Céline Callens1, Keltouma Driouch1, Anaïs Boulai1, Zakia Tariq1, Aurélie Comte2, Frédérique Berger3, Lisa Belin3, Ivan Bièche1, Vincent Servois4, Patricia Legoix5, Virginie Bernard5, Sylvain Baulande5, Walid Chemlali1, François-Clément Bidard2, Virginie Fourchotte6, Anne Vincent- Salomon7, Etienne Brain8, Rosette Lidereau1, Thomas Bachelot9, Mahasti Saghatchian10, Mario Campone11, Sylvie Giacchetti12, Brigitte Sigal Zafrani7, Paul Cottu13. 1. Genetics Department, Institut Curie, PSL Research University, Paris, France. 2. Department of Medical Oncology, Institut Curie, PSL Research University, 26 rue d'Ulm, 75005, Paris, France. 3. Department of Biostatistics, Institut Curie, Saint-Cloud, France. 4. Imaging Department, Institut Curie, PSL Research University, Paris, France. 5. Institut Curie Genomics of Excellence (ICGex) Platform, Institut Curie Research Center, PSL Research University, Paris, France. 6. Surgery Department, Institut Curie, Paris, France. 7. Pathology and Tumor Biology Department, Institut Curie, PSL Research University, Paris, France. 8. Medical Oncology, Institut Curie, Saint-Cloud, France. 9. Centre Léon Bérard, Lyon, France. 10. Gustave Roussy Cancer Campus, Villejuif, France. 11. Institut de Cancérologie de l'Ouest Nantes, Nantes, France. 12. Hôpital Saint Louis, Breast diseases center, Paris, France. 13. Department of Medical Oncology, Institut Curie, PSL Research University, 26 rue d'Ulm, 75005, Paris, France. paul.cottu@curie.fr.
Abstract
BACKGROUND: Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of metastatic subtyping during the initial metastatic event in a prospective study. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting the findings transferability to clinical use. METHODS: We developed a multicenter, single-arm, prospective clinical trial in order to address these issues. Between November 2010 and September 2013, 123 eligible patients were included. Patients at the first, untreated metastatic event were eligible. All matched primary tumors and metastatic samples were centrally reviewed for pathological typing. Targeted and whole-exome sequencing was applied to matched pairs of frozen tissue. A multivariate overall survival analysis was performed (median follow-up 64 months). RESULTS: Per central review in 84 patients (out of 130), we show that luminal A breast tumors are more prone to subtype switching. By combining targeted sequencing of a 91 gene panel (n = 67) and whole-exome sequencing (n = 30), a slight excess of mutations is observed in the metastases. Luminal A breast cancer has the most heterogeneous mutational profile and the highest number of mutational signatures, when comparing primary tumor and the matched metastatic tissue. Tumors with a subtype change have more mutations that are private. The metastasis-specific mutation load is significantly higher in late than in de novo metastases. The most frequently mutated genes were TP53 and PIK3CA. The most frequent metastasis-specific druggable genes were PIK3CA, PTEN, KDR, ALK, CDKN2A, NOTCH4, POLE, SETD2, SF3B1, and TSC2. Long-term outcome is driven by a combination of tumor load and metastasis biology. CONCLUSIONS: Profiling of the first, untreated, metastatic event of breast cancer reveals a profound heterogeneity mostly in luminal A tumors and in late metastases. Based on this profiling, we can derive information relevant to prognosis and therapeutic intervention, which support current guidelines recommending a biopsy at the first metastatic relapse. TRIAL REGISTRATION: The trial was registered at ClinicalTrials.gov ( NCT01956552 ).
