Genome-Wide Transcript Profiling Reveals Novel Breast Cancer-Associated Intronic Sense RNAs

Non-coding RNAs (ncRNAs) play major roles in development and cancer progression. To identify novel ncRNAs that may identify key pathways in breast cancer development, we performed high-throughput transcript profiling of tumor and normal matched-pair tissue samples. Initial transcriptome profiling using high-density genome-wide tiling arrays revealed changes in over 200 novel candidate genomic regions that map to intronic regions. Sixteen genomic loci were identified that map to the long introns of five key protein-coding genes, CRIM1, EPAS1, ZEB2, RBMS1, and RFX2. Consistent with the known role of the tumor suppressor ZEB2 in the cancer-associated epithelial to mesenchymal transition (EMT), in situ hybridization reveals that the intronic regions deriving from ZEB2 as well as those from RFX2 and EPAS1 are down-regulated in cells of epithelial morphology, suggesting that these regions may be important for maintaining normal epithelial cell morphology. Paired-end deep sequencing analysis reveals a large number of distinct genomic clusters with no coding potential within the introns of these genes. These novel transcripts are only transcribed from the coding strand. A comprehensive search for breast cancer associated genes reveals enrichment for transcribed intronic regions from these loci, pointing to an underappreciated role of introns or mechanisms relating to their biology in EMT and breast cancer

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Spatiotemporal Angiogenic Patterns in the Development of the Mouse Fetal Blood–Brain Barrier System During Pregnancy

Understanding the timing of fetal brain vulnerability to inflammatory changes in pregnancy complications is crucial for predicting neurodevelopmental risks. Beyond the placenta, the developing brain’s vascular system is believed to form a secondary defense, the blood–brain barrier (BBB), which restricts harmful substances that could disrupt neurodevelopment. However, the precise timing and mechanisms underlying BBB development are poorly understood. In this study, we examined the spatiotemporal expression of key BBB components and fetal brain vascularization in mice from gestational days (GD) 10 to 18. Fetal brain sections were immunostained to identify BBB components, including CD31, Factor VIII, NG2, and claudin-5. Our results showed that endothelial precursor cells form the primitive vascular network in a caudal-to-rostral gradient by GD10, with pericyte recruitment stabilizing vessels by GD12 in a lateral-to-medial gradient that aligns with neurogenesis, despite some regional exceptions. However, Factor VIII was not detected until GD15, and claudin-5 until GD18, suggesting a significant delay in endothelial maturation and tight junction formation. These findings highlight the critical timing of structural developments in the fetal brain vasculature and its vulnerability to placental diseases, laying the groundwork for future research on the impact of placental disorders on fetal brain development and potential therapeutic interventions

Paired-end sequencing read patterns confirm the presence of intronic transcripts.

<p><b>A-C</b>) The number of reads obtained from overlapping paired sequence reads (connected blue boxes) are indicated next to each paired read. Gradient bars (grey to black) represent known transcription factor binding sites obtained from ENCODE ChIP-Seq experiments, generated using UCSC genome browser; darker boxes represent increased transcription factor binding signal strengths across ENCODE experiments. Bottom bar plotgraphs (blue) represent the extent (4 = high, -4 = low) of evolutionary conservation in placental mammals. Reads obtained at locations of CRIM1:1 (<b>A</b>), RFX2:1a (<b>B</b>), and ZEB2:2g (<b>C</b>) reveal clusters of transcript regions that are generally located next to known transcription factor binding sites (Gradient bars) and highly conserved locations (blue). <b>D</b>) qPCR detection of differential expression of CRIM1, RFX2, and ZEB2 intronic transcripts in model breast cancer lines (MCF-7 and MDA-MB-231), in comparison to the model epithelial (normal) cell line, MCF10A. <b>E</b>) Analysis of CRM1:1 and ZEB2:2g locations by northern blot reveals the overabundance of novel transcripts that range from ~300–1000 nts for CRIM1:1 and ~500nts for MCF10A. <b>F</b>) the location of probes used for the northern blot.</p