Usage Information
Citation Information: JCI Insight. 2019;4(6):e126543. https://doi.org/10.1172/jci.insight.126543.
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
Usage data is cumulative from November 2023 through November 2024.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 866 | 298 |
| 86 | 65 | |
| Figure | 220 | 15 |
| Supplemental data | 69 | 6 |
| Citation downloads | 42 | 0 |
| Totals | 1,283 | 384 |
| Total Views | 1,667 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
