Anti-proliferative action of vitamin D in MCF7 is still active after siRNA-VDR knock-down
© Costa et al; licensee BioMed Central Ltd. 2009
Received: 17 June 2009
Accepted: 28 October 2009
Published: 28 October 2009
The active form of Vitamin D, 1,25-dihydroxyvitamin D3 (1,25D), has strong anti-proliferative effects, yet the molecular mechanisms underneath this effect remain unclear. In contrast, the molecular mechanism of 1,25D for the regulation of calcium homeostasis has principally been resolved, demonstrating a pivotal role for the vitamin D receptor (VDR).
We first addressed the question whether the anti-proliferative effects of 1,25D are influenced by VDR. Knockdown of VDR by siRNA did not affect the anti-proliferative effects of 1,25D in MCF7 breast cancer cells. This unanticipated finding led us to take an alternative approach using genome wide screens to study the molecular mechanisms of 1,25D in proliferation. For that purpose, four independently developed and stable 1,25D resistant MCF7 cell lines were analyzed. Array CGH identified a copy number alteration in a region of 13.5 Mb at chromosome 11q13.4-14.1 common to all four 1,25D resistant cell lines. Expression arrays revealed that no single gene was differentially expressed between the sensitive and resistant cells, but multiple membrane receptor signaling pathways were altered in the 1,25D resistant cell lines. Importantly, in the genome wide experiments neither VDR, CYP24A1 nor other known vitamin D signaling pathway genes were associated with 1,25D resistance.
In conclusion, siRNA and genome wide studies both suggest that the anti-proliferative effects of 1,25D in MCF7 breast tumor cell lines do not rely on classical Vitamin D pathway per se.
Strong anti-proliferative effects of 1,25-dihydroxyvitamin D3 (1,25D) have been demonstrated in a wide spectrum of solid cancers, in vitro and in animal models . A link between 1,25D status and cancer has also been demonstrated in epidemiological studies. Together these data lead to a number of clinical trials to test the efficacy of 1,25D or synthetic analogs . Yet, the molecular mechanisms by which the 1,25D pathway exerts its anti-proliferative effects remain unclear. There is much need for detailed knowledge of the molecular mechanism behind the anti-proliferative action of 1,25D, since calcemic side-effects form a major obstacle for the development of 1,25D or derivative drugs. Classically, 1,25D mediates the maintenance of calcium homeostasis through activation of the vitamin D receptor (VDR), a ligand dependent transcription factor. The 1,25D-VDR receptor-ligand complex functions by interacting with vitamin D response elements (VDREs) present in the promoter region of responsive genes. While many known VDRE-containing genes contribute to calcium regulation (e.g. CYP24A1, osteocalcin and osteopontin), others are involved in cellular processes like proliferation and apoptosis (e.g. p21, c-fos, and Bcl 2) [2–4]. Alternative, non-genomic pathways have been suggested to explain the anti-proliferative action of 1,25D. For example a membrane bound VDR was proposed  and other forms of signaling outside the nucleus .
In previous years, several MCF7 cell lines have been generated of which proliferation is not affected by 1,25D. Their 1,25D resistance was introduced by long time low dose or increasing dose of 1,25D [7, 8]. Notably, even when cultured in the absence of 1,25D these cell lines still persist to proliferate whenever exposed to 1,25D. This makes it reasonable to assume that the alterations that led to the resistance need to be (epi-)genetically fixed (chromosomal copy number alterations [CNAs], point-mutations, methylation). We therefore hypothesized that genome wide screens could potentially identify these (epi-)genetic changes in the absence of Vitamin D. In this study we thus utilized genome wide approaches to identify these stable alterations.
Our understanding that stable changes exist in these cell lines which underlie their response to 1,25D, prompted us to avoid the use of 1,25D. To perform this genomics study in the presence of 1,25D would identify the massive number of 1,25D downstream genes involved in proliferation and cell cycle. Indeed, there are various examples in the literature where 1,25D has been used resulting in the identification of such genes [9–13]. Although causative/driver genes may have been identified in these studies, they would be difficult to pinpoint within the massive amount of proliferative genes. Thus, omission of 1,25D in our genomic screens could potentially identify the causative/driver alterations that cause resistance in our model, whilst omitting the detection of downstream proliferative genes. Prior to these experiments we performed VDR knockdown experiments to study the role of this receptor in 1,25D anti-proliferation effect.
