Summary Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. We describe quantitative mass spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers of which 77 provided high-quality data. Integrated analyses allowed insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. The 5q trans effects were interrogated against the Library of Integrated Network-based Cellular Signatures, thereby connecting CETN3 and SKP1 loss to elevated expression of EGFR, and SKP1 loss also to increased SRC. Global proteomic data confirmed a stromal-enriched group in addition to basal and luminal clusters and pathway analysis of the phosphoproteome identified a G Protein-coupled receptor cluster that was not readily identified at the mRNA level. Besides ERBB2, other amplicon-associated, highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in −4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

In BriefPathway analysis of PTM data sets is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases. We have developed a PTM signatures database (PTMsigDB) providing curated phosphorylation signatures of kinases, perturbations and signaling pathways to enable site-specific PTM signature enrichment analysis (PTM-SEA). Application of PTM-SEA to phosphoproteomes of several cell lines perturbed with growth factors, cell cycle inhibitors, or a specific PI3K inhibitor demonstrated the potential of our site centric approach to study dysregulated pathways in cancers. Graphical Abstract Highlights• Database of PTM site-specific phosphorylation signatures of kinases, perturbations and signaling pathways (PTMsigDB).• PTM signature enrichment analysis (PTM-SEA) outperformed gene-centric analysis in detection of EGF induced phospho signaling events.• PI3K perturbation signatures were readily detected in PI3Ka inhibited human breast cancer cells.• PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.

There is a pressing need to identify therapeutic targets in tumors with low mutation rates such as the malignant pediatric brain tumor medulloblastoma. To address this challenge, we quantitatively profiled global proteomes and phospho-proteomes of 45 medulloblastoma samples. Integrated analyses revealed that tumors with similar RNA expression vary extensively at the post-transcriptional and post-translational levels. We identified distinct pathways associated with two subsets of SHH tumors, and found post-translational modifications of MYC that are associated with poor outcomes in group 3 tumors. We found kinases associated with subtypes and showed that inhibiting PRKDC sensitizes MYC-driven cells to radiation. Our study shows that proteomics enables a more comprehensive, functional readout, providing a foundation for future therapeutic strategies.

BackgroundNeurotropic flaviviruses such as tick-borne encephalitis virus (TBEV), Japanese encephalitis virus (JEV), West Nile virus (WNV), and Zika virus (ZIKV) are causative agents of severe brain-related diseases including meningitis, encephalitis, and microcephaly. We have previously shown that local type I interferon response within the central nervous system (CNS) is involved in the protection of mice against tick-borne flavivirus infection. However, the cells responsible for mounting this protective response are not defined.MethodsPrimary astrocytes were isolated from wild-type (WT) and interferon alpha receptor knock out (IFNAR−/−) mice and infected with neurotropic flaviviruses. Viral replication and spread, IFN induction and response, and cellular viability were analyzed. Transcriptional levels in primary astrocytes treated with interferon or supernatant from virus-infected cells were analyzed by RNA sequencing and evaluated by different bioinformatics tools.ResultsHere, we show that astrocytes control viral replication of different TBEV strains, JEV, WNV, and ZIKV. In contrast to fibroblast, astrocytes mount a rapid interferon response and restrict viral spread. Furthermore, basal expression levels of key interferon-stimulated genes are high in astrocytes compared to mouse embryonic fibroblasts. Bioinformatic analysis of RNA-sequencing data reveals that astrocytes have established a basal antiviral state which contributes to the rapid viral recognition and upregulation of interferons. The most highly upregulated pathways in neighboring cells were linked to type I interferon response and innate immunity. The restriction in viral growth was dependent on interferon signaling, since loss of the interferon receptor, or its blockade in wild-type cells, resulted in high viral replication and virus-induced cytopathic effects. Astrocyte supernatant from TBEV-infected cells can restrict TBEV growth in astrocytes already 6 h post infection, the effect on neurons is highly reinforced, and astrocyte supernatant from 3 h post infection is already protective.ConclusionsThese findings suggest that the combination of an intrinsic constitutive antiviral response and the fast induction of type I IFN production by astrocytes play an important role in self-protection of astrocytes and suppression of flavivirus replication in the CNS.Electronic supplementary materialThe online version of this article (doi:10.1186/s12974-016-0748-7) contains supplementary material, which is available to authorized users.

