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JMD 2004, Vol. 6, No. 3
Copyright © 2004 American Society for Investigative Pathology & Association for Molecular Pathology

Gene Expression Screening of Salivary Gland Neoplasms

Molecular Markers of Potential Histogenetic and Clinical Significance

Shin-ichiro Maruya*, Hyung-Woo Kim{dagger}, Randal S. Weber{ddagger}, Jack J. Lee{dagger}, Merril Kies§, Mario A. Luna*, John G. Batsakis* and Adel K. El-Naggar*

From the Departments of Pathology, * Biostatistics, {dagger} Head and Neck Surgery, {ddagger} and Medical Oncology, § The University of Texas M.D. Anderson Cancer Center, Houston, Texas


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Salivary gland neoplasms comprise phenotypically and biologically diverse lesions of uncertain histogenesis. The molecular events associated with their development and clinicopathological heterogeneity remain unknown. To reveal these events, we performed microarray expression analysis using a nylon-filter membrane platform on 18 primary lesions representing the most common benign and malignant types. Our study identified a small set of genes that are differentially altered between normal salivary gland tissues and benign and malignant tumors. Of the 5000 genes arrayed, 136 genes were differentially expressed by normal tissue, benign tumors, and various malignant neoplasms. Hierarchical clustering analysis differentiated between adenoid cystic carcinomas (ACCs) and other malignant subtypes. Non-ACC specimens manifested overlapping patterns of gene expression within and between tumors. Most of the differentially expressed genes share functional similarities with members of the adhesion, proliferation, and signal transduction pathways. Our study identified: 1) a set of genes that differentiate normal tissue from tumor specimens, 2) genes that differentiate pleomorphic adenoma and ACCs from other malignant salivary gland neoplasms, and 3) different patterns of expression between ACCs arising from major and minor salivary gland sites. The differentially expressed genes provide new information on potential genetic events of biological significance in future studies of salivary gland tumorigenesis.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Salivary gland neoplasms are uncommon lesions1, 2, 3 characterized by widely varied phenotypic features and unpredictable clinical outcomes.4, 5, 6, 7, 8, 9 Such overlapping histologies and variable biological progression pose clinical and differential diagnostic challenges. Despite efforts to identify new parameters to improve their diagnosis and therapy, little progress in the management of patients with these tumors has been achieved in the last 3 decades.

Previous cytogenetic and molecular genetic analyses of these tumors have been limited in scope and size and did not account for their inherent morphological and biological heterogeneity.10, 11, 12, 13, 14, 15, 16 Large-scale gene expression analysis offers a broad approach to exploring the genetic alterations of functional significance in tumors and identifying potential diagnostic and prognostic markers. Recent studies using these technologies have identified different profiles in gene expression among histological phenotypes in several tumor types,17, 18, 19, 20 including a recent analysis of adenoid cystic carcinomas (ACCs).20

To identify new genetic markers of clinical relevance, we analyzed the gene expression profile of 18 primary tumors representing the major benign and malignant subtypes of these tumors using a membrane-based DNA microarray platform.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Tissue Samples
Fresh frozen tissues from 18 primary salivary gland tumors [three each pleomorphic adenoma (PMA), mucoepidermoid carcinoma (MEC), acinic cell carcinoma (ACI), salivary duct carcinoma (SDC), and 6 ACCs] and matched normal tissues excised at the Department of Head and Neck Surgery and Pathology at the University of Texas M.D. Anderson Cancer Center between 1995 and 2000 formed the materials of this study. Tissue samples were immediately taken from surgical specimens, frozen in liquid nitrogen, and stored at –80°C until used.

RNA Extraction
Total RNA was extracted from normal salivary gland tissues and tumors (1.5 mg) using TRIzol reagent (Life Technologies, Inc., Gaithersburg, MD) according to the manufacturer’s protocol with some modifications. The quality of RNA samples was verified by electrophoresis on 2% agarose gel.

cDNA Microarray Analysis
The gene filter used in this study was composed of a nylon filter array GF200 (Research Genetics, Huntsville, AL) containing ~5000 genes, including function-known genes and unknown expressed sequence tags. Probe preparation and hybridization were performed as previously described.21 The filter was wrapped in 3M Whatman paper and scanned by the Cyclone Phosphor Imaging System (Packard Bioscience Company, Meriden, CT).

Statistical Considerations
Our main objectives were to identify differentially expressed genes in tumor and normal tissue and to perform molecular classification using the bidirectional cluster analysis algorithm. A total of 5453 genes were spotted on GF200 with 192 control-positive spots containing the total genomic DNA (tgDNA) and 192 housekeeping genes (HKGs). A logarithm 10-based transformation was applied to all raw intensity data. The hexbin scatter plot and scatter plot matrix using the S-PLUS (S-PLUS 200 Guide, 2000) were used to display the log intensity of gene expression of tumor versus normal tissue for each matched-pair experiment. Brushing technique was applied to highlight selected genes such as tgDNA or HKG. From the scatter plots, we found that tgDNA clustered by itself with moderate intensity (indicating adequate hybridization) in both normal and tumor samples. Because tgDNA is used for the purpose of providing positive controls and it contains both human and nonhuman genes, we removed the tgDNA genes from further analysis. There were a total of 8055 unique genes included in the analysis.

