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. 2017 Jul 17;7:5517. doi: 10.1038/s41598-017-04811-5

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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External and internal validation of the three-gene prognostic model. Two independent expression microarray HCC data sets GSE54236 (A) and GSE14520 (B) were downloaded from the GEO and were used as the signature validation cohort. The risk scores were calculated as Prognostic Index (PI) = 0.384 × RTN3-0.561 × SOCS2-0.434 × UPB1. (C) Kaplan-Meier curves of overall survival in the TCGA cohort stratified by the three-gene prognostic signature. We used the time-dependent ROC curve analysis to assessed the prognostic accuracy of the three-gene prognostic signature of the microarray data and LIHC dataset (Fig. 3A lower panel, Fig. 3B lower panel, Fig. 3C lower panel). ROC: receiver operator characteristic. AUC: area under the curve. (D) Kaplan–Meier curves of HCC patients based on the SOCS2 (left panel), RTN3 (middle panel), or UPB1 (right panel) expression level. 360 patients were sorted by the RSEM values of a gene, and the lower third of the patients was defined as the low mRNA expression, the upper third as high mRNA expression, thus divided patients into 3 groups. (E) The survival curve of HCC patients stratified by T stage and gene expression. Firstly, 360 patients were divided into two groups based on SOCS2 (left panel), RTN3 (middle panel), or UPB1 (right panel) expression. The cutoff value of high and low expression was set as the median. Then, patients were classified into three subgroups according to the T stage. (F) Survival curves of 360 HCC patients based on the combination of RTN3 and UPB1 (left panel), RTN3 and SOCS2 (middle panel), SOCS2 and UPB1 (right panel) expression. The cutoff value of high and low expression was set as the median.