These experiments suggest that the anti-proliferative effects of 1,25D can either be dissociated or only require extremely low levels of the VDR in MCF7. In addition we found that structural changes on chromosome 11q13.4-14.1 may be involved in 1,25D resistance of MCF7.
Four MCF7 breast tumor cell lines and their 1,25D resistant counterparts were obtained and designated, MCF7wt1-MCF7 VDR, MCF7wt2-MCF7 DR, MCF7wt2-MCF7 DRA and MCF7wt3-MCF7 D3res . The MCF7 VDR resistant line was obtained by exposure to increasing amounts of 1,25D (0.01-10 μM), whereas MCF7 DR, MCF7 DRA and MCF7 D3res were exposed to maximal concentrations of 100 nM 1,25D for up to 12 months. All cell lines were maintained in Dulbecco's modified Eagle's medium (Invitrogen, Leek, The Netherlands), supplemented with 10% fetal bovine serum (Invitrogen), 2 mM glutamine, 100 U/l penicillin and 100 U/l streptomycin and were cultured at 37°C in a humid atmosphere consisting of 5% CO2 and 95% air. Cell proliferation was measured by the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay  (Sigma-Aldrich, Sintra, Portugal) in the presence of 1,25D 100 nM or vehicle for 72 h.
VDR knockdown by siRNA
List of primers used for Q-PCR experiments
Primers 5' → 3'
Western blot and antibodies
Protein lysates were made of cells at approximately 70-80% confluency. Cells were washed twice with PBS, lysed on ice [1% (v/v) Triton X-100 and 1% (v/v) NP-40 in desionized PBS with 1:7 proteases inhibitors cocktail], vortexed and clarified by centrifugation at 14000 × rpm for 10 min at 4°C. Protein concentration was determined using Dc protein assay (Bio-Rad, Amadora, Portugal). A total of 50 μg of total protein lysates were analyzed by 8% SDS-polyacrylamide gel electrophoresis and transferred to a Amersham Hybond ECL nitrocellulose membrane (GE Healthcare, Carnaxide, Portugal), using a Trans-Blot SD Semi-Dry Transfer Cell (Bio-Rad). Membranes were probed with the antibodies against VDR (GR37 Calbiochem, VWR, Carnaxide, Portugal) and α-tubulin (T6199 Sigma Aldrich). Quenching and immunostaining of the blots was done according to the manufacturer's instructions. Detection was done using Amersham ECL Western Blotting Detection Reagents (GE Healthcare). Immunoblots were performed at least three times, and representative figures are shown. The BioRad Quantity One 1-D Analysis Software (Bio-Rad) was used to quantify the band intensities.
Nucleic acid extractions
Cell lines were cultured in 75 cm2 flasks to 70-80% confluency and harvested using 1 ml/10 cm2 of TRIzol reagent (Invitrogen). Both RNA and DNA were extracted with TRIzol reagent according to the manufacturers' protocols. Nucleic acids were quantified using a NanoDrop ND-1000 (NanoDrop Technologies, Wilmington, USA) and quality was visually confirmed by gel electrophoresis.
Arrays and data acquisition
For expression, NMD and CGH arrays hybridizations were performed onto slides containing 60-mer oligonucleotides representing 26845 unique genes based on The Human Release 2.0 oligonucleotide library as designed by Compugen (San Jose, California, USA), and obtained from Sigma-Genosys . Following hybridization using a HybArray 12 (Perkin-Elmer, Zaventem, Belgium) the slides were scanned with a Microarray Scanner G2505B (Agilent Technologies Netherlands B.V., Amstelveen, The Netherlands). Spot analysis and quality control were fully automated using BlueFuse version 3.2 (BlueGnome, Cambridge, UK) and spots with quality flag <1 or confidence value < 0.1 were excluded from further analysis. Original data files for all arrays can be found in GEO (http://www.ncbi.nlm.nih.gov/geo/; accession numbers - GSE9867, GSE9887 and GSE9959).
