Applying HDACis to increase SSTR2 expression and radiolabeled DOTA-TATE uptake: from cells to mice.

Life sciences(2023)

引用 0|浏览5
暂无评分
摘要
AIMS:The aim of our study was to determine the effect of histone deacetylase (HDAC) inhibitors (HDACis) on somatostatin type-2 receptor (SSTR2) expression and [111In]In-/[177Lu]Lu-DOTA-TATE uptake in vitro and in vivo. MATERIALS AND METHODS:The human cell lines NCI-H69 (small-cell lung carcinoma) and BON-1 (pancreatic neuroendocrine tumor) were treated with HDACis (i.e. entinostat, mocetinostat (MOC), LMK-235, CI-994 or panobinostat (PAN)), and SSTR2 mRNA expression levels and [111In]In-DOTA-TATE uptake were measured. Furthermore, vehicle- and HDACi-treated NCI-H69 and BON-1 tumor-bearing mice were injected with radiolabeled DOTA-TATE followed by biodistribution studies. Additionally, SSTR2 and HDAC mRNA expression of xenografts, and of NCI-H69, BON-1, NCI-H727 (human pulmonary carcinoid) and GOT1 (human midgut neuroendocrine tumor) cells were determined. KEY FINDINGS:HDACi treatment resulted in the desired effects in vitro. However, no significant increase in tumoral DOTA-TATE uptake was observed after HDACi treatment in NCI-H69 tumor-bearing animals, whereas tumoral SSTR2 mRNA and/or protein expression levels were significantly upregulated after treatment with MOC, CI-994 and PAN, i.e. a maximum of 2.1- and 1.3-fold, respectively. Analysis of PAN-treated BON-1 xenografts solely demonstrated increased SSTR2 mRNA expression levels. Comparison of HDACs and SSTR2 expression in BON-1 and NCI-H69 xenografts showed a significantly higher expression of 6/11 HDACs in BON-1 xenografts. Of these HDACs, a significant inverse correlation was found between HDAC3 and SSTR2 expression (Pearson r = -0.92) in the studied cell lines. SIGNIFICANCE:To conclude, tumoral uptake levels of radiolabeled DOTA-TATE were not enhanced after HDACi treatment in vivo, but, depending on the applied inhibitor, increased SSTR2 expression levels were observed.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要