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.

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.

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).

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.