The Systems Oncology Group
The Systems Oncology group
The Systems Oncology group
The research group System Oncology apply a system biology approach to understand basal cellular mechanisms, improve diagnostic and optimize the outcome of cancer treatment. Systems biology is defined as the bridging of cellular systems and computational modeling in order to interpret complex biological systems and large-scale molecular datasets generated through high-throughput techniques.
Rational development of anti-cancer drug combinations
Colorectal cancer (CRC) is one of the leading cancers worldwide. A number of therapies, both targeted and standard chemotherapies have been approved, but response to these treatments vary considerably due to huge heterogeneity among the patients. Research in systems biology has revealed the highly complex networking structure of signaling pathways that account for variations in treatment response as well as acquired resistance.
Complications in designing effective therapies due to inter-tumour heterogeneity make CRC a clear choice for personalized medicine. Standard treatment is inadequate for many patients because their specific tumour types will have individual variation in drug efficacy and drug resistance, forcing high drug dosage, which can lead to severe adverse effects. Combinatorial drug treatment tailored to the individual tumour is expected to overcome many of these problems, but our knowledge on designing beneficial drug combinations is still limited. In order to accomplish personalised oncology, clinicians need advanced decision support systems that can underpin the choice of (combination) treatment by assisting in the interpretation of patient data, increasingly provided by “omics” technologies that produce ‘big data’.
Our aim is to lay the foundations of a pipeline for combined drug screening. As a means to guide drug screening, we use computational model (Boolean network), representative of the signaling network in cancer cells. By helping us to understand the synergy mechanisms of drug combinations, as well as enabling prediction making of cellular response to combined targeted therapy, these models will hopefully guide and accelerate experimental conductions as we progress towards personalized therapies. Se the EU project NTNU DrugLogics Initiative. The further aim is to use this pipeline for clinical decision-making in precision medicine and targeted therapy of CRC patients.
To date, colonoscopy and histological analysis remain the standard diagnostic methods of choice for CRC patients. These are time consuming techniques and there is a critical need for the development and introduction of more sensitive and noninvasive detection methods in the diagnostic of CRC.
Extracellular vesicles encompass a number of small protein-containing molecules including exosomes (30-120nm), secreted from the all cells and which are key mediators of intracellular interactions and transmission of intercellular biological signals. In the last decade, the study of exosomes has attracted great interest as exosomes mirror the protein content of the parental cells from which they are derived including cancer cells. These characteristics make exosomes ideal in the study of key biomarkers allowing for early CRC detection but also predicting appropriate personalized treatment responses for patients.