Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Integrated Epigenomic and Genomic View on Phyllodes and Phyllodes-Like Breast Tumors

Version 1 : Received: 2 December 2021 / Approved: 22 December 2021 / Online: 22 December 2021 (12:46:50 CET)

How to cite: Hench, J.; Vlajnic, T.; Soysal, S.D.; Obermann, E.C.; Frank, S.; Muenst, S. An Integrated Epigenomic and Genomic View on Phyllodes and Phyllodes-Like Breast Tumors. Preprints 2021, 2021120366. https://doi.org/10.20944/preprints202112.0366.v1 Hench, J.; Vlajnic, T.; Soysal, S.D.; Obermann, E.C.; Frank, S.; Muenst, S. An Integrated Epigenomic and Genomic View on Phyllodes and Phyllodes-Like Breast Tumors. Preprints 2021, 2021120366. https://doi.org/10.20944/preprints202112.0366.v1

Abstract

Fibroepithelial lesions (FL) of the breast, in particular Phyllodes tumors (PT) and fibroadenomas, pose a significant diagnostic challenge. There are no generally accepted criteria that distinguish benign, borderline, malignant PT, and FA. Combined genome-wide DNA methylation and copy number variant (CNV) profiling is an emerging strategy to classify tumors. We compiled a series of patient-derived archival biopsy specimens reflecting the FL spectrum and histological mimickers including clinical follow-up data. DNA methylation and CNVs were determined by well-established microarrays. Comparison of the patterns with a pan-cancer dataset assembled from public resources including "The Cancer Genome Atlas" (TCGA) and "Gene Expression Omnibus" (GEO) suggests that FLs form a methylation class distinct from both control breast tissue as well as common breast cancers. Complex CNVs were enriched in clinically aggressive FLs. Subsequent fluorescence in situ hybridization (FISH) analysis detected respective aberrations in the neoplastic mesenchymal component of FLs only, confirming that the epithelial component is non-neoplastic. Of note, our approach could lead to the elimination of the diagnostically problematic category of borderline PT and allow for optimized prognostic patient stratification. Furthermore, the identified recurrent genomic aberrations such as 1q gains (including MDM4), CDKN2a/b deletions and EGFR amplifications may inform therapeutic decision-making.

Keywords

fibroepithelial breast lesions; phyllodes tumors; methylation analysis; copy number alterations; dimension reduction; unsupervised machine learning

Subject

Medicine and Pharmacology, Pathology and Pathobiology

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