.6 5.8 
SYT138.9 3.3 0.8 0.6 
LU 5.3 3.1 31.4 14.6 
HAS3 5.3 32.5 6.3 21.7 
JAG2 7.3 6.7 1.0 5.4 
IRX5 3.9 17.0 5.9 4.5 
LOXL4 2.5 17.0 11.0 15.0 
DSIPI4.7 14.8 23.9 8.9 
CSDA 3.3 12.3 2.0 8.6 
RABL5 3.1 10.8 3.7 3.7 
MDM2 2.6 5.4 1.3 3.8 
BDNF2.3 4.7 4.4 7.1 
TCF12 2.2 3.4 1.8 2.1 
ACVR2 2.2 2.2 0.7 1.0 
AK1 6.4 4.4 2.2 1.7 
KCNB1 3.2 1.9 2.3 0.7 
MITF 3.2 1.3 1.9 0.5 
KIAA1536 3.8 0.1 0.1 2.4 
EDG4 1.7 128.0 6.9 5.6 
LMO4 1.2 10.2 1.2 1.8 
PC4 0.8 8.7 1.6 5.7 
JPH2 0.6 8.1 5.2 1.4 
HUS1 0.9 7.2 2.6 4.1 
NFE2L10.6 5.0 2.9 0.5 
CLK3 1.9 4.5 0.9 3.2 
KCNJ11 1.2 4.3 4.2 0.7 
JMJ0.6 3.3 2.5 1.6 
ADAMTS4 1.4 3.0 5.5 1.3 
IL15RA1.0 1.2 2.8 5.9 
BMP4 0.2 0.0 0.0 0.2 
SHOX2 0.1 0.0 0.0 0.1 
     
Control
 
    
p21 28.8 36.7 6.8 4.6 
GADD45A 42.8 98.2 16.8 46.5 
Gene nameFold induction
p53p63p73αp73β
GAS6 425.0 561.1 112.3 61.6 
GEM 8.1 25.2 69.3 9.1 
VDR 12.1 17.5 10.3 20.2 
EFNB1 9.1 3.1 5.6 5.8 
SYT138.9 3.3 0.8 0.6 
LU 5.3 3.1 31.4 14.6 
HAS3 5.3 32.5 6.3 21.7 
JAG2 7.3 6.7 1.0 5.4 
IRX5 3.9 17.0 5.9 4.5 
LOXL4 2.5 17.0 11.0 15.0 
DSIPI4.7 14.8 23.9 8.9 
CSDA 3.3 12.3 2.0 8.6 
RABL5 3.1 10.8 3.7 3.7 
MDM2 2.6 5.4 1.3 3.8 
BDNF2.3 4.7 4.4 7.1 
TCF12 2.2 3.4 1.8 2.1 
ACVR2 2.2 2.2 0.7 1.0 
AK1 6.4 4.4 2.2 1.7 
KCNB1 3.2 1.9 2.3 0.7 
MITF 3.2 1.3 1.9 0.5 
KIAA1536 3.8 0.1 0.1 2.4 
EDG4 1.7 128.0 6.9 5.6 
LMO4 1.2 10.2 1.2 1.8 
PC4 0.8 8.7 1.6 5.7 
JPH2 0.6 8.1 5.2 1.4 
HUS1 0.9 7.2 2.6 4.1 
NFE2L10.6 5.0 2.9 0.5 
CLK3 1.9 4.5 0.9 3.2 
KCNJ11 1.2 4.3 4.2 0.7 
JMJ0.6 3.3 2.5 1.6 
ADAMTS4 1.4 3.0 5.5 1.3 
IL15RA1.0 1.2 2.8 5.9 
BMP4 0.2 0.0 0.0 0.2 
SHOX2 0.1 0.0 0.0 0.1 
     
Control
 
    
p21 28.8 36.7 6.8 4.6 
GADD45A 42.8 98.2 16.8 46.5 
*

Expression of p53 and p53 family target genes identified by in silico analysis was examined by real-time PCR in Saos-2 cells or DLD-1 cells.

