Projects

Proteomics and phosphoproteomics to unravel AML heterogeneity

Acute myeloid leukemia (AML) is an aggressive and heterogeneous malignancy characterized by infiltration of immature myeloblasts in the bone marrow. The disease can be cured by intensive chemotherapy, but approximately 50% patients who receive this therapy later die from chemoresistant relapse. Thus, there is a need for a better prognostic classification and therapeutic strategies. We have optimized workflows to characterize the proteome and phosphoproteome from AML patient cells by liquid chromatography-mass spectrometry (LC-MS). Using these methodologies, we have found that relapse was associated with perturbed signaling, protein expression and phosphorylation status; including RNA processing and V-ATPase proteins as well as cyclin-dependent kinases. Recently, we have shown that analyses of serial samples during the first week of treatment by proteomic and phosphoproteomic profiling can be used for the early identification of responders to low-toxicity all-trans retinoic acid (ATRA)/valproic acid-based treatment.

Project leaders: Maria Hernandez-Valladares and Frode Selheim

Characterization of post-translational modifications

A protein can have multiple biological functions because of its different post-translational modifications (PTMs). Thus, PTM discovery contributes significantly to the understanding of cellular signaling and to the finding of new clinical biomarkers. We characterize cell phosphoproteomes by LC-MS using titanium immobilized metal affinity chromatography (Ti-IMAC) or the titanium/iron/hydrophilic interaction chromatography workflow (TiSH) for deeper coverage. We also performed analyses of tyrosine-phosphopeptide- and acetylpeptide-enriched samples by antibody-based capture as well as N-linked glycopeptide preparations by zwitterionic separation. Branched workflows to isolate several PTMs are preferred when performing PTM cross-talk studies.

Project leader: Maria Hernandez-Valladares

Multiple sclerosis biomarker project

Multiple sclerosis is a chronic inflammatory disabling disease of the central nervous system with largely unknown cause and pathogenesis. There is a general lack of available biomarkers for diagnosis, prognosis and treatment prediction. Early diagnosis and treatment is essential to slow down progressive deterioration and accumulation of disability, and biological markers for early detection of the disease are much needed. In our multiple sclerosis biomarker discovery project, we are using state-of-the-art quantitative proteomics methods to discover and verify disease specific protein biomarkers for multiple sclerosis with potential diagnostic or prognostic value, or biomarkers that can be used to follow treatment efficiency. The proteomics methods that we use in this project are: label-free and iTRAQ semi-quantitative shotgun approaches for biomarker discovery, and selected reaction monitoring for biomarker verification.

Project leader: Frode Berven

Obtaining novel biomedical knowledge from omics research

The amount of data generated in biomedical research has grown exponentially, resulting in new challenges for the analysis of the data, especially regarding how to interpret project specific findings in a larger biomedical context. At the same time, recent developments in computer science have made it possible to perform large scale analysis and interpretation of increasingly more complex datasets. Together with the rapidly growing amount of biomedical knowledge available in online repositories, this now provides the opportunity to greatly improve the outcome of biomedical research. The main objective of the Barsnes Group is to combine state-of-the-art bioinformatics research with the current biomedical knowledge, thus building a bridge between project specific high-throughput omics analyses and novel biomedical knowledge.

Project leader: Harald Barsnes