Abstract
The development of the mammary gland is a complex process that evolves throughout life. It can undergo drastic changes to support lactation, before involuting back to a rudimentary organ after weaning, in a perfectly orchestrated mechanism. This study aimed to identify the pathways coordinating mammary gland organogenesis, using mouse organoids as a model. In developmental assays, the mechanistic target of rapamycin (mTOR) was shown to be a regulator of cellular lineage determination and branching morphogenesis, acting in a time-dependent manner to control these processes. Indeed, mTOR inhibition during the initial growth phase of organoids abrogated the presence of basal epithelial cells, forcing the expansion of the luminal compartment. At later time points during development, mTOR inhibition promoted branching morphogenesis, increasing the organoid capacity to generate branching/buds. Mechanistically, the mTOR signalling inhibition led to alterations in the expression levels of genes and proteins connected to branching morphogenesis, extracellular matrix remodelling, metabolism, and cell migration. Altogether, this study demonstrates the regulatory functions of mTOR in controlling mammary epithelial cells’ capacity to generate organoids.
Data availability
The omics datasets generated during the current study were deposited in public repositories. For proteomics data, they were assigned MassIVE number MSV000100067 (http://massive.ucsd.edu). For RNA-seq data, they were deposited on the Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo) and were assigned the number GSE298518.
References
Rauner, G. Using organoids to tap mammary gland diversity for novel insight. J. Mammary Gland Biol. Neoplasia. 29, 7. https://doi.org/10.1007/s10911-024-09559-z (2024).
Watson, C. J. Involution: apoptosis and tissue remodelling that convert the mammary gland from milk factory to a quiescent organ. Breast Cancer Res. 8, 203. https://doi.org/10.1186/bcr1401 (2006).
Majumder, S. et al. Divergent paths of mammary gland involution: unveiling the cellular dynamics in abruptly and gradually involuted mouse models. Breast Cancer Res. 27, 1. https://doi.org/10.1186/s13058-024-01933-3 (2025).
Macias, H. & Hinck, L. Mammary gland development. WIREs Dev. Biol. 1, 533–557. https://doi.org/10.1002/wdev.35 (2012).
Hannan, F. M., Elajnaf, T., Vandenberg, L. N., Kennedy, S. H. & Thakker, R. V. Hormonal regulation of mammary gland development and lactation. Nat. Rev. Endocrinol. 19, 46–61. https://doi.org/10.1038/s41574-022-00742-y (2023).
Arendt, L. M. & Kuperwasser, C. Form and function: how Estrogen and progesterone regulate the mammary epithelial hierarchy. J. Mammary Gland Biol. Neoplasia. 20, 9–25. https://doi.org/10.1007/s10911-015-9337-0 (2015).
Manavathi, B., Samanthapudi, V. S. K. & Gajulapalli, V. N. R. Estrogen receptor coregulators and pioneer factors: the orchestrators of mammary gland cell fate and development. Front. Cell. Dev. Biol. 2. https://doi.org/10.3389/fcell.2014.00034 (2014).
Palaniappan, M. et al. The genomic landscape of Estrogen receptor α binding sites in mouse mammary gland. PLoS ONE. 14, e0220311. https://doi.org/10.1371/journal.pone.0220311 (2019).
Walker, V. R. & Korach, K. S. Estrogen receptor knockout mice as a model for endocrine research. ILAR J. 45, 455–461. https://doi.org/10.1093/ilar.45.4.455 (2004).
Lacouture, A. et al. A FACS-Free purification method to study Estrogen Signaling, organoid Formation, and metabolic reprogramming in mammary epithelial cells. Front. Endocrinol. 12, 672466. https://doi.org/10.3389/fendo.2021.672466 (2021).
Lacouture, A. et al. Estrogens and endocrine-disrupting chemicals differentially impact the bioenergetic fluxes of mammary epithelial cells in two- and three-dimensional models. Environ. Int. 179, 108132. https://doi.org/10.1016/j.envint.2023.108132 (2023).
Caruso, M., Huang, S., Mourao, L. & Scheele, C. L. G. J. A mammary organoid model to study branching morphogenesis. Front. Physiol. 13, 826107. https://doi.org/10.3389/fphys.2022.826107 (2022).
Sahu, S. et al. Growth factor dependency in mammary organoids regulates ductal morphogenesis during organ regeneration. Sci. Rep. 12, 7200. https://doi.org/10.1038/s41598-022-11224-6 (2022).
Merle, C. et al. Transcriptional landscapes underlying Notch-induced lineage conversion and plasticity of mammary basal cells. EMBO J. https://doi.org/10.1038/s44318-025-00424-1 (2025).
Ortiz, J. R. et al. Single-Cell transcription mapping of murine and human mammary organoids responses to female hormones. J. Mammary Gland Biol. Neoplasia. 29, 3. https://doi.org/10.1007/s10911-023-09553-x (2024).
