Naunyn-Schmiedeberg's Arch Pharmacol DOI 10.1007/s00210-015-1150-1
ORIGINAL ARTICLE
Role of NR1I2 (pregnane X receptor) polymorphisms in head and neck squamous cell carcinoma Tasmin Reuter 1 & Rolf Warta 2,3 & Dirk Theile 1 & Andreas D. Meid 1 & Juan Pablo Rigalli 1 & Carolin Mogler 4,5 & Esther Herpel 4,5 & Niels Grabe 6,7 & Bernd Lahrmann 5,7 & Peter K. Plinkert 8 & Christel Herold-Mende 2,3 & Gerhard Dyckhoff 3 & Walter Emil Haefeli 1 & Johanna Weiss 1
Received: 30 March 2015 / Accepted: 23 June 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract The pregnane X receptor (PXR) is a transcription factor regulating genes involved not only in pharmacokinetics but also in chemotherapy resistance and cancer progression. The significance of PXR for survival of head and neck squamous cell carcinoma (HNSCC) patients is unknown so far. Single nucleotide polymorphisms (SNPs) in the PXRencoding NR1I2 gene influence receptor functionality and inducibility by ligands and thus modulate expression and activity of its target genes. In this study, seven SNPs in the NR1I2 gene were investigated for an association with PXR protein expression and survival of HNSCC patients. Genotyping was conducted using hybridisation probe format methodology. PXR protein expression was quantified by immunohistochemistry of tissue microarray samples of HNSCC biopsies. Genotypes were correlated to PXR protein expression by a linear model regressing on the continuous gene expression value and a Cox model regressing on overall survival times. Haplotype analysis was performed by reconstruction of hap-
lotypes from genotype information according to the expectation-maximisation algorithm. Of all tested SNPs, rs1054190 and rs1054191 allele variants tended to correlate with a reduced protein expression score of PXR (p=0.088). Four haplotypes, each consisting of two SNPs, rs3814055/ rs1054190 and rs3814055/rs1054191 as well as rs1523127/ rs1054190 and rs1523127/rs1054191, showed a significant reduction of the PXR expression score (p=0.049 and p= 0.032). However, neither allele variants nor haplotypes influenced overall survival of the respective patients. Certain NR1I2 SNPs showed an impact on PXR protein expression in HNSCC but did not influence overall survival times, questioning their value as prognostic biomarkers.
* Johanna Weiss [email protected]
4
Tissue Bank of the National Center for Tumour Diseases (NCT) Heidelberg, Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
5
Institute of Pathology, University of Heidelberg, Im Neuenheimer Feld 244, 69120 Heidelberg, Germany
6
Department of Medical Oncology, National Center for Tumour Diseases, University of Heidelberg, Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
1
Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
Keywords Genotype/phenotype correlation . Head and neck squamous cell carcinoma . NR1I2 polymorphism . Pregnane X receptor
2
Experimental Neurosurgery Research, Department of Neurosurgery, University of Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
7
Hamamatsu Tissue Imaging and Analysis Center, BIOQUANT, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
3
Molecular Cell Biology Group, Department of Otorhinolaryngology, Head and Neck Surgery, University of Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
8
Department of Otorhinolaryngology, Head and Neck Surgery, University of Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
Naunyn-Schmiedeberg's Arch Pharmacol
Introduction The pregnane X receptor (PXR, NR1I2) is a transcription factor belonging to the family of ligand-dependent nuclear receptors. Members of this family are known to regulate protein expression by enhancing gene transcription. Upon activation by an agonist, PXR heterodimerises with the retinoid X receptor alpha (RXRα, NR2B1) and translocates to the nucleus. There, the DNA-binding domain of PXR, located at the Nterminus, binds to a specific DNA sequence called the hormone-responsive element finally enhancing the transcription process (Pondugula et al. 2009). Ligands of PXR are structurally heterogeneous and include both endobiotics (e.g. pregnenolone, progesterone, and bile acids) (Kliewer et al. 1998) and xenobiotics such as rifampicin, spironolactone, and numerous antineoplastic drugs (Kliewer et al. 1998; Rigalli et al. 2011; Harmsen et al. 2009; Bertilsson et al. 1998). In humans, PXR is mainly expressed in the liver and small intestine and plays a crucial role in drug disposition (Kliewer et al. 1998), because it