# Deciphering mechanisms driving malignant transformation in Neurofibromatosis Type I, from single-cell transcriptomics

Audrey Onfroy¹,², Fanny Coulpier¹, Katarzyna Radomska¹, Denis Thieffry² and Piotr Topilko¹

¹ Institut Mondor de Recherche Biomédicale, Inserm U955 - Team 9, Créteil, France

² Institut de Biologie de l'École Normale Supérieure, UMR CNRS 8197, Inserm U1024, PSL Université, Paris, France

Contact : audrey.onfroy@inserm.fr

## NF1 IS A GENETIC DISEASE

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* Affects 1 / 3,000 births worldwide

* Bi-allelic mutation of **NF1** in Schwann cell lineage

* Numerous symptoms, including development of benign nerve sheath tumors : **neurofibromas** (NFs), and their progression to malignant peripheral nerve sheath tumors (**MPNSTs**)

nerve sheath

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plexiform NF

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dysplastic NF

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MPNST

purpose of my PhD project

no treatment to date

## Nf1-KO MOUSE MODEL [1]

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* Bi-allelic mutation of **Nf1** in Schwann cell lineage

* Nf1 mutant cells are traced by the **Tomato** reporter

* Nf1-KO mice share common features with NF1 patients, including development of pNFs and their progression into MPNSTs through a dysplastic stage

What are the molecular events driving malignant transformation of pNF into MPNST, in tumor forming cell populations, in the mouse model and in NF1 patients ?

## AVAILABLE DATASETS

Single-cell transcriptomic technologies enable the study of NFs and MPNSTs transcriptional landscapes considering their cellular heterogeneity.

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Single-cell RNA sequencing : for each biological sample, we have a genes x cells expression matrix

## METHODS

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## RESULTS

### Peripheral Nerve Sheath Tumors atlas from Nf1-KO mice

What is the identity of each cell population ?

**Figure 1** - tSNE showing 60,000 cells from 16 datasets. One dot represents one single cell. Cells are colored by sample of origin. Batch-effect has been removed using harmony [2]. Some cell populations are specific from pNF (blue) or MPNST (brown).

**Figure 2** - (A) tSNE showing 60,000 cells from 16 datasets. We designed an automatic cell type annotation method. Annotation is validated using **Tomato** expression level, a tumor immune cell atlas [3], and known marker genes. (B) Barplot depicting tumor type specific composition. Tumor cell population (■) becomes predominant in MPNST, while stromal cells (■) decline, and immune cells (■) amount peaks in dysplastic tumors.

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### Tumor cell populations transcriptional landscape from pNF to MPNST

What is the transcriptomic profile of tumor cells ?

**Figure 3** - (A) Representation of 20,000 tumor cells from 16 datasets. Cells are colored by sample of origin. Same legend as Fig. 1. (B) Pseudotime inference using Slingshot [4] reconstructs cell-to-cell transcriptomic changes from pNFs to MPNSTs. (C) Heatmap showing gene expression changes along pseudotime. Expression of genes in blue have been validated by immunolabeling. Tumor cells in pNF carry a glial signature (Sox10) whereas MPNST cells have a mesenchymal signature (Sox9).

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## CONCLUSIONS & PROSPECTS

### Single-cell transcriptomics allow tumor forming populations study at a single cell level

* Tumors are formed by about 10 cell populations, whose proportions and transcriptomic activities changes during malignant progression

* Tumor cell population becomes predominant in MPNST, while stromal cells decline, and immune cells amount peaks in dysplastic tumors

* Trajectory inference shows a switch in tumor cells identity, confirmed by immunolabeling

### Prospects

* Study the tumor micro-environment, and their interactions with the tumor cell populations

* Functional validation of candidate genes implicated in malignant transformation

* Integrate other types of data : mutational landscape, single-nuclei ATAC-Seq and NF1 patients scRNA-Seq

## REFERENCES

[1] Radomska et al., Cellular Origin, Tumor Progression, and Pathogenic Mechanisms of Cutaneous Neurofibromas Revealed by Mice with Nf1 Knockout in Boundary Cap Cells, Cancer Discovery (2019)

[2] Stuart et al., Comprehensive Integration of Single-Cell Data, Cell (2019)

[3] Nieto et al., A single-cell tumor immune atlas for precision oncology, Genome Research (2021)

[4] Street et al., Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics, BMC Genomics (2018)

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