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Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

  1. Author:
    Cherry, Christopher
    Andorko, James I
    Krishnan, Kavita
    Mejías, Joscelyn C
    Nguyen, Helen Hieu
    Stivers, Katlin B
    Gray-Gaillard, Elise F
    Ruta, Anna
    Han, Jin
    Hamada, Naomi
    Hamada, Masakazu
    Sturmlechner, Ines
    Trewartha, Shawn
    Michel, John H
    Davenport Huyer, Locke
    Wolf,Matthew
    Tam, Ada J
    Peña, Alexis N
    Keerthivasan, Shilpa
    Le Saux, Claude Jordan
    Fertig, Elana J
    Baker, Darren J
    Housseau, Franck
    van Deursen, Jan M
    Pardoll, Drew M
    Elisseeff, Jennifer H [ORCID]

  2. Author Address

    Translational Tissue Engineering Center, Wilmer Eye Institute and the Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA., Department of Pediatrics, Molecular Genetics Section, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, Netherlands., Laboratory of Cancer Immunometabolism, Center for Cancer Research, National Cancer Institute, Frederick, MD, USA., Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Bloomberg~Kimmel Institute for Cancer Immunotherapy and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Tumor Microenvironment Thematic Research Center, Bristol Myers Squibb, San Francisco, CA, USA., Department of Medicine, University of California, San Francisco, San Francisco, CA, USA., Department of Biomedical Engineering and Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA., Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA., Paul F. Glenn Center for the Biology of Aging Research at Mayo Clinic, Rochester, MN, USA., Translational Tissue Engineering Center, Wilmer Eye Institute and the Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jhe@jhu.edu., Bloomberg~Kimmel Institute for Cancer Immunotherapy and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jhe@jhu.edu.,
    1. Year: 2023
    2. Date: Apr 20
    3. Epub Date: 2023 04 20
  2. Journal: GeroScience
  4. Type of Article: Article
  1. Abstract:

    Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells' (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo-derived senescence signature (SenSig) using a foreign body response-driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and "cartilage-like" fibroblasts as senescent and defined cell type-specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34-CSF1R-TGFßR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies. © 2023. The Author(s), under exclusive licence to American Aging Association.

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External Sources

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  2. DOI: 10.1007/s11357-023-00785-7
  3. PMID: 37079217
  4. PII : 10.1007/s11357-023-00785-7

Library Notes

  1. Fiscal Year: FY2022-2023
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