regulates important drugmetabolising enzymes like cytochrome P450 3A4 (CYP3A4) (Bertilsson et al. 1998), UDPglucuronosyltransferase 1A3 (UGT1A3) (Gardner-Stephen et al. 2004), and also drug transporters such as Pglycoprotein (P-gp, ABCB1) (Synold et al. 2001; Harmsen et al. 2010). Furthermore, increased PXR protein expression has been demonstrated in various tumour entities (Qiao et al. 2013). For instance, breast carcinoma (Miki et al. 2006), colon cancer (Jiang et al. 2009), ovarian cancer (Yue et al. 2010), and endometrial cancer (Masuyama et al. 2003) exhibited higher PXR expression levels than non-neoplastic tissues. Due to its impact on the expression of drug transporter genes, PXR plays a crucial role in the development of chemotherapy resistance also known as multidrug resistance (MDR) (Harmsen et al. 2009; Qiao et al. 2013; Miki et al. 2006). In addition, there is emerging evidence implicating PXR in the regulation of signal pathways related to apoptosis, tumour proliferation, and metastasis (Pondugula et al. 2009). Together, high PXR expression or activity has been considered a surrogate marker for poor clinical course in ovarian and breast cancer (Yue et al. 2010; Conde et al. 2008). On the other side, PXR has also been suggested to be an indicator of rather favourable outcome in oesophageal squamous cell carcinoma (Takeyama et al. 2010) and prostate cancer (Fujimura et al. 2012). Head and neck squamous cell carcinoma (HNSCC) is one of the world’s leading cancers by incidence with 500,000 new cases per year. The 5-year survival rate of HNSCC is 40–50 % (Rousseau 2012). Chemotherapy of HNSCC is often hampered by MDR (Fanucchi and Khuri 2004) potentially mediated by increased expression and activity of drug transporters (Theile et al. 2011). Functionality of PXR is a key determinant of potential iatrogenic chemotherapy resistance, because
many antineoplastic agents are known to activate PXR and thus to enhance the expression of MDR proteins. In vitro, PXR is dysfunctional in HNSCC, because even the prototype activator of PXR rifampicin failed to enhance PXR activity in the majority of HNSCC cell lines tested (Rigalli et al. 2013). So far, the underlying molecular reason is unclear, but inactivating single nucleotide polymorphisms (SNPs) within the NR1I2 gene encoding PXR is one possible reason, because NR1I2 SNPs can modulate PXR expression, inducibility, and cancer pathogenesis as demonstrated in several other tissues (Zhang et al. 2008; Kotta-Loizou et al. 2013; Meyer zu Schwabedissen and Kim 2009). For instance, some silent SNPs in intronic regions of NR1I2 are associated with the variability of the CYP3A4 expression subsequent to PXR activation by rifampicin, indicating an impact of NR1I2 polymorphisms on inducibility by PXR (Zhang et al. 2001). In addition, the NR1I2 polymorphism rs6785049 might be associated with breast cancer risk (MARIE-GENICA Consortium on Genetic Susceptibility for Menopausal Hormone Therapy Related Breast Cancer Risk 2010). Moreover, NR1I2 polymorphisms modify the course of disease in primary sclerosing cholangitis (Karlsen et al. 2006). In summary, there is clear evidence for a central role of PXR in physiology and pathophysiology of cells, tissues, or whole organs. So far, the association of NR1I2 polymorphisms with the expression of PXR in HNSCC and their influence on patient survival has not been studied. Thus, we investigated the impact of seven NR1I2 SNPs (rs3814055 C>T, rs1523127 A>C, rs2472677 C>T, rs6785049 A >G, rs2276707 C > T, rs1054190 C > T, and rs1054191 G>A) previously associated with altered PXR function (Svard et al. 2010; Kotta-Loizou et al. 2013; Zhang et al. 2001; Andersen et al. 2011) on the overall survival of 58 HNSCC patients and PXR expression profiles of 45 tumour tissue samples at clinical stages I–IV in order to evaluate the role of NR1I2 polymorphisms in HNSCC.
Materials and methods Patients Blood and tissue samples from HNSCC patients were provided by the tissue bank of the National Center for Tumour Diseases (NCT, Heidelberg, Germany) in accordance with the regulations of the tissue bank and the approval of the ethics committee of Heidelberg University. Patients included did not receive chemo- or radiotherapy prior to surgery. Clinical tumour stage was defined according to Union for International Cancer Control (UICC). Clinical data of patients was assessed in an MS Database (Microsoft, Redmond, USA) and obtained by reviewing the medical records, and follow-up data were obtained by telephone or written correspondence. Patients who survived beyond the study period and patients who died
