VDR mRNA overexpression is associated with worse prognostic factors in papillary thyroid carcinoma

in Endocrine Connections

The purpose of this study was to assess the relationship between vitamin D receptor gene (VDR) expression and prognostic factors in papillary thyroid cancer (PTC). mRNA sequencing and somatic mutation data from The Cancer Genome Atlas (TCGA) were analyzed. VDR mRNA expression was compared to clinicopathologic variables by linear regression. Tree-based classification was applied to find cutoff and patients were split into low and high VDR group. Logistic regression, Kaplan–Meier analysis, differentially expressed gene (DEG) test and pathway analysis were performed to assess the differences between two VDR groups. VDR mRNA expression was elevated in PTC than that in normal thyroid tissue. VDR expressions were high in classic and tall-cell variant PTC and lateral neck node metastasis was present. High VDR group was also associated with classic and tall cell subtype, AJCC stage IV and lower recurrence-free survival. DEG test reveals that 545 genes were upregulated in high VDR group. Thyroid cancer-related pathways were enriched in high VDR group in pathway analyses. VDR mRNA overexpression was correlated with worse prognostic factors such as subtypes of papillary thyroid carcinoma that are known to be worse prognosis, lateral neck node metastasis, advanced stage and recurrence-free survival.

Abstract

The purpose of this study was to assess the relationship between vitamin D receptor gene (VDR) expression and prognostic factors in papillary thyroid cancer (PTC). mRNA sequencing and somatic mutation data from The Cancer Genome Atlas (TCGA) were analyzed. VDR mRNA expression was compared to clinicopathologic variables by linear regression. Tree-based classification was applied to find cutoff and patients were split into low and high VDR group. Logistic regression, Kaplan–Meier analysis, differentially expressed gene (DEG) test and pathway analysis were performed to assess the differences between two VDR groups. VDR mRNA expression was elevated in PTC than that in normal thyroid tissue. VDR expressions were high in classic and tall-cell variant PTC and lateral neck node metastasis was present. High VDR group was also associated with classic and tall cell subtype, AJCC stage IV and lower recurrence-free survival. DEG test reveals that 545 genes were upregulated in high VDR group. Thyroid cancer-related pathways were enriched in high VDR group in pathway analyses. VDR mRNA overexpression was correlated with worse prognostic factors such as subtypes of papillary thyroid carcinoma that are known to be worse prognosis, lateral neck node metastasis, advanced stage and recurrence-free survival.

Introduction

Thyroid carcinoma is the most common endocrine malignancy worldwide, the incidence of which is increasing. The most common subtype of thyroid carcinoma is papillary carcinoma (PTC), accounting for 80–90% of all cases (1). Although this type of cancer has an excellent prognosis, the prognosis significantly worsens when the tumor grows and metastasizes (2). For this reason, it is important to understand the characteristics of the tumor at the early stage.

Several epidemiological reports show that higher levels of vitamin D3 are associated with a lower risk of developing cancer (3). The active form of vitamin D3, 1,25-dihydroxyvitamin D3 (1,25D) exerts antitumor activity by binding to the vitamin D receptor (VDR). The antitumor activities of 1,25D include the inhibition of cancer cell proliferation and angiogenesis, promotion of cell differentiation and apoptosis (4, 5, 6, 7, 8).

The VDR is a receptor expressed by epithelial cells in both normal and malignant thyroid glands. Human VDR gene is located on chromosome 12q13.1 (9). In cancer cells, VDR expression is a response to 1,25-dihydroxyvitamin D3 (1,25D) by decreasing proliferative activity in vitro. Izkhakov and coworkers reported that expression of VDR mRNA in malignant thyroid tissues is higher than that in normal thyroid (2). They also reported correlations between VDR and other genes such as ECM1 (extracellular matrix protein-1) and TMPRSS4 (type II transmembrane serine protease-4), which are associated with tumor progression. Positive correlation was also observed between VDR and ECM1, as well as between VDR and TMPRSS4 (2).

Our study was designed to evaluate the correlation between the VDR mRNA expression and prognostic factors of PTC using ‘The Cancer Genome Atlas’ (TCGA) data. TCGA kindly provides multiplatform genomics data such as sequence and read count data from next-generation sequencing, copy-number analysis, methylomics and proteomics data (10). Genomic data were also combined with patient-matched clinical data to correlate the molecular findings with clinical characteristics.

