Differential signaling regulatory networks governing hormone refractory prostate cancers

To understand the organization of the biological networks that might potentially govern the pathogenesis of hormone refractory prostate cancer(HRPC), we investigated the transcriptional circuitry and signaling in androgen-dependent 22Rv1 and MDA PCa 2b cells, androgen- and estrogen-dependent LNCaP cells, and androgen-independent DU 145 and PC-3 prostate cancer(PCa) cell lines. We used microarray analyses, quantitative real-time PCR, pathway prediction analyses, and determination of Transcription Factor Binding Site(TFBS) signatures to dissect HRPC regulatory networks. We generated graphical representations of global topology and local network motifs that might be important in prostate carcinogenesis. Many important putative biomarker ‘target hubs' were identified in the current study including AP-1, NF-?B, EGFR, ERK1/2, JNK, p38 MAPK, TGF beta, VEGF, PDGF, CD44, Akt, PI3 K, NOTCH1, CASP1, MMP2 and AR. Our results suggest that complex cellular events including autoregulation, feedback loops and cross-talk might govern progression from early lesion to clinically diagnosed PCa, as well as metastatic potential of pre-existent high-grade prostate intraepithelial neoplasia(HG-PIN) and/or advancement to HRPC. The identification of TFBS signatures for TCF/LEF, SOX9 and ELK1 in the regulatory elements suggests additional biomarkers for the potential development of chemopreventive/therapeutic strategies against PCa. Taken together, in this study, we have identified putative biomarker ‘target hubs' in the architecture of PCa signaling networks, and investigated TFBS signatures that might enhance our understanding of key regulatory nodes in the progression and pathogenesis of HRPC.

Elucidation of regulatory interaction networks underlying human prostate adenocarcinoma

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.