Naunyn-Schmiedeberg's Arch Pharmacol
of a non-cancer-related death were censored. Vital tumour cell content ≥70 % was confirmed on haematoxylin-and-eosinstained sections by an experienced pathologist of the NCT Tissue Bank as described previously (Warta et al. 2014). Genotyping Genomic DNA was isolated from 58 whole-blood samples using the NucleoSpin Blood Quick Pure Kit from Macherey-Nagel (Düren, Germany) according to the manufacturer’s instructions. Primers and probes for genotyping were designed and provided by TIB MOLBIOL (Berlin, Germany); sequences are shown in Tables 1 and 2. For the SNPs rs3814055 C>T, rs1523127 A>C, rs6785049 A>G, rs2276707 C> T, rs1054190 C > T, and rs1054191 G > A, genotyping was performed by the hybridisation probe format on the LightCycler® 480 (Roche Applied Science, Mannheim, Germany). In this set-up, the anchor probe binds to the template DNA in a distance of up to five bases to the sensor probe that covers the polymorphic target sequence. The anchor probe is labelled with a LC Red 640 or 705 fluorescent dye at the 5′ end, and the sensor probe carries a fluorescein at the 3′ end. Binding of both hybridisation probes to the target DNA and excitation of the fluorescein lead to a fluorescence resonance energy transfer, resulting in a fluorescence signal detected by the LightCycler. Genotyping of rs2472677 C>T was accomplished using a simple probe. The simple probe covers the polymorphic target sequence and is labelled with a self-quenching fluorophore. By binding to the target, the quencher is released and the fluorophore emits a fluorescence signal when excited. During melting curve analysis, DNA is slowly heated while fluorescence is constantly being measured. Upon reaching the melting point, the sensor or simple probe melts off the template DNA strand and a lowering of fluorescence is detected. The variation in melting point Table 1
temperature depends solely on the sensor or simple probe, as any misfit within the sequence covered by the sensor or simple probe will cause a lowering of melting temperature. Melting temperatures for the alleles investigated are shown in Table 2. The total reaction volume was 10 μl, consisting of primers and probes, 1× LightCycler® 480 Genotyping Master (Roche Applied Science, Mannheim), and 5–20 ng genomic DNA. Ninety-six-well PCR plates were purchased from Biozym (Hessisch Oldendorf, Germany). Concentrations of primers and annealing temperatures for the amplification protocols are shown in Table 1. To validate the internal standard DNA samples of each genotype, the corresponding PCR products were sequenced by StarSEQ GMBH (Mainz, Germany). Sequences of standards were evaluated with BioEdit Sequence Alignment Editor software version 7.2.0 (Ibis Biosciences, Carlsbad, USA) running ClustalW multiple alignment in reference to the PXR sequence of the Genome Reference Consortium Human Build 37 patch release 10 (GRCh37.p10), NC_000003.1 (Hall 1999). Inter-run precision was tested by running replicates of each genotype control sample on three different days.
Quantification of PXR mRNA expression To check whether protein expression in tumour samples correlates with mRNA expression, mRNA expression was quantified with reverse transcriptase real-time PCR. Total RNA from frozen tissue samples was isolated using the TissueLyser II (Qiagen, Hilden, Germany) in combination with TRIzol (Invitrogen, Life Technologies, Darmstadt, Germany) reagent according to the manufacturer’s instruction. RNA amount and quality were analysed using the Eukaryote Total RNA Nano Assay of the Agilent 2100 Bioanalyzer
Sequences, concentrations, and annealing temperatures of primers used for genotyping
SNP
Primer
Sequence 5′→3′
Concentration (μM)
Annealing temp. (°C)
rs3814055 C>T
Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse
gCTggATTAAAgCATgTACTTCA TAACTgCTCCTACCTAAAAggCA AgCCAAgTgTTCACAgTgAg CACTTTgAACAATCCggTgC CATTTTTAAATTgggTTATTTgTAT AgTTTTCCTTATAAAgCATATTACTg gAgCTgTCTgCTgggTTgTg gCAAgTCCCTggCAgCAA AgATggAATggTggAAAACAA CAgCTTCTTCAgCATgTAgTgg gCACCAAATgTCAgAAgCTT gCTCCTACAgACTCATgTCCTC gCACCAAATgTCAgAAgCTT gCTCCTACAgACTCATgTCCTC
0.5 0.5 0.1 0.5 0.5 0.5 1 0.2 0.5 0.5 0.5 0.5 0.5 0.5
46
rs1523127 A>C rs2472677 C>T rs6785049 A>G rs2276707 C>T rs1054190 C>T rs1054191 G>A
50 46 50 50 50 50
Naunyn-Schmiedeberg's Arch Pharmacol Table 2
Sequences, concentrations, and melting points of probes used for genotyping
