BACKGROUND: Programmed death-ligand 1 (PD-L1) expression has been reported in several malignancies, but the expression of PD-L1 in papillary thyroid cancer (PTC) has been characterized rarely. The aim of this study was to assess the significance of PD-L1 expression and its associations with clinicopathologic factors and disease outcome in PTC. METHODS: Immunohistochemistry staining was conducted retrospectively to evaluate the expression of PD-L1 in a total of 260 PTC tumors and corresponding non-tumor tissues. The correlations between PD-L1 expressions with clinicopathologic features and recurrence-free survival (RFS) were analyzed. RESULTS: PD-L1 expression was positive in 52.3% (136/260) of PTC tumor tissues, which was significantly higher than in corresponding non-tumor thyroid tissues. In clinicopathologic analyses, this positive staining of PD-L1 was positively linked to multifocality (p = 0.001) and extrathyroidal extension (p = 0.001). In multivariate Cox regression analysis, positive PD-L1 expression in tumor tissue was significantly associated with worse RFS (hazard ratio 2.825 [confidence interval 1.149-6.943], p = 0.024). In subgroup analyses based on clinicopathologic factors, positive PD-L1 staining of tumor tissue was associated with worse RFS in males (p = 0.001), older patients (≥45 years; p = 0.001), and patients with a primary tumor size >4 cm (p = 0.002), multifocal tumors (p = 0.031), extrathyroidal extension (p = 0.012), and lymph node metastasis (p = 0.004). In contrast, positive PD-L1 staining predicted worse RFS in the subgroup of patients without Hashimoto's thyroiditis (p = 0.001) and treated with total thyroidectomy (p = 0.019). CONCLUSIONS: PD-L1 is important in determining aggressiveness of PTC and could predict the prognosis of patients. Therefore, inhibition of PD-L1 is suggested as a potential strategy for the treatment of advanced PTC with high expression of PD-L1.
BACKGROUND:Programmed death-ligand 1 (PD-L1) expression has been reported in several malignancies, but the expression of PD-L1 in papillary thyroid cancer (PTC) has been characterized rarely. The aim of this study was to assess the significance of PD-L1 expression and its associations with clinicopathologic factors and disease outcome in PTC. METHODS: Immunohistochemistry staining was conducted retrospectively to evaluate the expression of PD-L1 in a total of 260 PTCtumors and corresponding non-tumor tissues. The correlations between PD-L1 expressions with clinicopathologic features and recurrence-free survival (RFS) were analyzed. RESULTS:PD-L1 expression was positive in 52.3% (136/260) of PTCtumor tissues, which was significantly higher than in corresponding non-tumor thyroid tissues. In clinicopathologic analyses, this positive staining of PD-L1 was positively linked to multifocality (p = 0.001) and extrathyroidal extension (p = 0.001). In multivariate Cox regression analysis, positive PD-L1 expression in tumor tissue was significantly associated with worse RFS (hazard ratio 2.825 [confidence interval 1.149-6.943], p = 0.024). In subgroup analyses based on clinicopathologic factors, positive PD-L1 staining of tumor tissue was associated with worse RFS in males (p = 0.001), older patients (≥45 years; p = 0.001), and patients with a primary tumor size >4 cm (p = 0.002), multifocal tumors (p = 0.031), extrathyroidal extension (p = 0.012), and lymph node metastasis (p = 0.004). In contrast, positive PD-L1 staining predicted worse RFS in the subgroup of patients without Hashimoto's thyroiditis (p = 0.001) and treated with total thyroidectomy (p = 0.019). CONCLUSIONS:PD-L1 is important in determining aggressiveness of PTC and could predict the prognosis of patients. Therefore, inhibition of PD-L1 is suggested as a potential strategy for the treatment of advanced PTC with high expression of PD-L1.
Authors: Matthew W Rosenbaum; Benjamin J Gigliotti; Sara I Pai; Sareh Parangi; Heather Wachtel; Mari Mino-Kenudson; Viswanath Gunda; William C Faquin Journal: Endocr Pathol Date: 2018-03 Impact factor: 3.943
Authors: Ramy R Saleh; Jordan L Scott; Nicholas Meti; Danielle Perlon; Rouhi Fazelzad; Alberto Ocana; Eitan Amir Journal: Mol Diagn Ther Date: 2022-02-01 Impact factor: 4.074