Glucose-6-phosphate dehydrogenase (G6PD) deficiency has been revealed to be involved in the efficacy to anti-cancer therapy but the mechanism remains unclear. We aimed to investigate the anti-cancer mechanism of G6PD deficiency. In our study, dehydroepiandrosterone (DHEA) and shRNA technology were used for inhibiting the activity of G6PD of cervical cancer cells. Peak Force QNM Atomic Force Microscopy was used to assess the changes of topography and biomechanical properties of cells and detect the effects on living cells in a natural aqueous environment. Flow cytometry was used to detect the apoptosis and reactive oxygen species (ROS) generation. Scanning electron microscopy was used to observe cell morphology. Moreover, a laser scanning confocal microscope was used to observe the alterations in cytoskeleton to explore the involved mechanism. When G6PD was inhibited by DHEA or RNA interference, the abnormal Young's modulus and increased roughness of cell membrane were observed in HeLa cells, as well as the idioblasts. Simultaneously, G6PD deficiency resulted in decreased HeLa cells migration and proliferation ability but increased ROS generation inducing apoptosis. What's more, the inhibition of G6PD activity caused the disorganization of microfilaments and microtubules of cytoskeletons and cell shrinkage. Our results indicated the anti-cervix cancer mechanism of G6PD deficiency may be involved with the decreased cancer cells migration and proliferation ability as a result of abnormal reorganization of cell cytoskeleton and abnormal biomechanical properties caused by the increased ROS. Suppression of G6PD may be a promising strategy in developing novel therapeutic methods for cervical cancer.
Background Recent evidence suggests early screening of preeclampsia and small-for-gestational-age (SGA) would benefit pregnancies followed by subsequent prophylactic use of aspirin. Multi-marker models have shown capability of predicting preeclampsia and SGA in first trimester. Yet the clinical feasibility of combined screening model for Chinese pregnancies has not been fully assessed. The aim of this study is to evaluate the applicability of a multi-marker screening model to the prediction of preeclampsia and SGA in first trimester particularly among Chinese population. Methods Three thousand two hundred seventy pregnancies meeting the inclusion criteria took first-trimester screening of preeclampsia and SGA. A prior risk based on maternal characteristics was evaluated, and a posterior risk was assessed by combining prior risk with multiple of median (MoM) values of mean arterial pressure (MAP), serum placental growth factor (PLGF) and pregnancy associated plasma protein A (PAPP-A). Both risks were calculated by Preeclampsia PREDICTOR™ software, Perkin Elmer. Screening performance of prior and posterior risks for early and late preeclampsia by using PREDICTOR software was shown by Receiver Operating Characteristics (ROC) curves. The estimation of detection rates and false positive rates of delivery with both preeclampsia and SGA was made. Results Eight cases developed early preeclampsia (0.24%) and 35 were diagnosed as late preeclampsia (1.07%). Five with early preeclampsia and ten with late preeclampsia later delivered SGA newborns (0.46%); 84 without preeclampsia gave birth to the SGAs (2.57%). According to ROC curves, posterior risks performed better than prior risks in terms of preeclampsia, especially in early preeclampsia. At 10% false positive rate, detection rates of early and late preeclampsia were 87.50 and 48.57%, detection rates of early and late SGA were 41.67 and 28.00%, respectively. For SGA, detection rates in cases with preeclampsia were much higher than those in absence of it. Conclusions This study demonstrates that combined screening model could be useful for predicting early preeclampsia in Chinese pregnancies. Furthermore, the performance of SGA screening by same protocol is strongly associated with preeclampsia. Electronic supplementary material The online version of this article (10.1186/s12884-019-2455-8) contains supplementary material, which is available to authorized users.
Preeclampsia is a progressive, multisystem pregnancy disorder. According to the time of onset or delivery, preeclampsia has been subclassified into early-onset (<34 weeks) and late-onset (≥34 weeks), or preterm (<37 weeks) and term (≥37 weeks). Preterm preeclampsia can be effectively predicted at 11–13 weeks well before onset, and its incidence can be reduced by preventively using low-dose aspirin. However, late-onset and term preeclampsia are more prevalent than early forms and still lack effective predictive and preventive measures. This scoping review aims to systematically identify the evidence of predictive biomarkers reported in late-onset and term preeclampsia. This study was conducted based on the guidance of the Joanna Briggs Institute (JBI) methodology for scoping reviews. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) was used to guide the study. The following databases were searched for related studies: PubMed, Web of Science, Scopus, and ProQuest. Search terms contain “preeclampsia,” “late-onset,” “term,” “biomarker,” or “marker,” and other synonyms combined as appropriate using the Boolean operators “AND” and “OR.” The search was restricted to articles published in English from 2012 to August 2022. Publications were selected if study participants were pregnant women and biomarkers were detected in maternal blood or urine samples before late-onset or term preeclampsia diagnosis. The search retrieved 4,257 records, of which 125 studies were included in the final assessment. The results demonstrate that no single molecular biomarker presents sufficient clinical sensitivity and specificity for screening late-onset and term preeclampsia. Multivariable models combining maternal risk factors with biochemical and/or biophysical markers generate higher detection rates, but they need more effective biomarkers and validation data for clinical utility. This review proposes that further research into novel biomarkers for late-onset and term preeclampsia is warranted and important to find strategies to predict this complication. Other critical factors to help identify candidate markers should be considered, such as a consensus on defining preeclampsia subtypes, optimal testing time, and sample types.
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