IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-36505-0.html
   My bibliography  Save this article

Non-canonical functions of SNAIL drive context-specific cancer progression

Author

Listed:
  • Mariel C. Paul

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München)

  • Christian Schneeweis

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technische Universität München
    Technical University of Munich)

  • Chiara Falcomatà

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Chuan Shan

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München)

  • Daniel Rossmeisl

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Stella Koutsouli

    (Faculty of Medicine, LMU Munich)

  • Christine Klement

    (Technical University of Munich
    Technische Universität München
    German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Partner Site Munich)

  • Magdalena Zukowska

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Sebastian A. Widholz

    (Technical University of Munich
    Technische Universität München
    German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Partner Site Munich)

  • Moritz Jesinghaus

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich
    Technische Universität München)

  • Konstanze K. Heuermann

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Thomas Engleitner

    (Technical University of Munich
    Technische Universität München
    German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Partner Site Munich)

  • Barbara Seidler

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Katia Sleiman

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Katja Steiger

    (Technische Universität München)

  • Markus Tschurtschenthaler

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Benjamin Walter

    (Technische Universität München)

  • Sören A. Weidemann

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Regina Pietsch

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich)

  • Angelika Schnieke

    (Technische Universität München)

  • Roland M. Schmid

    (Technische Universität München)

  • Maria S. Robles

    (Faculty of Medicine, LMU Munich)

  • Geoffroy Andrieux

    (University of Freiburg
    Partner Site Freiburg)

  • Melanie Boerries

    (University of Freiburg
    Partner Site Freiburg)

  • Roland Rad

    (Technical University of Munich
    Technische Universität München
    German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Partner Site Munich)

  • Günter Schneider

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technical University of Munich
    Visceral and Pediatric Surgery)

  • Dieter Saur

    (German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK)
    Technische Universität München
    Technische Universität München
    Technical University of Munich)

Abstract

SNAIL is a key transcriptional regulator in embryonic development and cancer. Its effects in physiology and disease are believed to be linked to its role as a master regulator of epithelial-to-mesenchymal transition (EMT). Here, we report EMT-independent oncogenic SNAIL functions in cancer. Using genetic models, we systematically interrogated SNAIL effects in various oncogenic backgrounds and tissue types. SNAIL-related phenotypes displayed remarkable tissue- and genetic context-dependencies, ranging from protective effects as observed in KRAS- or WNT-driven intestinal cancers, to dramatic acceleration of tumorigenesis, as shown in KRAS-induced pancreatic cancer. Unexpectedly, SNAIL-driven oncogenesis was not associated with E-cadherin downregulation or induction of an overt EMT program. Instead, we show that SNAIL induces bypass of senescence and cell cycle progression through p16INK4A-independent inactivation of the Retinoblastoma (RB)-restriction checkpoint. Collectively, our work identifies non-canonical EMT-independent functions of SNAIL and unravel its complex context-dependent role in cancer.

