Genomic characterization of metastatic breast cancers

François Bertucci, Charlotte K. Y. Ng, Anne Patsouris, Nathalie Droin, Salvatore Piscuoglio, Nadine Carbuccia, Jean Charles Soria, Alicia Tran Dien, Yahia Adnani, Maud Kamal, Séverine Garnier, Guillaume Meurice, Marta Jimenez, Semih Dogan, Benjamin Verret, Max Chaffanet, Thomas Bachelot, Mario Campone, Claudia Lefeuvre, Herve Bonnefoi, Florence Dalenc, Alexandra Jacquet, Maria R. Filippo, Naveen Babbar, Daniel Birnbaum, Thomas Filleron, Christophe Tourneau and Fabrice André ()
Additional contact information
François Bertucci: CRCM, Predictive Oncology team, Inserm, Aix-Marseille Univ, CNRS, Institut Paoli-Calmettes
Charlotte K. Y. Ng: University Hospital Basel
Anne Patsouris: Inserm
Nathalie Droin: Genomic Core Facility UMS AMMICA Gustave Roussy Cancer Campus
Salvatore Piscuoglio: University Hospital Basel
Nadine Carbuccia: CRCM, Predictive Oncology team, Inserm, Aix-Marseille Univ, CNRS, Institut Paoli-Calmettes
Jean Charles Soria: Université Paris Sud
Alicia Tran Dien: Gustave Roussy Cancer Campus
Yahia Adnani: Gustave Roussy Cancer Campus
Maud Kamal: Institut Curie
Séverine Garnier: CRCM, Predictive Oncology team, Inserm, Aix-Marseille Univ, CNRS, Institut Paoli-Calmettes
Guillaume Meurice: Gustave Roussy Cancer Campus
Marta Jimenez: Unicancer
Semih Dogan: Inserm, Gustave Roussy Cancer Campus
Benjamin Verret: Inserm, Gustave Roussy Cancer Campus
Max Chaffanet: CRCM, Predictive Oncology team, Inserm, Aix-Marseille Univ, CNRS, Institut Paoli-Calmettes
Thomas Bachelot: Centre Léon Bérard
Mario Campone: Inserm
Claudia Lefeuvre: Centre Eugène Marquis
Herve Bonnefoi: Institut Bergonié
Florence Dalenc: Institut Claudius-Regaud, IUCT-oncopôle
Alexandra Jacquet: Unicancer
Maria R. Filippo: University Hospital Basel
Naveen Babbar: Novartis Pharmaceuticals Corporation
Daniel Birnbaum: CRCM, Predictive Oncology team, Inserm, Aix-Marseille Univ, CNRS, Institut Paoli-Calmettes
Thomas Filleron: Institut Claudius-Regaud, IUCT-oncopôle
Christophe Tourneau: Institut Curie
Fabrice André: Université Paris Sud

Nature, 2019, vol. 569, issue 7757, 560-564

Abstract: Abstract Metastasis is the main cause of death for patients with breast cancer. Many studies have characterized the genomic landscape of breast cancer during its early stages. However, there is evidence that genomic alterations are acquired during the evolution of cancers from their early to late stages, and that the genomic landscape of early cancers is not representative of that of lethal cancers1–7. Here we investigated the landscape of somatic alterations in 617 metastatic breast cancers. Nine driver genes (TP53, ESR1, GATA3, KMT2C, NCOR1, AKT1, NF1, RIC8A and RB1) were more frequently mutated in metastatic breast cancers that expressed hormone receptors (oestrogen and/or progesterone receptors; HR+) but did not have high levels of HER2 (HER2−; n = 381), when compared to early breast cancers from The Cancer Genome Atlas. In addition, 18 amplicons were more frequently observed in HR+/HER2− metastatic breast cancers. These cancers showed an increase in mutational signatures S2, S3, S10, S13 and S17. Among the gene alterations that were enriched in HR+/HER2− metastatic breast cancers, mutations in TP53, RB1 and NF1, together with S10, S13 and S17, were associated with poor outcome. Metastatic triple-negative breast cancers showed an increase in the frequency of somatic biallelic loss-of-function mutations in genes related to homologous recombination DNA repair, compared to early triple-negative breast cancers (7% versus 2%). Finally, metastatic breast cancers showed an increase in mutational burden and clonal diversity compared to early breast cancers. Thus, the genomic landscape of metastatic breast cancer is enriched in clinically relevant genomic alterations and is more complex than that of early breast cancer. The identification of genomic alterations associated with poor outcome will allow earlier and better selection of patients who require the use of treatments that are still in clinical trials. The genetic complexity observed in advanced breast cancer suggests that such treatments should be introduced as early as possible in the disease course.

Date: 2019
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DOI: 10.1038/s41586-019-1056-z

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