A dried blood spot mass spectrometry metabolomic approach for rapid breast cancer detection
Received 6 September 2015
Accepted for publication 13 November 2015
Published 11 March 2016 Volume 2016:9 Pages 1389—1398
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Ram Prasad
Peer reviewer comments 2
Editor who approved publication: Professor Daniele Santini
Qingjun Wang,1,2,* Tao Sun,3,* Yunfeng Cao,1,2,4,5 Peng Gao,2,4,6 Jun Dong,2,4 Yanhua Fang,2 Zhongze Fang,2 Xiaoyu Sun,2 Zhitu Zhu1,2
1Oncology Department 2, The First Affiliated Hospital of Liaoning Medical University, 2Personalized Treatment and Diagnosis Research Center, The First Affiliated Hospital of Liaoning Medical University and Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Jinzhou, 3Department of Internal Medicine 1, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Insititute, Shenyang, 4CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 5Key Laboratory of Contraceptives and Devices Research (NPFPC), Shanghai Engineer and Technology Research Center of Reproductive Health Drug and Devices, Shanghai Institute of Planned Parenthood Research, Shanghai, 6Clinical Laboratory, Dalian Sixth People’s Hospital, Dalian, People’s Republic of China
*These authors contributed equally to this work
Objective: Breast cancer (BC) is still a lethal threat to women worldwide. An accurate screening and diagnosis strategy performed in an easy-to-operate manner is highly warranted in clinical perspective. Besides the routinely focused protein markers, blood is full of small molecular metabolites with diverse structures and properties. This study aimed to screen metabolite markers with BC diagnosis potentials.
Methods: A dried blood spot-based direct infusion mass spectrometry (MS) metabolomic analysis was conducted for BC and non-BC differentiation. The targeted analytes included 23 amino acids and 26 acylcarnitines.
Results: Multivariate analysis screened out 21 BC-related metabolites in the blood. Regression analysis generated a diagnosis model consisting of parameters Pip, Asn, Pro, C14:1/C16, Phe/Tyr, and Gly/Ala. Tested with another set of BC and non-BC samples, this model showed a sensitivity of 92.2% and a specificity of 84.4%. Compared to the routinely used protein markers, this model exhibited distinct advantage with its higher sensitivity.
Conclusion: Blood metabolites screening is a more plausible approach for BC detection. Furthermore, this direct MS analysis could be finished within few minutes, which means that its throughput is higher than the currently used imaging techniques.
Keywords: breast cancer, metabolomics, dried blood spot testing
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