CD163 + Tumor-Associated Macrophage Recruitment Predicts Papillary Thyroid Cancer Recurrence.

Introduction: Skewed immune response plays a pivotal role in tumor progression. Systemic inflammatory responses represented by combined peripheral leukocyte fractions are prognostic predictors of multiple cancers, including thyroid cancer. We previously reported the prognostic significance of lymphocyte-to-monocyte ratio (LMR) in curatively resected papillary thyroid cancer (PTC). Therefore, this study aimed to analyze immune cell profiles in the tumor microenvironment and their association with LMR in curatively resected PTC.
Materials and Methods: The immune cell profiles of primary tumors in 162 patients with curatively resected PTC were analyzed clinicopathologically. Immunohistochemistry of tumor-associated macrophages (TAMs), myeloid-derived suppressor cells, and lymphocytes was performed using CD163, CD33, and CD3 antibodies, respectively. Prognostic analysis and correlation assays were performed using the immunocyte profiles. The gene expression of tumor-derived chemokines was assessed using a The Cancer Genome Atlas database.
Results: Patients with a higher density of CD163 ⁺ TAMs exhibited a significantly worse prognosis than their counterparts (10-y recurrence-free survival: 80.9% versus 91.2%, P = 0.011). Multivariate prognostic analyses revealed that high CD163 ⁺ cell density (P = 0.011), low preoperative LMR (P = 0.003), pN1b (P = 0.005), and high thyroglobulin level (P = 0.038) were independent predictors of recurrence. High CD163 ⁺ cell density had a prognostic impact on stage II and III PTC. Interestingly, high CD163 ⁺ cell density correlated with low LMR and high monocyte fraction in peripheral blood. Indeed, the expression of TAM-inducible, tumor-derived chemokines is increased in the The Cancer Genome Atlas database.
Conclusions: A high density of infiltrated CD163 ⁺ TAMs predicts recurrence in correlation with low LMR and circulating monocyte accumulation. Thus, TAMs should be considered when assessing advanced PTC.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)