Aims Breast neuroendocrine tumours (NETs) constitute a rare histologic subtype of oestrogen receptor (ER)-positive breast cancer, and their definition according to the WHO classification was revised in 2019. Breast NETs display histologic and transcriptomic similarities with mucinous breast carcinomas (MuBCs). Here, we sought to compare the repertoire of genetic alterations in breast NETs with MuBCs and NETs from other anatomic origins.
Methods On histologic review applying the new WHO criteria, 18 breast tumours with neuroendocrine differentiation were reclassified as breast NETs (n=10) or other breast cancers with neuroendocrine differentiation (n=8). We reanalysed targeted sequencing or whole-exome sequencing data of breast NETs (n=10), MuBCs type A (n=12) and type B (n=11).
Results Breast NETs and MuBCs were found to be genetically similar, harbouring a lower frequency of PIK3CA mutations, 1q gains and 16q losses than ER-positive/HER2-negative breast cancers. 3/10 breast NETs harboured the hallmark features of ER-positive disease (ie, PIK3CA mutations and concurrent 1q gains/16q losses). Breast NETs showed an enrichment of oncogenic/likely oncogenic mutations affecting transcription factors compared with common forms of ER-positive breast cancer and with pancreatic and pulmonary NETs.
Conclusions Breast NETs are heterogeneous and are characterised by an enrichment of mutations in transcription factors and likely constitute a spectrum of entities histologically and genomically related to MuBCs. While most breast NETs are distinct from ER-positive/HER2-negative IDC-NSTs, a subset of breast NETs appears to be genetically similar to common forms of ER-positive breast cancer, suggesting that some breast cancers may acquire neuroendocrine differentiation later in tumour evolution.
- neuroendocrine tumours
Data availability statement
Data are available from the authors upon reasonable request.
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Handling editor Runjan Chetty.
Contributors BW and JSR-F conceived the study. FP, CM and JSR-F reviewed the cases. SSKL and ADCP performed the bioinformatic analysis. FP, MV, CM, SSKL, ADCP, FD, EMdS, PS, HD, SC, HYW, AV-S and EB analysed and interpreted the data. FP, MV and JSR-F wrote the first manuscript, which was reviewed by all coauthors.
Funding This study was funded by the Breast Cancer Research Foundation. Research reported in this publication was funded in part by a Cancer Center Support Grant of the National Institutes of Health/National Cancer Institute (grant No P30CA008748). FP is partially funded by a K12 CA184746 grant, BW by Cycle for Survival and Stand Up To Cancer grants.
Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Competing interests JSR-F reports receiving personal/consultancy fees from Goldman Sachs and REPARE Therapeutics, membership of the scientific advisory boards of VolitionRx and Page.AI, and ad hoc membership of the scientific advisory boards of Roche Tissue Diagnostics, Ventana Medical Systems, Novartis, Genentech and InVicro, outside the scope of this study. All other authors declare no conflicts of interest. CM has received personal/consultancy fees from Roche, Bayer, Daiichi Sankyo, MSD, Thesaro, COR2ED, outside of the scope of the present work. SC has received research support from Daichi Sankyo and consulting fees from Novartis, Sermonix, BMS, Context Therapeutics, Revolution Medicine, Paige AI and Eli Lilly.
Provenance and peer review Not commissioned; externally peer reviewed.
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