Pathway level analysis by augmenting activities of transcription factor target genes

Abstract

Many approaches to discovering significant pathways in gene expression profiles have been developed to facilitate biological interpretation and hypothesis generation. In this work, the authors propose a pathway identification scheme integrating the activity of pathway member genes with that of target genes of transcription factors (TFs) in the same pathway by the weighted Z-method. The authors evaluated the integrative scoring scheme in gene expression profiles of essential thrombocythemia patients with JAK2V617F mutation status, primary breast tumour samples with the status of metastasis occurrence, two independent lung cancer expression profiles with their prognosis, and found that our approach identified cancer-type-specific pathways better than gene set enrichment analysis (GSEA) and Tian's method using the original pathways [pathways that have TFs from database] and the extended pathways (including target genes of TFs of the original pathways). The success of our scheme implicates that adding information of transcriptional regulation is better way of utilising mRNA measurements for estimating differential activities of pathways from gene expression profiles more exactly.