A gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence.

BACKGROUND: Oral Squamous Cell Carcinoma (OSCC) is a major cause of cancer death worldwide, which is mainly due to recurrence leading to treatment failure and patient death. Histological status of surgical margins is a currently available assessment for recurrence risk in OSCC; however histological status does not predict recurrence, even in patients with histologically negative margins. Therefore, molecular analysis of histologically normal resection margins and the corresponding OSCC may aid in identifying a gene signature predictive of recurrence. METHODS: We used a meta-analysis of 199 samples (OSCCs and normal oral tissues) from five public microarray datasets, in addition to our microarray analysis of 96 OSCCs and histologically normal margins from 24 patients, to train a gene signature for recurrence. Validation was performed by quantitative real-time PCR using 136 samples from an independent cohort of 30 patients. RESULTS: We identified 138 significantly over-expressed genes (> 2-fold, false discovery rate of 0.01) in OSCC. By penalized likelihood Cox regression, we identified a 4-gene signature with prognostic value for recurrence in our training set. This signature comprised the invasion-related genes MMP1, COL4A1, P4HA2, and THBS2. Over-expression of this 4-gene signature in histologically normal margins was associated with recurrence in our training cohort (p = 0.0003, logrank test) and in our independent validation cohort (p = 0.04, HR = 6.8, logrank test). CONCLUSION: Gene expression alterations occur in histologically normal margins in OSCC. Over-expression of the 4-gene signature in histologically normal surgical margins was validated and highly predictive of recurrence in an independent patient cohort. Our findings may be applied to develop a molecular test, which would be clinically useful to help predict which patients are at a higher risk of local recurrence.

Molecular characterization of salivary gland malignancy using the Smgb-Tag transgenic mouse model.

The molecular mechanisms underlying salivary gland tumorigenesis remain unclear. In order to identify genetic changes that occur during the development of invasive adenocarcinoma from normal salivary gland, we used the Smgb-Tag transgenic mouse model. This transgene induces the progressive development of dysplasia to invasive adenocarcinoma in the submandibular salivary gland. Gene expression patterns from 20 submandibular glands (two normal, nine dysplasia and nine adenocarcinoma samples) were assessed using a mouse 15 K cDNA array. Unsupervised hierarchical clustering was used to group gene expression based on 157 differentially expressed genes distinguishing between dysplasias and adenocarcinomas. Further analysis identified 25 significantly overexpressed and 28 underexpressed cDNA sequences in adenocarcinoma as compared to dysplasia. Differential expression of five genes (Lcn2, Ptn, Cd24a, Mapk6 and Rnps1) was validated by quantitative real-time RT-PCR in a total of 48 mouse salivary gland tissues (seven histologically normal, 13 dysplasias and 28 adenocarcinomas), including the 20 samples analyzed by cDNA arrays. Immunohistochemical analysis was used to validate the expression of Ptn and Cd24a at the protein level in a subset of 16 mouse salivary glands (four normal, five dysplasia and seven adenocarcinoma samples), as well as in 23 human submandibular gland tumors (16 pleomorphic adenomas, three adenoid cystic carcinomas, one acinic cell carcinoma, one adenocarcinoma NOS, one myoepithelial and one mucoepidermoid carcinoma). We thus demonstrated that the Smgb-Tag transgenic mouse model is a useful tool for the identification of genes that are deregulated in salivary gland adenocarcinomas. Our data suggest that Ptn and Cd24a may be genetic markers associated with salivary gland tumorigenesis and/or progression.

Molecular classification of oral cancer by cDNA microarrays identifies overexpressed genes correlated with nodal metastasis.

Our purpose was to classify OSCCs based on their gene expression profiles, to identify differentially expressed genes in these cancers and to correlate genetic deregulation with clinical and histopathologic data and patient outcome. After conducting proof-of-principle experiments utilizing 6 HNSCC cell lines, the gene expression profiles of 20 OSCCs were determined using cDNA microarrays containing 19,200 sequences and the BTSVQ method of data analysis. We identified 2 sample clusters that correlated with the T3-T4 category of disease (p = 0.035) and nodal metastasis (p = 0.035). BTSVQ analysis identified a subset of 23 differentially expressed genes with the lowest QE scores in the cluster containing more advanced-stage tumors. Expression of 6 of these differentially expressed genes was validated by quantitative real-time RT-PCR. Statistical analysis of quantitative real-time RT-PCR data was performed and, after Bonferroni correction, CLDN1 overexpression was significantly correlated with the cluster containing more advanced-stage tumors (p = 0.007). Despite the clinical heterogeneity of OSCC, molecular subtyping by cDNA microarray analysis identified distinct patterns of gene expression associated with relevant clinical parameters. Application of this methodology represents an advance in the classification of oral cavity tumors and may ultimately aid in the development of more tailored therapies for oral carcinoma.

Current applications of microarrays in head and neck cancer research.

OBJECTIVES/HYPOTHESIS: The objective was to introduce microarray technology and its applications in cancer research to the head and neck clinician. STUDY DESIGN: Literature review combined with methodology and examples from the authors' experiences with microarray analysis of tumors of the head and neck. METHODS: Search of literature and the authors' experience was made for technical details, alternative methods of data analysis, available bioinformatics tools, and applications of microarrays in cancer research. RESULTS: Microarrays allow the simultaneous analysis of the expression of thousands of genes. The use of a well-developed microarray study design leads to informative results. There are various bioinformatics resources widely available to aid in the analysis of microarray data. However, there is not yet a gold standard for analysis because this methodology is still evolving. CONCLUSION: Microarray studies may allow researchers to identify genetic changes relevant to diagnosis and prognosis in patients with head and neck cancer. Although still relatively new, this powerful methodology has immense potential to aid in understanding of the genetic changes that are important in head and neck cancer.

Evaluation of chest radiography versus chest computed tomography in screening for pulmonary malignancy in advanced head and neck cancer.

OBJECTIVE: To evaluate the role of chest radiography versus chest computed tomography (CT) in screening for pulmonary malignancy in advanced head and neck squamous cell carcinoma (HNSCC). DESIGN: Retrospective review of imaging. SETTING: Head and neck cancer unit. METHOD: Over a period of 1 year, 26 patients with advanced HNSCC (T3/T4) were screened for pulmonary malignancy with both chest radiography and chest CT prior to definitive therapy. OUTCOME MEASURES: Radiologic evidence of malignancy. RESULTS: Twenty patients had a normal chest radiograph and a normal CT scan. Four patients had a normal chest radiograph but an abnormal CT scan. Three of these patients had a pulmonary malignancy and one had a suspicious lesion that resolved following surgery to the index tumour. Two patients had both an abnormal chest radiograph and CT scan. One of these had a pulmonary malignancy and one had a CT-guided biopsy of the chest lesion 4 weeks postoperatively, which was normal. Chest CT scanning therefore identified three chest malignancies that would have been missed by chest radiography alone. CONCLUSIONS: Chest CT is an effective tool in screening for malignant pulmonary disease in patients with advanced head and neck cancer and should be used instead of chest radiography to avoid false-negative results.