• Medientyp: E-Artikel
  • Titel: Three-dimensional Imaging Reveals Immune-driven Tumor-associated High Endothelial Venules as a Key Correlate of Tumor Rejection Following Depletion of Regulatory T Cells
  • Beteiligte: Milutinovic, Stefan; Abe, Jun; Jones, Emma; Kelch, Inken; Smart, Kathryn; Lauder, Sarah N.; Somerville, Michelle; Ware, Carl; Godkin, Andrew; Stein, Jens V.; Bogle, Gib; Gallimore, Awen
  • Erschienen: American Association for Cancer Research (AACR), 2022
  • Erschienen in: Cancer Research Communications
  • Sprache: Englisch
  • DOI: 10.1158/2767-9764.crc-21-0123
  • ISSN: 2767-9764
  • Schlagwörter: General Earth and Planetary Sciences
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  • Beschreibung: <jats:p>High endothelial venules (HEV) are specialized post capillary venules that recruit naïve T cells and B cells into secondary lymphoid organs (SLO) such as lymph nodes (LN). Expansion of HEV networks in SLOs occurs following immune activation to support development of an effective immune response. In this study, we used a carcinogen-induced model of fibrosarcoma to examine HEV remodeling after depletion of regulatory T cells (Treg). We used light sheet fluorescence microscopy imaging to visualize entire HEV networks, subsequently applying computational tools to enable topological mapping and extraction of numerical descriptors of the networks. While these analyses revealed profound cancer- and immune-driven alterations to HEV networks within LNs, these changes did not identify successful responses to treatment. The presence of HEV networks within tumors did however clearly distinguish responders from nonresponders. Finally, we show that a successful treatment response is dependent on coupling tumor-associated HEV (TA-HEV) development to T-cell activation implying that T-cell activation acts as the trigger for development of TA-HEVs which subsequently serve to amplify the immune response by facilitating extravasation of T cells into the tumor mass.</jats:p><jats:sec><jats:title>Significance:</jats:title><jats:p>We used three-dimensional imaging methods with computational tools to analyze networks of specialized blood vessels called HEVs in LNs and tumors. By applying these techniques in a mouse model of carcinogen-induced tumors, we could identify network changes after depletion of Tregs.</jats:p></jats:sec>
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