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.

Isolating and targeting the real-time plasticity and malignant properties of epithelial-mesenchymal transition in cancer

Abstract

Epithelial-mesenchymal transition (EMT) is a driving force in promoting malignant cancer, including initiation, growth, and metastasis. EMT is a dynamic process that can undergo a mesenchymal-epithelial transition (MET) and partial transitions between both phenotypes, termed epithelial-mesenchymal plasticity (EMP). In cancer, the acquisition of EMP results in a spectrum of phenotypes, promoting tumor cell heterogeneity and resistance to standard of care therapy. Here we describe a real-time fluorescent dual-reporter for vimentin and E-cadherin, biomarkers of the mesenchymal and epithelial cell phenotypes, respectively. Stable dual-reporter cell lines generated from colorectal (SW620), lung (A549), and breast (MDA-MB-231) cancer demonstrate a spectrum of EMT cell phenotypes. We used the dual-reporter to isolate the quasi epithelial, epithelial/mesenchymal, and mesenchymal phenotypes. Although EMT is a dynamic process, these isolated quasi-EMT-phenotypes remain stable to spontaneous EMP in the absence of stimuli and during prolonged cell culture. However, the quasi-EMT phenotypes can readily be induced to undergo EMT or MET with growth factors or small molecules. Moreover, isolated EMT phenotypes display different tumorigenic properties and are morphologically and metabolically distinct. 3D high-content screening of ~23,000 compounds using dual-reporter mesenchymal SW620 tumor organoids identified small molecule probes that modulate EMT, and a subset of probes that effectively induced MET. The tools, probes, and models described herein provide a coherent mechanistic understanding of mesenchymal cell plasticity. Future applications utilizing this technology and probes are expected to advance our understanding of EMT and studies aimed at therapeutic strategies targeting EMT.

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: The dual-reporter allows for the identification and isolation of distinct EMT subtypes.
Fig. 2: The mesenchymal phenotype has higher stemness and invasive potential.
Fig. 3: Isolated EMT cell populations have distinct metabotypes.
Fig. 4: Treatment of M-phenotype CRC tumor organoids with 7 induces MET by metabolomics.
Fig. 5: A diverse set of probes reverse EMT in a dose-dependent manner.
Fig. 6: Mechanisms regulating mesenchymal cell EMP in CRC.

References

  1. 1.

    Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646–74.

    CAS  PubMed  Google Scholar 

  2. 2.

    Dongre A, Weinberg RA. New insights into the mechanisms of epithelial-mesenchymal transition and implications for cancer. Nat Rev Mol Cell Biol. 2019;20:69–84.

    CAS  PubMed  Google Scholar 

  3. 3.

    Voon DC, Huang RY, Jackson RA, Thiery JP. The EMT spectrum and therapeutic opportunities. Mol Oncol. 2017;11:878–91.

    PubMed  PubMed Central  Google Scholar 

  4. 4.

    Chaffer CL, San Juan BP, Lim E, Weinberg RA. EMT, cell plasticity and metastasis. Cancer Metast Rev. 2016;35:645–54.

    Google Scholar 

  5. 5.

    Kroger C, Afeyan A, Mraz J, Eaton EN, Reinhardt F, Khodor YL, et al. Acquisition of a hybrid E/M state is essential for tumorigenicity of basal breast cancer cells. Proc Natl Acad Sci USA. 2019;116:7353–62.

    PubMed  Google Scholar 

  6. 6.

    Yang J, Antin P, Berx G, Blanpain C, Brabletz T, Bronner M, et al. Guidelines and definitions for research on epithelial-mesenchymal transition. Nat Rev Mol Cell Biol. 2020;21:341–52.

    PubMed  PubMed Central  Google Scholar 

  7. 7.

    McDonald PC, Dedhar S. The role of epithelial-mesenchymal transition in cancer metastasis. In: Regad, T, Sayers TJ, Rees RC editors. Principles of stem cell biology and cancer future applications and therapeutics, 1st edn. West Sussex, UK: John Wiley & Sons, Ltd.; 2015. p. 101–21.

