Recurrent somatic ASXL1 mutations occur in patients with myelodysplastic syndrome, myeloproliferative neoplasms, and acute myeloid leukemia, and are associated with adverse outcome. Despite the ...genetic and clinical data implicating ASXL1 mutations in myeloid malignancies, the mechanisms of transformation by ASXL1 mutations are not understood. Here, we identify that ASXL1 mutations result in loss of polycomb repressive complex 2 (PRC2)-mediated histone H3 lysine 27 (H3K27) tri-methylation. Through integration of microarray data with genome-wide histone modification ChIP-Seq data, we identify targets of ASXL1 repression, including the posterior HOXA cluster that is known to contribute to myeloid transformation. We demonstrate that ASXL1 associates with the PRC2, and that loss of ASXL1 in vivo collaborates with NRASG12D to promote myeloid leukemogenesis.
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► ASXL1 mutations are loss-of-function mutations ► ASXL1 loss results in a genome-wide reduction in H3K27me3 occupancy ► ASXL1 interacts with the PRC2 complex and is important for PRC2 recruitment ► ASXL1 collaborates with co-occurring oncogenes in vivo to promote leukemogenesis
We report a mass spectrometry-based method for the integrated analysis of protein expression, phosphorylation, ubiquitination and acetylation by serial enrichments of different post-translational ...modifications (SEPTM) from the same biological sample. This technology enabled quantitative analysis of nearly 8,000 proteins and more than 20,000 phosphorylation, 15,000 ubiquitination and 3,000 acetylation sites per experiment, generating a holistic view of cellular signal transduction pathways as exemplified by analysis of bortezomib-treated human leukemia cells.
To address the growing need for a centralized, community resource of published results processed with Skyline, and to provide reviewers and readers immediate visual access to the data behind ...published conclusions, we present Panorama Public (https://panoramaweb.org/public.url), a repository of Skyline documents supporting published results. Panorama Public is built on Panorama, an open source data management system for mass spectrometry data processed with the Skyline targeted mass spectrometry environment. The Panorama web application facilitates viewing, sharing, and disseminating results contained in Skyline documents via a web-browser. Skyline users can easily upload their documents to a Panorama server and allow other researchers to explore uploaded results in the Panorama web-interface through a variety of familiar summary graphs as well as annotated views of the chromatographic peaks processed with Skyline. This makes Panorama ideal for sharing targeted, quantitative results contained in Skyline documents with collaborators, reviewers, and the larger proteomics community. The Panorama Public repository employs the full data visualization capabilities of Panorama which facilitates sharing results with reviewers during manuscript review.
Oxygen sensing is central to metazoan biology and has implications for human disease. Mammalian cells express multiple oxygen-dependent enzymes called 2-oxoglutarate (OG)-dependent dioxygenases ...(2-OGDDs), but they vary in their oxygen affinities and hence their ability to sense oxygen. The 2-OGDD histone demethylases control histone methylation. Hypoxia increases histone methylation, but whether this reflects direct effects on histone demethylases or indirect effects caused by the hypoxic induction of the HIF (hypoxia-inducible factor) transcription factor or the 2-OG antagonist 2-hydroxyglutarate (2-HG) is unclear. Here, we report that hypoxia promotes histone methylation in a HIF- and 2-HG-independent manner. We found that the H3K27 histone demethylase KDM6A/UTX, but not its paralog KDM6B, is oxygen sensitive. KDM6A loss, like hypoxia, prevented H3K27 demethylation and blocked cellular differentiation. Restoring H3K27 methylation homeostasis in hypoxic cells reversed these effects. Thus, oxygen directly affects chromatin regulators to control cell fate.
Pathway 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.
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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.
Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM data sets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTMSignature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized data set of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared with gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.
Polycomb repressive complex 2 (PRC2) plays crucial roles in transcriptional regulation and stem cell development. However, the context-specific functions associated with alternative subunits remain ...largely unexplored. Here we show that the related enzymatic subunits EZH1 and EZH2 undergo an expression switch during blood cell development. An erythroid-specific enhancer mediates transcriptional activation of EZH1, and a switch from GATA2 to GATA1 controls the developmental EZH1/2 switch by differential association with EZH1 enhancers. We further examine the in vivo stoichiometry of the PRC2 complexes by quantitative proteomics and reveal the existence of an EZH1-SUZ12 subcomplex lacking EED. EZH1 together with SUZ12 form a non-canonical PRC2 complex, occupy active chromatin, and positively regulate gene expression. Loss of EZH2 expression leads to repositioning of EZH1 to EZH2 targets. Thus, the lineage- and developmental stage-specific regulation of PRC2 subunit composition leads to a switch from canonical silencing to non-canonical functions during blood stem cell specification.
