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Identification of a transcriptional profile associated with in vitro invasion in non-small cell lung cancer cell lines

Although much has been learned about basic mechanisms of cell invasion, the genes whose expression is required for this process by malignant cell lines have remained obscure. We assessed invasion through Matrigel using EGF as a chemoattractant and gene expression profiles using oligonucleotide microarrays for 22 non-small cell lung cancer cell lines. The expression of 22 genes were significantly correlated (p < 0.001) with the measured invasion index. Cluster analysis demonstrated that gene expression profiles classify the cell lines into low and high invasive subgroups. Considering invasiveness as a dichotomous variable, Bayesian analysis was used to identify genes that have the highest probability of being differentially expressed between the high and low invasion groups. This analysis identified 16 genes whose expression was associated with invasiveness. “Leave one out” cross validation was 91% accurate. Nine genes were identified in both correlation and Bayesian analyses. Seven of the nine genes were negatively associated with invasion and four of those genes are plasma membrane proteins. The two genes with the highest inverse association with invasion, TACSTD1 and CLDN3, are involved with cell adhesion and cell-cell interactions, respectively. Interestingly, the gene with the highest positive association with invasion, SERPINE1 (PAI-1), is a protease inhibitor. These and the other genes identified by both analyses represent targets for further study to assess their importance in non-small cell lung cancer invasion and metastasis.