Abstract
Background: Although the impact of tumor-immune infiltrate has been reported on differentiated thyroid cancer (DTC) behavior, the expression of immune checkpoints [programmed cell death protein 1 (PD-1) and its ligand (PD-L1)] alone has not been able to predict response to immunotherapies. We aimed to identify tumor-infiltrating immune cells and checkpoints associated with DTC. Methods: We performed multiplex immunofluorescence on deparaffinized thyroid tissue collected at thyroidectomy from 17 adults with DTC to characterize the tumor immune microenvironment for leukocytes (CD45+), T cells (CD3+), T regulatory cells (Tregs) (CD3+FOXP3+), CD4(+) T cells (CD3+CD4(+)), CD8+ T cells (CD3+CD8+), macrophages (CD68+), M2 macrophages (CD68+CD163+), M1 Macrophages (CD68+ inducible nitric oxide synthase [iNOS]+), and immune checkpoints PD-1 and PD-L1. We compared the mean percentage expression of immune markers between tumor and adjacent thyroid tissue from the same patient by paired t-test and performed spatial analysis along the tumor's leading edge. Results: Immune checkpoints PD-1 and PD-L1 showed a significant increase in expression intratumorally as compared to adjacent thyroid tissue (p < 0.05). A higher trend for M2 macrophages was observed intratumorally compared to adjacent tissue. Along the leading edge, PD-L1 expression correlated negatively with CD45 and positively with CD163 intratumorally. On exploratory analysis, there was a nonsignificant trend for higher FOXP3 but less CD8 and iNOS expression in tumor from DTC with (n = 3) versus without distant metastases (n = 14). There was a nonsignificant trend for higher CD58 and iNOS expression in DTC with (n = 7) than without thyroiditis (n = 10). Conclusions: Higher tumoral PD-1 and PD-L1 expression indicate their role in DTC occurrence. A trend for more Tregs and M2 macrophages but less M1 macrophages intratumorally in patients with distant metastatic DTC, suggests their potential role as prognostic biomarkers. Future studies with larger sample sizes are needed to compare various clinicopathologic severities to harness tumor microenvironment for cancer prognostication and therapy.