Bioinformatics for precision oncology

Abstract

Molecular profiling of tumor biopsies plays an increasingly important role not only in cancer research, but also in the clinical management of cancer patients. Multi-omics approaches hold the promise of improving diagnostics, prognostics and personalized treatment. To deliver on this promise of precision oncology, appropriate bioinformatics methods for managing, integrating and analyzing large and complex data are necessary. Here, we discuss the specific requirements of bioinformatics methods and software that arise in the setting of clinical oncology, owing to a stricter regulatory environment and the need for rapid, highly reproducible and robust procedures. We describe the workflow of a molecular tumor board and the specific bioinformatics support that it requires, from the primary analysis of raw molecular profiling data to the automatic generation of a clinical report and its delivery to decision-making clinical oncologists. Such workflows have to various degrees been implemented in many clinical trials, as well as in molecular tumor boards at specialized cancer centers and university hospitals worldwide. We review these and more recent efforts to include other high-dimensional multi-omics patient profiles into the tumor board, as well as the state of clinical decision support software to translate molecular findings into treatment recommendations.

Keywords: cancer; clinical decision support; data analysis pipeline; molecular tumor board; mutation calling.

Figure 1

Schematic overview of the workflow of a MTB. Tumor biopsies are obtained from consenting patients, and DNA is extracted and sequenced. Variants are called and then annotated and prioritized for potential functional or clinical relevance before being reported to a tumor board, where an interdisciplinary team decides about treatment options.

Figure 2

Schematic overview of analysis steps for DNA variant calling (blue, top) and RNA expression analysis (red, bottom).

Figure 3

Example of concise report summary from an MTBZ report, including mutational burden, HLA-I type of the patient, mutational state of cancer-type-specific set of important genes, grouped according to level of approval.