Abstract
Objective: We have developed a statistical model based on gene expression within 9 core cancer pathways using The Cancer Genome Atlas (TCGA) microarray dataset that predicts clinical response to cytotoxic chemotherapies at the time of progression of serous ovarian carcinoma. We assayed the applicability of our microarray signatures to gene expression in quantitative polymerase chain reaction (qPCR) with patient-matched snap frozen and formalin-fixed, paraffin-embedded (FFPE) tissue samples. Successful results will enable large-scale validation from FFPE archival tissue with abundant clinical information and follow-up.
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