Ilias Alevizos

Oral cancer in vivo gene expression profiling assisted by laser capture microdissection and microarray analysis.

Large scale gene expression profiling was carried out on laser capture microdissected (LCM) tumor and normal oral epithelial cells and analysed on high-density oligonucleotide microarrays. About 600 genes were found to be oral cancer associated. These oral cancer associated genes include oncogenes, tumor suppressors, transcription factors, xenobiotic enzymes, metastatic proteins, differentiation markers, and genes that have not been implicated in oral cancer. The database created provides a verifiable global profile of gene expression during oral carcinogenesis, revealing the potential role of known genes as well as genes that have not been previously implicated in oral cancer.

Genomic dissection for characterization of cancerous oral epithelium tissues using transcription profiling

Genome-wide and high-throughput functional genomic tools offer the potential of identifying disease-associated genes and dissecting disease regulatory patterns. There is a need for a set of systematic bioinformatic tools that handles efficiently a large number of variables for extracting biological meaning from experimental outputs. We present well-characterized statistical tools to discover genes that are differentially expressed between malignant oral epithelial and normal tissues in microarray experiments and to construct a robust classifier using the identified discriminatory genes. Those tools include Wilks lambda score, error rate estimated from leave-one out cross-validation (LOOCV) and Fisher Discriminant Analysis (FDA). High Density DNA microarrays and Real Time Quantitative PCR were employed for the generation and validation of the transcription profile of the oral cancer and normal samples. We identified 45 genes that are strongly correlated with malignancy. Of the 45 genes identified, six have been previously implicated in the disease, and two are uncharacterized clones.

Odontogenic carcinoma: a functional genomic comparison with oral mucosal squamous cell carcinoma

Intraosseous squamous cell carcinomas of the mandible arise de novo or secondary to a tumor or transformed cyst epithelium. Current diagnostic tests frequently fail to distinguish between these tumors, leading to confusing classification schemes. We report the functional genomic analysis of a mandibular odontogenic carcinoma. Malignant keratinocytes from the lesion were isolated using laser capture microdissection. Target sample generated from the total RNA of the LCM-procured cells was used to hybridize high-density oligonucleotide arrays. Functional genomic analysis of the odontogenic carcinoma database compared with four oral mucosal squamous cell carcinoma gene expression databases was performed. Preliminary results suggest a small subset of genes distinguish this odontogenic carcinoma from oral mucosal epidermoid carcinomas.

Linking hepatic transcriptional changes to high-fat diet induced physiology for diabetes-prone and obese-resistant mice.

Insulin resistance is characterized by high insulin levels and decreased responsiveness of tissues to the clearance of glucose from the bloodstream. This study maintained the diabetes-prone C57BL/6J and obese-resistant A/J mice strains on a high-fat diet for 12 weeks to transcriptionally profile the liver for changes caused by high fat diet. In the 8th week of the experiment, the C57BL/6J mice began exhibiting signs of insulin resistance, while the A/J mice did not show any such indications during the course of the experiment. A regression model of partial least squares between serum insulin measurements and the liver gene expression profile for the C57BL/6J mice on a high-fat diet was constructed in an effort to quantitatively link the physiological measurement with the gene expressions. A series of discriminating genes between high fat and chow fed mice was generated for both the C57BL/6J and A/J strains. These discriminatory genes contain information about the mechanisms responsible for the development of insulin resistance, and the compensation for a high fat diet, respectively. The results identified several genes involved in the development of insulin resistance and serve as a framework for other studies involving other organs affected by this systemic disease.

Dissecting oral cancer through large-scale gene expression profiling of laser capture microdissection samples

Dissecting oral cancer through large-scale gene expression profiling of laser capture microdissection samples