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Tumour clonality in paired invasive breast carcinomas

Poster
Authors Jana Biermann
Toshima Z Parris
Szilard Nemes
Anna Danielsson
Hanna Engqvist
Elisabeth Werner Rönnerman
Eva Forssell-Aronsson
Anikó Kovács
Per Karlsson
Khalil Helou
Published in Cancer Research
ISSN 0008-5472
Publication year 2019
Published at Institute of Clinical Sciences, Department of Radiation Physics
Institute of Clinical Sciences, Department of Oncology
Sahlgrenska Cancer Center
Institute of Biomedicine, Department of Pathology
Language en
Links cancerres.aacrjournals.org/content/...
Keywords Bilateral breast cancer; Intertumour heterogeneity; Ipsilateral breast cancer; Multiple breast cancer; Similarity index; Tumour clonality
Subject categories Bioinformatics (Computational Biology), Genetics, Cancer and Oncology

Abstract

Background: Multiple invasive breast tumours may represent either independent primary tumours or clonal recurrences of the first tumour, where the same progenitor cell gives rise to all of the detected tumours. Consequently, the driver events for the progenitor cell need to have been identical in early tumour development. Molecular classification of tumour clonality is not currently evaluated in multiple invasive breast carcinomas, despite evidence suggesting common clonal origins. Furthermore, there is no consensus about which type of biological data (e.g. copy number, mutation, histology) and especially which statistical method is most suitable to distinguish clonal recurrences from independent primary tumours. Methods: Thirty-seven invasive breast tumour pairs were stratified by laterality (bilateral vs. ipsilateral) and the time interval between the diagnoses of the first and second tumours (synchronous vs. metachronous). Both tumours from the same patient were analysed by integrating clinical characteristics (n = 37), DNA copy number (n = 37), DNA methylation (n = 8), gene expression microarray (n = 7), RNA sequencing (n = 3), and SNP genotyping data (n = 3). Different statistical methods, e.g. the diagnostic similarity index (SI), distance measure, shared segment analysis etc., were used to classify the tumours from the same patient as clonally related recurrences or independent primary tumours. Results: The SI applied on DNA copy numbers derived from aCGH (array comparative genomic hybridization) data was determined as the strongest indicator of clonal relatedness as it showed the highest concordance with all other methods. The distance measure was the most conservative method and the shared segment analysis most liberal. Concordant evidence for tumour clonality was found in 46% (17/37) of the patients. Notably, no significant association was found between the clinical characteristics and molecular tumour features. Conclusions: A more accurate classification of clonal relatedness between multiple breast tumours may help to mitigate treatment failure and relapse by integrating tumour-associated molecular features, clinical parameters, and statistical methods. In cases of extremely similar or different tumour pairs, the results showed consistency regardless of the method used. The SI can be easily integrated into clinical routine using FFPE samples to obtain copy number data. However, clinical guidelines with exact thresholds need to be defined to standardize clonality testing in a routine diagnostic setting.

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