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.

Necroptotic virotherapy of oncolytic alphavirus M1 cooperated with Doxorubicin displays promising therapeutic efficacy in TNBC

Abstract

Triple-negative breast cancer (TNBC) is the most aggressive molecular subtype among breast tumors and remains a challenge even for the most current therapeutic regimes. Here, we demonstrate that oncolytic alphavirus M1 effectively kills both TNBC and non-TNBC. ER-stress and apoptosis pathways are responsible for the cell death in non-TNBC as reported in other cancer types, yet the cell death in TNBC does not depend on these pathways. Transcriptomic analysis reveals that the M1 virus activates necroptosis in TNBC, which can be pharmacologically blocked by necroptosis inhibitors. By screening a library of clinically available compounds commonly used for breast cancer treatment, we find that Doxorubicin enhances the oncolytic effect of the M1 virus by up to 100-fold specifically in TNBC in vitro, and significantly stalls the tumor growth of TNBC in vivo, through promoting intratumoral virus replication and further triggering apoptosis in addition to necroptosis. These findings reveal a novel antitumor mechanism and a new combination regimen of the M1 oncolytic virus in TNBC, and highlight a need to bridge molecular diagnosis with virotherapy.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Oncolytic effect of M1 on TNBC and non-TNBC cells in vitro and in vivo.
Fig. 2: M1 triggers ER stress-mediated apoptosis in non-TNBC cells but not in TNBC cells.
Fig. 3: M1 triggers necroptosis-mediated death in TNBC cells.
Fig. 4: Combinatorial drug screen identifies Doxorubicin as the top sensitizer for M1 virus in TNBC cells.
Fig. 5: Doxorubicin inhibits the M1 virus-induced IFN signal by activating the GAS6/AXL pathway.
Fig. 6: Doxorubicin amplifies virus replication of M1, thus leading to necroptosis and apoptosis.
Fig. 7: Combinatorial Doxorubicin and M1 treatment is more effective than M1 alone in vivo.
Fig. 8: Graphical model of differential cell death induced by M1 virus in two breast cancer types and the synergic effect of Doxorubicin andM1 in TNBC.

References

  1. 1.

    Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70:7-30.

  2. 2.

    DeSantis CE, Ma J, Goding Sauer A, Newman LA, Jemal A. Breast cancer statistics, 2017, racial disparity in mortality by state. CA Cancer J Clin. 2017;67:439-448.

  3. 3.

    Dent R, Hanna WM, Trudeau M, Rawlinson E, Sun P, Narod SA. Pattern of metastatic spread in triple-negative breast cancer. Breast Cancer Res Treat. 2009;115:423–8.

    Article  Google Scholar 

  4. 4.

    Wahba HA, El-Hadaad HA. Current approaches in treatment of triple-negative breast cancer. Cancer Biol Med. 2015;12:106-16.

  5. 5.

    Adair RA, Roulstone V, Scott KJ, Morgan R, Nuovo GJ, Fuller M, et al. Cell carriage, delivery, and selective replication of an oncolytic virus in tumor in patients. Sci Transl Med. 2012;4:138–77.

    Google Scholar 

  6. 6.

    Miest TS, Cattaneo R. New viruses for cancer therapy: meeting clinical needs. Nat Rev Microbiol. 2014;12:23–34.

    CAS  Article  Google Scholar 

  7. 7.

    Cai J, Yan G. The identification and development of a novel oncolytic virus: alphavirus M1. Hum Gene Ther. 2021;32:138–49.

    CAS  Article  Google Scholar 

  8. 8.

    Rehman H, Silk AW, Kane MP, Kaufman HL. Into the clinic: talimogene laherparepvec (T-VEC), a first-in-class intratumoral oncolytic viral therapy. J Immunother Cancer. 2016;4:53.

    Article  Google Scholar 

  9. 9.

    Poh A. First oncolytic viral therapy for melanoma. Cancer Discov. 2016;6:6.

    PubMed  Google Scholar 

  10. 10.

    Russell SJ, Peng K-W, Bell JC. Oncolytic virotherapy. Nat Biotechnol. 2012;30:658–70.

    CAS  Article  Google Scholar 

  11. 11.

    Lawler SE, Speranza M-C, Cho C-F, Chiocca EA. Oncolytic viruses in cancer treatment: a review. JAMA Oncol. 2017;3:841–9.

    Article  Google Scholar 

  12. 12.

    Goradel NH, Baker AT, Arashkia A, Ebrahimi N, Ghorghanlu S, et al. Oncolytic virotherapy: Challenges and solutions. Curr Probl Cancer. 2021;45:100639.

  13. 13.

    Moskovskich A, Goldmann U, Kartnig F, Lindinger S, Konecka J, Fiume G, et al. The transporters SLC35A1 and SLC30A1 play opposite roles in cell survival upon VSV virus infection. Sci Rep. 2019;9:10471.

