Combined MicroRNA and ER Expression: a New Classifier for Familial and Sporadic Breast Cancer Patients

Overview

Journal J Transl Med

Publisher Biomed Central

Specialties Biomedical Engineering
General Medicine

Date 2014 Nov 20

PMID 25406994

Citations 5

Authors

Katia Danza

Simona De Summa

Brunella Pilato

Massimo Carella

Orazio Palumbo

Ondina Popescu

Angelo Paradiso

Rosamaria Pinto

Stefania Tommasi

Affiliations

Soon will be listed here.

Abstract

Background: The role of miRNAs in familial breast cancer (fBC) is poorly investigated as also in the BRCA-like tumors. To identify a specific miRNA expression pattern which could allow a better fBC classification not only based on clinico-pathological and immunophenotypical parameters we analyzed miRNA profile in familial and sporadic samples. Moreover since BRCA1 tumors and sporadic triple negative (TN) breast tumors share similarities regarding clinical outcomes and some histological characteristics, we focused on TN and not TN cases.

Methods: The sample set included fresh frozen tissue samples, including 39 female fBCs (19 BRCA-related and 20 BRCAX) and 12 male fBC (BRCAX). Moreover, we considered TN and non TN (NTN), 21 BRCA-related and 27 sporadic BCs. MiRNA profiling was performed through GeneChip miRNA v.1.0 Array (Affymetrix). ANOVA, hierarchical and consensus clustering analyses allowed identification of pattern of expression of miRNAs and pathway enrichment analysis, considering validated target genes, was carried out to achieve a deeper biological understanding.

Results: ANOVA test led to the identification of 53 deregulated miRNAs; hierarchical and consensus clustering of female fBCs (fFBCs) and male fBCs (fMBCs) highlighted the presence of 3 sample clusters named FBC1, FBC2 and FBC3. We found a correlation between ER-status and the three sample clusters. The three clusters are distinct by a different expression of two clusters of miRNAs (CLU1 and CLU2), which resulted to be different in targeted pathways. In particular, CLU1 targets cellular pathways and CLU2 is involved in epigenetic activities. Considering TN and NTN BRCA-related and sporadic tumors, a hierarchical clustering identified two clusters of miRNAs, which were not so different from CLU1 and CLU2, both in miRNA content and targeted pathways.

Conclusions: Our results highlighted the importance of miRNA regulation to better clarify similarities and differences between familial and sporadic BC groups.

Citing Articles

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Identifying a miRNA signature for predicting the stage of breast cancer.

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Merino M, Gil S, Macias C, Lara K J Cancer. 2018; 9(3):450-459.

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TGFbeta and miRNA regulation in familial and sporadic breast cancer.

Danza K, De Summa S, Pinto R, Pilato B, Palumbo O, Carella M Oncotarget. 2017; 8(31):50715-50723.

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Grolmusz V, Borka K, Kovesdi A, Nemeth K, Balogh K, Dekany C Virchows Arch. 2017; 471(3):401-411.

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References

Zhou J, Teng R, Wang Q, Xu C, Guo J, Yuan C . Endocrine resistance in breast cancer: Current status and a perspective on the roles of miRNAs (Review). Oncol Lett. 2013; 6(2):295-305. PMC: 3789028. DOI: 10.3892/ol.2013.1405. View

Lehmann B, Bauer J, Chen X, Sanders M, Chakravarthy A, Shyr Y . Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest. 2011; 121(7):2750-67. PMC: 3127435. DOI: 10.1172/JCI45014. View

Melchor L, Benitez J . The complex genetic landscape of familial breast cancer. Hum Genet. 2013; 132(8):845-63. DOI: 10.1007/s00439-013-1299-y. View

Garcia-Becerra R, Santos N, Diaz L, Camacho J . Mechanisms of resistance to endocrine therapy in breast cancer: focus on signaling pathways, miRNAs and genetically based resistance. Int J Mol Sci. 2013; 14(1):108-45. PMC: 3565254. DOI: 10.3390/ijms14010108. View

DIppolito E, Iorio M . MicroRNAs and triple negative breast cancer. Int J Mol Sci. 2013; 14(11):22202-20. PMC: 3856060. DOI: 10.3390/ijms141122202. View

Lowery A, Miller N, Devaney A, McNeill R, Davoren P, Lemetre C . MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer. Breast Cancer Res. 2009; 11(3):R27. PMC: 2716495. DOI: 10.1186/bcr2257. View

Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T . miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res. 2008; 37(Database issue):D105-10. PMC: 2686554. DOI: 10.1093/nar/gkn851. View

Esteller M . Epigenetic changes in cancer. F1000 Biol Rep. 2011; 3:9. PMC: 3100810. DOI: 10.3410/B3-9. View

Zhou W, Slingerland J . Links between oestrogen receptor activation and proteolysis: relevance to hormone-regulated cancer therapy. Nat Rev Cancer. 2014; 14(1):26-38. DOI: 10.1038/nrc3622. View

10.

Hsu S, Tseng Y, Shrestha S, Lin Y, Khaleel A, Chou C . miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res. 2013; 42(Database issue):D78-85. PMC: 3965058. DOI: 10.1093/nar/gkt1266. View

11.

Cascione L, Gasparini P, Lovat F, Carasi S, Pulvirenti A, Ferro A . Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer. PLoS One. 2013; 8(2):e55910. PMC: 3566108. DOI: 10.1371/journal.pone.0055910. View

12.

Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov J . GenePattern 2.0. Nat Genet. 2006; 38(5):500-1. DOI: 10.1038/ng0506-500. View

13.

Turner N, Reis-Filho J . Basal-like breast cancer and the BRCA1 phenotype. Oncogene. 2006; 25(43):5846-53. DOI: 10.1038/sj.onc.1209876. View

14.

Muggia F, Safra T . 'BRCAness' and its implications for platinum action in gynecologic cancer. Anticancer Res. 2014; 34(2):551-6. PMC: 4682661. View

15.

Esteller M . Cancer Epigenetics for the 21st Century: What's Next?. Genes Cancer. 2011; 2(6):604-6. PMC: 3174266. DOI: 10.1177/1947601911423096. View

16.

Cho E, Chang M, La Choi Y, Lee J, Nam S, Yang J . Potential candidate biomarkers for heterogeneity in triple-negative breast cancer (TNBC). Cancer Chemother Pharmacol. 2010; 68(3):753-61. DOI: 10.1007/s00280-010-1548-x. View

17.

Fu S, Chen L, Man Y . miRNA Biomarkers in Breast Cancer Detection and Management. J Cancer. 2011; 2:116-22. PMC: 3072617. DOI: 10.7150/jca.2.116. View

18.

Saeed A, Sharov V, White J, Li J, Liang W, Bhagabati N . TM4: a free, open-source system for microarray data management and analysis. Biotechniques. 2003; 34(2):374-8. DOI: 10.2144/03342mt01. View

19.

Pinto R, Pilato B, Ottini L, Lambo R, Simone G, Angelo Paradiso . Different methylation and microRNA expression pattern in male and female familial breast cancer. J Cell Physiol. 2012; 228(6):1264-9. DOI: 10.1002/jcp.24281. View

20.

Murria Estal R, Palanca Suela S, de Juan Jimenez I, Egoavil Rojas C, Garcia-Casado Z, Juan Fita M . MicroRNA signatures in hereditary breast cancer. Breast Cancer Res Treat. 2013; 142(1):19-30. DOI: 10.1007/s10549-013-2723-7. View