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:

RNA binding protein RBMS3 is a common EMT effector that modulates triple-negative breast cancer progression via stabilizing PRRX1 mRNA

Oncogene volume 40, pages 6430–6442 (2021)Cite this article

Subjects

Abstract

The epithelial-to-mesenchymal transition (EMT) has been recognized as a driving force for tumor progression in breast cancer. Recently, our group identified the RNA Binding Motif Single Stranded Interacting Protein 3 (RBMS3) to be significantly associated with an EMT transcriptional program in breast cancer. Additional expression profiling demonstrated that RBMS3 was consistently upregulated by multiple EMT transcription factors and correlated with mesenchymal gene expression in breast cancer cell lines. Functionally, RBMS3 was sufficient to induce EMT in two immortalized mammary epithelial cell lines. In triple-negative breast cancer (TNBC) models, RBMS3 was necessary for maintaining the mesenchymal phenotype and invasion and migration in vitro. Loss of RBMS3 significantly impaired both tumor progression and spontaneous metastasis in vivo. Using a genome-wide approach to interrogate mRNA stability, we found that ectopic expression of RBMS3 upregulates many genes that are resistant to degradation following transcriptional blockade by actinomycin D (ACTD). Specifically, RBMS3 was shown to interact with the mRNA of EMT transcription factor PRRX1 and promote PRRX1 mRNA stability. PRRX1 is required for RBMS3-mediated EMT and is partially sufficient to rescue the effect of RBMS3 knockdown in TNBC cell lines. Together, this study identifies RBMS3 as a novel and common effector of EMT, which could be a promising therapeutic target for TNBC treatment.

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: RBMS3 is commonly upregulated during EMT and associated with EMT-like gene expression in breast cancer cells.
Fig. 2: RBMS3 induces EMT and maintains mesenchymal differentiation.
Fig. 3: RBMS3 is required for mesenchymal gene expression and cell migration/invasion in TNBC.
Fig. 4: RBMS3 is required for tumor progression and spontaneous metastasis in vivo.
Fig. 5: RBMS3 regulates the expression and stability of PRRX1 mRNA.
Fig. 6: PRRX1 is a critical effector of RBMS3-mediated EMT and cell motility in human mammary epithelial cells.
Fig. 7: PRRX1 plays a vital role in RBMS3-mediated EMT and motility in TNBC cells.
Fig. 8: The RBMS3 working model.

Similar content being viewed by others

Data availability

Microarray data that support the funding of this study have been deposited in the GEO under accession number GSE181322. RNA-seq data that support the finding of this study have been deposited in the GEO under accession number GSE181237.

References

  1. Kalluri R, Weinberg RA. The basics of epithelial-mesenchymal transition. J Clin Invest. 2009;119:1420–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Thiery JP, Acloque H, Huang RY, Nieto MA. Epithelial-mesenchymal transitions in development and disease. Cell. 2009;139:871–90.

    Article  CAS  PubMed  Google Scholar 

  3. Mani SA, Guo W, Liao MJ, Eaton EN, Ayyanan A, Zhou AY, et al. The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell. 2008;133:704–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Meng F, Speyer CL, Zhang B, Zhao Y, Chen W, Gorski DH, et al. PDGFRalpha and beta play critical roles in mediating Foxq1-driven breast cancer stemness and chemoresistance. Cancer Res. 2015;75:584–93.

    Article  CAS  PubMed  Google Scholar 

  5. Polyak K, Weinberg RA. Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nat Rev Cancer. 2009;9:265–73.

    Article  CAS  PubMed  Google Scholar 

  6. Shibue T, Weinberg RA. EMT, CSCs, and drug resistance: the mechanistic link and clinical implications. Nat Rev Clin Oncol. 2017;14:611–29.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Aiello NM, Kang Y. Context-dependent EMT programs in cancer metastasis. J Exp Med. 2019;216:1016–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Yeung KT, Yang J. Epithelial-mesenchymal transition in tumor metastasis. Mol Oncol. 2017;11:28–39.

