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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Eur J Cancer. Author manuscript; available in PMC Apr 4, 2007.
Published in final edited form as:
PMCID: PMC1847595
NIHMSID: NIHMS18134

Identification of differentially expressed genes in HPV-positive and HPV-negative oropharyngeal squamous cell carcinomas

Abstract

Human papillomaviruses (HPVs) have been implicated in the pathogenesis of a subset of squamous cell carcinoma of the head and neck (SCCHN). The goal of this study was to compare the cellular gene expression profiles of HPV-positive and HPV-negative oropharyngeal carcinomas with those of the normal oral epithelium. Using Affymetrix Human U133A GeneChip, our results showed that 397 genes were differentially expressed in HPV-positive SCCHN compared to the normal oral epithelium. The up-regulated genes included those involved in cell cycle regulation (CDKN2A), cell differentiation (SFRP4) and DNA repair (RAD51AP1), while the down-regulated genes included those involved in proteolysis (PRSS3). We also found 162 differentially expressed genes in HPV-negative SCCHN compared to the normal oral mucosa. The up-regulated genes included those involved in cell proliferation (AKR1C3) and transcription regulation (SNAPC1), while down-regulated genes included those involved in apoptosis (CLU) and RNA processing (RBM3). Our studies also identified a subgroup of 59 differentially expressed genes in HPV-positive SCCHN as compared to both HPV-negative SCCHN and normal oral tissues. Such up-regulated genes included those involved in nuclear structure and meiosis (SYCP2), DNA repair (RFC5), and transcription regulation (ZNF238). Genes involved in proteolysis (KLK8) and signal transduction (CRABP2) were found to be down-regulated in HPV-positive SCCHN. The results of GeneChip experiments were validated by quantitative real-time RT-PCR analysis of a few representative genes. Our results reveal specific gene expression patterns in HPV-positive and HPV-negative oropharyngeal squamous carcinomas that may serve as potential biomarkers for the development of SCCHN.

Keywords: Human papillomavirus, oral cancer, microarray, gene expression

1. Introduction

There are approximately 500,000 new cases of squamous cell carcinoma of the head and neck (SCCHN) worldwide and 45,000 cases in the United States per year.13 SCCHN is usually associated with such risk factors as heavy consumption of alcohol and/or tobacco. The survival in SCCHN patients is still poor and has not improved recently despite the advances in detection and therapies. It is well-established that human papillomaviruses (HPVs) are involved in the pathogenesis of cervical cancer.47 Recently, molecular epidemiologic studies have shown a strong correlation between oncogenic HPV infections and a subset of oropharyngeal cancers.812 It is not currently understood whether these HPV infections are an independent etiologic factor or a co-factor in the development of such tumours. Interestingly, a relative risk reduction from death of approximately 50% has been observed in HPV-associated tumours compared to those without detectable HPV DNA.11

HPVs are small double-stranded DNA viruses of approximately 7900 base pairs (bp). At present, more than 150 different types of HPV have been identified, and the high risk HPV types 16 and 18 are associated with a majority of cases of cervical cancer.6, 7 Replication of HPVs requires the viral E1 and E2 proteins as well as host replication factors.1314 The E2 protein also downregulates the transcription of the viral E6 and E7 oncogenes, which are transcribed from the p97 promoter.1517 The E6 and E7 oncoproteins of high-risk HPVs are involved in cellular transformation.1519 Most benign and low-grade cervical lesions contain HPV DNA in an extrachromosomal state.20 However, in most cases of cervical carcinomas the HPV DNA is usually found integrated into the host chromosomes, frequently disrupting the E1 and E2 genes.6, 7, 20, 21 This results in increased expression of the viral E6 and E7 oncogenes.22 The E6 protein promotes ubiquitination and consequently proteasomal degradation of the cellular tumour suppressor proteins p53 and PDZ domain-containing disc large protein (DLG).4, 7, 2325 E6 is also known to interact with a number of other cellular proteins and activates telomerase.6, 7 The E7 protein binds to and inactivates the function of pRB and related p107 and p130 proteins.4, 7 E7 also interacts with additional cellular proteins such as TBP, histone H1 kinase, cyclin E, etc.1416, 18, 19 The E6 and E7 proteins are also known to alter cellular gene expression but the precise molecular mechanisms involved are not well-understood.16, 18, 19 In addition, E6/E7 expression promotes chromosomal instability, foreign DNA integration and other mutagenic events in the cell.4, 6, 15, 26 Although several studies have suggested a possible role for HPV infection in a subset of SCCHN, very little is known about the molecular events involved in carcinogenesis. Although the distribution of episomal and integrated HPV forms in precancerous and cancerous lesions of the head and neck has not been determined, limited evidence suggests a similar physical state as observed in cervical carcinoma. Molecular studies of HPV-associated SCCHN are necessary for a better understanding of the physical state and potential role of this virus in carcinogenesis, and for the development of new, more targeted therapeutic strategies.

