Expression of Hypoxia-Associated Protein HIF-1α in Follicular Thyroid Cancer is Associated with Distant Metastasis

Abstract

Follicular thyroid carcinomas (FTCs) are the second most common malignant neoplasia of the thyroid and in general its prognosis is quite favorable. However, the occurrence of metastases or non-responsiveness to radioiodine therapy worsens the prognosis considerably. We evaluated immunohistochemically the expression of hypoxia-associated proteins by hypoxia-induced factor 1α (HIF-1α), the stroma-remodeling marker Tenascin C, as well as markers for the epithelial-mesenchymal transition (EMT), namely E-cadherin and slug in a series of 59 sporadic FTCs. In addition, various clinicopathologic parameters were assessed like TNM-staging, age, tumor size as well as tumor characteristics like desmoplasia, necrosis, and calcification. Overexpression of HIF-1α was seen in 29 of 59 tumors (49.2%) including 21 (35.6%) FTC with strong expression of tumor cell groups. HIF-1α correlated significantly with metastasis (p < 0.001; Mann-Whitney U test), degree of desmoplasia (p = 0.042, Kruskal-Wallis test), tenascin C expression (p = 0.042, Kruskal-Wallis test), calcification (p < 0.025, Kruskal–Wallis test), necrosis (p = 0.002), age (p = 0.011, Kruskal-Wallis test) and tumor stage UICC (p = 0.022, Kruskal-Wallis test). Furthermore, metastasis was associated with the degree of desmoplasia (p = 0.014; Fisher's exact test), calcification (p = 0.008, Fisher's exact test), necrosis (p = 0.042, Fisher's exact test), tumor size (p = 0.015, Mann-Whitney U test), and age (p = 0.001, Mann-Whitney U test). In a Cox proportional hazards model, only metastasis remained as an independent risk factor for overall survival (hazard rate: 10.2 [95% CI, 02.19 to 47.26]; p = 0.003). Our data suggest that HIF-1α plays a critical role in the remodeling of the extracellular matrix as well as metastasizing process of follicular thyroid carcinoma and targeting hypoxia-associated and -regulated proteins may be considered as potential targets for personalized medicine.

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