Individualising Radiotherapy Through Mechanistic Models
Lead Research Organisation:
Queen's University of Belfast
Department Name: Sch of Medicine, Dentistry & Biomed Sci
Abstract
Radiotherapy treats cancer through the precise delivery of high doses of radiation to tumours, killing cancerous cells by damaging their DNA. Radiotherapy is highly effective because radiation can be accurately targeted to tumours while avoiding normal tissue, preventing the unwanted side effects which would result from killing healthy cells. The introduction of new advanced treatment techniques and better imaging to improve tumour targeting has significantly improved patient outcomes following radiotherapy. However, while radiotherapy benefits from a high degree of physical personalisation, more can be done to improve treatment outcomes.
Cancer is a highly complex disease, associated with a large number of different types of genetic mutation. These mutations can significantly affect the radiation sensitivity of a given patient's cancer. Despite this, all patients with cancer in a particular organ are typically treated with the same dose and treatment schedule. While these doses have been tailored to cancer at a population level, this almost certainly under- and over-treats some patients. If individual radiosensitivity can be precisely defined before treatment, significant improvements in outcome could be achieved, in terms of improved tumour control or reduced side effects, depending on the patient's particular genetics.
This fellowship seeks to address this challenge by developing models of how cells respond to radiation, which can accurately predict the sensitivity of an individual's disease based on the mutations present in their particular cancer. In work to date, we have developed models and characterised responses related to DNA repair, and shown that we can effectively predict and quantify quantify how DNA repair failure impacts on radiosensitivity.
However, this work has also shown that although loss of DNA repair is important, it only explains a small fraction of the variability between the responses of different cancers and different patients. As a result, this approach needs to be expanded to better understand the range of responses seen in the clinic.
In this renewal phase, we will work to better characterise these differences, measuring the impact that changes in other biological processes - such as those related to cell growth and cell death - have on radiation sensitivity, and integrate this into a combined model. We will demonstrate the efficacy of this model using new data generated locally, and then develop a method by which these predictions can be applied in clinical treatment plans, to enable its predictions to be tested in real patient data.
If successful, this research programme will deliver a unique tool to enable the tailoring of radiotherapy using both physical and biological factors, offering more personalised therapy and better treatment outcomes for patients suffering from cancer in the future.
Cancer is a highly complex disease, associated with a large number of different types of genetic mutation. These mutations can significantly affect the radiation sensitivity of a given patient's cancer. Despite this, all patients with cancer in a particular organ are typically treated with the same dose and treatment schedule. While these doses have been tailored to cancer at a population level, this almost certainly under- and over-treats some patients. If individual radiosensitivity can be precisely defined before treatment, significant improvements in outcome could be achieved, in terms of improved tumour control or reduced side effects, depending on the patient's particular genetics.
This fellowship seeks to address this challenge by developing models of how cells respond to radiation, which can accurately predict the sensitivity of an individual's disease based on the mutations present in their particular cancer. In work to date, we have developed models and characterised responses related to DNA repair, and shown that we can effectively predict and quantify quantify how DNA repair failure impacts on radiosensitivity.
However, this work has also shown that although loss of DNA repair is important, it only explains a small fraction of the variability between the responses of different cancers and different patients. As a result, this approach needs to be expanded to better understand the range of responses seen in the clinic.
In this renewal phase, we will work to better characterise these differences, measuring the impact that changes in other biological processes - such as those related to cell growth and cell death - have on radiation sensitivity, and integrate this into a combined model. We will demonstrate the efficacy of this model using new data generated locally, and then develop a method by which these predictions can be applied in clinical treatment plans, to enable its predictions to be tested in real patient data.
If successful, this research programme will deliver a unique tool to enable the tailoring of radiotherapy using both physical and biological factors, offering more personalised therapy and better treatment outcomes for patients suffering from cancer in the future.
