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Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion.
Lapuente-Santana, Óscar; Sturm, Gregor; Kant, Joan; Ausserhofer, Markus; Zackl, Constantin; Zopoglou, Maria; McGranahan, Nicholas; Rieder, Dietmar; Trajanoski, Zlatko; da Cunha Carvalho de Miranda, Noel Filipe; Eduati, Federica; Finotello, Francesca.
Afiliação
  • Lapuente-Santana Ó; Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, 5612 AZ Eindhoven, the Netherlands.
  • Sturm G; Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), 28029 Madrid, Spain.
  • Kant J; Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, 6020 Innsbruck, Austria.
  • Ausserhofer M; Boehringer Ingelheim International Pharma GmbH & Co KG, 55216 Ingelheim am Rhein, Germany.
  • Zackl C; Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, 5612 AZ Eindhoven, the Netherlands.
  • Zopoglou M; Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada.
  • McGranahan N; Department of Molecular Biology, Digital Science Center (DiSC), University of Innsbruck, 6020 Innsbruck, Austria.
  • Rieder D; Department of Molecular Biology, Digital Science Center (DiSC), University of Innsbruck, 6020 Innsbruck, Austria.
  • Trajanoski Z; Department of Molecular Biology, Digital Science Center (DiSC), University of Innsbruck, 6020 Innsbruck, Austria.
  • da Cunha Carvalho de Miranda NF; Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London WC1E 6DD, UK.
  • Eduati F; Cancer Genome Evolution Research Group, University College London Cancer Institute, London WC1E 6DD, UK.
  • Finotello F; Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, 6020 Innsbruck, Austria.
iScience ; 27(8): 110529, 2024 Aug 16.
Article em En | MEDLINE | ID: mdl-39161957
ABSTRACT
The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomics. We demonstrate that this signature, which we called iHet, is conserved in different cancers and associated with antitumor immunity. Through analysis of single-cell and spatial transcriptomics data, we trace back the cellular origin of the variability explaining the iHet signature. Finally, we demonstrate that iHet has predictive value for cancer immunotherapy, which can be further improved by disentangling three major determinants of anticancer immune responses activity of immune cells, immune infiltration or exclusion, and cancer-cell foreignness. This work shows how transcriptomics data can be integrated to derive a holistic representation of the phenotypic heterogeneity of the TME and to predict its unfolding and fate during immunotherapy with immune checkpoint blockers.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: IScience Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: IScience Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda
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