Miyanaga Akihiko, Gemma Akihiko, Noro Rintaro, Kataoka Kiyoko, Matsuda Kuniko, Nara Michiya, Okano Tetsuya, Seike Masahiro, Yoshimura Akinobu, Kawakami Akiko, Uesaka Haruka, Nakae Hiroki, Kudoh Shoji
Department of Internal Medicine, Division of Pulmonary Medicine, Infectious Diseases and Oncology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, Tokyo 113-8602, Japan.
Mol Cancer Ther. 2008 Jul;7(7):1923-30. doi: 10.1158/1535-7163.MCT-07-2140. Epub 2008 Jul 7.
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.
为了确定基于组蛋白去乙酰化酶(HDAC)抑制剂的治疗在非小细胞肺癌(NSCLC)中的潜力,我们通过3-(4,5-二甲基噻唑-2-基)-2,5-二苯基四氮唑溴盐法分析了曲古抑菌素A(TSA)和伏立诺他(异羟肟酸苯丁酯)对16种NSCLC细胞系的抗肿瘤作用。TSA和伏立诺他在50%的NSCLC细胞系中均表现出强大的抗肿瘤活性,这表明需要使用预测性标志物来选择接受该治疗的患者。对TSA和伏立诺他的反应性之间存在很强的相关性(P < 0.0001)。为了确定NSCLC中对HDAC抑制剂治疗敏感的分子模型,我们使用cDNA阵列对同一组细胞系进行了基因表达谱研究,并使用改良的美国国立癌症研究所程序将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软件进行了通路分析。我们使用通过基因-药物敏感性相关性和通路分析确定的9个基因构建了支持向量机算法模型,通过该模型可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通过另外9个细胞系进行了验证,在确定对TSA和伏立诺他的反应方面预测值达到了100%。我们的结果表明:(a)HDAC抑制剂可能是NSCLC有前景的抗癌药物;(b)九基因分类器有助于预测对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。