Diagnosis and Clinical Management of Neuroendocrine Tumor of the Breast: Report of Six Cases and Systematic Review of Existing Literature

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Alberto Bottini Alessandro De Luca Andrea Sagona Corrado Tinterri Emilia Marrazzo Erika Barbieri Federico Frusone Giulia Puliani Giuseppe Canavese Wolfgang Gatzemeier

Corresponding Author

Corrado Tinterri
Humanitas Research Hospital and Cancer Center, Breast Surgery Department, Milan, Rozzano, Italy

A B S T R A C T

Introduction: Neuroendocrine neoplasm of the breast (bNENs) are considered a rare disease, even if in WHO data they represent about 2-5 % of all breast cancer. The last WHO classification includes: welldifferentiated neuroendocrine tumor (bNET), neuroendocrine carcinoma (NEC) and invasive carcinoma with neuroendocrine differentiation. The current knowledge on clinical management of bNENs is poor and patients are usually treated according to non-endocrine tumor components guidelines. Materials and Methods: We presented our experience of six cases of bNENs. Moreover, we conducted a systematic review of published data on diagnosis, treatment and outcome of this kind of tumors. Results: bNENS usually presented as palpable breast masses, classically appearing as irregular hypoechoic lesions at US examination and as hyperdense masses at mammography. Usually pre-operative tumor biopsy is not able to recognize the neuroendocrine components and the final diagnosis is performed only on definitive histopathological assessment. The most frequent subtype seems to be neuroendocrine carcinoma and synaptophysin is positive in most specimens. Treatment strategies, including surgical treatment, radiotherapy and medical treatment are nowadays based on current non-endocrine breast cancer guidelines, independently from neuroendocrine components, even if some studies have proposed the use of somatostatin analogues for bNET and cisplatin-etoposide for NEC. Prognosis of all bNENs, especially of poorly differentiated neoplasia, seems worse compared to non-neuroendocrine breast cancer and stage and morphology seem the best predictor of tumor outcome. Conclusions: We provide an algorithm for clinical management of bNETs, basing on available data. More studies are necessary for confirming the best treatment strategy for these patients, in order to improve clinical outcome

Article Info

Article Type

Research Article

Publication history

Received: Wed 25, Dec 2019
Accepted: Thu 09, Jan 2020
Published: Tue 04, Feb 2020

Copyright

© 2023 Corrado Tinterri. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Hosting by Science Repository.
DOI: 10.31487/j.ACO.2020.01.02