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Antitumor activity of histone deacetylase inhibitors in non-small cell lung cancer cells: development of a molecular predictive model.

机译:组蛋白脱乙酰基酶抑制剂在非小细胞肺癌细胞中的抗肿瘤活性:建立分子预测模型。

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To ascertain the potential for histone deacetylase (HDAC) inhibitor-based treatment in non-small cell lung cancer (NSCLC), we analyzed the antitumor effects of trichostatin A (TSA) and suberoylanilide hydroxamic acid (vorinostat) in a panel of 16 NSCLC cell lines via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. TSA and vorinostat both displayed strong antitumor activities in 50% of NSCLC cell lines, suggesting the need for the use of predictive markers to select patients receiving this treatment. There was a strong correlation between the responsiveness to TSA and vorinostat (P 0.0001). To identify a molecular model of sensitivity to HDAC inhibitor treatment in NSCLC, we conducted a gene expression profiling study using cDNA arrays on the same set of cell lines and related the cytotoxic activity of TSA to corresponding gene expression pattern using a modified National Cancer Institute program. In addition, pathway analysis was done with Pathway Architect software. We used nine genes, which were identified by gene-drug sensitivity correlation and pathway analysis, to build a support vector machine algorithm model by which sensitive cell lines were distinguished from resistant cell lines. The prediction performance of the support vector machine model was validated by an additional nine cell lines, resulting in a prediction value of 100% with respect to determining response to TSA and vorinostat. Our results suggested that (a) HDAC inhibitors may be promising anticancer drugs to NSCLC and (b) the nine-gene classifier is useful in predicting drug sensitivity to HDAC inhibitors and may contribute to achieving individualized therapy for NSCLC patients.
机译:为了确定在非小细胞肺癌(NSCLC)中基于组蛋白脱乙酰基酶(HDAC)抑制剂治疗的潜力,我们分析了16种NSCLC细胞中曲古抑菌素A(TSA)和辛二酰苯胺异羟肟酸(vorinostat)的抗肿瘤作用。通过3-(4,5-二甲基噻唑-2-基)-2,5-二苯基溴化四溴联苯醚测定。 TSA和伏立诺他都在50%的NSCLC细胞系中均显示出强大的抗肿瘤活性,这表明需要使用预测标记来选择接受该治疗的患者。对TSA的反应性与伏立诺他有很强的相关性(P <0.0001)。为了确定对NSCLC中HDAC抑制剂治疗敏感的分子模型,我们使用改良的美国国家癌症研究所计划在同一组细胞系上使用cDNA阵列进行了基因表达谱研究,并将TSA的细胞毒活性与相应的基因表达模式相关联。此外,使用Pathway Architect软件进行路径分析。我们使用通过基因-药物敏感性相关性和途径分析鉴定的9个基因,建立了一个支持向量机算法模型,通过该模型可以区分敏感细胞系和耐药细胞系。支持向量机模型的预测性能已通过另外的9个细胞系进行了验证,就确定对TSA和伏立诺他的响应而言,得出的预测值为100%。我们的结果表明,(a)HDAC抑制剂可能是有希望的NSCLC抗癌药物,并且(b)九基因分类器可用于预测对HDAC抑制剂的药物敏感性,并可能有助于实现NSCLC患者的个体化治疗。

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