Expression microarrays and analysis
A total of 14 microarray expression experiments were carried out, with four biological replicates and 10 technical replicates including dye swaps. cDNA probes were generated from 30 μg of total RNA, and experiments performed as previously described . After scanning and data acquisition, genes with spots flagged in more than one array were excluded for further analysis. For the remaining genes, the value of a flagged spot was imputed using K nearest neighbors' imputation as implemented in the R-package "impute". Curvature in the MA plots was limited but nevertheless normalized using Lowess as implemented in the R-package "MAAnova" . Using an analysis of variance (ANOVA) model, "dye", "hybridization date" and "sample" were specified as factors together with the factor of interest, "treatment" ("parental" minus "resistant"). MAAnova was used to perform ANOVA for all genes. Permutations were applied to the sample labels and uncorrected pooled p-values from the F-statistics were computed for the treatment effect. FDR corrected p-values were computed to adjust for multiple testing. PANTHER Classification System was used to statistically determine over- or under- representation of pathways http://www.pantherdb.org/.
Nonsense mediated decay arrays (NMD arrays) and analysis
Cells were incubated with the drug Emetine (Fluka), which inhibits the NMD pathway, hereby blocking the degradation of non-sense mRNAs . Approximately 4 × 106 cells at 70%-80% confluence were treated with 100 μg/ml emetine for 10 hours . Following incubation with emetine, cells were directly lyzed by the addition of TRIzol (Invitrogen) omitting any treatment with Actinomycin D. In total four hybridizations were performed (four biological replicates), one for each of the paired (MCF7 resistant vs. MCF7) emetine treated cell lines. For this reason the inclusion of a control experiments consisting of "normal" keratinocytes as suggested  was unnecessary and therefore omitted in the study. After scanning and data acquisition, spots flagged were excluded for further analysis and a distribution curve was built with the log2 ratios for the remaining genes. In typical conditions a normal distribution of the ratios is expected. By blocking the degradation of nonsense mRNAs an accumulation of genes with mutations is expected, which can be measured by a "skew" in the "normal" distribution plot towards the positive side.
Array comparative genomic hybridization (array CGH) and analysis
CGH arrays were performed as previously described . DNA from resistant and sensitive cell lines were differentially labeled and co-hybridized. For interpretation and visualization purposes, smoothing was performed using "aCGH-Smooth" , with lambda set to 3.0. Smoothed log2 ratios of -0.15 and 0.15 were used as thresholds to define gains and losses.
Quantitative PCR (Q-PCR) confirmation of siRNA and expression arrays
Gene expression was technically confirmed by Q-PCR using SYBR green chemistry. Non-redundant primers were designed and are listed in Table 1. Primer pairs were checked for linear response over a range of cDNA input and for nonspecific targets with dissociation curves. Total RNA (360 ng) was reverse-transcribed to cDNA according to the manufacturer's instructions (Multi-Scribe Reverse Transcriptase, Applied Biosystems, Nieuwerkerk aan den IJssel, The Netherlands) and subsequently used in the amplification with 10 μM gene specific primers and 12.5 μl of 2× SYBR green master mix (Applied Biosystems) in a total reaction volume of 25 μl. Reactions were carried out using standard cycle parameters on an ABI PRISM Sequence 7700 Detection System (Applied Biosystems). Relative transcript levels were determined using GAPDH as an internal reference. Statistically significant differences between resistant and sensitive cell lines were determined using comparative delta-delta Ct test . All reactions were done in triplicate and expressed as mean of the values from three separate experiments.
In silico analysis of array CGH profiles from solid breast tumors
Publicly available array CGH datasets were analyzed for the presence of alterations in the region 11q13.4-14.1. A total of four datasets corresponding to 356 individual profiles were screened [22–25]. The datasets were obtained from publicly available databases (GEO accession numbers: GSE8757 freeze March 2006, GSE6448 freeze May 2004 and ArrayExpress: E-TABM-170 freeze July 2003) and the journal website (http://www.pnas.org/content/99/20/12963/suppl/DC1, freeze October 2000). The 356 profiles included 315 breast tumors and 41 breast tumor cell lines. The CGHcall package  was used to identify alterations in the 13.5 Mb region at chromosome 11.
