Expression of TLR4 in Non-Small Cell Lung Cancer Is Associated with PD-L1 and Poor Prognosis in Patients Receiving Pulmonectomy

非小细胞肺癌中 TLR4 的表达与 PD-L1 及肺切除术患者预后不良相关

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作者:Kaiyuan Wang, Jian Wang, Feng Wei, Ning Zhao, Fan Yang, Xiubao Ren

Abstract

Currently, the effect of inflammation on tumorigenesis and progression has been widely noted. As a member of pattern recognition receptors, toll-like receptor 4 (TLR4) plays a pivotal role in tumor immune microenvironment and has been increasingly investigated. In the present study, we evaluated TLR4 expression and its association with programmed cell death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC) tissues and assessed the predicting value of TLR4 on postoperative outcome. A total of 126 NSCLC patients receiving complete pulmonary resection and systematic lymph node dissection between April 2008 and August 2014 were enrolled. All the patients had integrated clinicopathological records and follow-up data. TLR4 and PD-L1 expression on NSCLC samples were determined by immunohistochemistry, and serum soluble TLR4 (sTLR4) levels were measured by enzyme-linked immunosorbent assay. Results showed that TLR4 expression level in cancer tissue was significantly higher than that in para-cancer tissue. Elevated TLR4 expression was significantly associated with histological type (adenocarcinoma higher than squamous cell carcinoma, P = 0.041), increased clinical TNM stage (P < 0.001), and presence of lymphatic invasion (P < 0.001). Besides, TLR4 expression level in cancer samples was inversely correlated with serum sTLR4 level in patients with early-stage NSCLC (r = -0.485, P = 0.003). TLR4 expression level was also positively correlated with the PD-L1 expression level (r = 0.545, P < 0.0001). Multivariate analysis showed that expression level of TLR4 was an independent prognostic factor and TLR4 overexpression indicated a poor overall survival and disease-free survival. Taken together, we conclude that expression of TLR4 in lung cancer is associated with PD-L1 and could predict the outcome of patients with NSCLC receiving pulmonary resection for cancer.

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