Delaneyhejlesen0476

The diagnosis of and criteria for gestational diabetes mellitus (GDM) continue to divide the scientific and medical community, both between and within countries. Many argue for universal adoption of the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria and feel that further clinical trials are unjustified and even unethical. However, there are concerns about the large increase in number of women who would be diagnosed with GDM using these criteria and the subsequent impact on health care resources and the individual. This Perspective reviews the origins of the IADPSG consensus and points out some of its less well-known limitations, particularly with respect to identifying women at risk for an adverse pregnancy outcome. It also questions the clinical and cost-effectiveness data often cited to support the IADPSG glycemic thresholds. We present the argument that adoption of diagnostic criteria defining GDM should be based on response to treatment at different diagnostic thresholds of maternal glycemia. This will likely require an international multicenter trial of treatment.Epigenetic mechanisms such as aberrant DNA methylation (DNAme) are known to drive esophageal squamous cell carcinoma (ESCC), yet they remain poorly understood. Here, we studied tumor-specific DNAme in ESCC cases from nine high-incidence countries of Africa, Asia, and South America. Infinium MethylationEPIC array was performed on 108 tumors and 51 normal tissues adjacent to the tumors (NAT) in the discovery phase, and targeted pyrosequencing was performed on 132 tumors and 36 NAT in the replication phase. Top genes for replication were prioritized by weighting methylation results using RNA-sequencing data from The Cancer Genome Atlas and GTEx and validated by qPCR. Methylome analysis comparing tumor and NAT identified 6,796 differentially methylated positions (DMP) and 866 differential methylated regions (DMR), with a 30% methylation (Δβ) difference. The majority of identified DMPs and DMRs were hypermethylated in tumors, particularly in promoters and gene-body regions of genes involved in transcription activation. The top three prioritized genes for replication, PAX9, SIM2, and THSD4, had similar methylation differences in the discovery and replication sets. These genes were exclusively expressed in normal esophageal tissues in GTEx and downregulated in tumors. The specificity and sensitivity of these DNAme events in discriminating tumors from NAT were assessed. Our study identified novel, robust, and crucial tumor-specific DNAme events in ESCC tumors across several high-incidence populations of the world. Methylome changes identified in this study may serve as potential targets for biomarker discovery and warrant further functional characterization. SIGNIFICANCE This largest genome-wide DNA methylation study on ESCC from high-incidence populations of the world identifies functionally relevant and robust DNAme events that could serve as potential tumor-specific markers. GRAPHICAL ABSTRACT http//cancerres.aacrjournals.org/content/canres/81/10/2612/F1.large.jpg.Intestinal crypts are composed of heterogeneous and highly plastic cell populations. Lgr5high-stem cells (SC) are responsible for homeostatic renewal, but other cells can revert to an SC-like phenotype to maintain epithelial integrity. Despite their distinct roles in orchestrating homeostasis, both populations have been designated as the putative "cell-of-origin" of colorectal cancer. However, their respective involvement in the emergence of drug-resistant cancer SCs (CSC), responsible for tumor relapse and associated with poor outcome of colorectal cancer, remains elusive. In this context, the intestinal SC/progenitor-marker Musashi1 (MSI1) is interesting as it plays important functions in intestinal homeostasis and is frequently overexpressed in human colorectal cancer. Therefore, our aims were (i) to study the impact of chemotherapy on Lgr5-expressing and MSI1-expressing cell populations, (ii) to explore the effect of increased MSI1 levels in response to treatment, and (iii) to evaluate the relevance in human colorectal cancer. Engineered mouse models treated with the therapeutic agent 5-fluorouracil showed that upon increased MSI1 levels, Lgr5high SCs remain sensitive while Lgr5low progenitors reprogram to a drug-resistant phenotype. This resulted in the expansion of an MSI1-expressing cell subpopulation with improved resistance to DNA damage and increased detoxification, typical properties of dormant-CSCs that can reactivate after chemotherapy. Analysis in patients with colorectal cancer revealed a correlation between MSI1 levels and tumor grading, CSC phenotype, and chemoresistance. Altogether, these results shed new light on the biology and plasticity of normal crypt and cancer cell populations and also open new perspectives to target MSI1 to improve chemotherapy outcome. SIGNIFICANCE This study unveils paradoxical roles for MSI1, underlining its importance in facilitating intestinal regeneration upon injury but also unraveling its new function in drug-resistant colorectal cancer stem cells.Label-free nonlinear microscopy enables nonperturbative visualization of structural and metabolic contrast within living cells in their native tissue microenvironment. fMLP solubility dmso Here a computational pipeline was developed to provide a quantitative view of the microenvironmental architecture within cancerous tissue from label-free nonlinear microscopy images. To enable single-cell and single-extracellular vesicle (EV) analysis, individual cells, including tumor cells and various types of stromal cells, and EVs were segmented by a multiclass pixelwise segmentation neural network and subsequently analyzed for their metabolic status and molecular structure in the context of the local cellular neighborhood. By comparing cancer tissue with normal tissue, extensive tissue reorganization and formation of a patterned cell-EV neighborhood was observed in the tumor microenvironment. The proposed analytic pipeline is expected to be useful in a wide range of biomedical tasks that benefit from single-cell, single-EV, and cell-to-EV analysis.