Abstract 723: Distinguishing macrophages by a unique gene signature to measure response to treatment

Abstract

Abstract Objectives: Tumor-associated macrophage infiltration is associated with poor prognosis, making macrophage depletion an ideal therapy. This study aims to identify a macrophage-specific gene signature to quantify macrophage content and measure response to treatment of high-grade serous cancer (HGSC) with colony stimulating factor-1 receptor (CSF1R) inhibitor. Methods: 39 murine genes were identified in the literature as being macrophage-specific. Corresponding human orthologous genes were identified using BioMart database. Expression levels (log-transformed normalized RSEM values) of human homologous genes were retrieved from The Cancer Genome Atlas (TCGA) portal. Principal component (PC) and hierarchical clustering (HC) analysis of 305 primary HGSC was performed. Q-PCR was performed on human macrophage cell line, endothelial cell line, and fibroblast cell line. Q-PCR was also performed on tumor tissue obtained from CD57Bl/6 mice injected with murine ovarian cancer and treated with CSF1R inhibitor. Results: 37 human homologous genes were identified for the macrophage specific murine genes. Of the 37 genes, 12 tracked together tightly and included the top 3 genes with greatest median absolute deviance of RSEM values, thus were chosen for further analysis. Q-PCR using human macrophage cell line revealed high expression in all 12 genes (delta CT <25), with TBXAS, CD14, and FCGR1A being the highest. All 12 genes showed greater expression in macrophages versus fibroblasts and endothelial cells, to varying degrees. Expression of CD14, TLR7, FCGR2C, and FCGR1B was significantly higher (p<0.0001) in macrophages compared to both fibroblasts and endothelial cells. Of these 12 human genes, 4 had homologous murine genes. These genes were used for Q-PCR on murine tumor tissue treated with CSF1R inhibitor. There was a statistically significant decrease in the level of CSF3R (p = 0.005), FCGR (p = 0.02), and PON3 (p = 0.002) between the control group and the group treated with CSF1R inhibitor. Conclusions: These data suggest that macrophage specific genes could be useful for quantifying macrophage content in tumor samples to monitor therapy-related changes. Citation Format: Yasmin A. Lyons, Sunila Pradeep, Jean M. Hansen, Rebecca A. Previs, Hui Yao, Keith A. Baggerly, Anil K. Sood. Distinguishing macrophages by a unique gene signature to measure response to treatment. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 723.