    Article  PubMed  Google Scholar 

  9. Davis FM, Stewart TA, Thompson EW, Monteith GR. Targeting EMT in cancer: opportunities for pharmacological intervention. Trends Pharm Sci. 2014;35:479–88.

    Article  CAS  PubMed  Google Scholar 

  10. Marcucci F, Stassi G, De Maria R. Epithelial-mesenchymal transition: a new target in anticancer drug discovery. Nat Rev Drug Discov. 2016;15:311–25.

    Article  CAS  PubMed  Google Scholar 

  11. Pasquier J, Abu-Kaoud N, Al Thani H, Rafii A. Epithelial to mesenchymal transition in a clinical perspective. J Oncol. 2015;2015:792182.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Stemmler MP, Eccles RL, Brabletz S, Brabletz T. Non-redundant functions of EMT transcription factors. Nat Cell Biol. 2019;21:102–12.

    Article  CAS  PubMed  Google Scholar 

  13. Taube JH, Herschkowitz JI, Komurov K, Zhou AY, Gupta S, Yang J, et al. Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes. Proc Natl Acad Sci USA. 2010;107:15449–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Morel AP, Hinkal GW, Thomas C, Fauvet F, Courtois-Cox S, Wierinckx A, et al. EMT inducers catalyze malignant transformation of mammary epithelial cells and drive tumorigenesis towards claudin-low tumors in transgenic mice. PLoS Genet. 2012;8:e1002723.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Blanco MJ, Moreno-Bueno G, Sarrio D, Locascio A, Cano A, Palacios J, et al. Correlation of Snail expression with histological grade and lymph node status in breast carcinomas. Oncogene. 2002;21:3241–6.

    Article  CAS  PubMed  Google Scholar 

  16. Wang J, Ye Q, Cao Y, Guo Y, Huang X, Mi W, et al. Snail determines the therapeutic response to mTOR kinase inhibitors by transcriptional repression of 4E-BP1. Nat Commun. 2017;8:2207.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Park SY, Kim MJ, Park SA, Kim JS, Min KN, Kim DK, et al. Combinatorial TGF-beta attenuation with paclitaxel inhibits the epithelial-to-mesenchymal transition and breast cancer stem-like cells. Oncotarget. 2015;6:37526–43.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Addison JB, Voronkova MA, Fugett JH, Lin CC, Linville NC, Trinh B, et al. Functional hierarchy and cooperation of EMT master transcription factors in breast cancer metastasis. Mol Cancer Res. 2021;19:784–98.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Fritz D, Stefanovic B. RNA-binding protein RBMS3 is expressed in activated hepatic stellate cells and liver fibrosis and increases expression of transcription factor Prx1. J Mol Biol. 2007;371:585–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Jayasena CS, Bronner ME. Rbms3 functions in craniofacial development by posttranscriptionally modulating TGF-beta signaling. J Cell Biol. 2012;199:453–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Creighton CJ, Li X, Landis M, Dixon JM, Neumeister VM, Sjolund A, et al. Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features. Proc Natl Acad Sci USA. 2009;106:13820–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ghandi M, Huang FW, Jane-Valbuena J, Kryukov GV, Lo CC, McDonald ER 3rd, et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature. 2019;569:503–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zhang P, Sun Y, Ma L. ZEB1: at the crossroads of epithelial-mesenchymal transition, metastasis and therapy resistance. Cell Cycle. 2015;14:481–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Block CJ, Dyson G, Campeanu IJ, Watza D, Ratnam M, Wu G. A stroma-corrected ZEB1 transcriptional signature is inversely associated with antitumor immune activity in breast cancer. Sci Rep. 2019;9:17807.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Lombaerts M, van Wezel T, Philippo K, Dierssen JW, Zimmerman RM, Oosting J, et al. E-cadherin transcriptional downregulation by promoter methylation but not mutation is related to epithelial-to-mesenchymal transition in breast cancer cell lines. Br J Cancer. 2006;94:661–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lv ZD, Kong B, Liu XP, Jin LY, Dong Q, Li FN, et al. miR-655 suppresses epithelial-to-mesenchymal transition by targeting Prrx1 in triple-negative breast cancer. J Cell Mol Med. 2016;20:864–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Ocana OH, Corcoles R, Fabra A, Moreno-Bueno G, Acloque H, Vega S, et al. Metastatic colonization requires the repression of the epithelial-mesenchymal transition inducer Prrx1. Cancer Cell. 2012;22:709–24.

