A new CLL patient classifier would allow patients of the future to be offered the best treatment first time according to their CLL subgroup, saving unnecessary treatments with potentially toxic side effects
Jackie Martin
This study paves the way for routine clinical application of whole genome analyses for risk stratification in other cancer types. The team’s analysis also identified 148 new putative genetic drivers of CLL. Future research on these drivers may uncover new mechanisms in CLL initiation and progression, with potential for the development of novel therapeutics.
Professor Sir Mark Caulfield, Vice Principal for Health for Queen Mary University of London and former Chief Scientist and lead of the 100,000 Genomes Project at Genomics England, said: ‘This is the largest international genomic analysis of this blood cancer, which excitingly demonstrates the real value of whole genome sequencing from the 100,000 Genomes Project. It also harnesses the high-quality blood cancer samples from the Liverpool Chronic Lymphocytic Leukaemia Biobank and associated clinical data collected by the Clinical Trial Units at Liverpool and Leeds universities as part of multi-centre National Cancer Research Institute-supported clinical trials. Our work shows that the entire genome is superior in classifying patients into groups compared to the conventional targeted approaches and that we can predict response to treatment more precisely and in more patients.’
Professor Andrew Pettitt, founding Director of the UK CLL Biobank and Chief Investigator for two of the contributing clinical trials, said: ‘This ground-breaking study is a paradigm for what can be achieved through a nationally coordinated approach to collaborative working that allows the application of cutting-edge science to a large number of high-quality samples obtained from uniform, well-defined patient cohorts and linked to high-quality clinical outcome data.’
Jackie Martin, patient representative for the Genomics England haematology project, commented: ‘A new CLL patient classifier would allow patients of the future to be offered the best treatment first time according to their CLL subgroup, saving unnecessary treatments with potentially toxic side effects. It will also aid in selecting the most appropriate patients for trials of new, targeted therapies. This work has a potentially huge, positive impact on patients with CLL and importantly demonstrates the feasibility of this approach in other cancer types.’
Source: University of Oxford
Source: Healthcare in Europe
