Meerzaman Daoud, Dunn Barbara K, Lee Maxwell, Chen Qingrong, Yan Chunhua, Ross Sharon
Center for Biomedical Informatics & Information Technology, Computational Genomics and Bioinformatics Group, National Cancer Institute, National Institutes of Health, Rockville, MD 20852, USA.
Chemoprevention Agent Development Research Group, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Semin Oncol. 2016 Feb;43(1):36-48. doi: 10.1053/j.seminoncol.2015.09.004. Epub 2015 Sep 8.
Cancer is a complex category of diseases caused in large part by genetic or genomic, transcriptomic, and epigenetic or epigenomic alterations in affected cells and the surrounding microenvironment. Carcinogenesis reflects the clonal expansion of cells that progressively acquire these genetic and epigenetic alterations-changes that, in turn, lead to modifications at the RNA level. Gradually advancing technology and most recently, the advent of next-generation sequencing (NGS), combined with bioinformatics analytic tools, have revolutionized our ability to interrogate cancer cells. The ultimate goal is to apply these high-throughput technologies to the various aspects of clinical cancer care: cancer-risk assessment, diagnosis, as well as target identification for treatment and prevention. In this article, we emphasize how the knowledge gained through large-scale omics-oriented approaches, with a focus on variations at the level of nucleic acids, can inform the field of chemoprevention.
癌症是一类复杂的疾病,在很大程度上由受影响细胞及其周围微环境中的基因或基因组、转录组以及表观遗传或表观基因组改变所引起。致癌作用反映了细胞的克隆性扩增,这些细胞逐渐获得这些基因和表观遗传改变,而这些改变反过来又会导致RNA水平的修饰。技术的不断进步,以及最近下一代测序(NGS)的出现,再加上生物信息学分析工具,彻底改变了我们研究癌细胞的能力。最终目标是将这些高通量技术应用于临床癌症护理的各个方面:癌症风险评估、诊断以及治疗和预防的靶点识别。在本文中,我们强调通过大规模的组学导向方法所获得的知识,特别是关注核酸水平的变异,如何能够为化学预防领域提供信息。
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