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Summary There is a lack of effective predictive biomarkers to precisely assign optimal therapy to cancer patients. While most efforts are directed at inferring drug response phenotype based on genotype, there is very focused and useful phenotypic information to be gained from directly perturbing the patient’s living cancer cell with the drug(s) in question. To satisfy this unmet need, we developed the Dynamic BH3 Profiling technique to measure early changes in net pro-apoptotic signaling at the mitochondrion (“priming”) induced by chemotherapeutic agents in cancer cells, not requiring prolonged ex vivo culture. We find in cell line and clinical experiments that early drug-induced death signaling measured by Dynamic BH3 Profiling predicts chemotherapy response across many cancer types and many agents, including combinations of chemotherapies. We propose that Dynamic BH3 Profiling can be used as a broadly applicable predictive biomarker to predict cytotoxic response of cancers to chemotherapeutics in vivo. [ABSTRACT FROM AUTHOR]

Ovarian cancer is a leading cause of death from gynecologic malignancies. Treatment for advanced-stage disease remains limited and, to date, targeted therapies have been incompletely explored. By systematically suppressing each human tyrosine kinase in ovarian cancer cell lines by RNAi, we found that an autocrine signal-transducing loop involving NRG1 and activated ErbB3 operates in a subset of primary ovarian cancers and ovarian cancer cell lines. Perturbation of this circuit with ErbB3-directed RNAi decreased cell growth in three-dimensional culture and resulted in decreased disease progression and prolonged survival in a xenograft mouse model of ovarian cancer. Furthermore, a monoclonal ErbB3-directed antibody (MM-121) also significantly inhibited tumor growth in vivo. These findings identify ErbB3 as a potential therapeutic target in ovarian cancer., (Copyright 2010 Elsevier Inc. All rights reserved.)