Proliferation in 1,25D resistant and sensitive MCF7 cell lines
Effect of VDR knockdown on 1,25D mediated proliferation inhibition
Identification of differential gene expression between 1,25D resistant and sensitive MCF7 cell lines
Selected list of genes associated with 1,25D resistance identified by expression array analysisa
Top 5 down-regulated
Family with sequence similarity 14, member A
Cytochrome P450 (Vitamin D 24-hydroxylase)
Pleckstrin homology-like domain, family A, member 1
Zinc finger protein 276
cDNA clone IMAGE:4083158
Top 5 up-regulated
SLIT and NTRK-like family, member 6
Bone morphogenetic protein 7
cDNA clone IMAGE:4417140
DNA-damage-inducible transcript 4
Cytoplasmic FMR1 interacting protein 2
Forkhead box C1
Cellular retinoic acid binding protein 2
GalNAc alpha-2,6-sialyltransferase V
NUAK family, SNF1-like kinase, 1
Vitamin D receptor
VDR signaling pathway is not identified by expression arrays on the 1,25D resistant cell lines
Pathways associated with 1,25D resistance identified using Panther Ontology gene enrichment analysis
B cell activation
EGF receptor signaling pathway
PDGF signaling pathway
Interleukin signaling pathway
FGF signaling pathway
Toll receptor signaling pathway
Genes present in at least three of the significant pathways identified
Panther Ontology Pathway
Nonsense mutations were not identified in 1,25D resistant cell lines
Nonsense mediated decay (NMD) analysis was performed to identify genes that might have undergone mutational events related to the 1,25D resistance phenotype. Resistant and sensitive cell lines were treated with emetine to block degradation of nonsense RNAs. Hybridizations were performed of resistant vs. sensitive emetine treated cell lines such that all 4 biological replicates were hybridized on a total of 4 arrays. The results indicated that no genes were recurrent in the biological replicates. In addition, the top positive log2 ratio was similar to the top negative log2 ratio. Visualization of all log2 ratios further revealed a normal distribution of the data around zero with no gene that stood out to the positive side of the curve. Thus, overall this data did not support the concept that the 1,25D resistant cell lines shared one or more common mutated genes.
Resistant cell lines exhibit copy number reduction of chromosome 11q13.4-14.1
The molecular mechanisms underlying the anti-proliferative effects of 1,25D are poorly understood, despite the well known role of 1,25D in the regulation of calcium homeostasis. In this study we show that the anti-proliferative effects of 1,25D may be functional in MCF7 breast tumor cell lines, without a role for the central player in calcium homeostasis, VDR. These results were unanticipated since several known regulators of cell growth, such as p21 and GADD45A, contain functional VDREs in their promoter region and are induced by the 1,25D-VDR complex in cancer cells [35, 36]. Furthermore, cell lines derived from VDR knockout (KO) mice are resistant to 1,25D mediated growth arrest , and re-introduction of VDR into these cells restores sensitivity to 1,25D mediated growth inhibition (Keith and Welsh, unpublished). While additional studies are needed to determine whether residual VDR activity in the MCF7 cells expressing VDR-siRNA is sufficient to mediate growth inhibitory signals upon binding 1,25D, our data demonstrates that marked reductions (~90% at the transcript level and ~85% at the protein level) in VDR do not necessarily induce 1,25D resistance. Seemingly contradictive to the role of VDR, this finding is consistent with previous data from MCF7 sub-lines selected in vitro for resistance to 1,25D, in which VDR function is retained [7, 8], indicating dissociation between VDR expression and 1,25D mediated growth inhibition.
In the light of these results, we hypothesized that driver/causative genes other than VDR, or alternative pathways unrelated to vitamin D calcium signaling might impact 1,25D sensitivity or replace its function. Therefore we used genome wide screens to identify genetic alterations that cause resistance in our model. Indeed, in all four 1,25D resistant cell lines one common chromosomal region had reduced copy number at 11q13.4-14.1 (Figure 3). Eighty genes are present in this 13.5 Mb chromosomal region, none of which could readily be assigned to 1,25D mediated VDR signaling. In focally aberrant regions (<3 Mb) identification of driver genes is often straight forward, but it is our experience , acknowledged by others  that identification of candidate genes in larger chromosomal regions is problematic. One effort made was integration with our expression array data which did not proof helpful; hence pathway analysis of genes in this region would be arbitrary. Other authors performed similar array experiments in the presence of 1,25D, yet again none of the 80 genes in this region was identified [9–13]. Our expression array analysis confirmed that 1,25D resistant cells did not exhibit significant reductions in VDR gene expression. Still, as described previously the VDR-transcriptome may be significantly altered . Indeed, these authors showed that CYP24A1 was the only induced gene that was common to the genetic profiles of the parental and the 1,25D resistant cell lines when treated with 1,25D treated . In contrast, our expression array analysis identified CYP24A1 as one of the top five down-regulated genes in the 1,25D resistant MCF7 cell lines. Since CYP24A1 is strongly regulated by 1,25D in a negative feed-back, but no 1,25D was present in our test, any discussion on this apparent down-regulation remains speculative.
