Lund University

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Proteomics data mining for improved cancer precision medicine

Principle Investigator Fredrik Levander


The aim of the project is to reveal protein biomarkers that can be used for improving clinical decisions in cancer treatment. To accomplish this, new methods for data processing and analysis will be developed and applied to liquid chromatography- mass spectrometry proteomics data.

With many upcoming treatment options for cancers, it is essential with molecular characterization to select the most appropriate treatment regime for each patient. In the project we will explore the possibilities of adding proteomic biomarkers to the decision process, alone or added to clinical and gene expression data, by exploiting liquid chromatography - tandem mass spectrometry (LC-MS/MS) data from patient samples. New data processing and analysis strategies will be developed to quantify key molecules, and to detect new potential markers that can be used clinically. The analysis strategy will be based on development of new data processing and analysis workflows for LC-MS/MS data, and exploit both publicly available and in-house generated data that are now available for hundreds of patients. The main focus will be on breast cancer, but also other cancer types can be explored within the postdoctoral project, and clinical key questions to address will be selected in collaboration with the project collaborators.


Key requirements:

  • PhD in bioinformatics, computational biology or equivalent     
  • excellent knowledge in scripting and programming languages, preferably R and Python/Java
  • experience with omics data processing and analysis.


Advantageous skills/knowledge:

  • experience in working with proteomics data
  • experience in cancer research
  • experience with bioinformatic tool development.


Partners: Region Skåne, SCAN-B initiative, Immunovia AB

Homepage: Fredrik Levander