    Article  CAS  PubMed  Google Scholar 

  28. Takahashi Y, Sawada G, Kurashige J, Uchi R, Matsumura T, Ueo H, et al. Paired related homoeobox 1, a new EMT inducer, is involved in metastasis and poor prognosis in colorectal cancer. Br J Cancer. 2013;109:307–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Takano S, Reichert M, Bakir B, Das KK, Nishida T, Miyazaki M, et al. Prrx1 isoform switching regulates pancreatic cancer invasion and metastatic colonization. Genes Dev. 2016;30:233–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Wu G, Cao L, Zhu J, Tan Z, Tang M, Li Z, et al. Loss of RBMS3 confers platinum resistance in epithelial ovarian cancer via activation of miR-126-5p/beta-catenin/CBP signaling. Clin Cancer Res. 2019;25:1022–35.

    Article  CAS  PubMed  Google Scholar 

  31. Lu CK, Lai YC, Chen HR, Chiang MK. Rbms3, an RNA-binding protein, mediates the expression of Ptf1a by binding to its 3’UTR during mouse pancreas development. DNA Cell Biol. 2012;31:1245–51.

    Article  CAS  PubMed  Google Scholar 

  32. Chen J, Kwong DL, Zhu CL, Chen LL, Dong SS, Zhang LY, et al. RBMS3 at 3p24 inhibits nasopharyngeal carcinoma development via inhibiting cell proliferation, angiogenesis, and inducing apoptosis. PLoS One. 2012;7:e44636.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Li Y, Chen L, Nie CJ, Zeng TT, Liu H, Mao X, et al. Downregulation of RBMS3 is associated with poor prognosis in esophageal squamous cell carcinoma. Cancer Res. 2011;71:6106–15.

    Article  CAS  PubMed  Google Scholar 

  34. Wu Y, Meng D, You Y, Sun R, Yan Q, Bao J, et al. Increased expression of RBMS3 predicts a favorable prognosis in human gallbladder carcinoma. Oncol Rep. 2020;44:55–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Zhang T, Wu Y, Fang Z, Yan Q, Zhang S, Sun R, et al. Low expression of RBMS3 and SFRP1 are associated with poor prognosis in patients with gastric cancer. Am J Cancer Res. 2016;6:2679–89.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Puisieux A, Brabletz T, Caramel J. Oncogenic roles of EMT-inducing transcription factors. Nat Cell Biol. 2014;16:488–94.

    Article  CAS  PubMed  Google Scholar 

  37. Li Y, Zhang Y, Yao Z, Li S, Yin Z, Xu M. Forkhead box Q1: a key player in the pathogenesis of tumors (Review). Int J Oncol. 2016;49:51–58.

    Article  CAS  PubMed  Google Scholar 

  38. Zhang H, Meng F, Liu G, Zhang B, Zhu J, Wu F, et al. Forkhead transcription factor foxq1 promotes epithelial-mesenchymal transition and breast cancer metastasis. Cancer Res. 2011;71:1292–301.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Bagati A, Bianchi-Smiraglia A, Moparthy S, Kolesnikova K, Fink EE, Lipchick BC, et al. Melanoma suppressor functions of the carcinoma oncogene FOXQ1. Cell Rep. 2017;20:2820–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Caramel J, Papadogeorgakis E, Hill L, Browne GJ, Richard G, Wierinckx A, et al. A switch in the expression of embryonic EMT-inducers drives the development of malignant melanoma. Cancer Cell. 2013;24:466–80.

    Article  CAS  PubMed  Google Scholar 

  41. Zhu L, Xi PW, Li XX, Sun X, Zhou WB, Xia TS, et al. The RNA binding protein RBMS3 inhibits the metastasis of breast cancer by regulating Twist1 expression. J Exp Clin Cancer Res. 2019;38:105.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Penkov D, Ni R, Else C, Pinol-Roma S, Ramirez F, Tanaka S. Cloning of a human gene closely related to the genes coding for the c-myc single-strand binding proteins. Gene. 2000;243:27–36.