VDR as a direct transcriptional target of p53. Among the putative p53 target genes identified by our comparative sequence analysis, we focused on the VDR gene, which encodes a nuclear receptor that mediates the effects of 1,25(OH)2D3 and has potential tumor-suppressive activity (12). Vitamin D and its analogues induce cell cycle arrest and apoptosis and, potentially, could be used for cancer prevention (12, 13). However, transcriptional regulation of the VDR gene is not fully understood. Whereas our computational search revealed that its promoter and intronic regions contain several potential p53 binding sites, only a single site located at position 4,695-4,704 relative to the transcription start site is conserved between the human and mouse genomes (Fig. 3A and B). Further examination for this region using our p53RE prediction system revealed that it contains five copies of the consensus 10-bp motif and that these sequences are well conserved in the human, chimpanzee, mouse, rat, and dog genomes (Fig. 3C; Supplementary Fig. S3). From these results, we predicted this region could mediate p53-dependent transactivation.

Figure 3.

VDR is a direct transcriptional target of p53. A, the genomic structure of the VDR gene. Exons are shown as numbered boxes, introns as lines. B, a computational search revealed several candidate p53 binding sites in the first intron of the human and mouse VDR genes. Boxes, putative p53 binding sites; the number of nucleotides matching the consensus p53 binding sequence and the spacer length are shown above each of the potential p53 binding sites; solid boxes, binding sites that are conserved between human and mouse. The nucleotide sequences of the conserved p53 binding site (VDR-p53RE) are indicated within the dotted lines; lowercase letters, divergence from the consensus sequence. C, the conserved p53 binding sites predicted by bioinformatic analysis (VDR-p53RE) consist of five 10-bp motifs. The nucleotide sequences were compared among four mammalian species; asterisks, conserved sequences. The five 10-bp motifs in human are the most conserved to the consensus among the four species. D, ChIP analysis of the VDR-p53RE. ChIP assays were carried out with DLD-1 cells transfected with Ad-p53 or Ad-LacZ, and the chromatin was immunoprecipitated using an anti-p53 antibody (Santa Cruz Biotechnology). After extensive washing, the cross-linking was reversed and the DNA was subjected to PCR using primers specific for the indicated conserved regions. The region around the p53RE of the p21 gene was amplified as a positive control. E, luciferase assay for VDR-p53RE. Saos-2 and H1299 cells (p53-null) were cotransfected with pGL3-VDR-RE or pGL3-p53CBS (21), together with pcDNA-p53 (p53+) or pcDNA3.1 (p53−). The relative luciferase activity was defined as the activity in the cells transfected with pGL3-VDR-RE (wt) divided by the activity in cells transfected with pGL3-VDR-RE (mut). Columns, mean of three independent experiments; bars, SD.

Figure 3.

VDR is a direct transcriptional target of p53. A, the genomic structure of the VDR gene. Exons are shown as numbered boxes, introns as lines. B, a computational search revealed several candidate p53 binding sites in the first intron of the human and mouse VDR genes. Boxes, putative p53 binding sites; the number of nucleotides matching the consensus p53 binding sequence and the spacer length are shown above each of the potential p53 binding sites; solid boxes, binding sites that are conserved between human and mouse. The nucleotide sequences of the conserved p53 binding site (VDR-p53RE) are indicated within the dotted lines; lowercase letters, divergence from the consensus sequence. C, the conserved p53 binding sites predicted by bioinformatic analysis (VDR-p53RE) consist of five 10-bp motifs. The nucleotide sequences were compared among four mammalian species; asterisks, conserved sequences. The five 10-bp motifs in human are the most conserved to the consensus among the four species. D, ChIP analysis of the VDR-p53RE. ChIP assays were carried out with DLD-1 cells transfected with Ad-p53 or Ad-LacZ, and the chromatin was immunoprecipitated using an anti-p53 antibody (Santa Cruz Biotechnology). After extensive washing, the cross-linking was reversed and the DNA was subjected to PCR using primers specific for the indicated conserved regions. The region around the p53RE of the p21 gene was amplified as a positive control. E, luciferase assay for VDR-p53RE. Saos-2 and H1299 cells (p53-null) were cotransfected with pGL3-VDR-RE or pGL3-p53CBS (21), together with pcDNA-p53 (p53+) or pcDNA3.1 (p53−). The relative luciferase activity was defined as the activity in the cells transfected with pGL3-VDR-RE (wt) divided by the activity in cells transfected with pGL3-VDR-RE (mut). Columns, mean of three independent experiments; bars, SD.

