SWITCHdna
SWITCHdna identifies subtype-associated copy number aberrations (CNA) in breast cancer by analyzing intensity data from copy number platforms to detect and significance-test transition points within defined genomic segments.
Key Features:
- Subtype-Specific CNA Identification: Classifies tumors by gene expression subtypes and identifies subtype-associated CNAs using a training set of 180 tumors with validation on 359 tumors.
- Transition-Point Detection: Detects transition points within defined genomic segments from intensity data generated by copy number platforms.
- Significance Testing: Performs statistical significance testing of detected CNAs and transition points.
- Statistical Analysis Methods: Implements Fisher's exact tests, Chi-square approximations, and Wilcoxon rank-sum tests to evaluate differences in CNAs across subtypes.
- Functional Significance Assessment: Integrates RNA interference (RNAi) knockdown experiments with drug sensitivity assays and DNA repair foci formation studies to assess functional consequences of CNAs.
Scientific Applications:
- Breast Cancer Subtype Characterization: Identifies subtype-specific CNAs that define distinct genomic profiles, including losses in Basal-like tumors affecting genes such as RB1 and BRCA1.
- Genomic Instability Insights: Highlights CNAs associated with increased genomic instability, for example loss of 5q11-35 encompassing RAD17, RAD50, and RAP80, which correlates with genomic instability and poorer survival.
- Therapeutic Implications: Supports therapeutic hypotheses targeting DNA repair pathways, noting increased sensitivity to PARP inhibitors and carboplatin in cell lines with knockdown of RAD17 or RAD17/RAD50.
Methodology:
Analyzes intensity data from copy number platforms, detects transition points within defined genomic segments, conducts significance testing, classifies tumors by gene expression subtype with a 180-sample training set and 359-sample validation set, and applies Fisher's exact tests, Chi-square approximations, and Wilcoxon rank-sum tests.
Topics
Details
- Tool Type:
- library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Weigman VJ, Chao H, Shabalin AA, He X, Parker JS, Nordgard SH, Grushko T, Huo D, Nwachukwu C, Nobel A, Kristensen VN, Børresen-Dale A, Olopade OI, Perou CM. Basal-like Breast cancer DNA copy number losses identify genes involved in genomic instability, response to therapy, and patient survival. Breast Cancer Research and Treatment. 2011;133(3):865-880. doi:10.1007/s10549-011-1846-y. PMID:22048815. PMCID:PMC3387500.