Materials and methods

Data preparation

We downloaded TCGA thyroid cancer data, including clinical information, somatic mutations and gene expression data derived from RNA sequencing. Pathologic data were re-evaluated using scanned images of the paper-written pathologic documents provided by TCGA-associated hospitals. PTC subtype classification and MACIS scores were referenced from the 2014 TCGA thyroid cancer paper’s Supplemental Tables (10). The total number of TCGA samples comprised 59 normal tissues and 501 cancer tissues. Total 499 patient samples were assessed after joining the clinical data without missing attributes.

Somatic mutations were provided by two different mutation calling files from the Illumina DNA-sequencing machine. Sequencing experiments were performed by the Baylor College of Medicine, the Broad Institute at MIT and Harvard Genome Sequencing Center. Mutation status of BRAF, RAS (NRAS, HRAS and KRAS) and VDR genes was identified from somatic mutation calling files: identical results in two different calling files were considered as a meaningful mutation.

TCGA gene expression data from RNA sequencing were provided with level 3 RSEM (RNA-Seq by expectation–maximization) counts after upper quartile normalization to maintain the standardization of different platforms or housekeeping genes (https://wiki.nci.nih.gov/). RNA sequencing was performed by the University of North Carolina using an Illumina HiSeq RNA Sequencing machine. We analyzed VDR gene expression according to tissue type (normal vs cancer) and clinical information. Next, all 20,531 genes were used to assess gene ontology and pathway analysis.

Statistical analysis

Paired t-test was used to assess the differences in gene expression between 59 paired donor-matched normal and cancer samples, whereas unpaired t-test was used to assess the global differences between the 59 normal tissues and 499 cancer tissues. Association between clinical variables and VDR gene expression was measured by univariable and multivariable linear regression analysis. To predict cancer recurrence based on VDR expression, continuous VDR expressions was converted into two binary groups (low VDR and high VDR group) using tree-based classification analysis with a maximized area under the ROC (receiver-operating characteristic) curve. Binary VDR groups were used for univariable and multivariable logistic regression analyses to assess the relationship between VDR expression and clinicopathologic variables. Backward selection method was used in both linear and logistic regression for multiple model fitting. Kaplan–Meier estimator with log-rank test was used for survival analysis.

Differentially expressed genes (DEG) and gene ontology (GO) tests between two VDR groups were performed using ‘EdgeR’ package, which is one of the bioinformatics tools in Bioconductor (https://www.bioconductor.org/) (11). Pathway enrichment analysis was performed using The Database for Annotation, Visualization and Integrated Discovery (DAVID) (12, 13) and the Gene Set Enrichment Analysis (GSEA) program (14). False discovery rate (FDR) correction was used to adjust false-positive rate from multiple testing. All statistical analyses were performed using R 3.2.4. (R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/).

Results

No VDR gene single-nucleotide variants were observed in either of the two different mutation calling files. Figure 1 shows the difference in VDR mRNA expression between normal and PTC tissues. Both paired and unpaired tests revealed that VDR expression was higher in cancer tissue than that in normal tissue (VDR expression in 55 normal tissues = 238.971 ± 14.987; in 55 paired cancer tissues = 307.567 ± 26.808; in 501 cancer tissues = 395.276 ± 10.323, mean ± standard error of mean (s.e.m.)).

Figure 1

Download Figure

Figure 1

VDR mRNA expression counts in normal and papillary thyroid carcinoma tissue. (A) Fifty-nine paired normal and cancer tissues. (B) 59 normal vs 501 cancer tissues.

Citation: Endocrine Connections 6, 3; 10.1530/EC-17-0001

Correlations of VDR mRNA expression according to clinicopathologic variables are shown in Table 1. VDR gene expression was higher with statistical significance in classic and tall-cell variant PTC (TCVPTC) than that in follicular variant PTC (FVPTC). VDR expression was also significantly upregulated in cases with T4 (tumor stage), N1b (lateral neck node metastasis), high MACIS group and AJCC stage IV. Gender, PTC subtype and N stage were only included in multiple linear regression model. The results also showed an association between VDR expression with BRAFV600E mutation and recurrence, although the results did not reach statistical significance.