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We next carried out ChIP assays to determine whether the p53 protein binds directly to the predicted p53RE in the VDR gene in cells. Immunoprecipitation of DNA-protein complexes using mouse anti-human p53 mAb was carried out on formaldehyde-cross-linked extract of Ad-p53-infected DLD-1 cells; after which, we measured the abundance of the candidate sequence within the immunoprecipitated complexes using PCR. The ChIP assays revealed that p53 protein bound reproducibly to a DNA fragment containing the candidate p53RE of the VDR gene (Fig. 3D). Furthermore, to determine whether this p53RE could be involved in transcriptional regulation, three copies of oligonucleotides containing the wild-type p53RE (VDR-RE wt) or an inactive mutant form (VDR-RE mut) were cloned upstream of a luciferase reporter gene; after which, the resultant constructs were transfected into H1299 cells, with or without p53 (pcDNA-p53). Unlike the mutated sequence, wild-type VDR-RE rendered the reporter construct responsive to p53, leading to a 20-fold increase in luciferase activity (Fig. 3E). Taken together, these findings indicate that the nucleotide sequence spanning positions 4,695-4,704 in intron 1 of the VDR gene constitutes a bona fide p53RE, and VDR is a direct transcriptional target of p53.

Induction of VDR by p53 family genes and genotoxic stresses. To investigate the effect of p53 on endogenous VDR induction, the expression levels of VDR mRNA were examined in several cell lines. We found that there was significant induction of VDR mRNA subsequent to infection with Ad-p53 in Saos-2 and HCT116 cells (Fig. 4A,, top) and in DLD-1 and SW480 cells (Supplementary Fig. S4A), but no induction in those cells infected with Ad-LacZ. Interestingly, induction of VDR is more prominent in cells transfected with Ad-p63 or Ad-p73, indicating that p53 family members are strong inducers of VDR. These results were confirmed by quantitative real-time PCR, which showed that p53 family genes induced a 4- to 10-fold increase in the expression of VDR mRNA over that seen in cells infected with control vector (Fig. 4A,, bottom). Furthermore, we confirmed induction of VDR mRNA in Saos-2, DLD-1, and H1299 cells by Northern blot analysis, and also induction of VDR protein in Saos-2, HCT116, DLD-1, and RKO cells by Western blot analysis (Fig. 4B and C and Supplementary Fig. S4B and C). In addition, immunocytochemical analysis showed that when Saos-2 cells were infected with Ad-p53, a significant amount of VDR protein accumulated in the nucleus (Fig. 4D). Similar nuclear accumulation of VDR protein was seen in Saos-2 cells infected with Ad-p63 and Ad-p73 but not in cells with Ad-lacZ (Fig. 4D) and in DLD-1 cells infected with Ad-p53, Ad-63, and Ad-73 (Supplementary Fig. S4D).

Figure 4.

Induction of VDR by p53 family genes. A, RT-PCR (top) and real-time PCR (bottom) analysis of VDR expression. RNA was extracted from Saos-2 and HCT116 cells infected with Ad-lacZ, Ad-p53, Ad-p63γ, Ad-p73α, or Ad-p73β, and tested for expression of VDR mRNA by RT-PCR. For real-time PCR, expression levels of VDR mRNA were normalized to those of GAPDH mRNA. Columns, mean of three independent experiments; bars, SD. B, Northern blot analysis of VDR mRNA in Saos-2 cells infected with Ad-p53, Ad-p73β, or Ad-p63 γ. An ethidium-stained gel containing 28S RNA shows the amounts of mRNA loaded in each lane. C, Western blot analysis of VDR protein in Saos-2 and HCT116 cells infected with Ad-LacZ, Ad-p53, Ad-p63γ, or Ad-p73β. p21 expression served as a positive control for a p53 target; actin expression was used as a loading control. D, immunofluorescence analysis of Ad-p53-induced VDR protein expression. Saos-2 cells were infected with Ad-lacZ, Ad-p53, Ad-p63, or Ad-p73β; after which, VDR was detected using an anti-VDR antibody and an FITC-conjugated secondary antibody. The nucleus was stained with DAPI. E, induction of VDR by a chemotherapeutic drug. Expression levels of VDR mRNA in response to Adriamycin (ADR) in RKO, HCT116, and U2OS cells were analyzed by RT-PCR (top) and real-time RT-PCR (bottom). RKO cells were treated with 0.2 μg/mL Adriamycin for the indicated times (0, 12, and 24 hours). HCT116 and U2OS cells were treated with Adriamycin at the indicated concentration (0-0.5 mg/mL) for 24 hours. F, Western blot analysis of VDR and p53 proteins following treatment with Adriamycin (0-0.5 μg/mL) for 24 hours.

