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Methods to Investigate the Tumour Microenvironment: Cherry-niche

Cherry-niche is an in-vivo labelling tool to study cell neighbourhoods. It allows unique staining of tumour cells and non-tumour niche cells of the tumour microenvironment (TME). The result means that one can study unique tumour and non-tumour niche biomarkers and their respective therapeutic targets.

Dr. Luigi Ombrato, Lecturer and Group Lead, Barts Cancer Institute, Queen Mary University London, is the primary developer of Cherry-niche tool and recently spoke at a Front Line Genomics webinar. In this article, we will give an overview of Cherry-niche and its potential applications using quotes taken directly from the webinar. To hear the full set of talks on The Latest and Greatest Methods To Interrogate the Tumour Microenvironment, please follow the webinar link.

Cancer Metastasis

Systematic metastasis is responsible for more than 90% of cancer deaths because treatment options are limited once the cancer cells reach this state. Metastasis is the process by which a tumour ‘spreads’ to, and colonizes, secondary tissues. It is interestingly a very inefficient process. Tumour cells that migrate into the blood stream have a high percentage chance of exiting into the secondary tissues but only 2% successfully for a new colony and 0.02% achieve metastasis. It is unknown what happens in this early metastasis environment to result in such low success.

Luigi’s team believes that the cells from the tumour microenvironment are essential for understanding this bottleneck and the potential therapeutic window it offers.

Luigi: “How the cells of the TME cross-talk, communicate between themselves and with the cells in the tumour is critical to set-up this tumour-favourable environment”

Pulling apart the niche

There are many state-of-the-art tools to study the TME in-vitro and ex-vivo including organoids, single-cell and spatial transcriptomics. When it comes to metastasis, it’s harder to study since tumour cells spreading to different tissues is a dynamic process, and understanding early metastasis using human samples is very challenging.

Luigi’s tool, Cherry-niche, addresses these issues and directly reveals the metastatic niche. It is an in vivo labelling tool and relies on transferring a modified fluorescent protein. By engineering cancer cells with the Cherry-niche marking system, these cells can then release the Cherry-niche to their neighbours, who uptake the Cherry-niche and become positive. This reveals the metastatic microenvironment.

If you engineer cancer cells to be GFP positive (green fluorescence) and mCherry positive (red fluorescence), the mCherry will dissociate to the neighbours while the GFP will not.

Luigi: “If we now take the whole tissue and dissociate by FACS, we can clearly discriminate the double positive tumour cells, that are green and red and the single, cherry-positive cells, and these are the cells of the niche”

Figure 1. Cherry-niche labelling cells of the metastatic niche. Image taken directly from FLG webinar (July 6th, 2023), full credit – Dr. Luigi Ombrato

Exemplar use case

By doing this in live cells, Cherry-niche gives you the power to characterise the TME as opposed to the tumour cells and to identify the metastatic niche which the tumour cell establishes when it invades.

By isolating lung tissue in mice at an early and late stage metastasis, Luigi’s group were able to analyse the cells of the niche and identify a novel role for epithelial cells in the early formation of the lung parenchyma metastatic niche. These cells appear to create a tissue regeneration response that supports cancer cell growth.

Cherry-niche has been distributed to over 300 laboratories in the world to help deconstruct the cancer microenvironment in a variety of cancer types. The original publications should be consulted for a thorough overview of the method1-3.

Webinar Questions and Answers

Q: What properties does the tumour niche possess that makes it favourable for metastasis?

A: There are several properties, but just to mention a few. We know that there are different types of cells in the TME, and some of these cells (a classic example is the CD8 cytotoxic T cells) should be there and should have the ability to kill the tumour cells. This is prevented by other cells that create an immunosuppressive environment. Another example is cells such as fibroblasts, which are able to remodel the ECM to which the tumour is confined. Having cells that help to degrade this matrix can help the tumour to invade this matrix.

Q: How can studying the metastatic niche help bring new treatment opportunities to patients?

A: It is very important that we understand what is going on. The research is aiming to understanding the events and distinctive changes in the niche that are supporting the tumour’s growth.  This is the first step. If we don’t understand the biology of the processes, how can we target them? By understanding the metastatic niche, we can have the most effective and most targeted treatment.

Q: Do you have future plans for Cherry-niche? Or what would you like to see another lab use Cherry-niche for?

A:The future plans are to extend the feasibility of this model to different tumour models and different TMEs. A lot of people are already doing that. Something less obvious; if you could perhaps engineer stem cells with Cherry-niche, you could understand other types of processes. One group used Cherry-niche to study viral infection – how the virus enters the first cells, how it spreads to surrounding cells and how the surrounding cells change to host the viral replication over time. This shows the versatility of this tool.

To hear from the other speakers at this webinar and for the full Q&A please use this link.

References

1. Ombrato, L. In vivo labelling system to study cell neighbourhoods. Nature Reviews Cancer 22, 661-661 (2022).

2. Ombrato, L. et al. Metastatic-niche labelling reveals parenchymal cells with stem features. Nature 572, 603-608 (2019).

3. Ombrato, L. et al. Generation of neighbor-labeling cells to study intercellular interactions in vivo. Nat Protoc 16, 872-892 (2021).