a Department of Investigational Cancer Therapeutics , The University of Texas MD Anderson Cancer Center , Houston , TX , USA.
Expert Rev Clin Pharmacol. 2018 Aug;11(8):797-804. doi: 10.1080/17512433.2018.1504677. Epub 2018 Aug 10.
In recent years, the therapeutic management of selected patients with cancer has shifted toward the 'precision medicine' approach based on patient's mechanisms of tumorigenesis, and their baseline characteristics and comorbidities. Complete tumor and cell-free DNA profiling using next-generation sequencing, proteomic and RNA analysis, and immune mechanisms should to be taken into consideration and accurate bioinformatic analysis is essential to optimize patient's treatment. Areas covered: The challenges and opportunities of conducting clinical trials in precision oncology are summarized. Expert commentary: Precision medicine has significantly changed the diagnostic and therapeutic landscape of cancer. Successful implementation of precision medicine requires translational and bioinformatics infrastructure to support optimization of treatment selection. Targeted therapy, immunotherapy, T-cell therapy alone or in combination with cytotoxic or other effective therapeutic strategies and innovative clinical trials with adaptive design should be offered to all patients. Data sharing and 'N-of-1' models hold the promise to optimize the treatment of individual patients and expedite drug approval for rare alterations and tumor types. Artificial intelligence will facilitate accurate utilization of sequencing data to perform algorithm analysis. Collaboration of healthcare providers with pharmaceutical and biotechnical companies, scientific organizations, and governmental regulatory agencies have a crucial role in curing cancer.
近年来，癌症患者的治疗管理已转向基于患者肿瘤发生机制、基线特征和合并症的“精准医学”方法。应考虑使用下一代测序、蛋白质组学和 RNA 分析以及免疫机制进行完整的肿瘤和无细胞 DNA 分析，并进行准确的生物信息学分析以优化患者的治疗。
总结了在精准肿瘤学中进行临床试验的挑战和机遇。
精准医学已极大地改变了癌症的诊断和治疗格局。成功实施精准医学需要转化和生物信息学基础设施，以支持治疗选择的优化。应向所有患者提供靶向治疗、免疫疗法、单独或联合细胞毒性或其他有效治疗策略的 T 细胞疗法，以及具有适应性设计的创新临床试验。数据共享和“N-of-1”模型有望优化个体患者的治疗，并加速批准罕见改变和肿瘤类型的药物。人工智能将有助于准确利用测序数据进行算法分析。医疗保健提供者与制药和生物技术公司、科学组织以及政府监管机构的合作对于治愈癌症具有关键作用。
