Department of Dermatology, Yale School of Medicine, New Haven, Connecticut, USA; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Department of Dermatology, Yale School of Medicine, New Haven, Connecticut, USA.
J Invest Dermatol. 2020 Dec;140(12):2319-2325.e1. doi: 10.1016/j.jid.2020.09.020.
The identification and application of targeted therapies that inhibit critical pathways in malignant cells have shown tremendous promise for improving clinical outcomes for patients with advanced cutaneous malignancies. However, tumor cell heterogeneity, development of drug resistance, and risks of off-target effects remain barriers to prolonged remission and definitive cure. Herein, we describe the potential that combinations of antitumor targeted agents may offer in overcoming these challenges and detail techniques whereby promising combination regimens can be identified and further evaluated preclinically. Cancer cell lines and primary patient-derived malignant cells can be utilized to perform dose-response screenings in vitro for individual targeted agents before moving toward the evaluation of potential synergistic combinations. Mathematical analyses, including the Chou-Talalay method, determine combination indices and Hill slopes that permit relative comparisons among various drug combinations by quantification of synergistic activities. Further preclinical in vivo evaluation of promising single versus combination regimens may be studied in relevant mouse models of cutaneous malignancy. Ultimately, the formulation of combination targeted therapy regimens may be more broadly effective and less toxic, helping to better inform clinical trial design and prioritization.
针对恶性细胞中关键途径的靶向治疗药物的鉴定和应用,为改善晚期皮肤恶性肿瘤患者的临床疗效带来了巨大的希望。然而,肿瘤细胞异质性、耐药性的发展以及脱靶效应的风险仍然是延长缓解和根治的障碍。在此,我们描述了抗肿瘤靶向药物联合应用可能克服这些挑战的潜力,并详细介绍了如何识别和在临床前进一步评估有前途的联合方案的技术。可以使用癌细胞系和原发性患者来源的恶性细胞,在进行潜在协同组合的评估之前,在体外对单个靶向药物进行剂量反应筛选。包括 Chou-Talalay 方法在内的数学分析确定了组合指数和 Hill 斜率,通过对协同作用的定量分析,允许对各种药物组合进行相对比较。在皮肤恶性肿瘤的相关小鼠模型中,可以进一步研究有前途的单药与联合方案的临床前体内评估。最终,联合靶向治疗方案的制定可能会更广泛地有效且毒性更小,有助于更好地为临床试验设计和优先级提供信息。