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Original research
Neuroendocrine tumours of the breast: a genomic comparison with mucinous breast cancers and neuroendocrine tumours of other anatomic sites
  1. Fresia Pareja1,
  2. Mahsa Vahdatinia1,
  3. Caterina Marchio2,3,
  4. Simon S K Lee1,
  5. Arnaud Da Cruz Paula4,
  6. Fatemeh Derakhshan1,
  7. Edaise M da Silva1,
  8. Pier Selenica1,
  9. Higinio Dopeso1,
  10. Sarat Chandarlapaty5,
  11. Hannah Y Wen1,
  12. Anne Vincent-Salomon6,
  13. Edi Brogi1,
  14. Britta Weigelt1,
  15. Jorge S Reis-Filho1
  1. 1Department of Pathology, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
  2. 2Department of Medical Sciences, University of Turin, Turin, Italy
  3. 3Unit of Pathology, Candiolo Cancer Institute, FPO IRCCS, Candiolo, Italy
  4. 4Department of Surgery, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
  5. 5Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
  6. 6Department de Medicine Diagnostique et Theranostique, Institut Curie, Paris, France
  1. Correspondence to Dr Fresia Pareja, Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; parejaf{at}mskcc.org; Dr Jorge S Reis-Filho, Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; reisfilj{at}mskcc.org

Abstract

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
  • pathology
  • molecular
  • breast

https://doi.org/10.1136/jclinpath-2020-207052

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    Footnotes

    • 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.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data are available from the authors upon reasonable request.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.