The OSU-IU Center for Cancer Systems Biology (CCSB, formerly designated as OSU-IU ICBP) has assembled a team of 25 computational and bench scientists to study epigenetic control of critical signaling networks in prostate, breast, and ovarian cancers. Based on our recent progress and preliminary findings, we will test the hypothesis that epigenetic deregulation of androgen receptor (AR), estrogen receptor a (ERa), or TGF-ß/SMAD4 signaling-mediated transcriptional networks underlies the transition of a hormone-/chemo-sensitive phenotype to a hormone-/chemo-insensitive phenotype in cancer. We anticipate that the study will yield significant insight into the role of permissive and non-permissive chromatin in cancer and drug-resistant disease.

Using integrated epigenomics data, we will employ probabilistic and stochastic modeling approaches to define two different modes of signaling-mediated transcription: 1) ligand-dependent genomic functions and 2) ligand-independent genomic functions. In mode 1, activation of signal transduction results in a ligand-nuclear receptor interaction. This interaction then triggers a cascade of events that enables the binding of transcription factor complexes to specific DNA sequences to activate or deactivate target genes. Secondly, in the absence of ligand (mode 2), transcription factors can be phosphorylated through kinase signaling that directly or indirectly regulates gene transcription. Although other modes of transcriptional regulation not directly mediated by AR, ERa, or TGF-ß/SMAD4 networks have been previously described, these “non-genomic” signaling pathways will be the secondary focus of our study.

In addition to the modes of signaling-mediated transcription described above, DNA structure in TFBSs and promoter targets must maintain a permissive state in order to facilitate binding of gTF/cTF complexes. Epigenetic mechanisms play an important role in controlling this maintenance function. Post-translational modifications of histones are well-known epigenetic modifications, and the sum total of combinatorial histone modifications is usually referred to as the “histone code”, which is “written” and “read” by various modifying enzymes and co-factors. While histone methylation in general is associated with a closed chromatin structure (i.e., condensed nucleosomes) that prevents the binding of a TF to its binding site, histone acetylation, in contrast, often leads to chromatin-decondensation, allowing for TF binding. Acquired DNA methylation is also related to a condensed chromatin state in GC-rich regions, called CpG islands. If this epigenetic event is found in a promoter CpG island, the transcription of its corresponding gene is usually silenced.

While histone modifications and DNA methylation are the two best-studied epigenetic phenomena, spatial interactions between TFs and the promoter target are also important for regulating gene transcription. Emerging evidence indicates that TFBSs are located far away from the transcription start sites (TSSs) of target genes. Through a process known as “chromosome looping”, TFs and their collaborating factors are brought into close proximity of promoter targets for transcriptional activation or de-activation. This spatial interaction is therefore a newly discovered epigenetic component that will further be explored in this proposal.

In this study, we will employ "omics" approaches to investigate how AR, ERa, and TGF-b/SMAD4 signaling networks are exploited by hormone-/chemo-insensitive cancer cells to gain a growth advantage. Instead of organizing specific projects according to these biological themes (as we did in the previous iteration), the tasks have been rearranged to place the major emphasis on computational modeling, thereby allowing for maximum interactions among experimental and computational scientists.

Omics data will be generated by bench scientists and deposited in the QUEST database. Utilizing integrated omics data, three teams of modelers will develop computational tools to analyze spatial TFBS-promoter interactions (Aim 1), network dynamics of transcription hubs (Aim 2), and DNA motif prediction for TFBSs and promoter targets (Aim 3). Collaborating efforts among these modelers will allow us to define epigenetic control of gene repression. To validate these computational findings, bench scientists will conduct appropriate functional assays for prostate, breast, and ovarian cancer cell types (Aim 4). The experimental findings may either support or refute epigenetic hypotheses. If the outcomes do not support the hypothesis due to inaccurate prediction of TFBS-promoter interactions, computational scientists will refine modeling tools for new queries. Bench scientists may then re-test the revised hypotheses. The fourth modeling team (i.e., pilot project) will implement computational tools for additional queries of miRNA-mediated gene expression. These epigenomics data and modeling tools will also be used to train young systems scientists who will develop skills to master both bench work and computational tools.