gms | German Medical Science

64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

08. - 11.09.2019, Dortmund

Proteogenomics: integrating multiple lines of evidence for patient stratification

Meeting Abstract

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  • Jens Allmer - Medical Informatics and Bioinformatics, Hochschule Ruhr-West – University of Applied Sciences, Mülheim an der Ruhr, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Dortmund, 08.-11.09.2019. Düsseldorf: German Medical Science GMS Publishing House; 2019. DocAbstr. 47

doi: 10.3205/19gmds203, urn:nbn:de:0183-19gmds2032

Veröffentlicht: 6. September 2019

© 2019 Allmer.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



Introduction: A disease often manifests itself through protein dysregulation or protein sequence variation. Sequence variation can occur by chance due to transcription/translation errors or because they are encoded in the genome. Changes in protein abundance depend on regulation and may be controlled genomically, epigenomically or post-transcriptionally. Proteogenomics aims to investigate proteins and correlate them with the genomic level. With decreasing sequencing costs, exome sequencing can be applied on a per patient level. Mass spectrometry to investigate the protein level is also becoming a routine analysis that can be applied for precision medicine.

Methods: A genome codes for the possible proteins that can be expressed. Full genome sequencing is not generally indicated for patient stratification and, therefore, exome sequencing is employed here. On the proteomics level, shotgun sequencing using mass spectrometry (MS) is the current tool of choice. Many modifications can occur to proteins including alternative splicing and alternative open reading frame start sites. These and other differences can be quantified using MS-based proteomics. Proteogenomics offers the possibility to integrate genomic and proteomic information.

Results: This workshop will show how proteogenomics can be achieved for large eukaryotic genomes such as human. Transcript and protein biomarkers can be discovered using a protegenomics workflow and such mechanisms will be discussed in the workshop.

Discussion: This workflow will show how protegenomics fits into the medical workflow for biomarker discovery and patient stratification for precision medicine.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.