Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Targeting the IRE1α-XBP1s axis confers selective vulnerability in hepatocellular carcinoma with activated Wnt signaling

Oncogene volume 43, pages 1233–1248 (2024)Cite this article

Subjects

Abstract

Liver-specific Ern1 knockout impairs tumor progression in mouse models of hepatocellular carcinoma (HCC). However, the mechanistic role of IRE1α in human HCC remains unclear. In this study, we show that XBP1s, the major downstream effector of IRE1α, is required for HCC cell survival both in vitro and in vivo. Mechanistically, XBP1s transactivates LEF1, a key co-factor of β-catenin, by binding to its promoter. Moreover, XBP1s physically interacts with LEF1, forming a transcriptional complex that enhances classical Wnt signaling. Consistently, the activities of XBP1s and LEF1 are strongly correlated in human HCC and with disease prognosis. Notably, selective inhibition of XBP1 splicing using an IRE1α inhibitor significantly repressed the viability of tumor explants as well as the growth of tumor xenografts derived from patients with distinct Wnt/LEF1 activities. Finally, machine learning algorithms developed a powerful prognostic signature based on the activities of XBP1s/LEF1. In summary, our study uncovers a key mechanistic role for the IRE1α-XBP1s pathway in human HCC. Targeting this axis could provide a promising therapeutic strategy for HCC with hyperactivated Wnt/LEF1 signaling.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: XBP1s activity is correlated with human HCC development.
Fig. 2: Genetic or pharmacological inhibition of XBP1s impairs the cell growth of HCC.
Fig. 3: XBP1s transcriptionally activates LEF1 to facilitate classical Wnt signaling.
Fig. 4: XBP1s cooperates with LEF1 to regulate target gene expression.
Fig. 5: XBP1s and LEF1 are functionally linked in human HCC.
Fig. 6: Selective targeting of XBP1s in preclinical models derived from patients with HCC.
Fig. 7: Construction and validation of the XBP1s/LEF1 combined HCC prognostic model.

Similar content being viewed by others

Data availability

The RNA-seq and ChIP-seq data is archived in the GEO database (GSE164615) and available to all. Other data that support the findings of this study is available from the corresponding author upon request.

References

  1. Llovet JM, Castet F, Heikenwalder M, Maini MK, Mazzaferro V, Pinato DJ, et al. Immunotherapies for hepatocellular carcinoma. Nat Rev Clin Oncol. 2022;19:151–72.

    Article  CAS  PubMed  Google Scholar 

  2. Hou J, Zhang H, Sun B, Karin M. The immunobiology of hepatocellular carcinoma in humans and mice: basic concepts and therapeutic implications. J Hepatol. 2020;72:167–82.

    Article  CAS  PubMed  Google Scholar 

  3. Rebouissou S, Nault JC. Advances in molecular classification and precision oncology in hepatocellular carcinoma. J Hepatol. 2020;72:215–29.

    Article  CAS  PubMed  Google Scholar 

  4. Finn RS, Zhu AX. Evolution of Systemic Therapy for Hepatocellular Carcinoma. Hepatology. 2021;73 Suppl 1:150−7.

  5. Perugorria MJ, Olaizola P, Labiano I, Esparza-Baquer A, Marzioni M, Marin JJG, et al. Wnt-beta-catenin signalling in liver development, health and disease. Nat Rev Gastroenterol Hepatol. 2019;16:121–36.

    Article  CAS  PubMed  Google Scholar 

  6. Santiago L, Daniels G, Wang D, Deng FM, Lee P. Wnt signaling pathway protein LEF1 in cancer, as a biomarker for prognosis and a target for treatment. Am J Cancer Res. 2017;7:1389–406.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Ron D, Walter P. Signal integration in the endoplasmic reticulum unfolded protein response. Nat Rev Mol Cell Biol. 2007;8:519–29.

    Article  CAS  PubMed  Google Scholar 

  8. Zhang T, Li N, Sun C, Jin Y, Sheng X. MYC and the unfolded protein response in cancer: synthetic lethal partners in crime? EMBO Mol Med. 2020;12:e11845.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Walter P, Ron D. The unfolded protein response: from stress pathway to homeostatic regulation. Science. 2011;334:1081–6.

