Elucidation of regulatory interaction networks underlying human prostate adenocarcinoma

作     者：Sujit Nair Celine Liew Tin-Oo Khor Li Cai Ah-Ng Tony Kong Sujit Nair;Celine Liew;Tin-Oo Khor;Li Cai;Ah-Ng Tony Kong

作者机构：Amrita Cancer Discovery Biology Laboratory and Amrita School of Pharmacy Amrita Vishwa Vidyapeetham University Ponekkara P.O. Kochi-682041 Kerala India Department of Pharmaceutics Rutgers The State University of New Jersey Piscataway NJ-08854 USA Department of Pharmacy National University of Singapore 18 Science Drive 4 Singapore--117543 Department of Biomedical Engineering Rutgers the State University of New Jersey Piscataway NJ-08854 USA 

出 版 物：《Journal of Chinese Pharmaceutical Sciences》 (中国药学（英文版）)

年 卷 期：2015年第24卷第1期

页      面：12-27页

核心收录：

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

基　　金：RO1 CA 094828 to Prof. Ah-Ng Tony Kong and in part by R21 CA133675 to Dr.Li Cai both from the National Institutes of Health(NIH) 

主　　题：Human prostate cancer Microarray Biological network Biomarker 

摘      要：The incidence of prostate cancer is rising in the Asia-Pacific region as well as other countries. Androgen-ablation therapy is clinically useful in the androgen-dependent phenotype however, many patients progress to hormone refractory prostate cancer that is difficult to treat and needs newer interventions that are more effective. The objective of this study was to determine functionally-relevant biological networks, to appreciate the potential crosstalk between signaling members, and to identify biomarker signatures in prostate cancer. We used microarray analyses to identify key genes that were upregulated or down regulated at least five-fold in human prostate cancer and constructed canonical interaction networks that are important in prostate cancer through metabolomics analyses. Our prostate cancer network architecture revealed several key biomarkers including ERK1/2, JNK, p38, MEK, PI3 K, NFκB, AP-1, 14-3-3, VEGF, PDGF, Rb, WNT8 A, WNT10 A, CD44, ESR2, FSH and LH. Furthermore, the top ten transcription factors identified by TFBS-association signature analysis in the regulatory elements of co-regulated biomarkers were delineated, which may crosstalk with upstream or downstream genes elicited in our network architecture. Taken together, our results demonstrate that the regulatory interaction networks in prostate cancer provide a universal view of crosstalk between important biomarkers, i.e., key players in the pathogenesis of this disease. This will facilitate more rapid screening of functional biomarkers in early/intermediate drug discovery.