SNP
Probe
Sequence 5′→3′
ci (μM)
Tm wt
Tm var
rs3814055 C>T
Sensor Anchor Sensor Anchor Sensor (simple probe) Sensor Anchor Sensor Anchor Sensor Anchor
AggTAgAAAAgAAAACCTgggA-fl 640-TgCCAAAAAATgACCACAgTTgTCTTCAg p CTgTCCTgAACAAggCAgC-fl 640-CTCCTTggTAAAgCTACTCCTTgATCgATC p ACTTTTTTgTgCCA XI TATTTTTTCTgATT p CCTCTCACCCCCAACTTCT-fl 640-ATTATgggATggCTgCTggTgCCggC p gCCCCTCCATCCTgTTACC-fl 640-TCCACAggTggCTTCCAgCAACTTCTACTg p AggCTACCTATTATCAgTgCTTAATA-fl 640-TgTgTTCAAATggATgCAgAgACACAgAA p
0.2 0.2 0.15 0.15 0.1 0.2 0.4 0.2 0.2 0.2 0.2
51.1±0.3
58.2±0.2
52.6±0.3
62.9±0.6
54.0±0.3 60.9±0.2
61.7±0.3 53.9±0.2
60.6±0.3
47.3±0.5
54.7±0.2
60.4±0.2
Sensor Anchor
CAgTgCCCgCCATCACA-fl 705-CTCAgCATCCACACAgggAAATTCCTTgT p
0.2 0.2
54.5±0.5
61.0±0.3
rs1523127 A>C rs2472677 C>T rs6785049 A>G rs2276707 C>T rs1054190 C>T rs1054191 G>A
ci concentration, fl fluorescein, p phosphorylated, XI simple probe label site, Tm melting point, wt ancestral allele, var polymorphic allele
(Waldbronn, Germany). Degraded RNA was excluded from further analysis. mRNA expression was quantified by real-time RT-PCR with the LightCycler® 480 (Roche Applied Science, Mannheim, Germany). PCR amplification was carried out in 20 μl reaction volume containing 5 μl 1:20 diluted cDNA, 1× Absolute QPCR SYBR Green Mix (Abgene, Hamburg, Germany), 0.3–0.5 μM of each primer, and between 3 and 4 mM MgCl2. Primer sequences were published previously (König et al. 2010; Theile et al. 2011). The most suitable housekeeping gene for normalisation in the tumour samples was identified using geNorm (version 3.4, Center for Medical Genetics, Ghent, Belgium), which determines the most stable reference genes from a set of tested genes in a given cDNA sample panel (Vandesompele et al. 2002). Among the housekeeping genes tested (glucuronidase β, GU; ribosomal protein L13, RPL13; hypoxanthine-phosphoribosyltransferase 1, HPRT; 60S human acidic ribosomal protein P1, HUPO), GU proved to be the most stable one for this data set. Data were evaluated by calibrator-normalised relative quantification with efficiency correction using the LightCycler® 480 software version 1.5 (Roche Applied Science, Mannheim, Germany). All samples were amplified in duplicate. However, due to limited material, some degraded RNAs, and the generally low mRNA expression of NR1I2, mRNA could only be quantified reliably in a small sample size precluding a correlation analysis with the protein expression.
tissue cylinders were embedded in paraffin and subsequently cut into sections of 5 μm thickness on precleaned microscope slides (Superfrost Plus from T hermo Scientific, Braunschweig, Germany). Prior to TMA staining, specificity of the primary PXR antibody clone G-11 (SC48403) from Santa Cruz Biotechnology (Heidelberg, Germany) was ens u r e d u s i n g a n i s o t y p e c o n t r o l ( S M 1 0 P, A c r i s , Hiddenhausen, Germany). Deparaffinisation was carried out by immersing slides in 100 % xylol (3×3 min), followed by 90, 80, 70, and 50 % ethanol (2×3 min each). Finally, slides were washed in distilled water (2×3 min). Antigen retrieval was performed in an autoclave at 1 bar, 125 °C for 20 min, using antigen retrieval buffer (DAKO, Hamburg, Germany) at pH 6.10. Incubation with primary and secondary antibodies and detection with Vectastain ELITE ABC Kit (Vector Laboratories, Burlingame, USA) were carried out as described earlier (Herold-Mende et al. 1996). Slides were scanned subsequently and protein expression was evaluated semiquantitatively by two independent investigators (DT, JW). Ranking of PXR expression intensity values ranged from 1 (no staining) to 4 (very strong staining) and extent of tumour staining from 1 (no staining) to 5 (75–100 %) as described (Warta et al. 2014). Scores were calculated as the product of intensity values and extent of tumour staining values and thus ranged from 1 to 20.
Statistical analysis Quantification of PXR expression Protein expression of PXR was quantified by immunostaining of tissue microarrays (TMA) for 70 tumour samples. Representative tumour regions were selected from HNSCC tissue by an experienced pathologist, and cylinders with a diameter of 0.6 mm were cut from each of the tumours. The
Definition of allele and haplotype frequencies and linkage analysis were performed with HAPLOVIEW 4.2 (Broad Institute, Cambridge, USA). Chi-square test was used to compare allele frequencies to the Hardy-Weinberg equilibrium. Differences were considered significant when p < 0.05 (Barrett et al. 2005).
