A Plasma-Derived Protein-Metabolite Multiplexed Panel for Early-Stage Pancreatic Cancer

Abstract

Background: We applied a training and testing approach to develop and validate a plasma metabolite panel for the detection of early-stage pancreatic ductal adenocarcinoma (PDAC) alone and in combination with a previously validated protein panel for early-stage PDAC.

Methods: A comprehensive metabolomics platform was initially applied to plasmas collected from 20 PDAC cases and 80 controls. Candidate markers were filtered based on a second independent cohort that included nine invasive intraductal papillary mucinous neoplasm cases and 51 benign pancreatic cysts. Blinded validation of the resulting metabolite panel was performed in an independent test cohort consisting of 39 resectable PDAC cases and 82 matched healthy controls. The additive value of combining the metabolite panel with a previously validated protein panel was evaluated.

Results: Five metabolites (acetylspermidine, diacetylspermine, an indole-derivative, and two lysophosphatidylcholines) were selected as a panel based on filtering criteria. A combination rule was developed for distinguishing between PDAC and healthy controls using the Training Set. In the blinded validation study with early-stage PDAC samples and controls, the five metabolites yielded areas under the curve (AUCs) ranging from 0.726 to 0.842, and the combined metabolite model yielded an AUC of 0.892 (95% confidence interval [CI] = 0.828 to 0.956). Performance was further statistically significantly improved by combining the metabolite panel with a previously validated protein marker panel consisting of CA 19-9, LRG1, and TIMP1 (AUC = 0.924, 95% CI = 0.864 to 0.983, comparison DeLong test one-sided P= .02).

Conclusions: A metabolite panel in combination with CA19-9, TIMP1, and LRG1 exhibited substantially improved performance in the detection of early-stage PDAC compared with a protein panel alone.

Figure 1.

Schematic of study design. AUC = area under the curve; PDAC = pancreatic ductal carcinoma.

Figure 2.

Distributions of the five metabolite biomarkers in discovery cohorts 1 and 2. Box and whisker plots are shown for individual metabolites. Values represent the ratios of the respective metabolite relative to historical quality control reference measurement (see the “Methods”). Statistical significance was determined by two-sided Wilcoxon rank-sum test. PDAC = pancreatic ductal carcinoma.

Figure 3.

Areas under the curve (AUCs) of individual metabolites and metabolite panels in the Training and Test Sets. A) Receiver operating characteristic (ROC) curves for individual metabolites and the five-marker metabolite panel for distinguishing pancreatic ductal adenocarcinoma (PDAC; n = 29) from healthy subjects (n = 10). B) ROC curves for individual metabolites and the five-marker metabolite panel for distinguishing resectable PDAC (n = 39) from healthy subjects (n = 82; Test Set 1). AUC = area under the curve; CI = confidence interval.

Figure 4.

Areas under the curve (AUCs) for protein-metabolite multiplexed panel, five-marker metabolite-panel, three-marker protein panel, and CA19-9. A and B) Receiver operating characteristic (ROC) curves for protein-metabolite multiplexed panel, five-marker metabolite-panel, three-marker (LRG, TIMP1, CA19-9) protein panel, and CA19-9 in the Training Set (29 PDAC vs 10 healthy subjects) and independent Test Set (39 PDAC vs 82 healthy subjects). AUC = area under the curve; CI = confidence interval.

Figure 5.

Polyamine and lipid metabolism in PDAC. A) Abundances (area units +/- SD) of N1/N8-acetylspermidine or diacetylspermine in cell lysates of 11 PDAC cell lines. B) Abundance (area units +/- SD) of N1/N8-acetylspermidine or diacetylspermine in serum-free media collected one, two, four, and six hours post conditioning from 11 PDAC cell lines. C) Network displaying enzymes involved in the biosynthesis of polyamines and their acetylated derivatives. Node color (light gray = decreased; dark gray = increased) and size depict the direction and magnitude of change in mRNA expression of respective enzymes between PDAC and adjacent control tissue. Thickened node border illustrates statistical significance (two-sided paired t test P < .05). Box and whisker plots illustrate the distribution of mRNA expression for the respective enzyme between PDAC and adjacent control tissue. mRNA expression data were obtained from Oncomine (15) and are based on the Badea data set (14). D) Percent change in serum-containing media composition of lysophosphatidylcholine(18:0), lysophosphatidylcholine(20:3), and glycerophosphocholine in PANC1 and SU8686 PDAC cell lines following 24, 48, and 72 hours of culturing. E) Heat map depicting mRNA expression of enzymes and surface receptors known to directly participate in the metabolism or binding of lysophosphatidylcholines between PDAC and adjacent control tissue. Data were obtained from Oncomine (15) and are based on the Badea data set (14). Unsupervised clustering was performed using Euclidean distance with Ward’s method.