Recently, DNA microarrays have been successfully used to identify global patterns of gene expression in different human neoplasias, including head and neck cancers.2730 In the case of breast cancer studies, a set of 70 genes correctly predicted the nature and progression of the disease as well as the outcome.29, 30 These studies support the idea that changes in the molecular profiles of gene expression are early events during carcinogenesis and such global expression profiles can be used effectively to predict the course of the disease. Recently, investigators have used microarrays to analyze gene expression changes in SCCHN tissues and cell lines, but little is known about the gene expression changes in HPV-associated SCCHN.3135 The identification of molecular portrait of gene expression profiles in HPV-positive and HPV-negative SCCHN, including their differences, could result in a better understanding of critical events during carcinogenesis.

This study was undertaken to identify changes in cellular gene expression profiles in HPV-positive and HPV-negative SCCHN as compared to normal tissues as well as to each other. Our microarray analysis showed considerable differences in the gene expression profiles that were specifically associated with these two types of cancers. Several of the differentially expressed genes were found to be involved in cell cycle regulation (CDKN2A), nuclear structure and meiosis (SYCP2), DNA replication and repair (RFC5), transcription regulation (ZNF238), cell differentiation (KLK8) and epidermis development (CRABP2). Unsupervised clustering analysis also showed that genes located in specific chromosomal regions such as 1p31–p36 and 12q21–24 were specifically overexpressed in HPV-positive oropharyngeal squamous carcinomas.

2. Material and methods

2.1. Tissue samples and cell lines

A total of 11 samples were analysed in this study: Three HPV-positive (SK20, SK30, SK31), four HPV-negative (SK32, SK33, SK34, SK35), and four normal oral mucosa (SK16, SK17, SK36, SK37). Tumours and normal mucosal specimens were snap-frozen and stored at −80°C until further use. Collection of tissues was performed under an IRB-approved Tissue Banking protocol, and written informed consent was obtained from each patient prior to sample collection. The SCCHN samples were from the oropharynx (tonsil and base of tongue), while the normal oral mucosa specimens were obtained from patients undergoing removal of the oropharyngeal tissues: tonsils, soft palate and uvula for sleep apnea. None of the patients received prior chemotherapy or radiotherapy. Cervical carcinoma cell lines were obtained from the American Type Culture Collection (ATCC) and maintained in Dulbecco’s modified Eagle medium (C-33A) or RPMI 1640 (CaSki) supplemented with 10% fetal bovine serum (FBS) at 37°C in the presence of 5% CO2.

2.2. Isolation of RNA and RT-PCR analysis

Total RNA from all frozen tumour samples and oropharyngeal mucosal tissues was isolated using the RNeasy Mini Kit (Qiagen Inc.) according to the manufacturer’s protocol. The mucosa was carefully dissected from any subjacent muscle or lymphoid tissue before RNA extraction, so that only normal squamous epithelium was studied. The RNA pellet was dried under a vacuum and resuspended in 30–50 μl of DEPC treated water. The integrity of RNA samples was confirmed by analysing 1 μg of total RNA on 1.2% (w/v) denaturing formaldehyde-agarose gels. Before DNA synthesis, RNA was treated with deoxyribonuclease I, Amplification Grade (Invitrogen) for 15 min at room temperature to avoid DNA contamination. DNase I was inactivated by incubation with 25 mM EDTA at 65ºC for 10 min. We examined the expression of the HPV-16 E6 and E7 genes in the above samples by RT-PCR36 using the following primers: HPV-16 E6 (forward) 5′- ATGCACCAAAAGAGAACTGC -3′ and (reverse) 5′- TTACAGCTGGGTTTCTCTAC -3′ (477-bp PCR product); HPV-16 E7 (forward) 5′-GTAACCTTTTGTTGCAAGTGTGACT-3′ and (reverse) 5′-GATTATGGTTTCTGAGAACAGATGG-3′ (137-bp RT-PCR product). The expression of the cellular glyceraldehyde-3-phosphate dehydrogenase (GAPDH) house-keeping gene was used as a positive control using the following primers: GAPDH (forward) 5′- ACCACAGTCCATGCCATCAC-3′ and (reverse) 5′- TCCACCACCCTGTTGCTGTA-3′ (452-bp RT-PCR product). All RT-PCR reactions were done using the Thermoscript One-step System kit (Invitrogen Corp.). The cDNA synthesis was performed at 37°C for 1 hour in a final volume of 20 μl using 1 μg of total RNA template, 0.5 μg of oligo (dT)15, 10 mM dNTPs, 30 U of RNase inhibitor and 200 units of MMLV reverse transcriptase. PCR was performed in a 50 μl volume containing 50 mM KCl, 10 mM Tris (pH 8.3), 1.5 mM MgCl2, 0.01 % gelatin (w/v), 200 μM deoxynucleoside triphosphate (dNTP) mix, 0.4 μM of each primer and 2.5 units of the Taq DNA polymerase. The DNA was denatured at 94°C for 5 min, followed by 40 PCR amplification cycles that consisted of denaturation (94°C, 1 min), annealing (58–60°C, 1 min) and extension (72°C, 2 min). An additional extension step of 72°C for 5 min was included at the end of the reaction.

