PRINCESSA: Erstellung eines R-Paketes und einer zugehörigen Web-Applikation zur ProteinCoexpressions-Analyse

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1 PRINCESSA: Erstellung eines R-Paketes und einer zugehörigen Web-Applikation zur ProteinCoexpressions-Analyse Studienprojekt im Vertiefungsgebiet Bioinformatik Ruhr-Universität Bochum July 11th, 2018 Dr. Michael Turewicz Medical Faculty Medizinisches Proteom-Center

2 Biomarker Candidates in Liver Cancer: ICC vs. PDAC Histological discrimination of ICC and mpdac is challenging for the pathologist Different treatment options make differential diagnosis clinically highly relevant Novel biomarkers are urgently needed Immunohistochemical Validation of Protein Biomarkers: (73 ICC vs. 78 PDAC) Protein Biomarker Candidate Discovery Phase: Label-free Proteome Analysis (9 ICC vs. 11 PDAC) Padden J, Ahrens M, Kälsch J, Bertram S, Megger DA, Bracht T, Eisenacher M, Kocabayoglu P, Meyer HE, Sipos B, Baba HA, Sitek B (2016) Immunohistochemical Markers Distinguishing Cholangiocellular Carcinoma (CCC) from Pancreatic Ductal Adenocarcinoma (PDAC) Discovered by Proteomic Analysis of Microdissected Cells. Mol Cell Proteomics 2016 Mar;15(3):

3 Generic MS based proteomics workflow Pre-processing Sample collection (breaking up cells, fractionation, enrichment, ) (cell culture, tissue, ) Protein quantification Digestion into peptides (bottom-up) High-PerformanceLiquid-Chromatography (Reduction of complexity) Protein inference Proteins A D B C E Peptide- / spectrum-identification 1 4 Peptides MS and MS/MS

4 Protein expression profiles 4

5 Here: Sub-network of interconnected (= co-expressed) proteins Network inference Nodes = proteins Edges = coexpression 5

6 Network interpretation Enrichment results (adjusted p-values): GO (cellular component): proteasome core complex, alpha subunit complex (p = 3.66e14) KEGG pathway: proteasome (p = 1.54e-12) PFAM domains: proteasome subunit (p = 1.3e-17) INTERPRO domains: Proteasome, subunit alpha/beta (p = 2.77e-17) Components of the ubiquitinproteasome pathway are known targets for cancer therapy (proteasome inhibitors) also in discussion for HCC = proteasome subunit 6 6

7 Objectives of the PRINCESSA project (PRoteIN CoexprESSion Analysis) Implementation of an R package that Detects sub-networks of interconnected (= co-expressed) proteins in datasets of thousands of proteins ( network inference & topological clustering) Visualizes these sub-networks Links knowledge from public databases to facilitate results interpretation Implementation of an web application that Makes the above R package available for a broad audience Technology: E.g., R-Shiny or more advanced techniques Summarizes all results (i.e., statistics of protein expression, co-expression sub-networks, knowledge from external sources) in an intuitive manner 7 7

8 PRINCESSA: Organisation Möglicher Beginn: Teilnehmer: 2 BSc oder MSc Erwartete Fähigkeiten: Erfahrung mit Linux-basierten Systemen grundlegende Webprogrammierungs-Kenntnisse (u.a. HTML, CSS, Javascript) grundlegende Statistik-Kenntnisse R-Programmierkenntnisse bzw. Bereitschaft R zu erlernen Voraussetzungen: Bioinformatik-Kenntnisse (hilfreich, aber kein Muss) Organisation der Arbeit: erste Besprechung: anschl. regelmäßige Treffen oder Arbeitsplatz am Institut Erwünschte Angaben seitens der Interessenten: Angaben zu den obigen Fähigkeiten (z.b. bisherige Veranstaltungen) Ansprechpartner: PD Dr. Martin Eisenacher, 29288, martin.eisenacher@rub.de (Prüfer) Dr. Michael Turewicz, 29290, michael.turewicz@rub.de (Betreuer) 8 8

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