• 2019-10
  • 2019-11
  • 2020-03
  • 2020-07
  • 2020-08
  • br Functional Enrichment Analysis of Kinase and Phosphatase


    Functional Enrichment Analysis of Kinase and Phosphatase Clusters
    Our analysis indicated that signaling proteins with different cata-lytic domain sequences may affect signaling networks similarly when overexpressed. To understand the functional relationship between proteins with similar overexpression effects, we per-formed a functional enrichment analysis using the STRING database (Szklarczyk et al., 2017) on the 10 identified clusters (Figures 2A and 3A). We found that 7 of the 10 clusters had sig-nificant functional enrichment (p < 0.01; statistical details in STAR Methods). Physical and functional interaction enrichments are shown as protein-protein association networks for cluster 7 in Figure 3B and for all other clusters in Figure S3A.
    Cluster 7 is enriched for protein tyrosine phosphatases that negatively regulate MAPK pathways. Several MAPK regulating kinases are present in this cluster, including KSR1 and ARAF, which have overexpression effects similar to those of the phos-phatases (Figure 3B). KSR1 and ARAF are core components of the KSR-RAF dimeric protein complex that transduces signal
    Figure 2. Kinase and Phosphatase Classification Based on Abundance-Dependent Effects on Cancer Signaling Network
    (A) t-SNE analysis of overexpressed kinases and phosphatases performed on signed-BP-R2 of all measured Ethylmalonyl Coenzyme A sites with and without EGF stimulation, color coded by hierarchical clusters.
    (B) The mean signed-BP-R2 values of all measured phosphorylation sites in each cluster of kinases or phosphatases shown in literature-guided canonical signaling network visualizations.
    Figure 3. Functional Enrichment Analysis of Kinases and/or Phosphatases in Each Cluster
    (A) An unrooted tree shows the hierarchical clustering of the kinases and phosphatases based on their signed-BP-R2 scores. Terms of enriched functions (p < 0.05) from each cluster are annotated, with circle color indicating the p value and circle size showing the coverage of cluster components. The percentage of associated proteins is indicated by the size of the adjacent circle.
    (B) Functional association analysis performed with the STRING database (Szklarczyk et al., 2017) for cluster 7. Confident edges are shown in the network. Functional enrichments are shown as color-coded pies, with the pie radius indicating the p value.
    in the MAPK-ERK cascade (Lavoie and Therrien, 2015). Overex-pressing one subunit of this protein complex may result in competitive inhibition, diminishing the downstream signal activ-ities in a manner similar to that of phosphatase overexpression. These analyses demonstrated that proteins with different cata-lytic functions can mediate highly related signaling responses when overexpressed and that kinase overexpression does not affect signaling networks in the same manner as direct kinase activation.
    To assess the relationship between overexpression effects and
    protein catalytic activities, we chose to overexpress five kinase-dead mutants: AKT3K177M, AXLK567R, MAPK3K71R, PRKCEK437W, and MAP2K1K97M. Unlike wild-type kinases, the overexpression 
    of kinase-dead mutants AXLK567R and PRKCEK437W had almost no network effect (Figure S3B), indicating that Ethylmalonyl Coenzyme A the detected abun-dance-dependent network modulations of these kinases are related to their catalytic functions. In contrast, the main network effects of AKT3, MAPK3, and MAP2K1 were also observed when the kinase-dead mutants were overexpressed (Figure S3B). This suggests that overexpression-induced signaling network modulations for these kinases are non-catalytic. In addition, 26 kinases in our screen were previously predicted to be catalytically inactive (Manning et al., 2002). We found that 6 of these 26 pro-teins influenced the measured network, with a total of 17 pairs of strong signaling relationships detected (Table S5), also demonstrating that our analysis captured non-catalytic network
    Figure 4. Prediction of Potential Signaling Connections by Comparison with Literature Evidence in the Signaling Interaction Database OmniPath
    (A) Abundance-dependent relationship strength for each pair of overexpressed POIs and measured phosphorylation site, as quantified with signed-BP-R2, plotted on the length of shortest signed, directed path between the two extracted from the OmniPath database (Tureiā‚¬ et al., 2016).
    (B) Occurrences of strong signaling relationships (BP-R2 > 0.13), with path length from to 5 or infinite path length (OmniPath) in each individual hierarchical cluster.
    (C and D) For clusters 8 (C) and 5 (D), respectively, the shortest signed directed path length for each determined strong signaling relationship is shown in Circos plots (Krzywinski et al., 2009).