Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications

Breast Cancer Research

Mario Campone¹  Catherine Guérin-Charbonnel²  Wilfried Gouraud²  Pascal Jézéquel²  Delphine Loussouarn³  Véronique Verrièle⁴  Olivier Kerdraon⁴  Suzette Delaloge⁵  Florence Dalenc⁶  Andrea Gombos⁷  Jean-Luc Canon⁸  Hubert Hondermarck⁹  Jérôme Lemonnier^1,10  Hamza Lasla^1,11 

[1] CRCINA, UMR 1232 INSERM, Université de Nantes, Université d’Angers, Institut de Recherche en Santé-Université de Nantes;Département de Biopathologie, Unité Mixte de Génomique du Cancer, Institut de Cancérologie de l’Ouest – site René Gauducheau;Départment d’Anatomie et Cytologie Pathologiques, Centre Hospitalo-Universitaire;Laboratoire d’Anatomie et Cytologie Pathologiques, Institut de Cancérologie de l’Ouest;Oncologie Médicale, Gustave Roussy;Oncologie Médicale, IUCT-Oncopole;Oncologie Médicale, Institut Jules Bordet;Oncologie-Hématologie, Grand Hôpital de Charleroi;School of Biomedical Sciences and Pharmacy, Hunter Medical Research Institute, University of Newcastle;UCBG, R&D UNICANCER, Fédération Nationale des Centres de Lutte Contre le Cancer;Unité de Bioinfomique, Institut de Cancérologie de l’Ouest;

关键词: Breast cancer;    Triple-negative;    Transcriptomics;    Molecular subtypes;    Immunome;    Tertiary lymphoid structures;   

DOI  :  10.1186/s13058-019-1148-6

来源: DOAJ

【 摘 要 】

Abstract Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies.

【 授权许可】

Unknown