TY - JOUR T1 - A Biotin Label-based Antibody Array for High-content Profiling of Protein Expression JF - Cancer Genomics - Proteomics JO - Cancer Genomics Proteomics SP - 129 LP - 141 VL - 7 IS - 3 AU - RUOCHUN HUANG AU - WEIDONG JIANG AU - JEAN YANG AU - YING QING MAO AU - YING ZHANG AU - WEIMING YANG AU - DONGZI YANG AU - BRETT BURKHOLDER AU - RANI FAN HUANG AU - RUO-PAN HUANG Y1 - 2010/05/01 UR - http://cgp.iiarjournals.org/content/7/3/129.abstract N2 - Background/Aim: Profiling protein expression on a global scale will have significant impact on biomedical research, particularly in the discovery and development of drugs and biomarkers. Through the years, several antibody array systems have been invented and developed for multiple protein detection. However, a reliable and high-content system for protein profiling from many biological samples has yet been developed. This study aimed to develop a reliable, easy to use and cost effective method to profile protein expression levels in high-content manner with sufficient sensitivity and specificity. Materials and Methods: To address this problem, a high density antibody array was developed and used this technology to uncover the potential biomarkers of ovarian cancer. In this system, biological samples are labeled with biotin. The biotinylated proteins are then incubated with antibody chips. The presence of proteins captured by the antibody chip is detected using streptavidin-conjugated fluorescent dye (Cy3 equivalent) as a reporter. The signals, which are visualized by laser scanning, are normalized using positive, negative, and internal controls. Results: Using this biotin label-based antibody array technology, the expression levels of 507 human, 308 mouse and 90 rat target proteins can be simultaneously detected, including of cytokines, chemokines, adipokines, growth factors, angiogenic factors, proteases, soluble receptors, soluble adhesion molecules, and other proteins in a variety of samples. Most proteins can be detected at pg/ml and ng/ml levels, with a coefficient of variation of less than 20%. Using human biotin-based antibody arrays, we screened the serum expression profiles of 507 proteins in ovarian cancer patients and healthy individuals. A panel of protein expression showed significant difference between normal and cancer samples (p<0.05). By classification analysis and split-point score analysis of these two groups, a small group of proteins were found to be useful in distinguishing ovarian cancer patients from normal subjects. Conclusion: Our results suggest the biotin label-based antibody arrays that we have developed have great potential in applications for biomarker discovery. ER -