Laboratory of Cancer Biology, Department of Clinical Pharmacology, University of Oxford, Old Road Campus Research Building, Old Road Campus, Oxford OX3 7DQ, UK.
Nat Rev Clin Oncol. 2011 Aug 23;8(10):587-96. doi: 10.1038/nrclinonc.2011.121.
Advances in our understanding of the intricate molecular mechanisms for transformation of a normal cell to a cancer cell, and the aberrant control of complementary pathways, have presented a much more complex set of challenges for the diagnostic and therapeutic disciplines than originally appreciated. The oncology field has entered an era of personalized medicine where treatment selection for each cancer patient is becoming individualized or customized. This advance reflects the molecular and genetic composition of the tumors and progress in biomarker technology, which allow us to align the most appropriate treatment according to the patient's disease. There is a worldwide acceptance that advances in our ability to identify predictive biomarkers and provide them as companion diagnostics for stratifying and subgrouping patients represents the next leap forward in improving the quality of clinical care in oncology. As such, we are progressing from a population-based empirical 'one drug fits all' treatment model, to a focused personalized approach where rational companion diagnostic tests support the drug's clinical utility by identifying the most responsive patient subgroup.
我们对正常细胞向癌细胞转化的复杂分子机制以及互补途径的异常控制的理解的进步，给诊断和治疗学科带来了比最初预期更为复杂的一系列挑战。肿瘤学领域已经进入了个性化医疗时代，每个癌症患者的治疗选择都变得个体化或定制化。这一进展反映了肿瘤的分子和遗传组成以及生物标志物技术的进步，使我们能够根据患者的疾病选择最合适的治疗方法。人们普遍认为，我们识别预测性生物标志物的能力的提高，并将其作为伴随诊断用于分层和亚组患者，代表了提高肿瘤学临床护理质量的下一个飞跃。因此，我们正在从基于人群的经验性“一种药物适合所有人”的治疗模式向以患者为中心的个性化方法转变，合理的伴随诊断测试通过确定最有反应的患者亚组来支持药物的临床实用性。