Winkler, J. et al. Bisphenol A replacement chemicals, BPF and BPS, induce protumorigenic changes in human mammary gland organoid morphology and proteome. Proc. Natl. Acad. Sci. U S A. 119, e2115308119. https://doi.org/10.1073/pnas.2115308119 (2022).
Kim, H. Y., Sinha, I., Sears, K. E., Kuperwasser, C. & Rauner, G. Expanding the evo-devo toolkit: generation of 3D mammary tissue from diverse mammals. Development 151, dev202134. https://doi.org/10.1242/dev.202134 (2024).
Ben-Sahra, I. & Manning, B. D. mTORC1 signaling and the metabolic control of cell growth. Curr. Opin. Cell. Biol. 45, 72–82. https://doi.org/10.1016/j.ceb.2017.02.012 (2017).
Caron, A., Briscoe, D. M., Richard, D. & Laplante, M. DEPTOR at the nexus of Cancer, Metabolism, and immunity. Physiol. Rev. 98, 1765–1803. https://doi.org/10.1152/physrev.00064.2017 (2018).
Panwar, V. et al. Multifaceted role of mTOR (mammalian target of rapamycin) signaling pathway in human health and disease. Sig Transduct. Target. Ther. 8, 1–25. https://doi.org/10.1038/s41392-023-01608-z (2023).
Laplante, M. & Sabatini, D. M. mTOR signaling at a glance. J. Cell Sci. 122, 3589–3594. https://doi.org/10.1242/jcs.051011 (2009).
Morrison, M. M. et al. mTOR directs breast morphogenesis through the PKC-alpha-Rac1 signaling axis. PLoS Genet. 11, e1005291. https://doi.org/10.1371/journal.pgen.1005291 (2015).
Zhang, R. et al. Th-POK regulates mammary gland lactation through mTOR-SREBP pathway. PLoS Genet. 14, e1007211. https://doi.org/10.1371/journal.pgen.1007211 (2018).
Jankiewicz, M., Groner, B. & Desrivières, S. Mammalian target of Rapamycin regulates the growth of mammary epithelial cells through the inhibitor of deoxyribonucleic acid binding Id1 and their functional differentiation through Id2. Mol. Endocrinol. 20, 2369–2381. https://doi.org/10.1210/me.2006-0071 (2006).
Thoreen, C. C. et al. An ATP-competitive mammalian target of Rapamycin inhibitor reveals Rapamycin-resistant functions of mTORC1. J. Biol. Chem. 284, 8023–8032. https://doi.org/10.1074/jbc.M900301200 (2009).
Sarbassov, D. D. et al. Prolonged Rapamycin treatment inhibits mTORC2 assembly and Akt/PKB. Mol. Cell. 22, 159–168. https://doi.org/10.1016/j.molcel.2006.03.029 (2006).
Norman, A. W. & Henry, H. L. Hormones of Pregnancy, Parturition and Lactation. In: Hormones (Elsevier), 297–320 https://doi.org/10.1016/B978-0-08-091906-5.00014-8 (2015).
Audet-Walsh, É. et al. Nuclear mTOR acts as a transcriptional integrator of the androgen signaling pathway in prostate cancer. Genes Dev. 31, 1228–1242. https://doi.org/10.1101/gad.299958.117 (2017).
Dufour, C. R. et al. The mTOR chromatin-bound interactome in prostate cancer. Cell. Rep. 38, 110534. https://doi.org/10.1016/j.celrep.2022.110534 (2022).
Pal, B. et al. Single cell transcriptome atlas of mouse mammary epithelial cells across development. Breast Cancer Res. 23, 69. https://doi.org/10.1186/s13058-021-01445-4 (2021).
Gray, G. K., Girnius, N., Kuiken, H. J., Henstridge, A. Z. & Brugge, J. S. Single-cell and Spatial analyses reveal a tradeoff between murine mammary proliferation and lineage programs associated with endocrine cues. Cell. Rep. 42, 113293. https://doi.org/10.1016/j.celrep.2023.113293 (2023).
Alayev, A. et al. mTORC1 directly phosphorylates and activates ERα upon Estrogen stimulation. Oncogene 35, 3535–3543. https://doi.org/10.1038/onc.2015.414 (2016).
Yu Miao, R. et al. MYB is essential for mammary tumorigenesis. Cancer Res. 71, 7029–7037. https://doi.org/10.1158/0008-5472.CAN-11-1015 (2011).
Wang, X., Angelis, N. & Thein, S. L. MYB - A regulatory factor in hematopoiesis. Gene 665, 6–17. https://doi.org/10.1016/j.gene.2018.04.065 (2018).
Oh, I. H. & Reddy, E. P. The myb gene family in cell growth, differentiation and apoptosis. Oncogene. https://doi.org/10.1038/sj.onc.1202839 (1999).
Ramsay, R. G. & Gonda, T. J. MYB function in normal and cancer cells. Nat. Rev. Cancer. 8, 523–534. https://doi.org/10.1038/nrc2439 (2008).