Pathway analysis of the expression arrays did not identify any other known vitamin D pathway genes either. Instead, over-representation of multiple membrane receptor signaling pathways known to be involved in the control of proliferation and apoptosis were associated with the 1,25D resistant phenotype. The five membrane-bound receptor signaling pathways identified in our analysis share the Grb2 and SOS genes and drive cell proliferation. Interestingly, previous analysis of one set of these sub-lines indicated that, in the absence of 1,25D, the doubling time of the MCF7 D3res cells was shorter than that of the MCF7 sensitive cells from which they were derived . Furthermore, using proteomic approaches we previously identified several proteins in the MAPK-ERK-RAS mitogenic pathway that were differentially expressed in the MCF7 D3res cells relative to their sensitive MCF7 counterparts under basal conditions . Although mechanisms have yet to be clarified, chronic up-regulation of these mitogenic pathways may selectively disable VDR signaling, leading to 1,25D resistance. In support of this idea, RAS activation has been shown to induce 1,25D resistance in keratinocytes via direct phosphorylation of VDR .
In a previous study we used the same genome wide tools to identify the mechanisms of Gemcitabine resistance . Results were simple and straightforward to interpret; Gemcitabine had selected for tumor cells with high level amplifications, leading to high expression levels of genes within that amplicon which resulted in drug resistance . Here a similar simple mechanism for 1,25D resistance was not identified. A possible explanation may be that most therapeutic drugs (e.g. Gemcitabine) are synthetic and 1,25D is generated endogenously. Consequently, malignant cells would need to develop resistance to the anti-proliferative effects of 1,25D in a very early stage of their development to allow tumor expansion. Accordingly, we hypothesized that many solid tumors would also contain alterations at 11q13.4-14.1. Indeed, screening of four datasets covering 358 individual array CGH profiles showed that the region in chromosome 11q13.4-14.1 is highly unstable strengthening this hypothesis.
Evidence accumulates demonstrating an important role for Vitamin D not only in the treatment but also in the prevention of cancer, mainly breast cancer. Dozens of vitamin D analogues have been developed by pharmaceutical firms with the goal of dissociating the potentially toxic calcemic actions of 1,25D from its anti-tumor actions for use in cancer therapy. Because vitamin D analogs are currently in approximately 20 clinical trials , understanding the mechanisms by which 1,25D mediates growth inhibition, as well as the basis for development of 1,25D resistance, is crucial. Our genome wide screening analysis has identified chromosomal regions, membrane receptor pathways and new candidate genes outside of the classical VDR signaling pathway that may be associated with 1,25D resistance. These data provide new avenues for future explorations that may facilitate the development and use of vitamin D based drugs for cancer and other clinical applications.
Solvay Pharmaceuticals B.V. (Weesp, The Netherlands) is thanked for kindly providing 1,25D and Leo Pharmaceutical Products (Ballerup, Denmark) for providing their 1,25D resistant cell line MCF7/VDR.
This work was supported by the Fundação para a Ciência e Tecnologia (grant numbers SFRH/BPD/20370/2004 and PIC/IC/83264/2007); a grant of the Centre for Medical Systems Biology (NL); and the National Institutes of Health (USA grant number #CA69700).
