Other Compounds and Targets in Non–Small Cell Lung Cancer

Identifying set-wise differential co-expression in gene expression microarray data

Background

Previous differential coexpression analyses focused on identification of differentially coexpressed gene pairs, revealing many insightful biological hypotheses. However, this method could not detect coexpression relationships between pairs of gene sets. Considering the success of many set-wise analysis methods for microarray data, a coexpression analysis based on gene sets may elucidate underlying biological processes provoked by the conditional changes. Here, we propose a differentially coexpressed gene sets (dCoxS) algorithm that identifies the differentially coexpressed gene set pairs between conditions.

Results

dCoxS is a two-step analysis method. In each condition, dCoxS measures the interaction score (IS), which represents the expression similarity between two gene sets using Renyi relative entropy. When estimating the relative entropy, multivariate kernel density estimation was used to model gene-gene correlation structure. Statistical tests for the conditional difference between the ISs determined the significance of differential coexpression of the gene set pair. Simulation studies supported that the IS is a representative measure of similarity between gene expression matrices. Single gene coexpression analysis of two publicly available microarray datasets detected no significant results. However, the dCoxS analysis of the datasets revealed differentially coexpressed gene set pairs related to the biological conditions of the datasets.

Conclusion

dCoxS identified differentially coexpressed gene set pairs not found by single gene analysis. The results indicate that set-wise differential coexpression analysis is useful for understanding biological processes induced by conditional changes.

Targeted therapy in advanced non-small cell lung cancer (NSCLC): where do we stand?

Cytotoxic chemotherapy has helped improve the outcomes in patients with advanced non-small cell lung cancer (NSCLC), but we seem to have reached a plateau with respect to the benefit obtained. Also, a large subset of elderly patients and those with a poor performance status cannot tolerate these drugs at recommended doses. There is a growing need to incorporate newer drugs with different mechanisms of action and better safety profile. The epidermal growth factor receptor family (EGFR) and vascular endothelial growth factor (VEGF) have been identified as potential targets and agents acting specifically against these targets have been developed with the hope of improving outcomes. Although recent data with the small molecule EGFR tyrosine kinase inhibitors have been disappointing, there have been instances of dramatic responses thereby raising questions about the ideal patient to whom these drugs should be administered. Cetuximab, the anti-EGFR antibody has shown promising results. Bevacizumab, the anti-VEGF antibody was the first drug to demonstrate a survival benefit in first line treatment when added to chemotherapy. This review will briefly discuss the important trials using these targeted agents in advanced NSCLC.