Table 1

Association between VDR mRNA expression and clinicopathologic characteristics of 499 PTC patients by linear regression analysis.

VariableNumberMean ± s.e.m.P value (univariate)P value (multivariate)
Age<45228390.989 ± 14.2570.669
≥45271399.888 ± 14.838
GenderM134372.818 ± 17.5390.1790.058
F365404.267 ± 12.590
SubtypeClassic PTC355408.001 ± 12.670ReferenceReference
FVPTC101318.546 ± 19.165<0.0010.009
TCVPTC35494.194 ± 32.0230.0330.059
Others8400.611 ± 98.3830.9280.955
Size≤2 cm200399.179 ± 15.8650.791
>2 cm299393.576 ± 13.657
Lymphovascular invasionNo392393.643 ± 11.8270.688
Yes107403.803 ± 21.394
T stageT1144377.999 ± 17.633Reference
T2154382.805 ± 20.7370.858
T3184411.481 ± 16.1510.193
T417495.216 ± 61.7360.048
N stageN0278363.768 ± 12.188ReferenceReference
N1a120410.893 ± 23.8580.0590.381
N1b101466.142 ± 24.895<0.0010.002
M stageM0490396.254 ± 10.4940.759
M19372.300 ± 58.740
MACISLow345386.576 ± 12.243Reference
Intermediate78383.270 ± 24.0770.909
High76450.675 ± 29.9090.029
StageI289379.548 ± 12.535Reference
II44367.811 ± 35.5990.753
III98410.995 ± 26.2920.243
IV68461.242 ± 30.2430.009
BRAF mutationNo258378.672 ± 15.039Reference
V600E236415.103 ± 14.2990.081
Others5370.710 ± 82.3870.939
RAS mutationNo446399.870 ± 11.1870.257
Yes53361.755 ± 25.071
RecurrenceNo459390.370 ± 10.9050.0750.155
Yes40458.378 ± 30.682
SurvivalAlive485394.442 ± 10.4220.433
Dead14443.627 ± 78.110

Follicular variant PTC; tall cell variant PTC.

To predict recurrence using VDR gene expression, we divided continuous VDR expression values into binary variables using the tree-based classification and ROC curve. Optimal VDR cutoff value obtained was 466.5, with a maximal AUC of 0.624. Based on the cutoff, patients were divided into a low VDR group and a high VDR group. Low VDR group comprised 342 patients and high VDR group comprised 157 patients. Table 2 shows the logistic regression results according to binary VDR group. Both the univariable and multivariable regression models revealed that high VDR group was associated with classic PTC and TCVPTC, advanced AJCC stage (stage IV) and recurrence.

Table 2

Logistic regression analysis using binary VDR mRNA expression (cutoff value = 466.5; AUC = 0.624; low VDR group, n = 342; high VDR group, n = 157).

VariablesUnivariateMultivariate
Odds ratioP valueOdds ratioP value
Age (<45)≥451.1080.597
Gender (M)Female1.0570.801
Subtype (classic)FVPTC0.5150.0160.5760.051
TCVPTC2.7830.0042.5400.013
Others0.6960.6600.7640.747
Size (≤2 cm)>2 cm0.9230.683
Lymphovascular invasion (No)Yes1.2630.309
T stage (T1)T20.8230.458
T31.5070.086
T42.8260.046
N stage (N0)N1a1.4310.128
N1b1.9620.006
M stage (M0)M11.0910.903
MACIS (low)Intermediate1.1560.592
High1.7820.027
Stage (I)II0.6490.2750.8070.596
III1.3410.2391.0800.772
IV2.2440.0031.9250.020
BRAF mutation (No)V600E1.3490.123
Others1.6890.570
RAS mutation (No)Yes0.5380.080
Recurrence (No)Yes2.6250.0042.3290.014
Survival (alive)Dead1.2170.729

Total 40 patients showed recurrence after surgery. 21 patients had locoregional recurrence including central and lateral neck nodes, whereas 15 patients had distant recurrence such as bone, lung, etc. There is no information for four patients. In high VDR group, 11 patients had locoregional and six patients had distant recurrence (P value from Fisher’s exact test = 0.002). Figure 2 illustrates recurrence-free survival difference for two VDR groups using the Kaplan–Meier estimator. The high VDR group showed worse recurrence-free survival than the low VDR group (P value = 0.018, follow-up duration: median 647 days, range 1–5150 days). There’s no statistical significance in overall survival between the two VDR groups.

