LAUSR

Background: miRNA have been shown to be central communicators between the immune system and cancer. They are attractive as candidate blood-based cancer detection targets because they are secreted in high copy number from cancer cells, are bound to circulating proteins and have secondary structures that prolong their half-life in blood. miRNAs that are thought to communicate between cancer associated fibroblasts and immune cells are of special interest for their potential involvement in transitions in the TIME from "hot" - an inflammatory state with a greater likelihood of sensitivity to immune checkpoint inhibitors - to "cold" - tumors with an immunosuppressive state or immune inert state or vice versa. We have previously described a gene expression signature that distinguishes immunomodulatory (IM, inflammatory cells), mesenchymal (M, EMT differentiated cells), and mesenchymal stem-like (MSL, cancer associated fibroblasts) features of the TIME, and when converted to a binary classifier, has been shown to be correlated with response to immune checkpoint inhibitors (ICI). Here we use TCGA microRNA data to identify a microRNA correlate of this classifier. Methods: miRNA and RNA expression were collected from TCGA across five tissue types. Each tumor case was assigned a TIME phenotype as previously described [1]. Lung, breast, colon, and bladder data were used to identify miRNA’s whose expression pattern significantly correlated with at least one of three immune phenotypes identified by the previously defined algorithm. Data from the IntAct database were used to identify putative gene targets of the candidate miRNA. Results: Of the 151 miRNAs of interest, 147 known interactions were found in the IntAct database. Of these 147 interactions, 107 were between miRNA and genes of different TIME (or immune) phenotypes while 89 were interactions between miRNAs and genes implicated in regulating immune hot and cold phenotypes. Conclusions: We identified miRNA whose expression patterns correlates with a classifier of the TIME that has been shown to identify likely responders to immune checkpoint inhibitors. This candidate gene list was significantly enriched for both miRNA targets of known immune mediators and or targets implicated in modulating the TIME. Next steps are to further narrow the list to those detectable in blood in cancer, and to train a blood-based diagnostic that might be able to predict response to ICI therapy for those patients where tissue is not available. References: [1] Seitz, R.S., Hurwitz, M.E., Nielsen, T.J. et al. Translation of the 27-gene immuno-oncology test (IO score) to predict outcomes in immune checkpoint inhibitor treated metastatic urothelial cancer patients. J Transl Med 20, 370 (2022). https://doi.org/10.1186/s12967-022-03563-9 Citation Format: Catherine T. Cronister, Robert S. Seitz, Brian Z. Ring, Douglas T. Ross, Brock Schweitzer. The role of microRNAs in the tumor immune microenvironment. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4118.