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Nucleic Acids Res. Apr 2012; 40(8): 3538–3547.
Published online Dec 19, 2011. doi:  10.1093/nar/gkr1219
PMCID: PMC3333873

Genome-wide Runx2 occupancy in prostate cancer cells suggests a role in regulating secretion

Abstract

Runx2 is a metastatic transcription factor (TF) increasingly expressed during prostate cancer (PCa) progression. Using PCa cells conditionally expressing Runx2, we previously identified Runx2-regulated genes with known roles in epithelial–mesenchymal transition, invasiveness, angiogenesis, extracellular matrix proteolysis and osteolysis. To map Runx2-occupied regions (R2ORs) in PCa cells, we first analyzed regions predicted to bind Runx2 based on the expression data, and found that recruitment to sites upstream of the KLK2 and CSF2 genes was cyclical over time. Genome-wide ChIP-seq analysis at a time of maximum occupancy at these sites revealed 1603 high-confidence R2ORs, enriched with cognate motifs for RUNX, GATA and ETS TFs. The R2ORs were distributed with little regard to annotated transcription start sites (TSSs), mainly in introns and intergenic regions. Runx2-upregulated genes, however, displayed enrichment for R2ORs within 40 kb of their TSSs. The main annotated functions enriched in 98 Runx2-upregulated genes with nearby R2ORs were related to invasiveness and membrane trafficking/secretion. Indeed, using SDS–PAGE, mass spectrometry and western analyses, we show that Runx2 enhances secretion of several proteins, including fatty acid synthase and metastasis-associated laminins. Thus, combined analysis of Runx2's transcriptome and genomic occupancy in PCa cells lead to defining its novel role in regulating protein secretion.

INTRODUCTION

The mammalian Runx family includes three transcription factors that regulate cellular commitment and differentiation in several systems including hematopoeisis (Runx1), skeletogenesis (Runx2) and gastric epithelium development (Runx3) (1–4). Runx proteins also play positive and negative roles in carcinogenesis, with Runx2 emerging as a master regulator of tumor metastasis (5,6). The interest in its pro-metastatic activity initiated with the idea that expression of Runx2, an osteoblast master regulator (7,8), in prostate cancer (PCa) and breast cancer (BCa) cells could explain their high predilection to the skeleton (9). In fact, accumulative evidence now implicates Runx2 not only in bone targeting, but also in various other aspects of metastasis. Nuclear Runx2 is increased in malignant versus benign prostate tissue and is associated with tumor aggression in general and metastasis in particular (10,11). In animal models of carcinogenesis, increased Runx2 levels were observed early during the development of various malignancies, including PCa (12) and thyroid cancer (13). Mechanistically, Runx2 has been shown to promote epithelial–mesenchymal transition (EMT) and invasiveness, as well as survival in the bone environment (14,15). Thus, Runx2 plays a variety of roles during both early and late stages of cancer metastasis, including but not limited to bone metastasis.

Runx2 stimulates the expression of numerous genes with known roles in cancer metastasis (5,14–16). Among them are SOX9, LCN2 and SNAI2, which promote EMT; MMP9, MMP13 and PGC which play roles in extracellular matrix degradation and invasiveness; VEGFA and EDN2, which are important for angiogenesis; and RANKL, PTHrP, IL8, SPHK1, EDG3 and CSF2, which likely contribute to the osteolytic phenotype induced by Runx2-expressing cancer cells that metastasize to bone (5,14). To gain a better understanding of Runx2's mechanisms in PCa, we performed Runx2 ChIP-seq analysis using C4-2B/Rx2dox cells, in which Runx2 expression is inducible by doxycycline (14). Combined analysis of gene expression profiles and the genomic Runx2 occupancy data led to the identification of a subset of Runx2-responsive genes with nearby Runx2-occupied regions (R2ORs). These presumably direct target genes are related not only to cellular properties already associated with Runx2, such as invasiveness, but also to the secretory machinery, whose stimulation by Runx2 may facilitate cell–cell and cell–matrix interactions that promote metastasis.

