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. 2019 Jul 4;9:9715. doi: 10.1038/s41598-019-46064-4

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© The Author(s) 2019

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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Kaplan-Meier survival analysis based on categorized gene expression levels of the HOTPAM9 genes. (a) Kaplan-Meier survival curves based on categorized gene expression levels for all the HOTPAM9 genes (n = 223). Overall survival stratified based on high or low gene expression analysis for the Moffitt TCC data set. For all the HOTPAM9 genes the overall log rank test is significant. p value between primary groups is shown in each plot (left two panels). Kaplan-Meier Recurrence-Free survival (RFS) curves are based on categorized gene expression levels for all the HOTPAM9 genes (n = 173). For RFS in the MSKCC data set, the overall log rank tests are all significant (right two panels). (b) Performance of statistical stratification model built on the basis of gene expression data of CIT/STK21 and HSPB8 as biomarkers to distinguish indolent from aggressive disease in MSKCC training data set. Stratification scores for the aggressive disease were compared between patients with primary tumors and those with metastatic tumors (left). ROC curve analysis was used to evaluate an ability to distinguish patients with primary cancer from those with metastatic disease (right). (c) Performance of the stratification model on Moffitt TCC data set by dividing patients’ classification scores at the optimal threshold (left). ROC curve was used to evaluate overall performance of the stratification model (right).