Savas Sevtap, Liu Geoffrey
Department of Medical Biophysics, Division of Applied Molecular Oncology, Ontario Cancer Institute, Toronto, Ontario, Canada.
Hum Mutat. 2009 Oct;30(10):1369-77. doi: 10.1002/humu.21078.
Cancer molecular epidemiology traditionally studies the relationship between genetic variations and cancer risk. However, recent studies have also focused on disease outcomes. The application and design of disease outcome studies have been an extension of disease risk assessment. Yet there are a number of unique considerations important in outcome assessments. We review how genetic approaches used for disease susceptibility, such as candidate gene and genome-wide association study (GWAS) approaches, can be adapted carefully to systematically identify cancer prognostic and predictive alleles. We discuss the interrelatedness among the disease susceptibility, treatment response, and prognosis at the genetic level and focus on how the emerging technologies and approaches can uniquely benefit the genetic prognosis studies.
癌症分子流行病学传统上研究基因变异与癌症风险之间的关系。然而，最近的研究也聚焦于疾病结局。疾病结局研究的应用和设计是疾病风险评估的延伸。然而，在结局评估中有一些独特的重要考量因素。我们回顾了用于疾病易感性的基因方法，如候选基因和全基因组关联研究（GWAS）方法，如何能够经过精心调整以系统地识别癌症预后和预测等位基因。我们讨论了在基因层面上疾病易感性、治疗反应和预后之间的相互关联性，并着重探讨新兴技术和方法如何能够为基因预后研究带来独特的益处。