BACKGROUND: Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of metastatic subtyping during the initial metastatic event in a prospective study. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting the findings transferability to clinical use. METHODS: We developed a multicenter, single-arm, prospective clinical trial in order to address these issues. Between November 2010 and September 2013, 123 eligible patients were included. Patients at the first, untreated metastatic event were eligible. All matched primary tumors and metastatic samples were centrally reviewed for pathological typing. Targeted and whole-exome sequencing was applied to matched pairs of frozen tissue. A multivariate overall survival analysis was performed (median follow-up 64 months). RESULTS: Per central review in 84 patients (out of 130), we show that luminal A breast tumors are more prone to subtype switching. By combining targeted sequencing of a 91 gene panel (n = 67) and whole-exome sequencing (n = 30), a slight excess of mutations is observed in the metastases. Luminal A breast cancer has the most heterogeneous mutational profile and the highest number of mutational signatures, when comparing primary tumor and the matched metastatic tissue. Tumors with a subtype change have more mutations that are private. The metastasis-specific mutation load is significantly higher in late than in de novo metastases. The most frequently mutated genes were TP53 and PIK3CA. The most frequent metastasis-specific druggable genes were PIK3CA, PTEN, KDR, ALK, CDKN2A, NOTCH4, POLE, SETD2, SF3B1, and TSC2. Long-term outcome is driven by a combination of tumor load and metastasis biology. CONCLUSIONS: Profiling of the first, untreated, metastatic event of breast cancer reveals a profound heterogeneity mostly in luminal A tumors and in late metastases. Based on this profiling, we can derive information relevant to prognosis and therapeutic intervention, which support current guidelines recommending a biopsy at the first metastatic relapse. TRIAL REGISTRATION: The trial was registered at ClinicalTrials.gov ( NCT01956552 ).
Entities:
Keywords:
Breast cancer; Metastasis; Next generation sequencing; Prognosis; Targetable genes; de novo metastases
Authors: Willemijne A M E Schrijver; Karijn P M Suijkerbuijk; Carla H van Gils; Elsken van der Wall; Cathy B Moelans; Paul J van Diest Journal: J Natl Cancer Inst Date: 2018-06-01 Impact factor: 13.506
Authors: D Pectasides; A Gaglia; P Arapantoni-Dadioti; A Bobota; C Valavanis; V Kostopoulou; N Mylonakis; A Karabelis; M Pectasides; T Economopoulos Journal: Anticancer Res Date: 2006 Jan-Feb Impact factor: 2.480
Authors: François Bertucci; Charlotte K Y Ng; Anne Patsouris; Thomas Filleron; Christophe Le Tourneau; Fabrice André; 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 De Filippo; Naveen Babbar; Daniel Birnbaum Journal: Nature Date: 2019-05-22 Impact factor: 49.962
Authors: Samuel W Brady; Jasmine A McQuerry; Yi Qiao; Stephen R Piccolo; Gajendra Shrestha; David F Jenkins; Ryan M Layer; Brent S Pedersen; Ryan H Miller; Amanda Esch; Sara R Selitsky; Joel S Parker; Layla A Anderson; Brian K Dalley; Rachel E Factor; Chakravarthy B Reddy; Jonathan P Boltax; Dean Y Li; Philip J Moos; Joe W Gray; Laura M Heiser; Saundra S Buys; Adam L Cohen; W Evan Johnson; Aaron R Quinlan; Gabor Marth; Theresa L Werner; Andrea H Bild Journal: Nat Commun Date: 2017-11-01 Impact factor: 14.919
Authors: Dan R Robinson; Yi-Mi Wu; Robert J Lonigro; Pankaj Vats; Erin Cobain; Jessica Everett; Xuhong Cao; Erica Rabban; Chandan Kumar-Sinha; Victoria Raymond; Scott Schuetze; Ajjai Alva; Javed Siddiqui; Rashmi Chugh; Francis Worden; Mark M Zalupski; Jeffrey Innis; Rajen J Mody; Scott A Tomlins; David Lucas; Laurence H Baker; Nithya Ramnath; Ann F Schott; Daniel F Hayes; Joseph Vijai; Kenneth Offit; Elena M Stoffel; J Scott Roberts; David C Smith; Lakshmi P Kunju; Moshe Talpaz; Marcin Cieślik; Arul M Chinnaiyan Journal: Nature Date: 2017-08-02 Impact factor: 49.962
Authors: Weiyi Toy; Yang Shen; Helen Won; Bradley Green; Rita A Sakr; Marie Will; Zhiqiang Li; Kinisha Gala; Sean Fanning; Tari A King; Clifford Hudis; David Chen; Tetiana Taran; Gabriel Hortobagyi; Geoffrey Greene; Michael Berger; José Baselga; Sarat Chandarlapaty Journal: Nat Genet Date: 2013-11-03 Impact factor: 38.330