- Masuda S, Jones G: Promise of vitamin D analogues in the treatment of hyperproliferative conditions. Molecular Cancer Therapeutics. 2006, 5 (4): 797-808. 10.1158/1535-7163.MCT-05-0539.View ArticlePubMedGoogle Scholar
- Deeb KK, Trump DL, Johnson CS: Vitamin D signalling pathways in cancer: potential for anticancer therapeutics. Nature Reviews in Cancer. 2007, 7 (9): 684-700. 10.1038/nrc2196.View ArticleGoogle Scholar
- Dusso AS, Brown AJ, Slatopolsky E: Vitamin D. American Journal of Physiology - Renal Physiology. 2005, 289 (1): F8-28. 10.1152/ajprenal.00336.2004.View ArticlePubMedGoogle Scholar
- Haussler MR, Whitfield GK, Haussler CA, Hsieh JC, Thompson PD, Selznick SH, Dominguez CE, Jurutka PW: The nuclear vitamin D receptor: biological and molecular regulatory properties revealed. Journal of Bone and Mineral Research. 1998, 13 (3): 325-349. 10.1359/jbmr.1922.214.171.1245.View ArticlePubMedGoogle Scholar
- Norman AW, Mizwicki MT, Norman DP: Steroid-hormone rapid actions, membrane receptors and a conformational ensemble model. Nature Reviews Drug Discovery. 2004, 3 (1): 27-41. 10.1038/nrd1283.View ArticlePubMedGoogle Scholar
- Gniadecki R: Nongenomic signaling by vitamin D: a new face of Src. Biochemical Pharmacology. 1998, 56 (10): 1273-1277. 10.1016/S0006-2952(98)00182-8.View ArticlePubMedGoogle Scholar
- Hansen CM, Rohde L, Madsen MW, Hansen D, Colston KW, Pirianov G, Holm PK, Binderup L: MCF-7/VD(R): a new vitamin D resistant cell line. Journal of Cell Biochemistry. 2001, 82 (3): 422-436. 10.1002/jcb.1162.View ArticleGoogle Scholar
- Narvaez CJ, VanWeelden K, Byrne I, Welsh J: Characterization of a vitamin D3-resistant MCF-7 cell line. Endocrinology. 1996, 137 (2): 400-409. 10.1210/en.137.2.400.PubMedGoogle Scholar
- Byrne B, Welsh J: Identification of novel mediators of Vitamin D signaling and 1,25(OH)2D3 resistance in mammary cells. Journal of Steroid Biochemistry and Molecular Biology. 2007, 103 (3-5): 703-707. 10.1016/j.jsbmb.2006.12.061.PubMed CentralView ArticlePubMedGoogle Scholar
- Palmer HG, Sanchez-Carbayo M, Ordonez-Moran P, Larriba MJ, Cordon-Cardo C, Munoz A: Genetic signatures of differentiation induced by 1alpha,25-dihydroxyvitamin D3 in human colon cancer cells. Cancer Research. 2003, 63 (22): 7799-7806.PubMedGoogle Scholar
- Swami S, Raghavachari N, Muller UR, Bao YP, Feldman D: Vitamin D growth inhibition of breast cancer cells: gene expression patterns assessed by cDNA microarray. Breast Cancer Research and Treatment. 2003, 80 (1): 49-62. 10.1023/A:1024487118457.View ArticlePubMedGoogle Scholar
- Towsend K, Trevino V, Falciani F, Stewart PM, Hewison M, Campbell MJ: Identification of VDR-responsive gene signatures in breast cancer cells. Oncology. 2006, 71 (1-2): 111-123. 10.1159/000100989.View ArticlePubMedGoogle Scholar
- Wang TT, Tavera-Mendoza LE, Laperriere D, Libby E, MacLeod NB, Nagai Y, Bourdeau V, Konstorum A, Lallemant B, Zhang R, et al: Large-scale in silico and microarray-based identification of direct 1,25-dihydroxyvitamin D3 target genes. Mol Endocrinol. 2005, 19 (11): 2685-2695. 10.1210/me.2005-0106.View ArticlePubMedGoogle Scholar
- Peter R, Dirk P, Christian H, Yves C: A new, rapid colorimetric assay for quantitative determination of cellular proliferation, growth inhibition, and viability. Methods in Cell Science. 1993, 15 (1): 37-41.Google Scholar
- Ijssel van den P, Tijssen M, Chin SF, Eijk P, Carvalho B, Hopmans E, Holstege H, Bangarusamy DK, Jonkers J, Meijer GA, et al: Human and mouse oligonucleotide-based array CGH. Nucleic Acids Research. 2005, 33 (22): e192-10.1093/nar/gni191.PubMed CentralView ArticlePubMedGoogle Scholar
