Combining network topology with transcriptomic data for identifying radiosensitive gene signatures

Article type: Research Article

Authors: Cui, Qinghua | Sun, Tingting^* | Nie, Zongyao

Affiliations: Urban Construction Department, Anhui Vocational College of City Management, Hefei, Anhui, China

Correspondence: [*] Corresponding author: Tingting Sun, Urban Construction Department, Anhui Vocational College of City Management, Hefei, Anhui, China. E-mail: dasunting@163.com.

Abstract: Radiotherapy sensitivity assay can gain insight into radiation biology and clinically improve radiotherapy of cancer patients. This paper proposesd to combine gene network information and gene expression profiles for identifying radiosensitive signatures. Specifically, the association of each gene with survival fraction (SF) induced by radiation was first estimated using Spearman correlation measure and then adjusted based on network topology. We used directed random walk (DRW) algorithm to assess the topological importance of genes. Two types of molecular networks, protein-to-protein interaction network and gene network, were considered in the DRW algorithm. The identified signatures were verified via pathways enrichment analysis, shown rich in disease pathways. The findings suggested useful guidelines for the clinical practice of radiotherapy of cancer patients.

Keywords: Sensitive gene of tumor radiotherapy, radiation therapy, pathway enrichment analysis, network topology

DOI: 10.3233/JCM-180848

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 19, no. 3, pp. 565-579, 2019