Phosphoproteomics of Primary Cells Reveals Druggable Kinase Signatures in Ovarian Cancer

[1]  Ruedi Aebersold,et al.  Mass-spectrometric exploration of proteome structure and function , 2016, Nature.

[2]  Marco Y. Hein,et al.  The Perseus computational platform for comprehensive analysis of (prote)omics data , 2016, Nature Methods.

[3]  Ronald J. Moore,et al.  Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer , 2016, Cell.

[4]  Michael L. Gatza,et al.  Proteogenomics connects somatic mutations to signaling in breast cancer , 2016, Nature.

[5]  I. Shih,et al.  The Dualistic Model of Ovarian Carcinogenesis: Revisited, Revised, and Expanded. , 2016, The American journal of pathology.

[6]  D. Sabatini,et al.  A PHGDH inhibitor reveals coordination of serine synthesis and 1-carbon unit fate , 2016, Nature chemical biology.

[7]  Eytan Ruppin,et al.  System-wide Clinical Proteomics of Breast Cancer Reveals Global Remodeling of Tissue Homeostasis. , 2016, Cell systems.

[8]  A. Zelanis,et al.  Proteomics and drug discovery in cancer. , 2016, Drug discovery today.

[9]  Min Sik Kim,et al.  A multi-omic analysis of human naïve CD4+ T cells , 2015, BMC Systems Biology.

[10]  David Fenyö,et al.  Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts* , 2015, Molecular & Cellular Proteomics.

[11]  V. Beral,et al.  Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer , 2015, Nature Reviews Cancer.

[12]  Robert G. Ramsay,et al.  Directly targeting transcriptional dysregulation in cancer , 2015, Nature Reviews Cancer.

[13]  C. Gourley,et al.  Ovarian Cancer Molecular Stratification and Tumor Heterogeneity: A Necessity and a Challenge , 2015, Front. Oncol..

[14]  Panagiotis K. Papasaikas,et al.  Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data , 2015, BMC Genomics.

[15]  Panagiotis K. Papasaikas,et al.  Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data , 2015, BMC Genomics.

[16]  Jesper V Olsen,et al.  Recent findings and technological advances in phosphoproteomics for cells and tissues , 2015, Expert review of proteomics.

[17]  R. Young,et al.  CDK7-Dependent Transcriptional Addiction in Triple-Negative Breast Cancer , 2015, Cell.

[18]  D. Price,et al.  THZ1 Reveals Roles for Cdk7 in Co-transcriptional Capping and Pausing. , 2015, Molecular cell.

[19]  Xiongbin Lu,et al.  Abstract A36: TP53 loss creates therapeutic vulnerability in colorectal cancer , 2017 .

[20]  Janos X. Binder,et al.  DISEASES: Text mining and data integration of disease–gene associations , 2014, bioRxiv.

[21]  E. Seifritz,et al.  Altered emotionality and neuronal excitability in mice lacking KCTD12, an auxiliary subunit of GABAB receptors associated with mood disorders , 2015, Translational Psychiatry.

[22]  Agnieszka K. Witkiewicz,et al.  The history and future of targeting cyclin-dependent kinases in cancer therapy , 2015, Nature Reviews Drug Discovery.

[23]  Ludovic C. Gillet,et al.  Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps , 2015, Nature Medicine.

[24]  P. Ostano,et al.  Patient-derived ovarian tumor xenografts recapitulate human clinicopathology and genetic alterations. , 2014, Cancer research.

[25]  Yan Liu,et al.  Targeting transcriptional addictions in small cell lung cancer with a covalent CDK7 inhibitor. , 2014, Cancer cell.

[26]  B. Davidson,et al.  Ovarian Cancer: Diagnostic, Biological and Prognostic Aspects , 2014, Women's health.

[27]  A. Shilatifard,et al.  Inhibit globally, act locally: CDK7 inhibitors in cancer therapy. , 2014, Cancer Cell.

[28]  Sridhar Ramaswamy,et al.  Targeting transcription regulation in cancer with a covalent CDK7 inhibitor , 2014, Nature.

[29]  Gary D Bader,et al.  A draft map of the human proteome , 2014, Nature.

[30]  B. Kuster,et al.  Mass-spectrometry-based draft of the human proteome , 2014, Nature.

[31]  J. Hernandez-Fernaud,et al.  Quantitative phosphoproteomics unveils temporal dynamics of thrombin signaling in human endothelial cells. , 2014, Blood.

[32]  M. Mann,et al.  Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells , 2014, Nature Methods.

[33]  S. Gabriel,et al.  Discovery and saturation analysis of cancer genes across 21 tumor types , 2014, Nature.

[34]  M. Mann,et al.  Status of Large-scale Analysis of Post-translational Modifications by Mass Spectrometry* , 2013, Molecular & Cellular Proteomics.

[35]  Blagoy Blagoev,et al.  Functional proteomics defines the molecular switch underlying FGF receptor trafficking and cellular outputs. , 2013, Molecular cell.

[36]  R. Drapkin,et al.  Modeling High-Grade Serous Carcinoma: How Converging Insights into Pathogenesis and Genetics are Driving Better Experimental Platforms , 2013, Front. Oncol..

