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. 2020 Aug 17;20:771. doi: 10.1186/s12885-020-07277-3

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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. 8 — Relationship between risk-associated ARGs and drug resistance. The plots represent the correlation of (a) HDAC1, (b) RHEB and (c) SQSTM1 expression with the IC50 of several specific drugs in the liver cell lines. Red dots represent positive correlation between IC50 of the drug and the expression level of risk-associated ARGs, which indicates increased drug resistance with higher ARG expression (p < 0.05). Conversely, green dots represent negatively correlated drugs’ IC50 with the expression of risk-associated ARGs, indicating increased drug sensitivity with higher ARG expression (p < 0.05). These plots were created using R software v3.6.1