MATERIALS AND METHODS

Cell culture

We previously described the cell lines C4-2B/Rx2dox, LNCaP/Rx2dox and MCF7/Rx2dox, which express Flag-Runx2 in response to doxycycline (dox); C4-2B/Rx2-Mdox, which expresses a DNA-binding deficient mutant of Runx2 in response to dox; and T47D/shRx2dox, which knocks down endogenous Runx2 in response to dox (14,15,17). C4-2B/Rx2dox, C4-2B/Rx2-Mdox, LNCaP/Rx2dox and T47D/shRx2dox cells were maintained in RPMI medium and MCF7/Rx2dox cells were maintained in DMEM, each supplemented with 10% FBS. Dox was added in fresh medium at 0.5 µg/ml.

Gene expression analysis

The GEO data set GSE24261, containing gene expression profiles of C4-2B/Rx2dox cells treated in quadruplicate with dox or vehicle (14) was re-analyzed using statistical methods described previously (18). Briefly, differentially expressed genes were identified using Benjamini–Hochberg adjusted t-test comparing cells treated with dox or vehicle for either 1 or 2 days. To validate Runx2-responsiveness of individual genes of interest in independent cultures, RNA was isolated using the Bio-Rad Total RNA kit, and cDNA was made using Quanta qScript cDNA synthesis kit. qPCR was performed using a Bio-Rad CFX96 machine, Fermentas Maxima SYBR mastermix and the primers listed in Supplementary Table S1. Amplification reactions had efficiency of 90–110% and no primer-dimers were produced. Relative expression was calculated using the delta Ct method.

Chromatin immunoprecipitation-PCR

Flag-ChIP for Runx2 was carried out essentially as described for the androgen receptor (19) with the following modifications. C4-2B/Rx2dox cultures containing 5 × 107 cells were crosslinked in 1.5% formaldehyde for 10 min at room temperature, and crosslinking was then halted by addition of glycine to 125 mM. Chromatin was sonicated to yield 500–1000 bp fragments in a buffer containing 50 mM Tris–HCl (pH 8.0), 0.1% SDS and 2 mM EDTA. Following preclearing with protein A dynabeads (Invitrogen), chromatin was incubated overnight with 0.5 µg Flag M2 antibody (Sigma) at +4°C and immunocomplexes were pulled down with Protein A dynabeads. Crosslinks for both ChIP and input DNA were reversed at 65°C for 5 h and DNA was cleaned using Qiagen QIAQuick spin DNA kit. Precipitated fragments were quantified by qPCR as described earlier, and percentage input values were corrected for negative control regions when indicated.

ChIP-sequencing and peak calling

Runx2 ChIP DNA along with ChIP input DNA were prepared as above from C4-2B/Rx2dox cells treated with dox for 14 h, and high throughput sequencing of the 500–1000 bp fragments was performed using Illumina Hi-Seq 2000. Libraries for ChIP-seq were prepared following protocols recommended by Illumina. Enrichment for known target sequences was verified by qPCR before ChIP and input DNA were sequenced. A total of 98 165 959 and 92 795 549 sequences were generated for input and ChIP samples, respectively. MAQ (20) was used to generate 95 514 565 and 70 493 488 alignments to the hg18 reference genome. These alignments were reduced to 78 152 251 and 11 371 023 after filtering for only uniquely mapable positions in the genome (Mapping quality score ≥20) and condensing multiple reads aligned to identical positions in the genome (i.e. potential PCR duplicates) to a single count. Peak Calling was performed using FindPeaks 4.0 (21), with the ChIP input used as control. Briefly, using the filtered BAM alignment files for Runx2 and input, FindPeaks first searches for peaks in ChIP sample, then assesses each peak for enrichment relative to the Input control. It performs this by normalizing the two distributions globally using linear regression, and then modeling the background as a Poisson distribution about the regression line. Length of fragments was inferred using the FindPeaks ‘triangle’ distribution. Runx2 peaks with P values <10−10 were identified as R2OR and used for downstream analyses. ChIP and input reads have been uploaded to the Sequence Read Archive, accession SRA048119.2 and to GEO, Accession GSE33889.

