A Novel Multivariate Index for Pancreatic Cancer Detection Based On the Plasma Free Amino Acid Profile

Abstract

Background: The incidence of pancreatic cancer (PC) continues to increase in the world, while most patients are diagnosed with advanced stages and survive <12 months. This poor prognosis is attributable to difficulty of early detection. Here we developed and evaluated a multivariate index composed of plasma free amino acids (PFAAs) for early detection of PC.

Methods: We conducted a cross-sectional study in multi-institutions in Japan. Fasting plasma samples from PC patients (n = 360), chronic pancreatitis (CP) patients (n = 28), and healthy control (HC) subjects (n = 8372) without apparent cancers who were undergoing comprehensive medical examinations were collected. Concentrations of 19 PFAAs were measured by liquid chromatography-mass spectrometry. We generated an index consisting of the following six PFAAs: serine, asparagine, isoleucine, alanine, histidine, and tryptophan as variables for discrimination in a training set (120 PC and matching 600 HC) and evaluation in a validation set (240 PC, 28 CP, and 7772 HC).

Results: Several amino acid concentrations in plasma were significantly altered in PC. Plasma tryptophan and histidine concentrations in PC were particularly low, while serine was particularly higher than that of HC. The area under curve (AUC) based on receiver operating characteristic (ROC) curve analysis of the resulting index to discriminate PC from HC were 0.89 [95% confidence interval (CI), 0.86-0.93] in the training set. In the validation set, AUCs based on ROC curve analysis of the PFAA index were 0.86 (95% CI, 0.84-0.89) for all PC patients versus HC subjects, 0.81 (95% CI, 0.75-0.86) for PC patients from stage IIA to IIB versus HC subjects, and 0.87 (95% CI, 0.80-0.93) for all PC patients versus CP patients.

Conclusions: These findings suggest that the PFAA profile of PC was significantly different from that of HC. The PFAA index is a promising biomarker for screening and diagnosis of PC.

Fig 1. Summary of study design and inclusion and exclusion criteria.

Fig 2. PFAA profiles of PC patients.

The results of receiver–operator characteristic (ROC) curve analysis of PFAA profiles in the training set (120 PC and matching 600 HC). Axes show the AUC of ROC for each amino acid to discriminate patients from healthy controls. Black bold lines indicate the point where the AUC of ROC = 0.5.

Fig 3. ROC curves of the PFAA index of PC patients compared with those of healthy controls in the training set (120 PC and matching 600 HC) (A) and the validation set (240 PC and 7772 HC) (B).

Fig 4. ROC curves of the PFAA index with different tumor stages, sizes, and locations.

(A) ROC curves of the PFAA index in stage IIA (red), stage IIB (pink), stage III (orange), and stage IV (yellow–green), respectively. (B) ROC curves in TS1 (red), TS2 (pink), TS3 (orange), and TS4 (yellow–green), respectively. TS1 ≤ 2.0 cm, 2.0 cm < TS2 ≤ 4.0 cm, 4.0 cm < TS3 ≤ 6.0 cm, and TS4 > 6.0 cm. (C) ROC curves in the pancreatic head (red), body (pink), and tail (orange), respectively.

Fig 5. Correlation of PFAA index and other biomarkers (CA19-9, CEA, and elastase 1).

The dotted line shows the cut-off of each biomarker or PFAA index. For data analysis, the upper normal limits of CA19-9, CEA, and elastase-1 were defined as 37 U/mL, 5 ng/dL, and 300 ng/dL, respectively. There were no significant correlations between each biomarker and the PFAA index.