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.
Hwang
Daehee
D
Department of Chemical Engineering, Room 56-469, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Alevizos
Ilias
I
Schmitt
William A
WA
Misra
Jatin
J
Ohyama
Hiroe
H
Todd
Randy
R
Mahadevappa
Mamatha
M
Warrington
Janet A
JA
Stephanopoulos
George
G
Wong
David T
DT
Stephanopoulos
Gregory
G
D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D020022:Genetic Predisposition to Disease; D016678:Genome; D006801:Humans; D009061:Mouth Mucosa / Q000473:pathology; D009062:Mouth Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D016133:Polymerase Chain Reaction / Q000379:methods; D020133:Reverse Transcriptase Polymerase Chain Reaction; D013223:Statistics as Topic; D014158:Transcription, Genetic