Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer.
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.


CONCLUSIONS
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.


CONCLUSIONS
These biomarkers could improve early detection and diagnosis of lung cancer.
University of California, Davis Genome Center, Davis, California.
Johannes F
JF
Fahrmann
Division of Biostatistics, Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, California.
Kyoungmi
K
Kim
University of California, Davis Genome Center, Davis, California.
Brian C
BC
DeFelice
Division of Biostatistics, Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, California.
Sandra L
SL
Taylor
Division of Hematology and Oncology, Department of Internal Medicine, School of Medicine, University of California, Davis Medical Center, Sacramento, California.
David R
DR
Gandara
Division of Pulmonary Medicine, Department of Internal Medicine, UC Davis Medical Center, Sacramento, California.
Ken Y
KY
Yoneda
Division of Thoracic Surgery, Department of Surgery, School of Medicine, University of California, Davis Medical Center, Sacramento, California.
David T
DT
Cooke
University of California, Davis Genome Center, Davis, California. Department of Biochemistry, Faculty of Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
Oliver
O
Fiehn
Division of Hematology and Oncology, Department of Internal Medicine, School of Medicine, University of California, Davis Medical Center, Sacramento, California.
Karen
K
Kelly
Division of Hematology and Oncology, Department of Internal Medicine, School of Medicine, University of California, Davis Medical Center, Sacramento, California. smiyamoto@ucdavis.edu.
Suzanne
S
Miyamoto
D000230:Adenocarcinoma / Q000097:blood / Q000175:diagnosis*; D000368:Aged; D014408:Biomarkers, Tumor / Q000097:blood; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000097:blood / Q000175:diagnosis*; D008297:Male; D055432:Metabolomics; D008875:Middle Aged
D014408:Biomarkers, Tumor