Analysis of Breast Cancer Based on the Dysregulated Network

Yanhao Huo; Xianbin Li; Peng Xu; Zhenshen Bao; Wenbin Liu

doi:10.3389/fgene.2022.856075

Analysis of Breast Cancer Based on the Dysregulated Network

Front Genet. 2022 Feb 15:13:856075. doi: 10.3389/fgene.2022.856075. eCollection 2022.

Authors

Yanhao Huo¹, Xianbin Li¹, Peng Xu^{1

2}, Zhenshen Bao^{1

2}, Wenbin Liu¹

Affiliations

¹ Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
² School of Computer Science of Information Technology, Qiannan Normal University for Nationalities, Duyun, China.

Abstract

Breast cancer is a heterogeneous disease, and its development is closely associated with the underlying molecular regulatory network. In this paper, we propose a new way to measure the regulation strength between genes based on their expression values, and construct the dysregulated networks (DNs) for the four subtypes of breast cancer. Our results show that the key dysregulated networks (KDNs) are significantly enriched in critical breast cancer-related pathways and driver genes; closely related to drug targets; and have significant differences in survival analysis. Moreover, the key dysregulated genes could serve as potential driver genes, drug targets, and prognostic markers for each breast cancer subtype. Therefore, the KDN is expected to be an effective and novel way to understand the mechanisms of breast cancer.

Keywords: breast cancer; cancer-related pathways; driver genes; drug targets; dysregulated network; survival analysis.