Wu Duojiao, Wang Xiangdong
Zhongshan Hospital of Fudan University, Biomedical Research Center, Shanghai Institute of Clinical Bioinformatics, Fucan University Center for Clinical Bioinformatics, Shanghai, 200032, China.
Cancer Metastasis Rev. 2015 Jun;34(2):209-16. doi: 10.1007/s10555-015-9564-2.
The fact that lung cancer is a heterogeneous disease suggests that there is a high likelihood that effective lung cancer biomarkers will need to address patient-specific molecular defects, clinical characters, and aspects of the tumor microenvironment. In this transition, clinical bioinformatics tools and resources are the most appropriate means to improve the analysis, as major biological databases are now containing clinical data alongside genomics, proteomics, and other biological data. Clinical bioinformatics comprises a series of concepts and approaches that have been used successfully both to delineate novel biological mechanisms and to drive translational advances in individualized healthcare. In this article, we outline several of emerging clinical bioinformatics-based strategies as they apply specifically to lung cancer.
肺癌是一种异质性疾病，这一事实表明，有效的肺癌生物标志物很可能需要针对患者特定的分子缺陷、临床特征以及肿瘤微环境的各个方面。在这一转变过程中，临床生物信息学工具和资源是改善分析的最合适手段，因为主要的生物数据库现在除了包含基因组学、蛋白质组学和其他生物学数据外，还包含临床数据。临床生物信息学包含一系列概念和方法，这些概念和方法已成功用于阐明新的生物学机制以及推动个性化医疗的转化进展。在本文中，我们概述了几种基于临床生物信息学的新兴策略，这些策略特别适用于肺癌。
