Development of molecular predictive model for molecular targeted therapy in lung cancer using pathway analysis

为了确定NSCLC分子靶向治疗敏感性的分子模型，我们使用cDNA阵列对同一组细胞系进行了基因表达谱研究，并使用修改后的国家癌症研究所程序将细胞毒性活性与相应的基因表达模式相关联。此外，使用Pathway Architect软件进行通路分析。利用基因-药物敏感性相关性和途径分析确定的基因，建立了区分敏感细胞系和耐药细胞系的支持向量机算法模型。基因分类器可用于预测HDAC抑制剂的药物敏感性。此外，本发明还提供了一种方法，我们确定了HDAC抑制剂治疗影响的基因，并利用这些串扰设计了联合治疗方案。设计的SAHA和S-1联合治疗肺癌可能是有希望的，因为它有可能通过HDAC抑制剂调节5-FU/S-1敏感性相关生物标志物（TS）来克服S-1耐药。我们通过对具有基因相关性的分子的通路分析，药敏相关性，并利用它们建立了区分敏感细胞系和耐药细胞系的支持向量机算法模型。通路分析显示JAK/STAT信号通路是涉及对enzaelatin敏感性的主要通路之一。同时给予恩扎鲁肽和JAK抑制剂可抑制恩扎鲁肽诱导的细胞生长抑制作用。此外，慢病毒介导的JAK 1过表达细胞比对照细胞对enzavin更敏感。我们的研究结果表明，JAK 1通路可以作为一个单一的预测生物标志物恩扎鲁肽治疗。

To identify a molecular model of sensitivity to molecular target therapy in NSCLC, we conducted a gene expression profiling study using cDNA arrays on the same set of cell lines and related the cytotoxic activity to corresponding gene expression pattern using a modified National Cancer Institute program. In addition, pathway analysis was done with Pathway Architect software. We used the 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-gene classifier is useful in predicting drug sensitivity to HDAC inhibitors. In addition, we identified the genes influenced by HDAC inhibitor treatment and designed combination using these cross-talk The designed combination therapy with SAHA and S-1 in lung cancer may be promising due to its potential to overcome S-1 resistance via modulation of 5-FU/S-1 sensitivity-associated biomarker(TS) by HDAC inhibitor.We identified eight genesrelated PKC inhibitor by pathway analysis of molecules having gene-drug sensitivity correlation, and used them to build a support vector machine algorithm model by which sensitive cell lines were distinguished from resistant cell lines. Pathway analysis revealed that the JAK/STAT signalling pathway was one of the main ones involved in sensitivity to enzastaurin. Simultaneous administration of enzastaurin and JAK inhibitor inhibited enzastaurin-induced cell growth-inhibitory effect. Furthermore, lentiviral-mediated JAK1-overexpressing cells were more sensitive to enzastaurin than control cells. Our results suggested that the JAK1 pathway may be used as a single predictive biomarker for enzastaurin treatment.