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. 2019 Oct 8;10:4562. doi: 10.1038/s41467-019-12543-5

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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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Fig. 4 — Putatively regulatory effects of eRNAs on clinically actionable genes and immune checkpoints. a Correlation between eRNAs and clinically actionable genes in human cancers. Red dots denote significantly correlation. X-axis is cancer type and y-axis is symbol of gene. b Number of tissues with Hi-C interactions between clinically actionable genes and their eRNAs. c Hi-C interaction between MDM2 and MDM2e in blade. d Hi-C interaction between MYC and MYCe in lung. e Correlation between eRNA and cancer immune checkpoints in human cancers. f Number of tissues with remarkable Hi-C interaction between cancer immune checkpoints and their eRNA. g Hi-C interaction between CD200 and CD200e in ovary. Scale bars denote spearman correlation (Rs) in (a) and (e), and Hi-C O/E value in (b), (c), and (g), respectively