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MicroRNAs Discriminate Familial from Sporadic Non-BRCA1/2 Breast Carcinoma Arising in Patients ≤35 Years

The influence of genetic factors may contribute to the poor prognosis of breast cancer (BC) at a very young age. However BRCA1/2 mutations could not explain the majority of cases arising in these patients. MicroRNAs (miRs) have been implicated in biological processes associated with BC. Therefore, w...

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Detalles Bibliográficos
Autores principales: Bastos, Elen Pereira, Brentani, Helena, Pasini, Fatima Solange, Silva, Aderbal Ruy T., Torres, Cesar Henrique, Puga, Renato David, Olivieri, Eloisa Helena Ribeiro, Piovezani, Amanda Rusiska, Pereira, Carlos Alberto de Bragança, Machado-Lima, Ariane, Carraro, Dirce Maria, Brentani, Maria Mitzi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4090167/
https://www.ncbi.nlm.nih.gov/pubmed/25006670
http://dx.doi.org/10.1371/journal.pone.0101656
Descripción
Sumario:The influence of genetic factors may contribute to the poor prognosis of breast cancer (BC) at a very young age. However BRCA1/2 mutations could not explain the majority of cases arising in these patients. MicroRNAs (miRs) have been implicated in biological processes associated with BC. Therefore, we investigated differences in miRs expression between tumors from young patients (≤35 years) with sporadic or familial history and non-carriers of BRCA1/2 mutations. Thirty-six young Brazilian patients were divided into 2 groups: sporadic (NF-BC) or familial breast cancer (F-BC). Most of the samples were classified as luminal A and B and the frequency of subtypes did not differ between familial or sporadic cases. Using real time qPCR and discriminant function analysis, we identified 9 miRs whose expression levels rather than miR identity can discriminate between both patient groups. Candidate predicted targets were determined by combining results from miRWalk algorithms with mRNA expression profiles (n = 91 differently expressed genes). MiR/mRNA integrated analysis identified 91 candidate genes showing positive or negative correlation to at least 1 of the 9 miRs. Co-expression analysis of these genes with 9 miRs indicated that 49 differentially co-expressed miR-gene interactions changes in F-BC tumors as compared to those of NF-BC tumors. Out of 49, 17 (34.6%) of predicted miR-gene interactions showed an inverse correlation suggesting that miRs act as post-transcriptional regulators, whereas 14 (28.6%) miR-gene pairs tended to be co-expressed in the same direction indicating that the effects exerted by these miRs pointed to a complex level of target regulation. The remaining 18 pairs were not predicted by our criteria suggesting involvement of other regulators. MiR–mRNA co-expression analysis allowed us to identify changes in the miR-mRNA regulation that were able to distinguish tumors from familial and sporadic young BC patients non-carriers of BRCA mutations.