Metastatic and recurrent, malignant breast phyllodes tumors harbor aberrations in genes frequently altered in other advanced neoplasms
Bruzas S.1, Breit E.1, Theuerkauf I.2, Harrach H.1, Kümmel S.1, Chiari O.1, Schindowski D.1, Moka D.3, Reinisch M.1
1Evang. Kliniken Essen-Mitte, Senologie, Essen, Deutschland, 2Institut für Pathologie Viersen, Viersen, Deutschland, 3Nuclear Medicine Centre, Essen, Deutschland
Purpose: Phyllodes tumors (PTs) of the breast are fibroepithelial neoplasms and represent up to 0.5% of all breast tumors. Due to the rarity of the disease, the pathogenesis and genetic drivers of PTs are poorly understood. We therefore conducted next-generation sequencing (NGS), followed by functional analysis of indicated aberrations, for tumor samples of two patients with malignant PTs (MPTs).
Patients and methods: Formalin-fixed, paraffin-embedded specimens of the primary tumor and pulmonary metastases of Patient 1, and the primary, and recurrent tumor of Patient 2 were subjected to NGS with the FoundationOne® assay for exons of 315 genes and introns of 28 genes frequently associated with various cancer types. The FATHMM-XF score and MutationTaster2 were used for prediction of functional consequences of identified genetic aberrations.
Results: A total of 38 genomic alterations were identified, and 11 were predicted to be probably benign. In Patient 1, 13 and 16 sequence variants were detected in the primary and distant lesions, respectively, with 11 overlapping findings. In patient 2, 17 and 15 sequence variants were found in the primary and recurrent tumor, respectively, 13 of which were identical. Affected genes included seven out of the top 10 genes frequently altered in other advanced cancer entities (TP53, TERT, APC, ARID1A, EGFR, KMT2D, and RB1), seven receptor tyrosine kinases, and four druggable targets.
Conclusion: Evaluation of data generated by NGS provided new insights into the molecular pathogenesis of recurrent and metastatic MPTs and suggests potential therapeutic options. Functional analysis can identify potentially disease-causing alterations.