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Genome Wide Proteomics of ERBB2 and EGFR and Other Oncogenic Pathways in Inflammatory Breast Cancer
Zhang, Emma Yue,Cristofanilli, Massimo,Robertson, Fredika,Reuben, James M.,Mu, Zhaomei,Beavis, Ronald C.,Im, Hogune,Snyder, Michael,Hofree, Matan,Ideker, Trey,Omenn, Gilbert S.,Fanayan, Susan,Jeong, S American Chemical Society 2013 Journal of proteome research Vol.12 No.6
<P>In this study we selected three breast cancer cell lines (SKBR3, SUM149 and SUM190) with different oncogene expression levels involved in ERBB2 and EGFR signaling pathways as a model system for the evaluation of selective integration of subsets of transcriptomic and proteomic data. We assessed the oncogene status with reads per kilobase per million mapped reads (RPKM) values for ERBB2 (14.4, 400, and 300 for SUM149, SUM190, and SKBR3, respectively) and for EGFR (60.1, not detected, and 1.4 for the same 3 cell lines). We then used RNA-Seq data to identify those oncogenes with significant transcript levels in these cell lines (total 31) and interrogated the corresponding proteomics data sets for proteins with significant interaction values with these oncogenes. The number of observed interactors for each oncogene showed a significant range, e.g., 4.2% (JAK1) to 27.3% (MYC). The percentage is measured as a fraction of the total protein interactions in a given data set vs total interactors for that oncogene in STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 9.0) and I2D (Interologous Interaction Database, version 1.95). This approach allowed us to focus on 4 main oncogenes, ERBB2, EGFR, MYC, and GRB2, for pathway analysis. We used bioinformatics sites GeneGo, PathwayCommons and NCI receptor signaling networks to identify pathways that contained the four main oncogenes and had good coverage in the transcriptomic and proteomic data sets as well as a significant number of oncogene interactors. The four pathways identified were ERBB signaling, EGFR1 signaling, integrin outside-in signaling, and validated targets of C-MYC transcriptional activation. The greater dynamic range of the RNA-Seq values allowed the use of transcript ratios to correlate observed protein values with the relative levels of the ERBB2 and EGFR transcripts in each of the four pathways. This provided us with potential proteomic signatures for the SUM149 and 190 cell lines, growth factor receptor-bound protein 7 (GRB7), Crk-like protein (CRKL) and Catenin delta-1 (CTNND1) for ERBB signaling; caveolin 1 (CAV1), plectin (PLEC) for EGFR signaling; filamin A (FLNA) and actinin alpha1 (ACTN1) (associated with high levels of EGFR transcript) for integrin signalings; branched chain amino-acid transaminase 1 (BCAT1), carbamoyl-phosphate synthetase (CAD), nucleolin (NCL) (high levels of EGFR transcript); transferrin receptor (TFRC), metadherin (MTDH) (high levels of ERBB2 transcript) for MYC signaling; S100-A2 protein (S100A2), caveolin 1 (CAV1), Serpin B5 (SERPINB5), stratifin (SFN), PYD and CARD domain containing (PYCARD), and EPH receptor A2 (EPHA2) for PI3K signaling, p53 subpathway. Future studies of inflammatory breast cancer (IBC), from which the cell lines were derived, will be used to explore the significance of these observations.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/jprobs/2013/jprobs.2013.12.issue-6/pr4001527/production/images/medium/pr-2013-001527_0010.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/pr4001527'>ACS Electronic Supporting Info</A></P>
The HUPO Plasma Proteome Project: A report from the Munich congress
Omenn, Gilbert S.,Paik, Young-Ki,Speicher, David WILEY-VCH Verlag 2006 Proteomics Vol.6 No.1
<P>The Human Proteome Organization has several major collaborative research initiatives, including the Plasma Proteome Project. A major feature of the HUPO World Congress in Munich in August 2005 was the release of the special issue of PROTEOMICS with 28 articles from the pilot phase of the Plasma Proteome Project. An open Workshop and a presentation in the closing plenary session of the congress focused on next phases for the Plasma Proteome Project.</P>
Omenn, Gilbert S.,Aebersold, Ruedi,Paik, Young-Ki WILEY-VCH Verlag 2009 Proteomics Vol.9 No.1
<P>The HUPO Plasma Proteome Project new phase, PPP-2, held its initial workshop on 17 August, 2008, at the 7<SUP>th</SUP> World Congress of Proteomics in Amsterdam. Technology platforms, data repositories, informatics, and engagement of research groups for the submission of major datasets were key topics. Plasma is expected to be the common pathway for biomarker development and application through collaboration and integration with other HUPO initiatives.</P>
Omenn, Gilbert S.,Lane, Lydie,Overall, Christopher M.,Corrales, Fernando J.,Schwenk, Jochen M.,Paik, Young-Ki,Van Eyk, Jennifer E.,Liu, Siqi,Snyder, Michael,Baker, Mark S.,Deutsch, Eric W. American Chemical Society 2018 Journal of proteome research Vol.17 No.12
<P>The Human Proteome Project (HPP) annually reports on progress throughout the field in credibly identifying and characterizing the human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2018-01-17, the baseline for this sixth annual HPP special issue of the <I>Journal of Proteome Research</I>, contains 17 470 PE1 proteins, 89% of all neXtProt predicted PE1-4 proteins, up from 17 008 in release 2017-01-23 and 13 975 in release 2012-02-24. Conversely, the number of neXtProt PE2,3,4 missing proteins has been reduced from 2949 to 2579 to 2186 over the past two years. Of the PE1 proteins, 16 092 are based on mass spectrometry results, and 1378 on other kinds of protein studies, notably protein-protein interaction findings. PeptideAtlas has 15 798 canonical proteins, up 625 over the past year, including 269 from SUMOylation studies. The largest reason for missing proteins is low abundance. Meanwhile, the Human Protein Atlas has released its Cell Atlas, Pathology Atlas, and updated Tissue Atlas, and is applying recommendations from the International Working Group on Antibody Validation. Finally, there is progress using the quantitative multiplex organ-specific popular proteins targeted proteomics approach in various disease categories.</P> [FIG OMISSION]</BR>
Omenn, Gilbert ,S.,States, David ,J.,Adamski, Marcin,Blackwell, Thomas ,W.,Menon, Rajasree,Hermjakob, Henning,Apweiler, Rolf,Haab, Brian ,B.,Simpson, Richard ,J.,Eddes, J WILEY-VCH 2005 PROTEOMICS -WEINHEIM- Vol.5 No.13
<P>HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs.</P><P>We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches.</P><P>This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.</P>