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Mathematics Provides More Effective Cancer Treatment

Mathematicians at Roskilde University, in collaboration with hematologists at Zealand University Hospital, have developed mathematical models for how normal blood production, development of blood cancer and inflammation mutually affect each other. In synergy with blood samples from the individual patient, the models can provide a guide for more effective, individualised cancer treatment.
Morten Andersen
Morten Andersen is an Associate Professor of Mathematics and Mathematical Modelling in the Department of Science and Environment. He completed his Master’s in Mathematics and Physics at Roskilde University and then wrote his PhD at DTU before returning to Roskilde University.

Roskilde University’s mathematical mapping of blood cancers stems from an invitation from  Zealand University Hospital. In 2015, Hans Hasselbalch, clinical professor at Department of Hematology, contacted Roskilde University to help him better understand how blood production and cancer affect each other. From day one, the objective was to develop methods which, with greater statistical certainty, can compare existing treatment protocols and target them to the individual patient.  

At the university, Morten Andersen is a mathematician who works on the borderline between mathematics and biology. In recent years, most of his time as a researcher at Roskilde University has been spent translating biological knowledge of diseases into mathematical modelling, which can lead to an understanding of the disease and act as a guide to the most effective treatment response.

Better overall picture of cancer

He is part of the Roskilde University’s Mathematical Bioscience academic environment: one of the few groups in Europe to specialise in mathematical cancer research. He particularly investigates the link between blood cancer and chronic inflammation that occurs as part of the body’s immune system when the cancer strikes. It has created a new framework for understanding how blood production, cancer and inflammation affect each other. On the basis of clinical data – usually blood tests – the model can describe in more detail what doctors need to measure to make accurate diagnoses, how the cancer develops and whether the cancer treatment is effective.   

»We have achieved many reliable results from the biological research, which constitute the pieces in the jigsaw puzzle, which we are attempting to put together in our attempt to understand cancer. But if we cannot translate biology into equations and models we can count on, it is almost impossible to see what the individual results mean vis-à-vis the overall picture of the disease. By applying mathematics to biology, we can focus on the main causes and investigate mathematically what are the possible outcomes of an intervention. We can pass that knowledge directly to the doctors who treat patients,« says Morten Andersen who, together with his colleagues, has now set up mathematical models in close collaboration with doctors and molecular biologists from the University Hospital of Zealand.   

»Based on measurements in the first months after a new treatment has been initiated, the models help to reveal  what happens as time progresses. The models can thus capture both cancer development and the effects of treatment.  Because, on the basis of the models, we can document that if a few parameters are applied, the number of cancer cells will decrease rather than increase. So, to put it bluntly, when compared with individual clinical data, our model can determine when and how patients’ disease drops below a critical level,« says Morten Andersen.

The collaboration has not only provided access to analysing existing blood test data from patients. Doctors and researchers across the natural sciences at Roskilde University have also been able to optimise exactly what needs to be measured in the blood tests in order to be able to set up accurate models that can guide doctors towards better diagnoses and courses of treatment.

Matematisk model på tavle

About the form of cancer known as Myeloprofilerative Neoplasmis

Many people instinctively equate blood cancer and leukaemia, but in reality, there are many different types of blood cancer. In recent years, Morten Andersen and his research group have been doing mathematical modelling of cancers known as myeloprofilative neoplasms. What these cancers have in common is that the stem cells in the bone marrow that turn into blood cells grow uncontrolledly. The disease is classified as a so-called ‘chronic myeloprofilative disease’ At the end of 2016, 4,125 people in Denmark had been diagnosed with it. Source: The Danish Cancer Society