P5-04-02: TNBL: An Integrated Knowledge Space of Triple-Negative and Basal-Like Breast Cancers.
Authors: J Zhu
Journal: Cancer Research (2011)

Abstract Background: To facilitate drug discovery and development in triple-negative (TNBC) and basal-like (BLBC) breast cancers, an integrated knowledge space was developed through standardizing and linking information reported in scientific publications. The tool was designed to 1) track and consolidate knowledge around TNBC and BLBC; 2) centralize computational resources on molecular profiles, disease models, drug effects and clinical outcomes; 3) establish a computational platform to facilitate identification of drug targets and biomarkers; 4) enable hypothesis generation for novel uses of pre-existing compounds including new indications and combinations. Material and Methods: Querying PubMed with “(basal-like or triple-negative) breast cancer” generated 1200 hits. First, text-mining techniques were employed to filter publications for curation. Second, information extracted from biomedical literature and public domain databases was standardized with control vocabularies. Third, interactions originally presented in natural language were translated into a well-structured format according to specific semantic rules suited for computational purposes. The concepts and associated interactions were captured in a database and could be browsed as lists, tables and interactive networks. Results: Based on the initial assessment of the 1200 abstracts, 500 papers were selected for further analysis. About 1400 unique concepts were extracted and categorized: 1) 600 molecular components such as DNA loci, SNP, mRNA, microRNA, protein and complexes; 2) 120 cellular processes; 3) 100 model systems such as cell lines, xenograft, and tissues; 4) 220 compounds and regimens; 5) 180 clinical and non-clinical parameters such as survival and chemoresistance; 6) 264 disease definitions. The most implicated genes in TNBC and BLBC were EGFR, BRCA1, TP53, CK5/6, AR, TP63, KRT14, CDH1, AKT1, CCND1, VEGF, PTEN, CD44, NFKB1 etc. There were 80 genes reported related to TNBC and BLBC by more than 3 papers. Using the published gene expression datasets of breast cancers, the 80-gene set proved to be a highly accurate classifier for BLBC and non-BLBC. The most researched cellular processes included epithelial to mesenchymal transition (EMT), cell migration/metastasis, apoptosis, cell proliferation, angiogenesis, beta-catenin/WNT, PI3k/AKT. The most studied experimental therapies included PARP inhibitors, cisplatin, dasatinib, doxorubicin and EGFR inhibitors. Concepts and interactions were visualized in networks. For example, the EMT network comprised 110 nodes and 162 interactions based on 19 references, and the TNBC network contained 514 nodes and 874 interactions from 217 papers. Discussion: The number of research papers on TNBC and BLBC are growing rapidly with 30–50% increase annually. TNBL provides a platform for the research community to standardize scientific findings and exchange knowledge efficiently. Through its powerful semantic technology and robust visualization capability, it offers integrated and comprehensive views of TNBC and BLBC which are not possible in the scope of any single research paper. In addition, it facilitates high quality hypothesis generation through consolidating up-to-date information from all possible sources in a computable format. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P5-04-02.