    Article  CAS  PubMed  Google Scholar 

  10. Yoshida H, Matsui T, Yamamoto A, Okada T, Mori K. XBP1 mRNA is induced by ATF6 and spliced by IRE1 in response to ER stress to produce a highly active transcription factor. Cell. 2001;107:881–91.

    Article  CAS  PubMed  Google Scholar 

  11. Calfon M, Zeng H, Urano F, Till JH, Hubbard SR, Harding HP, et al. IRE1 couples endoplasmic reticulum load to secretory capacity by processing the XBP-1 mRNA. Nature. 2002;415:92–6.

    Article  CAS  PubMed  Google Scholar 

  12. Lerner AG, Upton JP, Praveen PV, Ghosh R, Nakagawa Y, Igbaria A, et al. IRE1alpha induces thioredoxin-interacting protein to activate the NLRP3 inflammasome and promote programmed cell death under irremediable ER stress. Cell Metab. 2012;16:250–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Sheng X, Nenseth HZ, Qu S, Kuzu OF, Frahnow T, Simon L, et al. IRE1alpha-XBP1s pathway promotes prostate cancer by activating c-MYC signaling. Nat Commun. 2019;10:323.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Zhao N, Cao J, Xu L, Tang Q, Dobrolecki LE, Lv X, et al. Pharmacological targeting of MYC-regulated IRE1/XBP1 pathway suppresses MYC-driven breast cancer. J Clin Investig. 2018;128:1283–99.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Logue SE, McGrath EP, Cleary P, Greene S, Mnich K, Almanza A, et al. Inhibition of IRE1 RNase activity modulates the tumor cell secretome and enhances response to chemotherapy. Nat Commun. 2018;9:3267.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Wang Y, Wang K, Jin Y, Sheng X. Endoplasmic reticulum proteostasis control and gastric cancer. Cancer Lett. 2019;449:263–71.

    Article  CAS  PubMed  Google Scholar 

  17. Lhomond S, Avril T, Dejeans N, Voutetakis K, Doultsinos D, McMahon M, et al. Dual IRE1 RNase functions dictate glioblastoma development. EMBO Mol Med. 2018;10:e7929.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Lebeaupin C, Vallee D, Hazari Y, Hetz C, Chevet E, Bailly-Maitre B. Endoplasmic reticulum stress signalling and the pathogenesis of non-alcoholic fatty liver disease. J Hepatol. 2018;69:927–47.

    Article  CAS  PubMed  Google Scholar 

  19. Hetz C, Axten JM, Patterson JB. Pharmacological targeting of the unfolded protein response for disease intervention. Nat Chem Biol. 2019;15:764–75.

    Article  CAS  PubMed  Google Scholar 

  20. Marciniak SJ, Chambers JE, Ron D. Pharmacological targeting of endoplasmic reticulum stress in disease. Nat Rev Drug Discov. 2022;21:115–40.

    Article  CAS  PubMed  Google Scholar 

  21. Fang P, Xiang L, Huang S, Jin L, Zhou G, Zhuge L, et al. IRE1alpha-XBP1 signaling pathway regulates IL-6 expression and promotes progression of hepatocellular carcinoma. Oncol Lett. 2018;16:4729–36.

    PubMed  PubMed Central  Google Scholar 

  22. Wu S, Du R, Gao C, Kang J, Wen J, Sun T. The role of XBP1s in the metastasis and prognosis of hepatocellular carcinoma. Biochem Biophys Res Commun. 2018;500:530–7.

    Article  CAS  PubMed  Google Scholar 

  23. Wu Y, Shan B, Dai J, Xia Z, Cai J, Chen T, et al. Dual role for inositol-requiring enzyme 1alpha in promoting the development of hepatocellular carcinoma during diet-induced obesity in mice. Hepatology. 2018;68:533–46.

