Both of which were correlated with age. However, a recent gene expression profiling meta-analysis proposed that BC at young age appears to be biologically distinct beyond subtype distribution. We recently reported a study of 54 young Brazilian patients. Of these, 29% presented a familial cancer history and specifically, 37.5% were carriers of germ line mutation in the BRCA1/2 genes, which was displayed by only 8.6% of the tumors from non-familial BC cases. In addition, gene expression profiling appropriately discriminated tumors according to the presence/ absence of BRCA1/2 germ line mutations. However, gene expression profile differences between familial and sporadic early onset BC patients who were not carriers of BRCA1/2 mutations were not found. An additional improvement of gene signatures could be found from the examination of microRNAs, which have recently emerged as important players in BC development, progression, and metastasis. MiRs are a class of small non-coding RNAs that post transcriptionally regulate the expression of protein-coding genes opening a new area of marker research complementary to the transcriptional gene signature. Differentially expressed miRs were identified according to different BC molecular subtypes, metastasis, and overall survival. However, little is still known about the involvement of miRs in the molecular mechanisms underlying the aggressiveness of BC in young women. An association between miR-146a phenotype and tumor age-of-onset in BRCA1/2-negative familial BC cases has been reported. In addition, a recent study highlighted that non-BRCA1/2 hereditary BC may be sub-classified using specific miR signatures. Recently, Estal and coworkers suggested that the miR expression profile may facilitate the identification of sporadic BC carrying genetic/epigenetic changes in BRCA genes. Our specific aims in the current study were to identify a miR expression signature that could discriminate between familial and sporadic BC in young patients who are noncarriers of BRCA1/2 mutations; and to identify candidate target-genes related with the differentially expressed miRs. In other words, if a given miR was upregulated, the expression of its target is expected to be downregulated and vice-versa. From the 31 predicted miR– mRNA interactions, 17 pairs presented inverse fold-change values between F-BC and NF-BC. These MDV3100 915087-33-1 results suggested that 17 predicted miR–mRNA interactions could be supported by the potential miRs post-transcription regulator function. Analysis of those miR–mRNA interactions defined a network of 16 genes and 7 miRs whose co-expression is different in F-BC and NF-BC. Comparing both network profiles, F-BC against NF-BC, we observed different colors of edges representing negative or positive co-expression correlation as well as the different thickness of the edges, where thicker edges indicate high values of co-expression correlation, and thinner edges represent low values of co-expression correlation. We can also visualize that genes from the NF-BC group exhibited downregulation and 5 genes.