Figure 2

Download Figure

Figure 2

Recurrence-free survival in the low and high VDR expression groups.

Citation: Endocrine Connections 6, 3; 10.1530/EC-17-0001

We performed DEG tests for the low and high VDR groups using EdgeR package. The differential gene expression pattern is shown in Fig. 3. DEG boundaries were defined as follows: average log CPM (counts per million) >0 and | logFC (fold change) | >1, and FDR q-value <0.01 (indicated as vertical and horizontal lines in Fig. 3). A total of 545 genes were highly expressed in high VDR group, whereas 91 genes were highly expressed in low VDR group. Table 3 lists the top 20 highly expressed DEGs in high VDR group.

Figure 3

Download Figure

Figure 3

MA plot of genes differentially expressed in the low and high VDR expression groups. DEG cutoff consisted of average logCPM (count per million) >0, | logFC (fold change) | >1 and FDR q-value <0.01.

Citation: Endocrine Connections 6, 3; 10.1530/EC-17-0001

Table 3

Top 20 upregulated genes in the high VDR group.

Gene IDGene symbollogFClogCPMP valueFDR
7421VDR1.2824.3122.61E-1494.39E-145
165904XIRP14.1000.5243.83E-933.22E-89
256076COL6A56.0880.7554.51E-922.53E-88
57016AKR1B107.4362.4831.73E-867.27E-83
1646AKR1C24.0523.3931.47E-784.95E-75
2877GPX25.0530.2964.00E-771.12E-73
146802SLC47A23.1991.0981.38E-593.32E-56
8038ADAM122.4293.2503.35E-567.05E-53
8111GPR681.8682.1994.08E-536.24E-50
729238SFTPA24.1754.5879.36E-531.31E-49
10468FST2.8230.5791.06E-511.37E-48
1281COL3A12.0489.3474.38E-504.91E-47
6947TCN14.2531.2949.78E-501.03E-46
1278COL1A21.8949.4902.00E-481.87E-45
1293COL6A31.7617.4593.02E-482.67E-45
3909LAMA32.2892.6711.02E-478.32E-45
92747BPIFB14.5290.5661.04E-478.32E-45
10699CORIN1.8360.2841.21E-479.22E-45
1462VCAN2.0825.7406.74E-474.93E-44
10631POSTN2.1606.8671.07E-467.52E-44

Supplementary Table 1 (see section on supplementary data given at the end of this article) shows the pathways that are significantly enriched by 545 upregulated DEGs in high VDR group, using DAVID. Cellular interaction, autoimmune thyroid disease, immune receptor-related signal pathways, cancer-related chemokine signaling and the JAK-STAT pathway were significantly enriched in high VDR group. The GSEA pathway analysis showed similar results: chemokine signaling, immune cell-related pathways, cell adhesion, cellular interactions and the JAK-STAT pathway, all of which are associated with carcinogenesis, were significantly enriched in the high VDR group compared to low VDR group (Supplementary Table 2). The ‘chemokine signaling pathway’ that was enriched in both DAVID and GSEA analysis harbors thyroid cancer related ‘MAPK signaling pathway’ composed with RAS-RAF-MEK-ERK1/2 cascade.

GO analysis conducted with EdgeR also showed increased immune-related biological processes, enrichment of cell membrane components and upregulation of receptor signaling activity in the high VDR group. Top 10 enriched gene ontologies in high VDR group are listed in Supplementary Table 3.

Discussion

Although most thyroid carcinomas have a good prognosis, some types of cancer have intractable features and a significantly unfavorable prognosis. Current prognosis and treatment guidelines are based on clinicopathologic data. Recently, additional information using immunohistochemistry and molecular methods was introduced to improve the sensitivity and specificity of the diagnosis and to predict disease prognosis. Molecular markers such as BRAF, RAS, RET/PTC rearrangement, RAX8/PPARγ and galectin-3 may be useful for these purposes according to the American Thyroid Association guidelines (15).

