application of biomarkers in cancer risk management evaluation from stochastic clonal evolutionary and dynamic system optimization points of view生物标志物应用于癌症风险管理评估随机克隆进化和动态系统优化的观点.pdf

Perspective Application of Biomarkers in Cancer Risk Management: Evaluation from Stochastic Clonal Evolutionary and Dynamic System Optimization Points of View 1 1,2 1,3 1,2,4,5 Xiaohong Li *, Patricia L. Blount , Thomas L. Vaughan , Brian J. Reid 1 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, University of Washington, Seattle, Washington, United States of America, 2 Department of Medicine, University of Washington, Seattle, Washington, United States of America, 3 Department of Epidemiology, University of Washington, Seattle, Washington, United States of America, 4 Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America, 5 Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America Abstract: Aside from primary pre- Introduction identified many molecular abnormalities vention, early detection remains that develop during neoplastic progres- the most effective way to decrease Detection of cancer at an early stage sion, some of which are highly associated mortality associated with the ma- could significantly reduce cancer mortality with cancer [7–10]. Currently, there is a jority of solid cancers. Previous and the overall burden of cancer [1–4]. quest to find the perfect cancer biomark- cancer screening models are largely The most common cancer risk model is er(s) that could be used to separate based on classification of at-ris