A cellular hierarchy in melanoma uncouples growth and metastasis

Karras, Panagiotis; Bordeu, Ignacio; Poźniak, Joanna; Nowosad, Ada; Pazzi, Cecilia; Raemdonck, Nina Van; Landeloos, Ewout; Herck, Yannick Van; Pedri, Dennis; Bervoets, Greet; Makhzami, Samira; Khoo, Jia Hui; Pavie, Benjamin; Lamote, Jochen; Marín-Béjar, Oskar; Dewaele, Michael; Liang, Han; Zhang, Xingju; Hua, Yichao; Wouters, Jasper; Browaeys, Robin; Bergers, Gabriele; Saeys, Yvan; Bosisio, Francesca Maria; Oord, Joost van den; Lambrechts, Diether; Rustgi, Anil K.; Bechter, Oliver; Blanpain, Cédric; Simons, Benjamin D.; Rambow, Florian; Marine, Jean–Christophe

doi:10.1038/s41586-022-05242-7

Cited by 96 publications

(83 citation statements)

References 59 publications

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“…This is, for instance, illustrated by the proximity we describe between the Antigen Presentation cell population and T cells, which suggests that this particular transcriptional program may be acquired through an intercellular communication pathway established by T cells. In concordance with this hypothesis, we previously observed that engraftment of a homogeneous mouse melanocytic cell line into immune competent, but not into immunodeficient, mice resulted in the formation melanoma lesions harbouring a complex and heterogenous transcriptomic landscape that included the Antigen Presentation cell state 32 (data not shown). Moreover, a cancer cell state that expresses both antigen processing and interferon response genes was recently shown to recur across multiple tumour types and to colocalize with T cells 60 .…”

Section: Discussionsupporting

confidence: 73%

“… C, AUCell scores of the functionally enriched marker genes per malignant mouse state (acquired from Karras et. al 32 ), averaged and plotted across the malignant human states.…”

Section: Resultsmentioning

confidence: 99%

“…For the functional annotation of malignant clusters (Figure 1B) we relied both on the interpretation of DEG lists, with various gene set enrichment tools (Supplemental Table S4), and prior biological knowledge acquired through analysis of a scRNA-seq dataset from Tyr::NRasQ61K/°;Ink4a-/-mouse tumours 32 . Unsupervised clustering of these mouse lesions identified 7 distinct melanoma cell states, which we named Melanocytic, Mesenchymal-like, Neural Crest-like, Stress (hypoxia), RNA-processing, Stem-like (pre-EMT) and Antigen Presenting cell states.…”

Section: Resultsmentioning

confidence: 99%

“…Notably, using such approaches, we recently demonstrated that a population of MES cells present in primary tumours in minute amounts drives the metastatic process 32 .…”

Section: Discussionmentioning

confidence: 99%

“…Since these clusters were only detected in individual patients, we postulated that they may be driven by specific genetic alterations. Note that while the murine pre-EMT stem-like state did not emerge as an independent cluster, supervised analysis highlighted human melanoma cells from different patients residing in this state 32 .…”

Section: Portraying the Treatment-naive Human Melanoma Transcriptomic...mentioning

confidence: 98%

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A TCF4/BRD4-dependent regulatory network confers cross-resistance to targeted and immune checkpoint therapy in melanoma

Poźniak

Pedri

Landeloos

et al. 2022

Preprint

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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-naive 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.

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Section: Discussionsupporting

confidence: 73%

“… C, AUCell scores of the functionally enriched marker genes per malignant mouse state (acquired from Karras et. al 32 ), averaged and plotted across the malignant human states.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…Notably, using such approaches, we recently demonstrated that a population of MES cells present in primary tumours in minute amounts drives the metastatic process 32 .…”

Section: Discussionmentioning

confidence: 99%

Section: Portraying the Treatment-naive Human Melanoma Transcriptomic...mentioning

confidence: 98%

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A TCF4/BRD4-dependent regulatory network confers cross-resistance to targeted and immune checkpoint therapy in melanoma

Poźniak

Pedri

Landeloos

et al. 2022

Preprint

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Mapping the single cell spatial immune landscapes of the melanoma microenvironment

Magrill,

Moldoveanu,

et al. 2024

Clin Exp Metastasis

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Melanoma is a highly immunogenic malignancy with an elevated mutational burden, diffuse lymphocytic infiltration, and one of the highest response rates to immune checkpoint inhibitors (ICIs). However, over half of all late-stage patients treated with ICIs will either not respond or develop progressive disease. Spatial imaging technologies are being increasingly used to study the melanoma tumor microenvironment (TME). The goal of such studies is to understand the complex interplay between the stroma, melanoma cells, and immune cell-types as well as their association with treatment response. Investigators seeking a better understanding of the role of cell location within the TME and the importance of spatial expression of biomarkers are increasingly turning to highly multiplexed imaging approaches to more accurately measure immune infiltration as well as to quantify receptor-ligand interactions (such as PD-1 and PD-L1) and cell-cell contacts. CyTOF-IMC (Cytometry by Time of Flight - Imaging Mass Cytometry) has enabled high-dimensional profiling of melanomas, allowing researchers to identify complex cellular subpopulations and immune cell interactions with unprecedented resolution. Other spatial imaging technologies, such as multiplexed immunofluorescence and spatial transcriptomics, have revealed distinct patterns of immune cell infiltration, highlighting the importance of spatial relationships, and their impact in modulating immunotherapy responses. Overall, spatial imaging technologies are just beginning to transform our understanding of melanoma biology, providing new avenues for biomarker discovery and therapeutic development. These technologies hold great promise for advancing personalized medicine to improve patient outcomes in melanoma and other solid malignancies.

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Spatial transcriptomics in human biomedical research and clinical application

Zhang

Mei

et al. 2023

Curr Med

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Over the past 15 years, single-cell RNA sequencing (scRNA-seq) technology, in combination with other omics, has revealed the mechanisms of human development, tumors, and complex diseases at the genome, transcriptome, and proteome levels. However, this approach fails to directly reflect relevant spatial information, such as cell location and interactions. This limitation has been addressed with the advancement of the combination of high-resolution scRNA-seq and spatial transcriptomics (ST), which enables the identification of cell composition, intercellular and intermolecular interaction, and unravels the mechanisms of disease phenotypes. This review explores two types of ST - imaging-based ST (iST) and sequencing-based ST (sST) - and demonstrates how ST analysis can follow disease pathogenesis in a spatiotemporal manner, searching for disease-specific biomarkers. ST technology is an effective tool for resolving major biomedical and clinical problems, including tumor research, brain science, embryonic development, organ atlas construction and other pathological analysis. Looking towards the future, despite its limitations, ST has the potential to address these problems in conjunction with “dynamics, multi-omics, and resolution”. Ultimately, the development of ST technology, improvement of algorithms, utilization of deep learning, and refinement of the analysis process and interpretation will determine the key to transforming ST from bench to bedside.

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A cellular hierarchy in melanoma uncouples growth and metastasis

Cited by 96 publications

References 59 publications

A TCF4/BRD4-dependent regulatory network confers cross-resistance to targeted and immune checkpoint therapy in melanoma

A TCF4/BRD4-dependent regulatory network confers cross-resistance to targeted and immune checkpoint therapy in melanoma

Mapping the single cell spatial immune landscapes of the melanoma microenvironment

Spatial transcriptomics in human biomedical research and clinical application

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