gms | German Medical Science

In times where the genetic screening of patient material is not only technically, but also financially feasible the demand to treat people specifically based on their genetic characteristics is increasing. This demand is met using precision medicine in molecular tumor boards (MTB). To prepare these conferences a molecular oncologists reviews the sequencing data and gathers information about variants from different external and internal databases. The resulting therapy suggestions are discussed in the MTB in a group of experts from different fields of oncology and bioinformatics and given to the treating physician.

This preparation of the MTB represents the bottleneck of the process, as the gathering of information about actionable variants is a time consuming task [1]. The MASTER-program at the National Center for Tumor Diseases in Heidelberg, Germany is one of the biggest molecular studies in Europe and conduct MTB since 2013. In close collaboration with the physicians of this study, we developed a tool, which supports the whole workflow of a MTB. Briefly, external databases are queried automatically with sequencing data, which was previously pre-filtered by bioinformaticians [2]. Relevant information on effects of the mutation on the protein, drugs targeting the specific variant or the gene, and pathways the gene is involved in are gathered. This information is harmonized across the various external databases to make it comparable and is displayed together with the sequencing data in one view. As information can also be added manually by the physician, the system can learn from these entries, and an internal database is created and extended, which can be queried for future cases. After choosing actionable variants, which support a therapy suggestion, the tool offers an interface to document these suggestions in detail. Based on the variants the physician can support specific suggestions with scientific sources and add text, which will be used for the MTB report. Via a specifically designed MTB view, the preparing oncologist can present the therapy suggestions and what these suggestions are based on. As soon as the MTB members agree on the recommendations to be sent to the treating physician, the system automatically generates a MTB report containing the therapy suggestions, the supporting scientific sources and added text. Finally, free text fields enable the physician to extend the report with additional information and comments the treating physician should take into account for therapy decision.

By summarizing important information from various databases as well as previously provided therapy suggestions and integrating the different steps of a MTB workflow in a single tool, we not only want to facilitate and accelerate the process of the MASTER MTB, but also want to ensure consistency of therapy suggestions between physicians. With this first project, we also want to proof the concept of a MTB support tool and to open possibilities to adapt the system to other institutions and programs. With this, we hope to increase the amount of patients who can benefit from precision medicine.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.