In the tumor microenvironment, immune cells have emerged as key regulators of cancer progression. While much work has focused on characterizing tumor‐related immune cells through gene expression profiling, microRNAs (miRNAs) have also been reported to regulate immune cells in the tumor microenvironment. Using regression‐based computational methods, we have constructed for the first time, immune cell signatures based on miRNA expression from The Cancer Genome Atlas breast and ovarian cancer datasets. Combined with existing mRNA immune cell signatures, the integrated mRNA‐miRNA leukocyte signatures are better able to delineate prognostic immune cell subsets within both cancers compared to the mRNA or miRNA signatures alone. Moreover, using the miRNA signatures, the anti‐inflammatory M2 macrophages emerged as the most significantly prognostic cell type in the breast cancer data (HR [hazard ratio]: 12.9; CI [confidence interval]: 3.09‐52.9;
Tumors develop in a complex physical, biochemical, and cellular milieu, referred to as the tumor microenvironment. Of special interest is the set of immune cells that reciprocally interact with the tumor, the tumor-immune microenvironment (TIME). The diversity of cell types and cell–cell interactions in the TIME has led researchers to apply concepts from ecology to describe the dynamics. However, while tumor cells are known to induce immune cells to switch from anti-tumor to pro-tumor phenotypes, this type of ecological interaction has been largely overlooked. To address this gap in cancer modeling, we develop a minimal, ecological model of the TIME with immune cell conversion, to highlight this important interaction and explore its consequences. A key finding is that immune conversion increases the range of parameters supporting a co-existence phase in which the immune system and the tumor reach a stalemate. Our results suggest that further investigation of the consequences of immune cell conversion, using detailed, data-driven models, will be critical for greater understanding of TIME dynamics.
more » « less- Award ID(s):
- 2019745
- NSF-PAR ID:
- 10452694
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Bulletin of Mathematical Biology
- Volume:
- 85
- Issue:
- 10
- ISSN:
- 0092-8240
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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