Naunyn-Schmiedeberg's Arch Pharmacol
For correlation of genotypes with PXR gene expression and overall survival data, a continuous predictor variable was calculated counting the frequencies of polymorphic alleles deviating from wild-type. In order to investigate the association of these alleles with gene expression as described above and overall survival, a linear model regressing on the continuous gene expression value and a Cox model regressing on overall survival times were used, respectively. In addition to semi-parametric modelling, differences in survival times were calculated using log rank tests. Haplotype analysis was performed by reconstruction of haplotypes from genotype information according to the expectation-maximisation algorithm using the haplo.em function in R statistic software/ environment (Sinnwell and Schaid 2013). Resulting haplotypes were treated as categorical predictor variables. Groups with less than two subjects were combined with the next smallest group. Global haplotype influence was assessed by Wald tests in Cox regression analyses of overall survival and Wald tests comparing the full model with the null model in linear regression analyses of gene expression values. All tests were two-tailed, 95 % confidence intervals (CI) were calculated, and p values
ORIGINAL ARTICLE
Role of NR1I2 (pregnane X receptor) polymorphisms in head and neck squamous cell carcinoma Tasmin Reuter 1 & Rolf Warta 2,3 & Dirk Theile 1 & Andreas D. Meid 1 & Juan Pablo Rigalli 1 & Carolin Mogler 4,5 & Esther Herpel 4,5 & Niels Grabe 6,7 & Bernd Lahrmann 5,7 & Peter K. Plinkert 8 & Christel Herold-Mende 2,3 & Gerhard Dyckhoff 3 & Walter Emil Haefeli 1 & Johanna Weiss 1
Received: 30 March 2015 / Accepted: 23 June 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract The pregnane X receptor (PXR) is a transcription factor regulating genes involved not only in pharmacokinetics but also in chemotherapy resistance and cancer progression. The significance of PXR for survival of head and neck squamous cell carcinoma (HNSCC) patients is unknown so far. Single nucleotide polymorphisms (SNPs) in the PXRencoding NR1I2 gene influence receptor functionality and inducibility by ligands and thus modulate expression and activity of its target genes. In this study, seven SNPs in the NR1I2 gene were investigated for an association with PXR protein expression and survival of HNSCC patients. Genotyping was conducted using hybridisation probe format methodology. PXR protein expression was quantified by immunohistochemistry of tissue microarray samples of HNSCC biopsies. Genotypes were correlated to PXR protein expression by a linear model regressing on the continuous gene expression value and a Cox model regressing on overall survival times. Haplotype analysis was performed by reconstruction of hap-
lotypes from genotype information according to the expectation-maximisation algorithm. Of all tested SNPs, rs1054190 and rs1054191 allele variants tended to correlate with a reduced protein expression score of PXR (p=0.088). Four haplotypes, each consisting of two SNPs, rs3814055/ rs1054190 and rs3814055/rs1054191 as well as rs1523127/ rs1054190 and rs1523127/rs1054191, showed a significant reduction of the PXR expression score (p=0.049 and p= 0.032). However, neither allele variants nor haplotypes influenced overall survival of the respective patients. Certain NR1I2 SNPs showed an impact on PXR protein expression in HNSCC but did not influence overall survival times, questioning their value as prognostic biomarkers.
* Johanna Weiss [email protected]
4
Tissue Bank of the National Center for Tumour Diseases (NCT) Heidelberg, Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
5
Institute of Pathology, University of Heidelberg, Im Neuenheimer Feld 244, 69120 Heidelberg, Germany
6
Department of Medical Oncology, National Center for Tumour Diseases, University of Heidelberg, Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
1
Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
Keywords Genotype/phenotype correlation . Head and neck squamous cell carcinoma . NR1I2 polymorphism . Pregnane X receptor
2
Experimental Neurosurgery Research, Department of Neurosurgery, University of Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
7
Hamamatsu Tissue Imaging and Analysis Center, BIOQUANT, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
3
Molecular Cell Biology Group, Department of Otorhinolaryngology, Head and Neck Surgery, University of Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
8
Department of Otorhinolaryngology, Head and Neck Surgery, University of Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
Naunyn-Schmiedeberg's Arch Pharmacol
