Johan Staaf

Researcher, Associate Professor, Associate Professor, PhD, MSc, MSc

Research areas and keywords

UKÄ subject classification

  • Cancer and Oncology
  • Bioinformatics (Computational Biology)


  • Lung cancer, biomarkers, genomic characterization, NGS, Bioinformatics, prognostic factors, predictive factors


Lung cancer, the leading cause of cancer death, is divided into several histological subtypes with large differences in molecular alterations, clinical presentation, and patient outcome. By a combined clinical and molecular approach the current project focuses on improving the molecular understanding of lung cancer and translate research findings into a clinical diagnostic setting.

By characterization of the genomic, transcriptional, and DNA methylation landscape in lung cancer subgroups defined by histology and other clinicopathological factors in both own and public cohorts we search for new molecular subgroups of potential clinical relevance, additional targets for synergistic treatment, and a deepened understanding of the molecular pathogenesis.

To identify operable lung cancer patients with risk for metastatic relapse we search for new prognostic biomarkers based on analysis of genome-wide gene expression data and conventional protein marker validation based on analysis of primary tumor tissue. By analysis of patient specific alterations in circulating tumor DNA in blood samples we aim to establish blood-based assays for early detection of lung cancer, treatment monitoring, and early detection of relapse in the primary and advanced setting.

Highlighted research outputs

Karlsson, A. K., Hans Brunnström, Ericson Lindquist, K., Karin Jirström, Mats Jönsson, Rosengren, F., Reuterswärd, C., Helena Cirenajwis, Åke Borg, Jönsson, P., Maria Planck, Göran B Jönsson & Johan Staaf, 2015, In : Oncotarget. 6, 26, p. 22028-22037

Research output: Contribution to journalArticle

Karlsson, A. K., Markus Ringnér, Martin Lauss, Botling, J., Micke, P., Maria Planck & Johan Staaf, 2014, In : Clinical Cancer Research. 20, 18, p. 4912-4924

Research output: Contribution to journalArticle

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