Oncoproteomic profiling of AML: moving beyond genomics
Abstract
Much of what is known about protein-signaling networks in cancer, or ‘oncoproteomics,’ has been indirectly derived from transcriptomic analyses[1],[2]. However, RNA regulation precludes a one-to-one correlation of mRNA abundance to protein abundance or activity. A corollary of this is that evaluation of RNA by itself is insufficient to fully appreciate pathogenic cellular signaling within the tumor ecosystem. Global proteomics and phosphoproteomics have emerged as powerful unbiased methodologies for detailing fundamental signaling networks of cancer cells and perturbations that sustain resistance against targeted therapies, contributing to the discovery of new therapeutic targets[3]. Similar to other cancers, the utility of mass spectrometrybased technologies has augmented our ability to categorize the underlying heterogeneity in acute myeloid leukemia (AML) – expanding our capacity to classify AML beyond genomic features alone. Efforts over the past decade have resulted in the creation of new datasets that have begun to characterize the AML proteome and phosphoproteome. A subset of these studies have been exploratory in nature [4–9] – leading to the generation of new hypotheses, while others have focused on examining particular aspects of a disease state (e.g. drug resistance) to identify new biomarkers. These data provide a rich resource for further investigations aimed at mapping the ‘post-genomic’ landscape of AML (Table 1). Within this editorial, we discuss how…
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