Meta-microRNA Biomarker Signatures to Classify Breast Cancer Subtypes.

Breast cancer is one of the leading causes of morbidity and mortality that is in need of novel diagnostics and therapeutics. Meta-analysis of microarray data offers promise to combine studies and provide more robust results. We report here a molecular classification of pathological subtypes (estrogen receptor [ER], progesterone receptor [PR], and Human Epidermal Growth Factor Receptor 2 [HER2]) of breast cancers with microRNA (miRNA)-dependent signatures. A ranking-based meta-analysis approach was applied to eight independent microarray data sets and meta-miRNA lists were obtained that are specific to each breast cancer subtype. The comparison of the lists with miRCancer and the PhenomiR 2.0 databases pointed out nine prominent miRNAs: let-7b-5p, let-7c-5p, let-7e-5p, miR-130a-3p, miR-30a-5p, miR-92a-1-5p, miR-211-5p, miR-500a-3p, and miR-516b-3p. Further analysis conducted with the TCGA data showed that these miRNAs can differentiate tumors from normal samples as well as discriminate the molecular subtypes of breast cancer. According to the PAM50 classification, three of these miRNAs (let-7b-5p, let-7c-5p, and miR-30a-5p) downregulated significantly, whereas miR-130a-3p, miR-92a-1-5p, miR-211-5p, and miR-500a-3p upregulated in tumors from the luminal A to the basal-like subtypes. When the prominent meta-miRNAs and their targets were analyzed, they appeared to be taking part in important signaling pathways in cancer such as the PI3K-Akt signaling and the p53 signaling pathways. Furthermore, the regulatory genes, which are key players for ER, PR, and ErBb signaling pathways, were found to be under control of several meta-miRNAs. These meta-miRNAs and the genes they are regulating offer new promise for future translational research and potential targets for precision medicine diagnostics.

DICER1 gene and miRNA dysregulation in mesenchymal stem cells of patients with myelodysplastic syndrome and acute myeloblastic leukemia.

Multipotent mesenchymal stem cells (MSC) are key components of the bone marrow (BM) microenvironment. The contribution of this microenvironment to the pathophysiology of myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) is not well defined. A recent study in mice demonstrated that DICER1 gene deletion in osteoprogenitor cells from the BM microenvironment suppressed osteogenic differentiation and induced MDS and AML-like haematological findings. The present study evaluated the expression profiles of microRNAs (miRNAs) and DICER1 gene in BM-derived MSC of patients with AML (n=12), MDS (n=10) and healthy controls (HC) (n=8).miRNA expression profiles were analyzed by microarray and confirmations were performed using quantitative real-time PCR (qRT-PCR). Patient MSC displayed impaired proliferative and differentiation potential compared to HC. DICER1 gene expression was lower in MSC from MDS and AML patients than HC and some differentially expressed miRNAs indicated the potential involvement of DICER1 in the pathogenesis of MDS and AML. qRT-PCR confirmation revealed down-regulated miRNAs (hsa-miR-30d-5p, hsa-miR-222-3p and hsa-miR-30a-3p in MDS; hsa-miR-1275, hsa-miR-4725-5p and hsa-miR-143-3p in AML) and over-expressed miRNAs (hsa-miR-4462 in MDS; hsa-miR-134-5p and hsa-miR-874-3p in AML) in MDS and AML. Thus, our findings validate the results of the aforementioned animal study and demonstrate downregulation of DICER1 gene and abnormal miRNA profile in MDS and AML, which may have implications for understanding MDS and AML pathogenesis and contribute to developing targeted treatment strategies.

Identification of Polycystic Ovary Syndrome (PCOS) Specific Genes in Cumulus and Mural Granulosa Cells.

Polycystic ovary syndrome (PCOS) is a metabolic and endocrine disorder which affects women of reproductive age with prevalence of 8-18%. The oocyte within the follicle is surrounded by cumulus cells (CCs), which connect with mural granulosa cells (MGCs) that are responsible for secreting steroid hormones. The main aim of this study is comparing gene expression profiles of MGCs and CCs in PCOS and control samples to identify PCOS-specific differentially expressed genes (DEGs). In this study, two microarray databases were searched for mRNA expression microarray studies performed with CCs and MGCs obtained from PCOS patients and control samples. Three independent studies were selected to be integrated with naive meta-analysis since raw meta-data from these studies were found to be highly correlated. DEGs in these somatic cells were identified for PCOS and control groups. This study enabled us to reveal dysregulation in MAPK (mitogen activated protein kinase), insulin and Wnt signaling pathways between CCs and MGCs in PCOS. The meta-analysis results together with qRT-PCR validations provide evidence that molecular signaling is dysregulated through MGCs and CCs in PCOS, which is important for follicle and oocyte maturation and may contribute to the pathogenesis of the syndrome.

A ranking-based meta-analysis reveals let-7 family as a meta-signature for grade classification in breast cancer.

Breast cancer is one of the most important causes of cancer-related deaths worldwide in women. In addition to gene expression studies, the progressing work in the miRNA area including miRNA microarray studies, brings new aspects to the research on the cancer development and progression. Microarray technology has been widely used to find new biomarkers in research and many transcriptomic microarray studies are available in public databases. In this study, the breast cancer miRNA and mRNA microarray studies were collected according to the availability of their data and clinical information, and combined by a newly developed ranking-based meta-analysis approach to find out candidate miRNA biomarkers (meta-miRNAs) that classify breast cancers according to their grades and explain the relation between miRNAs and mRNAs. This approach provided meta-miRNAs specific to breast cancer grades, pointing out let-7 family members as grade classifiers. The qRT-PCR studies performed with independent breast tumors confirmed the potential biomarker role of let-7 family members (meta-miRNAs). The concordance between the meta-mRNAs and miRNA target genes specific to tumor grade (common genes) supported the idea of mRNAs as miRNA targets. The pathway analysis results showed that most of the let-7 family miRNA targets, and also common genes, were significantly taking part in cancer-related pathways. The qRT-PCR studies, together with bioinformatic analyses, confirmed the results of meta-analysis approach, which is dynamic and allows combining datasets from different platforms.