    Article  CAS  PubMed  Google Scholar 

  24. Shin GC, Moon SU, Kang HS, Choi HS, Han HD, Kim KH. PRKCSH contributes to tumorigenesis by selective boosting of IRE1 signaling pathway. Nat Commun. 2019;10:3185.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Yang TH, Chiang YH, Shiue SC, Lin PH, Yang YC, Tu KC, et al. Cancer DEIso: an integrative analysis platform for investigating differentially expressed gene-level and isoform-level human cancer markers. Comput Struct Biotechnol J. 2021;19:5149–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lu Y, Yang A, Quan C, Pan Y, Zhang H, Li Y, et al. A single-cell atlas of the multicellular ecosystem of primary and metastatic hepatocellular carcinoma. Nat Commun. 2022;13:4594.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Sanches M, Duffy NM, Talukdar M, Thevakumaran N, Chiovitti D, Canny MD, et al. Structure and mechanism of action of the hydroxy-aryl-aldehyde class of IRE1 endoribonuclease inhibitors. Nat Commun. 2014;5:4202.

    Article  CAS  PubMed  Google Scholar 

  28. Chen X, Iliopoulos D, Zhang Q, Tang Q, Greenblatt MB, Hatziapostolou M, et al. XBP1 promotes triple-negative breast cancer by controlling the HIF1alpha pathway. Nature. 2014;508:103–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Pramanik J, Chen X, Kar G, Henriksson J, Gomes T, Park JE, et al. Genome-wide analyses reveal the IRE1a-XBP1 pathway promotes T helper cell differentiation by resolving secretory stress and accelerating proliferation. Genome Med. 2018;10:76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Hu F, Guo L, Yu J, Dai D, Xiong Y, He Y, et al. Using patient-derived xenografts to explore the efficacy of treating head-and-neck squamous cell carcinoma with anlotinib. Pathol Oncol Res. 2021;27:1610008.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Harnoss JM, Le Thomas A, Shemorry A, Marsters SA, Lawrence DA, Lu M, et al. Disruption of IRE1alpha through its kinase domain attenuates multiple myeloma. Proc Natl Acad Sci USA. 2019;116:16420–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Wei M, Nurjanah U, Herkilini A, Huang C, Li Y, Miyagishi M, et al. Unspliced XBP1 contributes to cholesterol biosynthesis and tumorigenesis by stabilizing SREBP2 in hepatocellular carcinoma. Cell Mol Life Sci. 2022;79:472.

    Article  CAS  PubMed  Google Scholar 

  34. Chen X, Cubillos-Ruiz JR. Endoplasmic reticulum stress signals in the tumour and its microenvironment. Nat Rev Cancer. 2021;21:71–88.

    Article  CAS  PubMed  Google Scholar 

  35. Xia Z, Wu S, Wei X, Liao Y, Yi P, Liu Y, et al. Hypoxic ER stress suppresses beta-catenin expression and promotes cooperation between the transcription factors XBP1 and HIF1alpha for cell survival. J Biol Chem. 2019;294:13811–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Crowley MJP, Bhinder B, Markowitz GJ, Martin M, Verma A, Sandoval TA, et al. Tumor-intrinsic IRE1alpha signaling controls protective immunity in lung cancer. Nat Commun. 2023;14:120.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Xie H, Tang CH, Song JH, Mancuso A, Del Valle JR, Cao J, et al. IRE1alpha RNase-dependent lipid homeostasis promotes survival in Myc-transformed cancers. J Clin Investig. 2018;128:1300–16.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Dong H, Adams NM, Xu Y, Cao J, Allan DSJ, Carlyle JR, et al. The IRE1 endoplasmic reticulum stress sensor activates natural killer cell immunity in part by regulating c-Myc. Nat Immunol. 2019;20:865–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Le Reste PJ, Pineau R, Voutetakis K, Samal J, Jegou G, Lhomond S, et al. Local intracerebral inhibition of IRE1 by MKC8866 sensitizes glioblastoma to irradiation/chemotherapy in vivo. Cancer Lett. 2020;494:73–83.

    Article  PubMed  Google Scholar 

  40. Xiao R, You L, Zhang L, Guo X, Guo E, Zhao F, et al. Inhibiting the IRE1alpha Axis of the unfolded protein response enhances the antitumor effect of AZD1775 in TP53 mutant ovarian cancer. Adv Sci. 2022;9:e2105469.

    Article  Google Scholar 

  41. Wang Q, Zhou H, Bu Q, Wei S, Li L, Zhou J, et al. Role of XBP1 in regulating the progression of non-alcoholic steatohepatitis. J Hepatol. 2022;77:312–25.

