Year: 2012
Type: article
Abstract: MOTIVATION: Triple-negative breast cancer (TNBC) is a heterogeneous breast cancer group, and identification of molecular subtypes is essential for understanding the biological characteristics and clinical behaviors of TNBC as well as for developing personalized treatments. Based on 3,247 gene expression profiles from 21 breast cancer data sets, we discovered six TNBC subtypes from 587 TNBC samples with unique gene expression patterns and ontologies. Cell line models representing each of the TNBC subtypes also displayed different sensitivities to targeted therapeutic agents. Classification of TNBC into subtypes will advance further genomic research and clinical applications. RESULT: We developed a web-based subtyping tool TNBCtype for candidate TNBC samples using our gene expression meta data and classification methods. Given a gene expression data matrix, this tool will display for each candidate sample the predicted subtype, the corresponding correlation coefficient, and the permutation P-value. We offer a user-friendly web interface to predict the subtypes for new TNBC samples that may facilitate diagnostics, biomarker selection, drug discovery, and the more tailored treatment of breast cancer.
Source: Cancer Informatics
DOI: 10.4137/cin.s9983
Authors: Xi Chen, Jiang Li, William H. Gray, Brian D. Lehmann, Joshua A. Bauer, Yu Shyr, Jennifer A. Pietenpol
Institutions: Vanderbilt University, Vanderbilt-Ingram Cancer Center
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,650
Funder: National Cancer Institute
OpenAlex ID: W1989938935