5th September 2018
Understanding how cancers develop and change over time is a big challenge. For obvious reasons, scientists can’t simply sit and watch a cancer growing in a person. Members of the Evolution and Cancer Laboratory at the BCI, including lead author Dr William Cross, were part of a collaborative team that set out to identify when particular genetic changes arise during bowel cancer development.
Read more30th August 2018
A team of researchers from BCI’s Centre for Molecular Oncology, led by Prof Claude Chelala, have made new developments to SNPnexus- a computational tool that allows for the assessment of the functional effect of sequence variants within the genome.
Read more11th July 2018
A team of researchers from the BCI, led by Prof Trevor Graham, Lead of the Evolution and Cancer Biology Laboratory, have reported the genetic events involved in the early development of bowel cancer in patients with inflammatory bowel disease (IBD). Such knowledge may be able to be exploited to design simple diagnostic tests to stratify patients with IBD at high risk of developing cancer.
Read more13th June 2018
Dr Sarah McClelland from Barts Cancer Institute, Queen Mary University of London, has recently published new research in the journal Cell Reports revealing new insights into why cell division can sometimes go wrong.
Read more8th June 2018
Current detection strategies are found to have identified only 2.6% of the BRCA gene mutation carriers in the Greater London population, according to a recent study published in the Journal of Medical genetics. The findings of the study, performed by researchers from the BCI’s Centre for Experimental Cancer Medicine, led by Dr Ranjit Manchanda, suggest that enhanced and new approaches are required to maximise the opportunity for breast and ovarian cancer prevention.
Read more28th May 2018
New research, published today in Nature Genetics, has developed a computer model that forecasts the changes that occur within tumours as they develop. In the future, it is hoped that such a model may enable the prediction of the trajectory of tumour growth in patients, allowing clinicians to pre-empt disease course and tailor treatment regimens accordingly.
Read more