The significance and robustness of a plasma free amino acid (PFAA) profile-based multiplex function for detecting lung cancer

• Published in: BMC cancer 2013-02, Vol.13 (1), p.77-77, Article 77
• Main Authors: Shingyoji, Masato, Iizasa, Toshihiko, Higashiyama, Masahiko, Imamura, Fumio, Saruki, Nobuhiro, Imaizumi, Akira, Yamamoto, Hiroshi, Daimon, Takashi, Tochikubo, Osamu, Mitsushima, Toru, Yamakado, Minoru, Kimura, Hideki
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; Amino acids; Amino Acids - blood; Biomarkers, Tumor - blood; Cancer; Chromatography, High Pressure Liquid - methods; Diagnosis; Early Detection of Cancer - methods; Female; Food additives industry; High performance liquid chromatography; Hospitals; Humans; Ionization; Lung cancer; Lung Neoplasms - blood; Lung Neoplasms - diagnosis; Male; Mass spectrometry; Metabolites; Methods; Middle Aged; Multivariate Analysis; Oncology, Experimental; Plasma; Reproducibility of Results; Spectrometry, Mass, Electrospray Ionization - methods; Studies; Young Adult
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/1471-2407-13-77

We have recently reported on the changes in plasma free amino acid (PFAA) profiles in lung cancer patients and the efficacy of a PFAA-based, multivariate discrimination index for the early detection of lung cancer. In this study, we aimed to verify the usefulness and robustness of PFAA profiling for detecting lung cancer using new test samples. Plasma samples were collected from 171 lung cancer patients and 3849 controls without apparent cancer. PFAA levels were measured by high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-mass spectrometry (MS). High reproducibility was observed for both the change in the PFAA profiles in the lung cancer patients and the discriminating performance for lung cancer patients compared to previously reported results. Furthermore, multivariate discriminating functions obtained in previous studies clearly distinguished the lung cancer patients from the controls based on the area under the receiver-operator characteristics curve (AUC of ROC = 0.731 ~ 0.806), strongly suggesting the robustness of the methodology for clinical use. Moreover, the results suggested that the combinatorial use of this classifier and tumor markers improves the clinical performance of tumor markers. These findings suggest that PFAA profiling, which involves a relatively simple plasma assay and imposes a low physical burden on subjects, has great potential for improving early detection of lung cancer.