A risk model developed based on necroptosis to assess progression for ischemic cardiomyopathy and identify possible therapeutic drugs

A novel model based on necroptosis to assess progression for polycystic ovary syndrome and identification of potential therapeutic drugs

Background

Polycystic ovary syndrome (PCOS), a common endocrine and reproductive disorder, lacks precise diagnostic strategies. Necroptosis was found to be crucial in reproductive and endocrine disorders, but its function in PCOS remains unclear. We aimed to identify differentially diagnostic genes for necroptosis (NDDGs), construct a diagnostic model to assess the progression of PCOS and explore the potential therapeutic drugs.

Methods

Gene expression datasets were combined with weighted gene co-expression network analysis (WGCNA) and necroptosis gene sets to screen the differentially expressed genes for PCOS. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a necroptosis-related gene signatures. Independent risk analyses were performed using nomograms. Pathway enrichment of NDDGs was conducted with the GeneMANIA database and gene set enrichment analysis (GSEA). Immune microenvironment analysis was estimated based on ssGSEA algorithm analysis. The Comparative Toxicogenomics Database (CTD) was used to explore potential therapeutic drugs for NDDGs. The expression of NDDGs was validated in GSE84958, mouse model and clinical samples.

Results

Four necroptosis-related signature genes, IL33, TNFSF10, BCL2 and PYGM, were identified to define necroptosis for PCOS. The areas under curve (AUC) of receiver operating characteristic curve (ROC) for training set and validation in diagnostic risk model were 0.940 and 0.788, respectively. Enrichment analysis showed that NDDGs were enriched in immune-related signaling pathways such as B cells, T cells, and natural killer cells. Immune microenvironment analysis revealed that NDDGs were significantly correlated with 13 markedly different immune cells. A nomogram was constructed based on features that would benefit patients clinically. Several compounds, such as resveratrol, tretinoin, quercetin, curcumin, etc., were mined as therapeutic drugs for PCOS. The expression of the NDDGs in the validated set, animal model and clinical samples was consistent with the results of the training sets.

Conclusion

In this study, 4 NDDGs were identified to be highly effective in assessing the progression and prognosis of PCOS and exploring potential targets for PCOS treatment.

Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses

BACKGROUND

Preeclampsia (PE) is a serious pregnancy complication that can adversely affect the mother and fetus. Necroptosis is a recently discovered new form of programmed cell death involved in the pathological process of various pregnancy complications. Our study aimed to identify the necroptosis-related differentially expressed genes (NRDEGs), create a diagnosis model and related disease subtypes model based on these genes, and further investigate their relationship with immune infiltration.

METHODS

In this study, we identified NRDEGs by analyzing data from various databases, including Molecular Signatures, GeneCards, and Gene Expression Omnibus (GEO). Using minor absolute shrinkage and selection operator (LASSO) and logistic Cox regression analysis, we developed a novel PE diagnosis model based on NRDEGs. Furthermore, we developed PE subtype models using consensus clustering analysis based on key gene modules screened out by weighted correlation network analysis (WGCNA). Finally, we identified the difference in immune infiltration between the PE and control groups as well as between both PE subtypes by analyzing the immune cell infiltration across combined datasets and PE datasets.

RESULTS

Our study discovered that the necroptosis pathway was significantly enriched and active in PE samples. We identified nine NRDEGs that involved in this pathway, including BRAF, PAWR, USP22, SYNCRIP, KRT86, MERTK, BAP1, CXCL5, and STK38. Additionally, we developed a diagnostic model based on a regression model including six NRDEGs and identified two PE subtypes: Cluster1 and Cluster2, based on key module genes. Furthermore, correlation analysis showed that the abundance of immune cell infiltration was related to necroptosis genes and PE disease subtypes.

CONCLUSION

According to the present study, necroptosis is a phenomenon that occurs in PE and is connected to immune cell infiltration. This result suggests that necroptosis and immune-related factors may be the underlying mechanisms of PE pathophysiology. This study opens new avenues for future research into PE's pathogenesis and treatment options.