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Hunt for the tipping point during endocrine resistance process in breast cancer by dynamic network biomarkers Free
Rui Liu 1,† , Jinzeng Wang 2,3,† , Masao Ukai 4,5,† , Ki Sewon 5,† , Pei Chen 1,6 , Yutaka Suzuki7, Haiyun Wang 2,* , Kazuyuki Aihara 8,* , Mariko Okada-Hatakeyama 4,5,9,* , and Luonan Chen 6,8,10,11,12,*
1 School of Mathematics, South China University of Science and Technology, Guangzhou 510640, China
2 School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
3 National Research Center for Translational Medicine (Shanghai), Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
4 Graduate School of Medical Life Science, Yokohama City University, Yokohama 230-0045, Japan
5 Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama 230-0045, Japan
6 Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of
Sciences, Shanghai 200031, China
7 Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
8 Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan
9 Laboratory of Cell Systems, Osaka University, Osaka 565-0871, Japan
10 Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
11 School of Life Science and Technology, ShanghaiTech University, Shanghai 200031, China
12 Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai 201210, China
† These authors contributed equally to this work.
*Correspondence to:Luonan Chen, E-mail: lnchen@sibs.ac.cn; Haiyun Wang, E-mail: wanghaiyun@tongji.edu.cn; Kazuyuki Aihara, E-mail: aihara@sat.t. u-tokyo.ac.jp; Mariko Okada-Hatakeyama, E-mail: mokada@protein.osaka-u.ac.jp
J Mol Cell Biol, Volume 11, Issue 8, August 2019, 649-664,  

Acquired drug resistance is the major reason why patients fail to respond to cancer therapies. It is a challenging task to determine the tipping point of endocrine resistance and detect the associated molecules. Derived from new systems biology theory, the dynamic network biomarker (DNB) method is designed to quantitatively identify the tipping point of a drastic system transition and can theoretically identify DNB genes that play key roles in acquiring drug resistance. We analyzed time-course mRNA sequence data generated from the tamoxifen-treated estrogen receptor (ER)-positive MCF-7 cell line, and identified the tipping point of endocrine resistance with its leading molecules. The results show that there is interplay between gene mutations and DNB genes, in which the accumulated mutations eventually affect the DNB genes that subsequently cause the change of transcriptional landscape, enabling full-blown drug resistance. Survival analyses based on clinical datasets validated that the DNB genes were associated with the poor survival of breast cancer patients. The results provided the detection for the pre-resistance state or early signs of endocrine resistance. Our predictive method may greatly benefit the scheduling of treatments for complex diseases in which patients are exposed to considerably different drugs and may become drug resistant.


Volume 11, Issue 8
August 2019