Submitted by Catherine Atkins on Thu, 18/12/2025 - 10:16
Congratulations to a collaborative team of researchers representing the Early Cancer Institute at the University of Cambridge, the Wellcome Sanger Institute and University College London who have been successful in applying for a highly competitive Programme Award from the Medical Research Council (MRC).
The award, entitled AI-SEED-RCC - using generative AI to Spatially map Evolution, Environment, and Drug responses to Renal Cell Carcinoma, will fund research to uncover why kidney cancers can behave so differently between patients. Some patients have slow-growing tumours that are restricted to the kidney and respond well to treatment, whilst others experience aggressive disease that spreads to other organs and is unresponsive to treatment.
The research proposal is based on the idea that cancer is not just a problem of the faulty cells that become tumours ("the seed"), but also of the environment around those faulty cells ("the soil"), such as immune cells and blood vessels. It uses large collections of tumour samples, advanced imaging techniques, and powerful AI tools to study both the cancer cells themselves and the environment in which they grow. By analysing how the seed and soil interact, either constraining or promoting the growth of tumour cells, the project aims to predict cancer growth and identify personalised treatments.
Dr Tom Mitchell from the Early Cancer Institute at Cambridge commented: “I am thrilled that the MRC has awarded our team this funding. Kidney cancer is the sixth most common cancer type in the UK and being able to create personalised treatments, based on the knowledge of how the cancer is behaving in a certain individual, will make a great difference to patient outcomes.”
Dr Mo Lotfollahi, Group Leader at the Wellcome Sanger Institute, added: “This large-scale MRC Programme grant will enable us to explore the growth of kidney cancer in a way that hasn’t been possible before. Artificial intelligence has the power to transform cancer research, and we are excited to start to harness this to combine generative AI with the latest genomics technologies to help predict cancer growth and identify personalised treatments for kidney cancer.”
Reference: AI-SEED-RCC - using generative AI to Spatially map Evolution, Environment, and Drug responses to Renal Cell Carcinoma, APP73647