2. Academic Validation
  3. A TCF4-dependent gene regulatory network confers resistance to immunotherapy in melanoma

A TCF4-dependent gene regulatory network confers resistance to immunotherapy in melanoma

  • Cell. 2024 Jan 4;187(1):166-183.e25. doi: 10.1016/j.cell.2023.11.037.
Joanna Pozniak 1,  Dennis Pedri 2,  Ewout Landeloos 3,  Yannick Van Herck 4,  Asier Antoranz 5,  Lukas Vanwynsberghe 6,  Ada Nowosad 6,  Niccolò Roda 6,  Samira Makhzami 6,  Greet Bervoets 6,  Lucas Ferreira Maciel 6,  Carlos Ariel Pulido-Vicuña 6,  Lotte Pollaris 7,  Ruth Seurinck 7,  Fang Zhao 8,  Karine Flem-Karlsen 9,  William Damsky 10,  Limin Chen 11,  Despoina Karagianni 12,  Sonia Cinque 13,  Sam Kint 14,  Katy Vandereyken 14,  Benjamin Rombaut 7,  Thierry Voet 14,  Frank Vernaillen 15,  Wim Annaert 16,  Diether Lambrechts 17,  Veerle Boecxstaens 18,  Yvan Saeys 7,  Joost van den Oord 19,  Francesca Bosisio 19,  Panagiotis Karras 6,  A Hunter Shain 11,  Marcus Bosenberg 20,  Eleonora Leucci 13,  Annette Paschen 8,  Florian Rambow 21,  Oliver Bechter 22,  Jean-Christophe Marine 23
Affiliations

Affiliations

  • 1 Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium; Department of Oncology, KU Leuven, Leuven, Belgium. Electronic address: joanna.pozniak@kuleuven.be.
  • 2 Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium; Department of Oncology, KU Leuven, Leuven, Belgium; Laboratory for Membrane Trafficking, Center for Brain and Disease Research, VIB, Leuven, Belgium.
  • 3 Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium; Department of Oncology, KU Leuven, Leuven, Belgium; Department of General Medical Oncology, UZ Leuven, Leuven, Belgium.
  • 4 Department of General Medical Oncology, UZ Leuven, Leuven, Belgium.
  • 5 Laboratory of Translational Cell and Tissue Research, Department of Imaging and Pathology, KU Leuven and UZ Leuven, Leuven, Belgium.
  • 6 Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium; Department of Oncology, KU Leuven, Leuven, Belgium.
  • 7 Data Mining and Modeling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium; Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
  • 8 Laboratory of Molecular Tumor Immunology, Department of Dermatology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany.
  • 9 Department of Dermatology, Yale University, 15 York Street, New Haven, CT 05610, USA.
  • 10 Departments of Dermatology and Pathology, Yale University, 15 York Street, New Haven, CT 05610, USA.
  • 11 Department of Dermatology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
  • 12 Immune Regulation and Tumor Immunotherapy Group, Cancer Immunology Unit, Research Department of Haematology, UCL Cancer Institute, London WC1E 6DD, UK.
  • 13 Laboratory for RNA Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium.
  • 14 Laboratory of Reproductive Genomics, Department of Human Genetics, KU Leuven, Leuven, Belgium; KU Leuven Institute for Single Cell Omics (LISCO), KU Leuven, Leuven, Belgium.
  • 15 Bioinformatics Core, VIB, Ghent, Belgium.
  • 16 Laboratory for Membrane Trafficking, Center for Brain and Disease Research, VIB, Leuven, Belgium.
  • 17 Laboratory of Translational Genetics, Center for Cancer Biology, VIB, Leuven, Belgium; Center for Human Genetics, KU Leuven, Leuven, Belgium.
  • 18 Department of Surgical Oncology, UZ Leuven, Leuven, Belgium.
  • 19 Laboratory of Translational Cell and Tissue Research, Department of Pathology, UZ Leuven, Leuven, Belgium.
  • 20 Departments of Dermatology, Pathology and Immunobiology, Yale University, New Haven, CT 05610, USA.
  • 21 Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium; Department of Oncology, KU Leuven, Leuven, Belgium; Department of Applied Computational Cancer Research, Institute for AI in Medicine (IKIM), University Hospital Essen, Essen, Germany; University Duisburg-Essen, Essen, Germany. Electronic address: florian.rambow@uk-essen.de.
  • 22 Department of General Medical Oncology, UZ Leuven, Leuven, Belgium. Electronic address: oliver.bechter@uzleuven.be.
  • 23 Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium; Department of Oncology, KU Leuven, Leuven, Belgium. Electronic address: jeanchristophe.marine@kuleuven.be.
PMID: 38181739 DOI: 10.1016/j.cell.2023.11.037
Abstract

To better understand intrinsic resistance to immune checkpoint blockade (ICB), we established a comprehensive view of the cellular architecture of the treatment-naive melanoma ecosystem and studied its evolution under ICB. Using single-cell, spatial multi-omics, we showed that the tumor microenvironment promotes the emergence of a complex melanoma transcriptomic landscape. Melanoma cells harboring a mesenchymal-like (MES) state, a population known to confer resistance to targeted therapy, were significantly enriched in early on-treatment biopsies from non-responders to ICB. TCF4 serves as the hub of this landscape by being a master regulator of the MES signature and a suppressor of the melanocytic and antigen presentation transcriptional programs. Targeting TCF4 genetically or pharmacologically, using a bromodomain inhibitor, increased immunogenicity and sensitivity of MES cells to ICB and targeted therapy. We thereby uncovered a TCF4-dependent regulatory network that orchestrates multiple transcriptional programs and contributes to resistance to both targeted therapy and ICB in melanoma.

Keywords

BET inhibition; EMT; TCF4; antigen presentation; checkpoint immunotherapy; dedifferentiation; intra-tumor heterogeneity; melanoma; single-cell transcriptomics; tumor microenvironment.

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