Background and objectives: Gestational diabetes mellitus (GDM) is known to be associated with pregnancy complications but there is limited evidence about the strength of these associations in recent clinical practice, especially after the introduction of strict guidelines for the management of pregnancies with GDM in a multidisciplinary team setting. The objectives of our study were to first compare the rates of complications in pregnancies with GDM with those that had pre-existing diabetes mellitus and those without diabetes; and second, to derive measures of effect size expressed as odds ratios after adjustment for confounding factors to assess the independent association of GDM in prediction of these pregnancy complications. Materials and Methods: This was a prospective cohort study undertaken at a large maternity unit in the United Kingdom between January 2010 and June 2022. We included singleton pregnancies that were booked at our unit at 11–13 weeks’ gestation. Multivariate regression analysis was carried out to determine the risks of complications in pregnancies with GDM after adjusting for pregnancy characteristics. Risks were expressed as odds ratio (OR) (95% confidence intervals [CI]) and expressed graphically in forest plots. Results: The study population included 53,649 singleton pregnancies including 509 (1%) with pre-existing DM, 2089 (4%) with GDM and 49,122 (95%) pregnancies without diabetes. Multivariate regression analysis demonstrated that there was a significant independent contribution from GDM in the prediction of adverse outcomes, including maternal complications such as preterm delivery, polyhydramnios, preeclampsia and delivery of large for gestational age neonates and elective caesarean section (CS); and neonatal complications including admission to neonatal intensive care unit, hypoglycaemia, jaundice and respiratory distress syndrome. Conclusions: GDM is associated with an increased rate of pregnancy complications compared to those without diabetes, even after adjustment for maternal and pregnancy characteristics. GDM does not increase the risk of stillbirth, hypoxic ischaemic encephalopathy or neonatal death.

Endometrial cancer rates are increasing annually due to an aging population and rising rates of obesity. Currently there is no widely available, accurate, non-invasive test that can be used to triage women for diagnostic biopsy whilst safely reassuring healthy women without the need for invasive assessment. The aim of this systematic review and meta-analysis is to evaluate studies assessing blood and urine-based biomarkers as a replacement test for endometrial biopsy or as a triage test in symptomatic women. For each primary study, the diagnostic accuracy of different biomarkers was assessed by sensitivity, specificity, likelihood ratio and area under ROC curve. Forest plots of summary statistics were constructed for biomarkers which were assessed by multiple studies using data from a random-effect models. All but one study was of blood-based biomarkers. In total, 15 studies reported 29 different exosomal biomarkers; 34 studies reported 47 different proteomic biomarkers. Summary statistic meta-analysis was reported for micro-RNAs, cancer antigens, hormones, and other proteomic markers. Metabolites and circulating tumor materials were also summarized. For the majority of biomarkers, no meta-analysis was possible. There was a low number of small, heterogeneous studies for the majority of evaluated index tests. This may undermine the reliability of summary estimates from the meta-analyses. At present there is no liquid biopsy that is ready to be used as a replacement test for endometrial biopsy. However, to the best of our knowledge this is the first study to report and meta-analyze the diagnostic accuracy of different classes of blood and urine biomarkers for detection of endometrial cancer. This review may thus provide a reference guide for those wishing to explore candidate biomarkers for further research.

Background: Protein Tyrosine Phosphatase Receptor Type D (PTPRD) is involved in the regulation of cell growth, differentiation, and oncogenic transformation, as well as in brain development. PTPRD also mediates the effects of asprosin, which is a glucogenic hormone/adipokine derived following the cleavage of the C-terminal of fibrillin 1. Since the asprosin circulating levels are elevated in certain cancers, research is now focused on the potential role of this adipokine and its receptors in cancer. As such, in this study, we investigated the expression of PTPRD in endometrial cancer (EC) and the placenta, as well as in glioblastoma (GBM). Methods: An array of in silico tools, in vitro models, tissue microarrays (TMAs), and liquid biopsies were employed to determine the gene and protein expression of PTPRD in healthy tissues/organs and in patients with EC and GBM. Results: PTPRD exhibits high expression in the occipital lobe, parietal lobe, globus pallidus, ventral thalamus, and white matter, whereas in the human placenta, it is primarily localised around the tertiary villi. PTPRD is significantly upregulated at the mRNA and protein levels in patients with EC and GBM compared to healthy controls. In patients with EC, PTPRD is significantly downregulated with obesity, whilst it is also expressed in the peripheral leukocytes. The EC TMAs revealed abundant PTPRD expression in both low- and high-grade tumours. Asprosin treatment upregulated the expression of PTPRD only in syncytialised placental cells. Conclusions: Our data indicate that PTPRD may have potential as a biomarker for malignancies such as EC and GBM, further implicating asprosin as a potential metabolic regulator in these cancers. Future studies are needed to explore the potential molecular mechanisms/signalling pathways that link PTPRD and asprosin in cancer.

Background: Metabolic syndrome (MetS) is a syndrome that comprises central obesity, increased serum triglyceride (TG) levels, decreased serum HDL cholesterol (HDL) levels, raised blood pressure (BP), and impaired glucose regulation, including prediabetic and diabetic glycaemic levels. Recently, the association with endometrial cancer (EC) has been described but it is unclear if the risk associated with MetS is higher than the individual effect of obesity alone. This study investigates the association between MetS components and differing MetS definitions on EC risk and compares the risk of MetS with the risk posed by obesity alone. It also analyses how MetS affects the risk of EC development in the pre- and post-menopausal subgroups. Methods: A prospective cohort study was undertaken using data from the UK biobank. Multivariable Cox proportional risk models with the time to diagnosis (years) were used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of MetS and its components on the risk of EC. A subgroup analysis was also undertaken for pre- and post-menopausal participants. Kaplan–Meier (KM) was undertaken to assess the difference in the risk of EC development in differing BMI classes, and in pre- and post-menopausal subgroups. Results: A total of 177,005 females from the UK biobank were included in this study. Of those participants who developed EC (n = 1454), waist circumference > 80 cm, BMI > 30 kg/m², hypertension > 130/80 mmHg, hyperlipidaemia and diabetes (HbA1C > 48 mmol/L were significant predictors of EC development, with waist circumference being the strongest predictor (HR = 2.21; 95% CI: 1.98–2.47, p < 0.001). Comparing the pre- and post-menopausal subgroup, hypertriglyceridaemia and diabetes were the strongest predictors of EC in the pre-menopausal subgroup (HR = 1.53; 95% CI: 1.18–1.99 and HR = 1.51; 95% CI: 1.08–2.12, p < 0.05, respectively). Raised waist circumference was not a significant independent predictor in the pre-menopausal subgroup. A KM curve analysis showed a clear distinction between those with and without MetS in the pre-menopausal group, suggesting a benefit of testing for MetS components in pre-menopausal women with obesity. Conclusions: Components of MetS, both independently and in combination, significantly increase the risk of EC. Screening those with obesity for MetS in their pre-menopausal years may help to identify those at the highest risk.