Rewiring of regulatory networks in breast cancer by transcription factor isoforms
- Rewiring of regulatory networks in breast cancer by transcription factor isoforms
List of Collaborating Institutions
- Brigham & Women’s Hospital
Dana-Farber Cancer Institute
Harvard Medical School
One of the ultimate goals of cancer systems biology is to generate predictive and dynamic models of tumorigenesis by identifying and quantifying all perturbed functional interactions in a cancerous cellular system. The central hypothesis of our CSBC is that functional perturbations emerging from cancer-specific gene expression of alternative isoforms are crucial for tumorigenesis. Genome alterations such as amplification, deletion, translocations and mutations, are often considered primary events of cancer progression. However, cancer-specific isoforms resulting from alternative splicing, alternative sites of transcriptional initiation, and/or alternative transcriptional termination sites, have also been shown to have functional impact on tumorigenesis.
Changes in gene regulatory networks (GRNs) by transcription factor (TF) isoforms have been shown to play a major role in tumorigenesis and metastasis in multiple types of cancer. What remains unclear is the extent to which differences in TF isoforms between normal and cancer tissue affect global GRNs and how such regulatory network rewiring leads to altered gene expression programs in cancer. In this CSBC project, we are characterizing and modeling the effect(s) of large numbers of breast cancer-specific TF isoforms in the context of cancer interactome networks. We will combine network modeling and high-throughput systematic experimental strategies at the level of molecular protein-protein and protein-DNA interactions to predict cancer drivers and suppressors.
Altogether, this project will contextualize and functionalize large numbers of TF isoforms implicated in breast cancer. Lessons learned from this project will lead to the identification of novel cancer drivers and suppressors, the generation of mechanistic models of GRN rewiring in cancer and provide a framework for the design of novel therapeutics. The resulting hypotheses will be tested experimentally using various large-scale functional assays in breast cancer cells as a model system. As part of the experimental testing, we will establish state-of-the-art genome editing methodologies for testing the effects of isoform-specific perturbations on GRNs in mammalian cells.
Martha L. Bulyk, Ph.D.
Dr. Bulyk is a Professor in the Division of Genetics in the Department of Medicine, and also a Professor of Pathology, at Brigham & Women’s Hospital and Harvard Medical School. She is also an Associate Member of the Broad Institute of MIT and Harvard, and an Associate Member of the Dana Farber Cancer Institute’s Center for Cancer Systems Biology. Her group is focused on studies of transcription factors, DNA regulatory elements, gene regulatory networks, and the effects of genetic variation, using a variety of experimental and computational approaches including new technologies, they have developed.
Juan Fuxman Bass, Ph.D.
Dr. Fuxman Bass is an Assistant Professor of Biology at Boston University where his laboratory studies the structure, evolution, function and rewiring of gene regulatory networks (GRNs). GRNs can be rewired by germline or somatic noncoding variants or by transcription factor coding variants or isoforms that lead to different diseases including cancer. Although there has been some progress in characterizing these variants in silico, progress towards experimental characterization has been limited due to the lack of suitable methods. Juan pioneered an innovative experimental approach to characterize noncoding variants and transcription factor coding variants associated with disease.
Marc Vidal, Ph.D.
Dr. Vidal is Director of the Center for Cancer Systems Biology (CCSB) at Dana-Farber Cancer Institute and Professor of Genetics at Harvard Medical School. His research is focused on understanding complex macromolecular networks and systems operating inside cells. The main hypothesis is that cells can be better understood as a wiring diagram of dynamic molecular interactions and that perturbations of such interactions underlie most genotype-phenotype relationships. He pioneered the concept of “interactome network modeling”, based on interdisciplinary strategies to discover fundamental systems properties in the human interactome network and unravel fundamental relationships between cellular systems, genetic variation, host-pathogen relationships and human disease.