Exit seminar Anthony Fejes-PhD student

The University of British Columbia

EXIT SEMINAR
Anthony P. Fejes
BSc. University of Waterloo, 2000
B.I.S. University of Waterloo, 2001
M.Sc. University of British Columbia, 2004
Friday, October 21, 2011 at 11 AM
LOCATION: Lecture Theatre, BCCRC
Decyphering Metastatic Ductal Carcinoma Cell Lines

Abstract:

One in nine women will develop breast cancer at some point in their lives, and just over half of those cancers will be a form of ductal carcinoma, arising from the cells lining the milk ducts of the breast. Ductal carcinomas are commonly believed to progress through varying stages, transforming from mostly benign ductal carcinoma in situ (DCIS) to the generally malignant invasive ductal carcinoma (IDC) if not caught early. The most difficult IDC to treat are the so called triple negative IDC, which lack the three common markers of the Estrogen Receptor (ER), Progesterone Receptor and the Human Epidermal Growth Factor Receptor 2 (Her2). These triple negative breast cancers have a higher recurrence and lower response rate to treatment than other forms of IDC.

We have studied eight ductal carcinoma cell lines taken from high grade primary tumours, four of which have matched Epstein Bar Virus transformed B-cell derived normal cell lines. The cell lines include three that are triple negative for ER/PR/Her2 markers, whereas the other five cell lines each exhibit one or more of the markers. DNA from each of the eight cell lines was subjected to exome capture and sequencing on the Illumina GAII platform, while RNA was harvested and sequenced from those cell lines in paired normal-cancer sets. All of the sequencing results were processed to identify single nucleotide variants, which were then imported into a local database of variations (Fejes et al, 2011) used to identify genes with novel non-synonymous variations.

Several interesting facets of the data are presented, including the filtering and identification of novel variations, the identification of genes with recurrent mutations, comparison of RNA and DNA generated data and the integration of DNA and RNA sequencing to identify high quality variations. Finally, the integration of recurrent high quality variations, RNA expression and a knowledge based approach can be used to suggest a pathway of interest, providing interesting opportunities for developing further targets.

References:

Dent et al, Triple-negative breast cancer: clinical features and patterns of recurrence. 2007. Clin. Cancer Res.
Fejes et al, Human variation database: an open-source database template for genomic discovery. 2011. Bioinformatics

Supervisor: Dr. Steven JM Jones, Professor, Molecular Biology & Biochemistry, Simon Fraser University. Professor, Medical Genetics, University of British Columbia