Project description
Mapping tumours at single-cell resolution
The tumour microenvironment (TME) is a complex ecosystem where tumour, immune and stromal cells interact. Cancer progression involves the diversification and expansion of tumour subclones influenced by the TME. Advances in single-cell genomics help explore these interactions, but key questions remain about the environment surrounding successful subclones. The ERC-funded Tx-phylogeography project will develop transcriptional phylogeography to study tumour development at single-cell resolution. Using CRISPR/Cas9 mutations and single-cell RNA sequencing, it will create a dataset that identifies key subclonal traits and their relationships with the TME. The project will also address analytical challenges in this field, aiming to link the TME with tumour evolution.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences genetics mutation
- medical and health sciences clinical medicine oncology
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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(opens in new window) ERC-2022-COG
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7610001 Rehovot
Israel
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