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•During blood cell development there is a switch from EZH2 to EZH1 expression•GATA switch regulates EZH2 to EZH1 switch through lineage-specific EZH1 enhancers•EZH1 and SUZ12 form a non-canonical PRC2 complex in transcriptional activation•Alternative PRC2 subunit composition confers a switch to non-canonical functions
Xu et al. show that the developmental switch of lineage-specifying GATA factors controls an expression switch of EZH2 to EZH1 during blood cell differentiation. EZH1 and SUZ12 assemble a non-canonical complex independent of EED and positively regulate gene expression. Thus, the alternative PRC2 subunit composition confers non-canonical functions during development.
Introduction of antibodies specific for acetylated lysine has significantly improved the detection of endogenous acetylation sites by mass spectrometry. Here, we describe a new, commercially ...available mixture of anti-lysine acetylation (Kac) antibodies and show its utility for in-depth profiling of the acetylome. Specifically, seven complementary monoclones with high specificity for Kac were combined into a final anti-Kac reagent which results in at least a twofold increase in identification of Kac peptides over a commonly used Kac antibody. We outline optimal antibody usage conditions, effective offline basic reversed phase separation, and use of state-of-the-art LC-MS technology for achieving unprecedented coverage of the acetylome. The methods were applied to quantify acetylation sites in suberoylanilide hydroxamic acid-treated Jurkat cells. Over 10,000 Kac peptides from over 3000 Kac proteins were quantified from a single stable isotope labeling by amino acids in cell culture labeled sample using 7.5 mg of peptide input per state. This constitutes the deepest coverage of acetylation sites in quantitative experiments obtained to-date. The approach was also applied to breast tumor xenograft samples using isobaric mass tag labeling of peptides (iTRAQ4, TMT6 and TMT10-plex reagents) for quantification. Greater than 6700 Kac peptides from over 2300 Kac proteins were quantified using 1 mg of tumor protein per iTRAQ 4-plex channel. The novel reagents and methods we describe here enable quantitative, global acetylome analyses with depth and sensitivity approaching that obtained for other well-studied post-translational modifications such as phosphorylation and ubiquitylation, and should have widespread application in biological and clinical studies employing mass spectrometry-based proteomics.
Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular ...underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet.
Labeling of primary amines on peptides with reagents containing stable isotopes is a commonly used technique in quantitative mass spectrometry. Isobaric labeling techniques such as iTRAQ™ or TMT™ ...allow for relative quantification of peptides based on ratios of reporter ions in the low m/z region of spectra produced by precursor ion fragmentation. In contrast, nonisobaric labeling with mTRAQ™ yields precursors with different masses that can be directly quantified in MS1 spectra. In this study, we compare iTRAQ- and mTRAQ-based quantification of peptides and phosphopeptides derived from EGF-stimulated HeLa cells. Both labels have identical chemical structures, therefore precursor ion- and fragment ion-based quantification can be directly compared. Our results indicate that iTRAQ labeling has an additive effect on precursor intensities, whereas mTRAQ labeling leads to more redundant MS2 scanning events caused by triggering on the same peptide with different mTRAQ labels. We found that iTRAQ labeling quantified nearly threefold more phosphopeptides (12,129 versus 4,448) and nearly twofold more proteins (2,699 versus 1,597) than mTRAQ labeling. Although most key proteins in the EGFR signaling network were quantified with both techniques, iTRAQ labeling allowed quantification of twice as many kinases. Accuracy of reporter ion quantification by iTRAQ is adversely affected by peptides that are cofragmented in the same precursor isolation window, dampening observed ratios toward unity. However, because of tighter overall iTRAQ ratio distributions, the percentage of statistically significantly regulated phosphopeptides and proteins detected by iTRAQ and mTRAQ was similar. We observed a linear correlation of logarithmic iTRAQ to mTRAQ ratios over two orders of magnitude, indicating a possibility to correct iTRAQ ratios by an average compression factor. Spike-in experiments using peptides of defined ratios in a background of nonregulated peptides show that iTRAQ quantification is less accurate but not as variable as mTRAQ quantification.
Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, ...candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.
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