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Association of cytokines levels with epidermal growth factor receptor mutation in lung cancer patients

腺癌 医学 表皮生长因子受体 肺癌 内科学 细胞因子 癌症研究 突变 癌症 肿瘤科 基因型 表皮生长因子 受体 生长因子受体 胃肠病学 外显子
作者
Sandeep Bhattacharya,Priyanka Gaur,Surya Kant,RA. S. Kushwaha,Gaurav Singh,Sarika Pandey
出处
期刊:Journal of Cancer Research and Therapeutics [BioMed Central]
卷期号:16 (4): 811-811 被引量:6
标识
DOI:10.4103/jcrt.jcrt_632_18
摘要

BACKGROUND: Lung cancer is one of the most frequent types of cancer and the leading cause of cancer-related deaths. Epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (TK) being highly expressed in lung cancers. Activation of EGFR through oncogenic mutations leads to upregulation of gene expression that may heighten the inflammatory response in certain situations. EGFR acts as a key regulator and a cellular hub for inflammatory cytokine signaling, thereby promoting tumor cell proliferation, invasion, migration, metastases, and survival. The aim of the present study is to determine the serum cytokines levels and EGFR mutation status in lung cancer patients to investigate the association between the EGFR mutation status and cytokines levels with lung cancer patients. MATERIALS AND METHODS: Blood and tissue samples of lung cancer patients were collected. The EGFR mutations of lung cancer patients were determined by the immunohistochemistry (IHC) and serum cytokines levels of lung cancer patients were determined using ELISA. RESULTS: Statistically significant association of EGFR mutations with adenocarcinoma subtypes and non-smokers were found (P < 0.05). Lung cancer patients with EGFR mutations had significantly higher tumor necrosis factor-alpha levels when compared to lung cancer patients without EGFR mutations (P < 0.01), and EGFR mutation status was not significantly associated with interleukin-6 levels (P = 0.24). CONCLUSION: EGFR mutation detection by the IHC method is a potentially useful tool to guide clinicians for personalized treatment of lung cancer patients of adenocarcinoma subtype, and cytokines are good biomarkers for the diagnosis, prognosis, and prediction of treatment responses in lung cancer patients as well as act as therapeutic targets. This study will provide biomarkers for lung cancer diagnosis and treatments.

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