Oral Cancer News

Source: emedicine.medscape.com
Authors: Perminder S Parmar, MD et al.

Introduction
Since the draft sequence of the human genome was published in 2001 (Lander, 2001), the Cancer Genome Anatomy Project index of tumor genes has classified more than 40,000 genes directly or indirectly involved in one or more cancers (Strausberg, 2001; Strausberg, 2000). Conventional techniques of gene investigation in cancer rely on the identification of single genetic alterations associated with disease. This has proven to be both time consuming and cost ineffective. The introduction of complementary DNA (cDNA) microarray technology in 1995 (Schena, 1995) has helped to facilitate the identification and classification of DNA sequence information and the assignment of functions to these new genes by allowing investigators to analyze expression of thousands of genes simultaneously in a single experiment.

Microarrays are a significant advance because they contain a very large number of genes and because of their small size. Therefore, microarrays are useful when one wants to survey a large number of genes quickly or when the study sample is small. Microarrays may be used to assay gene expression within a single sample or to compare gene expression in 2 different cell types or tissue samples, such as in healthy and diseased tissue. Because a microarray can be used to examine the expression of hundreds or thousands of genes at once, it promises to revolutionize the way gene expression is examined.

Methods
DNA microarrays are small solid supports onto which the sequences from thousands of different genes are attached at fixed locations. The supports themselves are usually glass microscope slides but can also be silicon chips or nylon membranes. The DNA is printed, spotted, or actually synthesized directly onto the support.

Messenger RNA (mRNA) from the sample of interest can serve as a template for producing complementary DNA (cDNA) in the presence of a reverse transcriptase enzyme. This cDNA can then be fluorescently labeled and hybridized to the target gene sequences on the microarray. A confocal scanner then reads the fluorescent intensity of each hybridized sequence in the array. The scanner that records the intensity value is linked to digital image analysis software, which produces a color-coded image of the array, and a quantitative value is recorded for each target gene. The intensity of fluorescence is analyzed and correlates with expression of the gene.

The data produced from a microarray experiment typically constitute a long list of measurements of spot intensities and intensity ratios, generated either by a pair-wise comparison of 2 samples or by a comparison of several samples with a common control. The challenge is to sort through this data to find meaningful results. Because of the complexity of the data sets generated by microarray experiments, the use of data-analysis software is essential. Several commercial and public data-analysis tools have been developed for this purpose.

Current Applications In Head And Neck Oncology
In recent years, the use of microarray technology has been of great interest in head and neck squamous cell carcinoma (HNSCCa). Microarrays may eventually help in the understanding of the disease and ultimately lead to improvements in diagnosis, treatment, and outcome (Warner, 2004). Furthermore, the quantitative and qualitative aspect of microarrays may eventually be exploited to screen for molecular markers of head and neck cancer (Sok, 2003). Numerous expression studies of HNSCCa have been performed (Sok, 2003; Belbin, 2002; Villaret, 2000; Leethanakul, 2000; Squire, 2002).

Belbin et al used complementary DNA (cDNA) microarrays that contained 9216 clones to measure global patterns of gene expression in HNSCCa. Through the use of statistical analysis, they identified 375 differentially expressed genes, which divided 17 patients with head and neck tumors into 2 clinically distinct subgroups based on gene-expression patterns. The results of their analysis demonstrated that gene-expression profiling can be used as a predictor of outcome and highlighted pathways, meriting exploration for possible links to outcome in HNSCC.

Using cDNA subtractive methodology in conjunction with microarray technology to screen for HNSCCa-specific genes, Villaret et al were able to identify 9 known genes that were significantly overexpressed in HNSCCa compared with healthy tissue specimens. In addition, they found 4 previously unidentified genes that were overexpressed in a subset of tumors.

Using a cDNA array of 588 known human cancer-related genes and 9 housekeeping genes, Leethanakul et al demonstrated a consistent decrease in the expression of differentiation markers, such as cytokeratins, and an increase in the expression of numerous signal-transducing and cell cycle regulatory molecules, as well as growth and angiogenic factors and tissue-degrading proteases. The authors also found that most HNSCCas overexpress members of the Wnt and Notch growth and differentiation regulatory system, suggesting that the Wnt and Notch pathways may contribute to squamous cell carcinogenesis.

In their study, Squire et al, using spectral karyotyping (SKY), comparative genomic hybridization (CGH), and microarrays, identified consensus regions of chromosomal imbalance and structural rearrangement in HNSCCa. The authors were able to demonstrate recurrent chromosomal alterations using CGH and SKY and to correlate them to expression array analysis.

In their study, Sok et al, using hierarchical clustering analysis, revealed that the gene-expression profiles obtained from a panel of 12,000 genes could distinguish tumor from nonmalignant tissues. Gene expression changes were reproducibly observed in 227 genes, representing previously identified factors associated with neoplasia. Furthermore, significant expression of the collagen type XI alpha-1 gene and a novel gene were reproducibly observed in all 9 tumors, whereas these genes were virtually undetectable in their corresponding, adjacent nonmalignant tissues.

Future
Despite strides in prevention and advances in treatment, cancer of the head and neck remains a disease of considerable morbidity and mortality. The use of complementary DNA (cDNA) microarray technology to explore gene expression on a global level is rapidly evolving. Although still in its infancy, cDNA microarray technology may prove helpful in the diagnosis, prognosis, and management of head and neck cancer.

Authors and affiliations:
James M Pearson, MD, Staff Physician, Department of Otolaryngology – Head and Neck Surgery, New York Eye and Ear Infirmary; Stimson P Schantz, MD, Head, Department of Otolaryngology, Division of Head and Neck Surgery, New York Eye and Ear Infirmary