蛋白质组学在肺癌相关标志物挖掘中的应用  

The application of proteomics in lung cancer related biomarkers in data mining

作　　者：梁委军[1] 覃世逆[1] 袁天柱[1] 戴盛明[1] LIANG Weijun QIN Shini YUAN Tianzhu DAI Shengming(Liuzhou Key Laboratory of Tumor Diseases and Prevention, Clinical Laboratory, Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, China, 54500)

机构地区：[1]广西医科大学第四附属医院医学检验科柳州市肿瘤疾病与防治重点实验室,广西柳州545005

出　　处：《分子诊断与治疗杂志》2017年第4期289-292,共4页Journal of Molecular Diagnostics and Therapy

基　　金：广西柳州市科技局科技创新能力与条件建设资助项目(2014G020403)

摘　　要：肺癌是全球发病率和死亡率最高的恶性肿瘤,其5年生存率仅为15%,但早期诊断出的肺癌患者5年生存率可达52%。缺乏早期诊断及有效治疗手段使得肺癌的死亡率很高。因此,寻找新的早期诊断和预后标志物为治疗打开新途径迫在眉睫。蛋白质组学技术具有足够的灵敏度,特异性和可重复性,它正成为肺癌生物标志物和治疗靶点研究的一个重要工具。本文就近年来肺癌的蛋白质组学研究进展包括肺癌的预防、早期诊断和治疗方法等进行综述。Lung cancer is the most common cause of cancer death over the world,with a 5-year survival rate of 15%,and with a 5-year survival rate of 85% by early diagnosis.The high mortality from lung cancer is due not only to the lack of early diagnosis but also to the lack of effective treatments.Therefore,there is an urgent need to find new markers for early diagnosis and prognosis that could serve to open novel therapeutic avenues.Having adequate sensitivity,specificity,and reproducibility,proteomics is becoming an important tool for the identification of biomarkers and therapeutic targets for lung cancer.In this article,the latest reports in proteomic studies of lung cancer will briefly introduced.It contains the identification of new diagnostic,prognostic,and predictive markers for lung cancer,using proteomics technologies.

关 键 词：肺癌 蛋白质组学 肿瘤标志物 

分 类 号：R730.43[医药卫生—肿瘤] R734.2[医药卫生—临床医学]