Résumé
Background: Owing to the explosion of information generated by human genomics, analysis ofpublicly available databases can help identify potential candidate genes relevant to the cancerousphenotype. The aim of this study was to scan for such genes by whole-genome in silico subtractionusing Expressed Sequence Tag (EST) data.Methods: Genes differentially expressed in normal versus tumor tissues were identified using acomputer-based differential display strategy. Bcl-xL, an anti-apoptotic member of the Bcl-2 family,was selected for confirmation by western blot analysis.Results: Our genome-wide expression analysis identified a set of genes whose differentialexpression may be attributed to the genetic alterations associated with tumor formation andmalignant growth. We propose complete lists of genes that may serve as targets for projectsseeking novel candidates for cancer diagnosis and therapy. Our validation result showed increasedprotein levels of Bcl-xL in two different liver cancer specimens compared to normal liver. Notably,our EST-based data mining procedure indicated that most of the changes in gene expressionobserved in cancer cells corresponded to gene inactivation patterns. Chromosomes andchromosomal regions most frequently associated with aberrant expression changes in cancerlibraries were also determined.Conclusion: Through the description of several candidates (including genes encoding extracellularmatrix and ribosomal components, cytoskeletal proteins, apoptotic regulators, and novel tissuespecificbiomarkers), our study illustrates the utility of in silico transcriptomics to identify tumor cellsignatures, tumor-related genes and chromosomal regions frequently associated with aberrantexpression in cancer.