Abstract 1901: Untargeted metabolomic profiling identifies diagnostic and prognostic biomarkers of lung cancer

• Published in: Cancer research (Chicago, Ill.) Ill.), 2013-04, Vol.73 (8_Supplement), p.1901-1901
• Main Authors: Haznadar, Majda, Mathe, Ewy, Patterson, Andrew D., Manna, Soumen K., Krausz, Kristopher W., Bowman, Elise D., Idle, Jeffrey R., Kazandjian, Dickran G., Gonzalez, Frank J., Harris, Curtis C.
• Format: Article
• Language: English
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2013-1901

Lung cancer remains the most common cause of cancer deaths world-wide. Despite the intensive research over many years, the prognosis of this deadly disease is still very poor, with fewer than 15% of the patients surviving 5 years after primary diagnosis. While there are several methodologies described and proposed for early detection of lung cancer (spiral CT, circulating pro-inflammatory cytokines IL6, IL8 and CRP), the specificity and robustness remains to be achieved. What we readily know is that cancer cells have a distinguishable metabolic fingerprint compared to normal cells. Metabolomics holds promise to be able to detect and capture subtle shifts in multiple metabolic paths and cellular modifiers that will enable identification of critical components of cancer risk and tumor behavior. We conducted a first of its kind effort using mass spectrometry-based untargeted metabolic profiling of urine samples obtained from 469 lung cancer patients and 536 healthy population controls. We identified four robust biomarkers, high levels of which are associated with lung cancer diagnosis and poorer survival. After the adjustment for potential confounding factors, all four biomarkers were significantly associated with lung cancer diagnosis (FDR-adjusted p-values