Lund University

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Phosphoproteomic-guided personalized cancer therapy

Principle Investigator Magnus Jakobsson


Aberrant protein phosphorylation is linked to most key cancer hallmarks and enables cells to obtain properties for migration, invasion, and metastasis. Mapping and matching phosphorylation-regulated signaling pathways affected by drugs with those dysregulated in tumors therefore has great potential in personalized cancer therapy.

The research team aspires to improve health on a population level trough the development of new diagnostic tools and therapeutic strategies. This is achieved through molecular characterization of disease states using mass spectrometry (MS)-based proteomics. MS is today the method of choice for large-scale analysis of proteins and their regulatory post translational modifications (PTMs). The group routinely uses state-of-the-art MS to quantitatively assess differences in protein abundance and PTMs, such as site-specific protein phosphorylation and methylation, across complex biological samples, such as plasma and solid tumors. To process large cohorts of clinical samples we use semi-automated sample preparation protocols based on the KingFisher Flex platform and an EvoSep nLC system coupled to a hybrid quadrupole mass spectrometer.

A key focus of the research group is ovarian cancer (OC) which affects roughly 1.5 % of the female population. Symptoms are often diffuse and, consequently, the disease is diagnosed at a late stage resulting in poor prognosis and low survival. Tools for improved diagnosis and precision therapy would therefore be of tremendous value.

The project will encompass initial optimization of lab workflows for the combined phospho-proteomic and proteomic characterization of complex human proteomes, in addition to setting up a system for (automated) analysis of corresponding data. The workflows may be applied i) to map signaling pathways modulated by cancer drugs and ii) to identify druggable kinase enzymes and dysregulated signaling pathways in ovarian cancer. These collective efforts may uncover biomarkers enabling the identification of drug-responding patient cohorts and represent a significant step towards personalized ovarian cancer therapy.

The project will be approached in close collaboration with the PTM proteomics-oriented precision oncology company Acrivon AB and will mainly be performed at the Dept. of Immunotechnology, both located at Medicon Village, Lund. The department offers a friendly working atmosphere and expertise in proteomics, bioinformatics and cancer biology. The specific focus of the position will be set in dialogue with the applicant in relation to his/her previous knowledge and experience.


Key requirements:

·       PhD within proteomics, cancer biology, biomarkers or other relevant field.

·       Experience with proteomics and analysis of PTM and/or (prote)-omic data.

·       Demonstrate enthusiasm, motivation, flexibility and confidence.

·       At least one key author publication in a reputable scientific journal.

·       Written and oral proficiency in English.


Advantageous skills:

  • Hands-on experience with liquid chromatography and tandem mass spectrometry (LC-MS/MS) using Thermo Scientific oribitrap instruments such as the QExactive HF-X series, or similar.
  • Knowledge and experience concerning preparation of biological samples (e.g. tissue, cells, plasma, serum) for MS-based proteomics.
  • Experience with quantative analysis of peptides/proteins from biological material using nanoLC and MS-techniques (DDA, DIA, SRM, MRM).
  • Ability to pursue and evaluate quantitative proteomic workflows as well as skills to analyze comprehensive data sets using e.g. MaxQuant, Spectronaut, Skyline and other type of software for bioinformatics analysis.
  • Experience in Python, R or other programming language.
  • Independent thinking and analytical aptitude for devising innovative scientific or technical solutions.
  • Capacity for effective independent work and as part of a team.


Partners: Acrivon AB, Medicon Village Lund.

Homepage: Magnus Jakobsson