R2OR genomic distributions

Genomic distribution of R2ORs relative to gene annotations was performed using annotations from the UCSC knownGenes annotation track (hg18). For each annotation comparison, R2OR values were shown side by side with a set of regions picked randomly from the genome, with the randomized regions having the same number, distribution among different chromosomes and size as the actual R2ORs. One thousand such randomized sets were generated, and empirical background distributions were generated from this set of 1000 trials, from which summary statistics are shown in all comparisons.

Motif discovery and analysis

De novo motif discovery was performed using HOMER [script v3.1 (05-25-2011)] as previously described (22). Briefly, R2OR and background genomic sequences were extracted using Galaxy (23,24) and were divided into ‘target’ and ‘background’ sets for each application of the algorithm (HOMER perl script ‘findMotifs.pl’). Motifs of length 6, 7, 8, 9, 10, 11 and 12 bp were identified separately for enrichment in ‘target’ compared to ‘background’ set using the cumulative hypergeometric distribution to score enrichment. To increase sensitivity of the method, up to two mismatches were allowed in each oligonucleotide sequence and distributions of CpG content in ‘target’ and ‘background’ sequences were selectively weighted to equalize the distributions of CpG content in both sets. HOMER perl script ‘annotatePeaks.pl’ (22) and R software [R version 2.13.1, 2011-07-08, (25)] plus ‘ggplot2’ package (26) were used to generate genomic distribution of each identified motif. Additional statistical tools included the Database for Annotation, Visualization and Integrated Discovery (DAVID) and NextBio™. All statistical tests were done using R software [R version 2.13.1, 2011-07-08, (25)] and packages in Bioconductor (27).

Protein analyses

Western blot analysis was performed as previously described (14) with the following antibodies: Flag M2 from Sigma, GAPDH and FAS (h-300) from Santa Cruz Biotech, Laminin B1 (ab44941) and Laminin C1 (ab69632) from Abcam, LAMA5 (2F7) from Abnova and Tubulin from the Developmental Studies Hybridoma Bank. For mass spectrometry analysis of conditioned medium, C4-2B/Rx2dox cells were treated with dox or vehicle for 48 h in complete growth media followed by 24 h in serum-free media. Non-adherent cells were removed from the culture supernatant by brief centrifugation, and proteins precipitated with 20% trichloroacetic acid were resolved by SDS–PAGE and stained with Coomassie Blue. Gel slices of interest were subjected to in-gel trypsin digestion as described (28). The resulting peptides were cleaned using C18 OmixTips (Varian) and analyzed by the Proteomics Facility at Childrens Hospital Los Angeles essentially as previously described (29) using an Eksigent nanoLC-2D coupled to a Thermo Orbitrap XL mass spectrometer. Proteins were identified from tandem mass spectra by comparison to the human Uniprot database (downloaded 200908) using complementary protein identification software systems, Bioworks 3.3.1 (Thermo) and Scaffold 3 (Proteome Software) (30). Protein identification was based on at least two peptides, with peptide and protein probabilities of at least 95%.

RESULTS

Runx2 binds its targets in a cyclical fashion

Unlike most PCa tumors, the LNCaP and C4-2B cell lines are essentially Runx2-negative, providing a close-to-zero background system for the investigation of Runx2 function in PCa. In C4-2B/Rx2dox and LNCaP/Rx2dox cells, Flag-Runx2 is expressed in response to dox at levels comparable to or lower than those seen in other PCa cells and osteoblasts (14). Prior to performing Runx2 ChIP-seq in C4-2B/Rx2dox cells, and because there are relatively few published studies of Runx2 ChIP in general and in PCa cells in particular, we first optimized our ChIP assay based on Runx2 occupancy upstream of the CSF2 and KLK2 genes (Figure 1A). We chose these regions because CSF2 and KLK2 were strongly stimulated by Runx2 in C4-2B/Rx2dox cells (14), and because they contained clusters of Runx motifs (Figure 1A), a feature thought to constitute strong binding sites for Runx transcription factors (31,32). Runx2 binding upstream of the CSF2 and KLK2 genes was tested by quantitative ChIP assays every 2 h between 12 and 24 h of Runx2 induction. A cyclical binding pattern of Runx2 was obvious (Figure 1B), even though the protein level of Runx2 did not change significantly (Figure 1C). Untreated C4-2B/Rx2dox cells were processed in parallel; because they do not express Flag-Runx2, they serve as an ideal negative control for our ChIP experiments. As shown in Figure 1B, Flag-ChIP of the untreated cells did not show any enrichment at the CSF2 and KLK2 versus the negative control regions, indicating high specificity of the Flag-ChIP assay.

