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Automated High-Content Screening for Compounds That Disassemble the Perinucleolar Compartment

机译:自动高内涵筛选可拆卸核仁室的化合物

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All solid malignancies share characteristic traits, including unlimited cellular proliferation, evasion of immune regulation, and the propensity to metastasize. The authors have previously described that a subnuclear structure, the perinucleolar compartment (PNC), is associated with the metastatic phenotype in solid tumor cancer cells. The percentage of cancer cells that contain PNCs (PNC prevalence) is indicative of the malignancy of a tumor both in vitro and in vivo, and thus PNC prevalence is a marker that reflects metastatic capability in a population of tumor cells. Although the function of the PNC remains to be determined, the PNC is highly enriched with small RNAs and RNA binding proteins. The initial chemical biology studies using a set of anticancer drugs that disassemble PNCs revealed a direct association of the structure with DNA. Therefore, PNC prevalence reduction as a phenotypic marker can be used to identify compounds that target cellular processes required for PNC maintenance and hence used to elucidate the nature of the PNC function. Here the authors report the development of an automated high-content screening assay that is capable of detecting PNC prevalence in prostate cancer cells (PC-3M) stably expressing a green fluorescent protein (GFP)-fusion protein that localizes to the PNC. The assay was optimized using known PNC-reducing drugs and non-PNC-reducing cytotoxic drugs. After optimization, the fidelity of the assay was probed with a collection of 8284 compounds and was shown to be robust and capable of detecting known and novel PNC-reducing compounds, making it the first reported high-content phenotypic screen for small changes in nuclear structure. (Journal of Biomolecular Screening 2009:1045-1053)
机译:所有实体恶性肿瘤都具有特征性特征,包括无限的细胞增殖,逃避免疫调节以及转移的倾向。作者先前已经描述了亚核结构,核仁室(PNC),与实体瘤癌细胞的转移表型有关。包含PNC的癌细胞的百分比(PNC患病率)指示体内外肿瘤的恶性程度,因此PNC患病率是反映肿瘤细胞群中转移能力的标志物。尽管PNC的功能尚待确定,但PNC高度富含小RNA和RNA结合蛋白。最初的化学生物学研究使用了一组可分解PNC的抗癌药物,揭示了该结构与DNA的直接关联。因此,作为表型标记的PNC流行率降低可用于鉴定靶向PNC维持所需细胞过程的化合物,因此可用于阐明PNC功能的性质。在这里,作者报告了一种自动化的高内涵筛选测定法的开发,该测定法能够检测稳定表达定位于PNC的绿色荧光蛋白(GFP)融合蛋白的前列腺癌细胞(PC-3M)中的PNC患病率。使用已知的减少PNC的药物和非减少PNC的细胞毒性药物对测定进行了优化。经过优化后,用8284种化合物探测了该方法的保真度,结果显示该方法非常可靠,并且能够检测已知和新颖的PNC还原化合物,从而成为首次报道的针对核结构微小变化的高含量表型筛选。 (生物分子筛选杂志2009:1045-1053)

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