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The mycosis fungoides cutaneous microenvironment shapes dysfunctional cell trafficking, antitumor immunity, matrix interactions, and angiogenesis
Alyxzandria M. Gaydosik, Connor J. Stonesifer, Tracy Tabib, Robert Lafyatis, Larisa J. Geskin, Patrizia Fuschiotti
Alyxzandria M. Gaydosik, Connor J. Stonesifer, Tracy Tabib, Robert Lafyatis, Larisa J. Geskin, Patrizia Fuschiotti
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Research Article Dermatology Oncology

The mycosis fungoides cutaneous microenvironment shapes dysfunctional cell trafficking, antitumor immunity, matrix interactions, and angiogenesis

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Abstract

Malignant T lymphocyte proliferation in mycosis fungoides (MF) is largely restricted to the skin, implying that malignant cells are dependent on their specific cutaneous tumor microenvironment (TME), including interactions with non-malignant immune and stromal cells, cytokines, and other immunomodulatory factors. To explore these interactions, we performed a comprehensive transcriptome analysis of the TME in advanced-stage MF skin tumors by single-cell RNA sequencing. Our analysis identified cell-type compositions, cellular functions, and cell-to-cell interactions in the MF TME that were distinct from those from healthy skin and benign dermatoses. While patterns of gene expression were common among patient samples, high transcriptional diversity was also observed in immune and stromal cells, with dynamic interactions and crosstalk between these cells and malignant T lymphocytes. This heterogeneity mapped to processes such as cell trafficking, matrix interactions, angiogenesis, immune functions, and metabolism that affect cancer cell growth, migration, and invasion, as well as antitumor immunity. By comprehensively characterizing the transcriptomes of immune and stromal cells within the cutaneous microenvironment of individual MF tumors, we have identified patterns of dysfunction common to all tumors that represent a resource for identifying candidates with therapeutic potential as well as patient-specific heterogeneity that has important implications for personalized disease management.

Authors

Alyxzandria M. Gaydosik, Connor J. Stonesifer, Tracy Tabib, Robert Lafyatis, Larisa J. Geskin, Patrizia Fuschiotti

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Figure 3

Transcriptional profile of B lymphocytes within individual MF tumors.

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Transcriptional profile of B lymphocytes within individual MF tumors.
(A...
(A) Transcriptomes of 1,018 MS4A1+ cells (10 from HC and 1,008 from MF samples) revealing grouping in each MF sample (n = 7) compared with all HC skin samples (n = 9). Cells from each subject are indicated by different colors. All samples are combined. (B) Mature memory B cells and plasma cells were identified. (C) Multicolor immunofluorescence microscopy staining for CD20 and CD138 in advanced MF (n = 7) and HC (n = 4) skin samples. Representative examples are shown (×1,000). DAPI stains nuclei. (D) Seurat analysis identified 4 discrete Louvain clusters from the B cell data set. (E) Bar plot showing the proportion of cells from each MF sample within individual clusters. (F) Heatmap showing examples of the most highly significant differentially expressed genes (n = 10) for each cluster from D. Differential tests were performed as described in Figure 2E and Methods. Cluster numbers are indicated at the top. Each column represents a cell. (G) Highly significant examples of upregulated pathways by individual clusters are shown. Pathways are represented by enrichment scores (–log P values) and selected by absolute z scores over 2. (H) Heatmap shows average gene expression of B cell signature genes from individual MF samples versus HCs. Gene differential tests are described in Methods. (I) Individual tumors compared with control significant differential expression gene lists (P value < 0.05, log fold change 0.1, minimum percentage 10%) were analyzed in IPA and then compared with each other for common pathways. Heatmap shows z scores of pathways for up- or downregulation of pathways.

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