Figure 4.

Induction of VDR by p53 family genes. A, RT-PCR (top) and real-time PCR (bottom) analysis of VDR expression. RNA was extracted from Saos-2 and HCT116 cells infected with Ad-lacZ, Ad-p53, Ad-p63γ, Ad-p73α, or Ad-p73β, and tested for expression of VDR mRNA by RT-PCR. For real-time PCR, expression levels of VDR mRNA were normalized to those of GAPDH mRNA. Columns, mean of three independent experiments; bars, SD. B, Northern blot analysis of VDR mRNA in Saos-2 cells infected with Ad-p53, Ad-p73β, or Ad-p63 γ. An ethidium-stained gel containing 28S RNA shows the amounts of mRNA loaded in each lane. C, Western blot analysis of VDR protein in Saos-2 and HCT116 cells infected with Ad-LacZ, Ad-p53, Ad-p63γ, or Ad-p73β. p21 expression served as a positive control for a p53 target; actin expression was used as a loading control. D, immunofluorescence analysis of Ad-p53-induced VDR protein expression. Saos-2 cells were infected with Ad-lacZ, Ad-p53, Ad-p63, or Ad-p73β; after which, VDR was detected using an anti-VDR antibody and an FITC-conjugated secondary antibody. The nucleus was stained with DAPI. E, induction of VDR by a chemotherapeutic drug. Expression levels of VDR mRNA in response to Adriamycin (ADR) in RKO, HCT116, and U2OS cells were analyzed by RT-PCR (top) and real-time RT-PCR (bottom). RKO cells were treated with 0.2 μg/mL Adriamycin for the indicated times (0, 12, and 24 hours). HCT116 and U2OS cells were treated with Adriamycin at the indicated concentration (0-0.5 mg/mL) for 24 hours. F, Western blot analysis of VDR and p53 proteins following treatment with Adriamycin (0-0.5 μg/mL) for 24 hours.

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To then determine the extent to which VDR transcription is induced by elevation of endogenous p53, we examined the levels of VDR mRNA in three cell lines that have wild-type p53 (RKO, HCT116, and U2OS cells) following treatment with Adriamycin, a DNA-damaging agent, which can induce endogenous p53 (Fig. 4E and F). We found that VDR mRNA was up-regulated ∼3- to 4-fold in cells treated with Adriamycin.

The role of VDR in the antiproliferative effect of vitamin D3. The HCT116 cell line was evaluated as a suitable model system in which to study the function of p53 family members in inducing VDR target genes and in modulating response of the cells to vitamin D3. To investigate the biological significance of up-regulating VDR on inhibition of cell-proliferation, HCT116 cells were transfected with pCMV-VDR, an expression vector containing the full-length VDR gene for 48 hours, and high expression levels of VDR mRNA were detected (Fig. 5A). Subsequently, we assessed expression of VDR-downstream genes in cells overexpressing VDR and in control cells in the presence or absence of vitamin D3 (Fig. 5B). In HCT116 cells transfected with a control vector (pCMV-Tag2), expression of genes associated with mineral metabolism (e.g., CYP24A1, a key gene involved in vitamin D metabolism) was increased in response to vitamin D3, despite the low level of VDR expression. In contrast, genes involved in cell cycle arrest (e.g., CDKN1A) showed no sensitivity to vitamin D3 unless VDR was overexpressed, in which case CDKN1A was up-regulated ∼2-fold by vitamin D3 treatment. It thus seems that elevation of VDR expression may be necessary for the antiproliferative effect of vitamin D3 in HCT116 cells. Consistent with this hypothesis, colony formation assays carried out in the presence and absence of vitamin D3 showed that HCT116 cells transfected with control vector were insensitive to vitamin D3 and thus exhibited significant colony formation, regardless of vitamin D3 treatment (Fig. 5C and D). In contrast, cells expressing high levels of VDR were sensitive to vitamin D3, which dramatically inhibited their colony-forming ability (Fig. 5C and D).

