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Deep sequencing of breast cancer tumors to predict clinical outcomes after single dose of therapy
Date:12/12/2013

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Dr. Harris' co-presenters are: Nicole Williams, Vinay Varadan, Kristy Miskimen, Aditi Vadodkar, Debora Poruban,, Simone Edelheit, Hannah Gilmore, Steve Maximuk, Natalie Sinclair, Kimberly Lezon-Geyda, Maysa Abu-Khalaf, William Sikov, University Hospitals Case Medical Center/Case Western Reserve University, Cleveland, OH; Yale University School of Medicine; Yale Comprehensive Cancer Center, New Haven, CT; Warren Alpert Medical School of Brown, Providence, RI.

About the Studies

P1-08-16: Poster Session 1: Prognosis and Response Prediction: Response Predictive Factors
Deep sequencing of breast tumor biopsies reveals an association between pathologic complete response (pCR) and reduction of TP53 clonal abundance upon brief exposure to therapy
Wednesday 12/11, 5:00 PM -7:00 PM

Investigators evaluated 120 Stage IIA to IIIB breast cancer patients and compared a first biopsy after brief exposure to either biologic or chemotherapy treatment with a second biopsy taken after surgery. Researchers utilized deep genomic sequencing to quantify the abundance of clonal mutations in breast core biopsies, assess changes in these mutations after brief exposure to a targeted therapy and then evaluate the corresponding change in abundance of these mutations after exposure. This process of quantifying and monitoring clonal mutations between initial therapy exposure and surgery allowed researchers to determine how changes in the abundance of these mutations related to a patient's response to preoperative therapy. Through this analysis, investigators determined that clonal abundance upon brief exposure to therapy may be associated with clinical outcomes.


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Contact: Alicia Reale
alicia.reale@uhhospitals.org
216-844-5158
University Hospitals Case Medical Center
Source:Eurekalert

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