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Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance., Dysregulated phosphorylation is well-known in cancers, but it has largely been studied in isolation from mutations. Here the authors introduce HotPho, a tool that can discover spatial interactions between phosphosites and mutations, which are associated with activating mutation and genetic dependencies in cancer.

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities., National Cancer Institute (U.S.) (Grant R01CA180006)

Translation initiation of most mammalian mRNAs is mediated by a 5′ cap structure that binds eukaryotic initiation factor 4E (eIF4E). However, inactivation of eIF4E does not impair translation of many capped mRNAs, suggesting an unknown alternate mechanism may exist for cap-dependent but eIF4E-independent translation. We show that DAP5, an eIF4GI homolog that lacks eIF4E binding, utilizes eIF3d to facilitate cap-dependent translation of approximately 20% of mRNAs. Genome-wide transcriptomic and translatomic analyses indicate that DAP5 is required for translation of many transcription factors and receptor capped mRNAs and their mRNA targets involved in cell survival, motility, DNA repair and translation initiation, among other mRNAs. Mass spectrometry and crosslinking studies demonstrate that eIF3d is a direct binding partner of DAP5. In vitro translation and ribosome complex studies demonstrate that DAP5 and eIF3d are both essential for eIF4E-independent capped-mRNA translation. These studies disclose a widespread and previously unknown mechanism for cap-dependent mRNA translation by DAP5-eIF3d complexes., Binding of eIF4E to the 5′ cap of mRNAs is a key early step in canonical translation initiation, but the requirement for eIF4E is not universal. Here the authors show that the eIF4G homolog DAP5 interacts with eIF3 to promote cap-dependent translation of a significant number of mRNA in an eIF4E-independent manner.

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities., Patient-derived xenografts recapitulate major genomic signatures and transcriptome profiles of their original tumours. Here, the authors, performing proteomic and phosphoproteomic analyses of 24 breast cancer PDX models, demonstrate that druggable candidates can be identified based on a comprehensive proteogenomic profiling.

Nature Communications 8: Article number: 14864 (2017)); Published: 28 March 2017; Updated: 25 April 2017 The original version of this Article contained a typographical error in the spelling of the author Beifang Niu, which was incorrectly given as Beifung Niu. This has now been corrected in both thePDF and HTML versions of the Article.