Introduction, objectives and overview of the research programme

Cancer is a major cause of death and suffering, rendering it a huge concern to the general public. It constitutes a group of diseases characterized by abnormal cell growth, stage-wise progression, heterogeneity, and potential to develop resistance to therapies. All these aspects are consequences of the evolutionary nature of cancer, which underlines the importance of studying cancer as an evolutionary process. Fortunately, single cell genomic sequencing has recently begun to provide opportunity to unprecedented detailed insights into tumour evolution, new techniques are presently emerging for assaying the spatial distribution of tumour heterogeneity, and future yet unforeseen experimental breakthroughs are inevitable. Pharmaceutical, biotech, and software industry constitutes the corners of an intersectorial application triangle that is key to the implementation and translational success of evolutionary cancer studies. We will train future computational cancer biologists, providing them with deep academic modeling and computational training and, in collaboration with partners, enable them to understand the clinical reality and goals as well as the working mode and potential of biotech, but also equip them with the skills required for professional software development in these commercial areas.

Due to its burden on society, cancer has been one of the main targets for application of the molecular techniques developed during the last 20-25 years. In particular genomics and transcriptomics techniques have yielded molecular markers, based on single genes or signatures consisting of multiple genes; subtyping of individual cancer forms, e.g., breast cancer; and new therapeutics. Although genomic heterogeneity was first studied and described using bulk sequencing data, single  cell sequencing has only recently rendered it possible to study genomic heterogeneity by assaying individual tumour cells, e.g., when searching for subpopulations with potential to confer therapeutic resistance. Single cell sequencing is a key breakthrough, because the cell is the canonical unit in biology, in particular in cancer where a cell population is the evolving unit. Emerging spatial techniques will allow us to also map out the spatial distribution of a tumour’s and its stroma’s heterogeneous cells, e.g., revealing ecological properties in the cell population of consequence to the tumour’s phenotype. Insights into the complexities of tumor heterogeneity and evolution will be crucial for the design of better cancer therapies.

CONTRA will provide interdisciplinary and intersectorial training enabling the next generation of computational cancer biologists to lead developments across the application triangle of pharmaceutical, biotech and software industry. First, they will be able to design the basic analysis tools that biotech industry today must couple their experimental devices with, as well as advanced down-stream computational algorithms required for novel insights into tumor development & evolution, drug response & emergence of resistance. Second, they will be able to translate the technological and scientific accomplishments into tools to support clinical decision-making. Third, they will be educated to develop stable commercial software, so that they can be employed across the three corners of our application triangle. Our program will thus train PhDs with the competence necessary for unleashing the commercial potential in the battle against cancer as well as for its translational success.

CONTRA’s specific research and innovation objectives

1. To develop novel, powerful single cell models and tools for somatic evolution in cancer,
   including spatial aspects, building on methods for classic evolution as well as
   probabilistic machine learning in general.
2. Among the partners and in collaboration with other groups apply new tools in cutting
   edge cancer studies – with a special focus on clinical and pharmaceutical relevance.
3. Construct a novel translational training triangle between academia, software industry,
   and pharmaceutical and biotech industry.
4. Develop novel methods & tools with potential for improving clinical cancer care.