  8. 8.

    Yun JA, Kim SH, Hong HK, Yun SH, Kim HC, Chun HK, et al. Loss of E-Cadherin expression is associated with a poor prognosis in stage III Colorectal cancer. Oncology. 2014;86:318–28.

    CAS  PubMed  Google Scholar 

  9. 9.

    Richardson F, Young GD, Sennello R, Wolf J, Argast GM, Mercado P, et al. The evaluation of E-Cadherin and vimentin as biomarkers of clinical outcomes among patients with non-small cell lung cancer treated with erlotinib as second- or third-line therapy. Anticancer Res. 2012;32:537–52.

    CAS  PubMed  Google Scholar 

  10. 10.

    Dhanasekaran SM, Barrette TR, Ghosh D, Shah R, Varambally S, Kurachi K, et al. Delineation of prognostic biomarkers in prostate cancer. Nature. 2001;412:822–6.

    CAS  PubMed  Google Scholar 

  11. 11.

    Kashiwagi S, Yashiro M, Takashima T, Nomura S, Noda S, Kawajiri H, et al. Significance of E-cadherin expression in triple-negative breast cancer. Br J Cancer. 2010;103:249–55.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Ye Z, Zhang X, Luo Y, Li S, Huang L, Li Z, et al. Prognostic values of vimentin expression and its clinicopathological significance in non-small cell lung cancer: a meta-analysis of observational studies with 4118 cases. PLoS ONE. 2016;11:e0163162.

    PubMed  PubMed Central  Google Scholar 

  13. 13.

    Toiyama Y, Yasuda H, Saigusa S, Tanaka K, Inoue Y, Goel A, et al. Increased expression of Slug and Vimentin as novel predictive biomarkers for lymph node metastasis and poor prognosis in colorectal cancer. Carcinogenesis. 2013;34:2548–57.

    CAS  PubMed  Google Scholar 

  14. 14.

    Rodriguez-Pinilla SM, Sarrio D, Honrado E, Moreno-Bueno G, Hardisson D, Calero F, et al. Vimentin and laminin expression is associated with basal-like phenotype in both sporadic and BRCA1-associated breast carcinomas. J Clin Pathol. 2006;60:1006–12.

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Sciacovelli M, Frezza C. Metabolic reprogramming and epithelial-to-mesenchymal transition in cancer. FEBS J. 2017;284:3132–44.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Tam WL, Weinberg RA. The epigenetics of epithelial-mesenchymal plasticity in cancer. Nat Med. 2013;19:1438–49.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Zeisberg M, Neilson EG. Biomarkers for epithelial-mesenchymal transitions. J Clin Invest. 2009;119:1429–37.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Bierie B, Pierce SE, Kroeger C, Stover DG, Pattabiraman DR, Thiru P, et al. Integrin-beta4 identifies cancer stem cell-enriched populations of partially mesenchymal carcinoma cells. Proc Natl Acad Sci USA. 2017;114:E2337–46.

    CAS  PubMed  Google Scholar 

  19. 19.

    Bighetti-Trevisan RL, Sousa LO, Castilho RM, Almeida LO. Cancer stem cells: powerful targets to improve current anticancer therapeutics. Stem Cells Int. 2019;2019:9618065.

  20. 20.

    Yeung TM, Gandhi SC, Wilding JL, Muschel R, Bodmer WF. Cancer stem cells from colorectal cancer-derived cell lines. Proc Natl Acad Sci USA. 2010;107:3722–7.

    CAS  PubMed  Google Scholar 

  21. 21.

    Batlle E, Clevers H. Cancer stem cells revisited. Nat Med. 2017;23:1124–34.

    CAS  PubMed  Google Scholar 

  22. 22.

