Agreement between genomic and proteomic molecular signatures can be used to identify core disease-related signatures. Recently, proteogenomics analyzing proteomic and genomic data for the same biological samples has emerged to identify these core molecular signatures related to diseases. In this study, we performed mRNA- and exome-sequencing and also global protein and phosphorylation profiling of the tissues collected from 50 gastric cancer tissues and matched normal tissues. By integrating proteomic and genomic datasets, we analyzed agreements between two datasets, identified subgroups of disease samples based on two datasets, and selected cellular pathways represented by both proteomic and genomic datasets as core pathways of gastric cancer. Our results demonstrate the power of analyzing collectively multiple global datasets in selecting the core disease-related pathways. Currently, the clinical implications of the identified core gastric cancer pathways are being verified using independent samples by multiple reaction monitoring technics.
Daehee Hwang1 , Harkyun Kim2 , Sanghyuk Lee3 , Sang-Won Lee4 , Eunok Peak5 , and Eunkyung Yang6 1Department of New Biology, DGIST, Republic of Korea; 2National Cancer Center, Republic of Korea, 3Department of Life Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea; 4Department of Chemistry, Korea University, Republic of Korea; 5Department of Computer Science, Hanyang University, Republic of Korea; and 5Korean Institute of Science and Technology, Republic of Korea
- 2013.10- : Daegu Gyeongbuk Institute of Science & Technology, Daegu, Korea Department of New Biology, Professor
- 2010.9-2011.8 : System Bio-dynamics National Core Research Center, Pohang, Korea School of Interdisciplinary Bioscience and Bioengineering, Director
- 2006.8-2013.9 : Pohang University of Science and Technology, Pohang, Korea School of Interdisciplinary Bioscience and Bioengineering & Chemical Engineering, Assistant & Associate Professor
- 2006.1-2006.8 : Institute for Systems Biology, Seattle, WA Senior Scientist Data Integration and Network Reverse Engineering in Disease Models