Research Papers:

Plasma lipidomics profiling identified lipid biomarkers in distinguishing early-stage breast cancer from benign lesions

Xiaoli Chen, Hankui Chen, Meiyu Dai, Junmei Ai, Yan Li, Brett Mahon, Shengming Dai and Youping Deng _

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Oncotarget. 2016; 7:36622-36631. https://doi.org/10.18632/oncotarget.9124

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Xiaoli Chen1,2,*, Hankui Chen2,*, Meiyu Dai1,2, Junmei Ai2, Yan Li2, Brett Mahon3, Shengming Dai1, Youping Deng2,4,5

1Department of Clinical Laboratory, The Fourth Hospital Affiliated to Guangxi Medical University, Liuzhou City, Guangxi Province, China

2Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA

3Department of Pathology, Rush University Medical Center, Chicago, Illinois, USA

4Department of Anatomy and Cell Biology, Rush University Medical Center, Chicago, Illinois, USA

5Medical College, Wuhan University of Science and Technology, Wuhan, Hubei Province, China

*These authors have contributed equally to this work

Correspondence to:

Youping Deng, e-mail: [email protected]

Shengming Dai, e-mail: [email protected]

Keywords: breast cancer, lipidomics, benign lesion, biomarker, plasma

Abbreviations: LPC, lysophosphatidylcholine; PC, phosphatidylcholine; ePC, ether-linked phosphatidylcholine; CE, cholesterol ester; PLA2, phospholipase A2

Received: January 19, 2016     Accepted: April 16, 2016     Published: May 2, 2016


Background: Breast cancer is very common and highly fatal in women. Current non-invasive detection methods like mammograms are unsatisfactory. Lipidomics, a promising detection method, may serve as a novel prognostic approach for breast cancer in high-risk patients.

Results: According the predictive model, the combination of 15 lipid species had high diagnostic value. In the training set, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the combination of these 15 lipid species were 83.3%, 92.7%, 89.7%, and 87.9%, respectively. The AUC in the training set was 0.926 (95% CI 0.869-0.982). Similar results were found in the validation set, with the sensitivity, specificity, PPV and NPV at 81.0%, 94.5%, 91.9%, and 86.7%, respectively. The AUC was 0.938 (95% CI 0.889-0.986) in the validation set.

Methods: Using triple quadrupole liquid chromatography electrospray ionization tandem mass spectrometry, this study was to detect global lipid profiling of a total of 194 plasma samples from 84 patients with early-stage breast cancer (stage 0–II) and 110 patients with benign breast disease included in a training set and a validation set. A binary logistic regression was used to build a predictive model for evaluating the lipid species as potential biomarkers in the diagnosis of breast cancer.

Conclusion: The combination of these 15 lipid species as a panel could be used as plasma biomarkers for the diagnosis of breast cancer.

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