Linking genes to symptoms
A recent study published in Genome Biology describes a novel platform for accelerating informed treatments for cancers based on genomic information.
The utility of massive genome sequencing programmes has come into sharp focus in recent years, as the cost of genetic sequencing has dropped and the computing power to analyse such huge data sets has increased. And the utility of this data in healthcare is beginning to catch up, as the data is linked with clinical information.
The paper describes the MyPersonalMutanome (MPM) platform, developed by the team at the Cleveland Clinic, in Ohio, USA. MPM is seeking to bridge the gap between the large volume of genomic data that we can now generate, and the decision making that’s needed in the clinic. The tool will allow the identification of the mutations and genes that are implicate in range of cancers, together with information about drug targets and other biomarkers associated with tumours. The team have built data on half a million mutations into MPM, covering the thousands of relevant DNA sections from over 30 types of cancer to build their comprehensive database. Mapping this – and other data on protein interactions – against clinical data on patient treatment outcomes and patient responses to medicines – has allowed the team to model how certain genetic information is linked with specific mutations within the cancers and how they respond to treatment.
One of the next phases of the project will see the team apply artificial intelligence to mine the data to identify novel drug treatment targets and may facilitate discovery of new precision medicines for a range of cancers and other diseases.