Suppr超能文献

靶向乳腺癌起始细胞的层层 siRNA 纳米载体的设计与体外评价。

Design and in vitro evaluation of layer by layer siRNA nanovectors targeting breast tumor initiating cells.

机构信息

Department of Nanomedicine, Houston Methodist Research Institute, Houston, Texas, United States of America.

Cancer Center of Excellence, Houston Methodist Research Institute, Houston, Texas, United States of America.

出版信息

PLoS One. 2014 Apr 2;9(4):e91986. doi: 10.1371/journal.pone.0091986. eCollection 2014.

Abstract

Efficient therapeutics and early detection has helped to increase breast cancer survival rates over the years. However, the recurrence of breast cancer remains to be a problem and this may be due to the presence of a small population of cells, called tumor initiating cells (TICs). Breast TICs are resistant to drugs, difficult to detect, and exhibit high self-renewal capabilities. In this study, layer by layer (LBL) small interfering RNA (siRNA) nanovectors (SNVs) were designed to target breast TICs. SNVs were fabricated using alternating layers of poly-L-lysine and siRNA molecules on gold (Au) nanoparticle (NP) surfaces. The stability, cell uptake, and release profile for SNVs were examined. In addition, SNVs reduced TIC-related STAT3 expression levels, CD44+/CD24-/EpCAM+ surface marker levels and the number of mammospheres formed compared to the standard transfection agent. The data from this study show, for the first time, that SNVs in LBL assembly effectively delivers STAT3 siRNA and inhibit the growth of breast TICs in vitro.

摘要

多年来,有效的治疗方法和早期检测帮助提高了乳腺癌的存活率。然而,乳腺癌的复发仍然是一个问题,这可能是由于存在一小部分称为肿瘤起始细胞(TICs)的细胞。乳腺 TICs 对药物有抵抗力,难以检测,并表现出高自我更新能力。在这项研究中,设计了层层(LBL)小干扰 RNA(siRNA)纳米载体(SNVs)来靶向乳腺 TICs。SNVs 是通过在金(Au)纳米颗粒(NP)表面交替层状的聚-L-赖氨酸和 siRNA 分子来制造的。研究了 SNVs 的稳定性、细胞摄取和释放特性。此外,与标准转染试剂相比,SNVs 降低了 TIC 相关 STAT3 表达水平、CD44+/CD24-/EpCAM+表面标记物水平和形成的乳腺球体数量。本研究首次表明,LBL 组装中的 SNVs 可有效递送 STAT3 siRNA 并抑制体外乳腺 TIC 的生长。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a50/3973666/eb2001859ca2/pone.0091986.g001.jpg

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