2.3. Quantitative real-time RT-PCR analysis

We validated the microarray data by quantitative real-time RT-PCR (QRT-PCR) analysis of a few representative genes using the QuantiTect SYBR Green one-step RT-PCR kit (QIAGEN, Valencia, CA). Approximately 400 ng of DNase I-treated total RNA from the samples was mixed with 25 μl of 2 X QuantiTect SYBR Green RT-PCR Master Mix, 0.5 μM of specific forward and reverse primers and RNase-free water in a final volume of 50 μl. The amount of fluorescence emitted by SYBR Green I was quantified by the ABI Prism 7700 system software (Applied Biosystems, Foster City, CA). The genes and primers used for this analysis are shown in Table 1. The following RT-PCR cycle parameters were used: reverse transcription at 50°C for 30 min, hot-start DNA polymerase activation 95°C for 15 min, 40 cycles of denaturation at 94°C for 15 sec each, annealing at 58°C for 30 sec and extension at 72°C for 30 sec. Each reaction was run in triplicate in a 96-well plate. Relative expression of the target gene was calculated using the 2 delta CT method described previously:37 (Relative expression = 2−ΔCT; where ΔCT = CT (Target gene) − CT (endogenous control gene)) where GAPDH was used as the endogenous control gene.

Table 1
Primer sequences for quantitative RT-PCR

2.4. cRNA synthesis and microarray analysis

Microarray analysis was carried out using the high-density oligonucleotide U133A GeneChip® expression microarray (Affymetrix, Santa Clara, CA) that contains 22,215 transcript sets representing 14,820 human genes. RNA isolated from the samples described above was further purified by using the RNeasy Total RNA Isolation Kit (QIAGEN, Valencia, CA) to remove contaminating DNA. Twenty micrograms of total RNA from each sample were used to generate double-stranded (ds) cDNA using the Superscript II Choice system (GIBCO-BRL, Rockville, MD). First-strand synthesis was carried out using a T7-(dT)24 primer (Sigma-GenoSys, The Woodlands, TX) and Superscript II reverse transcriptase. This primer includes the promoter sequence for the T7 RNA polymerase. The second-strand synthesis was performed using RNase H and DNA polymerase I. The resulting ds cDNA was used to synthesize cRNA using biotin-labeled ribonucleotides and T7 RNA polymerase utilizing the BioArray HighYield RNA transcript labelling kit (ENZO Life Sciences, Inc. Farmingdale, NY). The cRNA was fragmented to 35–200 bases length and hybridized to the Human Genome U133A GeneChip® expression microarray in the Affymetrix Hybridization Oven (Affymetrix, Santa Clara, CA). The GeneChips were washed, and then stained with streptavidin-phycoerythrin (SAPE) to generate fluorescent signals from biotin-labeled cRNA. The GeneChips were scanned using an Affymetrix GeneArray® scanner (Affymetrix, Santa Clara, CA). Each probed array was scanned twice to calculate an average of two images, define the probe cells and compute intensity for each cell. Fragmentation, hybridization, staining and scan were performed by the Pitt Array Facility, University of Pittsburgh.

2.5. Microarray data analysis

The CEL image files obtained from the Affymetrix Microarray Suite 5.0 were converted to DCP files using the program dChip version 1.2 (www.dchip.org). Two different statistical tests, Significance Analysis of Microarray (SAM) program version 1.21 (www.stat.stanford.edu/~tibs/SAM/) and Gene Expression Data Analysis (GEDA) program, were used to analyze the microarray data in order to identify differentially expressed genes that were robust enough to appear in both the analyses. For SAM analysis, the dChip program was used to generate normalized intensity signal data. The invariant set normalization method used by dChip program is one of the most commonly used normalization method for analysing the data in the SAM program.38 In SAM analysis, a false discovery rate (FDR) of less than 5 percent and a difference of at least 2-fold was chosen to identify the total number of differentially expressed genes. We also utilized the GEDA tool developed at the University of Pittsburgh (James Lyons-Weiler, University of Pittsburgh Cancer Institute, http://bioinformatics.upmc.edu) for statistical analysis. For this, non-normalized intensity signal data from dChip (PM-only model) were normalized (log-base2 transformation, median within arrays, Global Mean Adjustment among arrays) and analysed with a t-Test at level alpha = 0.05. This normalization method is specifically used by the GEDA program. Genes with an expression ratio of at least 2-fold difference relative to the controls were considered to be differentially expressed in GEDA analysis. After analyzing the data with the two statistical tests, we overlapped the lists of differentially expressed genes in order to generate a list of differentially expressed genes using software developed by Dr. Jim Lund at the University of Kentucky (http://elegans.uky.edu/MA/progs/Compare.html). All the microarray experiments were designed in accordance with the MIAME guidelines.39

For unsupervised hierarchical clustering analysis, we first filtered the genes using a threshold of 0.05 in the ratio of the standard deviation and the mean of a gene’s expression values across all samples (Coefficient of Variation), and then applied an algorithm for similarity measurements using Pearson’s correlation coefficient.40

3. Results

3.1. Expression of the HPV-16 early genes in SCCHN samples by RT-PCR analysis

RT-PCR analysis was carried out to test for the presence and expression of HPV early genes in all the SCCHN samples and the control normal oral tissues. RNA from CasKi and C-33A cervical carcinoma cell lines was used as positive and negative control, respectively, for HPV-16 gene expression. The E6 (with different splicing variants) and E7 viral oncogene transcripts were present in the HPV-16 positive SCCHN samples SK20, SK30 and SK31 but not in the HPV-negative SCCHN samples SK32, SK33, SK34, and SK35 or the normal oral mucosa samples SK16, SK17, SK36 and SK37 (Fig. 1). The above results confirmed the appropriate expression of the HPV-16 oncogenes in the three HPV-positive SCCHN samples.