The hallmark of thyroid cancer, besides aggressive behavior, is a loss of uptake and trapping of radioactive iodine, which means resistance to the best systemic therapy for thyroid cancer. The standard chemotherapy regimens approved for thyroid cancer have poor efficacy and relatively high toxicity compared to their benefit. Therefore, the discovery of alternative therapeutic targets for advanced differentiated thyroid cancer is important (16).

Vitamin D receptor is a member of the nuclear hormone receptor superfamily. It binds to DNA at vitamin D3 response elements upon ligand binding to alter the transcription of vitamin D3-responsive genes (17). Vitamin D3 appears to exert anticancer activity by decreasing proliferation, promoting re-differentiation, inhibiting angiogenesis and accentuating the effects of standard chemotherapy (18, 19, 20, 21).

Clinical interest in the association of vitamin D levels with cancer, and in the potential of vitamin D receptor as a therapeutic target, has dramatically increased in recent years. A correlation between vitamin D and cancer prevention has been shown in breast, prostate and colorectal cancer (22). It rises to a consensus conference by the World Health Organization evaluating the evidence associated with vitamin D and cancer (23). Observational, preclinical and clinical studies strongly suggest that vitamin D3 deficiency increases the risk of developing multiple malignancies, whereas other studies do not support this hypothesis (24). However, several studies suggest that adequate vitamin D3 levels may provide protection against chronic diseases such as cancer and may improve cancer prognosis (25, 26, 27). Expression of the VDR gene and 25-hydroxyvitamin D3 1-α-hydroxylase, the rate-limiting enzyme in the production of active vitamin D3, has been found in several tissues and tumor types (28). Active vitamin D3 is important for regulating differentiation and cell growth in many different organs, and expression of 1a-hydroxylase/VDR is regarded as an important response against tumor progression.

A prior report by Izkhakov and coworkers showed that VDR mRNA expression was higher in malignant thyroid tissues than that in normal thyroid tissues, which indicates a possible correlation between VDR gene expression and thyroid cancer prognosis (2); however, there were no clinicopathological differences between patients with low levels of gene expression and those with high levels of gene expression. Clinckspoor and coworkers reported that lower vitamin D3 metabolism was associated with the progression of thyroid cancer of follicular origin (29). Here, we found that overexpression of VDR mRNA was correlated with aggressive PTC subtypes – classic PTC and TCVPTC, lateral neck node metastasis, advanced tumor (T4) and AJCC stage (IV) and worse recurrence-free survival. Our results also showed an association between high VDR mRNA and BRAFV600E mutant PTC, although did not gain statistical significance. Chemokine signaling pathway enrichment that harbors MAPK signaling cascade derived from two different pathway analyses also suggest that high VDR expression may be associated with thyroid cancer progression by enhancing MAPK pathway. Overall, results show that overexpression of VDR mRNA is associated with poor prognostic factors in PTC, aggressive subtype, advanced T and AJCC stage, lateral neck node metastasis and worse recurrence-free survival.

One possible explanation for these results is impaired expression of vitamin D receptor on the cell membrane: VDR mRNA may be overexpressed in response to decreased vitamin D receptor protein expression in damaged cellular membranes. Another explanation may be genomic discordance between the expression levels of mRNA and the expression of protein. Guo and coworkers reported on the usefulness of mRNA to predict protein expression, but they described that the prediction of protein expression using mRNA was far from perfect (30). Because of limitations in our study design, the correlation between VDR mRNA expression and vitamin D receptor protein expression could not be clearly assessed in this report. Further study in thyroid cancer is required.

In conclusion, we used public multigenomics data to demonstrate that elevated VDR mRNA levels are associated with aggressive PTC subtypes, worse prognostic factors and recurrence-free survival. Further experimental validation should be performed to prove the biologic influence of VDR and circulating vitamin D.

Supplementary data

This is linked to the online version of the paper at http://dx.doi.org/10.1530/EC-17-0001.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This study was supported by the Research Grant Number CB-2011-03-01 of the Korean Foundation for Cancer Research.