    Article  Google Scholar 

  14. 14.

    de Graaf JF, de Vor L, Fouchier RAM, van den Hoogen BG. Armed oncolytic viruses: a kick-start for anti-tumor immunity. Cytokine Growth Factor Rev. 2018;41:28–39.

    Article  Google Scholar 

  15. 15.

    Turnbull S, West EJ, Scott KJ, Appleton E, Melcher A, Ralph C. Evidence for oncolytic virotherapy: where have we got to and where are we going? Viruses. 2015;7:6291–312.

    CAS  Article  Google Scholar 

  16. 16.

    Wen J-S, Zhao W-Z, Liu J-W, Zhou H, Tao J-P, Yan H-J, et al. Genomic analysis of a Chinese isolate of Getah-like virus and its phylogenetic relationship with other Alphaviruses. Virus Genes. 2007;35:597–603.

    CAS  Article  Google Scholar 

  17. 17.

    Brown CM, Timoney PJ. Getah virus infection of Indian horses. Trop Anim Health Prod. 1998;30:241–52.

    CAS  Article  Google Scholar 

  18. 18.

    Zhang H, Lin Y, Li K, Liang J, Xiao X, et al. Naturally Existing Oncolytic Virus M1 Is Nonpathogenic for the Nonhuman Primates After Multiple Rounds of Repeated Intravenous Injections. Hum Gene Ther. 2016;27:700-11.

  19. 19.

    Pu Z-Q, Liu D, Lobo Mouguegue HPP, Jin C-W, Sadiq E, Qin D-D, et al. NR4A1 counteracts JNK activation incurred by ER stress or ROS in pancreatic β-cells for protection. J Cell Mol Med. 2020;24:14171–83.

    CAS  Article  Google Scholar 

  20. 20.

    Tan Y, Lin Y, Li K, Xiao X, Liang J, Cai J, et al. Selective antagonism of Bcl-xL potentiates M1 oncolysis by enhancing mitochondrial apoptosis. Hum Gene Ther. 2018;29:950–61.

    CAS  Article  Google Scholar 

  21. 21.

    Zhang H, Li K, Lin Y, Xing F, Xiao X, et al. Targeting VCP enhances anticancer activity of oncolytic virus M1 in hepatocellular carcinoma. Sci Transl Med. 2017;9:eaam7996.

  22. 22.

    Xiao X, Liang J, Huang C, Li K, Xing F, Zhu W, et al. DNA-PK inhibition synergizes with oncolytic virus M1 by inhibiting antiviral response and potentiating DNA damage. Nat Commun. 2018;9:4342.

    Article  Google Scholar 

  23. 23.

    Muhuri M, Gao G. Oncolytic virus alphavirus M1: a new and promising weapon to fight cancer. Hum Gene Ther 2021;32:136–7.

    CAS  Article  Google Scholar 

  24. 24.

    Hu J, Cai X-F, Yan G. Alphavirus M1 induces apoptosis of malignant glioma cells via downregulation and nucleolar translocation of p21WAF1/CIP1 protein. Cell Cycle. 2009;8:3328–39.

    CAS  Article  Google Scholar 

  25. 25.

    Lin Y, Zhang H, Liang J, Li K, Zhu W, Fu L, et al. Identification and characterization of alphavirus M1 as a selective oncolytic virus targeting ZAP-defective human cancers. Proc Natl Acad Sci USA. 2014;111:E4504–12.

    CAS  Article  Google Scholar 

  26. 26.

    Sun L, Wang H, Wang Z, He S, Chen S, Liao D, et al. Mixed lineage kinase domain-like protein mediates necrosis signaling downstream of RIP3 kinase. Cell. 2012;148:213–27.

    CAS  Article  Google Scholar 

  27. 27.

    Gong Y, Fan Z, Luo G, Yang C, Huang Q. et al. The role of necroptosis in cancer biology and therapy. Mol Cancer. 2019;18:100 https://doi.org/10.1186/s12943-019-1029-8.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Zhang J, Yang Y, He W, Sun L. Necrosome core machinery: MLKL. Cell Mol Life Sci. 2016;73:2153–63.

    CAS  Article  Google Scholar 

  29. 29.

    Tanzer MC, Matti I, Hildebrand JM, Young SN, Wardak A, Tripaydonis A, et al. Evolutionary divergence of the necroptosis effector MLKL. Cell Death Differ. 2016;23:1185–97.

    CAS  Article  Google Scholar 

  30. 30.

    Liu S, Liu H, Johnston A, Hanna-Addams S, Reynoso E, Xiang Y, et al. MLKL forms disulfide bond-dependent amyloid-like polymers to induce necroptosis. Proc Natl Acad Sci USA. 2017;114:E7450–9.

    CAS  Article  Google Scholar 

  31. 31.

    Budhwani M, Mazzieri R, Dolcetti R. Plasticity of type I interferon-mediated responses in cancer therapy: from anti-tumor immunity to resistance. Front Oncol. 2018;8:322.

    Article  Google Scholar 

  32. 32.

    Lazear HM, Schoggins JW, Diamond MS. Shared and distinct functions of type I and type III interferons. Immunity. 2019;50:907–23.

