Wongsurawat Thidathip, Woo Chin Cheng, Giannakakis Antonis, Lin Xiao Yun, Cheow Esther Sok Hwee, Lee Chuen Neng, Richards Mark, Sze Siu Kwan, Nookaew Intawat, Kuznetsov Vladimir A, Sorokin Vitaly
Department of Genome and Gene Expression Data Analysis, Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), Singapore 138671, Singapore.
Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
Data Brief. 2018 Feb 6;17:1112-1135. doi: 10.1016/j.dib.2018.01.108. eCollection 2018 Apr.
This article contains further data and information from our published manuscript [1]. We aim to identify significant transcriptome alterations of vascular smooth muscle cells (VSMCs) in the aortic wall of myocardial infarction (MI) patients. Microarray gene analysis was applied to evaluate VSMCs of MI and non-MI patients. Prediction Analysis of Microarray (PAM) identified genes that significantly discriminated the two groups of samples. Incorporation of gene ontology (GO) identified a VSMCs-associated classifier that discriminated between the two groups of samples. Mass spectrometry-based iTRAQ analysis revealed proteins significantly differentiating these two groups of samples. Ingenuity Pathway Analysis (IPA) revealed top pathways associated with hypoxia signaling in cardiovascular system. Enrichment analysis of these proteins suggested an activated pathway, and an integrated transcriptome-proteome pathway analysis revealed that it is the most implicated pathway. The intersection of the top candidate molecules from the transcriptome and proteome highlighted overexpression.
本文包含了我们已发表手稿[1]中的更多数据和信息。我们旨在确定心肌梗死（MI）患者主动脉壁中血管平滑肌细胞（VSMC）的显著转录组改变。应用微阵列基因分析来评估MI患者和非MI患者的VSMC。微阵列预测分析（PAM）确定了能显著区分两组样本的基因。基因本体（GO）分析确定了一个能区分两组样本的VSMC相关分类器。基于质谱的iTRAQ分析揭示了两组样本间有显著差异的蛋白质。 Ingenuity通路分析（IPA）揭示了心血管系统中与缺氧信号相关的主要通路。对这些蛋白质的富集分析表明存在一条激活的通路，综合转录组-蛋白质组通路分析显示这是最相关的通路。转录组和蛋白质组中顶级候选分子的交集突出了过表达情况。
