Lung cancer is the leading cause of cancer-related deaths in US. For the majority of patients (70%), the extent of the disease precludes complete surgical resection and treatment relies solely on radiation, chemotherapy or a combination of both. Unfortunately, these treatments improve survival only minimally and are accompanied by considerable adverse side effects. Despite immense research efforts over the last 20 years, the mean survival of lung cancer patients has only increased by 13 days. This relatively poor mean survival is attributed to inadequate therapy selection. Current therapy selection is mainly based on the histopathologic examination of needle biopsies obtained during bronchoscopy. There is growing concern that these classifications and stratification are insufficient to predict treatment response of individual tumors. To complement current histopathological-based tumor classification, we investigated the suitability of metabolomics to improve tumor classification. Therefore, metabolomic profiles were obtained from various lung cancer cell-lines. Data were analyzed for molecular features characteristic for cell-lines derived from adenocarcinoma (AdenoCa) or squamous cell carcinoma (SqCCa). Data analyses revealed 78 features that are capable of clearly separating AdenoCa, SqCCa, and lung fibroblasts from each other. Subsequently, the studies were extended to specimen from 30 lung cancer patients. Similar to the cell-line experiments, metabolomic profiles were obtained and analyzed for characteristic features of patients with AdenoCa, SqCCa, or non-malignant specimen. The analysis of the human specimen revealed 21 unique features that are potentially suitable biomarkers for tumor classification. Our data suggest that metabolomic profiling is a promising approach to classify and distinguish between individual tumor cell-lines and to distinguish patients with AdenoCa from patients with SqCCa.

Citation Format: Daniel R. Sappington, Scott Helms, Ishwori B. Dhakal, Eric R. Siegel, Thaddeus Bartter, Gunnar Boysen. Molecular characterization of lung tumors based on metabolomic profiling. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3236. doi:10.1158/1538-7445.AM2013-3236