    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.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Esquer H, Zhou Q, Abraham AD, LaBarbera DV. Advanced high-content-screening applications of clonogenicity in cancer. SLAS Disco. 2020;25:734–43.

    CAS  Google Scholar 

  24. 24.

    Franken NA, Rodermond HM, Stap J, Haveman J, van Bree C. Clonogenic assay of cells in vitro. Nat Protoc. 2006;1:2315–9.

    CAS  PubMed  Google Scholar 

  25. 25.

    Leggett SE, Sim JY, Rubins JE, Neronha ZJ, Williams EK, Wong IY. Morphological single cell profiling of the epithelial-mesenchymal transition. Integr Biol: Quant Biosci nano macro. 2016;8:1133–44.

    CAS  Google Scholar 

  26. 26.

    Ackland ML, Newgreen DF, Fridman M, Waltham MC, Arvanitis A, Minichiello J, et al. Epidermal growth factor-induced epithelio-mesenchymal transition in human breast carcinoma cells. Lab Invest. 2003;83:435–48.

    CAS  PubMed  Google Scholar 

  27. 27.

    Li Q, Chen C, Kapadia A, Zhou Q, Harper MK, Schaack J, et al. 3D Models of epithelial-mesenchymal transition in breast cancer metastasis: high-throughput screening assay development, validation, and pilot screen. J Biomol Screen. 2011;16:141–54.

    CAS  PubMed  Google Scholar 

  28. 28.

    Abraham AD, Esquer H, Zhou Q, Tomlinson N, Hamill BD, Abbott JM, et al. Drug design targeting T-cell factor-driven epithelial-mesenchymal transition as a therapeutic strategy for colorectal cancer. J Med Chem. 2019;62:10182–203.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Zhou Q, Abraham AD, Li L, Babalmorad A, Bagby S, Arcaroli JJ, et al. Topoisomerase IIα mediates TCF-dependent epithelial-mesenchymal transition in colon cancer. Oncogene. 2016;35:4990–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Li H, Ning S, Ghandi M, Kryukov GV, Gopal S, Deik A, et al. The landscape of cancer cell line metabolism. Nat Med. 2019;25:850–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Longo N, Frigeni M, Pasquali M. Carnitine transport and fatty acid oxidation. Biochim Biophys Acta. 2016;1863:2422–35.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Hale JS, Otvos B, Sinyuk M, Alvarado AG, Hitomi M, Stoltz K, et al. Cancer stem cell-specific scavenger receptor CD36 drives glioblastoma progression. Stem Cells. 2014;32:1746–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Ye H, Adane B, Khan N, Sullivan T, Minhajuddin M, Gasparetto M, et al. Leukemic stem cells evade chemotherapy by metabolic adaptation to an adipose tissue niche. Cell Stem Cell. 2016;19:23–37.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Sánchez-Tilló E, de Barrios O, Siles L, Cuatrecasas M, Castells A, Postigo A. β-catenin/TCF4 complex induces the epithelial-to-mesenchymal transition (EMT)-activator ZEB1 to regulate tumor invasiveness. Proc Natl Acad Sci USA. 2011;108:19204–9.

    PubMed  Google Scholar 

  35. 35.

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

    CAS  Google Scholar 

  36. 36.

    Zhang JH, Chung TD, Oldenburg KR. A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen. 1999;4:67–73.

    CAS  PubMed  Google Scholar 

  37. 37.

    Buchser W, Collins M, Garyantes T, Guha R, Haney S, Lemmon V, et al. Assay development guidelines for image-based high content screening, high content analysis and high content imaging. In: Sittampalam GS, Gal-Edd N, Arkin M, Auld D, Austin C, Bejcek B, et al. editors. Assay Guidance Manual: Bethesda (MD), 2004- [Updated 2014].

  38. 38.

    Jia D, Lu M, Jung KH, Park JH, Yu L, Onuchic JN, et al. Elucidating cancer metabolic plasticity by coupling gene regulation with metabolic pathways. Proc Natl Acad Sci USA. 2019;116:3909–18.

