Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution

Creators: Murrow, Lyndsay M.; Weber, Robert J.; Caruso, Joseph A.; McGinnis, Christopher S.; Phong, Kiet; Gascard, Philippe; Rabadam, Gabrielle; Borowsky, Alexander D.; Desai, Tejal A.; Thomson, Matthew¹; Tlsty, Thea; Gartner, Zev J.

1. California Institute of Technology

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Abstract

The rise and fall of estrogen and progesterone across menstrual cycles and during pregnancy regulates breast development and modifies cancer risk. How these hormones impact each cell type in the breast remains poorly understood because they act indirectly through paracrine networks. Using single-cell analysis of premenopausal breast tissue, we reveal a network of coordinated transcriptional programs representing the tissue-level response to changing hormone levels. Our computational approach, DECIPHER-seq, leverages person-to-person variability in breast composition and cell state to uncover programs that co-vary across individuals. We use differences in cell-type proportions to infer a subset of programs that arise from direct cell-cell interactions regulated by hormones. Further, we demonstrate that prior pregnancy and obesity modify hormone responsiveness through distinct mechanisms: obesity reduces the proportion of hormone-responsive cells, whereas pregnancy dampens the direct response of these cells to hormones. Together, these results provide a comprehensive map of the cycling human breast.

Additional Information

© 2022 The Authors. Published by Elsevier Under a Creative Commons license - Attribution 4.0 International (CC BY 4.0). Received 2 February 2021, Revised 2 March 2022, Accepted 22 June 2022, Available online 20 July 2022. We thank Drs. Tom Norman and Jonathan Weissman for technical support and for generously providing access to equipment and computing resources. Sequencing was performed in the Center for Advanced Technology at UCSF. Tissue samples were provided by the Cooperative Human Tissue Network (CHTN), which is funded by the National Cancer Institute. Other investigators may have received specimens from the same subjects. Samples from the Susan G. KTB at the IU Simon Cancer Center were used in this study. We thank contributors, including Indiana University who collected samples used in this study, as well as donors and their families, whose help and participation made this work possible. This research was supported by grants from the Department of Defense Breast Cancer Research Program (W81XWH-10-1-1023 and W81XWH-13-1-0221), NIH (U01CA199315 and DP2 HD080351-01), the NSF (MCB-1330864), and the UCSF Center for Cellular Construction (DBI-1548297), an NSF Science and Technology Center, to Z.J.G. Z.J.G. is a Chan Zuckerberg BioHub Investigator. L.M.M. is a former Damon Runyon Fellow supported by the Damon Runyon Cancer Research Foundation (DRG-2239-15). Author contributions. L.M.M., R.J.W., and Z.J.G. conceived the project. L.M.M., J.A.C., R.J.W., C.S.M., and K.P. performed the sequencing experiments. C.S.M. generated aligned reads and barcode matrices. C.S.M. and L.M.M. performed sample demultiplexing. P.G. coordinated sample acquisition and provided critical guidance for sample selection. L.M.M. and J.A.C. performed fluorescent immunohistochemistry and RNA-FISH experiments. L.M.M. and J.A.C. performed flow cytometry experiments. L.M.M. and J.A.C. performed histopathology on tissue sections. A.D.B. performed histopathological tissue analysis. L.M.M. analyzed and visualized the data. L.M.M., C.S.M., and G.R. wrote and tested the code used in data analysis. M.T. provided guidance in data analyses and computational approaches. T.T. and A.D.B. provided guidance in human breast biology. T.T., M.T., and Z.J.G. provided critical resources. T.A.D., M.T., T.T., and Z.J.G. supervised the project. L.M.M. and Z.J.G. wrote the manuscript. All authors reviewed and edited the manuscript. Declaration of interests. Z.J.G. and C.S.M. hold patents related to the MULTI-seq barcoding method. Z.J.G. is an equity holder in Scribe Biosciences and Provenance bio and a member of the scientific advisory board of Serotiny Bio. C.S.M. is a consultant for ImYoo. Since January 10, 2022, L.M.M. is an employee of Genentech, a member of the Roche group. Inclusion and diversity. We worked to ensure ethnic or other types of diversity in the recruitment of human subjects. One or more of the authors of this paper self-identifies as a member of the LGBTQ+ community. One or more of the authors of this paper self-identifies as an underrepresented ethnic minority in science. One or more of the authors of this paper self-identifies as living with a disability. Data and code availability: Single-cell RNA-seq data (raw FASTQ files, processed gene expression and barcode count matrices, and de-identified patient metadata) have been deposited at the Gene Expression Omnibus (GEO: GSE198732) and are publicly available as of the date of publication. Accession numbers are listed in the key resources table. All original code has been deposited at Zenodo and Github and is publicly available as of the date of publication. DOIs are listed in the key resources table. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

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