Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer

Esther H. Lips, Tapsi Kumar, Anargyros Megalios, Lindy L. Visser, Michael Sheinman, Angelo Fortunato, Vandna Shah, Marlous Hoogstraat, Emi Sei, Diego Mallo, Maria Roman-escorza, Ahmed A. Ahmed, Mingchu Xu, Alexandra W. Van Den Belt-dusebout, Wim Brugman, Anna K. Casasent, Karen Clements, Helen R. Davies, Liping Fu, Anita GrigoriadisTimothy M. Hardman, Marielle Krete, Petra Kristel, Michiel De Maaker, Carlo C. Maley, Jeffrey R. Marks, Brian A. Menegaz, Lennart Mulder, Frank Nieboer, Salpie Nowinski, Sarah Pinder, Jelmar Quist, Carolina Salinas-souza, Michael Schaapveld, Marjanka K. Schmidt, Abeer M. Shaaban, Rana Shami, Mathini Sridharan, John Zhang, Hilary Stobart, Deborah Collyar, Serena Nik-zainal, Lodewyk F. A. Wessels, E. Shelley Hwang, Nicholas E. Navin, P. Andrew Futreal, P. Andrew Futreal, E. Shelley Hwang, Jos Jonkers, Jacco, Fariba Behbod, Daniel Rea, Proteeti Bhattacharjee, Donna Pinto, Ellen Verschuur, Marja Van Oirsouw, Alastair M. Thompson, Jelle Wesseling, Elinor J. Sawyer

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Abstract

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5–10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.
Original languageEnglish
Pages (from-to)850-860
Number of pages11
JournalNature Genetics
Volume54
Issue number6
Early online date9 Jun 2022
DOIs
Publication statusPublished - Jun 2022

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