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

Hwang, Daehee; Alevizos, Ilias; Schmitt, William A; Misra, Jatin; Ohyama, Hiroe; Todd, Randy; Mahadevappa, Mamatha; Warrington, Janet A; Stephanopoulos, George; Wong, David T; Stephanopoulos, Gregory

doi:10.1016/S1368-8375(02)00108-2

« Previous Next »Oral Oncology
Volume 39, Issue 3 , Pages 259-268, April 2003

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

Daehee Hwang
- Department of Chemical Engineering, Room 56-469, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
Ilias Alevizos
- Department of Chemical Engineering, Room 56-469, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
William A Schmitt
- Department of Chemical Engineering, Room 56-469, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
Jatin Misra
- Department of Chemical Engineering, Room 56-469, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
Hiroe Ohyama
- Laboratory of Molecular Pathology, Department of Oral Medicine and Diagnostic Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
Randy Todd
- Laboratory of Molecular Pathology, Department of Oral Medicine and Diagnostic Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
Mamatha Mahadevappa
- Affymetrix, Inc., Santa Clara, CA 95051, USA
Janet A Warrington
- Affymetrix, Inc., Santa Clara, CA 95051, USA
George Stephanopoulos
- Department of Chemical Engineering, Room 56-469, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
David T Wong
- Laboratory of Molecular Pathology, Department of Oral Medicine and Diagnostic Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
Gregory Stephanopoulos
- Department of Chemical Engineering, Room 56-469, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
- Corresponding author. Fax: +1-617-253-9695

Received 11 July 2002; accepted 7 August 2002.

Abstract

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.

Keywords: Oral epithelial cancer, DNA microarray, Discriminatory genes, Pattern recognition, Statistical analysis