Work packages

Drug Screening

The main aim of this work package is to establish a pipeline for cancer drug sensitivity screening of pancreatic cancer based on patient-derived xenografts and organoids.

We will develop:

  • 3D patient-derived organoids
  • assemble a custom library for drug screening of pancreatic cancer
  • screen samples
  • correlate drug sensitivity data with –omics and morphological tumour features (in collaboration with work packages 'Omics and biomarkers' and 'Pathology')
  • Pancreatic ductal adenocarcinoma organoids are ex-vivo models of pancreatic cancer that can be established from very small biopsies, enabling the study of localized, advanced, and metastatic disease.

    In order to obtain an overview of drug responses, we will use a set of established PDX models. These are based on patient cancer cells that have been expanded in animals, such that sufficient material is available to screen against our library of cancer drugs. We will use the generated data from this screen and our overview of clinically used drugs to assemble a small custom library for further screening.

    Given the limited amount of primary patient material, we will set up 3D organoids and establish a Cancer Drug Sensitivity Screening (CDSS) pipeline tailored to pancreatic cancer. Approximately 10 3D organoids will be developed from fresh tissue samples for this purpose. Subsequently, 20 to 30 samples will be used to obtain CDSS data, correlate with findings in work package 'Molecular characterization of tumour tissue and liquid biopsies', and validate against clinical response data to see whether this method can predict therapy responses.

    Ultimately, we want to be able to routinely assist in treatment decision making in the clinic by identifying drug combinations that have higher efficiency than currently available treatment options for each individual patient.

    Collaborators

    • Elin H. Kure (work package “Omics and biomarkers”), Oslo University Hospital

    • Knut Jørgen Labori (work package “Surgery”), Oslo University Hospital/University of Oslo

    • Caroline Verbeke (work package “Pathology”), University of Oslo/Oslo University Hospital

    • Stein Kaasa and Olav Dajani (work package “Oncology”), Oslo University Hospital/University of Oslo

    • Ivar Gladhaug (work package “Metabolomics”), University of Oslo

    • Tero Aittokallio (Computational medicine), Oslo University Hospital/University of Oslo