Figure 1.
Cyclical genomic recruitment of Runx2 to KLK2 and CSF2. (A) Diagram depicting predicted Runx binding sites within the 5-kb sequences upstream of the KLK2 and CSF2 TSSs. Runx motifs that appear as clusters are shown, with red and blue tics representing ...

Runx2 primarily occupies intergenic and intronic regions, distal to TSSs

For genome-wide mapping of R2ORs, Illumina high throughput single end sequencing was performed on a large-scale Runx2 ChIP, in which the CSF2 and KLK2 upstream Runx motifs were enriched by 8- and 16.5-fold, respectively. High throughput sequencing resulted in approximately 11 million sequence tags that uniquely mapped to the human genome build 18. As a control, the input DNA material was also subjected to high throughput sequencing, resulting in 78 million tags that were uniquely mapped. We initially examined the ChIP-seq data for Runx2 occupancy at the KLK2 and CSF2 loci (Figure 2A). In both cases, several R2ORs were readily identified, some with more occupancy than the regions initially selected for the conventional ChIP assays (black bars in Figures 1A and and2A).2A). At both loci, Runx2 occupancy occurred at presumed enhancer elements as well as at the transcription start sites (TSSs).

Figure 2.
Genome-wide characterization of Runx2 occupied regions (R2ORs). C4-2B/Rx2dox cells were subjected to Runx2 ChIP-seq analysis after dox treatment and immunoprecipitation of Runx2-bound DNA fragments with anti-FLAG antibodies. (A) ChIP-seq results showing ...

Using the FindPeaks program (21), we identified in the C4-2B cell genome 5413 R2ORs with an FDR-adjusted P-value <0.01 (Supplementary Table S2). Among them, some were found in the vicinity of genes previously shown to be regulated by Runx2 in PCa and other cell types, including CXCL12, MMP9, VEGFA and DUSP1 (14), PLAC8 and CRISPLD2 (15), HEY1 and TNC (33) as well as RUNX1, RUNX3 and RUNX2 itself (Supplementary Figure S1). Runx2 occupancy at rRNA genes (34) could not be assessed because these gene sequences are highly repetitive and thus not unequivocally mapped to the hg18 human genome build used in our study.

For further analyses, we applied a more stringent FDR-adjusted P-value of 10−10 resulting in 1603 peaks that included KLK2, but not CSF2 R2ORs (Supplementary Table S3). We then tested biological reproducibility of Runx2 occupancy at 16 regions by quantitative PCR (qPCR) of independent chromatin immunoprecipitates. Occupancy was confirmed in every case (Supplementary Figure S2A). Furthermore, when plotted against peak scores, the qPCR values were in good agreement with the ChIP-seq data (Figure 2B). In addition to the validation of Runx2 ChIP-seq peaks in C4-2B/Rx2dox cells, we analyzed in a similar fashion the related LNCaP/Rx2dox PCa cell line (14) and observed Runx2 occupancy at all 16 sites (Supplementary Figure S2B). Finally, the specificity of our results was tested by measuring occupancy of 10 R2ORs by a DNA-binding incompetent Runx2 mutant (14). Flag-ChIP assays of C4-2B/Rx2-Mdox cells, which inducibly express the Flag-tagged Runx2 mutant, showed that in contrast to wild-type Runx2, the mutant form did not bind to any of the R2ORs (Supplementary Figure S2C).

