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Functional proteomics represents a powerful approach to understand the pathophysiology and therapy of cancer. However, comprehensive cancer proteomic data have been relatively limited. As a part of The Cancer Genome Atlas (TCGA) Project and other efforts, we have generated protein expression data over a large number of tumor and cell line samples using reverse-phase protein arrays (RPPAs). RPPA is a quantitative, antibody-based technology that can assess multiple protein markers in many samples in a cost-effective, sensitive and high-throughput manner 1 , 2 . This technology has been extensively validated for both cell line and patient samples 3 , 4 , 5 , and its applications range from building reproducible prognostic models 6 to generating experimentally verified mechanistic insights 7 .
Li et al. (Sun,) studied this question.
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