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Systems analysis identifies endothelin 1 axis blockade for enhancing the anti-tumor effect of multikinase inhibitor

Cancer Gene Therapy volume 29, pages 845–858 (2022)Cite this article

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Abstract

Multikinase inhibitors, such as sorafenib, are used for the treatment of advanced carcinomas but the response shows limited efficacy or varies a lot with patients. Here we adopted the systems approach combined with high-throughput data analysis to discover key mechanism embedded in the drug response. When analyzing the transcriptomic data from the Cancer Cell Line Encyclopedia (CCLE) database, endothelin 1 (EDN1) was enriched in cancer cells with low responsiveness to sorafenib. We found that the level of EDN1 is higher in the tissue and blood of hepatocellular carcinoma (HCC) patients showing poor response to sorafenib. In vitro experiment showed that EDN1 not only induces activation of angiogenic-promoting pathways in HCC cells but also stimulates proliferation and migration. Moreover, EDN1 is related with poor responsiveness to sorafenib by mitigating unfolded protein response (UPR), which was validated in both transcriptomic data analysis and in silico simulation. Finally, we found that endothelin receptor B (EDNRB) antagonists can enhance the efficacy of sorafenib in both HCC cells and xenograft mouse models. Our findings provide that EDN1 is a novel diagnostic marker for sorafenib responsiveness in HCC and a basis for testing macitentan, which is currently used for pulmonary artery hypertension, in combination with sorafenib in advanced HCC patients.

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Fig. 1: EDN1 expression level determines different responses to sorafenib treatment.
Fig. 2: The comparison of EDN1 levels between the responder group and the non-responder group.
Fig. 3: EDN1 affects the efficacy of sorafenib and EDNRB antagonists sensitize HCC cells to sorafenib.
Fig. 4: EDN1 blunts sorafenib-induced changes in the ER stress response.
Fig. 5: Simulation of the EDN1-regulated UPR signaling network.
Fig. 6: The combination treatment with macitentan and sorafenib reduced tumor growth in vivo.

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Data availability

The python code for the signal flow analysis is available at https://github.com/dwgoon/sfa. All codes related to this paper may be requested from the authors. The GEO accession numbers for RNA-seq data is GSE178280.

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Acknowledgements

We thank Nancy R Gough (BioSerendipity, LLC) for constructive input and editorial support. This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea Government, the Ministry of Science and ICT (2020R1A2B5B03094920), and Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean government (21ZS1100, Core Technology Research for Self-Improving Integrated Artificial Intelligence System). It was also supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science & ICT (2021M3A9I4024447) and partially supported by grants from the SNUH Research Fund (number 03-2018-0390) and the Liver Research Foundation of Korea, and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1277).

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Author notes

  1. These authors contributed equally: Chae Young Hwang, Su Jong Yu, Jae-Kyung Won, Sang-Min Park.

  2. These authors jointly supervised this work: Jung-Hwan Yoon, Kwang-Hyun Cho.

Authors and Affiliations

  1. Laboratory for Systems Biology and Bio-inspired Engineering, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea

    Chae Young Hwang, Jae-Kyung Won, Sang-Min Park, Soobeom Lee & Kwang-Hyun Cho

  2. Aventi, Inc., Daejeon, Korea

    Chae Young Hwang

  3. Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea

    Su Jong Yu, Hyojin Noh, Eun Ju Cho, Jeong-Hoon Lee, Yoon Jun Kim & Jung-Hwan Yoon

  4. Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea

    Jae-Kyung Won & Kyung Bun Lee

  5. KM Data Division, Korea Institute of Oriental Medicine, Daejeon, Korea

    Sang-Min Park

  6. Department of Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea

    Kyung-Suk Suh

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Contributions

CYH, SJY, and J-KW designed and performed experiments, collected and analyzed the data, interpreted the results, and wrote the manuscript. S-MP conducted modeling, analysis, and wrote the manuscript. SL and KBL provided analytical support, and HN, EJC, and J-HL provided experimental support. YJK and K-SS contributed to the acquisition of data, analysis and interpretation of data, and material support. J-HY and K-HC designed the experiments, interpreted the results, coordinated the study, and wrote the paper. K-HC designed the project and supervised the study. All authors contributed to writing and providing feedback.

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Correspondence to Kwang-Hyun Cho.

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Hwang, C.Y., Yu, S.J., Won, JK. et al. Systems analysis identifies endothelin 1 axis blockade for enhancing the anti-tumor effect of multikinase inhibitor. Cancer Gene Ther 29, 845–858 (2022). https://doi.org/10.1038/s41417-021-00373-x

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