Multiscale Analysis of CGH Arrays from Breast Cancer Patients Using Computational

San Francisco State University, San Francisco CA

Investigators

Linked publications & trials

Abstract

COLLABORATIVE RESEARCH PROJECT #3 MULTISCALE ANALYSIS OF CGH ARRAYS FROM BREAST CANCER PATIENTS USING COMPUTATIONAL ALGEBRAIC TOPOLOGY Javier Arsuaga, Principal Investigator San Francisco State University Mariel Vazquez, Principal Investigator San Francisco State University Daniel Pinkel, Mentor/Collaborator UCSF Cancer Center Abstract Breast cancer, the most common cancer in women worldwide, is one of the leading causes of cancer deaths, second only to lung cancer. The American Cancer Society has estimated that in the US alone almost 200,000 new cases of breast cancer will be diagnosed during 2008. In order to improve the survival rates from this disease, there is a need for new approaches to facilitate a more effective stratification of patients into distinct clinical subgroups likely to benefit from different treatment regimes. To meet this need, Drs. Arsuaga and Vazquez propose to develop a computational method for analyzing DMA copy number changes. These changes, which are known to be associated with the progression of cancer, can be detected through array Comparative Genomic Hybridization (CGH); however, the application of this technology for the prediction of recurrence remains a challenge due to the complexity of the data involved. The goal of the proposed project is to develop a novel computational method, based on computational algebraic homology, to analyze CGH profiles at multiple levels of resolution in order to predict recurrence of breast cancer. The Pis will first determine the chromosome regions which contain genes associated with breast cancer recurrence, and then establish the contribution of the overall characteristics of the CGH profile to the recurrence. The study will involve the examination not just of independent interchromosomal regions but also of relationships between proximal and distal intrachromosomal regions. Software developed for the project will be made publicly available through the web. The Pis will be supported through a mentoring relationship with Professor Daniel Pinkel from the University of California, San Francisco (UCSF), an expert on CGH array development and analysis as well as on breast cancer.