High accuracy prostate cancer detection using human blood serum metabolomics profiling

MARÍA E. MONGE; XIAOLING ZANG; NAEL A. MCCARTY; ARLENE A. STECENKO; FACUNDO M. FERNÁNDEZ

Rosario

Simposio; 2nd Latin American Metabolic Profiling Symposium; 2016

Progressive lung function decline and ultimately respiratory failure is the most common cause of death in cystic fibrosis (CF).1 This decline is punctuated by acute pulmonary exacerbations (APEs) and, in many cases there is failure to return to baseline lung function. In this study, we utilize a discovery-based metabolomics approach to analyze exhaled breath condensate (EBC) samples from 17 clinically stable CF patients, 9 CF patients with an APE, 5 CF patients during recovery from an APE event (termed post-APE), and 4 CF patients who were clinically stable at the time of collection but in the subsequent 1 to 3 months developed a severe APE (termed pre-APE), using ultraperformance liquid chromatography-quadrupole-time-of-flight mass spectrometry in combination with supervised multivariate classification models. A panel containing 2 metabolic discriminant features identified as 4-hydroxycyclohexylcarboxylic acid and pyroglutamic acid differentiated the APE from the stable CF samples with 84.6% accuracy. Pre-APE EBC samples were distinguished from stable CF EBC samples by lactic acid and pyroglutamic acid with 90.5% accuracy, and in general matched the ?APE signature? when projected into the APE vs. stable CF model. Post-APE samples were on average more similar to stable CF samples in terms of their metabolomic signature. These results show feasibility for detecting APEs, and even predicting an oncoming APE, or monitoring APE treatment using EBC metabolites.