Correlation of tumor microenvironment-related markers with clinical outcomes in patients with squamous cell carcinoma of the lung

肺鳞状细胞癌患者肿瘤微环境相关标志物与临床结局的相关性研究

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Abstract

BACKGROUND: Squamous cell carcinoma (SCC) is the major histological type in lung cancer (LC). The tumor microenvironment (TME) drives tumor progression and metastasis. In the TME, cancer-associated fibroblasts (CAFs) play key roles in carcinogenesis. However, the roles of CAFs in lung SCC remain unknown. In this study, we evaluated whether the CAF phenotype was determined by various CAF-related proteins and whether CAF-related protein expression contributed to clinical outcomes in patients with lung SCC. METHODS: We examined the associations of CAF- and epithelial-mesenchymal transition (EMT)-related markers expressed in CAFs, including α-smooth muscle actin (α-SMA), CD10, podoplanin, fibroblast-specific protein 1 (FSP1), platelet-derived growth factor receptor (PDGFR) α, PDGFRβ, adipocyte enhancer-binding protein 1 (AEBP1), fibroblast activation protein (FAP), tenascin-C, Zinc finger E-box binding homeobox 1 (ZEB1), and twist homolog 1 gene (TWIST1), in 108 lung SCC tissues using immunohistochemistry. In addition, cluster analysis was used to identify objective expression patterns of immunohistochemical markers. Finally, the CD3/CD8 ratio was evaluated in order to identify the associations of CAF-related proteins with the CD3/CD8 ratio using immunohistochemistry. RESULTS: SCC samples were classified into two subgroups (CAF-phenotype), which were significantly correlated with disease-free and overall survival using univariate and multivariate analyses. Moreover, high AEBP1 expression was identified as an independent prognostic marker in this cohort by univariate and multivariate analyses. The CD3/CD8 ratio was not correlated with the CAF-phenotype. CONCLUSIONS: The presence of a specific subgroup defined by multiple markers could be used for prediction of prognosis in patients with lung SCC. In addition, AEBP1 overexpression played key roles in prediction of a poor prognosis in patients with lung SCC.

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