UCSD Bioinformatics Graduate Program, La Jolla, CA, USA.
IET Syst Biol. 2009 Nov;3(6):534-42. doi: 10.1049/iet-syb.2008.0183.
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.
许多用于发现基因表达谱中显著途径的方法已经被开发出来，以促进生物学解释和假设的产生。在这项工作中，作者通过加权 Z 方法提出了一种途径识别方案，该方案将途径成员基因的活性与同一途径中转录因子 (TF) 的靶基因的活性结合起来。作者在 JAK2V617F 突变状态的特发性血小板增多症患者的基因表达谱、发生转移的原发性乳腺癌样本、两个具有预后的独立肺癌表达谱中评估了综合评分方案，发现我们的方法比使用原始途径 [具有数据库中 TF 的途径] 和扩展途径 (包括原始途径的 TF 的靶基因) 的基因集富集分析 (GSEA) 和 Tian 方法更好地识别了癌症类型特异性途径。我们方案的成功表明，添加转录调控信息是利用 mRNA 测量更准确地估计基因表达谱中途径的差异活性的更好方法。
