Refinement of breast cancer molecular classification by miRNA expression profiles

Research output: Contribution to journalArticle


BACKGROUND: Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction.

RESULTS: We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day's signatures.

CONCLUSIONS: We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.


External organisations
  • Skåne University Hospital
  • German Cancer Research Centre
  • Lund University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Cancer and Oncology
  • Cell and Molecular Biology
Original languageEnglish
Article number503
Number of pages12
JournalBMC Genomics
Issue number1
Publication statusPublished - 2019 Jun 17
Publication categoryResearch