Introduction The pregnane X receptor (PXR, NR1I2) is a transcription factor belonging to the family of ligand-dependent nuclear receptors. Members of this family are known to regulate protein expression by enhancing gene transcription. Upon activation by an agonist, PXR heterodimerises with the retinoid X receptor alpha (RXRα, NR2B1) and translocates to the nucleus. There, the DNA-binding domain of PXR, located at the Nterminus, binds to a specific DNA sequence called the hormone-responsive element finally enhancing the transcription process (Pondugula et al. 2009). Ligands of PXR are structurally heterogeneous and include both endobiotics (e.g. pregnenolone, progesterone, and bile acids) (Kliewer et al. 1998) and xenobiotics such as rifampicin, spironolactone, and numerous antineoplastic drugs (Kliewer et al. 1998; Rigalli et al. 2011; Harmsen et al. 2009; Bertilsson et al. 1998). In humans, PXR is mainly expressed in the liver and small intestine and plays a crucial role in drug disposition (Kliewer et al. 1998), because it regulates important drugmetabolising enzymes like cytochrome P450 3A4 (CYP3A4) (Bertilsson et al. 1998), UDPglucuronosyltransferase 1A3 (UGT1A3) (Gardner-Stephen et al. 2004), and also drug transporters such as Pglycoprotein (P-gp, ABCB1) (Synold et al. 2001; Harmsen et al. 2010). Furthermore, increased PXR protein expression has been demonstrated in various tumour entities (Qiao et al. 2013). For instance, breast carcinoma (Miki et al. 2006), colon cancer (Jiang et al. 2009), ovarian cancer (Yue et al. 2010), and endometrial cancer (Masuyama et al. 2003) exhibited higher PXR expression levels than non-neoplastic tissues. Due to its impact on the expression of drug transporter genes, PXR plays a crucial role in the development of chemotherapy resistance also known as multidrug resistance (MDR) (Harmsen et al. 2009; Qiao et al. 2013; Miki et al. 2006). In addition, there is emerging evidence implicating PXR in the regulation of signal pathways related to apoptosis, tumour proliferation, and metastasis (Pondugula et al. 2009). Together, high PXR expression or activity has been considered a surrogate marker for poor clinical course in ovarian and breast cancer (Yue et al. 2010; Conde et al. 2008). On the other side, PXR has also been suggested to be an indicator of rather favourable outcome in oesophageal squamous cell carcinoma (Takeyama et al. 2010) and prostate cancer (Fujimura et al. 2012). Head and neck squamous cell carcinoma (HNSCC) is one of the world’s leading cancers by incidence with 500,000 new cases per year. The 5-year survival rate of HNSCC is 40–50 % (Rousseau 2012). Chemotherapy of HNSCC is often hampered by MDR (Fanucchi and Khuri 2004) potentially mediated by increased expression and activity of drug transporters (Theile et al. 2011). Functionality of PXR is a key determinant of potential iatrogenic chemotherapy resistance, because
many antineoplastic agents are known to activate PXR and thus to enhance the expression of MDR proteins. In vitro, PXR is dysfunctional in HNSCC, because even the prototype activator of PXR rifampicin failed to enhance PXR activity in the majority of HNSCC cell lines tested (Rigalli et al. 2013). So far, the underlying molecular reason is unclear, but inactivating single nucleotide polymorphisms (SNPs) within the NR1I2 gene encoding PXR is one possible reason, because NR1I2 SNPs can modulate PXR expression, inducibility, and cancer pathogenesis as demonstrated in several other tissues (Zhang et al. 2008; Kotta-Loizou et al. 2013; Meyer zu Schwabedissen and Kim 2009). For instance, some silent SNPs in intronic regions of NR1I2 are associated with the variability of the CYP3A4 expression subsequent to PXR activation by rifampicin, indicating an impact of NR1I2 polymorphisms on inducibility by PXR (Zhang et al. 2001). In addition, the NR1I2 polymorphism rs6785049 might be associated with breast cancer risk (MARIE-GENICA Consortium on Genetic Susceptibility for Menopausal Hormone Therapy Related Breast Cancer Risk 2010). Moreover, NR1I2 polymorphisms modify the course of disease in primary sclerosing cholangitis (Karlsen et al. 2006). In summary, there is clear evidence for a central role of PXR in physiology and pathophysiology of cells, tissues, or whole organs. So far, the association of NR1I2 polymorphisms with the expression of PXR in HNSCC and their influence on patient survival has not been studied. Thus, we investigated the impact of seven NR1I2 SNPs (rs3814055 C>T, rs1523127 A>C, rs2472677 C>T, rs6785049 A >G, rs2276707 C > T, rs1054190 C > T, and rs1054191 G>A) previously associated with altered PXR function (Svard et al. 2010; Kotta-Loizou et al. 2013; Zhang et al. 2001; Andersen et al. 2011) on the overall survival of 58 HNSCC patients and PXR expression profiles of 45 tumour tissue samples at clinical stages I–IV in order to evaluate the role of NR1I2 polymorphisms in HNSCC.
Materials and methods Patients Blood and tissue samples from HNSCC patients were provided by the tissue bank of the National Center for Tumour Diseases (NCT, Heidelberg, Germany) in accordance with the regulations of the tissue bank and the approval of the ethics committee of Heidelberg University. Patients included did not receive chemo- or radiotherapy prior to surgery. Clinical tumour stage was defined according to Union for International Cancer Control (UICC). Clinical data of patients was assessed in an MS Database (Microsoft, Redmond, USA) and obtained by reviewing the medical records, and follow-up data were obtained by telephone or written correspondence. Patients who survived beyond the study period and patients who died
