Proteomics

Genomic changes as causes for malignant diseases were intensively studied in the past and their profiling is efficiently integrated in the clinical routine. Genetic alterations lead to changes in essential cellular processes, such as cell survival and metabolism, whose activation status can be read out in the proteome and phosphoproteome. Thus, the integration of genomic, proteomic and phosphoproteomic data of cancer patients gains more and more importance for detailed diagnostics and the identification of new therapeutic targets, due to a better accessibility of proteins as target structures. This is why, several MSTARS partners focus on a mass spectrometry (MS)-based deep analysis of proteomic alterations and join forces to implement standardized and advanced proteomic analyses that may be applied in the clinics in the future. An immediate goal is also to identify proteomic signatures that support therapy recommendations.

Mertins Lab

The group of Philipp Mertins has long-standing expertise in the field of genome and proteome integration for a deep characterization of disease mechanisms. With their approaches, they analyze in detail, which effects genetic alterations have on protein regulatory networks and signaling pathways in tumors and combine these information with results obtained from drug efficacy tests. The group uses advanced technologies, such as label-free and tandem mass tag (TMT)-based global and targeted protein quantification, post-translational modification analysis, ultrahigh-pressure liquid chromatography and high-resolution orbitrap MS, and focuses on further augmenting the throughput and coverage of these techniques.
In the MSTARS consortium, AG Mertins characterizes the proteome and phosphoproteome of treated and untreated patient-derived HNSCC models and clinical cohorts of pro- and retrospective patient samples, to improve subtyping and stratification of HNSCC cases. The generated data will be analyzed and evaluated in terms of associations with the disease entity, molecular subtypes, survival, and the treatment response. Further aims are the development of yet more sensitive and comprehensive MS methods for tissue proteomics applications and MS-based assays for disease-associated proteins as diagnostic tools.

Selbach Lab

Matthias Selbach and his team are experts in the analysis of global proteome dynamics. They seek to understand how genomic information is interpreted to yield a specific phenotype by analyzing protein synthesis and degradation, protein-protein interactions and posttranslational modifications. To tackle this task they use quantitative affinity purification combined with MS (q-AP-MS) that allows the efficient analysis of protein function in healthy and diseased individuals, shedding light on e.g. protein-protein interactions during signal transduction and as a consequence of pathogenic mutations.
As part of the MSTARS consortium AG Selbach aims for the implementation of q-AP-MS workflows for clinical samples. To this end, they are developing a scalable technique that increases the throughput of q-AP-MS, which will be used to analyze central signaling hubs of the EGFR, PI3K and mTOR signaling pathways in treated and untreated patient-derived models and patient samples. Their analyses will deliver information on protein-protein interactions that might either correlate with therapy success or failure.

Ralser Lab

The proteomic analysis of clinical samples requires robust mass spectrometric methods with a high throughput and accurate quantification. The work of AG Ralser focuses on the advancement of mass spectrometric methods in these areas heading towards high-throughput metabolomic and proteomic analyses as well as their integration into clinical and epidemiological studies. In addition, the group of Markus Ralser combines the advanced methods with functional genomics to study regulatory functions of the cell metabolism and the maintenance of its dynamics.
In the context of the MSTARS consortium, AG Ralser uses the newest ultra high-throughput MS analysis platform, combined with Scanning-SWATH as acquisition method, to analyze the available untreated and treated patient-derived models as well as blood and tissue samples of patients to perform comparative analyses of proximal (tissue) and distal (blood) proteomic signatures. Furthermore, the measured proteomes will be compared to epidemiologic data to evaluate the predictive value for treatment outcomes and peptide standards are established that allow in combination with diagnostic features the design of prognostic assays for the clinics. In a last step, the group of Markus Ralser addresses the value of ionomics as a tool for patient stratification.