Fig. 1
Analysis of HPV16 E6 and E7 gene expression in oropharyngeal tissue samples by RT-PCR. CaSki (HPV-16 positive) and C-33A (HPV-negative) cervical cell lines were used as controls. Expression of E6 splicing variants (E6, 477 bp, E6*I, 293 bp, E6*II, 176 ...

3.2. Microarray analysis of genes differentially expressed in the HPV-positive SCCHN samples compared to the normal oral tissue

In order to identify differentially expressed genes in HPV-16 positive SCCHN samples (SK20, SK30 and SK31) as compared to the normal oral tissue samples (SK16, SK17, SK36 and SK37), we utilized the Affymetrix U133A GeneChip. Normalization and differential gene expression analyses were carried out as described in material and methods. A total of 1,329 and 1,431 genes showed up- and down-regulation, respectively, using a pooled variance t-Test analysis when all the HPV-16 positive SCCHN samples were compared to the normal oral tissues (supplementary data, Table A). On the other hand, 470 and 424 genes were found to be up- and down-regulated, respectively, using the SAM-Test analysis (supplementary data, Table B). When the results of the above two statistical tests were overlapped, 228 genes were found to be upregulated and 169 downregulated in HPV-16 positive SCCHN samples as compared to the normal oral tissues (Fig. 2). A list of differentially expressed genes representing various cellular pathways is shown in Table 2. A complete list of genes is shown in the supplementary data, Table C. Our analysis identified genes that have previously been shown to be overexpressed in HPV-infected cervical or oral epithelial cells such as those involved in DNA replication and cell cycle regulation: cyclin-dependent kinase inhibitor 2A (CDKN2A), minichromosome maintenance deficient genes (MCM2, MCM3), topoisomerase (DNA) II alpha 170-kDa (TOP2A) and proliferating cell nuclear antigen (PCNA).4143 These findings suggest that some carcinogenic pathways are frequently affected in HPV-positive cervical as well as HPV-positive oral cancers. Our experiments also identified several genes that were previously implicated in tumourigenesis of different tissues but not in SCCHN. Examples of these include the upregulation of genes involved in cell differentiation or DNA repair such as secreted frizzled-related protein 4 (SFRP4), and RAD51 associated protein 1 (RAD51AP1).44, 45 Our results also showed the downregulation of genes involved in proteolysis such as protease serine 3 (PRSS3) and chemotaxis, such as chemokine (C-C motif) ligand 14 (CCL14), for the first time in HPV-positive SCCHN (Table 2).

Fig. 2
Summary of differentially expressed genes identified by microarray analysis using two different statistical analyses. The ovals represent the 3 groups of samples used in our study. The overlapping regions indicate the number of genes found to be up- or ...
Table 2
Genes found differentially expressed in HPV-positive SCCHN versus normal oral epithelium

3.3. Genes differentially expressed in HPV-negative SCCHN compared to the normal oral mucosa

Using the pooled variance t-Test analysis, we found that 1,052 genes were upregulated and 850 downregulated in HPV-negative SCCHN samples compared to the normal oral tissues (supplementary data, Table D). The SAM test identified 244 upregulated and 310 downregulated genes in the HPV-negative SCCHN samples (supplementary data, Table E). A comparison of the differentially expressed genes revealed that 79 upregulated and 83 downregulated genes were common in both the pooled variance t-Test and SAM analyses (supplementary data, Table F) (Fig. 2). A list of differentially expressed genes representing various cellular pathways is shown in Table 3. Upregulated genes involved in cell-cell signaling such as parathyroid hormone-like hormone (PTHLH ) or angiogenesis such as endothelial cell growth factor 1 (ECGF1), as well as downregulated genes involved in signal transduction or apoptosis such as insulin-like growth factor binding protein 5 (IGFBP5) and programmed cell death 4 (neoplastic transformation inhibitor) (PDCD4) were identified in our studies similar to those found in previous SCCHN studies, providing a good correlation with our results.46, 47 We also found differentially expressed genes that were not previously reported in SCCHN, although they were implicated in other types of tumours. Such upregulated genes included those involved in cell proliferation and transcription regulation such as aldo-keto reductase family 1, member C3 (AKR1C3), and small nuclear RNA activating complex, polypeptide 1, 43-kDa (SNAPC1), while downregulated genes included those involved in apoptosis or RNA processing such as clusterin (CLU) and RNA binding motif protein 3 (RBM3).4852

Table 3
Genes found differentially expressed in HPV-negative SCCHN versus normal oral epithelium

3.4. Identification of genes differentially expressed between HPV-positive and HPV-negative SCCHN

To identify pathways unique to the pathogenesis of HPV positive and negative SCCHN, we compared the gene expression profiles in these two types of cancers. The pooled t-Test analysis revealed that a total of 1,040 genes were upregulated and 1,363 downregulated in the HPV-positive SCCHN samples compared to the HPV-negative SCCHN samples (supplementary data, Table G). Using the SAM test, we identified 347 upregulated and 175 downregulated genes in the HPV-positive SCCHN compared to HPV-negative SCCHN (supplementary data, Table H). A comparison of the results obtained using the above two tests was done to identify genes present in both of these analyses. This showed that 124 genes were upregulated and 42 downregulated in HPV-16 positive SCCHN as compared to the HPV-negative SCCHN (Fig.2). A list of differentially expressed genes representing various cellular pathways is shown in Table 4 (a complete list of genes is shown in the supplementary data, Table I).