Next we assessed the distribution of the 1603 stringently defined R2ORs in relation to RefSeq gene annotations. As shown in Figure 2C, the distribution of R2ORs with respect to nearest TSSs is very similar to the distribution of matched random sets of genomic sequences, with R2ORs having a slight preference for TSSs. The vast majority of R2ORs are located in introns (44%) and distal intergenic regions (50%) with only 2% at promoters (Figure 2D). Thus, similar to Runx1 in differentiating megakaryocytes (35) and in hematopoietic progenitor cells (36), Runx2 in PCa cells appears to primarily associate with enhancers and not promoters.

Motif analysis

The three mammalian RUNX proteins have highly homologous DNA-binding domains and therefore bind similar consensus TGTGGT motifs in vitro. De novo motif-finding analysis of the 1603 top R2ORs in C4-2B/Rx2dox cells revealed the highest enrichment for the YTGTGGTTW sequence, containing the TGTGGT consensus as a core (Figure 3A). Eighty-one percent of the R2ORs in C4-2B/Rx2dox cells contained this sequence (Figure 3C), which is similar to that found for Runx1 in hematopoietic cells (35–37) (Figure 3A). Following the remarkable but expected enrichment of the R2ORs for the classical Runx motif (P = 10−699), additional de novo motif analysis indicated strong enrichment (P < 10e−100) for the GATA consensus motif, AGATAA, as well as a motif representing a hybrid of Runx and Ets cognate sequences (Figure 3B). The GATA and the Runx/Ets motifs were found in 26% and 6% of R2ORs, respectively (Figure 3C). Both GATA and ETS transcription factors have been previously reported to physically interact with RUNX proteins (35–42).

Figure 3.
DNA sequence motifs enriched in R2ORs. Motifs enriched in R2ORs compared to 1603 matched random sequences were identified using HOMER 3.1. (A) Logo for the top motif (Runx2) is shown above the Runx1 logo identified by Pencovich et al. (35). (B) Motifs ...

Runx2-induced genes with nearby R2ORs are functionally related to protein secretion

Although R2ORs are generally far from TSSs, we asked whether they were specifically enriched near TSSs of Runx2-responsive genes. We first re-analyzed our genome-wide expression data (14) and generated four sets of genes, those up- or down-regulated after 1 or 2 days of Runx2 induction (FDR-adjusted P < 10−3; Supplementary Figure S3). For each gene set, we plotted the histogram of distances between the responsive TSSs and the nearest R2ORs (Figure 4 and Supplementary Figure S4). To control for the responsive TSSs, we generated multiple random size-matched sets of TSSs, and subjected them to the same analysis. A remarkable enrichment for R2ORs was observed within ~40 kb of the TSSs of upregulated, but not downregulated, genes (Figure 4 and Supplementary Figure S4). Supplementary Table S4 lists 98 upregulated genes with nearby (<40 kb) R2ORs, presumably direct Runx2 targets.

Figure 4.
R2ORs are enriched close to TSS of upregulated genes. Analysis of the distances between the TSSs of differentially expressed genes and their respective nearest R2ORs was performed for genes whose expression changed after 24 h of Runx2 induction ...

To ascertain the functional significance of the 98 Runx2-upregulated genes with nearby R2ORs, we carried out pathway analysis using DAVID (43). The top functional pathways enriched in this gene set related to cell attachment and invasion functions (Supplementary Table S5), consistent with the established role of Runx2 in metastasis (5,14,16). In addition, DAVID analysis of the 98-gene set highlighted membrane trafficking and secretion as a potential Runx2 target pathway (Figure 5A and Supplementary Table S5). In particular, Runx2-upregulated genes with nearby R2ORs coded for enzymes that modify membrane lipids and small GTPases of the Rab family, major components of the secretory pathway (Figure 5A) (44–47). ChIP-seq results showing R2ORs near the TSSs of RAB3B, RAB43 and RAB35 are presented in Figure 5B. Validation of these R2ORs in independent ChIP experiments, as well as independent validation of Runx2-mediated upregulation of RAB3B, RAB43 and RAB35 mRNA are presented in Figure 5C and D, respectively.

