Bioinformatics methods in biomarkers of preeclampsia and associated potential drug applications

Targeting Neutrophil Extracellular Trap Formation: Exploring Promising Pharmacological Strategies for the Treatment of Preeclampsia

Neutrophils, which constitute the most abundant leukocytes in human blood, emerge as crucial players in the induction of endothelial cell death and the modulation of endothelial cell responses under both physiological and pathological conditions. The hallmark of preeclampsia is endothelial dysfunction induced by systemic inflammation, in which neutrophils, particularly through the formation of neutrophil extracellular traps (NETs), play a pivotal role in the development and perpetuation of endothelial dysfunction and the hypertensive state. Considering the potential of numerous pharmaceutical agents to attenuate NET formation (NETosis) in preeclampsia, a comprehensive assessment of the extensively studied candidates becomes imperative. This review aims to identify mechanisms associated with the induction and negative regulation of NETs in the context of preeclampsia. We discuss potential drugs to modulate NETosis, such as NF-κβ inhibitors, vitamin D, and aspirin, and their association with mutagenicity and genotoxicity. Strong evidence supports the notion that molecules involved in the activation of NETs could serve as promising targets for the treatment of preeclampsia.

Comprehensive analyses of mitophagy-related genes and mitophagy-related lncRNAs for patients with ovarian cancer

BACKGROUND

Both mitophagy and long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC). We sought to explore the characteristics of mitophagy-related gene (MRG) and mitophagy-related lncRNAs (MRL) to facilitate treatment and prognosis of OC.

METHODS

The processed data were extracted from public databases (TCGA, GTEx, GEO and GeneCards). The highly synergistic lncRNA modules and MRLs were identified using weighted gene co-expression network analysis. Using LASSO Cox regression analysis, the MRL-model was first established based on TCGA and then validated with four external GEO datasets. The independent prognostic value of the MRL-model was evaluated by Multivariate Cox regression analysis. Characteristics of functional pathways, somatic mutations, immunity features, and anti-tumor therapy related to the MRL-model were evaluated using abundant algorithms, such as GSEA, ssGSEA, GSVA, maftools, CIBERSORT, xCELL, MCPcounter, ESTIMATE, TIDE, pRRophetic and so on.

RESULTS

We found 52 differentially expressed MRGs and 22 prognostic MRGs in OC. Enrichment analysis revealed that MRGs were involved in mitophagy. Nine prognostic MRLs were identified and eight optimal MRLs combinations were screened to establish the MRL-model. The MRL-model stratified patients into high- and low-risk groups and remained a prognostic factor (P < 0.05) with independent value (P < 0.05) in TCGA and GEO. We observed that OC patients in the high-risk group also had the unfavorable survival in consideration of clinicopathological parameters. The Nomogram was plotted to make the prediction results more intuitive and readable. The two risk groups were enriched in discrepant functional pathways (such as Wnt signaling pathway) and immunity features. Besides, patients in the low-risk group may be more sensitive to immunotherapy (P = 0.01). Several chemotherapeutic drugs (Paclitaxel, Veliparib, Rucaparib, Axitinib, Linsitinib, Saracatinib, Motesanib, Ponatinib, Imatinib and so on) were found with variant sensitivity between the two risk groups. The established ceRNA network indicated the underlying mechanisms of MRLs.

CONCLUSIONS

Our study revealed the roles of MRLs and MRL-model in expression, prognosis, chemotherapy, immunotherapy, and molecular mechanism of OC. Our findings were able to stratify OC patients with high risk, unfavorable prognosis and variant treatment sensitivity, thus improving clinical outcomes for OC patients.

Identification and validation of feature genes associated with M1 macrophages in preeclampsia

Preeclampsia (PE) is a pregnancy-specific cardiovascular complication that is the leading cause of maternal and neonatal morbidity and mortality. Previous studies have indicated the importance of immune cells, such as M1 and M2 macrophages, in the pathogenesis of PE. However, the mechanisms leading to immune dysregulation are unclear. Data-independent acquisition proteomic analysis was performed on placental tissues collected from patients with PE and healthy controls. Transcriptome data for placenta samples from patients with PE and their corresponding controls were obtained from the Gene Expression Omnibus database. Differential analysis of transcriptome and proteome data between PE and control groups was performed using R software. Immunocytic infiltration scoring was performed using the quantiseq algorithm. Weighted gene co-expression network analysis (WGCNA) screened for feature genes associated with M1 cell infiltration. Protein-protein interaction (PPI) analysis identified hub genes. We confirm that the infiltration score of M1 macrophages was significantly increased in the placental tissues of patients with PE. Differential analysis, WGCNA, and PPI analysis identified four hub molecules associated with M1 cell infiltration (HTRA4, POGK, MFAP5, and INHBA). The hub molecules displayed dysregulated expression in PE tissues. The qPCR, Western blots, and immunohistochemistry analyses confirmed that Inhibin, beta A (INHBA) was highly expressed in placental tissues of patients with PE. Immunofluorescence revealed the extensive infiltration of M1 macrophages in the placental tissues of patients with PE and their co-localization with INHBA. The collective results identified hub genes associated with M1 macrophage infiltration, providing potential targets for the pathogenesis and treatment of PE.

Characterization of the lncRNA-mediated ceRNA regulatory networks in preeclampsia by integrated bioinformatics

Preeclampsia (PE) is a significant threat to all pregnancies that is highly associated with maternal mortality and developmental disorders in infants. However, the etiopathogenesis of this condition remains unclear. This study aims to explore the regulatory roles of long noncoding RNAs (lncRNAs) and the mediated competing endogenous RNAs (ceRNA) in the etiopathogenesis of PE through analysis of lncRNA expression patterns in PE and healthy pregnant women (HPW), as well as the construction of lncRNA-mediated ceRNA regulatory networks using bioinformatics. A total of 896 significant differentially expressed lncRNAs, including 586 upregulated lncRNAs and 310 downregulated lncRNAs, were identified in comparison between PE and HPW. Analysis of these differential expressed lncRNAs revealed their predominant enrichment in molecular functions such as sphingosine-1-phosphate phosphatase activity, lipid phosphatase activity, phosphatidate phosphatase activity, thymidylate kinase activity, and UMP kinase activity. Moreover, these differential expressed lncRNAs were predominantly enriched in KEGG analyses such as fat digestion and absorption, lysine degradation, ether lipid metabolism, glycerolipid metabolism, and sphingolipid metabolism. Two ceRNA regulatory networks were constructed based on ceRNA score, including one that had 31 upregulated lncRNAs, 11 downregulated miRNAs, and 34 upregulated mRNAs, while the other contained 128 downregulated lncRNAs, 40 upregulated miRNAs, and 113 downregulated mRNAs. These results may provide a clue to explore the roles of lncRNAs in the etiopathogenesis of PE.