Summary

Langerhans cell histiocytosis (LCH) is a rare neoplasm predominantly affecting children. It occupies a hybrid position between cancers and inflammatory diseases, and it provides an attractive model for studying cancer development. To explore the molecular mechanisms underlying the pathophysiology of LCH and its characteristic clinical heterogeneity, we investigated the transcriptomic and epigenomic diversity in primary LCH lesions. Using single-cell RNA sequencing, we identified multiple recurrent types of LCH cells within these biopsies, including putative LCH progenitor cells and several subsets of differentiated LCH cells. We confirmed the presence of proliferative LCH cells in all analysed biopsies using immunohistochemistry, and we defined an epigenomic and gene regulatory basis of the different LCH cell subsets by chromatin accessibility profiling. In summary, our single-cell analysis of LCH un-covered an unexpected degree of cellular, transcriptomic, and epigenomic heterogeneity among LCH cells, indicative of complex developmental hierarchies in LCH lesions.

This study sketches a molecular portrait of LCH lesions by combining single-cell transcriptomics with epigenome profiling. We uncovered extensive cellular heterogeneity, explained in part by an intrinsic developmental hierarchy of LCH cells. Our findings provide new insights and hypotheses for advancing LCH research and a starting point for personalising therapy.

On this website we present additional supplementary materials accompanying the publication.

Data Tables

Data tables of processed single-cell RNA-seq and bulk ATAC-seq data for easy re-use.

Name	Description and link
Single-cell RNA-seq	Gene expression matrix (raw UMI counts): lch_10x_raw.csv.gz (38.9 MB) Gene expression matrix (normalised UMI counts): lch_10x_norm.csv.gz (109.4 MB) Metadata (per cell: barcode, patient ID, % mitochondrial content, G1/S/G2M scores, biopsy site, sex, disease extent, assigned cluster ID, cell type, LCH cell subset (if applicable), and t-SNE coordinates): lch_10x_meta.csv.gz (0.9 MB) Further links to raw and processed data are available below.
ATAC-seq	Peak coordinates: lch_atac_LCH-S1_1_peaks.bed.gz lch_atac_LCH-S1_2_peaks.bed.gz lch_atac_LCH-S11_1_peaks.bed.gz lch_atac_LCH-S11_2_peaks.bed.gz lch_atac_LCH-S12_1_peaks.bed.gz lch_atac_LCH-S12_2_peaks.bed.gz (0.2 - 0.5 MB) Merged peak coordinates and module assignments: lch_atac_merged_peaks.csv.gz (0.4 MB) Signal intensities (raw read counts): lch_atac_raw.csv.gz (0.3 MB) Signal intensities (DESeq2-normalised): lch_atac_norm.csv.gz (0.4 MB) Metadata: lch_atac_meta.csv.gz (~0 MB) Further links to raw and processed data are available below. Please also take note of the genome browser track hub.

Marker Genes

Lists marker genes based on differential analysis between groups of cells in the single-cell RNA-seq data.

Name	Description and link
LCH vs. non-LCH cells	Individual comparisons: lch_deg_vsnonlch.csv (0.1 MB) LCH gene signature: lch_deg_signature.csv (~0 MB) t-SNE plots of all genes mentioned in the paper in relation to LCH or non-LCH cells (not necessarily LCH-specific or highly expressed): tsne_all.zip (12.7 MB) || ARAF BRAF CCL3 CCL4 CD14 CD163 CD19 CD1A CD1E CD207 CD33 CD3D CD79A CLEC4C CST3 FOXP3 HLA-DQB2 IGHG1 IGKC IL32 IL3RA IRF7 IRF8 LYZ MAP2K1 MMP9 MYC NFKBIA S100A4 S100A8 TACSTD2 TCF4
LCH cell subsets	Markers of all LCH cell subsets: lch_deg_subsets.csv (~0 MB) t-SNE plots of all genes mentioned in the paper in relation to the LCH developmental hierarchy (not necessarily LCH-subset-specific or highly expressed): tsne_lch.zip (31.4 MB) || ANPEP AURKA AURKB BATF3 BCL11A BCL3 BCL6 BRAF CBX3 CCR7 CD1A CD207 CD300A CD63 CD68 CD83 CDK1 CDK7 CDK9 CENPA CLEC9A CXCR4 DNMT1 EP300 ETV3 FOSL1 FOSL2 GTF2B HLA-DQA2 HMGN3 IFI6 IFIT3 IL22RA2 IL7R IRF1 IRF4 IRF8 JDP2 JUNB KDM1A KDM2B KDM4A KDM5B KDM5C LAMP3 MITF MKI67 MMP12 MMP9 MTA3 MXD3 MXI1 MYB MYBL2 NFATC1 PHF19 PRDM1 RBBP5 REL RELB S100A3 SMYD3 SOX4 SPI1 SPIB STAT1 STAT2 STAT3 STAT5A TCF7L2 TFDP1 TUBA1B TUBB

Genome Browser Tracks

Genome browser tracks for visualisation of the genomic alignments of ATAC-seq data from LCH cell subsets.

Name	Description and link
Genome browser	Genome browser track hub: http://www.biomedical-sequencing.at/bocklab/papers/LCH_hierarchy/data/tracks/lch_hub.txt Direct link: Open in UCSC genome browser (USA), Open in UCSC genome browser (Europe), Open in Ensembl genome browser
Tutorials	UCSC: Using genome browser track hubs Ensembl: Adding track hubs

Gene Regulatory Networks

Interactive visualisations of the gene regulatory networks underlying different LCH cell subsets.

Name	Description and link
Network visualisations	LCH-S1 LCH-S12 LCH-S11
Description	Gene regulatory networks were inferred for three LCH cell subsets (LCH-S1, LCH-S12, LCH-S11), based on single-cell transcriptome and ATAC-seq data, and the key regulators identified by enrichment analysis. Nodes in the network correspond to the enriched transcription factors as well as their putative target genes (based on sequence proximity and chromatin 3D structure). Node size is proportional to both gene expression level and node out-degree (i.e., number of outgoing connections from the transcription factor) in the respective LCH subset. Edge colours indicate the module of the corresponding peak, and edge visibility is proportional to chromatin accessibility. Networks were implemented in R using igraph and converted into an interactive web version using visNetwork.

Data and Links

Links to raw data archives and related resources.

Name	Description and link
GEO	Processed single-cell RNA-seq and ATAC-seq data are openly available via Gene Expression Omnibus. Super-series: GSE133706 scRNA-seq: GSE133704 ATAC-seq: GSE133785
EGA	Raw sequencing reads are available as controlled access via the European Genome-Phenome Archive. EGA dataset: EGAS00001003822
Code	Computer code used for the analysis of single-cell RNA-seq and ATAC-seq data in the paper are available via GitHub. Via epigen organization: epigen/lch_hierarchy Via cancerbits organization: cancerbits/lch_hierarchy
Research Groups	Langerhans Cell Histiocytosis Biology Medical Epigenomics Integrative Analysis of Pediatric Cancer

Citation

If you use this resource in your research, please cite:

Halbritter F^*, Farlik M^*, Schwentner R, Jug G, Fortelny N, Schnoeller T, Pisa H, Schuster LC, Reinprecht A, Czech T, Gojo J, Holter W, Minkov M, Bauer W, Simonitsch-Klupp I, Bock C^#, Hutter C^#. Epigenomics and Single-cell Sequencing Define a Developmental Hierarchy in Langerhans Cell Histiocytosis. Cancer Discovery (2019), doi: 10.1158/2159-8290.CD-19-0138