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Åke Borg

Åke Borg

Principal investigator

Åke Borg

Refinement of breast cancer molecular classification by miRNA expression profiles


  • Rolf Søkilde
  • Helena Persson
  • Anna Ehinger
  • Anna Chiara Pirona
  • Mårten Fernö
  • Cecilia Hegardt
  • Christer Larsson
  • Niklas Loman
  • Martin Malmberg
  • Lisa Rydén
  • Lao Saal
  • Åke Borg
  • Johan Vallon-Christerson
  • Carlos Rovira

Summary, in English

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.


  • Cancer and non coding RNA
  • BioCARE: Biomarkers in Cancer Medicine improving Health Care, Education and Innovation
  • Personalized Breast Cancer Treatment
  • Breastcancer-genetics
  • Tumor Cell Biology
  • Tumor microenvironment
  • Translational Oncogenomics
  • Familial Breast Cancer

Publishing year





BMC Genomics





Document type

Journal article


BioMed Central (BMC)


  • Cancer and Oncology
  • Cell and Molecular Biology




  • Sweden Cancerome Analysis Network - Breast (SCAN-B): a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine

Research group

  • Cancer and non coding RNA
  • Personalized Breast Cancer Treatment
  • Tumor Cell Biology
  • Translational Oncogenomics
  • Familial Breast Cancer


  • ISSN: 1471-2164