Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer

Abstract

Background: Untargeted metabolomics was used in case-control studies of adenocarcinoma (ADC) lung cancer to develop and test metabolite classifiers in serum and plasma as potential biomarkers for diagnosing lung cancer.

Methods: Serum and plasma were collected and used in two independent case-control studies (ADC1 and ADC2). Controls were frequency matched for gender, age, and smoking history. There were 52 adenocarcinoma cases and 31 controls in ADC1 and 43 adenocarcinoma cases and 43 controls in ADC2. Metabolomics was conducted using gas chromatography time-of-flight mass spectrometry. Differential analysis was performed on ADC1 and the top candidates (FDR < 0.05) for serum and plasma used to develop individual and multiplex classifiers that were then tested on an independent set of serum and plasma samples (ADC2).

Results: Aspartate provided the best accuracy (81.4%) for an individual metabolite classifier in serum, whereas pyrophosphate had the best accuracy (77.9%) in plasma when independently tested. Multiplex classifiers of either 2 or 4 serum metabolites had an accuracy of 72.7% when independently tested. For plasma, a multimetabolite classifier consisting of 8 metabolites gave an accuracy of 77.3% when independently tested. Comparison of overall diagnostic performance between the two blood matrices yielded similar performances. However, serum is most ideal given higher sensitivity for low-abundant metabolites.

Conclusion: This study shows the potential of metabolite-based diagnostic tests for detection of lung adenocarcinoma. Further validation in a larger pool of samples is warranted.

Impact: These biomarkers could improve early detection and diagnosis of lung cancer.

Figure 1. ROC curves for individual- and multi-metabolite classifiers in serum

A) ROC curves for aspartate and Bin_225393 in serum. B) ROC curves for two multi-metabolite classifiers in serum. The 4 metabolite classifier contains all the metabolites included in the classifier (Table 2). The 3 metabolite classifier includes Bin_225393, aspartate and xylose. Confidence intervals for AUCs are provided in Supplemental Table S6.

Figure 2. ROC curves for individual- and multi-metabolite classifiers in plasma

A) ROC curves for maltose and pyrophosphate in plasma. B) ROC curves for the best multi-metabolite ADC1 classifier for plasma consisting of 5 metabolites (blue line) and the classifier consisting of 8 (black line) when applied to ADC2 are shown (Table 3). Confidence intervals for AUCs are provided in Supplemental Table S6.