Abstract
Abstract With the widespread adoption of breast cancer screening the incidence of pure ductal carcinoma in situ (DCIS) has increased. As DCIS is considered a non-obligate precursor of invasive ductal carcinoma most women with pure DCIS are treated with breast conserving surgery (BCS) +/- radiotherapy. However, for many this is likely to be overtreatment as only a minority will develop a subsequent ipsilateral recurrence. Studies also show that only ~60% of these ipsilateral recurrences are invasive disease with the remainder being pure DCIS. To predict which women are most likely to benefit from interventions, there is a need to identify biomarkers that are associated with invasive recurrence. Our aim was to assess whether copy number aberrations (CNAs) could be used to identify DCIS that was likely to recur as invasive disease or remain recurrence-free during long-time follow up. We performed somatic copy number profiling on 309 pure DCIS samples that had not developed an ipsilateral event (controls), 198 that had developed subsequent ipsilateral invasive disease (INV-cases) and 58 that had developed subsequent ipsilateral pure DCIS (DCIS-cases). The samples were obtained from two large nation-wide cohorts: the Sloane cohort, a prospective breast screening cohort from the UK with a median follow up of 12.5 years and a Dutch population based cohort, with a median follow up of 13 years. CNAs were assessed using the CytoSNP array or low pass whole genome sequencing and analyzed using GISTIC. Integrative cluster (IntClust) subtyping revealed that only 5 subtypes were well represented in DCIS compared to 10 in invasive disease and the distribution of clusters between INV-cases and controls was similar with the exception of IntClust 4, which was significantly more common in controls (P= 0.025, Fishers exact test). IntClust 4 is characterized to have low levels of genomic instability and a CNA-devoid. INV-cases were globally more aberrant than controls (P = 0.006, Wilcoxon test) as assessed by the chromosomal instability index (CIN) score. GISTIC identified 17 recurrent amplifications, 21 recurrent gains and 22 recurrent losses in the whole cohort. Six of these regions were more common in INV-cases compared to controls: amplifications at 17q24.1 and 8p11.23, losses at 1p36.13 and 11q23.2 and gains at 17q21.33 and 16p (Nominal P < 0.05 and FDR < 0.1, Fishers exact test). Subgroup analysis of ER+, Her2- INV-cases versus controls revealed an additional differential CNA, amplification at 11q13.3 more common in cases. DCIS-cases had similar CNAs to INV-cases and were more aberrant than controls in terms of CIN score (P < 0.037, Wilcoxon test) but not as aberrant as INV-cases. In conclusion, we have identified potential CNAs that are associated with invasive recurrence. Further analysis will integrate gene expression with copy number data to identify which genes are being targeted by these CNAs in order to identify pathways important in progression of DCIS. Citation Format: Ahmed A. Ahmed, Maria Roman-Escorza, Tycho Bismeijer, Michael Sheinman, Vandna Shah, Rana Shami, Jeffrey R. Marks, Lorraine M. King, Anargyros Megalios, Lindy L. Visser, Marlous Hoogstraat, Helen R. Davies, Tapsi Kumar, Deborah Collyar, Hilary Stobart, Sarah Pinder, Nicholas N. Navin, Andrew Futreal, Serena Nik-Zainal, E. Shelley Hwang, Lodewyk F. Wessels, Esther H. Lips, Alastair Thompson, Jelle Wesseling, Elinor J. Sawyer. Copy number analysis of pure DCIS and association with recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5108.
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