Table 4
Genes found to be differentially expressed in HPV-positive SCCHN versus HPV-negative SCCHN

Interestingly, a subgroup of 40 upregulated and 19 downregulated genes identified in HPV-positive versus HPV-negative SCCHN analysis, was also found in a comparison between HPV-positive SCCHN and normal oral tissues. Thus, it is likely that the expression of this group of genes (Table 5) is specifically affected by the presence of HPV. Such upregulated genes included those involved in nuclear structure and meiosis (synaptonemal complex protein 2 [SYCP2]), DNA repair (replication factor C 5 [RFC5]), and DNA methylation (DNA [cytosine-5-]-methyltransferase 1 [DNMT1]). Genes involved in proteolysis (kallikrein 7, 8, 10 [KLK7, KLK8, KLK10]) and signal transduction (cellular retinoic acid binding protein 2 [CRABP2]) were found to be downregulated in HPV-positive SCCHN compared to both HPV-negative SCCHN and normal oral tissues in these analyses.

Table 5
Genes found differentially expressed exclusively in HPV-positive SCCHN versus HPV-negative SCCHN or normal oral epithelium

3.5. Identification of differentially expressed genes present in all SCCHN samples in comparison to normal oral tissues

We also identified genes whose expression is similarly affected in both HPV- positive and HPV-negative SCCHN as compared to the normal oral mucosa. Based on the pooled t-Test and SAM test analyses, we found that 55 genes were upregulated and 42 downregulated in HPV-positive as well as HPV-negative SCCHN as compared to the normal oral mucosa. A list of differentially expressed genes representing various cellular pathways is shown in Table 6 (a complete list of genes is shown in the supplementary data, Table J). These genes may represent common pathways altered during SCCHN irrespective of the presence or absence of HPVs. The upregulated genes included those involved in cell cycle regulation, epidermis development and cell adhesion such as signal transducer and activator of transcription 1 (STAT1), keratin 14, 16 (KRT14, KRT16) and transforming growth factor, beta-induced, 68-kDa (TGFBI). Also, downregulated genes found in both types of SCCHN samples included those involved in chromatin remodeling, cell-cell adhesion and apoptosis such as p300/CBP-associated factor (PCAF), annexin A9 (ANXA9) and mal, T-cell differentiation protein (MAL).

Table 6
Genes found differentially expressed in all SCCHN samples versus normal oral epithelium

3.6. Identification of several gene expression clusters in HPV-positive, HPV-negative SCCHN and normal oral tissues

Unsupervised hierarchical cluster analysis was developed using all SCCHN specimens as well as normal oral tissues. After normalization and filtering with different criteria (described in materials and methods), we obtained a set of 8,286 genes with significant variation in their expression in one or more of the total of three types of samples (HPV-positive SCCHN, HPV-negative SCCHN, and control oral mucosa). From these filtered genes, we identified five clusters that showed differences in gene expression not only between all the SCCHN samples and the normal oral epithelium but also between HPV-positive SCCHN and HPV-negative SCCHN (Fig. 3). Interestingly, some of the genes found in this analysis were also found in the supervised statistical analysis such as ZNF238, DNMT1, MCM3, aldo-keto reductase family 1, member C3 (AKR1C3), growth factor receptor-bound protein 10 (GRB10), tyrosine kinase 2 (TYK2) and squamous cell carcinoma antigen recognized by T cells 3 (SART3) (underlined in Fig. 3). After this analysis, we mapped the chromosomal location of the genes found in these clusters in order to visualize genomic regions that could contain a significant number of genes altered in their expression in HPV-positive SCCHN as compared to HPV-negative SCCHN as well as the normal oral epithelium. Fig. 4 shows that several such genes are present in chromosomal regions 1p34–p36 and 12q21–q24 (a complete list of the clustered genes is shown in the supplementary data, Table K). The genes found in the 1p34–p36 region are involved in repression of splicing (FUS interacting protein 1 [FUSIP1]), histone and nucleosomal binding (nuclear autoantigenic sperm protein [NASP], high-mobility group nucleosomal binding domain 2 [HMGN2]) and intracellular vesicle traffic (taxilin alpha [TXLNA]). On the other hand, the genes found in the chromosome region 12q21–q24 are involved in JAK/STAT-signaling pathway (cysteine and glycine-rich protein 2 [CSRP2]), regulation of nuclear architecture (thymopoietin [TMPO/LAP2]), myotonic dystrophy kinase cascade (citron [CIT]) and regulation of mRNA splicing and HIV gene expression and replication (squamous cell carcinoma antigen recognized by T cells 3 [SART3]).

Fig. 3
Unsupervised hierarchical cluster analysis in oropharyngeal tissue samples. From a total of 22,215 transcripts on the microarray, 8,286 genes showed variations in expression across all the samples. From this group of filter genes, we identified 7 clusters ...
Fig. 4
Chromosomal location of genes found to be differentially expressed in the hierarchical cluster analysis. Squares to the right of the chromosomes indicate genes with increased expression in HPV-positive oropharyngeal squamous carcinomas as compared to ...