- Muris JJ, Ylstra B, Cillessen SA, Ossenkoppele GJ, Kluin-Nelemans JC, Eijk PP, Nota B, Tijssen M, de Boer WP, Wiel van de M, et al: Profiling of apoptosis genes allows for clinical stratification of primary nodal diffuse large B-cell lymphomas. British Journal of Haematology. 2007, 136 (1): 38-47. 10.1111/j.1365-2141.2006.06375.x.View ArticlePubMedGoogle Scholar
- Kerr MK, Martin M, Churchill GA: Analysis of variance for gene expression microarray data. Journal of Computational Biology. 2000, 7 (6): 819-837. 10.1089/10665270050514954.View ArticlePubMedGoogle Scholar
- Cho RJ, Campbell MJ: Transcription, genomes, function. Trends in Genetics. 2000, 16 (9): 409-415. 10.1016/S0168-9525(00)02065-5.View ArticlePubMedGoogle Scholar
- Huusko P, Ponciano-Jackson D, Wolf M, Kiefer JA, Azorsa DO, Tuzmen S, Weaver D, Robbins C, Moses T, Allinen M, et al: Nonsense-mediated decay microarray analysis identifies mutations of EPHB2 in human prostate cancer. Nature Genetics. 2004, 36 (9): 979-983. 10.1038/ng1408.View ArticlePubMedGoogle Scholar
- Jong K, Marchiori E, Meijer G, Vaart AV, Ylstra B: Breakpoint identification and smoothing of array comparative genomic hybridization data. Bioinformatics. 2004, 20 (18): 3636-3637. 10.1093/bioinformatics/bth355.View ArticlePubMedGoogle Scholar
- Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001, 25 (4): 402-408. 10.1006/meth.2001.1262.View ArticlePubMedGoogle Scholar
- Chin SF, Wang Y, Thorne NP, Teschendorff AE, Pinder SE, Vias M, Naderi A, Roberts I, Barbosa-Morais NL, Garcia MJ, et al: Using array-comparative genomic hybridization to define molecular portraits of primary breast cancers. Oncogene. 2007, 26 (13): 1959-1970. 10.1038/sj.onc.1209985.View ArticlePubMedGoogle Scholar
- Pollack JR, Sorlie T, Perou CM, Rees CA, Jeffrey SS, Lonning PE, Tibshirani R, Botstein D, Borresen-Dale AL, Brown PO: Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proceedings of the National Academy of Sciences. 2002, 99 (20): 12963-12968. 10.1073/pnas.162471999.View ArticleGoogle Scholar
- Fridlyand J, Snijders AM, Ylstra B, Li H, Olshen A, Segraves R, Dairkee S, Tokuyasu T, Ljung BM, Jain AN, et al: Breast tumor copy number aberration phenotypes and genomic instability. BMC Cancer. 2006, 6: 96-10.1186/1471-2407-6-96.PubMed CentralView ArticlePubMedGoogle Scholar
- Climent J, Dimitrow P, Fridlyand J, Palacios J, Siebert R, Albertson DG, Gray JW, Pinkel D, Lluch A, Martinez-Climent JA: Deletion of chromosome 11q predicts response to anthracycline-based chemotherapy in early breast cancer. Cancer Research. 2007, 67 (2): 818-826. 10.1158/0008-5472.CAN-06-3307.View ArticlePubMedGoogle Scholar
- Wiel van de MA, Kim KI, Vosse SJ, van Wieringen WN, Wilting SM, Ylstra B: CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics. 2007, 23 (7): 892-894. 10.1093/bioinformatics/btm030.View ArticlePubMedGoogle Scholar
- Losel R, Wehling M: Nongenomic actions of steroid hormones. Nature Reviews Molecular Cell Biology. 2003, 4 (1): 46-56. 10.1038/nrm1009.View ArticlePubMedGoogle Scholar
- Ly LH, Zhao XY, Holloway L, Feldman D: Liarozole acts synergistically with 1alpha,25-dihydroxyvitamin D3 to inhibit growth of DU 145 human prostate cancer cells by blocking 24-hydroxylase activity. Endocrinology. 1999, 140 (5): 2071-2076. 10.1210/en.140.5.2071.PubMedGoogle Scholar
