组学
医学
个性化医疗
蛋白质组学
基因组学
疾病
癌症
数据科学
个性化
医学研究
生物信息学
精密医学
计算生物学
计算机科学
病理
生物
内科学
基因组
基因
万维网
生物化学
作者
Min-qiang Lu,Xianquan Zhan
出处
期刊:The Epma Journal
[Springer Nature]
日期:2018-02-21
卷期号:9 (1): 77-102
被引量:179
标识
DOI:10.1007/s13167-018-0128-8
摘要
Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different "omics" technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.
科研通智能强力驱动
Strongly Powered by AbleSci AI