    Article  CAS  PubMed  Google Scholar 

  42. Sheng X, Arnoldussen YJ, Storm M, Tesikova M, Nenseth HZ, Zhao S, et al. Divergent androgen regulation of unfolded protein response pathways drives prostate cancer. EMBO Mol Med. 2015;7:788–801.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Zhou H, Zhang T, Chen L, Cui F, Xu C, Peng J, et al. The functional implication of ATF6alpha in castration-resistant prostate cancer cells. FASEB J. 2023;37:e22758.

    Article  CAS  PubMed  Google Scholar 

  44. Shu J, Dolman GE, Duan J, Qiu G, Ilyas M. Statistical colour models: an automated digital image analysis method for quantification of histological biomarkers. Biomed Eng Online. 2016;15:46.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Cui F, Pan Q, Wang S, Zhao F, Wang R, Zhang T, et al. Maternal benzophenone exposure impairs hippocampus development and cognitive function in mouse offspring. Adv Sci. 2021;8:e2102686.

    Article  Google Scholar 

  46. Liu R, Holik AZ, Su S, Jansz N, Chen K, Leong HS, et al. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. Nucleic Acids Res. 2015;43:e97.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 2003;34:267–73.

    Article  CAS  PubMed  Google Scholar 

  48. Shi C, Zhao F, Zhang T, Xu D, Hao Z, Cui F, et al. A novel prognostic signature in osteosarcoma characterised from the perspective of unfolded protein response. Clin Transl Med. 2022;12:e750.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Breiman L. Random forests. Mach Learn. 2001;45:5–32.

    Article  Google Scholar 

Download references

Funding

This study was supported by National Key R&D Program of China (2022YFA0807000) and Chinese Civil-Military Integration Program (145BGQ090003060X) to XS, the Fundamental Research Funds for the Central Universities (YCJJ202201011) to TZ, Young and Middle-aged Discipline Leader of Henan Provincial Health Commission (HNSWJW-2020027) and Excellent Young Scholar Fund of Natural Science Foundation of Henan Province (222300420072) to YZ, National Natural Science Foundation of China (81972752) to YJ, and Hepatobiliary Research Foundation of Henan Digestive Disease Association (GDXZ2019004) to JHS.

Author information

Author notes

  1. These authors contributed equally: Tingting Zhang, Faming Zhao, Yi Zhang.

Authors and Affiliations

  1. Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China

    Tingting Zhang, Faming Zhao, Fengzhen Cui, Weixiang Ma, Rong Zhong & Xia Sheng

  2. Department of Hepatobiliary and Pancreatic Surgery, Henan Key Laboratory of Digestive Organ transplantation, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450052, China

    Yi Zhang, Ji-Hua Shi, Kai Wang & Yang Jin

  3. Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China

    Yi Zhang

  4. School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China

    Chuanrui Xu

  5. Fosun Orinove PharmaTech Inc., Suzhou Industrial Park, Suzhou, 215123, China

    Qingping Zeng

  6. Tomas Lindahl Nobel Laureate Laboratory, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, China

    Ningning Li

  7. College of Life Sciences, Wuhan University, Wuhan, 430072, China

    Yong Liu

  8. School of Life and Health Sciences, Hainan University, Haikou, 570228, China

    Xia Sheng

Authors
  1. Tingting Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Faming Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ji-Hua Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fengzhen Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weixiang Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kai Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Chuanrui Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Qingping Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Rong Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ningning Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Yong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Yang Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Xia Sheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

TZ performed most of the experiments and helped in writing the manuscript. FZ performed bioinformatics analysis and helped in writing the manuscript. YZ helped in designing the study, constructed the TMA, and revised the manuscript. FC and WM contributed to experiments and data analyses. KW helped in TMA analyses. CX provided mouse HCC materials. QZ provided the MKC8866 compound. JHS, RZ, NL, YL, and YJ helped in data analyses and revised the manuscript. XS conceived the project, supervised the work, and wrote the manuscript. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Xia Sheng.

Ethics declarations

Competing interests

QZ is a shareholder of Fosun Orinove. Other authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, T., Zhao, F., Zhang, Y. et al. Targeting the IRE1α-XBP1s axis confers selective vulnerability in hepatocellular carcinoma with activated Wnt signaling. Oncogene 43, 1233–1248 (2024). https://doi.org/10.1038/s41388-024-02988-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41388-024-02988-4

Search

Advanced search

Quick links