Activation of phosphoinositide 3-kinase (PI3K) signaling is frequently observed in triplenegative breast cancer (TNBC), yet PI3K inhibitors have shown limited clinical activity.To investigate intrinsic and adaptive mechanisms of resistance, we analyzed a panel of patient-derived xenograft models of TNBC with varying responsiveness to buparlisib, a pan-PI3K inhibitor. In a subset of patient-derived xenografts, resistance was associated with incomplete inhibition of PI3K signaling and upregulated MAPK/MEK signaling in response to buparlisib. Outlier phosphoproteome and kinome analyses identified novel candidates functionally important to buparlisib resistance, including NEK9 and MAP2K4.Knockdown of NEK9 or MAP2K4 reduced both baseline and feedback MAPK/MEK signaling and showed synthetic lethality with buparlisib in vitro. A complex in/del frameshift in PIK3CA decreased sensitivity to buparlisib via NEK9/MAP2K4-dependent mechanisms. In summary, our study supports a role for NEK9 and MAP2K4 in mediating buparlisib resistance and demonstrates the value of unbiased omic analyses in uncovering resistance mechanisms to targeted therapy. STATEMENT OF SIGNIFICANCEIntegrative phospho-proteogenomic analyses is used to determine intrinsic resistance mechanisms of triple negative breast tumors to PI3K inhibition.

Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple biomedical databases and publications, pose a challenge to data integration. Here we present the Clinical Knowledge Graph (CKG), an open-source platform currently comprising close to 20 million nodes and 220 million relationships that represent relevant experimental data, public databases and literature. The graph structure provides a flexible data model that is easily extendable to new nodes and relationships as new databases become available. The CKG incorporates statistical and machine learning algorithms that accelerate the analysis and interpretation of typical proteomics workflows. Using a set of proof-of-concept biomarker studies, we show how the CKG might augment and enrich proteomics data and help inform clinical decision-making.

BackgroundBritain’s native oak species are currently under threat from acute oak decline (AOD), a decline-disease where stem bleeds overlying necrotic lesions in the inner bark and larval galleries of the bark-boring beetle, Agrilus biguttatus, represent the primary symptoms. It is known that complex interactions between the plant host and its microbiome, i.e. the holobiont, significantly influence the health status of the plant. In AOD, necrotic lesions are caused by a microbiome shift to a pathobiome consisting predominantly of Brenneria goodwinii, Gibbsiella quercinecans, Rahnella victoriana and potentially other bacteria. However, the specific mechanistic processes of the microbiota causing tissue necrosis, and the host response, have not been established and represent a barrier to understanding and managing this decline.ResultsWe profiled the metagenome, metatranscriptome and metaproteome of inner bark tissue from AOD symptomatic and non-symptomatic trees to characterise microbiota-host interactions. Active bacterial virulence factors such as plant cell wall-degrading enzymes, reactive oxygen species defence and flagella in AOD lesions, along with host defence responses including reactive oxygen species, cell wall modification and defence regulators were identified. B. goodwinii dominated the lesion microbiome, with significant expression of virulence factors such as the phytopathogen effector avrE. A smaller proportion of microbiome activity was attributed to G. quercinecans and R. victoriana. In addition, we describe for the first time the potential role of two previously uncharacterised Gram-positive bacteria predicted from metagenomic binning and identified as active in the AOD lesion metatranscriptome and metaproteome, implicating them in lesion formation.ConclusionsThis multi-omic study provides novel functional insights into microbiota-host interactions in AOD, a complex arboreal decline disease where polymicrobial-host interactions result in lesion formation on tree stems. We present the first descriptions of holobiont function in oak health and disease, specifically, the relative lesion activity of B. goodwinii, G. quercinecans, Rahnella victoriana and other bacteria. Thus, the research presented here provides evidence of some of the mechanisms used by members of the lesion microbiome and a template for future multi-omic research into holobiont characterisation, plant polymicrobial diseases and pathogen defence in trees.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0408-5) contains supplementary material, which is available to authorized users.