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. 2020 Sep 25;20:465. doi: 10.1186/s12935-020-01493-4

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© The Author(s) 2020

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Bioinformatics predicts the potential molecular mechanism of gastric cancer progression. a Venn program showed overlapped downregulated circRNA in gastric cancer from the circRNA microarray databases GSE83521 and GSE93541. b RT-qPCR determined the seven intersecting downregulated circRNA in gastric cancer biopsy specimens. c Potential miRs regulated by circ_002117 predicted by CircInteratome. d Venn analysis showed overlapped miRs from TargetScan-predicted target genes of miR-370 and the top 50 downregulated mRNAs in gastric cancer mRNA microarray data, GSE2685. e HERPUD1 expression in gastric cancer predicted by UALCAN. Data are shown as the mean ± standard deviation. Statistical comparisons were performed using unpaired t-test when only two groups were compared