Abstract 339: Rational selection of biomarkers to help direct erlotinib treatment for advanced non-small cell lung cancer (NSCLC)

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Background: The objective of this study was to identify serum biomarkers capable of identifying which advanced NSCLC patients are likely to receive clinical benefit from erlotinib therapy regardless of EGFR mutational status. Although patients harboring tumors with specific EGFR activating mutations are more likely to respond to erlotinib treatment, randomized clinical trials have shown that 30-40%of patients with wild-type EGFRs may also receive clinical benefit in the form of stable disease. Our general approach uses bioinformatic algorithms on gene expression microarray data to predict which tumor-shed biomarkers to assay for in the circulation. Methods and materials: Affymetrix U133A gene expression data (.CEL files) from Balko, et al. (BMC Cancer. 2009; 9: 145) were preprocessed in R using RMA and tested for differential expression using the Significance Analysis of Microarray (SAM) package. Pathway analysis was performed on the results based on KEGG and Gene ontogeny (GO) to define gene sets and tested for categorical significance by performing a Fisher Exact test. From these results, a selection of gene products either known or predicted to be secreted into circulation were combined with an assortment of previously investigated cancer biomarkers for further evaluation. Using pre-treatment serum from a total of 155 patients with advanced NSCLC we evaluated 43 biomarkers using the following MILLIPLEX®MAP immunoassay kits: Human Circulating Cancer Biomarker 24-plex, Human Soluble Cytokine Receptor 14-plex, and Human MMP panel 2 5-plex. Overall survival (OS) using the log rank test was the primary outcome for this study. Result: Preliminary single biomarker statistical analysis revealed a total of 23 prognostic biomarkers correlated (1p<0.01; 2 p<0.001) with OS in advanced NSCLC patients receiving erlotinib (n=72). High concentration of Prolactin1, total PSA1, CA15-31, CA1251, HGF1, sTNFRI2, sTNFRII2, CYFRA 21-12, interleukin-62, and osteopontin2 correlated with lower OS; whereas sEGFR1, Leptin1, TRAIL1 were associated with higher OS. Although the full complement of data has not been processed, similar findings and trends were observed within the patient cohorts treated with platinum-based chemotherapy (n=83) suggesting that this biomarker panel may be primarily prognostic and not predictive for outcome with a specific therapy. Conclusion: These serum biomarkers could be used to define a contingency-based algorithm that would ultimately be implemented alone or in tandem with a EGFR mutation analysis to provide a comprehensive means to both identify patients not likely to benefit from costly therapy and also allow patients to receive less toxic therapy earlier in their treatment course. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 339. doi:10.1158/1538-7445.AM2011-339