Research Article
Comparative Genome Analysis Identifies the Vitamin D Receptor
Gene as a Direct Target of p53-Mediated Transcriptional Activation
1
3
1,2,5
2
3
Reo Maruyama, Fumio Aoki, Minoru Toyota, Yasushi Sasaki, Hirofumi Akashi, Hiroaki Mita,
1,4
1,2
2
1
Hiromu Suzuki, Kimishige Akino, Mutsumi Ohe-Toyota, Yumiko Maruyama,
3
1
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2
Haruyuki Tatsumi, Kohzoh Imai, Yasuhisa Shinomura, and Takashi Tokino
2
1
First Department of Internal Medicine; 2Department of Molecular Biology, Cancer Research Institute; 3Information Center of Computer
Communication; and 4Department of Public Health, Sapporo Medical University, Sapporo, Japan; and 5Precursory Research
for Embryonic Science and Technology, Japan Science and Technology Agency, Kawaguchi, Japan
Abstract
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 D3dependent 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)
Introduction
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 (3–6). 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 (14–17). 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.
Materials and Methods
Note: Supplementary data for this article are available at Cancer Research Online
(http://cancerres.aacrjournals.org/).
Requests for reprints: Takashi Tokino, Department of Molecular Biology, Cancer
Research Institute, Sapporo Medical University, South 1, West 17, Chuo-ku, Sapporo
060-8556, Japan. Phone: 81-11-611-2111, ext. 2386; Fax: 81-11-618-3313; E-mail:
[email protected].
I2006 American Association for Cancer Research.
doi:10.1158/0008-5472.CAN-05-2562
Cancer Res 2006; 66: (9). May 1, 2006
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
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VDR Is Up-regulated by p53
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, p73a, p73h, p63g, and the bacterial LacZ gene (Ad-p53,
Ad-p73a, Ad-p73h, 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 Ag/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 Ag of sh-VDR20, sh-VDR32, or control pFIV-H1Puro 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 Ag/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 pGL3VDR-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 transcriptionPCR (RT-PCR) was carried out as previously described (6). Briefly, total RNA
was extracted using TRIzol (Invitrogen); after which, a 5-Ag 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
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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 Ag/mL salmon sperm DNA overnight at 42jC.
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 60jC. The
intensities of hybridization bands were quantitated using a BAS2000
Bioimage Analyzer (Fuji, Tokyo, Japan).
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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Cancer Research
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.
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 4jC 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 4V,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 60mm 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 Ag 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
Cancer Res 2006; 66: (9). May 1, 2006
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.
Results
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 genomewide pattern matching with all possible p53 patterns [patterns =
28 28 13 (spacer) = 851,968], we broke down this consensus
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VDR Is Up-regulated by p53
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.
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 (z70% 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.
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
6
7
Ad-p53, Ad-p63, Ad-p73a, Ad-p73h, 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).
VDR as a direct transcriptional target of p53. Among the
putative p53 target genes identified by our comparative sequence
Gene name
GAS6
GEM
VDR
EFNB1
SYT13*
LU
HAS3
JAG2
IRX5
LOXL4
DSIPI*
CSDA
RABL5
MDM2
BDNF*
TCF12
ACVR2
AK1
KCNB1
MITF
KIAA1536
EDG4
LMO4
PC4
JPH2
HUS1
NFE2L1*
CLK3
KCNJ11
JMJ*
ADAMTS4
IL15RA*
BMP4
SHOX2
Fold induction
p53
p63
p73a
p73h
425.0
8.1
12.1
9.1
8.9
5.3
5.3
7.3
3.9
2.5
4.7
3.3
3.1
2.6
2.3
2.2
2.2
6.4
3.2
3.2
3.8
1.7
1.2
0.8
0.6
0.9
0.6
1.9
1.2
0.6
1.4
1.0
0.2
0.1
561.1
25.2
17.5
3.1
3.3
3.1
32.5
6.7
17.0
17.0
14.8
12.3
10.8
5.4
4.7
3.4
2.2
4.4
1.9
1.3
0.1
128.0
10.2
8.7
8.1
7.2
5.0
4.5
4.3
3.3
3.0
1.2
0.0
0.0
112.3
69.3
10.3
5.6
0.8
31.4
6.3
1.0
5.9
11.0
23.9
2.0
3.7
1.3
4.4
1.8
0.7
2.2
2.3
1.9
0.1
6.9
1.2
1.6
5.2
2.6
2.9
0.9
4.2
2.5
5.5
2.8
0.0
0.0
61.6
9.1
20.2
5.8
0.6
14.6
21.7
5.4
4.5
15.0
8.9
8.6
3.7
3.8
7.1
2.1
1.0
1.7
0.7
0.5
2.4
5.6
1.8
5.7
1.4
4.1
0.5
3.2
0.7
1.6
1.3
5.9
0.2
0.1
28.8
42.8
36.7
98.2
6.8
16.8
4.6
46.5
Control
p21
GADD45A
*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.
http://www.repeatmasker.org/.
http://www.sapmed.ac.jp/freomaru/p53.html.
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Table 1. Summary of p53 and p53 family target genes
identified by in silico analysis
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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.
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.
Cancer Res 2006; 66: (9). May 1, 2006
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-crosslinked 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
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VDR Is Up-regulated by p53
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 Adp63 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-p63g, Ad-p73a, or Ad-p73h, 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-p73h, or Ad-p63 g. 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-p63g, or Ad-p73h. 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-p73h; 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 Ag/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 Ag/mL) for 24 hours.
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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.
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 f3- 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 upregulating 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 (pCMVTag2), expression of genes associated with mineral metabolism
(e.g., CYP24A1, a key gene involved in vitamin D metabolism) was
Cancer Res 2006; 66: (9). May 1, 2006
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 f2-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).
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
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VDR Is Up-regulated by p53
(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 (shVDR) 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.
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.
Discussion
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
(24–28).
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
Figure 6. Transcriptional activation of VDR target genes by p53, p63g, or p73. HCT116 cells were infected with Ad-LacZ, Ad-p53, Ad-p63g, and Ad-p73h 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 Ag/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.
(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/h-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
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 GADD45a ) can be activated
either directly by p53 or via activation of
VDR.
Cancer Res 2006; 66: (9). May 1, 2006
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VDR Is Up-regulated by p53
conditions may be partially explained by the p53-dependent upregulation 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.
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Acknowledgments
Received 7/20/2005; revised 1/31/2006; accepted 2/24/2006.
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.
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