    CAS  Article  Google Scholar 

  33. 33.

    Kok F, Rosenblatt M, Teusel M, Nizharadze T, Gonçalves Magalhães V, Dächert C, et al. Disentangling molecular mechanisms regulating sensitization of interferon alpha signal transduction. Mol Syst Biol. 2020;16:e8955.

    CAS  Article  Google Scholar 

  34. 34.

    Willson J. A matter of life and death for caspase 8. Nat Rev Mol Cell Biol. 2020;21:63.

    CAS  Article  Google Scholar 

  35. 35.

    Silke J, Strasser A. The FLIP Side of Life. Sci Signal. 2013;15;6:pe2.

  36. 36.

    Vanlangenakker N, Berghe T Vanden, Bogaert P, Laukens B, Zobel K, Deshayes K, et al. cIAP1 and TAK1 protect cells from TNF-induced necrosis by preventing RIP1/RIP3-dependent reactive oxygen species production. Cell Death Differ. 2011;656–65.

  37. 37.

    Wu J, Mamidi TKK, Zhang L, Hicks C. Unraveling the genomic-epigenomic interaction landscape in triple negative and non-triple negative breast cancer. Cancers. 2020;12. https://doi.org/10.3390/cancers12061559.

  38. 38.

    Thorn CF, Oshiro C, Marsh S, Hernandez-Boussard T, McLeod H, et al. Doxorubicin pathways: pharmacodynamics and adverse effects. Pharmacogenet Genomics. 2011;21:440-6.

  39. 39.

    Forrest RA, Swift LP, Rephaeli A, Nudelman A, Kimura K-I, Phillips DR, et al. Activation of DNA damage response pathways as a consequence of anthracycline-DNA adduct formation. Biochem Pharm. 2012;83:1602–12.

    CAS  Article  Google Scholar 

  40. 40.

    Wen S-H, Su S-C, Liou B-H, Lin C-H, Lee K-R. Sulbactam-enhanced cytotoxicity of doxorubicin in breast cancer cells. Cancer Cell Int. 2018;18:128.

    Article  Google Scholar 

  41. 41.

    Pang B, Qiao X, Janssen L, Velds A, Groothuis T, Kerkhoven R, et al. Drug-induced histone eviction from open chromatin contributes to the chemotherapeutic effects of doxorubicin. Nat Commun. 2013;4:1908.

    Article  Google Scholar 

  42. 42.

    Yang F, Teves SS, Kemp CJ, Henikoff S. Doxorubicin, DNA torsion, and chromatin dynamics. Biochim Biophys Acta. 2014;1845:84–89.

    CAS  PubMed  Google Scholar 

  43. 43.

    Yang F, Kemp CJ, Henikoff S. Doxorubicin enhances nucleosome turnover around promoters. Curr Biol. 2013;23:782–7.

    CAS  Article  Google Scholar 

  44. 44.

    Garrido-Castro AC, Lin NU, Polyak K. Insights into molecular classifications of triple-negative breast cancer: improving patient selection for treatment. Cancer Discov. 2019;9:176–98.

    CAS  Article  Google Scholar 

  45. 45.

    Zhu W, Liang J, Tan J, Guo L, Cai J, Hu J, et al. Real-time visualization and quantification of oncolytic M1 virus in vitro and in vivo. Hum Gene Ther. 2021;32:158–65.

    CAS  Article  Google Scholar 

  46. 46.

    Jensen EC. Quantitative analysis of histological staining and fluorescence using ImageJ. Anat Rec. 2013;296:378–81.

    Article  Google Scholar 

  47. 47.

    Trapnell C, Pachter, L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25:1105–11.

  48. 48.

    Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.

  49. 49.

    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.

  50. 50.

    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.

    CAS  Article  Google Scholar 

  51. 51.

    Reimand J, Isserlin R, Voisin V, Kucera M, Tannus-Lopes C, Rostamianfar A, et al. Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap. Nat Protoc. 2019;14:482–517.

    CAS  Article  Google Scholar 

  52. 52.

    Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinform. 2013;14:7.

    Article  Google Scholar 

Download references

Acknowledgements

We thank all authors who contributed to this work. This work was supported by the National Natural Science Foundation of China (No. 81872886), Fundamental Research Funds for the Central Universities (19ykpy36 and 19ykpy166), Guangdong Basic and Applied Basic Research Foundation (2020A1515011446), Pioneering talents project of Guangzhou Development Zone, Guangdong Province (CY2018-012), and Leading Team for Entrepreneurship in Guangzhou, Guangdong Province (201809020004).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Wenbo Zhu.

Ethics declarations

Competing interests

The 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

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhang, J., Liu, Y., Tan, J. et al. Necroptotic virotherapy of oncolytic alphavirus M1 cooperated with Doxorubicin displays promising therapeutic efficacy in TNBC. Oncogene 40, 4783–4795 (2021). https://doi.org/10.1038/s41388-021-01869-4

Download citation

Search

Quick links