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MicroRNA-155 coordinates the immunological landscape within murine melanoma and correlates with immunity in human cancers
H. Atakan Ekiz, Thomas B. Huffaker, Allie H. Grossmann, W. Zac Stephens, Matthew A. Williams, June L. Round, Ryan M. O’Connell
H. Atakan Ekiz, Thomas B. Huffaker, Allie H. Grossmann, W. Zac Stephens, Matthew A. Williams, June L. Round, Ryan M. O’Connell
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Research Article Immunology Oncology

MicroRNA-155 coordinates the immunological landscape within murine melanoma and correlates with immunity in human cancers

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Abstract

miR-155 has recently emerged as an important promoter of antitumor immunity through its functions in T lymphocytes. However, the impact of T cell–expressed miR-155 on immune cell dynamics in solid tumors remains unclear. In the present study, we used single-cell RNA sequencing to define the CD45+ immune cell populations at different time points within B16F10 murine melanoma tumors growing in either wild-type or miR-155 T cell conditional knockout (TCKO) mice. miR-155 was required for optimal T cell activation and reinforced the T cell response at the expense of infiltrating myeloid cells. Further, myeloid cells from tumors growing in TCKO mice were defined by an increase in wound healing genes and a decreased IFN-γ–response gene signature. Finally, we found that miR-155 expression predicted a favorable outcome in human melanoma patients and was associated with a strong immune signature. Moreover, gene expression analysis of The Cancer Genome Atlas (TCGA) data revealed that miR-155 expression also correlates with an immune-enriched subtype in 29 other human solid tumors. Together, our study provides an unprecedented analysis of the cell types and gene expression signatures of immune cells within experimental melanoma tumors and elucidates the role of miR-155 in coordinating antitumor immune responses in mammalian tumors.

Authors

H. Atakan Ekiz, Thomas B. Huffaker, Allie H. Grossmann, W. Zac Stephens, Matthew A. Williams, June L. Round, Ryan M. O’Connell

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Figure 1

Single-cell RNA sequencing reveals cellular dynamics within the tumor immune microenvironment in the presence and absence of T cell–specific miR-155.

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Single-cell RNA sequencing reveals cellular dynamics within the tumor im...
(A) Diagram showing the method employed for tumor-infiltrating immune cell single-cell RNA sequencing (SCseq). At the experimental endpoint, cells from 4 mice per group were combined and equal numbers were processed for 10× SCseq. (B) Tumor weights at the experimental endpoints of days 9 and 12, showing a higher tumor burden in miR-155 TCKO mice on day 12. Two-tailed t test was used for statistical comparisons. *P ≤ 0.05; ns, P > 0.05. (C) T-distributed stochastic neighbor embedding (t-SNE) plots of SCseq data showing 15 distinct cell clusters (aggregate data from WT and miR-155 TCKO samples from days 9 and 12). (D) Gene expression heatmap showing the top 10 differentially expressed genes in clusters. Columns indicate clusters and rows indicate genes. The column widths are proportional to the numbers of cells in clusters. Each vertical bar within the columns represents an individual cell. (E) Expression pattern of miR-155 host gene (Mir155hg) is shown. (F) Dot charts showing the expression of selected genes in cell clusters. The size of the dots represents the frequency of cells within the cluster expressing the gene of interest, while the color intensity indicates the level of expression. Dashed boxes indicate genes that are selectively expressed within clusters. (G) SCseq t-SNE plots showing the immune landscape in WT and miR-155 TCKO animals at 2 different time points. Activated CD8+ T cell (gray arrows), activated cycling CD8+ T cell (red arrows), naive CD8+ T cell (yellow arrowhead), pDC (dagger), Ly6a+ neutrophil (unfilled circle), Arg1+ neutrophil (filled circle), monocyte (unfilled square), and F4/80– macrophage (filled square) clusters are indicated. (H) Frequency of cell clusters in WT and miR-155 TCKO tumor microenvironment at days 9 and 12.

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