Genome-based identification of diagnostic molecular markers for human lung carcinomas by PLS-DA

Abstract

Partial least squares discriminant analysis (PLS-DA) provides a sound statistical basis for the selection of a limited number of gene transcripts most effective in discriminating different lung tumoral histotypes. The potentialities of the PLS-DA approach are pointed out by its ability to identify genes which, according to current knowledge, are considered molecular markers for colon cancer diagnostics and classification. Indeed application of PLS-DA to in vivo data allowed identification of a set of genes able to discriminate primary lung tumours from colon metastases.