Integrating Clinical Cancer and PTM Proteomics Data Identifies a Mechanism of ACK1 Kinase Activation.

Beyond the most common oncogenes activated by mutation (mut-drivers), there likely exists a variety of low-frequency mut-drivers, each of which is a possible frontier for targeted therapy. To identify new and understudied mut-drivers, we developed a machine learning (ML) model that integrates curated clinical cancer data and posttranslational modification (PTM) proteomics databases. We applied the approach to 62,746 patient cancers spanning 84 cancer types and predicted 3,964 oncogenic mutations across 1,148 genes, many of which disrupt PTMs of known and unknown function. The list of putative mut-drivers includes established drivers and others with poorly understood roles in cancer. This ML model is available as a web application. As a case study, we focused the approach on nonreceptor tyrosine kinases (NRTK) and found a recurrent mutation in activated CDC42 kinase-1 (ACK1) that disrupts the Mig6 homology region (MHR) and ubiquitin-association (UBA) domains on the ACK1 C-terminus. By studying these domains in cultured cells, we found that disruption of the MHR domain helps activate the kinase while disruption of the UBA increases kinase stability by blocking its lysosomal degradation. This ACK1 mutation is analogous to lymphoma-associated mutations in its sister kinase, TNK1, which also disrupt a C-terminal inhibitory motif and UBA domain. This study establishes a mut-driver discovery tool for the research community and identifies a mechanism of ACK1 hyperactivation shared among ACK family kinases. IMPLICATIONS: This research identifies a potentially targetable activating mutation in ACK1 and other possible oncogenic mutations, including PTM-disrupting mutations, for further study.

SGK2, 14-3-3, and HUWE1 Cooperate to Control the Localization, Stability, and Function of the Oncoprotein PTOV1.

PTOV1 is an oncogenic protein, initially identified in prostate cancer, that promotes proliferation, cell motility, and invasiveness. However, the mechanisms that regulate PTOV1 remain unclear. Here, we identify 14-3-3 as a PTOV1 interactor and show that high levels of 14-3-3 expression, like PTOV1, correlate with prostate cancer progression. We discover an SGK2-mediated phosphorylation of PTOV1 at S36, which is required for 14-3-3 binding. Disruption of the PTOV1-14-3-3 interaction results in an accumulation of PTOV1 in the nucleus and a proteasome-dependent reduction in PTOV1 protein levels. We find that loss of 14-3-3 binding leads to an increase in PTOV1 binding to the E3 ubiquitin ligase HUWE1, which promotes proteasomal degradation of PTOV1. Conversely, our data suggest that 14-3-3 stabilizes PTOV1 protein by sequestering PTOV1 in the cytosol and inhibiting its interaction with HUWE1. Finally, our data suggest that stabilization of the 14-3-3-bound form of PTOV1 promotes PTOV1-mediated expression of cJun, which drives cell-cycle progression in cancer. Together, these data provide a mechanism to understand the regulation of the oncoprotein PTOV1. IMPLICATIONS: These findings identify a potentially targetable mechanism that regulates the oncoprotein PTOV1.