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. 2021 Feb 18;10:519180. doi: 10.3389/fonc.2020.519180

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Copyright © 2021 Zhu, Tang, Lv, Meng, Weng, Zhang, Li, Fan, Zheng, Fang, Xu and Ji

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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Establishment and validation of diagnostic model to distinguish HCC from dysplastic nodules. (A, B) Confusion matrices of binary data indicated high specificity and sensitivity of model to identify HCC and dysplastic nodules in training cohort (GSE6764 cohort) and validation cohort (GSE98620 cohort). (C, D) Cox analysis and ROC curve predicted the good efficiency of diagnostic model both in GSE98620 cohort and GSE6764 cohort. (E, F) Unsupervised hierarchical clustering indicated the level of BAK1 and CSE1L in HCC and dysplastic nodules.