Refinement of breast cancer molecular classification by miRNA expression profiles
(2019) In BMC Genomics 20(1).- Abstract
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.... (More)
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.
(Less)
- author
- organization
-
- Cancer and non coding RNA (research group)
- BioCARE: Biomarkers in Cancer Medicine improving Health Care, Education and Innovation
- Personalized Breast Cancer Treatment (research group)
- Breastcancer-genetics
- Tumor Cell Biology (research group)
- Tumor microenvironment
- Translational Oncogenomics (research group)
- Familial Breast Cancer (research group)
- publishing date
- 2019-06-17
- type
- Contribution to journal
- publication status
- published
- subject
- in
- BMC Genomics
- volume
- 20
- issue
- 1
- article number
- 503
- pages
- 12 pages
- publisher
- BioMed Central (BMC)
- external identifiers
-
- pmid:31208318
- scopus:85067404705
- ISSN
- 1471-2164
- DOI
- 10.1186/s12864-019-5887-7
- project
- Sweden Cancerome Analysis Network - Breast (SCAN-B): a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine
- language
- English
- LU publication?
- yes
- id
- 4ac4a2d7-00dc-4f61-ba11-de7485b8028b
- date added to LUP
- 2019-06-19 13:17:28
- date last changed
- 2024-08-20 22:39:07
@article{4ac4a2d7-00dc-4f61-ba11-de7485b8028b, abstract = {{<p>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.</p><p>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.</p><p>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.</p>}}, author = {{Søkilde, Rolf and Persson, Helena and Ehinger, Anna and Pirona, Anna Chiara and Fernö, Mårten and Hegardt, Cecilia and Larsson, Christer and Loman, Niklas and Malmberg, Martin and Rydén, Lisa and Saal, Lao and Borg, Åke and Vallon-Christerson, Johan and Rovira, Carlos}}, issn = {{1471-2164}}, language = {{eng}}, month = {{06}}, number = {{1}}, publisher = {{BioMed Central (BMC)}}, series = {{BMC Genomics}}, title = {{Refinement of breast cancer molecular classification by miRNA expression profiles}}, url = {{http://dx.doi.org/10.1186/s12864-019-5887-7}}, doi = {{10.1186/s12864-019-5887-7}}, volume = {{20}}, year = {{2019}}, }