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

This project aims to develop transcriptional phylogeography to study tumor evolution in situ at single-cell resolution, linking tumor microenvironment characteristics to sub-clonal properties.

Subsidie
€ 2.000.000
2023

Projectdetails

Introduction

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 a manner that largely depends on the TME, e.g., through immune responses or metabolic crosstalk.

Advances in Research

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.

Key Questions

Fundamentally, what characterizes the immediate cellular environment of successful subclones?

Methodology

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.

Data Generation

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
  • Metastatic seeding

By doing so, we will investigate—through the lens of high-throughput genomics—how the TME is associated with these properties.

Analytical Challenges

We will also identify and offer solutions for outstanding analytical questions in this nascent area, including:

  1. Lineage inference given sparse data
  2. Characterizing the metabolic aspects of tumor-TME crosstalk

Conclusion

Together, these studies will help establish new causal links between the TME and tumor evolution and lay the foundation for transcriptional phylogeography analysis.

Financiële details & Tijdlijn

Financiële details

Subsidiebedrag€ 2.000.000
Totale projectbegroting€ 2.000.000

Tijdlijn

Startdatum1-4-2023
Einddatum31-3-2028
Subsidiejaar2023

Partners & Locaties

Projectpartners

  • WEIZMANN INSTITUTE OF SCIENCEpenvoerder

Land(en)

Israel

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