The transcription factor Sox1 is the earliest and most specific known marker for mammalian neural progenitors. During fetal development, Sox1 is expressed by proliferating progenitor cells throughout the central nervous system and in no tissue but the lens. We generated a reporter mouse line in which egfp is inserted into the Sox1 locus. Sox1 ^GFP animals faithfully recapitulate the expression of the endogenous gene. We have used the GFP reporter to purify neuroepithelial cells by fluorescence-activated cell sorting from embryonic day 10.5 embryos. RNAs prepared from Sox1 ^GFP+ and Sox1 ^GFP- embryo cells were then used to perform a pilot screen of subtracted cDNAs prepared from differentiating embryonic stem cells and arrayed on a glass chip. Fifteen unique differentially expressed genes were identified, all previously associated with fetal or adult neural tissue. Whole mount in situ hybridization against two genes of previously unknown embryonic expression, Lrrn1 and Musashi2 , confirmed the selectivity of this screen for early neuroectodermal markers.

Real-time quantitative polymerase-chain-reaction (qPCR) is a standard technique in most laboratories used for various applications in basic research. Analysis of qPCR data is a crucial part of the entire experiment, which has led to the development of a plethora of methods. The released tools either cover specific parts of the workflow or provide complete analysis solutions. Here, we surveyed 27 open-access software packages and tools for the analysis of qPCR data. The survey includes 8 Microsoft Windows, 5 web-based, 9 R-based and 5 tools from other platforms. Reviewed packages and tools support the analysis of different qPCR applications, such as RNA quantification, DNA methylation, genotyping, identification of copy number variations, and digital PCR. We report an overview of the functionality, features and specific requirements of the individual software tools, such as data exchange formats, availability of a graphical user interface, included procedures for graphical data presentation, and offered statistical methods. In addition, we provide an overview about quantification strategies, and report various applications of qPCR. Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

The epithelial to mesenchymal transition (EMT) represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer stemness. Notably, EMT has been increasingly recognized as an early event of metastasis. Numerous gene expression studies (GES) have been conducted to obtain transcriptome signatures and marker genes to understand the regulatory mechanisms underlying EMT. Yet, no meta-analysis considering the multitude of GES of EMT has been performed to comprehensively elaborate the core genes in this process. Here we report the meta-analysis of 18 independent and published GES of EMT which focused on different cell types and treatment modalities. Computational analysis revealed clustering of GES according to the type of treatment rather than to cell type. GES of EMT induced via transforming growth factor-β and tumor necrosis factor-α treatment yielded uniformly defined clusters while GES of models with alternative EMT induction clustered in a more complex fashion. In addition, we identified those up- and downregulated genes which were shared between the multitude of GES. This core gene list includes well known EMT markers as well as novel genes so far not described in this process. Furthermore, several genes of the EMT-core gene list significantly correlated with impaired pathological complete response in breast cancer patients. In conclusion, this meta-analysis provides a comprehensive survey of available EMT expression signatures and shows fundamental insights into the mechanisms that are governing carcinoma progression.

Standard DXA measurements, including Fracture Risk Assessment Tool (FRAX) scores, have shown limitations in assessing fracture risk in Type 2 Diabetes (T2D), underscoring the need for novel biomarkers and suggesting that other pathomechanisms may drive diabetic bone fragility. MicroRNAs (miRNAs) are secreted into the circulation from cells of various tissues proportional to local disease severity and were recently found to be crucial to bone homeostasis and T2D. Here, we studied, if and which circulating miRNAs or combinations of miRNAs can discriminate best fracture status in a well‐characterized study of diabetic bone disease and postmenopausal osteoporosis (n = 80 postmenopausal women). We then tested the most discriminative and most frequent miRNAs in vitro. Using miRNA‐qPCR‐arrays, we showed that 48 miRNAs can differentiate fracture status in T2D women and that several combinations of four miRNAs can discriminate diabetes‐related fractures with high specificity and sensitivity (area under the receiver‐operating characteristic curve values [AUCs], 0.92 to 0.96; 95% CI, 0.88 to 0.98). For the osteoporotic study arm, 23 miRNAs were fracture‐indicative and potential combinations of four miRNAs showed AUCs from 0.97 to 1.00 (95% CI, 0.93 to 1.00). Because a role in bone homeostasis for those miRNAs that were most discriminative and most present among all miRNA combinations had not been described, we performed in vitro functional studies in human adipose tissue–derived mesenchymal stem cells to investigate the effect of miR‐550a‐5p, miR‐188‐3p, and miR‐382‐3p on osteogenesis, adipogenesis, and cell proliferation. We found that miR‐382‐3p significantly enhanced osteogenic differentiation (p < 0.001), whereas miR‐550a‐5p inhibited this process (p < 0.001). Both miRNAs, miR‐382‐3p and miR‐550a‐5p, impaired adipogenic differentiation, whereas miR‐188‐3p did not exert an effect on adipogenesis. None of the miRNAs affected significantly cell proliferation. Our data suggest for the first time that miRNAs are linked to fragility fractures in T2D postmenopausal women and should be further investigated for their diagnostic potential and their detailed function in diabetic bone. © 2016 American Society for Bone and Mineral Research.

Disease-specific alterations of the cell-free DNA methylation status are frequently found in serum samples and are currently considered to be suitable biomarkers. Candidate markers were identified by bisulfite conversion-based genome-wide methylation screening of lung tissue from lung cancer, fibrotic ILD, and COPD. cfDNA from 400 μl serum (n = 204) served to test the diagnostic performance of these markers. Following methylation-sensitive restriction enzyme digestion and enrichment of methylated DNA via targeted amplification (multiplexed MSRE enrichment), a total of 96 markers were addressed by highly parallel qPCR. Lung cancer was efficiently separated from non-cancer and controls with a sensitivity of 87.8%, (95%CI: 0.67-0.97) and specificity 90.2%, (95%CI: 0.65-0.98). Cancer was distinguished from ILD with a specificity of 88%, (95%CI: 0.57-1), and COPD from cancer with a specificity of 88% (95%CI: 0.64-0.97). Separation of ILD from COPD and controls was possible with a sensitivity of 63.1% (95%CI: 0.4-0.78) and a specificity of 70% (95%CI: 0.54-0.81). The results were confirmed using an independent sample set (n = 46) by use of the four top markers discovered in the study (HOXD10, PAX9, PTPRN2, and STAG3) yielding an AUC of 0.85 (95%CI: 0.72-0.95). This technique was capable of distinguishing interrelated complex pulmonary diseases suggesting that multiplexed MSRE enrichment might be useful for simple and reliable diagnosis of diverse multifactorial disease states.