References

  • 1

    CongDHeMChenSLiuXLiuXSunH.Expression profiles of pivotal microRNAs and targets in thyroid papillary carcinoma: an analysis of the Cancer Genome Atlas. Journal of OncoTargets and Therapy2015822712277. (doi:10.2147/OTT.S85753)

  • 2

    IzkhakovESomjenDSharonOKnollEAizicAFlissD MLimorRSternN.Vitamin D receptor expression is linked to potential markers of human thyroid papillary carcinoma. Journal of Steroid Biochemistry and Molecular Biology20161592630. (doi:10.1016/j.jsbmb.2016.02.016)

  • 3

    GiovannucciE.Vitamin D and cancer incidence in the Harvard cohorts. Annals of Epidemiology2009198488. (doi:10.1016/j.annepidem.2007.12.002)

  • 4

    BurasRRSchumakerLMDavoodiFBrennerRVShabahangMNautaRJEvansSR.Vitamin D receptors in breast cancer cells. Breast Cancer Research and Treatment199431191202. (doi:10.1007/BF00666153)

  • 5

    DeebKKTrumpDLJohnsonCS.Vitamin D signalling pathways in cancer: potential for anticancer therapeutics. Nature Reviews Cancer20077684700. (doi:10.1038/nrc2196)

  • 6

    KostnerKDenzerNMullerCSKleinRTilgenWReichrathJ.The relevance of vitamin D receptor (VDR) gene polymorphisms for cancer: a review of the literature. Anticancer Research20092935113536.

  • 7

    KrishnanAVTrumpDLJohnsonCSFeldmanD.The role of vitamin D in cancer prevention and treatment. Rheumatic Disease Clinics of North America201238161178. (doi:10.1016/j.rdc.2012.03.014)

  • 8

    ZinserGMSuckowMWelshJ.Vitamin D receptor (VDR) ablation alters carcinogen-induced tumorigenesis in mammary gland, epidermis and lymphoid tissues. Journal of Steroid Biochemistry and Molecular Biology200597153164. (doi:10.1016/j.jsbmb.2005.06.024)

  • 9

    UitterlindenAGFangYVan MeursJBPolsHAVan LeeuwenJP.Genetics and biology of vitamin D receptor polymorphisms. Gene2004338143156. (doi:10.1016/j.gene.2004.05.014)

  • 10

    Cancer Genome Atlas Research Network. Integrated genomic characterization of papillary thyroid carcinoma. Cell2014159676690. (doi:10.1016/j.cell.2014.09.050)

  • 11

    RobinsonMDMcCarthyDJSmythGK.edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics201026139140. (doi:10.1093/bioinformatics/btp616)

  • 12

    Huang daWShermanBTLempickiR. A systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols200944457. (doi:10.1038/nprot.2008.211)

  • 13

    Huang daWShermanBTLempickiRA.Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Research200937113. (doi:10.1093/nar/gkn923)

  • 14

    SubramanianATamayoPMoothaVKMukherjeeSEbertBLGilletteMAPaulovichAPomeroySLGolubTRLanderESGene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. PNAS20051021554515550. (doi:10.1073/pnas.0506580102)

  • 15

    HaugenBRAlexanderEKBibleKCDohertyGMMandelSJNikiforovYEPaciniFRandolphGWSawkaAMSchlumbergerM2015American thyroid association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American thyroid association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid2016261133. (doi:10.1089/thy.2015.0020)

  • 16

    ShermanSI.Advances in chemotherapy of differentiated epithelial and medullary thyroid cancers. Journal of Clinical Endocrinology and Metabolism20099414931499. (doi:10.1210/jc.2008-0923)

  • 17

    MacDonaldPNBaudinoTATokumaruHDowdDRZhangC.Vitamin D receptor and nuclear receptor coactivators: crucial interactions in vitamin D-mediated transcription. Steroids200166171176. (doi:10.1016/S0039-128X(00)00200-2)

  • 18

    AliMMVaidyaV.Vitamin D and cancer. Journal of Cancer Research and Therapeutics20073225230. (doi:10.4103/0973-1482.38998)

  • 19

    MaYYuWDHershbergerPAFlynnGKongRXTrumpDLJohnsonCS.1alpha,25-Dihydroxyvitamin D3 potentiates cisplatin antitumor activity by p73 induction in a squamous cell carcinoma model. Molecular Cancer Therapeutics2008730473055. (doi:10.1158/1535-7163.MCT-08-0243)