Normalization of the gene expression intensity in the normal and tumor tissues for each pair was performed by plotting the logarithm-transformed intensity in tumor versus normal tissue; fitting a nonparametric regression line using the loess (locally weighted regression scatter plot smoothing) method; and assuming that most genes do not vary greatly in their expression levels (the goal was to move the loess line to superimpose with the 45° line where x and y coordinates are the same). This was achieved by projecting each point to the 45° line along the x axis and the y axis and then taking the average of the two. The differential expression was computed by forming the difference between normalized, log-transformed expressions in tumor and normal tissue and then taking the arithmetic average in replicated experiments. To identify the expressed genes between normal and tumor tissues for each of the two subtypes we applied the t-test with 5 degrees of freedom and select genes with P < 0.01. Method 5 takes the variability among patients into consideration by dividing the mean average by its SE. The Q-Q plots show that the statistics follow t-distribution with 5 degrees of freedom.

Hierarchical clustering analysis was performed on both GF200 differentially expressed genes of the 12 cases as previously described.21 Bidirectional clustering was performed to cluster both patients and genes. The Pearson correlation coefficient was used as the similarity metric, and the average-linkage method was applied to assemble all elements into a clustering tree.

The magnitude of gene was initially analyzed by Pathways Software (Research Genetics) and normalized using the standardization and normalization of microarray data method.22 A total of 5069 genes were normalized after excluding 192 positive control spots and 192 HKGs. Hierarchical clustering analysis and computation of t-statistics of the normalized log ratios were done as previously reported.21 Genes that exhibited an average intensity ratio more than twice as much as tumor or normal tissue in each histological subtype were considered to be differently expressed.

Real-Time Quantitative Reverse-Transcriptase Polymerase Chain Reaction (RT-PCR)
To assess the gene expression level of telencephalin (ICAM5), which was expressed differently in ACCs than in major salivary gland tissue in the cDNA microarray analysis, we performed a real-time quantitative RT-PCR under the endogenous control of the ß-actin gene using the ABI Prism 7900HT sequence detection system (Applied Biosystems, Foster City, CA). Mixtures of primer and FAM-labeled TaqMan probe of ICAM5 and ß-actin were obtained from Assays-on-Demand gene expression products (Applied Biosystems). Five samples of normal salivary gland, five cases of PMA, five cases of ACC from major salivary gland (ACC-major), and six cases of ACC from minor salivary gland (ACC-minor) were used in this assay. PCRs were performed in duplicate in 25-µl samples containing 100 ng of total RNA. The ABI TaqMan one-step RT-PCR master mix reagents kit was used for specimen analysis. The reaction conditions were 30 minutes at 48°C, 10 minutes at 95°C, and 40 cycles of 15 seconds at 95°C and 1 minute at 60°C.

A relative quantification method ({Delta}{Delta}CT method) was used for the quantification of gene amplification recognized as cycle numbers. The quantity of target genes, normalized by the HKG (ß-actin), was evaluated as 2–{Delta}{Delta}CT, where {Delta}{Delta}CT is {Delta}CTtarget – {Delta}CTß-actin. Higher 2–{Delta}{Delta}CT values reflect a relatively higher amount of ICAM5 transcript.

Immunohistochemistry
Paraffin-embedded tissue blocks from all tumors were available and a review of the corresponding hematoxylin and eosin-stained sections was performed. Selected blocks were sectioned at 4 µm for immunostaining monoclonal antibody for von Hippel-Lindau protein Ab-1 (VHL) (clone Ig22; Lab Vision/Neomarkers, Fremont, CA). Immunohistochemistry was performed using the avidin-biotin complex (ABC) method.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
The patients included nine men and nine women between 28 and 89 years of age. Tumor sites included 12 in parotid glands, 2 in submandibular glands, and 4 in oral minor glands. Histologically, there were six ACCs, and three each of SDC, MEC, ACI, and PMA.

Differential Gene Expression
Figure 1Go shows the plotted data based on the t-statistic and the simple average value of tumor to normal tissue. As depicted diagonally, the expression of most genes did not differ between normal salivary tissues and tumors, and only small number of overexpressed and underexpressed genes by both simple average and t-test methods are shown in the upper right and lower left corners of the graph.



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  		Figure 1. Example of comparative data analysis using the t-statistic and the mean of the gene expression for salivary gland tumors relative to normal tissue.

