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. 2017 Oct 16;7:13190. doi: 10.1038/s41598-017-13196-4

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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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A 14-gene expression signature predicts disease free survival in ccRCC. (A) Workflow diagram of selecting 14 genes correlated to 9 VF’s and training of two outcomes prediction models in the discovery cohort (N = 64). The 14VF classifier was trained on the risk groups defined by 9VF’s. The 14GT classifier was trained on 24-months disease free survival status. (B) Supervised clustering based on low risk (blue) and high risk (red) groups obtained from the 14VF model in the validation cohort (N = 301). (C) Kaplan-Meier plot of the 14VF model (n = 207, log-rank test p < 0.001, HR = 2.3). (D) Kaplan-Meier plot of the 14GT model (n = 257, log-rank test p < 0.001, HR = 3.33).