Relationship of immunohistochemistry, copy number aberrations and epigenetic disorders with BRCAness pattern in hereditary and sporadic breast cancer.

The study aims to identify the relevance of immunohistochemistry (IHC), copy number aberrations (CNA) and epigenetic disorders in BRCAness breast cancers (BCs). We studied 95 paraffin included BCs, of which 41 carried BRCA1/BRCA2 germline mutations and 54 were non hereditary (BRCAX/Sporadic). Samples were assessed for BRCA1ness and CNAs by Multiplex Ligation-dependent Probe Amplification (MLPA); promoter methylation (PM) was assessed by methylation-specific-MLPA and the expression of miR-4417, miR-423-3p, miR-590-5p and miR-187-3p by quantitative RT-PCR. IHC markers Ki67, ER, PR, HER2, CK5/6, EGFR and CK18 were detected with specific primary antibodies (DAKO, Denmark). BRCAness association with covariates was performed using multivariate binary logistic regression (stepwise backwards Wald option). BRCA1/2 mutational status (p = 0.027), large tumor size (p = 0.041) and advanced histological grade (p = 0.017) among clinic-pathological variables; ER (p < 0.001) among IHC markers; MYC (p < 0.001) among CNA; APC (p = 0.065), ATM (p = 0.014) and RASSF1 (p = 0.044) among PM; and miR-590-5p (p = 0.001), miR-4417 (p = 0.019) and miR-423 (p = 0.013) among microRNA expression, were the selected parameters significantly related with the BRCAness status. The logistic regression performed with all these parameters selected ER+ as linked with the lack of BRCAness (p = 0.001) and MYC CNA, APC PM and miR-590-5p expression with BRCAness (p = 0.014, 0.045 and 0.007, respectively). In conclusion, the parameters ER expression, APC PM, MYC CNA and miR-590-5p expression, allowed detection of most BRCAness BCs. The identification of BRCAness can help establish a personalized medicine addressed to predict the response to specific treatments.

MicroRNA signatures in hereditary breast cancer.

This study aims to identify signatures of miR associated with hereditary, BRCA1 or BRCA2 mutation positive breast cancer (BC), and non-hereditary BC, either sporadic (SBC) or non-informative (BRCAX). Moreover, we search for signatures associated with tumor stage, immunohistochemistry and tumor molecular profile. Twenty formalin fixed paraffin embedded (FFPE) BCs, BRCA1, BRCA2, BRCAX and SBC, five per group were studied. Affymetrix platform miRNA v.3.0 was used to perform miR expression analysis. ER, PR, HER2 and Ki67 protein expression was analyzed by immunohistochemistry. BRCA1, BRCA2 and RASSF1 methylation analysis, AURKA copy number variations, and BRCA1 and BRCA2 deletions, were studied by MLPA. We validated eight of the miR selected by the arrays in 77 BCs by qRT-PCR. The miR profiles associated with tumor features were studied applying the Sparse Partial Least Squares Discriminant Analysis. MiR discrimination capability to distinguish hereditary and non-hereditary BC was analyzed by the discriminant function. With 15 out of 1,733 hsa-miRs, it was possible to differentiate the four groups. BRCA1, BRCA2 and SBC were associated with clusters of hyper-expressed miRs, and BRCAX with hypo-expressed miRs. Hsa-miR-4417 and hsa-miR-423-3p expressions (included among the eight validated miRs) differentiated 70.1 % of hereditary and non-hereditary BCs. We found miR profiles associated with tumor features like node involvement, histological grade, ER, PR and HER2 expression. Regarding molecular parameters, we only found a weak association of miRs in BC harboring losses in AURKA. We conclude that array miR expression profiles can differentiate the four study groups using FFPE BC. However, miRs expression estimated by qRT-PCR differentiates only hereditary and non-inherited BCs. The miR expression array is a simple and rapid approach that could be useful to facilitate the identification of those SBC carrying genetic or epigenetic changes in BRCA genes responsible of BRCA-like phenotype. These patients could benefit from the treatment with PARP inhibitors.