Facilitated By

San Antonio Medical Foundation

Omics Analysis of Three-Dimensional Transcriptional Regulation

UT Health San Antonio

The UT Health San Antonio, with missions of teaching, research and healing, is one of the country’s leading health sciences universities.

Principal Investigator(s)
Jin, Victor
Funded by
NIH
Research Start Date
Status
Active

In this R01 proposal, we plan to use an integrative genomics (Omics) analysis to test two central hypotheses: 1) TF modules form different transcriptional chromatin hubs and co-regulate dynamical interactomes; and 2) an environmental or cellular stimulus such as hormones triggers different transcription modulators to facilitate dynamical chromatin conformation changes. The ultimate goal is to model and analyze TF modules from one- dimension (1D) to three-dimension (3D) scale and describe the relationship between chromatin organization and TF modules. Using a model system of ERa in breast cancer, our studies will examine 1) E2-mediated dynamic TF transcription modules and chromatin interactions; and 2) these hubs and interacting domains are altered in tamoxifen resistant breast cancer cells. The successful completion of our proposed studies will be of value to the genomics community and biologists in general, which may result in the better understanding of the principle of 3D transcriptional regulation and the regulatory role of E2/ERa in endocrine resistant breast cancer. PUBLIC HEALTH RELEVANCE: Gene regulation is controlled not only by the interaction of transcription factors (TFs) bound next to each other in a linear fashion, but also via three-dimensional (3D) conformation of specific chromatin that brings different TFs into close spatial contact. We will use the estrogen receptor-a (ERa) upon estrogen (E2)-treatment in MCF7 and tamoxifen (Tam)-treatment in MCF7-T at five time points respectively, as a model system (named ERa-omics) to study three-dimension (3D) transcriptional regulation and the regulatory role of E2/ERa in endocrine resistant breast cancer. The successful completion of our proposed studies will be of value to the genomics community and biologists in general.

Disease Modeling
Cancer