Figure 5.

VDR suppresses tumor growth in a vitamin D3-dependent manner. A and B, effect of different expression levels of VDR on vitamin D3 target genes. HCT116 cells were transfected with either pCMV-Tag2 (control plasmid encoding Flag-tag) or pCMV-VDR and incubated with 0.6 mg/mL G418 in the presence or absence of vitamin D3 (100 nmol/L). Total RNA was prepared from HCT116 cells; after which, expression of the vitamin D3 target genes was analyzed by RT-PCR (A) or real-time RT-PCR (B). C and D, suppression of growth was evaluated by assaying geneticin-resistant colony formation. HCT116 cells were transfected with either pCMV-Tag2 (control plasmid encoding a Flag epitope) or pCMV-VDR and incubated with 0.6 mg/mL G418 in the presence or absence of vitamin D3 (100 nmol/L). After 14 days, plates were stained with Giemsa solution (C) and the colonies were counted (D). Columns, mean of three independent experiments; bars, SD.

Figure 5.

VDR suppresses tumor growth in a vitamin D3-dependent manner. A and B, effect of different expression levels of VDR on vitamin D3 target genes. HCT116 cells were transfected with either pCMV-Tag2 (control plasmid encoding Flag-tag) or pCMV-VDR and incubated with 0.6 mg/mL G418 in the presence or absence of vitamin D3 (100 nmol/L). Total RNA was prepared from HCT116 cells; after which, expression of the vitamin D3 target genes was analyzed by RT-PCR (A) or real-time RT-PCR (B). C and D, suppression of growth was evaluated by assaying geneticin-resistant colony formation. HCT116 cells were transfected with either pCMV-Tag2 (control plasmid encoding a Flag epitope) or pCMV-VDR and incubated with 0.6 mg/mL G418 in the presence or absence of vitamin D3 (100 nmol/L). After 14 days, plates were stained with Giemsa solution (C) and the colonies were counted (D). Columns, mean of three independent experiments; bars, SD.

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VDR enhances the transcriptional activation of TP53 downstream genes. We next examined whether the induction of expression of VDR and its target genes by p53, p63, and p73 was enhanced by the addition of vitamin D3 in HCT116 cells. Among six genes examined, three (GADD45, SPP1, and IGFBP3) were induced when Ad-p63 and vitamin D3 were added, suggesting that VDR may play an important role in transcriptional activation by p63 (Fig. 6). Expression of CYP24A1 and CDH1 was induced by vitamin D3 but transfection with Ad-p53, Ad-p63, and Ad-p73 did not result in synergistic enhancement. Expression of CDKN1A was induced by Ad-p53, Ad-p63, and Ad-p73 but the effect of vitamin D3 was not significant. To further assess the role of VDR in transactivation of p53 target genes, we examined the effects of disrupting VDR expression in HCT116 cells using two VDR-specific shRNA (sh-VDR) constructs. Subsequent real-time PCR and Western blot analysis showed that VDR expression was down-regulated after puromycin selection of HCT116 cells that express sh-VDR (Fig. 7A). These results were confirmed using two different shRNA constructs. We also found that GADD45, SPP1, and IGFBP3, but not CDKN1A, were suppressed by sh-VDR. The results suggest that VDR plays a key role in the transcriptional activation of a subset of p53 target genes (Fig. 7B). We next examined whether down-regulation of VDR affects apoptosis induced by Ad-p53 and Ad-p63 (Fig. 7C). Down-regulation of VDR decreased the numbers of apoptotic HCT116 cells induced by Ad-p53 or Ad-p63.

Figure 6.

Transcriptional activation of VDR target genes by p53, p63γ, or p73. HCT116 cells were infected with Ad-LacZ, Ad-p53, Ad-p63γ, and Ad-p73β for 48 hours, then either mock treated (white column) or treated with 100 nmol/L of Vitamin D3 (gray column) for 48 hours. Total RNA was extracted for expression analysis by RT-PCR or real-time PCR. Columns, mean of three independent experiments; bars, SD. An unpaired t test was used to determine statistically significant effects of vitamin D3 treatment. *, P < 0.05, significance of differences between mock and vitamin D3 treated cells.

Figure 6.

