Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients

Thidathip Wongsurawat; Chin Cheng Woo; Antonis Giannakakis; Xiao Yun Lin; Esther Sok Hwee Cheow; Chuen Neng Lee; Mark Richards; Siu Kwan Sze; Intawat Nookaew; Vladimir A Kuznetsov; Vitaly Sorokin

doi:10.1016/j.dib.2018.01.108

Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients

Data Brief. 2018 Feb 6:17:1112-1135. doi: 10.1016/j.dib.2018.01.108. eCollection 2018 Apr.

Authors

Thidathip Wongsurawat^{1

2}, Chin Cheng Woo³, Antonis Giannakakis¹, Xiao Yun Lin⁴, Esther Sok Hwee Cheow⁵, Chuen Neng Lee^{3

4}, Mark Richards^{6

7}, Siu Kwan Sze⁵, Intawat Nookaew², Vladimir A Kuznetsov^{1

8}, Vitaly Sorokin^{3

4}

Affiliations

¹ Department of Genome and Gene Expression Data Analysis, Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), Singapore 138671, Singapore.
² Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
³ Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore.
⁴ Department of Cardiac, Thoracic and Vascular Surgery, National University Heart Centre, Singapore, National University Health System, Singapore 119228, Singapore.
⁵ School of Biological Sciences, Nanyang Technological University, Singapore 639798, Singapore.
⁶ Cardiovascular Research Institute, National University Heart Centre, Singapore, 119228, Singapore.
⁷ Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore.
⁸ School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore.

Abstract

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.