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Home > Programs and Groups > NCI-Designated Programs > Cancer Genetics and Genomics
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NCI-Designated Programs

Cancer Genetics and Genomics

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Duke Resources

Duke Institute for Genome Sciences & Policy

Leadership

Huntington F. Willard, PhD
willa009@mc.duke.edu

Program Overview

The Cancer Genetics and Genomics Research Program includes a group of outstanding investigators making important and major contributions to the understanding of the molecular mechanisms underlying oncogenesis, the identification of genetic and genomic variants that contribute to and confer susceptibility to cancer, and the development of genomic signatures that are promising for translation into clinical practice.

In partnership with the Duke Institute for Genome Sciences & Policy, this is a very interactive and integrated group of investigators that form a cohesive unit focused on the common goals of identifying genes and genomic alterations involved in oncogenesis and their role in the development of human cancer.
 
The activities of the program are organized into two specific areas of scientific focus that include cancer genetics, with a focus on the identification of genes that define familial risk of onset for disease as well as the spectrum of mutations and genomic alterations within cancer genomes; and cancer genomics, involving programs applying comprehensive genome-wide datasets to better understand the functional characteristics of tumors.
 
A major strength of the Cancer Genetics and Genomics Research Program is the synergistic activities that tie together the investigators -- discoveries in work on oncogenic signaling pathways feed the cancer genetics and genomics activities.

Similarly, advances made in genomic approaches to cancer outcomes have impacted the basic study of oncogenic pathways. As an extension of the fundamental exploration of cancer genetics and genomics, studies in the program have led to the development of a series of genomic signatures that characterize and predict different cancer states and can be used to predict cancer outcomes as well as pathway activation tied to response to targeted therapeutics. 

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