J Cancer 2015; 6(1):54-65. doi:10.7150/jca.10631
Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data
1. Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA;
2. Bon Secours Cancer Institute, Richmond VA, USA;
3. Division of Surgical Oncology, Walter Reed National Military Medical Center, Bethesda, MD, USA;
4. Department of Public Health School of Hunter College, City University of New York, NYC, USA;
5. Department of Mathematics and Statistics, Georgetown University, Washington DC, USA;
6. Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA, USA;
7. Genetics and Genomics Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Wang J, Zuo Y, Man Yg, Avital I, Stojadinovic A, Liu M, Yang X, Varghese RS, Tadesse MG, Ressom HW. Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data. J Cancer 2015; 6(1):54-65. doi:10.7150/jca.10631. Available from https://www.jcancer.org/v06p0054.htm
The advancement of high throughput omic technologies during the past few years has made it possible to perform many complex assays in a much shorter time than the traditional approaches. The rapid accumulation and wide availability of omic data generated by these technologies offer great opportunities to unravel disease mechanisms, but also presents significant challenges to extract knowledge from such massive data and to evaluate the findings. To address these challenges, a number of pathway and network based approaches have been introduced. This review article evaluates these methods and discusses their application in cancer biomarker discovery using hepatocellular carcinoma (HCC) as an example.
Keywords: Biological pathways, system biology, high-throughput omics data, cancer biomarker.