Transcriptional activation of VDR target genes by p53, p63γ, or p73. HCT116 cells were infected with Ad-LacZ, Ad-p53, Ad-p63γ, and Ad-p73β for 48 hours, then either mock treated (white column) or treated with 100 nmol/L of Vitamin D3 (gray column) for 48 hours. Total RNA was extracted for expression analysis by RT-PCR or real-time PCR. Columns, mean of three independent experiments; bars, SD. An unpaired t test was used to determine statistically significant effects of vitamin D3 treatment. *, P < 0.05, significance of differences between mock and vitamin D3 treated cells.

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Figure 7.

Disruption of VDR expression by sh-VDR. A, real-time PCR (top) and Western blot (bottom) analysis of VDR. HCT116 cells were transfected with control shRNA or VDR shRNA (sh-VDR20 or sh-VDR32), cultured with 1 μg/mL of puromycin for 48 hours, and total RNA and cell lysates were isolated. The amount of VDR mRNA was normalized to GAPDH. For Western blot analysis, membrane was blotted with anti-p53 and antiactin antibodies as control. B, sh-VDR suppresses expression of p53 target genes. Expression of CDKN1A, GADD45, SPP1, and IGFBP3 was determined by real-time PCR; expression levels were normalized to that of GAPDH. C, apoptosis induced by Ad-p53 or Ad-p63. HCT116 cells were infected with Ad-p53 or Ad-p63 for 48 hours and apoptotic cells were examined by flow cytometry. *, P < 0.01, apoptosis was observed in cells infected with Ad-p63 more frequently than in Ad-lacZ-infected cells.

Figure 7.

Disruption of VDR expression by sh-VDR. A, real-time PCR (top) and Western blot (bottom) analysis of VDR. HCT116 cells were transfected with control shRNA or VDR shRNA (sh-VDR20 or sh-VDR32), cultured with 1 μg/mL of puromycin for 48 hours, and total RNA and cell lysates were isolated. The amount of VDR mRNA was normalized to GAPDH. For Western blot analysis, membrane was blotted with anti-p53 and antiactin antibodies as control. B, sh-VDR suppresses expression of p53 target genes. Expression of CDKN1A, GADD45, SPP1, and IGFBP3 was determined by real-time PCR; expression levels were normalized to that of GAPDH. C, apoptosis induced by Ad-p53 or Ad-p63. HCT116 cells were infected with Ad-p53 or Ad-p63 for 48 hours and apoptotic cells were examined by flow cytometry. *, P < 0.01, apoptosis was observed in cells infected with Ad-p63 more frequently than in Ad-lacZ-infected cells.

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The data summarized above suggest that VDR plays a novel role in the p53 signaling pathways shown in Fig. 8. Under normal physiologic conditions, VDR induces its downstream genes associated with metabolic pathways, including vitamin D3–dependent Ca2+ uptake. Under genotoxic stress, however, VDR induced by p53 may serve as an effector to up-regulate expression of genes associated with cell cycle regulation, differentiation, and apoptosis.

Figure 8.

Diagram of common p53 and VDR target genes. The pathways were drawn by Ingenuity Pathway Analysis Software. The p53 target genes (e.g., p21, IGFBP3, and GADD45α) can be activated either directly by p53 or via activation of VDR.

Figure 8.

Diagram of common p53 and VDR target genes. The pathways were drawn by Ingenuity Pathway Analysis Software. The p53 target genes (e.g., p21, IGFBP3, and GADD45α) can be activated either directly by p53 or via activation of VDR.

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In this study, we used a computational approach to predict novel p53 target genes through a genome-wide search for consensus p53 binding sequences. Our results indicate that putative p53 binding sequences are present, on average, every 620 bp in the human genome, although it is likely that most of them are nonfunctional, at least for transactivation. In this regard, we found that comparison of the p53 binding sequences between human and mouse is highly useful for identifying functional p53REs. In several known p53 target genes, the sequences surrounding the p53 binding sites are highly conserved among different species, suggesting that other unknown elements (e.g., transcription factor binding sites) are necessary for p53 protein to bind to p53REs and function as a transcriptional coactivator. Detailed studies of functional regulatory elements combined with more sophisticated comparative genomics, including comparison across multiple species with varying degrees of divergence, should help in resolving the flexible regulatory landscape of mammalian genomes. The reason why the sequences surrounding p53REs are conserved among species remains unclear. Nevertheless, the information obtained in the present study should be useful not only for identifying p53 target genes but also for identifying transcriptional factors that function cooperatively with p53. Intriguingly, the sequences surrounding the functional p53RE of the VDR gene are also conserved across species (Supplementary Fig. S3). It is thus possible that conserved sequences close to p53REs may play a role in recruiting transcriptional coactivators such as p300, BRCA1, PML, SWI/SNF complex, and IRF-1 to activate gene expression (2428).

