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

Abstract

Background: 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.

Methods: 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).

Results: 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.

Conclusions: 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.

Figure 1

PFAA profiles of lung cancer patients. Axes show the AUC of the ROC for each amino acid to discriminate lung cancer patients from controls. Black bold lines indicate the point at which the AUC of the ROC = 0.5.

Figure 2

ROC curves of discriminating scores for each discriminating function. Black lines indicate the ROC curves of Dataset 1, blue lines indicate those of Dataset 2, and red lines indicate those of Dataset 3.

Figure 3

Sensitivities of discriminating scores for Discriminant- 3, levels of tumor markers, and combinatorial use of both markers. Black bars indicate the sensitivities of all of the data from Dataset 4, while gray bars indicate those of patients with stage I and II disease. * : p<0.05, **: p<0.01, ***: p<0.001 significant at McNemar test.