Gene expression analysis of MMPs in women with preeclampsia using cell-free fetal RNA in maternal plasma

Prediction of preeclampsia using maternal circulating mRNAs in early pregnancy

PURPOSE

Preeclampsia (PE) is one of the most common and serious complications of pregnancy, and novel methods for the early prediction of PE are needed for clinical application.

METHODS

In this study, a circulating cell-free RNA (cfRNA) panel of target genes for PE prediction was designed and validated in a case-control cohort and a nested case-control cohort. The QPCR was applied to quantify the copy number of cfRNA, and the data were normalized as multiples of the median. Ratios of serum placental growth factor (PIGF) and soluble fms-like tyrosine kinase 1 (sFLT-1) were also measured, and transabdominal ultrasonography was conducted for subjects in the prospective cohort. Binary logistic regression models for PE prediction were constructed and tested.

RESULTS

Our results revealed that the women with PE showed significant alterations in serum cfRNA profiles from early pregnancy onward and before the onset of PE symptoms. Compared with PIGF/sFLT-1 measurement and ultrasonographic imaging, cfRNA test can detect PE at a very early stage of pregnancy. The predictive model exhibited the best performance at gestation week 32, with a detection rate of 100%. At 12 weeks of gestation, the model still manifested an area under curve (AUC) of 0.9144, and sensitivity of 1.0000. If combined with clinical parameters and ultrasonographic indicators, the model can achieve the highest AUC for PE prediction at early gestation.

CONCLUSION

Measurement of cfRNA can be used to effectively predict PE with high performance, providing an additional method for monitoring PE throughout the course of pregnancy.

Maternal Immune System and State of Inflammation Dictate the Fate and Severity of Disease in Preeclampsia

Preeclampsia, a multisystem disorder in pregnant women, is diagnosed by onset of new hypertension, proteinuria, or organ damage. Antiangiogenic factors, such as soluble fms-like tyrosine kinase 1 (sFlt1) and soluble endoglin (sEng), are long known to be involved in preeclampsia. However, the role of maternal immune system and inflammation in promotion of preeclampsia has lately been a subject of immense interest. Link between maternal inflammation and preeclampsia is not well established. Furthermore, whether cigarette smoke promotes inflammation and also promotes severity of preeclampsia remains an open question. We herein investigated correlation of established inflammation signatures in the plasma and placental tissue from cohorts of preterm preeclampsia (PPE) and preterm pregnancies (control) with or without smoking history. Besides confirming increased levels of Flt1 and Eng in preeclampsia, we also observed an increase in various mediators of maternal inflammation in women with PPE compared to preterm cohort. Increased IL-6, IL-35, and TNF-α and reduced IL-10 in serum and higher MMP-12, TLR4, HMGB-1, and iNOS and lower Foxp3, CD56 transcripts in placental tissues of PPE compared to preterm pregnancies indicate an association of preterm preeclampsia with stark imbalance in maternal immune system and signatures of inflammation. Smoker PPE cohorts showed highest inflammatory signatures including statistically significant increase for many signatures compared to other cohorts. Together, these results provide evidence for association of inflammation with PPE and strong correlation of smoking with inflammatory signatures in PPE.

The Novel Target of Liver Cancer: MicroRNA-4324 Regulates Cell Proliferation and Migration via Targeting Neuraminidase 3

Background: MicroRNA-4324 has been reported to regulate various biological malignant cancer. Nonetheless, the expression and molecular mechanism of miR-4324 in liver cancer remain rarely known. This study aimed to investigate the effect miR-4324 on the proliferation, invasion and migration of hepatoma cells. Methods: The mRNA level of miR-4324 was assessed in four hepatoma cell lines (HepG2, Huh7, MHCC97, HB611) and human embryonic liver cell, HHL5. MiR-4324 was over-expressed in hepatoma cells. Subsequently, the effects of miR-4324 on cell proliferation, migration and invasion and the underlying molecular mechanisms were detected. Results: Our data indicated that miR-4324 was down-regulation in hepatoma cell lines compared with HHL5. Overexpression of miR-4324 inhibits cellular proliferation, colony-formation, migration and invasion abilities of hepatoma cells. However, the biological effects of miR-4324 overexpression on hepatoma cells were reversed after overexpressing NEU3. Conclusions: Our findings concluded that miR-4324 inhibits biological functions of hepatoma cells by targeting NEU3 and it might be a potential target for the treatment of liver cancer.

Commentary on a combined approach to the problem of developing biomarkers for the prediction of spontaneous preterm labor that leads to preterm birth

INTRODUCTION

Globally, preterm birth has replaced congenital malformation as the major cause of perinatal mortality and morbidity. The reduced rate of congenital malformation was not achieved through a single biophysical or biochemical marker at a specific gestational age, but rather through a combination of clinical, biophysical and biochemical markers at different gestational ages. Since the aetiology of spontaneous preterm birth is also multifactorial, it is unlikely that a single biomarker test, at a specific gestational age will emerge as the definitive predictive test.

METHODS

The Biomarkers Group of PREBIC, comprising clinicians, basic scientists and other experts in the field, with a particular interest in preterm birth have produced this commentary with short, medium and long-term aims: i) to alert clinicians to the advances that are being made in the prediction of spontaneous preterm birth; ii) to encourage clinicians and scientists to continue their efforts in this field, and not to be disheartened or nihilistic because of a perceived lack of progress and iii) to enable development of novel interventions that can reduce the mortality and morbidity associated with preterm birth.

RESULTS

Using language that we hope is clear to practising clinicians, we have identified 11 Sections in which there exists the potential, feasibility and capability of technologies for candidate biomarkers in the prediction of spontaneous preterm birth and how current limitations to this research might be circumvented.

DISCUSSION

The combination of biophysical, biochemical, immunological, microbiological, fetal cell, exosomal, or cell free RNA at different gestational ages, integrated as part of a multivariable predictor model may be necessary to advance our attempts to predict sPTL and PTB. This will require systems biological data using "omics" data and artificial intelligence/machine learning to manage the data appropriately. The ultimate goal is to reduce the mortality and morbidity associated with preterm birth.