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. 2019 May 6;9:6917. doi: 10.1038/s41598-019-43294-4

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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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IL-7- and IL-7Rα-expressing prostate cancers showed enrichment of epithelial–mesenchymal transition (EMT) and cancer stem cells gene sets. Public data sets for prostate cancer samples (n = 551) were collected from The Cancer Genome Atlas and subjected to gene set enrichment analysis (GSEA). (A) The patient gene expression profiles were categorized after correlating IL-7Rα and IL-7 expression distributions. The top and bottom 10% of the population were defined as the IL-7Rα^high IL-7^high and IL-7Rα^low IL-7^low groups (n = 55 each), respectively. (B) GSEA plots indicate significant enrichment of cancer stem cells and EMT in the IL-7Rα^highIL-7^high compared with IL-7Rα^lowIL-7^low patient groups. Genes were ordered according to their ranked ratios, and GSEA was performed using the GSEA tool at http://www.broad.mit.edu/gsea. The plot (black curve) shows the enrichment score (ES), a running-sum statistic, for ranked genes compared with cancer stem cells (upper panel) and EMT (lower panel) gene set. The normalized enrichment scores (NESs) and nominal P-values are indicated. Colors are mRNA expression levels of each gene normalized by the Z score transformation.