To the Editor—The optimal management of patients with cancer is increasingly dependent on individualized treatments guided by tumor sequencing data. As comprehensive genomic tests become routine in many disease settings and academic centers promote ‘-omics-guided’recruitment into clinical trials, accurate and scalable data interpretation represents a major challenge. The meticulous task of matching tumor alterations with approved or experimental therapies relies heavily on the expertise of each center. Unsurprisingly, we see similar sequencing results leading to different clinical recommendations1. While the number of drug biomarkers with target specificities is constantly growing, these disparities are likely to escalate, which may ultimately impair patients’ outcomes and research progress. Access to commercial test results does not simplify decision-making, as such tests often deliver generic reports that lack the necessary information for prioritizing emerging therapies. In addition, data interpretation must also contend with incidental germline findings, which further complicates the process. Medical teams face the extra burden of manually searching for the latest scientific evidence associated with detected gene alterations, which is a complex, time-consuming and error-prone task. Here we argue for the need to streamline expert-driven genomic-data interpretation and reporting workflows and to employ user-friendly decision support tools that foster interactive treatment planning.

In response, we have developed the Molecular Tumor Board Portal (MTBP), a clinical decision support system that unifies the analysis of sequencing results across seven European comprehensive cancer centers under the umbrella of the Cancer Core Europe (CCE) network2. The portal is used to select candidates for the Basket of Baskets trial (NCT03767075), a modular multi-arm study for genomically defined populations, as well as other clinical studies with active recruitment across CCE sites. Following a process agreed among CCE experts, the system automates ‘-omics’ data capture, interpretation and reporting, and creates a framework with which to share and harness results (Fig. 1). MTBP reports are discussed at weekly virtual meetings during which multidisciplinary