Figure 5.
Evidence that Runx2 directly stimulates genes associated with membrane trafficking and secretion. (A) The 98 Runx2-upregulated genes with nearby R2ORs were analyzed using DAVID for functional annotation. Top functions with fold enrichment >5 and ...

Based on the results of the integrated analysis of Runx2 occupancy and the Runx2 transcriptome, we next asked whether Runx2 regulated protein secretion by cancer cells. C4-2B/Rx2dox cells were treated with either vehicle as control or dox to induce Runx2, and proteins in conditioned media were visualized by SDS–PAGE and Coomassie Blue staining. Compared to control cultures, conditioned medium from cells expressing Runx2 exhibited dramatically increased levels of several secreted proteins (Figure 6A). The influence of Runx2 on protein secretion was also tested in breast cancer cells. As shown in Supplementary Figure S5, Runx2 expression enhanced protein secretion by the breast cancer cell line MCF7/Rx2dox; and, Runx2 knock-down in the Runx2-positive T47D cell line inhibited protein secretion. Thus, Runx2 appears to induce a secretory phenotype in both prostate and breast cancer cells, potentially contributing to its pro-metastatic property.

Figure 6.
Runx2 increases protein secretion by PCa cells. (A) Proteins were precipitated from media conditioned by dox-treated and control C4-2B/Rx2dox cells, resolved in SDS–PAGE and stained by Coomassie Blue. Proteins in the region indicated by a bracket ...

Runx2 particularly augmented the secretion of high molecular weight proteins (Figure 6A). To identify some of them, we analyzed by mass spectrometry proteins with MW >120 kDa present in medium conditioned by dox-treated C4-2B/Rx2dox cultures (bracket in Figure 6A). Sixteen proteins were identified with 95% confidence (Supplementary Table S6). Of the respective mRNAs, only three were upregulated by Runx2 (Supplementary Table S6), and among the remaining 13 proteins, 4 of particular interest were subjected to western blot analysis. As shown in Figure 6B, fatty acid synthase (FAS), which is abundantly expressed by PCa cells and serves as a serum marker for cancer progression (48–50), was readily detectable in medium conditioned by Runx2-expressing C4-2B cells, but not in control conditioned medium. Because FAS levels were comparable between the respective cell extracts (Figure 6B), we conclude that Runx2 stimulated FAS secretion. More interestingly, the 16 proteins identified by mass spectrometry included the laminins α5 (LAMA5), β1 (LAMB1) and γ1 (LAMC1), which together constitute the laminin 511 heterotrimer, strongly implicated in cancer cell motility (51). Of these three laminins, Runx2 robustly stimulated the secretion of LAMA5 and LAMB1 while having no or little effect on the respective cellular protein levels (Figure 6B). Because LAMC1 was equally present in media from dox-treated and control cultures (Figure 6B), the data suggest that Runx2-mediated LAMA5 and LAMB1 secretion may facilitate the assembly of the metastatic laminin 511 in prostate cancer cells. In summary, bioinformatics analysis of Runx2 target genes with nearby R2ORs suggested a role in regulating protein secretion, and such a role was indeed demonstrated for several proteins, thus providing novel insight into the pro-metastatic property of Runx2.

DISCUSSION

Runx2 regulates many genes and pathways promoting metastatic properties such as invasiveness, extravasation, angiogenesis, osteolysis and drug resistance (5,14,52). The present study demonstrates a role for Runx2 in regulating protein secretion by PCa cells (Figure 6). The hypothesis that Runx2 regulates secretion was based on the association of this cellular function with a set of 98 Runx2-stimulated genes with nearby Runx2-occupied regions (R2ORs). Such hypothesis was not invoked when the Runx2 transcriptome was originally analyzed by Ingenuity Pathway Analysis (14), or when re-analyzed in this study by DAVID without regard to R2ORs (Supplementary Table S7). Interestingly, the association of Runx2-regulated genes with R2ORs was found for up- but not down-regulated genes (Figure 4 and Supplementary Figure S4). Lack of R2OR enrichment near Runx2-downregulated genes suggests that their inhibition by Runx2 is likely a secondary event.

