In depth characterization of individual human tumor cell lines might serve to explore the concept of future personalized cancer management. To address this question, standardized serum-free cultures of normal oral keratinocytes (NOK) were compared relative to the tongue squamous cell carcinoma line LK0412 via multiple bioinformatics-based assessments of transcript and protein profiles. Two-dimensional polyacrylamide electrophoresis identified 27 differentially expressed abundant proteins in LK0412. Gene Ontology enrichment analysis indicated alterations of the regulation of cell death, protein metabolism, energy pathways and various binding activities. Based on the protein-enriched GO-categories, the web-based program AffyAnnotator conducted the selection of 119 differently expressed transcripts from the microarray data in LK0412 vs. NOK. Ingenuity Pathway Analysis of these pertubated transcripts then revealed associations to cancer, cellular assembly and organization as well as cellular movement, and moreover, identified an 11-gene profile composed of central regulators within the networks. Notably, the differently expressed proteins and transcripts, as well as the 11-gene profile, variably classified two independent public microarray data sets of totally 38 normal and 57 tumor tongue samples, including a power of 95% accuracy from the 11-gene profile. Additional evaluation of the derived signatures by so called “signature evaluation tool” (implementing the Golub's weighted voting algorithm), identified reduced gene number signatures that similarly discriminated the normal from the tongue tissues in both data sets up to an accuracy rate of 95%. The overall results suggest that combined bioinformatics processing of transcript and protein data might serve as a constructive strategy for identification of potential candidate biomarkers in individual tumor samples, that may then serve to aid in cancer management. Additionally, gene signature profiles, generated as described, may serve to improve current efforts to accurately classify normal and tumor tongue tissues.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2169.