Abstract 2700: In vitro-based COXEN biomarker model predicts outcome in metastatic colorectal cancer patients treated with cetuximab
Authors: Cho Sang-Hoon , Theodorescu Dan , Lee Jae K. , Laurent-Puig Pierre 
Published: February 2011

Purpose

While metastatic colorectal cancer (CRC) patients with KRAS mutations have shown extremely low clinical responses to cetuximab, an epidermal growth factor receptor (EGFR) inhibitor, about half of metastatic CRC patients with KRAS wild type have been found to be responsive to this targeted therapeutic agent. The current study was performed to apply refined “coexpression extrapolation” (COXEN) algorithm in order to identify and develop a predictive gene expression signature of cetuximab for metastatic CRC patients using in vitro drug activity data of CRC cell lines treated with erlotinib, another EGFR inhibitor.

Patients

Gene expression profiles (Illumina HumanHT-12 BeadChips®) and KRAS mutation information were obtained for 42 metastatic CRC patients at the Department of Medical School, University Paris Descartes. All patients received either a cetuximab monotherapy or a cetuximab-based combination regimen as a second-line or greater therapy. KRAS status of each patient's tumor was assessed by allelic discrimination. Each patient's clinical response to therapy was measured according to RECIST (Response Evaluation Criteria in Solid Tumors) criteria.

Methods

The refined COXEN algorithm comprising three main steps was applied to construct a multivariate prediction model of cetuximab for metastatic CRC patients. First, the gene expression profiles (Affymetrix HG-U133Plus2 GeneChips®) and the in vitro drug activities on erlotinib, which were previously published on 8 CRC cell lines, were utilized to identify drug sensitivity biomarkers most highly associated with the drug activities. Using these biomarkers, candidate multivariate prediction models were developed using the 8 CRC cell lines and evaluated on 7 CRC cell lines from the NCI-60 cell lines treated with erlotinib. The final prediction signature model with 70 biomarkers was prospectively validated on a CRC patient set recently reported in Khambata-Ford et al. (2007). For our patient set, a smaller 60-gene biomarker model was established by annotation matches between the two different array platforms.

Results

The refined COXEN signature models accurately predicted the clinical responses of metastatic CRC patients with KRAS wild-type receiving the cutuximab single or combination therapy (Spearman correlation test p-values between predicted scores and different degrees of clinical responses = 0.005 and 0.034 for Khambata-Ford and our patient sets, respectively). We also found that the COXEN prediction scores for patients were highly correlated with their disease-free survival times (Spearman correlation test p-values = 0.01 and 0.12 for the two sets, respectively).

Conclusion

The refined COXEN biomarker signature models demonstrated high potential and clinical utility to select a priori metastatic CRC patients who are likely to benefit from treatments with cetuximab.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2700.