 
PMAs
Tables 1Go and 2Go list the genes that were differentially expressed between PMA and normal salivary tissues. Fifteen known genes were overexpression and nine were underexpressed in PMA including type I collagen, calponin, galectin-9 isoform, transforming growth factor-ß, and MDR-5. Genes that differentiated between PMA and carcinomas are listed in Table 3Go . Among these were S-100ß, galectin-9 isoform, vimentin, and tyrosine kinase receptor, which were more highly expressed in adenomas than in carcinomas.


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  		Table 1. Highly Expressed Genes in PMA Compared to Normal Salivary Gland

 

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  		Table 2. Highly Expressed Genes in Normal Salivary Gland Compared to PMA

 

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  		Table 3. Genes that Classify Carcinoma and Pleomorphic Adenoma

 
Salivary Gland Carcinomas
The analysis of these tumors showed differences between ACCs and other types of malignant tumors (Figure 2)Go . The hierarchical clustering analysis showed that the latter group, including SDC, MEC, and ACI, shares overlapping gene expression patterns. The known differentially expressed genes are listed in Tables 4 to 13Go Go Go . Thirteen known genes were differentially expressed in MEC and ACI, 37 in SDC, and 59 in ACCs. Highly expressed genes included the genes for immunoglobulin J chain and chemokine HCC-1 in MEC, transcriptional factor IIF and SON DNA-binding protein in ACI, and von Hippel Lindau gene (VHL) in SDC. Underexpressed genes included the genes for the D13S824E locus in MEC, SKAP 55 protein in ACI, and KIAA0074 and prostate carcinoma tumor antigen in SDC.



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  		Figure 2. Heat map of 49 genes selected to classify ACCs and other carcinomas. Expression levels are relative to matched normal salivary gland tissue. The colors ranging from red to green correspond to increased and decreased gene expression. P11 to P6: ACC; P21.1 to P23.1: MEC; P31.1 to P33.1: ACI; P41.1 to P43.1: SDC.

 

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  		Table 4. Highly Expressed Genes in MEC Compared to Normal Salivary Gland

 

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  		Table 5. Highly Expressed Genes in Normal Salivary Gland Compared to MEC

 

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  		Table 6. Highly Expressed Genes in ACI Compared to Normal Salivary Gland

 
Interestingly, a distinctively different pattern within the ACCs was noted based on their site of origin (Figure 3)Go . According to the heat map of clustering within ACC cases, 11 known genes were found to discriminate between ACC cases from major salivary gland (ACC-major) and ACC from minor salivary gland (ACC-minor). Tables 10 to 13Go Go Go list the known genes that are differentially expressed in ACC-major and ACC-minor. The expression of keratin 5 and keratin 13 was markedly lower in ACC-major than in ACC-minor.



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  		Figure 3. Heat map of 17 genes selected to classify ACC-major and ACC-minor. Expression levels are relative to matched normal salivary gland tissue. The colors ranging from red to green correspond to increased and decreased gene expression. P11 to P13: ACC-major; P14 to P16: ACC-minor.

 

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  		Table 10. Highly Expressed Genes in ACC-Major Compared to Normal Salivary Gland

 

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  		Table 11. Highly Expressed Genes in Normal Salivary Gland Compared to ACC-Major

 

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  		Table 12. Highly Expressed Genes in ACC-Minor Compared to Normal Salivary Gland

 
Quantitative RT-PCR Analysis of ICAM5
To confirm the microarray results real-time quantitative RT-PCR was performed for the ICAM5 gene. Comparative levels of each gene were normalized using the cycle number of ß-actin amplification. As shown in Figure 4Go , the average expression levels of ICAM5 gene estimated as 2–{Delta}{Delta}CT value were elevated by 1.2-fold in PMA, 1.0-fold in ACC-minor, and 8.1-fold in ACC-major compared with the average value in normal salivary gland tissue (Figures 4Go and 5)Go . Comparative value was significantly higher in ACC-major than other groups (P < 0.01).



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  		Figure 4. Results of relative gene expression of ICAM5 under the endogenous control of ß-actin in normal salivary gland tissue, PMA, and ACC derived from major salivary gland (ACC-major) and minor salivary gland (ACC-minor).

 


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  		Figure 5. Representative graph of quantitative RT-PCR for ICAM5 and ß-actin as an endogenous control in normal salivary gland (A) and ACC (B).

 
Immunohistochemistry for VHL
Immunostaining of archival tissue from tumor used in array analysis showed restricted cytoplasmic positivity of the VHL protein in only SDCs (Figure 6)Go and negative staining in other benign and malignant salivary gland tumors (Figure 6 C and D)Go .



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  		Figure 6. Photomicrograph of VHL-immunostaining in normal parotid gland with faint cytoplasmic staining in small duct (A), negative staining in ACI (B), and strong cytoplasmic staining in two different SDCs (C and D).