3.7. Validation of microarray expression data by real-time quantitative RT-PCR analysis

We carried out quantitative real-time RT-PCR (QRT-PCR) analysis of a few representative genes in order to validate the differential gene expression profiles obtained by microarray analysis. Four genes found to be upregulated (CDKN2A, SYCP2, RFC5, ZNF238) and two genes found to be downregulated (KLK8, CRABP2) in HPV-positive SCCHN samples as compared to both the HPV-negative SCCHN as well as normal oral tissues were selected for validation (Fig. 5). The QRT-PCR analysis confirmed that CDKN2A and SYCP2 were up-regulated in all the HPV-positive SCCHN samples as compared to the HPV-negative SCCHN and normal epithelium, whereas RFC5 and ZNF238 were found to be up-regulated in two out of three HPV-positive SCCHN (Fig. 4). Similarly, the KLK8 and CRABP2 genes were downregulated in HPV-positive SCCHN (Fig. 5). However, there was variation in the extent of differential expression of the above genes in individual samples (Fig. 5). The above data showed that the results of QRT-PCR were consistent with those of the microarray analysis, although variations were observed in the fold-difference between these two types of analyses.

Fig. 5
Validation of microarray data in oropharyngeal tissue samples by quantitative RT-PCR. Total RNA from tissue samples was used to verify four upregulated genes (cyclin-dependent kinase inhibitor 2A [CDKN2A], synaptonemal complex protein 2 [SYCP2], zinc ...

Discussion

Recently, an improved understanding of SCCHN has resulted from studies on carcinogenic (tobacco, alcohol, etc.) versus viral (HPV, EBV, etc.) exposures. Several investigators have compared these subgroups in order to identify the pathway (s) and potential therapeutic targets which are unique to these tumours, which are often localized to distinct head and neck sub sites. Indeed, our study is unique since we focused specifically on tumours from the oropharyngeal site, in order to compare gene expression profiles between HPV-16 positive SCCHN tumours and normal squamous oropharyngeal mucosa.

To date, no study has described such a tri-partite analysis, including the epithelial squamous cells from which both tumours were derived. This significantly strengthens our ability to conclude that oncogenic signaling identified in HPV-positive and HPV-negative SCCHN is appropriately attributed to the transformation process and not to the genes expressed in oropharyngeal squamous cells. Although the number of specimens used in our study is small, a unique feature of this study is that we have exclusively utilized tissues derived from the oropharyngeal site. While HPV infection can be identified throughout tumours of the head and neck, a disproportionate frequency is found in the oropharynx (approximately 50%). Thus, identifying tumours in this region eliminates other sub site causes of tumour heterogeneity which have been observed by others. Finally, detailed statistical analysis using multiple tests of significance enhances our ability to identify genes that are expressed uniquely in HPV-16 positive tumours. We have also carried out quantitative RT-PCR analysis to validate the expression of some of the genes found to be differentially expressed in the microarray analysis (Fig. 5). This provides additional confidence in the genes identified by the microarray analysis.

After confirming the expression of the HPV-16 E6 and E7 genes in HPV-positive, HPV-negative SCCHN and normal squamous mucosal samples, we proceeded with the global gene expression analysis. After analyzing the microarray data with two different normalizations and statistical tests (pooled variance t-Test and SAM-Test) in order to identify differentially expressed genes that were robust enough to appear in both analyses, we found that 228 genes were upregulated and 169 downregulated in HPV-positive SCCHN samples as compared to the normal oral tissues. The upregulated genes included those involved in DNA replication and cell cycle regulation such as CDKN2A (p16INK4a), MCM2, PCNA, TOP2A and RBL1 that have been previously identified to be affected in HPV-infected cervical and oral carcinomas.4143 Several studies have shown either direct or indirect regulation of these genes by the tumour suppressor protein p53 (RBL1, PCNA, TOP2A) or by E2F transcription factors (CDKN2A and MCM2).43, 53 One possible explanation for the transcriptional deregulation of this group of genes may be the degradation of p53 and pRB (that bind and repress the activity of the family of E2F transcription factors) by the viral oncogenes E6 and E7, respectively. Interestingly, we also found several genes differentially expressed in our microarray analysis in HPV-positive SCCHN compared to the normal tissue that have been shown to be regulated by p53 or E2F such as the tumour necrosis factor receptor superfamily, member 10b (TNFRSF10B), mutS homolog 6 (MSH6), caldesmon 1 (CALD1), p300/CBP-associated factor (PCAF), collagen, type IV, alpha 1 (COL4A1), nidogen 2 (NID2), astrotactin 2 (ASTN2), cytochrome P450, family 4, subfamily F, polypeptide 3 (CYP4F3), DNA-damage-inducible transcript 4 (DDIT4), chondroitin sulfate proteoglycan 2 (CSPG2), insulin-like growth factor binding protein 6 (IGFBP6), keratin 17 (KRT17), CDC6 cell division cycle 6 homolog (CDC6), replication factor C4, 37kDa (RFC4), flap structure-specific endonuclease 1 (FEN1) and SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 3 (SMARCA3)43, 5355 (see supplementary data, table C). These data are consistent with the results of previous studies and support the notion that HPV-positive SCCHN has a specific transcription profile depends partly on E6 and E7 expression. Specific E6 or E7 knockdown studies will clarify the validity of this conclusion. After comparing the HPV-positive SCCHN samples against the normal oral tissues, we also identified a group of differentially expressed genes previously implicated in tumourigenesis of different tissues but not in SCCHN. These included the upregulated genes SFRP4 and RAD51AP1 and the downregulated gene PRSS3 (Table 2). SFRP4 has been found to be upregulated in prostate cancers and in microsatellite stable endometrial cancers.44, 56 This protein has also been implicated in the inhibition of the Wnt-signaling cascade that is involved in the regulation of cellular proliferation.44 RAD51AP1 is an S phase cell cycle checkpoint gene that has recently been found to be directly induced by E2F1.45 The overexpression of RAD51AP1 further supports the idea that dysregulation of E2F inducible transcripts occurs in HPV-positive SCCHN due to the inactivation of pRB by E7 expression. PRSS3 is a member of the serine protease family that shares significant homology with trypsinogen 1 and 2 and has been classified as a tumour suppressor gene in several types of cancers such as esophageal squamous cell carcinomas, gastric adenocarcinomas and non-small cell lung cancers.57 There is also some evidence that PRSS3 is downregulated by promoter hypermethylation in lung cancers.57 Interestingly our results show that DNMT1, which is responsible for transcriptional silencing through DNA methylation, is upregulated in HPV-positive SCCHN suggesting possible hypermethylation of genes including PRSS3 by this enzyme.

