Abstract A81: Global gene regulatory and protein interaction networks in breast cancer metastasis

Abstract

Abstract Purpose: Invasion-metastasis cascades that underlie macroscopic metastases remain poorly understood. Tackling such a complexity demands systems biology approaches by means of filtering and integrating myriad data. To gain a fine resolution of mechanisms underlying the process of metastasis, here we reconstruct global gene regulatory and protein interaction networks that potentially drive breast cancer metastasis. Procedures: A systematic literature review and a comprehensive data mining of well-curated cancer gene datasets were carried out to uncover a core metastasis gene set (CMGS) using an in house Boolean logic framework. Meanwhile, a gene regulatory network (GRN) was built up to distinguish between key cancer driver genes and passenger genes through integration of multiple large-scale genomic studies of breast cancer. Furthermore, CMGS was projected onto the latest HRPD protein interaction network (PIN) and the GRN to derive metastasis-specific protein interaction network (mPIN) and gene regulatory network (mGRN), respectively. To gain mechanistic insights of mPIN and mGRN, a key network driver analysis was employed to identify critical hub nodes of the networks as key regulators. Results: We demonstrate that CMGS is of significantly higher connectivity in both PIN and GRN than those not in CMGS, suggesting its critical controlling power to the system. As expected, both mPIN and mGRN are most enriched for angiogenesis, integrin signaling, and p53 pathways. Moreover, these metastasis specific networks are also enriched for well-known metastasis-related pathways such as Wnt, TGF-beta, and FGF pathways. Surprisingly, inflammatory pathways, such as chemokine signaling and B-cell activation pathways are also over-represented in the networks. The top hub genes of mPIN include AR, ABL1, ESR1, AKT1, SMAD4, TP53, CSNK2A1, MAPK1, PIK3R1 and SMAD3. This hub gene set is distinct from the top key regulators of mGRN including ACTA2, ACTL6A, ADM, AEBP1, ARF1, ARPC4, ATM, AURKA and BIRC5. Notably, all the top ten drivers of mGRN except ATM and AURKA are not in CMGS, suggesting the novel targets of metastasis uncovered through our integrative network analysis. Indeed, ARF1, encoding the GTPase ADP-ribosylation factor 1, has been shown to play an important role in both cancer cell proliferation and migration. Moreover, the subnetwork regulated by ARF1 clearly links to inflammatory key players, especially via microvesicle related biological process. Importantly, both driver gene sets are tightly connected by TP53 and MAPK8 physically and genetically, suggesting the strong connection between p53 pathway and inflammatory response as MAPK8 activation is pivotal for chemokine mediated inflammation processes especially for TNF-alpha. Conclusion: Taken together, our global metastasis-specific protein interaction and gene regulation networks as well as their key regulators shed light on a potential trajectory of invasion-metastasis cascades that enable the progress of breast cancer metastasis, underscoring the instrumental role of a novel signaling network involving p53, microvesicle associated ARF1, and TNF-alpha mediated inflammatory response pathways. Citation Format: Bin Zhang, Yongzhong Zhao, Jun Zhu. Global gene regulatory and protein interaction networks in breast cancer metastasis. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Invasion and Metastasis; Jan 20-23, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;73(3 Suppl):Abstract nr A81.