Spatial transcriptomics reveals substantial heterogeneity in triple-negative breast cancer with potential clinical implications

Xiaoxiao Wang(Université Libre de Bruxelles), David Venet(Université Libre de Bruxelles), Frédéric Lifrange, Denis Larsimont(Université Libre de Bruxelles), Mattia Rediti(Université Libre de Bruxelles), Linnea Stenbeck(KTH Royal Institute of Technology), Floriane Dupont(Université Libre de Bruxelles), Ghizlane Rouas(Université Libre de Bruxelles), Andrea Joaquin Garcia(Université Libre de Bruxelles), Ligia Craciun(Université Libre de Bruxelles), Laurence Buisseret(Université Libre de Bruxelles), Michail Ignatiadis(Université Libre de Bruxelles), Marcela Carausu(Université Libre de Bruxelles), Nayanika Bhalla(KTH Royal Institute of Technology), Yuvarani Masarapu(KTH Royal Institute of Technology), Eva Gracia Villacampa(KTH Royal Institute of Technology), Lovisa Franzén(KTH Royal Institute of Technology), Sami Saarenpää(KTH Royal Institute of Technology), Linda Kvastad(KTH Royal Institute of Technology), Kim Thrane(KTH Royal Institute of Technology), Joakim Lundeberg(KTH Royal Institute of Technology), Françoise Rothé(Université Libre de Bruxelles), Christos Sotiriou(Université Libre de Bruxelles)
Nature Communications
November 26, 2024
Cited by 70Open Access
Full Text

Abstract

While triple-negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigate TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We perform an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures leads to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identifies nine TNBC spatial archetypes, further validated in external datasets. Several spatial archetypes are associated with disease outcome and characterized by potentially actionable features. In this work, we provide a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy. Triple-negative breast cancer (TNBC) is a heterogenous disease with several molecular subtypes previously described. Here the authors perform a spatial transcriptomics analysis on a series of 92 patients, providing additional insights into the heterogeneity of TNBC, with implications for clinical outcomes and therapy.


Related Papers

No related papers found

Powered by citation graph analysis