Acute and late toxicity in normal tissues exposed during the course of radiotherapy, such as radiation-induced pneumonitis and lung fibrosis, is a major limiting factor in successful control of the local tumour in lung cancer patients. Identifying patients at inherently greater risk of normal tissue toxicity or detecting the early signs of toxicity could allow for real-time treatment optimisation, reducing the incidence of severe tissue reactions and improving tumour control. In this translational study, blood was collected before, during and after radiotherapy from non-small cell lung cancer (NSCLC) patients who are undergoing Gallium-68 ventilation/perfusion PET/CT (Universal Trial Number U1111-1138-4421). In one biomarker approach, blood plasma was studied throughout radiotherapy to identify cytokine responses that may correlate with treatment response and/or normal tissue toxicity. Here, we are reporting a second biomarker approach: the radiation-induced DNA damage response of normal cells as assessed by the γ-H2AX assay in lymphocytes (1, 2). Two complimentary experimental designs were used. In the first, the γ-H2AX assay was used to monitor the induction and repair of DNA double-strand breaks (DSB) in response to an ex vivo irradiation, to identify individuals with abnormal DNA repair kinetics before treatment commences. In the second, the same assay was used to measure the baseline level of DNA DSB before, during and after treatment. The biomarker candidates will ultimately be compared to the clinical response parameters to determine whether any have significant prognostic value. The ability to monitor normal tissue toxicity in real-time during treatment could improve individual patient outcomes, as well as provide a mechanism to compare novel treatment modalities alongside standard radiotherapy practice. Systemic plasma cytokine responses and changes in normal lymphocytes both represent readily-available and minimally-invasive methods to evaluate normal tissue responses during radiotherapy, and the search is now on to identify sensitive and reliable biomarkers.