23rd September 2022
New research, co-led by Dr Benjamin Werner from Barts Cancer Institute at Queen Mary University of London, indicates that the circular DNA structures present in around a third of cancers lead to extensive genetic diversity within tumours, giving them the ability to adapt rapidly to environmental stress and resist targeted cancer treatment.
Read more27th May 2022
Dr Sarah McClelland from BCI is part of a collaborative project that has secured £1.2 million in funding from the Medical Research Council to investigate the mechanisms leading to cancer development in cells infected with human papillomavirus.
Read more15th June 2021
Researchers from Barts Cancer Institute at Queen Mary University of London, led by Professor Fran Balkwill and Dr Oliver Pearce, have built two 3D multi-cellular models of the human tumour microenvironment (TME) in ovarian cancer. The models, which are the first created from the CanBuild project, have revealed novel insights into the role of the TME in cancer progression.
Read more10th April 2021
Research from Barts Cancer Institute, Queen Mary University of London, has revealed novel insights into the effects of chemotherapy on the tumour microenvironment (TME). The study found that chemotherapy enhances the anti-tumour actions of immune cells within the TME and their ability to support immune responses against cancer.
Read more30th September 2020
On 11th September 2020, Professors Hemant Kocher and Nick Lemoine hosted the eighth London Pancreas Workshop (LPW) – a forum for state-of-the-art clinical and basic research in pancreatic cancer. In a first for the biennial event, this year’s LPW took place online with pre-recorded speaker presentations and live, interactive Q&A sessions.
Read more27th January 2020
Research led by the Barts Cancer Institute, Queen Mary University of London, has revealed that mouse models of the most common and deadly form of ovarian cancer, high-grade serous ovarian cancer, can effectively replicate the disease in humans. These models provide useful pre-clinical tools that may help to determine which patients are likely to respond to particular treatments.
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