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Our study identified a small set of genes that are differentially expressed between normal salivary tissues and tumor specimens. These genes included several known and yet to be identified expressed sequence tags. Among the highly expressed genes in PMA are the genes for S-100, vimentin, type-1 collagen, and calponin gene markers that have been previously reported in PMA.23, 24, 25, 26 Similarly, extracellular matrix and basement membrane-related genes including the genes for laminin and type IV collagen have been found to be widely expressed in myoepithelium or terminal duct origin salivary gland tumors.27 We also noted that the ß-chain isoform of S-100 was up-regulated only in PMA, not in other salivary gland carcinomas (Table 3)Go . S-100 protein isoforms have previously been shown to differentiate myoepithelial cells in certain salivary gland neoplasms.24

Hierarchical cluster analysis delineated ACCs from other types of salivary carcinomas on the basis of differentially expressed genes of factors mostly related to the cell cycle, cell matrix, and extracellular adhesions. Of the down-regulated genes identified is the T-cell differentiation protein MAL, a putative cell-cycle tumor suppressor associated with several human cancers.21, 28, 29 In vitro induction of the MAL transcript was achieved by treatment with 5-aza-2'-deoxycytidine in some esophageal cancer cell lines,29 supporting a major role for methylation in the down-regulation of this gene. Interestingly, the overexpression of plasminogen activator and integrin family members seen in our study has been previously reported in ACC.20, 30

We, however, identified novel up-regulated genes in ACC, including the telencephalin (ICAM5) precursor-associated gene, a neural adhesion factor molecule,31 and the spermidine/spermine N1-acetyltransferase gene, a polyamine metabolism-associated gene.32 Our quantitative RT-PCR analysis validated the overexpression of ICAM5 mRNA in ACC in the microarray analysis. To our knowledge, this is a first report of up-regulated ICAM5 in any human cancers. ICAM5 is a cell surface glycoprotein molecule that is mapped at chromosome 19p13.2 and possesses structural and functional similarities with ICAM1. However, its expression has been limited to the telencephalic neurons.31, 33 Previous studies have shown that overexpression of ICAM1 is associated with distant metastasis in gastric cancer, lung cancer, and melanoma.34, 35, 36 The ICAM5 gene may also induce factors such as BDNF and NCAM adhesion molecules, which have been associated with perineural invasion in ACC.37, 38

We also observed unique gene expression patterns within and between different carcinoma subtypes. Of these, the mRNA of the sequence located at the D13S824E locus on chromosome 13q12 was found to be markedly underexpressed in MEC. This sequence shares marked homology to the sequence encoding the myotubularin-related protein-6 (MTMR6), which possess a structural resemblance to the PTEN tumor suppressor gene.39 Significantly, underexpression and overexpressed genes in ACI include SKAP 55, the enhancer of T-cell adhesion to antigen-presenting cells through fibronectin and ICAM1,40 and the transcription factor IIF (TFIIF), respectively. The latter is recognized as a positive regulator of androgen receptor-mediated transcription.41

Moreover, we observed the high expression of VHL tumor suppressor gene in SDC. The inactivation of this gene by genetic and epigenetic alterations is associated with familial and sporadic renal cell carcinoma.42, 43 However, high expression of VHL protein was previously reported in carcinomas of the lung, prostate, colon, breast, bladder, and thyroid in addition to renal cell carcinoma.44, 45 In addition, it has also been reported that VHL-overexpressing renal cell carcinoma cell lines resist chemically induced apoptosis through bcl-2 activation in vitro.46 These findings suggest that the VHL gene may play different oncogenic roles in tumorigenesis depending on the tumor type.

In general, our findings indicate that the functional properties of the genes identified appear to be linked to their putative origin from different salivary duct anatomical segments. This is supported by the genetic differences in PMA and ACC from those of acinar- and major duct-derived malignant tumors. Further studies of the genes associated with these tumors may lead to the identification of prognostic and therapeutic targets of these tumors.


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  		Table 7. Highly Expressed Genes in Normal Salivary Gland Compared to ACI

 

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  		Table 8. Highly Expressed Genes in SDC Compared to Normal Salivary Gland

 

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  		Table 9. Highly Expressed Genes in Normal Salivary Gland Compared to SDC

 

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  		Table 13. Highly Expressed Genes in Normal Salivary Gland Compared to ACC-Minor

 

   Footnotes
 
Address reprint requests to Adel K. El-Naggar, M.D., Ph.D., The University of Texas M.D. Anderson Cancer Center, Department of Pathology, Unit 85, 1515 Holcombe Blvd., Houston, TX 77030. E-mail: anaggar{at}mdanderson.org

Supported by the Kenneth D. Muller Professorship and Specialized Programs of Research Excellence for the Head and Neck.

Accepted for publication March 2, 2004.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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