Abstract A33: Integrated analysis of molecular and metabolomic data to identify drug resistance mechanisms in lung cancers

Consistent bioinformatics analysis approaches of chemically perturbed biological systems are needed in order to achieve meaningful integration of results from multiple experiments in support of cancer systems biology research. Our initial efforts have focused on identifying and contrasting molecular mechanisms that reveal biochemical events affecting non-small cell lung cancers in the context of combination drug therapies as a model for defining these approaches. While the link between growth factor receptor mutations, target inhibitor drugs and non-small cell lung cancer is well established, the basis of variable response in different patient cohorts is still poorly understood and is the subject of ongoing investigations. Data for our efforts were provided by the NCI9s Center for Advanced Preclinical Research. Mice genetically engineered to develop erlotinib-sensitive lung adenocarcinomas were subjected to drug compounds that are currently in clinical trials, as well as erlotinib, individually and in combination, to study early response and development of late resistance. Metabolite data, gene expression data, and histological data were collected and used in defining the initial analysis approach. While evaluation of analysis approaches continues, preliminary results already indicate these data can be effective in assessing drug efficacy on reducing tumor burden. Further efforts are underway to develop analysis techniques to explore the underlying dynamic processes. Citation Format: Anand S. Merchant, Natalie Fedorova Abrams, Eric A. Stahlberg, Zoe Weaver. Integrated analysis of molecular and metabolomic data to identify drug resistance mechanisms in lung cancers [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr A33.