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. 2022 Dec 15;10:1075810. doi: 10.3389/fcell.2022.1075810

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Copyright © 2022 Song, Zhang, Xie and Song.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Results of serum validation for metabolite markers discovered in tissue. (A) Diagram of recruited cohort of healthy donor (HD), TNBC patients, CPSI-MS screening for serum metabolomics, and machine learning process; (B) Venn graphs display the number of metabolites that are finally selected as serum screening markers and used for quantitative estimation; (C) Heatmap visualization indicate the consistent tendencies of these characteristic metabolites in tissue and serum; (D) The quantitative comparison of representative 10 metabolite markers in serum; (E) The scores predicted by Lasso classifier on the 381 TNBC and HD serum samples; (F) Histograms display the distribution of HD and TNBC samples in the training and test sets; (G) ROC curve for assessing the performances of the metabolite markers-based Lasso model for TNBC screening. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.