J Cancer 2017; 8(2):278-286. doi:10.7150/jca.17302

Research Paper

Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia

Xuye Yuan1, Jiajia Chen2, Yuxin Lin1, Yin Li1, Lihua Xu3, Luonan Chen4, Haiying Hua5✉, Bairong Shen1

1. Center for Systems Biology, Soochow University, Suzhou, 215006, China.
2. School of Chemistry and Biological Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China.
3. Department of Pediatrics, The First People's Hospital of Lianyungang, Lianyungang, 222002, China.
4. Key Laboratory of Systems Biology, Chinese Academy of Sciences, Shanghai, 200031, China.
5. Department of Hematology, The Third Hospital Affiliated to Nantong University, No. 585 North Xingyuan Road, Wuxi, Jiangsu214041, China.

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Yuan X, Chen J, Lin Y, Li Y, Xu L, Chen L, Hua H, Shen B. Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia. J Cancer 2017; 8(2):278-286. doi:10.7150/jca.17302. Available from http://www.jcancer.org/v08p0278.htm

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Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia.

Keywords: network biomarker, integrative analysis, leukemia.