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Multiscale Analysis of CGH Arrays from Breast Cancer Patients Using Computational

使用计算对乳腺癌患者的 CGH 阵列进行多尺度分析

基本信息

批准号：
8104025
负责人：
Francisco Javier Arsuaga
金额：
$ 12.32万
依托单位：
SAN FRANCISCO STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/8104025
关键词：
11q African American Algorithms American Cancer Society Biology California Cancer Center Cancer Etiology Cancer Patient Cessation of life Characteristics Chromosome Arm Chromosomes Chromosomes, Human, Pair 11 Chromosomes, Human, Pair 8 Classification Clinical Complex Computer software Computing Methodologies Data Data Analyses Data Set Detection Development Diagnosis Disease Distal Genes Genome Genomics Goals Hybridization Array Individual Internet Knowledge Lead Machine Learning Malignant Neoplasms Malignant neoplasm of lung Mentors Methods Minority Groups Noise Numerical value Patients Phenotype Physiology Population Principal Investigator Publishing Recommendation Recurrence Research Research Project Grants Resolution Sampling San Francisco Stratification Subgroup Survival Rate Techniques Technology The University of California San Francisco Cancer Center Underrepresented Minority Universities Woman abstracting base cancer diagnosis cancer recurrence cohort comparative genomic hybridization design effective therapy ethnic minority population improved malignant breast neoplasm meetings novel novel strategies outcome forecast professor software development treatment planning treatment response tumor tumor progression

项目摘要

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.

合作研究项目#3