From Omics Data to Therapies: Personalizing Treatments

The massive decrease in cost due to technological advances has made large-scale high-throughput data (genomics, transcriptomics, proteomics, metabolomics, etc.) available for large patient cohorts and has enabled comprehensive analyses of these big biological data sets. In particular for cancer, these analyses enable new insights into pathogenesis, patient stratification, and – ultimately – new therapeutic options. A particular challenge lies in leveraging these insights for the treatment of each individual patient. We present approaches for stratifying cancer therapies based on integrative analysis of omics data and describe how the analysis and interpretation of this data can be brought into a clinical setting. Molecular tumor boards (MTBs) provide an organizational framework to discuss integrated data and formulate therapeutic options. We present data analysis algorithms providing annotation and analysis of genomics and multi-omics data and discuss how these data can be brought to the clinician in a seamless manner – as well as the hurdles and pitfalls on that way