The development of radioresistance is a significant clinical issue for up to 20% of prostate cancer patients. The aim of our work is to thoroughly understand the proteomic and transcriptomic networks that respond to radiation therapy using a large cohort of prospective tissues. Our overall goal is to identify the drivers of resistance and boost the development of rational treatment regimens based on personalised molecular characteristics. To achieve this, biopsies were taken from men with clinically localised prostate tumours prior to and 14 days following high-dose-rate brachytherapy (a single dose of 10 Gy). These pre- and post-radiation tissues were subsequently analysed using 3’RNA sequencing and DIA mass spectrometry; routinely quantifying >11,000 mRNA transcripts and >5,000 proteins from the extremely limited tissue resource, respectively. Following comparative analysis and identification of significantly changed genes and proteins, we documented the overexpression of a core subset of more than two hundred mRNAs and/or proteins. An ontological investigation of these revealed the enrichment of known radiation-sensitive pathways such as p53-mediated DNA repair, complement activation and various immune responses consistent with tissue trauma. The most striking molecular feature was the consistent stimulation of various components of the extracellular matrix including collagens, laminins, thrombospondins and integrins – suggestive of an active wound healing and regenerative remodelling process within the tumour microenvironment. The identification of these pathways as core components of the radiation response opens the door to the development of clinically-actionable targets via modulation of the extracellular matrix. We are furthering this experimental approach by identifying key drivers and predictive biomarkers of resistance by analysing a compelling cohort of recurrent radioresistant tumours (with patient-matched treatment-naive tissue), as well as preclinical samples from excellent responders. Identifying these underlying genomic, transcriptional and proteomic networks could potentially inform more rational treatment decisions and/or adjuvant strategies that mitigate resistance altogether.