Naunyn-Schmiedeberg's Arch Pharmacol
of a non-cancer-related death were censored. Vital tumour cell content ≥70 % was confirmed on haematoxylin-and-eosinstained sections by an experienced pathologist of the NCT Tissue Bank as described previously (Warta et al. 2014). Genotyping Genomic DNA was isolated from 58 whole-blood samples using the NucleoSpin Blood Quick Pure Kit from Macherey-Nagel (Düren, Germany) according to the manufacturer’s instructions. Primers and probes for genotyping were designed and provided by TIB MOLBIOL (Berlin, Germany); sequences are shown in Tables 1 and 2. For the SNPs rs3814055 C>T, rs1523127 A>C, rs6785049 A>G, rs2276707 C> T, rs1054190 C > T, and rs1054191 G > A, genotyping was performed by the hybridisation probe format on the LightCycler® 480 (Roche Applied Science, Mannheim, Germany). In this set-up, the anchor probe binds to the template DNA in a distance of up to five bases to the sensor probe that covers the polymorphic target sequence. The anchor probe is labelled with a LC Red 640 or 705 fluorescent dye at the 5′ end, and the sensor probe carries a fluorescein at the 3′ end. Binding of both hybridisation probes to the target DNA and excitation of the fluorescein lead to a fluorescence resonance energy transfer, resulting in a fluorescence signal detected by the LightCycler. Genotyping of rs2472677 C>T was accomplished using a simple probe. The simple probe covers the polymorphic target sequence and is labelled with a self-quenching fluorophore. By binding to the target, the quencher is released and the fluorophore emits a fluorescence signal when excited. During melting curve analysis, DNA is slowly heated while fluorescence is constantly being measured. Upon reaching the melting point, the sensor or simple probe melts off the template DNA strand and a lowering of fluorescence is detected. The variation in melting point Table 1
temperature depends solely on the sensor or simple probe, as any misfit within the sequence covered by the sensor or simple probe will cause a lowering of melting temperature. Melting temperatures for the alleles investigated are shown in Table 2. The total reaction volume was 10 μl, consisting of primers and probes, 1× LightCycler® 480 Genotyping Master (Roche Applied Science, Mannheim), and 5–20 ng genomic DNA. Ninety-six-well PCR plates were purchased from Biozym (Hessisch Oldendorf, Germany). Concentrations of primers and annealing temperatures for the amplification protocols are shown in Table 1. To validate the internal standard DNA samples of each genotype, the corresponding PCR products were sequenced by StarSEQ GMBH (Mainz, Germany). Sequences of standards were evaluated with BioEdit Sequence Alignment Editor software version 7.2.0 (Ibis Biosciences, Carlsbad, USA) running ClustalW multiple alignment in reference to the PXR sequence of the Genome Reference Consortium Human Build 37 patch release 10 (GRCh37.p10), NC_000003.1 (Hall 1999). Inter-run precision was tested by running replicates of each genotype control sample on three different days.
Quantification of PXR mRNA expression To check whether protein expression in tumour samples correlates with mRNA expression, mRNA expression was quantified with reverse transcriptase real-time PCR. Total RNA from frozen tissue samples was isolated using the TissueLyser II (Qiagen, Hilden, Germany) in combination with TRIzol (Invitrogen, Life Technologies, Darmstadt, Germany) reagent according to the manufacturer’s instruction. RNA amount and quality were analysed using the Eukaryote Total RNA Nano Assay of the Agilent 2100 Bioanalyzer
Sequences, concentrations, and annealing temperatures of primers used for genotyping
SNP
Primer
Sequence 5′→3′
Concentration (μM)
Annealing temp. (°C)
rs3814055 C>T
Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse
gCTggATTAAAgCATgTACTTCA TAACTgCTCCTACCTAAAAggCA AgCCAAgTgTTCACAgTgAg CACTTTgAACAATCCggTgC CATTTTTAAATTgggTTATTTgTAT AgTTTTCCTTATAAAgCATATTACTg gAgCTgTCTgCTgggTTgTg gCAAgTCCCTggCAgCAA AgATggAATggTggAAAACAA CAgCTTCTTCAgCATgTAgTgg gCACCAAATgTCAgAAgCTT gCTCCTACAgACTCATgTCCTC gCACCAAATgTCAgAAgCTT gCTCCTACAgACTCATgTCCTC
0.5 0.5 0.1 0.5 0.5 0.5 1 0.2 0.5 0.5 0.5 0.5 0.5 0.5
46
rs1523127 A>C rs2472677 C>T rs6785049 A>G rs2276707 C>T rs1054190 C>T rs1054191 G>A
50 46 50 50 50 50
Naunyn-Schmiedeberg's Arch Pharmacol Table 2
Sequences, concentrations, and melting points of probes used for genotyping
SNP
Probe
Sequence 5′→3′
ci (μM)
Tm wt
Tm var
rs3814055 C>T
Sensor Anchor Sensor Anchor Sensor (simple probe) Sensor Anchor Sensor Anchor Sensor Anchor
AggTAgAAAAgAAAACCTgggA-fl 640-TgCCAAAAAATgACCACAgTTgTCTTCAg p CTgTCCTgAACAAggCAgC-fl 640-CTCCTTggTAAAgCTACTCCTTgATCgATC p ACTTTTTTgTgCCA XI TATTTTTTCTgATT p CCTCTCACCCCCAACTTCT-fl 640-ATTATgggATggCTgCTggTgCCggC p gCCCCTCCATCCTgTTACC-fl 640-TCCACAggTggCTTCCAgCAACTTCTACTg p AggCTACCTATTATCAgTgCTTAATA-fl 640-TgTgTTCAAATggATgCAgAgACACAgAA p
0.2 0.2 0.15 0.15 0.1 0.2 0.4 0.2 0.2 0.2 0.2
51.1±0.3
58.2±0.2
52.6±0.3
62.9±0.6
54.0±0.3 60.9±0.2
61.7±0.3 53.9±0.2
60.6±0.3
47.3±0.5
54.7±0.2
60.4±0.2
Sensor Anchor