[37]  C. Sander,et al.  Evaluating cell lines as tumour models by comparison of genomic profiles , 2013, Nature Communications.

[38]  Heiko Horn,et al.  In Vivo Phosphoproteomics Analysis Reveals the Cardiac Targets of β-Adrenergic Receptor Signaling , 2013, Science Signaling.

[39]  C. Gilks,et al.  Molecular abnormalities in ovarian carcinoma: clinical, morphological and therapeutic correlates , 2013, Histopathology.

[40]  Damian Szklarczyk,et al.  STRING v9.1: protein-protein interaction networks, with increased coverage and integration , 2012, Nucleic Acids Res..

[41]  R. Roskoski ERK1/2 MAP kinases: structure, function, and regulation. , 2012, Pharmacological research.

[42]  Richard J. Lavallee,et al.  Optimized fast and sensitive acquisition methods for shotgun proteomics on a quadrupole orbitrap mass spectrometer. , 2012, Journal of proteome research.

[43]  Matthias Mann,et al.  Proteomic portrait of human breast cancer progression identifies novel prognostic markers. , 2012, Cancer research.

[44]  Ruedi Aebersold,et al.  Protein expression changes in ovarian cancer during the transition from benign to malignant. , 2012, Journal of proteome research.

[45]  Ben Davidson,et al.  Epithelial–Mesenchymal Transition in Ovarian Carcinoma , 2012, Front. Oncol..

[46]  Ji Luo Cancer's sweet tooth for serine , 2011, Breast Cancer Research.

[47]  Benjamin J. Raphael,et al.  Integrated Genomic Analyses of Ovarian Carcinoma , 2011, Nature.

[48]  P. Boutros,et al.  In-depth proteomics of ovarian cancer ascites: combining shotgun proteomics and selected reaction monitoring mass spectrometry. , 2011, Journal of proteome research.

[49]  M. Mann,et al.  Andromeda: a peptide search engine integrated into the MaxQuant environment. , 2011, Journal of proteome research.

[50]  M. Daly,et al.  Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology , 2011, PLoS genetics.

[51]  E. Kohn,et al.  Proteomics as a guiding tool for more effective personalized therapy. , 2010, Annals of oncology : official journal of the European Society for Medical Oncology.

[52]  A. Kornblihtt,et al.  The carboxy terminal domain of RNA polymerase II and alternative splicing. , 2010, Trends in biochemical sciences.

[53]  Lennart Martens,et al.  PRIDE: Data Submission and Analysis , 2010, Current protocols in protein science.

[54]  K. Gevaert,et al.  Improved visualization of protein consensus sequences by iceLogo , 2009, Nature Methods.

[55]  J. Marto,et al.  Primary ex-vivo cultures of human fallopian tube epithelium as a model for serous ovarian carcinogenesis , 2009, Oncogene.

[56]  M. Mann,et al.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification , 2008, Nature Biotechnology.

[57]  Kathleen R. Cho,et al.  Comparative proteomic analysis of low stage and high stage endometrioid ovarian adenocarcinomas , 2008, Proteomics. Clinical applications.

[58]  A. Godwin,et al.  The differential role of L1 in ovarian carcinoma and normal ovarian surface epithelium. , 2008, Cancer research.

[59]  Gil Ast,et al.  Alternative splicing and disease , 2008, RNA biology.

[60]  M. Mann,et al.  Global, In Vivo, and Site-Specific Phosphorylation Dynamics in Signaling Networks , 2006, Cell.

[61]  R. Fisher Secrets of a double agent: CDK7 in cell-cycle control and transcription , 2005, Journal of Cell Science.

[62]  Gordon K. Smyth,et al.  limmaGUI: A graphical user interface for linear modeling of microarray data , 2004, Bioinform..

[63]  T. Honjo,et al.  ESDN, a Novel Neuropilin-like Membrane Protein Cloned from Vascular Cells with the Longest Secretory Signal Sequence among Eukaryotes, Is Up-regulated after Vascular Injury* , 2001, The Journal of Biological Chemistry.

[64]  J. Wityak,et al.  MEK inhibitors: the chemistry and biological activity of U0126, its analogs, and cyclization products. , 1998, Bioorganic & medicinal chemistry letters.

[65]  G. Breitenecker,et al.  Tissue expression of CA 125 in benign and malignant lesions of ovary and fallopian tube: a comparison with CA 19-9 and CEA. , 1989, Gynecologic Oncology.

[66]  J. Olsen,et al.  Simple and Reproducible Sample Preparation for Single-Shot Phosphoproteomics with High Sensitivity. , 2016, Methods in molecular biology.

[67]  J. Olsen,et al.  Offline High pH Reversed-Phase Peptide Fractionation for Deep Phosphoproteome Coverage. , 2016, Methods in molecular biology.

[68]  Ruedi Aebersold,et al.  Comprehensive proteomics. , 2011, Current opinion in biotechnology.

[69]  H. Taylor,et al.  3-Phosphoglycerate dehydrogenase expression is regulated by HOXA10 in murine endometrium and human endometrial cells. , 2010, Reproduction.

[70]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.