High throughput phylogeography of tumors: how the tissue environment influences cancer evolution?

Projektbeschreibung

Tumoren mit Einzelzellauflösung kartieren

Tumormikroumgebungen sind komplexe Ökosysteme, in denen Tumor-, Immun- und Stromazellen zusammenwirken. Fortschreitender Krebs beinhaltet die Diversifizierung und Expansion von Tumor-Subklonen, die von der Tumormikroumgebung beeinflusst werden. Fortschritte in der Einzelzellgenomik tragen zur Erforschung dieser Wechselwirkungen bei, aber es bleiben Schlüsselfragen über die Umgebung erfolgreicher Subklone offen. Das Team des ERC-finanzierten Projekts Tx-phylogeography wird die transkriptionelle Phylogeographie zur Untersuchung der Tumorentwicklung in Einzelzellauflösung entwickeln. Mithilfe von CRISPR/Cas9-Mutationen und Einzelzell-RNA-Sequenzierung wird ein Datensatz erstellt, aus dem die wichtigsten subklonalen Merkmale und ihre Beziehungen zur Tumormikroumgebung hervorgehen. Die Projektarbeit wird sich außerdem mit den analytischen Herausforderungen auf diesem Gebiet befassen und darauf abzielen, die Tumormikroumgebung mit der Tumorevolution zu verknüpfen.

Ziel

The tumor microenvironment (TME) is a dynamic ecosystem wherein tumor cells, immune cells and stromal cells interact and evolve. One of the primary characteristics of cancer progression is the diversification, selection and expansion of tumor sub-clones in manner that largely depends on the TME, e.g. through immune responses or metabolic crosstalk. Advances in single-cell and spatial genomics provide exciting opportunities for studying how tumors evolve in their tissue context, by lending an information-rich perspective on which cell subsets are present and how they might interact. However, fundamental questions, which require the knowledge of how single tumor cells are related sub-clonally, remain challenging to study through that perspective. Fundamentally - what characterizes the immediate cellular environment of successful subclones?

Here, we develop transcriptional phylogeography - a paradigm for studying tumor development in-situ, on a transcriptome-wide scale, and at single cell resolution. Our work will leverage studies by us and others that utilized CRISPR/Cas9 mutations coupled with single cell RNA sequencing to infer the lineage structure of thousands of single cells at a time. Adapting this system for in-situ profiling, we will generate the first of its kind phylogeography dataset of a tumor model. This data will allow us to identify tissue locations that harbor critical sub-clonal properties such as unrestrained growth, dedifferentiation, and metastatic seeding, and thereby investigate - through the lens of high throughput genomics- how the TME is associated with these properties. We will also identify and offer solutions for outstanding analytical questions in this nascent area, from lineage inference given sparse data to characterizing the metabolic aspects of tumor-TME cross talk. Together, these studies will help establish new causal links between the TME and tumor evolution and lay the foundation for transcriptional phylogeography analysis.