Clinical sequencing in leukemia with the assistance of artificial intelligence

Next generation sequencing (NGS) of cancer genomes is now becoming a prerequisite for accurate diagnosis and proper treatment in clinical oncology. Because the genomic regions for NGS expand from a certain set of genes to the whole exome or whole genome, the resulting sequence data becomes incredibly enormous and makes it quite laborious to translate the genomic data into medicine, so-called annotation and curation. We organized a clinical sequencing team and established a bidirectional (bed-to-bench and bench-to-bed) system to integrate clinical and genomic data for hematological malignancies. We also started a collaborative research project with IBM Japan to adopt the artificial intelligence Watson for Genomics (WfG) to the pipeline of medical informatics. Genomic DNA was prepared from malignant as well as normal tissues in each patient and subjected to NGS. Sequence data was analyzed using an in-house semi-automated pipeline in combination with WfG, which was used to identify candidate driver mutations and relevant pathways from which applicable drug information was deduced. Currently, we have analyzed more than 150 patients with hematological disorders, including AML and ALL, and obtained many informative findings. In this presentation, I will introduce some of the achievements we have made so far.