Åke Borg
Principal investigator
Refinement of breast cancer molecular classification by miRNA expression profiles
Author
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.
Department/s
- 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
2019-06-17
Language
English
Publication/Series
BMC Genomics
Volume
20
Issue
1
Document type
Journal article
Publisher
BioMed Central (BMC)
Topic
- Cancer and Oncology
- Cell and Molecular Biology
Status
Published
Project
- 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
ISBN/ISSN/Other
- ISSN: 1471-2164