Our ChIP-seq results for Runx2 in PCa cells share many features with those described for Runx1 in megakaryocytes and in hematopoietic progenitor cells (35,36). Both transcription factors bind mostly at regions far from gene promoters, likely enhancers that form shortcut loops to contact distant TSSs, up to hundreds of kilo-bases away. Whereas extraordinary efforts are needed to map such long-range interactions between enhancers and promoters, shorter-range interactions are suggested by the excess of R2ORs within 40 kb of TSSs of Runx2-upregulated genes. Such shorter-range interactions may be preferentially utilized by Runx2 in PCa cells to execute defined biological functions such as cell motility and protein secretion (Supplementary Table S5). It will be interesting to know if Runx1-upregulated genes with nearby Runx1-occupied regions (R1ORs) execute defined biological functions in hematopoietic progenitor cells or in megakaryocytes (35,36). Additional similarities between the Runx2 and the Runx1 ChIP-seq results relate to the DNA motifs enriched within the respective occupied regions. The motif most significantly enriched in R2ORs, YTGTGGTTW, is almost identical to that found in R1ORs in hematopoietic cells (35). Finally, both the R1ORs and the R2ORs were enriched for GATA and ETS factors, indeed both also show evidence of a Runx/Ets hybrid motif (37).

Using the dox-inducible system for Runx2 expression, we observed cyclical genomic occupancy of Runx2 (Figure 1B). It remains to be seen whether such behavior, which has been observed for ligand-activated transcription factors such as the estrogen receptor (53,54), is shared by Runx1, Runx3 or other TFs not activated by ligand. It will also be interesting to know whether the composition of Runx2-containing complexes changes between cycles of occupancy. Be that as it may, the robustness of the ChIP-seq peaks (Figures 1A and and5B)5B) is attributable in part to synchronization of Runx2 binding after dox treatment, as well as the Flag-ChIP-seq approach that mitigated the requirement for high quality antibodies against Runx2 (55–58).

Runx2 stimulated the secretion of many proteins by PCa cells, among which were the laminins α5 and ß1. Because laminin γ1 is also secreted by C4-2B/Rx2dox cells, the data suggest that Runx2 may render prostate cancer cells able to synthesize the α5β1γ1 laminin heterotrimer, also known as 511. Laminin 511 is abundant in malignant tumors, blood vessels and bone and has been implicated in guiding cancer cell metastasis as well as promoting aggression of breast, prostate and other cancer cells through activation of integrin signaling (51,59–63). Interestingly, integrin signaling is also enriched in the 98 upregulated genes with nearby R2ORs (Supplementary Table S5). Thus, via direct target genes, Runx2 may manipulate the cell microenvironment through the secretion of laminins, while augmenting cellular response through expression of the respective membrane signaling proteins.

In conclusion, Runx2 occupies sites in the PCa cell genome that are enriched for the canonical TGTGGT-containing Runx consensus motif and are usually located far from TSSs of annotated genes. A set of presumably direct Runx2-upregulated genes was identified based on proximity to R2ORs. These genes likely mediate both known and novel metastatic properties of Runx2, namely, cell motility and protein secretion.

SUPPLEMENTARY DATA

Supplementary Data are available at NAR Online: Supplementary Tables 1–7 and Supplementary Figures 1–5.

FUNDING

National Institutes of Health (NIH) (DK07112 to B.F. and CA109147 to G.A.C.). H.N. is supported by NIH training grant 5T32CA009320-27. B.F. holds the J. Harold and Edna L. LaBriola Chair in Genetic Orthopedic Research at USC. Funding for open access charge: NIH DK07112.

Conflict of interest statement. None declared.

Supplementary Material

Supplementary Data:

ACKNOWLEDGEMENTS

The authors are thankful to Charles Nicolet at the USC Epigenome Center for high throughput sequencing; to the USC High Performance Computing Center (http://www.usc.edu/hpcc/) for high performance computing support; and to Susan Lee at the Proteomics Facility of USC/Childrens Hospital Los Angeles for identification of proteins in conditioned media.

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