Clinical Proteomics in the Mann Group

The main research focus of Professor Matthias Mann’s laboratory is to identify novel biomarkers that can be used for patient diagnosis and possibly for the prevention and treatment of metabolic diseases, such as diabetes and cancer. To this end, the lab is developing and using cutting-edge mass spectrometry-based proteomics; an area in which the Mann Group is world-leading.

Research focus

The Mann Group undertakes ambitious research projects involving proteomics of blood, plasma, cerebrospinal fluid and tissue for the phenotyping of patients. One goal is to establish robust, high-throughput proteome profiling pipelines for these materials, allowing for the proteomic screening of clinical cohorts. The group’s overarching aim is to identify biological markers for early detection of metabolic disorders, to improve diagnosis and help to develop individualized therapies.

“Our eventual goal is to prevent the development of the metabolic syndrome in the first place, by targeted and personalized life style interventions,” says Professor and Group Leader, Matthias Mann.

To this end, the group builds on its longstanding expertise in mass spectrometry to implement an artificial intelligence-guided platform for analyzing the proteomes of patient tissue from low amounts of formalin-fixed, paraffin-embedded samples at high accuracy and sensitivity.

“Our highly sensitive methods now enable us to simultaneously profile thousands of proteins derived from only a few hundred cells, allowing us to identify the proteins that are most critical for various diseases,” Mann says.

Another area of focus is the interpretation of ‘multi-omics’ data, which is still a challenge. Often, a single ‘omics’ dimension is not sufficient to capture the full complexity of a disease. To overcome these challenges, the Mann Group is developing the Clinical Knowledge Graph where multi-omics data, together with vast amounts of meta-data, is collected and harmonized – enabling analyses and providing an excellent ecosystem for machine learning.

Main findings

Multi-level Proteomics Identifies CT45 as a Chemosensitivity Mediator and Immunotherapy Target in Ovarian Cancer.

Integrative proteomic analysis in clinical tumor samples identifies a platinum sensitivity regulator and immunotherapy target for ovarian cancer and illustrates the clinical potential of cancer proteomics.

Plasma proteome profiling discovers novel proteins associated with non-alcoholic fatty liver disease.
Lili Niu et al, Mol Syst Biol, accepted (2019)

We employed Plasma Proteome Profiling augmented by a novel mass spectrometry acquisition method – “Boxcar” to identify potential biomarkers of non-alcoholic fatty liver disease (NAFLD) in human cohorts. We identified PIGR and ALDOB, among other four proteins significantly associated with NAFLD as well as a panel of five proteins correlating with four classic liver enzymes. A mouse model recapitulated many of the changes seen in human cohorts.

Mass-spectrometric exploration of proteome structure and function.

Recent advances in mass spectrometry-based proteomics now enable the investigation of nearly complete proteomes and has evolved into the method of choice for the identification and quantitation of proteins as well as their site-specific posttranslational modifications.

Staff of the Mann Group

Group Leader: Professor and Research Director Matthias Mann

Staff of the Mann Group