Cell fate perturbations underlie many human diseases, including breast cancer1,2. Unfortunately, the mechanisms by which breast cell fate are regulated are largely unknown. The mammary gland epithelium consists of differentiated luminal epithelial and basal myoepithelial cells, as well as undifferentiated stem cells and more restricted progenitors3,4. Breast cancer originates from this epithelium, but the molecular mechanisms that underlie breast epithelial hierarchy remain ill-defined. Here, we use a high-content confocal image-based short hairpin RNA screen to identify tumour suppressors that regulate breast cell fate in primary human breast epithelial cells. We show that ablation of the large tumour suppressor kinases (LATS) 1 and 2 (refs 5, 6), which are part of the Hippo pathway, promotes the luminal phenotype and increases the number of bipotent and luminal progenitors, the proposed cells-of-origin of most human breast cancers. Mechanistically, we have identified a direct interaction between Hippo and oestrogen receptor-α (ERα) signalling. In the presence of LATS, ERα was targeted for ubiquitination and Ddb1–cullin4-associated-factor 1 (DCAF1)-dependent proteasomal degradation. Absence of LATS stabilized ERα and the Hippo effectors YAP and TAZ (hereafter YAP/TAZ), which together control breast cell fate through intrinsic and paracrine mechanisms. Our findings reveal a non-canonical (that is, YAP/TAZ-independent) effect of LATS in the regulation of human breast cell fate.

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We thank members of the Bentires-Alj laboratory for advice and discussions. P. Ringenbach, S. Thiebault and V. Lindner provided mammary tissue. We were supported by FMI and GNF facilities: S. Thiry for microarray hybridizations, H. Kohler for FACS analysis, S. Bichet for histology, L. Gelmant, R. Thierry, K. Volkmann and S. Bourke for imaging, A. Romero for lentiviral preparations, B. Tu for automation of the screen, and K. Drumm for animal studies. We thank T. Radimerski, A. Bauer, T. Schmelzle and M. Frederiksen for discussions and reagents. Research in the laboratory of M.B.-A. is supported by the Novartis Research Foundation, the European Research Council, the Swiss National Science Foundation, the Krebsliga Beider Basel, the Swiss Cancer League, the Department of Surgery of the University Hospital of Basel and the Swiss Initiative for Systems Biology (SystemsX.ch).

Author information

Author notes

    • Adrian Britschgi
    • , Stephan Duss
    •  & Sungeun Kim

    These authors contributed equally to this work.


  1. Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland

    • Adrian Britschgi
    • , Stephan Duss
    • , Joana Pinto Couto
    • , Heike Brinkhaus
    • , Shany Koren
    • , Duvini De Silva
    • , Cedric Leroy
    • , Tim Roloff
    • , Michael B. Stadler
    •  & Mohamed Bentires-Alj
  2. Genomics Institute of the Novartis Research Foundation, San Diego, California 92121, USA

    • Sungeun Kim
    • , Loren J. Miraglia
    • , Anthony P. Orth
    • , Ghislain M. C. Bonamy
    •  & Venkateshwar A. Reddy
  3. Department of Biomedicine, University of Basel, University Hospital Basel, 4031 Basel, Switzerland

    • Joana Pinto Couto
    • , Shany Koren
    • , Duvini De Silva
    •  & Mohamed Bentires-Alj
  4. Institute of Pathology Liestal, Cantonal Hospital Baselland, 4410 Liestal, Switzerland

    • Kirsten D. Mertz
    •  & Daniela Kaup
  5. Institute of Surgical Pathology, University Hospital Zurich, 8091 Zurich, Switzerland

    • Zsuzsanna Varga
  6. Novartis Institutes for Biomedical Research, 4058 Basel, Switzerland

    • Hans Voshol
    • , Alexandra Vissieres
    •  & Cedric Leroy
  7. Swiss Institute of Bioinformatics, 4058 Basel, Switzerland

    • Michael B. Stadler
  8. Institute of Stem Cell Research, German Research Center for Environmental Health, 85764 Neuherberg, Germany

    • Christina H. Scheel


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A.B., S.D. and S.Ki. conceived the study, designed and performed experiments, analysed the data, interpreted the results and wrote the manuscript. J.P.C. performed PHBECs and MECs FACS and imaging, lentiviral infection, cell culture and limiting dilution transplantations, analysed the data and interpreted the results. H.B. performed immunohistochemistry and immunofluorescence experiments, analysed the data and interpreted the results. D.D.S. and S.Ko. performed MECs FACS, cell culture, immunofluorescence and limiting dilution transplantations. K.D.M., D.K. and Z.V. performed and analysed experiments on archived human breast cancer samples. H.V., A.V. and C.L. performed immunoprecipitation and mass spectrometry experiments and analysed the data. T.R. and M.B.S. performed microarray data analysis. C.H.S. interpreted 3D collagen assay experiments. G.M.C.B. imaged and analysed the 3D imaging data and the resulting screen data. L.J.M. and A.P.O. contributed to the shRNA screen experiment and analysis. V.A.R. and M.B.-A. conceived the study, designed the experiments and interpreted the results. M.B.-A. wrote and V.A.R. revised the manuscript. All authors read and approved the final manuscript.

Competing interests

J.P.C., D.D.S., K.D.M., D.K., Z.V., T.R., M.B.S., S.Ko., C.H.S. and M.B.-A. declare no competing financial interests. A.B., S.D. and H.B. are employees of Roche Pharma AG. S.Ki. is an employee of Amgen. H.V., A.V., L.M., A.P.O. and G.M.C.B. are employees of Novartis Pharma AG. C.L. is an employee of Actelion. V.A.R. is a full-time employee of Pfizer.

Corresponding author

Correspondence to Mohamed Bentires-Alj.

Reviewer Information Nature thanks C. Watson and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Figure

    This file contains the raw data for Figures 1b, 2c, 4b,d,e.

Excel files

  1. 1.

    Supplementary Table 1: shRNA tumor suppressor library used for the 3D screen

    TRC numbers, oligo sequences, clone names, reference sequences, and gene names of the shRNA constructs used for the 3D cell fate screen in PHBECs.

  2. 2.

    Supplementary Table 2: Raw data of the 3D screen

    Excel file containing results of K14 and K19 immunofluorescent staining as well as morphological parameters (number and size of spheres) of all shRNA conditions. Marker 1 = K14, Marker 2 = K19.

  3. 3.

    Supplementary Table 3: Results of redundant shRNA analysis (RSA) of the 3D screen

    Excel file containing results of RSA analysis of the number of spheres as well as the number of double-positive cells.

  4. 4.

    Supplementary Table 4: Differentially regulated genes in PHBECs upon removal of LATS

    Excel file of the significantly differentially regulated genes in the contrast shLATS versus shNT at a cut-off of fold-change (FC) >2.0, expression value >4.0, adjusted P <0.01.

  5. 5.

    Supplementary Table 5: Differentially regulated genes in MCF10A cells upon removal of LATS and/or expression of YAP, TAZ and ERα

    Excel file of the significantly differentially regulated genes at a cut-off of fold-change (FC) >2.0, expression value >4.0, adjusted P <0.01.

  6. 6.

    Supplementary Table 6: ERα interactome in luminal breast cancer cells with and without LATS1

    Excel file of ratios of ERα interacting proteins in the presence or absence of LATS1.

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