Identification of Biomarkers for Breast Cancer Using Databases

Breast cancer is one of the major causes of cancer death in women. Many studies have sought to identify specific molecules involved in breast cancer and understand their characteristics. Many biomarkers which are easily measurable, dependable, and inexpensive, with a high sensitivity and specificity have been identified. The rapidly increasing technology development and availability of epigenetic informations play critical roles in cancer. The accumulated data have been collected, stored, and analyzed in various types of databases. It is important to acknowledge useful and available data and retrieve them from databases. Nowadays, many researches utilize the databases, including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Surveillance, Epidemiology and End Results (SEER), and Embase, to find useful informations on biomarkers for breast cancer. This review summarizes the current databases which have been utilized for identification of biomarkers for breast cancer. The information provided by this review would be beneficial to seeking appropriate strategies for diagnosis and treatment of breast cancer.

Connection Map for Compounds (CMC): A Server for Combinatorial Drug Toxicity and Efficacy Analysis

Drug discovery and development is a costly and time-consuming process with a high risk for failure resulting primarily from a drug's associated clinical safety and efficacy potential. Identifying and eliminating inapt candidate drugs as early as possible is an effective way for reducing unnecessary costs, but limited analytical tools are currently available for this purpose. Recent growth in the area of toxicogenomics and pharmacogenomics has provided with a vast amount of drug expression microarray data. Web servers such as CMap and LTMap have used this information to evaluate drug toxicity and mechanisms of action independently; however, their wider applicability has been limited by the lack of a combinatorial drug-safety type of analysis. Using available genome-wide drug transcriptional expression profiles, we developed the first web server for combinatorial evaluation of toxicity and efficacy of candidate drugs named "Connection Map for Compounds" (CMC). Using CMC, researchers can initially compare their query drug gene signatures with prebuilt gene profiles generated from two large-scale toxicogenomics databases, and subsequently perform a drug efficacy analysis for identification of known mechanisms of drug action or generation of new predictions. CMC provides a novel approach for drug repositioning and early evaluation in drug discovery with its unique combination of toxicity and efficacy analyses, expansibility of data and algorithms, and customization of reference gene profiles. CMC can be freely accessed at http://cadd.tongji.edu.cn/webserver/CMCbp.jsp .