Gene expression profiling and construction of a putative gene regulatory network of bladder cancer tumor-initiating cells
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Zhuoyuan Xin1,2,*, Zhao Yang3,*, Jianting Xu1,**, Chaoying Li2, Tong Shao2, Guoqing Wang2 and Chong Li3,4
1Cancer Centre, First Hospital of Jilin University, Changchun, China
2Department of Pathogenobiology, College of Basic Medical Science, Jilin University, Changchun, China
3Core Facility for Protein Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
4Beijing Jianlan Institute of Medicine, Beijing, China
*These authors contributed equally to this work
Chong Li, email: firstname.lastname@example.org
Guoqing Wang, email: email@example.com
Keywords: bladder cancer; gene expression profile; tumor-initiating cells; stem-like cells; gene regulatory network
Received: August 24, 2017 Accepted: September 22, 2017 Published: November 30, 2017
Human bladder cancer tumors have been shown to contain a subpopulation of cells with stem-like characteristics that may trigger tumor growth, recurrence, and metastasis. These cells, known as tumor-initiating cells (TICs), would be effective diagnostic tools and valuable therapeutic targets. Here, we report the isolation of TICs from seven bladder cancer cell lines and show that TICs from different sources vary on their ability to form tumorspheres in vitro and generate xenografts in vivo, which suggest they are remarkably heterogeneous. We used the Affymetrix PrimeViewTM Human Gene Expression Array to analyze gene expression profiles of bladder TICs, which may help understand their tumorigenic capacities and develop novel treatments specifically targeted toward these cells. We then constructed a transcription factor-gene regulatory network that includes three key transcription factors that are involved in cell survival, differentiation, proliferation, and apoptosis. We validated our findings by analyzing mRNA expression of the key genes in this network in 24 clinical tissues. Our results suggest that this transcription factor-gene regulatory network could be useful in the development of clinical diagnostic tools and therapy approaches for bladder cancer.
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