Oncological Sciences

Sean Tavtigian, PhD

Sean Tavtigian

Position:
Associate Professor, Oncological Sciences

Phone: (801) 587-4258
Lab Phone: (801) 213-4238
Fax: (801) 585-0900
Email: sean.tavtigian@hci.utah.edu

Mailing Address:

Huntsman Cancer Institute
2000 Circle of Hope
Salt Lake City, UT 84112-5550

Links:
Huntsman Cancer Institute Biography

Research Description
Research in my lab concentrates on two areas of genetic susceptibility to cancer. The first is identification and characterization of intermediate-risk and high-risk cancer susceptibility genes. The second is analysis of unclassified variants that are observed during the clinical testing of established high-risk cancer susceptibility genes.

Historically, most of the known high-risk cancer susceptibility genes were found either by linkage analysis/ positional cloning or by mutation screening of established high-risk susceptibility genes' biochemical pathway "nearest-neighbors". While the linkage analysis/ positional cloning approach is nearly obsolete, next-generation sequencing enables a number of new strategies for gene identification. On of these is whole-exome mutation screening in pedigrees as a method to identify relatively high-risk susceptibility genes. Another is biochemical pathway-based mutation screening in a case-control format as a method to identify intermediate-risk susceptibility genes. We are pursuing breast cancer genetics projects in both of these areas and are likely to expand to prostate cancer or colon cancer projects in the near future.

Clinical mutation screening of high-risk cancer susceptibility genes such as BRCA1, BRCA2, MLH1, and MSH2 will often find clearly pathogenic mutations, providing very useful information for the clinical management of high-risk patients and their close relatives. However, about 10% of patients who undergo mutation screening are found to carry an unclassified sequence variant (UV). Observations of UVs are problematic for clinical mutation screening services, for clinical cancer genetics, and for the patients. We have developed a bioinformatics method, called the "integrated evaluation", for analysis and eventual classification of UVs. Currently, the method is applicable to UVs in the breast cancer susceptibility genes BRCA1 and BRCA2. We are working to improve the method, to extend it to other susceptibility genes, and to create databases that will disseminate classification results to clinical cancer geneticists throughout the world.

Research Keywords:
Cancer genetics, bioinformatics, next-generation sequencing, mutation screening, unclassified variants