CAgTgCCCgCCATCACA-fl 705-CTCAgCATCCACACAgggAAATTCCTTgT p
0.2 0.2
54.5±0.5
61.0±0.3
rs1523127 A>C rs2472677 C>T rs6785049 A>G rs2276707 C>T rs1054190 C>T rs1054191 G>A
ci concentration, fl fluorescein, p phosphorylated, XI simple probe label site, Tm melting point, wt ancestral allele, var polymorphic allele
(Waldbronn, Germany). Degraded RNA was excluded from further analysis. mRNA expression was quantified by real-time RT-PCR with the LightCycler® 480 (Roche Applied Science, Mannheim, Germany). PCR amplification was carried out in 20 μl reaction volume containing 5 μl 1:20 diluted cDNA, 1× Absolute QPCR SYBR Green Mix (Abgene, Hamburg, Germany), 0.3–0.5 μM of each primer, and between 3 and 4 mM MgCl2. Primer sequences were published previously (König et al. 2010; Theile et al. 2011). The most suitable housekeeping gene for normalisation in the tumour samples was identified using geNorm (version 3.4, Center for Medical Genetics, Ghent, Belgium), which determines the most stable reference genes from a set of tested genes in a given cDNA sample panel (Vandesompele et al. 2002). Among the housekeeping genes tested (glucuronidase β, GU; ribosomal protein L13, RPL13; hypoxanthine-phosphoribosyltransferase 1, HPRT; 60S human acidic ribosomal protein P1, HUPO), GU proved to be the most stable one for this data set. Data were evaluated by calibrator-normalised relative quantification with efficiency correction using the LightCycler® 480 software version 1.5 (Roche Applied Science, Mannheim, Germany). All samples were amplified in duplicate. However, due to limited material, some degraded RNAs, and the generally low mRNA expression of NR1I2, mRNA could only be quantified reliably in a small sample size precluding a correlation analysis with the protein expression.
tissue cylinders were embedded in paraffin and subsequently cut into sections of 5 μm thickness on precleaned microscope slides (Superfrost Plus from T hermo Scientific, Braunschweig, Germany). Prior to TMA staining, specificity of the primary PXR antibody clone G-11 (SC48403) from Santa Cruz Biotechnology (Heidelberg, Germany) was ens u r e d u s i n g a n i s o t y p e c o n t r o l ( S M 1 0 P, A c r i s , Hiddenhausen, Germany). Deparaffinisation was carried out by immersing slides in 100 % xylol (3×3 min), followed by 90, 80, 70, and 50 % ethanol (2×3 min each). Finally, slides were washed in distilled water (2×3 min). Antigen retrieval was performed in an autoclave at 1 bar, 125 °C for 20 min, using antigen retrieval buffer (DAKO, Hamburg, Germany) at pH 6.10. Incubation with primary and secondary antibodies and detection with Vectastain ELITE ABC Kit (Vector Laboratories, Burlingame, USA) were carried out as described earlier (Herold-Mende et al. 1996). Slides were scanned subsequently and protein expression was evaluated semiquantitatively by two independent investigators (DT, JW). Ranking of PXR expression intensity values ranged from 1 (no staining) to 4 (very strong staining) and extent of tumour staining from 1 (no staining) to 5 (75–100 %) as described (Warta et al. 2014). Scores were calculated as the product of intensity values and extent of tumour staining values and thus ranged from 1 to 20.
Statistical analysis Quantification of PXR expression Protein expression of PXR was quantified by immunostaining of tissue microarrays (TMA) for 70 tumour samples. Representative tumour regions were selected from HNSCC tissue by an experienced pathologist, and cylinders with a diameter of 0.6 mm were cut from each of the tumours. The
Definition of allele and haplotype frequencies and linkage analysis were performed with HAPLOVIEW 4.2 (Broad Institute, Cambridge, USA). Chi-square test was used to compare allele frequencies to the Hardy-Weinberg equilibrium. Differences were considered significant when p < 0.05 (Barrett et al. 2005).
Naunyn-Schmiedeberg's Arch Pharmacol
For correlation of genotypes with PXR gene expression and overall survival data, a continuous predictor variable was calculated counting the frequencies of polymorphic alleles deviating from wild-type. In order to investigate the association of these alleles with gene expression as described above and overall survival, a linear model regressing on the continuous gene expression value and a Cox model regressing on overall survival times were used, respectively. In addition to semi-parametric modelling, differences in survival times were calculated using log rank tests. Haplotype analysis was performed by reconstruction of haplotypes from genotype information according to the expectation-maximisation algorithm using the haplo.em function in R statistic software/ environment (Sinnwell and Schaid 2013). Resulting haplotypes were treated as categorical predictor variables. Groups with less than two subjects were combined with the next smallest group. Global haplotype influence was assessed by Wald tests in Cox regression analyses of overall survival and Wald tests comparing the full model with the null model in linear regression analyses of gene expression values. All tests were two-tailed, 95 % confidence intervals (CI) were calculated, and p values