Suggested Citation

  • Mariel C. Paul & Christian Schneeweis & Chiara Falcomatà & Chuan Shan & Daniel Rossmeisl & Stella Koutsouli & Christine Klement & Magdalena Zukowska & Sebastian A. Widholz & Moritz Jesinghaus & Konsta, 2023. "Non-canonical functions of SNAIL drive context-specific cancer progression," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36505-0
    DOI: 10.1038/s41467-023-36505-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-36505-0
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-36505-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Xin Ye & Wai Leong Tam & Tsukasa Shibue & Yasemin Kaygusuz & Ferenc Reinhardt & Elinor Ng Eaton & Robert A. Weinberg, 2015. "Distinct EMT programs control normal mammary stem cells and tumour-initiating cells," Nature, Nature, vol. 525(7568), pages 256-260, September.
    2. Sebastian Mueller & Thomas Engleitner & Roman Maresch & Magdalena Zukowska & Sebastian Lange & Thorsten Kaltenbacher & Björn Konukiewitz & Rupert Öllinger & Maximilian Zwiebel & Alex Strong & Hsi-Yu Y, 2018. "Evolutionary routes and KRAS dosage define pancreatic cancer phenotypes," Nature, Nature, vol. 554(7690), pages 62-68, February.
    3. Xiaofeng Zheng & Julienne L. Carstens & Jiha Kim & Matthew Scheible & Judith Kaye & Hikaru Sugimoto & Chia-Chin Wu & Valerie S. LeBleu & Raghu Kalluri, 2015. "Epithelial-to-mesenchymal transition is dispensable for metastasis but induces chemoresistance in pancreatic cancer," Nature, Nature, vol. 527(7579), pages 525-530, November.
    4. Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
    5. M. Charlotte Hemmer & Michael Wierer & Kristina Schachtrup & Michael Downes & Norbert Hübner & Ronald M. Evans & N. Henriette Uhlenhaut, 2019. "E47 modulates hepatic glucocorticoid action," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    6. Osamu Tetsu & Frank McCormick, 1999. "β-Catenin regulates expression of cyclin D1 in colon carcinoma cells," Nature, Nature, vol. 398(6726), pages 422-426, April.
    7. Paul Krimpenfort & Kim C. Quon & Wolter J. Mooi & Ate Loonstra & Anton Berns, 2001. "Loss of p16Ink4a confers susceptibility to metastatic melanoma in mice," Nature, Nature, vol. 413(6851), pages 83-86, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lining Liang & Hao Sun & Wei Zhang & Mengdan Zhang & Xiao Yang & Rui Kuang & Hui Zheng, 2016. "Meta-Analysis of EMT Datasets Reveals Different Types of EMT," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-22, June.
    2. Aaron C Ericsson & J Wade Davis & William Spollen & Nathan Bivens & Scott Givan & Catherine E Hagan & Mark McIntosh & Craig L Franklin, 2015. "Effects of Vendor and Genetic Background on the Composition of the Fecal Microbiota of Inbred Mice," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-19, February.
    3. Hossain, Ahmed & Beyene, Joseph & Willan, Andrew R. & Hu, Pingzhao, 2009. "A flexible approximate likelihood ratio test for detecting differential expression in microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3685-3695, August.
    4. Xiaohong Li & Guy N Brock & Eric C Rouchka & Nigel G F Cooper & Dongfeng Wu & Timothy E O’Toole & Ryan S Gill & Abdallah M Eteleeb & Liz O’Brien & Shesh N Rai, 2017. "A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-22, May.
    5. Kerr Kathleen F., 2012. "Optimality Criteria for the Design of 2-Color Microarray Studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-9, January.
    6. Ambroise Jérôme & Bearzatto Bertrand & Robert Annie & Macq Benoit & Gala Jean-Luc, 2012. "Combining Multiple Laser Scans of Spotted Microarrays by Means of a Two-Way ANOVA Model," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-20, February.
    7. J. McClatchy & R. Strogantsev & E. Wolfe & H. Y. Lin & M. Mohammadhosseini & B. A. Davis & C. Eden & D. Goldman & W. H. Fleming & P. Conley & G. Wu & L. Cimmino & H. Mohammed & A. Agarwal, 2023. "Clonal hematopoiesis related TET2 loss-of-function impedes IL1β-mediated epigenetic reprogramming in hematopoietic stem and progenitor cells," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    8. Alexandra Gyurdieva & Stefan Zajic & Ya-Fang Chang & E. Andres Houseman & Shan Zhong & Jaegil Kim & Michael Nathenson & Thomas Faitg & Mary Woessner & David C. Turner & Aisha N. Hasan & John Glod & Ro, 2022. "Biomarker correlates with response to NY-ESO-1 TCR T cells in patients with synovial sarcoma," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    9. Sora Yoon & Seon-Young Kim & Dougu Nam, 2016. "Improving Gene-Set Enrichment Analysis of RNA-Seq Data with Small Replicates," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-16, November.
    10. Yu Lianbo & Gulati Parul & Fernandez Soledad & Pennell Michael & Kirschner Lawrence & Jarjoura David, 2011. "Fully Moderated T-statistic for Small Sample Size Gene Expression Arrays," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-22, September.
    11. Chaofeng Yuan & Wensheng Zhu & Xuming He & Jianhua Guo, 2019. "A mixture factor model with applications to microarray data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 60-76, March.
    12. Nan Li & Matthew N. McCall & Zhijin Wu, 2017. "Establishing Informative Prior for Gene Expression Variance from Public Databases," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 160-177, June.
    13. Brian Caffo & Liu Dongmei & Giovanni Parmigiani, 2004. "Power Conjugate Multilevel Models with Applications to Genomics," Johns Hopkins University Dept. of Biostatistics Working Paper Series 1062, Berkeley Electronic Press.
    14. Nott, David J. & Yu, Zeming & Chan, Eva & Cotsapas, Chris & Cowley, Mark J. & Pulvers, Jeremy & Williams, Rohan & Little, Peter, 2007. "Hierarchical Bayes variable selection and microarray experiments," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 852-872, April.
    15. Santu Ghosh & Alan M. Polansky, 2022. "Large-Scale Simultaneous Testing Using Kernel Density Estimation," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 808-843, August.
    16. Qianxing Mo & Faming Liang, 2010. "Bayesian Modeling of ChIP-chip Data Through a High-Order Ising Model," Biometrics, The International Biometric Society, vol. 66(4), pages 1284-1294, December.
    17. Ahmed Hossain & Hafiz T.A. Khan, 2016. "Identification of genomic markers correlated with sensitivity in solid tumors to Dasatinib using sparse principal components," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(14), pages 2538-2549, October.
    18. Alexander Kaever & Manuel Landesfeind & Kirstin Feussner & Burkhard Morgenstern & Ivo Feussner & Peter Meinicke, 2014. "Meta-Analysis of Pathway Enrichment: Combining Independent and Dependent Omics Data Sets," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    19. Iqbal Mahmud & Guimei Tian & Jia Wang & Tarun E. Hutchinson & Brandon J. Kim & Nikee Awasthee & Seth Hale & Chengcheng Meng & Allison Moore & Liming Zhao & Jessica E. Lewis & Aaron Waddell & Shangtao , 2023. "DAXX drives de novo lipogenesis and contributes to tumorigenesis," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    20. Ankur Chakravarthy & Ian Reddin & Stephen Henderson & Cindy Dong & Nerissa Kirkwood & Maxmilan Jeyakumar & Daniela Rothschild Rodriguez & Natalia Gonzalez Martinez & Jacqueline McDermott & Xiaoping Su, 2022. "Integrated analysis of cervical squamous cell carcinoma cohorts from three continents reveals conserved subtypes of prognostic significance," Nature Communications, Nature, vol. 13(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36505-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.