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

doi:10.1186/s12864-019-5887-7

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

Research output: Contribution to journal › Article › peer-review

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. 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.

Original language	English
Article number	503
Number of pages	12
Journal	BMC Genomics
Volume	20
Issue number	1
DOIs	https://doi.org/10.1186/s12864-019-5887-7
Publication status	Published - 2019 Jun 17

Subject classification (UKÄ)

Cancer and Oncology
Cell and Molecular Biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1186/s12864-019-5887-7

Sweden Cancerome Analysis Network - Breast (SCAN-B): a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine
Borg, Å. (PI), Ehinger, A. (PI), Hegardt, C. (PI), Larsson, C. (PI), Loman, N. (PI), Malmberg, M. (PI), Ryden, L. (PI) & Saal, L. (PI)
Mrs. Berta Kamprad's Cancer Foundation
2009/06/01 → …
Project: Network

Sweden Cancerome Analysis Network – Breast (SCAN-B)
Ehinger, A. (Contributor)
2010 → …
Activity: Consultancy, expert advice and memberships › Member of board/committee/council etc

Cite this

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title = "Refinement of breast cancer molecular classification by miRNA expression profiles",

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. 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.",

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doi = "10.1186/s12864-019-5887-7",

language = "English",

volume = "20",

journal = "BMC Genomics",

issn = "1471-2164",

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T1 - Refinement of breast cancer molecular classification by miRNA expression profiles

AU - Søkilde, Rolf

AU - Persson, Helena

AU - Ehinger, Anna

AU - Pirona, Anna Chiara

AU - Fernö, Mårten

AU - Hegardt, Cecilia

AU - Larsson, Christer

AU - Loman, Niklas

AU - Malmberg, Martin

AU - Rydén, Lisa

AU - Saal, Lao

AU - Borg, Åke

AU - Vallon-Christerson, Johan

AU - Rovira, Carlos

PY - 2019/6/17

Y1 - 2019/6/17

N2 - 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.

AB - 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.

U2 - 10.1186/s12864-019-5887-7

DO - 10.1186/s12864-019-5887-7

M3 - Article

C2 - 31208318

SN - 1471-2164

VL - 20

JO - BMC Genomics

JF - BMC Genomics

IS - 1

M1 - 503

ER -

Refinement of breast cancer molecular classification by miRNA expression profiles

Abstract

Subject classification (UKÄ)

UN SDGs

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Fingerprint

Projects

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

Activities

Sweden Cancerome Analysis Network – Breast (SCAN-B)

Cite this