We found that expression of the human VDR gene is directly up-regulated by p53, which confirmed an association between p53 and VDR and helps to elucidate one aspect of the biological significance of elevated VDR expression. Vitamin D analogues, such as 1,25(OH)2D3, can inhibit the growth of various types of malignant cells, including breast, prostate, colon, skin, and brain cancer cells, as well as myeloid leukemia cells (12, 13, 15, 29). Moreover, 1,25(OH)2D3 shows antitumor activity in animal models (30) and, accordingly, clinical studies to evaluate the effect of vitamin D analogues in patients with colorectal cancer and other neoplasms are under way (12, 13). The molecular mechanisms by which 1,25(OH)2D3 suppresses cell growth involve regulation of the cell cycle by inducing p21WAF1 and apoptosis mediated by BCL-2 and inhibitor of apoptosis protein (16, 31). In addition, vitamin D3 down-regulates the T-cell factor/β-catenin system (17).

VDR has been reported to be down-regulated during tumor progression although the molecular mechanism is not fully understood. Conversely, VDR is up-regulated by a variety of growth factors, Sp1 (32, 33), WT1 (34), and vitamin D3, and high levels of VDR expression are associated with a good prognosis in colorectal cancer (18). In addition, Palmer et al. (19) recently reported that VDR is down-regulated by the transcriptional repressor SNAIL. They showed that high levels of SNAIL expression are associated with cell dedifferentiation and a low level of VDR protein. SNAIL protein interacts directly with the VDR promoter, suppressing its activity and thereby abolishing induction of E-cadherin and other VDR target genes by vitamin D. The fact that VDR is a target gene of p53 suggests that alteration of p53 may be one of the causes of VDR dysregulation in cancer.

VDR pathways may partially overlap p53 pathways because several downstream VDR target genes are also targets of p53 (12, 14, 35) and because vitamin D3 can induce cell cycle arrest, differentiation, and apoptosis (Fig. 8). Under normal physiologic conditions, VDR may preferentially induce target genes involved in Ca2+ uptake and cellular differentiation (e.g., CYP24A1). In the presence of genotoxic stress however, VDR seems to induce target genes associated with cell cycle regulation and apoptosis. This difference in VDR target genes under normal and stressed conditions may be partially explained by the p53-dependent up-regulation of VDR protein expression induced by genotoxic stress.

VDR target genes also can be induced by stimulation of vitamin D3 in the presence of an inactive p53 mutant or in p53-deficient cells (35, 36). Consistent with these findings, we observed that p63 and p73 also induce VDR gene expression in cell lines. Although both p63 and p73 can bind to p53REs (37), they specifically bind to those elements containing three or four copies of the 10-bp consensus motif separated by spacer sequences (21). This is consistent with the fact that the p53RE in the VDR gene contains five copies of the 10-bp motif (Fig. 3C). Recent studies have shown that both vitamin D and p63 are associated with development and differentiation in several organs. Our results indicate that there is an association between p63 and VDR expression, which raises the possibility that up-regulation of VDR by p63 at appropriate stages in various cell types might increase their susceptibility to the proapoptotic activity of vitamin D metabolites.

In summary, we have identified novel p53 target genes by comparative analysis of p53REs. In particular, we also showed that VDR, which is a transcriptional regulator downstream of p53-dependent cellular signaling, is a direct transcriptional target of p53 and plays a role in p53-mediated suppression of tumor growth. Our results indicate that this in silico approach is a powerful method for identification of p53 target genes conserved among humans and other organisms and could serve to facilitate analysis of the function of p53 in tumorigenesis.

Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

Grant support: Grants-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Culture, Sports, Science, and Technology (M. Toyota, K. Imai, and T. Tokino) and a grant from New Energy and Industrial Technology Development Organization (M. Toyota).

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. Joseph F. Costello and William F. Goldman for valuable discussion.

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