  • 20

    WuFSZhengSSWuLJTengLSMaZMZhaoWHWuW.Calcitriol inhibits the growth of MHCC97 heptocellular cell lines by down-modulating c-met and ERK expressions. Liver International200727700707. (doi:10.1111/j.1478-3231.2007.01487.x)

  • 21

    ZhangXJiangFLiPLiCMaQNicosiaSVBaiW.Growth suppression of ovarian cancer xenografts in nude mice by vitamin D analogue EB1089. Clinical Cancer Research200511323328. (doi:10.1158/1078-0432.CCR-05-0400)

  • 22

    SongMWuKChanATFuchsCSGiovannucciEL.Plasma 25-hydroxyvitamin D and risk of colorectal cancer after adjusting for inflammatory markers. Cancer Epidemiology Biomarkers and Prevention20142321752180. (doi:10.1158/1055-9965.EPI-14-0712)

  • 23

    SharmaVFretwellDCreesZKeregeAKlopperJP.Thyroid cancer resistance to vitamin D receptor activation is associated with 24-hydroxylase levels but not the ff FokI polymorphism. Thyroid20102011031111. (doi:10.1089/thy.2010.0096)

  • 24

    FeldmanDKrishnanAVSwamiSGiovannucciEFeldmanBJ.The role of vitamin D in reducing cancer risk and progression. Nature Reviews Cancer201414342357. (doi:10.1038/nrc3691)

  • 25

    ColstonKWBergerUCoombesRC.Possible role for vitamin D in controlling breast cancer cell proliferation. Lancet19891188191. (doi:10.1016/S0140-6736(89)91204-X)

  • 26

    HausslerMRWhitfieldGKHausslerCAHsiehJCThompsonPDSelznickSHDominguezCEJurutkaPW.The nuclear vitamin D receptor: biological and molecular regulatory properties revealed. Journal of Bone and Mineral Research199813325349. (doi:10.1359/jbmr.1998.13.3.325)

  • 27

    MawerEBWallsJHowellADaviesMRatcliffeWABundredNJ.Serum 1,25-dihydroxyvitamin D may be related inversely to disease activity in breast cancer patients with bone metastases. Journal of Endocrinology and Metabolism199782118122. (doi:10.1210/jc.82.1.118)

  • 28

    ZehnderDBlandRWilliamsMCMcNinchRWHowieAJStewartPMHewisonM.Extrarenal expression of 25-hydroxyvitamin d(3)-1 alpha-hydroxylase. Journal of Endocrinology and Metabolism200186888894. (doi:10.1210/jcem.86.2.7220)

  • 29

    ClinckspoorIHaubenEVerlindenLVan den BruelAVanwalleghemLVander PoortenVDelaerePMathieuCVerstuyfADecallonneB.Altered expression of key players in vitamin D metabolism and signaling in malignant and benign thyroid tumors. Journal of Histochemistry and Cytochemistry201260502511. (doi:10.1369/0022155412447296)

  • 30

    GuoYXiaoPLeiSDengFXiaoGGLiuYChenXLiLWuSChenYHow is mRNA expression predictive for protein expression? A correlation study on human circulating monocytes. Acta Biochimica et Biophysica Sinica200840426436. (doi:10.1111/j.1745-7270.2008.00418.x)

If the inline PDF is not rendering correctly, you can download the PDF file here.

 

     European Society of Endocrinology

     Society for Endocrinology

Related Articles

Index Card

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 480 480 23
PDF Downloads 91 91 12

Altmetric Badge

Figures

  • View in gallery

    VDR mRNA expression counts in normal and papillary thyroid carcinoma tissue. (A) Fifty-nine paired normal and cancer tissues. (B) 59 normal vs 501 cancer tissues.

  • View in gallery

    Recurrence-free survival in the low and high VDR expression groups.

  • View in gallery

    MA plot of genes differentially expressed in the low and high VDR expression groups. DEG cutoff consisted of average logCPM (count per million) >0, | logFC (fold change) | >1 and FDR q-value <0.01.

PubMed

Google Scholar