Immune Landscape of Pituitary Tumors Reveals Association Between Macrophages and Gonadotroph Tumor Invasion

International audienceAbstract Purpose Pituitary neuroendocrine tumors (PitNETs) are frequent intracranial neoplasms that present heterogenic characteristics. Little is known about the immune cell network that exists in PitNETs and its contribution to their aggressive behavior. Methods Here we combined flow cytometry, t-SNE analysis, and histological approaches to define the immune landscape of surgically resected PitNETs. Xenografts of rodent pituitary tumor cells and resected PitNETs were performed in Rag2KO mice, in combination with in vitro analysis aimed at dissecting the role of pituitary tumor-cells in monocyte recruitment. Results We report that gonadotroph PitNETs present an increased CD68+ macrophage signature compared to somatotroph, lactotroph, and corticotroph PitNETs. Transcriptomic and histological characterizations confirmed gonadotroph infiltrating macrophages expressed CD163, MRC-1, ARG1, and CSF1R M2 macrophage markers. Use of growth hormone (GH)3/GH4 somatotroph and LβT2/αT3.1 gonadotroph cells drove THP1 macrophage migration through respective expression of CCL5 or CSF1. Although both LβT2 and GH3 cells recruited F4/80 macrophages following their engraftment in mice, only LβT2 gonadotroph cells showed a capacity for M2-like polarization. Similar observations were performed on patient-derived xenografts from somatotroph and gonadotroph tumors. Analysis of clinical data further demonstrated a significant correlation between the percentage of CD68+ and CD163+ infiltrating macrophages and the invasive character of gonadotroph tumors. Conclusions Gonadotroph tumor drive the recruitment of macrophages and their subsequent polarization to an M2-like phenotype. More importantly, the association between infiltrating CD68+/CD163+ macrophages and the invasiveness of gonadotroph tumors points to macrophage-targeted immunotherapies being a potent strategy to limit the progression of gonadotroph PitNETs