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

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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.