Dissection of oncogenic signaling pathways with functional genomics and proteomics approaches facilitates understanding dynamic information processing and how these pathways may be disrupted by mutations or targeted therapeutically (26
). By combining multiple, parallel genome-wide RNAi screens and TAP-MS interactome screens, we have assembled an integrated network of RTK-Ras-ERK signaling with both PPI interactions and functional information obtained in the same signaling environment. This network provides a resource for subsequent hypothesis-driven, mechanistic investigation of hundreds of conserved regulators.
Because high-throughput data sets are individually susceptible to multiple sources of technical and biological noise, confidence in subsets of any given “omics” data set can be increased by overlapping contrasting experimental approaches. Most integrative efforts up to now have queried data sets generated under disparate conditions and even different organisms. We found that only a small fraction of the hits from interactome or functional screening were isolated under all conditions tested, and most of these represented known “canonical” pathway components. Many of the hits that were identified from each method individually also showed evidence of activity in vivo. Comparing our studies to other studies of MAPK regulators suggests that the complete landscape of proteins regulating RTK-Ras-ERK signaling under specific conditions is likely to be larger than the conservative overlapping network that we describe. In comparison to a Y2H screen for MAPK pathway interactors, where >600 interactions were identified (14
), only 54 proteins overlapped with our network, 30 (56%) of which also were positive in our RNAi screen, including the proton transporter ATPsyn-β (ATP5B), which was a negative regulator in our RNAi screens. Of the 31 proteins from a study of dynamic ERK interactors that overlapped with our filtered data set (27
), 22 were encoded by genes positive in our RNAi screens, but only one, heat shock protein 60 (HspD1), was pulled down by ERK itself in our study. However, another 16 proteins interacted with Raf and 8 interacted with Dsor (MEK). By considering the Raf-MEK-ERK cassette as a whole, the number of overlapping interactions increased. Although these comparisons are limited by the differences in Y2H and TAP-MS techniques, the population of regulators that can be identified is probably highly technique- and condition-specific, and this work should be seen as a “first pass” at identifying the universe of proteins regulating the output of this pathway.
We used PPI mapping and functional genomic methods to identify several previously unknown regulators that also exhibited in vivo roles in RTK-Ras-ERK signaling. Translation of cell culture regulators to in vivo phenotypes is challenging due to lack of knowledge of the correct tissue in which to test for activity. Because many of the newly identified regulators are likely cell type– and RTK-specific, we were unable to identify phenotypes in the wing disc for many of these regulators. A large number of genes positive in the RNAi screens were not identified in the PPI network, either because of false negatives or because the encoding proteins modulate activity of the pathway indirectly. A prime example of this latter category is Rtf1, a histone methyltransferase knockdown of which enhanced ERK activation in vivo. Rtf1 enhances Notch pathway activity (33
), and the Notch pathway can inhibit ERK activity (34
); thus, Rtf1 may be a key mediator of Notch-ERK crosstalk. In contrast, we identified another protein phosphatase 2A (PP2A) family member, the PPP6 ortholog PpV and its regulatory subunit CG10289, as interacting with Raf, but did not identify the genes encoding these proteins in our RNAi screens. In mammals, PPP6 components can interact with the inhibitor of nuclear factor κB IκBε (18
) and regulate the cell cycle in normal and pathological contexts. The role of the Ser-Thr phosphatase PP2A in the Ras pathway has been principally described as a positive regulator through dephosphorylation of Ser259
on Raf and Ser392
on Ksr (numbering is based on human proteins), inducing 14-3-3 protein dissociation (36
); PPP6 may play a similar role in Raf activation in specific in vivo contexts. CG6453, a noncatalytic subunit of glucosidase II, was identified in the interaction screen and was identified in the RNAi screens, indicating a high-confidence interactor. Although its mechanism of regulating MAPK output remains unknown, it is consistent with the growing recognition that metabolic and other genes previously thought to have “housekeeping” roles can have specific functions in signaling (37
). Finally, despite its interaction with intracellular Ksr, TepIV has homology with CD109, a GPI-linked cell surface marker of T cells, endothelial cells, and activated platelets, that contains a protease inhibitor α2 macroglobulin domain (39
); CD109 is mutated in 7% of colorectal cancers (40
) and may thus affect ERK output in these cancers. As more human cancers are characterized through ongoing large-scale next-generation sequencing, our data set of regulators of RTK-Ras-ERK signaling will provide a resource for understanding the potential mechanistic contribution of somatic mutations to cancer development.