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; P = 4.22E-4), whereas the pro-inflammatory M1 macrophages emerged as the most prognostic immune cell type in the ovarian cancer data (HR: 0.2; CI: 0.04-0.56, P = 5.02E-3). These results suggest that our integrated miRNA and mRNA leukocyte signatures could be used to better delineate prognostic leukocyte subsets within cancers, whereas continued investigation may further support the regulatory relationships predicted between the miRNAs and immune cells found within our signature matrices.
Keywords: cancer genomics; cancer immunology; computational biology; miRNA immune cell signatures; tumor microenvironment; tumor-associated macrophages.
© 2018 Wiley Periodicals, Inc.