After statistical analysis of the data obtained with HPV-negative SCCHN, we found 79 upregulated and 83 downregulated genes as compared to the normal oropharyngeal squamous mucosa (supplementary data, Table F). The upregulated genes such as PTHLH and ECGF1, and downregulated genes such as IGFBP5 and PDCD4 were also reported in previous SCCHN studies46, 47 providing a validation of our results. At the same time, we found novel upregulated genes such as AKR1C3 and SNAPC1 and downregulated genes such as CLU and RBM3 that were previously not known to be differentially expressed in SCCHN. AKR1C3 is a hydroxysteroid dehydrogenases involved in the regulation of local concentration of androgens and estrogens in hormone dependent tissues like prostate, breast and endometrium.58 AKR1C3 has been found overexpressed at the mRNA and protein level in prostate cancer specifically in the stromal cells.58 SNAPC1 is a subunit of the TBP-TAF complex involved in the transcription of both RNA polymerase II and III dependent small nuclear RNA genes. SNAPC1 has been linked to the tumourigenesis of breast cancers.49 CLU is a multifunctional gene which is involved in spermatogenesis and in the control of the immunological complement cascade.50 It has recently been shown that CLU is downregulated in low- and high-grade human prostate cancers and it may be involved in supporting cell survival and the induction of programmed cell death.50 RBM3, a glycine-rich RNA-binding protein induced by cold-stress, has recently been found to have apoptotic modulatory capabilities with a possible role as a tumour suppressor gene.51 Interestingly, there is evidence that RBM3 can change the expression of some microRNAs and enhance global protein synthesis suggesting an involvement of a homeostatic mechanism that regulates global levels of protein synthesis under normal and cold-stress conditions.52

We found 124 upregulated and 42 downregulated genes in HPV-positive SCCHN as compared to HPV-negative SCCHN (supplementary data, Table I). Among this group of genes, we found a subset of genes (41 upregulated and 19 downregulated) that were also differentially expressed in HPV-positive SCCHN as compared to the normal oropharyngeal mucosa. It is likely that the differential expression of these 60 genes (Table 5) is a consequence of the presence of HPV-16. This group of genes included the upregulated genes SYCP2, RFC5, ZNF238 and DNMT1, and the downregulated genes KLK8 and CRABP2. SYCP2 is part of the synaptonemal complex involved in forming lateral elements and cross bridges that contribute to pairing of sister chromatids during meiosis and probably are involved in the interaction between chromatin and nuclear envelope.59 There is evidence that HPV infection in cervical cells promotes morphological changes in the nuclear membrane as well as condensation of chromatin attached to the inner part of the nuclear membrane.60 Thus, it is possible that SYCP2 may be involved in chromatin-nuclear envelope interactions in HPV-positive SCCHN. A recent study by Slebos and colleagues also reported up-regulation of the SYCP2 and cyclin-dependent kinase inhibitor 2C (CDKN2C) in HPV-positive SCCHN as compared to HPV-negative SCCHN,61 similar to our data obtained using the two statistical methods. Since the data presented by Slebos and colleagues were based solely on the use of the SAM statistical method, we also compared the differentially expressed genes in our study identified only by using this method (supplementary Table H). This analysis showed that the CDKN2A, NEFH and FLJ12973 genes were similarly affected in both the studies. This further strengthens the likelihood that the above genes play important roles in the carcinogenesis of HPV-related SCCHN. Based on the use of SAM statistical method alone, we found that the SMARCA2 gene was up-regulated in HPV-positive SCCHN as compared to the HPV-negative SCCHN (Table H). This gene belongs to a family of proteins involved in transcriptional regulation by conformational changes of nucleosomes.62 The closely-related and functionally similar SMARCA3 gene was found to be up-regulated in the study of Slebos and colleagues.61 Similarly, while replication factor C 5 (RFC5) was found to be overexpressed in HPV-positive SCCHN in our study (Table 5), Slebos and colleagues reported overexpression of RFC4. Theses genes encode part of the RFC protein complex required, in conjunction with PCNA, in chromosomal DNA replication by DNA polymerase delta and epsilon. RFC5 protein not only interacts directly with PCNA but also with RAD24 which is involved in DNA damage checkpoint control in Saccharomyces cerevisiae.63, 64 These findings suggest a possible role of RFC5 upon infection of the oropharyngeal tissue with HPVs that may promote a DNA damage response.

