divendres 20 de desembre de 2019

New classification system for tumours can guide diagnosis and treatment options for cancer

News from CRG

Based on the largest study of cancer patients of its kind, scientists have created a new way of classifying tumours. Clinicians can use genome sequencing to assign their patients’ tumours to one of sixteen groups in the new classification system, ten of which provide important information for the diagnosis and treatment of the disease, like whether an individual will respond to immunotherapy.

Researchers at the Centre Nacional d’Anàlisi Genòmica, part of the Centre for Genomic Regulation in Barcelona (CRG), analysed the mutations found in 2,583 patients with 37 different types of cancer. They detected a total of 45 million mutations across all tumours, of which at least 1.2 million were non-unique mutations, meaning they were found in the same location for two or more cancer patients. With six billion potential sites in human DNA that can be mutated, the number of non-unique mutations is far higher than what’s expected by chance alone. On average, 4% of the mutations in a tumour could also be found in one or more of the other tumours across the entire set of patients.

Based on the number and type of non-unique mutations, researchers were able to classify the 2,583 primary tumours into one of sixteen groups, each of which have independent characteristics. Ten of these groups are clinically relevant, with the potential to help doctors make a more accurate diagnosis and select a more effective treatment course. For example, the number and type of non-unique mutations that define one group are linked to tumours unable to correct specific type of damage to their genetic code, resulting in their DNA becoming unstable. These patients are likely to respond well to immunotherapy, which would in turn allow abstaining from conventional chemotherapy and its side effects.

 

Reference:
Stobbe MD, Thun GA, Diéguez-Docampo A, Oliva M, Whalley JP, Raineri E, et al. (2019) Recurrent somatic mutations reveal new insights into consequences of mutagenic processes in cancer. PLoS Comput Biol 15(11): e1007496. https://doi.org/10.1371/journal.pcbi.1007496

More information:
CRG website

 

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