Shortcuts in genome-scale cancer pharmacology research from multivariate analysis of the National Cancer Institute gene expression database

Application of a soft multivariate statistical procedure, called PLS, parti al least squares modelling in latent variables or projections to latent str uctures, allows extensive exploitation of the enormous amount of informatio n embedded in the National Cancer Institute gene expression and antitumour screen databases. Interpretation of the statistical results provides new si gnificant biological insights such as classification of human tumour cell l ines based on their gene expression patterns, evaluation of the influence o f gene transcripts on drug efficacy and assessment of their selectivity for classes of compounds which act by the same mechanism, and identification o f uncharacterized gene expression targets involved in cancer chemotherapy. Among them, the transcripts GC11121, GC17689, and GC18564 (unknown gene pro ducts extremely selective for RNA/DNA antimetabolites) are indicated by the present work as deserving high priority in future molecular studies. (C) 2 001 Elsevier Science Inc. All rights reserved.