The transcription factor ZNF238 (also known as RP58) is a component of a C2H2-type DNA-binding zinc finger protein that acts as a repressor of transcriptionally silent heterochromatin regions. Interestingly, the DNA methyltransferase protein Dnmt3a directly interacts with ZNF238 and promotes the repression of specific genes by histone deacetylation independently of its methyltransferase activity.65 The overexpression of ZNF238 could explain the downregulation of several genes in HPV-positive SCCHN as a consequence of chromatin condensation by histone deacetylation. KLK8, which is overexpressed in HPV-positive SCCHN, is a member of the human kallikrein gene family of serine proteases with a diverse physiologic function in many tissues. KLK8 is implicated in terminal differentiation of keratinocytes and in the modulation of interaction between cells and fibronectin in extracellular matrix required for tumour growth and invasion. Several studies show different patterns of KLK8 expression such as its downregulation in breast cancers, and in contrast, its overexpression in cervical cancers.66, 67 CRABP2 is a transcription factor that functions as a cytoplasmic retinoic acid binding protein that is highly expressed in human skin. Similar to our results showing its downregulation in HPV-positive SCCHN, CRABP2 is also downregulated in prostate cancer.68 Finally, in the unsupervised hierarchical cluster analysis, we were able to identify a group of genes in five different clusters with significant variation between HPV-positive SCCHN as compared to HPV-negative SCCHN as well as normal oropharyngeal epithelium (Fig.3). Some of the genes found to be differentially expressed in our statistical analysis were also found in these clusters such as ZNF238, DNMT1, MCM3, AKR1C3, GRB10, TYK2 and SART3 (underlined in Fig. 3). The absence of other clustered genes in our supervised statistical analysis could be explained by differences in expression levels below the 2-fold cut-off or by a value below the statistical significance that is considered by every test and overlapping processes. We also identified the localization of the various differentially expressed genes to particular chromosomes (Fig.4). Two regions in chromosome 1 (p34–p36) and 12 (q21–q240) showed a significant number of differentially expressed genes. This may suggest common regulatory pathways involved in the regulation of some of these genes.

Our studies also identified genes whose expression is similarly affected in both HPV-positive and HPV-negative SCCHN as compared to the normal oropharyngeal tissue. For example, STAT1 is overexpressed while PCAF is downregulated in both types of SCCHN. These genes may represent common pathways that are altered in oropharyngeal carcinogenesis. STAT1 is a transcription factor that participates in cellular events such as IFN signaling, development of the mammary gland and embryogenesis. It is considered a tumour suppressor gene since its activation is associated with growth arrest, but studies in head and neck cancers showed an overexpression of STAT1 in well or moderately differentiated tumours in vivo.69, 70 Our findings contrast with the recent publication of Xi and colleagues71 showing the downregulation of STAT1 in SCCHN through the hypermethylation of its promoter.

In summary, our data demonstrates specific changes in cellular gene expression profiles in HPV-positive SCCHN which also express the viral oncogenes. We have identified several genes such as those involved in nuclear structure and meiosis (SYCP2), cell differentiation (CRABP2), DNA repair (RFC5), transcription regulation (ZNF238) and epidermis development (KLK8) that were differentially expressed specifically in HPV-positive SCCHN as compared to both the HPV-negative SCCHN and normal oropharyngeal mucosa that could be used as potential biomarkers for the development of HPV-associated SCCHN.

Supplementary Material

01

Acknowledgments

We thank James Lyons-Weiler for help with the analysis of the microarray data. This work was supported by National Institutes of Health Grant DC016406 and pilot grants from the Hillman Foundation and University of Pittsburgh Cancer Institute. SAK and RLF are Hillman Fellows in Innovative Cancer Research.

Footnotes

Conflict of interest

None.

Novelty and impact of the paper: Using a 22,200 human transcript oligonucleotide microarray platform, we have examined the gene expression profiles in HPV-positive and HPV-negative oropharyngeal squamous cell carcinomas as compared to the normal oropharyngeal mucosa. Our study has identified several new genes whose expression is specifically associated with the presence of HPV-16 in the oropharyngeal squamous mucosa. Furthermore, we have identified several genes whose expression is altered in HPV-negative SCCHN as compared to the normal oral mucosa. Results of our study could contribute to the understanding of pathogenic mechanisms involved in the development of HPV-positive and HPV-negative oropharyngeal cancers and consequently in the identification of potential biomarkers associated with these two subtypes of squamous cell carcinomas.

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