Xu, J., Chen, Y. & Olopade, O. I. MYC and breast cancer. Genes Cancer. 1, 629–640. https://doi.org/10.1177/1947601910378691 (2010).
Bhin, J. et al. MYC is a clinically significant driver of mTOR inhibitor resistance in breast cancer. J. Exp. Med. 220, e20211743. https://doi.org/10.1084/jem.20211743 (2023).
Blakely, C. M. et al. Developmental stage determines the effects of MYC in the mammary epithelium. Development 132, 1147–1160. https://doi.org/10.1242/dev.01655 (2005).
Frégeau-Proulx, L. et al. Multiple metabolic pathways fuel the truncated Tricarboxylic acid cycle of the prostate to sustain constant citrate production and secretion. Mol. Metabolism. 62, 101516. https://doi.org/10.1016/j.molmet.2022.101516 (2022).
Andrews, S. FastQC A Quality Control tool for High Throughput Sequence Data. Babraham Bioinformatics. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).
Ewels, P., Magnusson, M., Lundin, S. & Käller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048. https://doi.org/10.1093/bioinformatics/btw354 (2016).
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12. https://doi.org/10.14806/ej.17.1.200 (2011).
Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527. https://doi.org/10.1038/nbt.3519 (2016).
Love, M. I., Huber, W. & Anders, S. Moderated Estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550. https://doi.org/10.1186/s13059-014-0550-8 (2014).
Subramanian, A. et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U S A. 102, 15545–15550. https://doi.org/10.1073/pnas.0506580102 (2005).
Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1523. https://doi.org/10.1038/s41467-019-09234-6 (2019).
Zhou, G. et al. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res. 47, W234–W241. https://doi.org/10.1093/nar/gkz240 (2019).
Lafront, C., Germain, L., Weidmann, C. & Audet-Walsh, É. A systematic study of the impact of estrogens and selective Estrogen receptor modulators on prostate cancer cell proliferation. Sci. Rep. 10, 4024. https://doi.org/10.1038/s41598-020-60844-3 (2020).
Moggridge, S., Sorensen, P. H., Morin, G. B. & Hughes, C. S. Extending the compatibility of the SP3 paramagnetic bead processing approach for proteomics. J. Proteome Res. 17, 1730–1740. https://doi.org/10.1021/acs.jproteome.7b00913 (2018).
Hughes, C. S. et al. Single-pot, solid-phase-enhanced sample Preparation for proteomics experiments. Nat. Protoc. 14, 68–85. https://doi.org/10.1038/s41596-018-0082-x (2019).
Prianichnikov, N. et al. MaxQuant software for ion mobility enhanced shotgun proteomics. Mol. Cell. Proteom. 19, 1058–1069. https://doi.org/10.1074/mcp.TIR119.001720 (2020).
Shah, A. D., Goode, R. J. A., Huang, C., Powell, D. R. & Schittenhelm, R. B. LFQ-Analyst: An Easy-To-Use Interactive Web Platform To Analyze and Visualize Label-Free Proteomics Data Preprocessed with MaxQuant. J. Proteome Res. 19, 204–211. https://doi.org/10.1021/acs.jproteome.9b00496. (2020).
Acknowledgements
This work was supported by funding to EAW from the National Sciences and Engineering Research Council of Canada (RGPIN-2019-04740). AL had a Ph.D. scholarship from the Fonds de Recherche du Québec-Santé (FRQS). LG had a Ph.D. scholarship from the FRQS and the Centre de recherche sur le cancer de l’Université Laval. CL had a Ph.D. scholarship from the Canadian Institutes of Health Research (CIHR). CJ had a master’s scholarship from the FRQS and the CIHR. EAW holds a Tier 2 Canada Research Chair, and JPL holds a Junior 2 salary award from the FRQS.
Funding
This work was supported by funding to EAW from the National Sciences and Engineering Research Council of Canada, NSERC (RGPIN-2019-04740).
Author information
Authors and Affiliations
Contributions
Conceptualization, Aurélie Lacouture, Étienne Audet-Walsh; Methodology, Aurélie Lacouture; Investigation, Aurélie Lacouture, Mame Sokhna Sylla, Lucas Germain, Louis Fréville, Camille Lafront, Cindy Weidmann, Cynthia Jobin, Mathieu Laplante, Marc-Étienne Huot, Jean-Philippe Lambert; Writing—original draft, Aurélie Lacouture, Mame Sokhna Sylla, Lucas Germain, Jean-Philippe Lambert, Étienne Audet-Walsh; Writing—review & editing, Aurélie Lacouture, Mame Sokhna Sylla, Lucas Germain, Louis Fréville, Camille Lafront, Cindy Weidmann, Cynthia Jobin, Mathieu Laplante, Marc-Étienne Huot, Jean-Philippe Lambert and Étienne Audet-Walsh; Supervision, Étienne Audet-Walsh.
Corresponding author
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
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Lacouture, A., Sylla, M.S., Germain, L. et al. The mTOR signaling pathway regulates key steps of mammary gland organoid genesis in a temporal manner. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37825-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-37825-z