title: Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes.
abstract: With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi) of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA). Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.
authors.affiliation: Research Center for Clinical & Translational Medicine, Beijing 302 Hospital, Beijing 100039, China. liuyang@bmi.ac.cn.
authors.forename: Yang
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Science and technology on Parallel and Distributed Processing Laboratory, National University of Defense Technology, Changsha 410073, China. yinxy1992@sina.com.
authors.forename: Xiaoyao
authors.initials: X
authors.lastname: Yin
authors.affiliation: Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou 313000, China. zhongjing1003@126.com.
authors.forename: Jing
authors.initials: J
authors.lastname: Zhong
authors.affiliation: Science and technology on Parallel and Distributed Processing Laboratory, National University of Defense Technology, Changsha 410073, China. ny_guan@nudt.edu.cn.
authors.forename: Naiyang
authors.initials: N
authors.lastname: Guan
authors.affiliation: Science and technology on Parallel and Distributed Processing Laboratory, National University of Defense Technology, Changsha 410073, China. zgluo@nudt.edu.cn.
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Luo
authors.affiliation: Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou 313000, China. malisha362@126.com.
authors.forename: Lishan
authors.initials: L
authors.lastname: Min
authors.affiliation: Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou 313000, China. yaoy333@126.com.
authors.forename: Xing
authors.initials: X
authors.lastname: Yao
authors.affiliation: Beijing Institute of Radiation Medicine, Beijing 100850, China. boxc@bmi.ac.cn.
authors.forename: Xiaochen
authors.initials: X
authors.lastname: Bo
authors.affiliation: Huzhou Key Laboratory of Molecular Medicine, Huzhou Central Hospital, Huzhou 313000, China. dlc21@126.com.
authors.forename: Licheng
authors.initials: L
authors.lastname: Dai
authors.affiliation: Beijing Institute of Radiation Medicine, Beijing 100850, China. huibai13@hotmail.com.|No. 451 Hospital of PLA, Xi'an 710054, China. huibai13@hotmail.com.
authors.forename: Hui
authors.initials: H
authors.lastname: Bai
keywords: Cancer Gene Census; DNA methylation; breast cancer; drug target; gene set enrichment analysis; library of integrated network-based cellular signatures