A suite of computational frameworks to support precision cancer medicine
Cancer precision medicine is an approach to cancer treatment that tailors medical care to the individual characteristics of each patient and their tumor. A cornerstone of this approach is the use of high-throughput genomic profiling technologies for a deep characterization of the molecular features of tumor samples. The diversity and complexity of molecular read-outs, combined with a rapidly evolving landscape of clinically actionable targets, poses significant requirements for advanced data interpretation tools. In this talk, I will present molecular data interpretation frameworks that we are actively developing to address the N-of-1 analytical challenge in precision oncology, that is to highlight treatment opportunities for each complex cancer case in light of existing knowledge and large-scale reference datasets. Herein, I will describe challenges and solutions with respect to molecular data integration and harmonization, the adoption of standards for evaluating the clinical significance of genomic aberrations, as well as the identification of relevant biomarker-guided clinical trials.
More about the researcher
Sigve Nakken works as a scientist at the Institute for Cancer Research at Oslo University Hospital, Norway, with affiliation to the Centre for Cancer Cell Reprogramming (CanCell), a Centre of Excellence at the University of Oslo. In addition, he holds an Adjunct Professor position at the Department of Informatics, University of Oslo. Nakken’s main interests are tool development for clinical interpretation of cancer genomes, mechanisms and impact of DNA variation in cancer (soma and germline), and knowledge integration for precision cancer medicine. He has a background from computer science (MSc) and computational biology (PhD), and extensive experience with analysis of data from high-throughput sequencing technologies. He is the lead developer of multiple bioinformatics tools used in high-throughput cancer biology.