Abstract 663: Diagnostic screen for lung cancer using high throughput metabolomics screen

Abstract

Lung cancer is one of the most common cancers in the world. It is a leading cause of cancer death in men and women in the United States, cigarette smoking being leading cause of lung cancer. There are two main types of lung cancer small cell and non-small cell lung cancer (NSCLC). The most common type being NSCLC which accounts for 80-85% of all reported cases. The ability to rapidly detect / diagnose lung cancer at an early stage is critical to successful treatment selection and patient survival. The use of metabolic profiling in biomedical applications metabolic profiling is being deployed as a method for finding novel, mechanistic, biomarkers of disease with obvious potential for improving diagnosis, and patient stratification. Here we present a rapid, simple and reliable high throughput targeted LC/MS single platform, for the quantification/monitoring of small molecule metabolites, lipids and peptides. The methodology employs a single set of LC/MS conditions which facilitate TCA cycle, bile acids, biogenic amine, free fatty acids, acyl carnitines, lipids and 100 protein panel without need for user intervention. Plasma from pilot cohort of lung cancer a health control samples were evaluated using this new methodology. The methodology showed excellent reproducibility and accuracy. The peptide analysis showed that 10 peptides were shown to be markers of lung cancer, these are listed in Table 1. Acylcarnitines were quantified over a range of 5 - 625ng/mL data showed that the C14:2 tetradecadienoyl carnitine and C16:1 palmitoleoyl carnitine were elevated in lung cancer samples whereas the C8:1 octenoyl carnitine level was reduced in the lung cancer samples . Although deoxycholic acid and chendeoxycholic acid appeared to be reduced in the lung cancer samples this was determined to be not statistically relevant. A total of 29 amino acids were measured during the analysis. Using t-test with p-value FDR cutoff adjusted to 0.01 the data clearly showed that sarcosine was highly over-expressed in lung cancer samples. Note: This abstract was not presented at the meeting. Citation Format: Robert S. Plumb, Lee Gethings, Andrew Peck. Diagnostic screen for lung cancer using high throughput metabolomics screen [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 663.