- Albertson DG, Ylstra B, Segraves R, Collins C, Dairkee SH, Kowbel D, Kuo WL, Gray JW, Pinkel D: Quantitative mapping of amplicon structure by array CGH identifies CYP24 as a candidate oncogene. Nature Genetics. 2000, 25 (2): 144-146. 10.1038/75985.View ArticlePubMedGoogle Scholar
- Costa JL, Meijer G, Ylstra B, Caldas C: Array comparative genomic hybridization copy number profiling: a new tool for translational research in solid malignancies. Seminars in Radiation Oncology. 2008, 18 (2): 98-104. 10.1016/j.semradonc.2007.10.005.View ArticlePubMedGoogle Scholar
- Jong K, Marchiori E, Vaart van der A, Chin SF, Carvalho B, Tijssen M, Eijk PP, Ijssel van den P, Grabsch H, Quirke P, et al: Cross-platform array comparative genomic hybridization meta-analysis separates hematopoietic and mesenchymal from epithelial tumors. Oncogene. 2007, 26 (10): 1499-1506. 10.1038/sj.onc.1209919.View ArticlePubMedGoogle Scholar
- Wiel van de MA, Costa JL, Smid K, Oudejans CB, Bergman AM, Meijer GA, Peters GJ, Ylstra B: Expression microarray analysis and oligo array comparative genomic hybridization of acquired gemcitabine resistance in mouse colon reveals selection for chromosomal aberrations. Cancer Research. 2005, 65 (22): 10208-10213. 10.1158/0008-5472.CAN-05-0760.View ArticlePubMedGoogle Scholar
- Buffart TE, Israeli D, Tijssen M, Vosse SJ, Mrsic A, Meijer GA, Ylstra B: Across array comparative genomic hybridization: A strategy to reduce reference channel hybridizations. Genes Chromosomes and Cancer. 2008, 47 (11): 994-1004. 10.1002/gcc.20605.View ArticlePubMedGoogle Scholar
- Taylor TD, Noguchi H, Totoki Y, Toyoda A, Kuroki Y, Dewar K, Lloyd C, Itoh T, Takeda T, Kim DW, et al: Human chromosome 11 DNA sequence and analysis including novel gene identification. Nature. 2006, 440 (7083): 497-500. 10.1038/nature04632.View ArticlePubMedGoogle Scholar
- Liu M, Lee MH, Cohen M, Bommakanti M, Freedman LP: Transcriptional activation of the Cdk inhibitor p21 by vitamin D3 leads to the induced differentiation of the myelomonocytic cell line U937. Genes and Development. 1996, 10 (2): 142-153. 10.1101/gad.10.2.142.View ArticlePubMedGoogle Scholar
- Jiang F, Li P, Fornace AJ, Nicosia SV, Bai W: G2/M arrest by 1,25-dihydroxyvitamin D3 in ovarian cancer cells mediated through the induction of GADD45 via an exonic enhancer. Journal of Biological Chemistry. 2003, 278 (48): 48030-48040. 10.1074/jbc.M308430200.View ArticlePubMedGoogle Scholar
- Zinser GM, McEleney K, Welsh J: Characterization of mammary tumor cell lines from wild type and vitamin D3 receptor knockout mice. Molecular and Cellular Endocrinology. 2003, 200 (1-2): 67-80. 10.1016/S0303-7207(02)00416-1.View ArticlePubMedGoogle Scholar
- Carvalho B, Postma C, Mongera S, Hopmans E, Diskin S, Wiel van de MA, van Criekinge W, Thas O, Matthai A, Cuesta MA, et al: Multiple putative oncogenes at the chromosome 20q amplicon contribute to colorectal adenoma to carcinoma progression. Gut. 2009, 58 (1): 79-89. 10.1136/gut.2007.143065.View ArticlePubMedGoogle Scholar
- Leary RJ, Lin JC, Cummins J, Boca S, Wood LD, Parsons DW, Jones S, Sjoblom T, Park BH, Parsons R, et al: Integrated analysis of homozygous deletions, focal amplifications, and sequence alterations in breast and colorectal cancers. Proceedings of the National Academy of Sciences. 2008, 105 (42): 16224-16229. 10.1073/pnas.0808041105.View ArticleGoogle Scholar
- Solomon C, Kremer R, White JH, Rhim JS: Vitamin D resistance in RAS-transformed keratinocytes: mechanism and reversal strategies. Radiation Research. 2001, 155 (1 Pt 2): 156-162. 10.1667/0033-7587(2001)155[0156:VDRIRT]2.0.CO;2.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.