DOI: 10.48804/gsaxbn
title: Dissecting the melanoma ecosystem one cell at the time during immunotherapy
title: scRNA-seq data of malignant cells from human melanoma metastatic biopsies

description: This dataset contains count matrices of malignant cells from the scRNA-seq data together with each cell assignment to the malignant state (column name: Malignant_clusters) and count matrices of the entire tumour microenvironment (TME) cells.
The full clinical metadata table can be found in the Pozniak et al., (Cell, 2024) paper (Table S1).


To explore the malignant data online please use this link to the Shiny app: https://marine-lab.shinyapps.io/Human_melanoma_scRNASeq/


To explore the immune data online please use this link to the Shiny app: https://marine-lab.shinyapps.io/Human_melanoma_immune_scRNASeq/


Moreover, here the images used for Visium Spatial Transciptomic experiment can be found.
description: Primary resistance drastically limits the clinical success of immune checkpoint blockade (ICB) in melanoma. Resistance to ICB may also develop when tumours relapse after targeted therapy. To identify cancer cell-intrinsic mechanisms driving resistance to ICB, we generated single-cell RNA-sequencing (scRNA-seq) data from a prospective longitudinal cohort of patients on ICB therapy, including an early time point obtained after only one cycle of treatment. Comparing these data with murine scRNA-seq datasets, we established a comprehensive view of the cellular architecture of the treatment-naïve melanoma ecosystem, and defined 6 evolutionarily conserved melanoma transcriptional metaprograms (Melanocytic or MEL, Mesenchymal-like or MES, Neural Crest-like, Antigen Presentation, Stress (hypoxia response) and Stress (p53 response)). Spatial multi-omics revealed a non-random geographic distribution of cell states that is, at least partly, driven by the tumour microenvironment. The single-cell data allowed unambiguous discrimination between melanoma MES cells and cancer-associated fibroblasts both in silico and in situ, a long-standing challenge in the field. Importantly, two of the melanoma transcriptional metaprograms were associated with divergent clinical responses to ICB. While the Antigen Presentation cell population was more abundant in tumours from patients who exhibited a clinical response to ICB, MES cells were significantly enriched in early on-treatment biopsies from non-responders, and their presence significantly predicted lack of response. Critically, we identified TCF4 (E2-2) as a master regulator of the MES program and suppressor of both MEL and Antigen Presentation programs. Targeting TCF4 expression in MES cells either genetically or pharmacologically using a bromodomain inhibitor increased immunogenicity and sensitivity to targeted therapy. This study describes an increasingly complex melanoma transcriptional landscape and its rapid evolution under ICB. It also identifies a putative biomarker of early response to ICB and an epigenetic therapeutic strategy that increases both immunogenicity of ICB-refractory melanoma and their sensitivity to targeted therapy.
description: Fastq files generated from the Visium Spatial Transcriptomic can be requested via EGA under dataset number EGAD00001010921.