    CAS  PubMed  Google Scholar 

  39. 39.

    San-Millan I, Julian CG, Matarazzo C, Martinez J, Brooks GA. Is lactate an oncometabolite? Evidence supporting a role for lactate in the regulation of transcriptional activity of cancer-related genes in MCF7 breast cancer cells. Front Oncol. 2019;9:1536.

    PubMed  Google Scholar 

  40. 40.

    Martinez-Outschoorn UE, Prisco M, Ertel A, Tsirigos A, Lin Z, Pavlides S, et al. Ketones and lactate increase cancer cell “stemness,” driving recurrence, metastasis and poor clinical outcome in breast cancer: achieving personalized medicine via Metabolo-Genomics. Cell Cycle. 2011;10:1271–86.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Faubert B, Li KY, Cai L, Hensley CT, Kim J, Zacharias LG, et al. Lactate metabolism in human lung tumors. Cell. 2017;171:358–71. e359.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Vlachostergios PJ, Oikonomou KG, Gibilaro E, Apergis G. Elevated lactic acid is a negative prognostic factor in metastatic lung cancer. Cancer Biomark. 2015;15:725–34.

    CAS  PubMed  Google Scholar 

  43. 43.

    Walenta S, Chau TV, Schroeder T, Lehr HA, Kunz-Schughart LA, Fuerst A, et al. Metabolic classification of human rectal adenocarcinomas: a novel guideline for clinical oncologists? J Cancer Res Clin Oncol. 2003;129:321–6.

    PubMed  Google Scholar 

  44. 44.

    Choi BJ, Park SA, Lee SY, Cha YN, Surh YJ. Hypoxia induces epithelial-mesenchymal transition in colorectal cancer cells through ubiquitin-specific protease 47-mediated stabilization of Snail: a potential role of Sox9. Sci Rep. 2017;7:15918.

    PubMed  PubMed Central  Google Scholar 

  45. 45.

    Raimundo N, Baysal BE, Shadel GS. Revisiting the TCA cycle: signaling to tumor formation. Trends Mol Med. 2011;17:641–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Wise DR, DeBerardinis RJ, Mancuso A, Sayed N, Zhang XY, Pfeiffer HK, et al. Myc regulates a transcriptional program that stimulates mitochondrial glutaminolysis and leads to glutamine addiction. Proc Natl Acad Sci USA. 2008;105:18782–7.

    CAS  PubMed  Google Scholar 

  47. 47.

    Serrano-Gomez SJ, Maziveyi M, Alahari SK. Regulation of epithelial-mesenchymal transition through epigenetic and post-translational modifications. Mol Cancer. 2016;15:18.

    PubMed  PubMed Central  Google Scholar 

  48. 48.

    Cojoc M, Peitzsch C, Kurth I, Trautmann F, Kunz-Schughart LA, Telegeev GD, et al. Aldehyde dehydrogenase is regulated by beta-Catenin/TCF and promotes radioresistance in prostate cancer progenitor cells. Cancer Res. 2015;75:1482–94.

    CAS  PubMed  Google Scholar 

  49. 49.

    Moore SF, van den Bosch MT, Hunter RW, Sakamoto K, Poole AW, Hers I. Dual regulation of glycogen synthase kinase 3 (GSK3)alpha/beta by protein kinase C (PKC)alpha and Akt promotes thrombin-mediated integrin alphaIIbbeta3 activation and granule secretion in platelets. J Biol Chem. 2013;288:3918–28.

    CAS  PubMed  Google Scholar 

  50. 50.

    Jacobsen A, Bosch LJW, Martens-de Kemp SR, Carvalho B, Sillars-Hardebol AH, Dobson RJ, et al. Aurora kinase A (AURKA) interaction with Wnt and Ras-MAPK signalling pathways in colorectal cancer. Sci Rep. 2018;8:7522.

