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

Authors :
Lips, Esther H.
Kumar, Tapsi
Megalios, Anargyros
Visser, Lindy L.
Sheinman, Michael
Fortunato, Angelo
Shah, Vandna
Hoogstraat, Marlous
Sei, Emi
Mallo, Diego
Roman-Escorza, Maria
Ahmed, Ahmed A.
Xu, Mingchu
van den Belt-Dusebout, Alexandra W.
Brugman, Wim
Casasent, Anna K.
Clements, Karen
Davies, Helen R.
Fu, Liping
Grigoriadis, Anita
Hardman, Timothy M.
King, Lorraine M.
Krete, Marielle
Kristel, Petra
de Maaker, Michiel
Maley, Carlo C.
Marks, Jeffrey R.
Menegaz, Brian A.
Mulder, Lennart
Nieboer, Frank
Nowinski, Salpie
Pinder, Sarah
Quist, Jelmar
Salinas-Souza, Carolina
Schaapveld, Michael
Schmidt, Marjanka K.
Shaaban, Abeer M.
Shami, Rana
Sridharan, Mathini
Zhang, John
Stobart, Hilary
Collyar, Deborah
Nik-Zainal, Serena
Wessels, Lodewyk F. A.
Hwang, E. Shelley
Navin, Nicholas E.
Futreal, P. Andrew
Thompson, Alastair M.
Wesseling, Jelle
Sawyer, Elinor J.
Source :
Nature Genetics; 20220101, Issue: Preprints p1-11, 11p
Publication Year :
2022

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.

Details

Language :
English
ISSN :
10614036 and 15461718
Issue :
Preprints
Database :
Supplemental Index
Journal :
Nature Genetics
Publication Type :
Periodical
Accession number :
ejs59921513
Full Text :
https://doi.org/10.1038/s41588-022-01082-3