Lohse Ines, Statz-Geary Kurt, Brothers Shaun P, Wahlestedt Claes
Center for Therapeutic Innovation, Miller School of Medicine, University of Miami, Miami, FL, USA.
Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL, USA.
Oncotarget. 2018 Dec 28;9(102):37790-37797. doi: 10.18632/oncotarget.26492.
Recent advances in high throughput technologies have led to the generation of vast amounts of clinical data and the development of personalized medicine approaches in acute myeloid leukemia (AML). The ability to treat cancer patients based upon their individual molecular characteristics or drug sensitivity profiles is expected to significantly advance cancer treatment and improve the long-term survival of patients with refractory AML, for whom current treatment options are restricted to palliative approaches. The clinical development of omics-based and phenotypic screens, however, is limited by a number of bottlenecks including the generation of cost-effective high-throughput data, data interpretation and integration of multiple approaches, sample availability, clinically relevant timelines, and the development and education of multidisciplinary teams. Recently, a number of small clinical trials have shown survival benefits in patients treated based on personalized medicine approaches. While these preliminary studies are encouraging, larger trials are needed to evaluate the utility of these technologies in routine clinical settings.
高通量技术的最新进展已促使大量临床数据的产生，并推动了急性髓系白血病（AML）个性化医疗方法的发展。基于癌症患者个体分子特征或药物敏感性谱进行治疗的能力，有望显著推进癌症治疗，并提高难治性AML患者的长期生存率，目前这些患者的治疗选择仅限于姑息治疗方法。然而，基于组学和表型筛选的临床开发受到诸多瓶颈的限制，包括具有成本效益的高通量数据的生成、多种方法的数据解读与整合、样本可用性、临床相关的时间线以及多学科团队的发展与培训。最近，一些小型临床试验表明，基于个性化医疗方法治疗的患者有生存获益。虽然这些初步研究令人鼓舞，但仍需要更大规模的试验来评估这些技术在常规临床环境中的效用。
