Area of Interest
Integrative Cancer Genomics/Gene Regulation/Chromatin/Computational Biology
Specialized transcriptional programs that determine proper expression levels of genes largely govern cell type identity and function in the human body. Aberrant perturbations of gene transcription programs due in large part to genetic changes such as DNA mutations but also natural variation contribute to cancer phenotypes including uncontrolled proliferation and resistance to therapies. The goal in the Furey lab is to better understand mechanisms of gene regulation in both normal and diseased cells. These studies are enabled by the development of genome-wide experiments employing high-throughput sequencing technologies that provide comprehensive and detailed information about the molecular state of a cell. Currently, there are two related efforts in the lab to accomplish this goal.
Genome-wide Identification and Characterization of Gene Regulatory Elements in Human Cell Types
The vast majority of DNA in a given cell is wrapped in a chromatin structure called a nucleosome that prevents the binding of proteins that regulate gene expression levels. DNase-seq and FAIRE-seq experiments identify regions of nucleosome-free open chromatin that contain gene regulatory elements. As part of the ENCyclopedia Of DNA Elements (ENCODE) project, we and our collaborators have mapped open chromatin sites in over one hundred human cell types. By comparing open chromatin patterns, we are beginning to identify regulatory elements with apparent cell-type specific functions and are exploring methods to link these elements to particular genes. This work will contribute to both the identification of key regulatory elements specific to cancer cells as well as a better understanding the effect of DNA mutations and natural genetic variation in genomic regions that do not correspond to gene sequences.
Integration of Heterogeneous Genomic Data to Uncover Molecular Traits of Cancer Phenotypes
Alterations to gene expression programs responsible for cancer phenotypes may be related to several cellular characteristics including its particular genotype, single-base mutations, large chromosomal changes, and epigenetic properties. Data can now be obtained genome-wide for each of these potential contributors. The Furey lab is developing statistical models and computational software to integrate information from these diverse data types to uncover a more complete picture of molecular changes responsible for cancer phenotypes. Key to this approach is a focus on whole biological pathways, such as those related to growth and metabolism, instead of individual genes.
Awards and Honors
- 1998-1999 UC Regents Fellowship
- 2000-2002 Achievement Rewards for Scientists (ARCS) Fellowship
- 2000 Thomson ISI New Hot Papers, Computer Science, January
- 2003 http://www.esitopics.com/nhp/2003/january- 03-Terrence Furey.html "Support Vector Machine Classification and Validation of Cancer Tissue Samples Using Microarray Expression Data," Bioinformatics, 16(10): 906-914 (2000).