Investigation of Metabolomic Blood Biomarkers for Detection of Adenocarcinoma Lung Cancer
Autor: | Suzanne Miyamoto, David R. Gandara, Kyoungmi Kim, Karen Kelly, Brian C. DeFelice, Ken Y. Yoneda, Sandra L. Taylor, David T. Cooke, Oliver Fiehn, Johannes F. Fahrmann |
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Rok vydání: | 2015 |
Předmět: |
Male
medicine.medical_specialty Pathology Lung Neoplasms Epidemiology Metabolite Adenocarcinoma Medical and Health Sciences Gastroenterology Article chemistry.chemical_compound Rare Diseases Metabolomics Clinical Research Internal medicine Genetics Biomarkers Tumor medicine Humans Multiplex Genetic Testing Lung cancer Lung Cancer Aged screening and diagnosis Tumor business.industry Lung Cancer Case-control study Middle Aged medicine.disease 4.1 Discovery and preclinical testing of markers and technologies Detection medicine.anatomical_structure Oncology chemistry Blood biomarkers Case-Control Studies Female Digestive Diseases business Biomarkers 4.2 Evaluation of markers and technologies |
Zdroj: | Fahrmann, JF; Kim, K; DeFelice, BC; Taylor, SL; Gandara, DR; Yoneda, KY; et al.(2015). Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer. Cancer Epidemiology Biomarkers and Prevention, 24(11), 1716-1723. doi: 10.1158/1055-9965.EPI-15-0427. UC Davis: Retrieved from: http://www.escholarship.org/uc/item/1dj8m7wn Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, vol 24, iss 11 |
ISSN: | 1538-7755 1055-9965 |
Popis: | 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. Cancer Epidemiol Biomarkers Prev; 24(11); 1716–23. ©2015 AACR. |
Databáze: | OpenAIRE |
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