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Updated: Dec 5, 2025

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Bilateral Phyllodes Giant Tumor. A Case Report Analyzed by Array-CGH
Francesco Fortarezza1, Federica Pezzuto1, Gerardo Cazzato2
1Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Pathology Unit, University of Padova, 35121 Padova, Italy.
Abstract:
The breast phyllodes tumor is a biphasic tumor that accounts for less than of 1% of all breast neoplasms. It is classified as benign, borderline, or malignant, and can mimic benign masses. Some recurrent alterations have been identified. However, a precise molecular classification of these tumors has not yet been established. Herein, we describe a case of a 43-year-old woman that was admitted to the emergency room for a significant bleeding from the breast skin. A voluminous ulcerative mass of the left breast and multiple nodules with micro-calcifications on the right side were detected at a physical examination. A left total mastectomy and a nodulectomy of the right breast was performed. The histological diagnosis of the surgical specimens reported a bilateral giant phyllodes tumor, showing malignant features on the left and borderline characteristics associated with a fibroadenoma on the right. A further molecular analysis was carried out by an array-Comparative Genomic Hybridization (CGH) to characterize copy-number alterations. Many losses were detected in the malignant mass, involving several tumor suppressor genes. These findings could explain the malignant growth and the metastatic risk. In our study, genomic profiling by an array-CGH revealed a greater chromosomal instability in the borderline mass (40 total defects) than in the malignant (19 total defects) giant phyllodes tumor, reflecting the tumor heterogeneity. Should our results be confirmed with more sensitive and specific molecular tests (DNA sequencing and FISH analysis), they could allow a better selection of patients with adverse pathological features, thus optimizing and improving patient's management.
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