Single-cell RNA sequencing reveals markers of disease progression in primary cutaneous T-cell lymphoma

Rindler, Katharina; Jonak, Constanze; Alkon, Natalia; Thaler, Felix M.; Kurz, Harald; Shaw, Lisa E.; Stingl, Georg; Weninger, Wolfgang; Halbritter, Florian; Farlik, Matthias; Brunner, Patrick M.

doi:10.1016/s0959-8049(21)00695-x

Cited by 3 publications

(10 citation statements)

References 59 publications

(67 reference statements)

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“…In parallel, the γδ T and CD8 T cells were extracted likewise from the CTCL patient MF318 scRNAseq dataset, downloaded from the publicly available GEO GSE173205 [10]. This dataset was separately pre-processed by using the same Seurat 3.0 pipeline, and its single cells were scored for multigene signatures to further digitally extract its γδ T and CD8 T lymphocytes by score and gate as above.…”

Section: Materials and Methods Scrnaseq Datasets Pre-processing And R...mentioning

confidence: 99%

“…The γδ T lymphoma cells of CTCL type were sourced from the public scRNAseq dataset of CTCL patient MF318 (GEO GSE173205, Methods), a 55 years old Caucasian female patient diagnosed with stage IIB CD30 + γδ MF without large cell transformation [10]. Its γδ T lymphocytes were digitally purified using score and gate by successively discarding the keratinocytes, melanocytes, myeloid, B, natural killer (NK), CD4 T, and finally CD8 T cells from the dataset.…”

Section: Extraction and Integration Of Skin γδ T Lymphocytes From The...mentioning

confidence: 99%

“…More specifically, MF represents a malignancy of skin resident T cells at the Tem differentiation stage, while leukemic CTCL is rather a malignancy of recirculating Tcm lymphocytes [9]. To explore the mechanisms of this early progression, here we digitally extracted the γδ T lymphocytes from a recently published scRNAseq dataset of γδ CTCL [10] with patch and plaque annotations (MF318 from GSE173205), and analyzed these cells by 'trajectory mapping'. The findings we report from this new type of data exploration provide novel insight into the cellular mechanisms underlying the early stages of this T cell malignancy.…”

Section: Introductionmentioning

confidence: 99%

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Single-cell differentiation trajectories define early stages of a human cutaneous T-cell lymphoma

et al. 2022

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Aim: The aim of this article is to characterize in detail the γδ T lymphocytes from an adult patient with primary cutaneous T-cell lymphoma of γδ subtype (γδ CTCL). Methods: Here this article reports trajectory mapping on high-resolution differentiation trajectories of γδ T lymphocytes digitally extracted from a scRNAseq dataset. Results: In the patch-to-plaque progression of CTCL, the TCRVγnon9 subset of γδ T cells differentiated from naive T cells (Tn) and central memory T cells (Tcm) to abundant effector memory T cells (Tem) while other cutaneous γδ T and CD8 T cells remained unchanged. Conclusions: This transcriptomic switch underlies the emergence of a CTCL-like progression of the TCRVγnon9 γδ T subtype and suggests new routes for treating these diseases.

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Section: Materials and Methods Scrnaseq Datasets Pre-processing And R...mentioning

confidence: 99%

Section: Extraction and Integration Of Skin γδ T Lymphocytes From The...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Single-cell differentiation trajectories define early stages of a human cutaneous T-cell lymphoma

et al. 2022

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“…Rindler et al discerned disease progression in primary cutaneous T‐cell lymphoma by performing scRNA‐seq αβ and T‐cell receptor sequencing on skin samples from patients with different stages of mycosis fungoides (MF), the most frequent type of this malignancy 75 . Lesion progression correlated with downregulation of tissue‐resident memory T‐cell markers CXCR4 and CD69, heat shock protein HSPA1A, immunoregulatory molecules ZFP36 and TXNIP, and interleukin receptor IL7R 75 . Furthermore, because malignant cells can spread from the skin in later stages, the authors profiled with scRNA‐seq and simultaneous V‐D‐J sequencing the tumor microenvironment of skin, blood and lymph node in a patient with advanced MF 76 …”

Section: Applications In Skin Researchmentioning

confidence: 99%

Section: Applications In Skin Researchmentioning

confidence: 99%

Single‐cell transcriptomics in human skin research: available technologies, technical considerations and disease applications

Theocharidis

Tekkela

Veves

et al. 2022

Experimental Dermatology

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The human skin is defined by a multilayer architecture based on diverse cell populations of mainly keratinocytes and fibroblasts, as well as various immune cells, melanocytes, adipocytes and endothelial cells that orchestrate events leading to wound repair of pathogenic infections and exposure to ultraviolet radiation and toxic compounds. 1 The transcriptomic profile of skin can provide information on gene expression, non-coding regulatory elements and gene splicing, and therefore shed light on skin physiology and pathology. Earlier approaches such as bulk RNA-seq and microarrays provided information about the average transcriptome status

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Phenotypic plasticity of malignant T cells in blood and skin of a Sézary syndrome patient revealed by single cell transcriptomics

et al. 2023

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BackgroundSézary Syndrome (SS) is an aggressive leukemic variant of cutaneous T-cell lymphomas (CTCL). In SS patients, malignant T cells are circulating through the blood and cause erythroderma.ObjectiveTo compare the transcriptome of single cells in blood and skin samples from a patient with advanced SS.MethodsWe utilized combined single cell RNA and T-cell receptor (TCR) sequencing (scRNA-seq).ResultsWe scrutinized the malignant T cells in blood and skin in an unbiased manner without pre-sorting of cells. We observed different phenotypes of the same monoclonal malignant T-cell population, confirmed by TCR sequencing and inferred copy number variation analysis. Malignant T cells present in the circulating blood expressed genes resembling central memory T cells such as CCR7, IL7R and CD27. In the skin, we detected two major malignant T-cell populations: One subpopulation was closely related to the malignant T cells from the blood, while the other subpopulation expressed genes reminiscent of skin resident effector memory T cells including GZMB and NKG7. Pseudotime analysis indicated crucial transcriptomic changes in the transition of malignant T cells between blood and skin. These changes included the differential regulation of TXNIP, a putative tumor suppressor in CTCL, and the adaptation to the hypoxic conditions in the skin. Tumor cell proliferation in the skin was supported by stimulating interactions between myeloid cells and malignant T cells.ConclusionsUsing scRNA-seq we detected a high degree of functional heterogeneity within the malignant T-cell population in SS and highlighted crucial differences between SS cells in blood and skin.

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Single-cell RNA sequencing reveals markers of disease progression in primary cutaneous T-cell lymphoma

Cited by 3 publications

References 59 publications

Single-cell differentiation trajectories define early stages of a human cutaneous T-cell lymphoma

Single-cell differentiation trajectories define early stages of a human cutaneous T-cell lymphoma

Single‐cell transcriptomics in human skin research: available technologies, technical considerations and disease applications

Phenotypic plasticity of malignant T cells in blood and skin of a Sézary syndrome patient revealed by single cell transcriptomics

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