The University of Texas MD Anderson Cancer Center, Department of Investigational Cancer Therapeutics, Houston, TX.
Department of Medical Oncology, Euromedica General Clinic, Thessaloniki, Greece.
Cancer Treat Rev. 2020 Jun;86:102019. doi: 10.1016/j.ctrv.2020.102019. Epub 2020 Mar 31.
In recent years, biotechnological breakthroughs have led to identification of complex and unique biologic features associated with carcinogenesis. Tumor and cell-free DNA profiling, immune markers, and proteomic and RNA analyses are used to identify these characteristics for optimization of anticancer therapy in individual patients. Consequently, clinical trials have evolved, shifting from tumor type-centered to gene-directed, histology-agnostic, with innovative adaptive design tailored to biomarker profiling with the goal to improve treatment outcomes. A plethora of precision medicine trials have been conducted. The majority of these trials demonstrated that matched therapy is associated with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To improve the implementation of precision medicine, this approach should be used early in the course of the disease, and patients should have complete tumor profiling and access to effective matched therapy. To overcome the complexity of tumor biology, clinical trials with combinations of gene-targeted therapy with immune-targeted approaches (e.g., checkpoint blockade, personalized vaccines and/or chimeric antigen receptor T-cells), hormonal therapy, chemotherapy and/or novel agents should be considered. These studies should target dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones that confer resistance to treatment. Mining and expansion of real-world data, facilitated by the use of advanced computer data processing capabilities, may contribute to validation of information to predict new applications for medicines. In this review, we summarize the clinical trials and discuss challenges and opportunities to accelerate the implementation of precision oncology.
近年来,生物技术的突破导致了与致癌作用相关的复杂而独特的生物特征的识别。肿瘤和无细胞 DNA 分析、免疫标志物以及蛋白质组学和 RNA 分析用于鉴定这些特征,以优化个体患者的抗癌治疗。因此,临床试验已经发展,从以肿瘤类型为中心转变为以基因为导向、组织学上不可知的治疗,采用创新的适应性设计,根据生物标志物分析进行定制,目标是改善治疗效果。已经进行了大量的精准医学试验。这些试验中的大多数表明,与非匹配治疗相比,匹配治疗在肿瘤类型和特定癌症中均与更好的结果相关。为了提高精准医学的实施效果,这种方法应该在疾病的早期阶段使用,并且患者应该进行完整的肿瘤分析,并获得有效的匹配治疗。为了克服肿瘤生物学的复杂性,应考虑联合基因靶向治疗与免疫靶向方法(例如,检查点阻断、个性化疫苗和/或嵌合抗原受体 T 细胞)、激素治疗、化疗和/或新型药物的临床试验。这些研究应针对肿瘤生物学异常的动态变化,消除微小残留疾病,并消除对治疗产生耐药性的显著亚克隆。通过利用先进的计算机数据处理能力,挖掘和扩展真实世界的数据,可能有助于验证信息,以预测药物的新应用。在这篇综述中,我们总结了临床试验,并讨论了加速精准肿瘤学实施的挑战和机遇。