DNA Methylation of a GC Repressor Element in the Smooth Muscle Myosin Heavy Chain Promoter Facilitates Binding of the Notch-Associated Transcription Factor, RBPJ/CSL1

OBJECTIVE: The goal of the present study was to identify novel mechanisms that regulate smooth muscle cell (SMC) differentiation marker gene expression. APPROACH AND RESULTS: We demonstrate that the CArG-containing regions of many SMC-specific promoters are imbedded within CpG islands. A previously identified GC repressor element in the SM myosin heavy chain (MHC) promoter was highly methylated in cultured aortic SMC but not in the aorta, and this difference was inversely correlated with SM MHC expression. Using an affinity chromatography/mass spectroscopy-based approach, we identified the multifunctional Notch transcription factor, recombination signal binding protein for immunoglobulin κ J region (RBPJ), as a methylated GC repressor-binding protein. RBPJ protein levels and binding to the endogenous SM MHC GC repressor were enhanced by platelet-derived growth factor-BB treatment. A methylation mimetic mutation to the GC repressor that facilitated RBPJ binding inhibited SM MHC promoter activity as did overexpression of RBPJ. Consistent with this, knockdown of RBPJ in phenotypically modulated human aortic SMC enhanced endogenous SMC marker gene expression, an effect likely mediated by increased recruitment of serum response factor and Pol II to the SMC-specific promoters. In contrast, the depletion of RBPJ in differentiated transforming growth factor-β-treated SMC inhibited SMC-specific gene activation, supporting the idea that the effects of RBPJ/Notch signaling are context dependent. CONCLUSIONS: Our results indicate that methylation-dependent binding of RBPJ to a GC repressor element can negatively regulate SM MHC promoter activity and that RBPJ can inhibit SMC marker gene expression in phenotypically modulated SMC. These results will have important implications on the regulation of SMC phenotype and on Notch-dependent transcription

A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)

Background The Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC, http://www.pcabc.upmc.edu ) is one of the first major project-based initiatives stemming from the Pennsylvania Cancer Alliance that was funded for four years by the Department of Health of the Commonwealth of Pennsylvania. The objective of this was to initiate a prototype biorepository and bioinformatics infrastructure with a robust data warehouse by developing a statewide data model (1) for bioinformatics and a repository of serum and tissue samples; (2) a data model for biomarker data storage; and (3) a public access website for disseminating research results and bioinformatics tools. The members of the Consortium cooperate closely, exploring the opportunity for sharing clinical, genomic and other bioinformatics data on patient samples in oncology, for the purpose of developing collaborative research programs across cancer research institutions in Pennsylvania. The Consortium's intention was to establish a virtual repository of many clinical specimens residing in various centers across the state, in order to make them available for research. One of our primary goals was to facilitate the identification of cancer-specific biomarkers and encourage collaborative research efforts among the participating centers. Methods The PCABC has developed unique partnerships so that every region of the state can effectively contribute and participate. It includes over 80 individuals from 14 organizations, and plans to expand to partners outside the State. This has created a network of researchers, clinicians, bioinformaticians, cancer registrars, program directors, and executives from academic and community health systems, as well as external corporate partners - all working together to accomplish a common mission. The various sub-committees have developed a common IRB protocol template, common data elements for standardizing data collections for three organ sites, intellectual property/tech transfer agreements, and material transfer agreements that have been approved by each of the member institutions. This was the foundational work that has led to the development of a centralized data warehouse that has met each of the institutions’ IRB/HIPAA standards. Results Currently, this “virtual biorepository” has over 58,000 annotated samples from 11,467 cancer patients available for research purposes. The clinical annotation of tissue samples is either done manually over the internet or semi-automated batch modes through mapping of local data elements with PCABC common data elements. The database currently holds information on 7188 cases (associated with 9278 specimens and 46,666 annotated blocks and blood samples) of prostate cancer, 2736 cases (associated with 3796 specimens and 9336 annotated blocks and blood samples) of breast cancer and 1543 cases (including 1334 specimens and 2671 annotated blocks and blood samples) of melanoma. These numbers continue to grow, and plans to integrate new tumor sites are in progress. Furthermore, the group has also developed a central web-based tool that allows investigators to share their translational (genomics/proteomics) experiment data on research evaluating potential biomarkers via a central location on the Consortium's web site. Conclusions The technological achievements and the statewide informatics infrastructure that have been established by the Consortium will enable robust and efficient studies of biomarkers and their relevance to the clinical course of cancer. </jats:sec