    PubMed  PubMed Central  Google Scholar 

  51. 51.

    Lee SK, Hwang JH, Choi KY. Interaction of the Wnt/beta-catenin and RAS-ERK pathways involving co-stabilization of both beta-catenin and RAS plays important roles in the colorectal tumorigenesis. Adv Biol Regul. 2018;68:46–54.

    CAS  PubMed  Google Scholar 

  52. 52.

    Wang C, Shao L, Pan C, Ye J, Ding Z, Wu J, et al. Elevated level of mitochondrial reactive oxygen species via fatty acid β-oxidation in cancer stem cells promotes cancer metastasis by inducing epithelial-mesenchymal transition. Stem Cell Res Ther. 2019;10:175–5.

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    Beharry Z, Mahajan S, Zemskova M, Lin YW, Tholanikunnel BG, Xia Z, et al. The Pim protein kinases regulate energy metabolism and cell growth. Proc Natl Acad Sci USA. 2011;108:528–33.

    CAS  PubMed  Google Scholar 

  54. 54.

    Bai F, Asojo OA, Cirillo P, Ciustea M, Ledizet M, Aristoff PA, et al. A novel allosteric inhibitor of macrophage migration inhibitory factor (MIF). J Biol Chem. 2012;287:30653–63.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Zhang X, Chen L, Wang Y, Ding Y, Peng Z, Duan L, et al. Macrophage migration inhibitory factor promotes proliferation and neuronal differentiation of neural stem/precursor cells through Wnt/beta-catenin signal pathway. Int J Biol Sci. 2013;9:1108–20.

    PubMed  PubMed Central  Google Scholar 

  56. 56.

    Zhang FX, Ge SN, Dong YL, Shi J, Feng YP, Li Y, et al. Vesicular glutamate transporter isoforms: the essential players in the somatosensory systems. Prog Neurobiol. 2018;171:72–89.

    CAS  PubMed  Google Scholar 

  57. 57.

    Nemkov T, Hansen KC, D’Alessandro A. A three-minute method for high-throughput quantitative metabolomics and quantitative tracing experiments of central carbon and nitrogen pathways. Rapid Commun Mass Spectrom. 2017;31:663–73.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Nemkov T, Reisz JA, Gehrke S, Hansen KC, D’Alessandro A. High-throughput metabolomics: isocratic and gradient mass spectrometry-based methods. Methods Mol Biol. 2019;1978:13–26.

    CAS  PubMed  Google Scholar 

  59. 59.

    Clasquin MF, Melamud E, Rabinowitz JD. LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine. Curr Protoc Bioinforma. 2012;Chapter 14:Unit14 11.

    Google Scholar 

Download references

Acknowledgements

This research was supported in part by grants awarded to DVL from the Department of Defense Peer Reviewed Cancer Research Program (W81XWH-18-1-0142), the NIH NCI (1R01CA251361-01), and The ALSAM Foundation Therapeutic Innovation Grant. TN was supported by a NIH Training Grant (5T32HL7171-42). SR was supported by the Cancer Foundation of Luxembourg. We thank the Eli Lilly and Company Open Innovation Drug Discovery Program, particularly Evan Castetter and Maria Jose Lorite, for providing the BIC library. We also thank CU AMC shared resource laboratories, including the Drug Discovery and Development Shared Resource (HTS/HCS Discovery Arm), MS Metabolomics, Flow Cytometry, and NMR. These shared resources are supported in part by the UCCC NIH NCI designated cancer center (P30CA046934). We are grateful to Claudia Esquer for graphic design input of Fig. 6.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Daniel V. LaBarbera.

Ethics declarations

Conflict of interest

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

Esquer, H., Zhou, Q., Nemkov, T. et al. Isolating and targeting the real-time plasticity and malignant properties of epithelial-mesenchymal transition in cancer. Oncogene 40, 2884–2897 (2021). https://doi.org/10.1038/s41388-021-01728-2

Download citation

Search

Quick links