    Article  CAS  PubMed  Google Scholar 

  43. Meng F, Wu L, Dong L, Mitchell AV, James Block C, Liu J, et al. EGFL9 promotes breast cancer metastasis by inducing cMET activation and metabolic reprogramming. Nat Commun. 2019;10:5033.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Zhang H, Meng F, Wu S, Kreike B, Sethi S, Chen W, et al. Engagement of I-branching {beta}-1, 6-N-acetylglucosaminyltransferase 2 in breast cancer metastasis and TGF-{beta} signaling. Cancer Res. 2011;71:4846–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Corley SM, Troy NM, Bosco A, Wilkins MR. QuantSeq. 3’ sequencing combined with Salmon provides a fast, reliable approach for high throughput RNA expression analysis. Sci Rep. 2019;9:18895.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  47. McDowell IC, Manandhar D, Vockley CM, Schmid AK, Reddy TE, Engelhardt BE. Clustering gene expression time series data using an infinite Gaussian process mixture model. PLoS Comput Biol. 2018;14:e1005896.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Tang Z, Kang B, Li C, Chen T, Zhang Z. GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res. 2019;47:W556–W560.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Orellana EA, Kasinski AL. Sulforhodamine B (SRB) assay in cell culture to investigate cell proliferation. Bio Protoc. 2016;6:e:1984–e:1992.

    Article  Google Scholar 

  50. Iorns E, Drews-Elger K, Ward TM, Dean S, Clarke J, Berry D, et al. A new mouse model for the study of human breast cancer metastasis. PLoS One. 2012;7:e47995.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Puchalapalli M, Zeng X, Mu L, Anderson A, Hix Glickman L, Zhang M, et al. NSG mice provide a better spontaneous model of breast cancer metastasis than athymic (nude) mice. PLoS One. 2016;11:e0163521.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Dr. Larry Matherly at the Karmanos Cancer Institute (KCI) and Wayne State University School of Medicine for helpful discussions and valuable comments. We also want to thank Dr. Robert A. Weinberg at MIT for providing the HMLE cell line.

Funding

This work is supported by Grant boost from Wayne State University (GW) and KCI strategic plan cancer immunology and immunotherapy award (GW and HG). The Biostatistics Core, AMTEC and the Biobanking and Correlative Sciences Core of KCI are supported by grant number P30-CA022453-38.

Author information

Authors and Affiliations

  1. Barbara Ann Karmanos Cancer Institute, Department of Oncology, Wayne State University School of Medicine, 4100 John R, Detroit, MI, 48201, USA

    C. James Block, Allison V. Mitchell, Ling Wu, James Glassbrook, Douglas Craig, Wei Chen, Gregory Dyson, Lisa Polin, Manohar Ratnam, Heather Gibson & Guojun Wu

  2. Department of Molecular and Cellular Biology, McNair Medical Institute Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA

    Ling Wu

  3. Department of Physiology, Wayne State University school of Medicine, Detroit, MI, 48201, USA

    Donald DeGracia

Authors
  1. C. James Block
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Allison V. Mitchell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ling Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. James Glassbrook
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Douglas Craig
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Gregory Dyson
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Donald DeGracia
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Lisa Polin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Manohar Ratnam
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Heather Gibson
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Guojun Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception and design: CJ B, HG, and GW. Data acquisition: CJB, GW, AVM, LW, JG, and LP. Data analyses and interpretation: CJB, GW, JG, DC, WC, GD, DD, MR, and HG. Drafting of manuscript: CJB and GW. Approval of final manuscript: CJB and GW.

Corresponding author

Correspondence to Guojun Wu.

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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Block, C.J., Mitchell, A.V., Wu, L. et al. RNA binding protein RBMS3 is a common EMT effector that modulates triple-negative breast cancer progression via stabilizing PRRX1 mRNA. Oncogene 40, 6430–6442 (2021). https://doi.org/10.1038/s41388-021-02030-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41388-021-02030-x

Search

Advanced search

Quick links