Suppr超能文献

维甲酸受体:乳腺癌细胞系中增殖抑制和凋亡诱导的途径

Retinoid receptors: pathways of proliferation inhibition and apoptosis induction in breast cancer cell lines.

作者信息

Raffo P, Emionite L, Colucci L, Belmondo F, Moro M G, Bollag W, Toma S

机构信息

Pre-clinical Oncology Laboratory, Advanced Biotechnology Center (ABC), Genoa, Italy.

出版信息

Anticancer Res. 2000 May-Jun;20(3A):1535-43.

Abstract

In this study we investigated the effects of several selective agonist retinoids (specific for RAR alpha, RAR beta, RAR gamma, and RXR alpha, respectively) on the proliferation and apoptosis of human breast cancer cell lines. All these retinoids inhibit proliferation through apoptosis induction, but with some differences among the tested molecules and the three cell lines. In particular, estrogen receptor positive (ER+) cells display a higher sensitivity to RARs selective compounds, the RAR alpha selective compound being the most effective agent, while estrogen receptor negative (ER-) cells show a greater responsiveness to the RXR alpha selective retinoid. In all tested cell lines a potent antiproliferative and apoptotic effect was also displayed by a high dose of the RAR gamma selective compound. The apoptosis induction is associated with bcl-2 down-regulation, while p53 expression is not modified by any retinoid. Only in one cell line (ZR-75.1), after RAR alpha selective retinoid treatment is there an induction of RAR beta: therefore not only RAR beta induction but also other mechanisms may contribute to the growth inhibitory effect of retinoids in tested breast cancer cell lines.

摘要

在本研究中,我们研究了几种选择性激动剂类视黄醇(分别对RARα、RARβ、RARγ和RXRα具有特异性)对人乳腺癌细胞系增殖和凋亡的影响。所有这些类视黄醇均通过诱导凋亡来抑制增殖,但在所测试的分子和三种细胞系之间存在一些差异。具体而言,雌激素受体阳性(ER+)细胞对RARs选择性化合物表现出更高的敏感性,其中RARα选择性化合物是最有效的药物,而雌激素受体阴性(ER-)细胞对RXRα选择性类视黄醇表现出更大的反应性。在所有测试的细胞系中,高剂量的RARγ选择性化合物也表现出强大的抗增殖和凋亡作用。凋亡诱导与bcl-2下调相关,而p53表达不受任何类视黄醇的影响。仅在一种细胞系(ZR-75.1)中,经RARα选择性类视黄醇处理后会诱导RARβ:因此,不仅RARβ诱导,其他机制也可能有助于类视黄醇对测试乳腺癌细胞系的生长抑制作用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验