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基于数据的乳腺癌化学预防剂的识别。

Data-Driven identification of chemopreventive agents for breast cancer.

机构信息

Department of Medical Oncology, Faculty of Medicine, University of Hacettepe, Ankara, Turkey

Department of Animal Nutrition, Faculty of Veterinary Medicine, Fırat University, Elazığ, Turkey

出版信息

Turk J Med Sci. 2020 Nov 3;50(SI-2):1691-1696. doi: 10.3906/sag-2003-138.

Abstract

Preclinical animal models of breast cancer provide the opportunity to identify chemopreventive drugs with single-agent activity as well as effective multi-modality regimens for primary as well as secondary prevention in high-risk persons. Our group has used the 7,12-dimethylbenz(a)anthracene (DMBA) mouse model of carcinogen-induced breast cancer to explore the clinical potential of two tyrosine kinase inhibitors and a nucleoside analog as chemopreventive agents. All three agents exhibited promising preclinical activity both as monotherapy and as components of combination therapy with the standard chemotherapy drug paclitaxel. The tumors developing despite chemoprevention were not only small and grew slowly, but they also displayed a uniquely more pro-apoptotic protein expression profile. Hence, our experimental chemopreventive drugs were capable of preventing the development of aggressive mammary gland tumors with an apoptosis-resistant protein expression profile.

摘要

乳腺癌的临床前动物模型为寻找单一药物活性的化学预防药物以及高危人群一级和二级预防的有效多模式方案提供了机会。我们的研究小组使用 7,12-二甲基苯并(a)蒽(DMBA)诱导的乳腺癌致癌剂小鼠模型,探索了两种酪氨酸激酶抑制剂和一种核苷类似物作为化学预防剂的临床潜力。所有三种药物在单独使用和与标准化疗药物紫杉醇联合使用时都表现出有希望的临床前活性。尽管进行了化学预防,但仍发展成的肿瘤不仅较小且生长缓慢,而且还表现出独特的更促凋亡蛋白表达谱。因此,我们的实验性化学预防药物能够预防具有抗凋亡蛋白表达谱的侵袭性乳腺肿瘤的发展。

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