Relative levels of let-7a, miR-17, miR-27b, miR-125a, miR-125b and miR-206 as potential molecular markers to evaluate grade, receptor status and molecular type in breast cancer.

MicroRNAs (miRNAs/miRs) are a class of short, single‑stranded nucleic acids, which have been investigated as potential molecular markers for various types of cancer. The gold‑standard and most sensitive method for comparing miRNA levels in cancer tissues is reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR). This technique uses stably expressed genes for normalisation. The aim of the present study was to improve this model of analysis in the context of RT‑qPCR results. A total of six known miRNAs (let‑7a, miR‑17, miR‑27b, miR‑125a, miR‑125b and miR‑206), RNU6B RNA and five mRNAs [erb‑b2 receptor tyrosine kinase 2 (ERBB2), hydroxymethylbilane synthase and polymerase (RNA) II (DNA directed) polypeptide A] were analysed pair‑wise, in order to determine which biomarker pairs best correlated with the histological groups of 27 breast cancer samples. The lowest P‑values and the highest area under the curve values in the receiver operating characteristic analysis were used to select the optimum ratios for discrimination among groups. Among the 21 pairs, miR‑17/miR‑27b and miR‑125a/RNU6B best discriminated three groups of samples with different tumour grades (G classification). miR‑125b/miR‑206 best discriminated two groups of samples with different tumour sizes (pT), let‑7a/RNU6B best discriminated two groups of samples with different lymph node status (pN), and let‑7a/miR‑125b best discriminated groups of samples with negative and positive oestrogen and progesterone receptor status. No pair of miRNAs was found to discriminate well between groups with either a negative or positive human epidermal growth factor receptor 2 (HER2) status. However, one miRNA/mRNA pair, miR‑125a/ERBB2, discriminated HER2‑negative from HER2‑positive groups. The breast cancer samples investigated in the present study were grouped by immunohistological methods into three molecular classes: Luminal, HER2 positive and basal (L, H and B, respectively). In order to discern L from H and L from B, two miRNA pairs were selected: miR‑125a/miR‑125b and miR‑125a/miR‑206. In conclusion, the pair‑wise method of RT‑qPCR data analysis may be a reasonable alternative to the standard method of using stably expressed reference genes, such as RNU6B RNA, for normalisation. This method may increase the classification power of miRNA biomarkers in breast cancer diagnostics.