Multi-omic Pathway and Network Analysis to Identify Biomakers for Hepatocellular Carcinoma

被引:0
作者
Barefoot, Megan E. [1 ,2 ]
Varghese, Rency S. [1 ,2 ]
Zhou, Yuan [1 ,2 ]
Di Poto, Cristina [1 ,2 ]
Ferrarini, Alessia [1 ,2 ]
Ressom, Habtom W. [1 ,2 ]
机构
[1] Georgetown Univ, Dept Oncol, Washington, DC 20007 USA
[2] Georgetown Univ, Lombardi Comprehens Canc Ctr, Washington, DC 20007 USA
来源
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2019年
关键词
multi-omic; network and pathway analysis; HCC; metabolomics; transcriptomics; glycoproteomics; LIVER; IDENTIFICATION; HEMOPEXIN; XCMS;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The threat of Hepatocellular Carcinoma (HCC) is a growing problem, with incidence rates anticipated to near double over two decades. The increasing burden makes discovery of novel diagnostic, prognostic, and therapeutic biomarkers distinguishing HCC from underlying cirrhosis a significant focus. In this study, we analyzed tissue and serum samples from 40 HCC cases and 25 patients with liver cirrhosis (CIRR) to better understand the mechanistic differences between HCC and CIRR. Through pathway and network analysis, we are able to take a systems biology approach to conduct multi-omic analysis of transcriptomic, glycoproteomic, and metabolomic data acquired through various platforms. As a result, we are able to identify the FXR/RXR Activation pathway as being represented by molecules spanning multiple molecular compartments in these samples. Specifically, serum metabolites deoxycholate and chenodeoxycholic acid and serum glycoproteins C4A/C4B, KNG1, and HPX are bioniarker candidates identified from this analysis that are of interest for future targeted studies. These results demonstrate the integrative power of multi-omic analysis to prioritize clinically and biologically relevant biomarker candidates that can increase understanding of molecular mechanisms driving HCC and make an impact in patient care.
引用
收藏
页码:1350 / 1354
页数:5
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