Hackman G Lavender, Collins Meghan, Lu Xiyuan, Lodi Alessia, DiGiovanni John, Tiziani Stefano
Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA.
Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA.
Cancers (Basel). 2020 Dec 10;12(12):3714. doi: 10.3390/cancers12123714.
Natural products have been used for centuries to treat various human ailments. In recent decades, multi-drug combinations that utilize natural products to synergistically enhance the therapeutic effects of cancer drugs have been identified and have shown success in improving treatment outcomes. While drug synergy research is a burgeoning field, there are disagreements on the definitions and mathematical parameters that prevent the standardization and proper usage of the terms synergy, antagonism, and additivity. This contributes to the relatively small amount of data on the antagonistic effects of natural products on cancer drugs that can diminish their therapeutic efficacy and prevent cancer regression. The ability of natural products to potentially degrade or reverse the molecular activity of cancer therapeutics represents an important but highly under-emphasized area of research that is often overlooked in both pre-clinical and clinical studies. This review aims to evaluate the body of work surrounding the antagonistic interactions between natural products and cancer therapeutics and highlight applications for high-throughput screening (HTS) and deep learning techniques for the identification of natural products that antagonize cancer drug efficacy.
几个世纪以来，天然产物一直被用于治疗各种人类疾病。近几十年来，已发现利用天然产物协同增强抗癌药物治疗效果的多药组合，并已在改善治疗结果方面取得成功。虽然药物协同作用研究是一个新兴领域，但在定义和数学参数方面存在分歧，这阻碍了协同、拮抗和相加等术语的标准化和正确使用。这导致关于天然产物对癌症药物的拮抗作用的数据相对较少，这些拮抗作用会降低其治疗效果并阻止癌症消退。天然产物潜在地降解或逆转癌症治疗药物分子活性的能力是一个重要但未得到充分重视的研究领域，在临床前和临床研究中常常被忽视。本综述旨在评估围绕天然产物与癌症治疗药物之间拮抗相互作用的研究工作，并强调高通量筛选（HTS）和深度学习技术在识别拮抗癌症药物疗效的天然产物方面的应用。
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