Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer.

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Association of the LEP gene with immune infiltration as a diagnostic biomarker in preeclampsia.

Objective: Preeclampsia (PE) is a serious condition in pregnant women and hence an important topic in obstetrics. The current research aimed to recognize the potential and significant immune-related diagnostic biomarkers for PE. Methods: From the Gene Expression Omnibus (GEO) data sets, three public gene expression profiles (GSE24129, GSE54618, and GSE60438) from the placental samples of PE and normotensive pregnancy were downloaded. Differentially expressed genes (DEGs) were selected and determined among 73 PE and 85 normotensive control pregnancy samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analysis. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the expression levels and diagnostic value of biomarkers in PE were verified in the GSE75010 data set (80 PE and 77 controls) and validated by qRT-RCR, Western blot, and immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in PE. Results: In total, 15 DEGs were recognized. The GO and KEGG analyses revealed that the DEGs were enriched in the steroid metabolic process, receptor ligand activity, GnRH secretion, and neuroactive ligand-receptor interaction. The recognized DEGs were primarily implicated in cell-type benign neoplasm, kidney failure, infertility, and PE. Gene sets related to hormone activity, glycosylation, multicellular organism process, and response to BMP were activated in PE. The LEP gene was distinguished as a diagnostic biomarker of PE (AUC = 0.712) and further certified in the GSE75010 data set (AUC = 0.850). The high expression of LEP was associated with PE in clinical samples. In addition, the analysis of the immune microenvironment showed that gamma delta T cells, memory B cells, M0 macrophages, and regulatory T cells were positively correlated with LEP expression (P < 0.05). Conclusion: LEP expression can be considered to be a diagnostic biomarker of PE and can offer a novel perspective for future studies regarding the occurrence and molecular mechanisms of PE.

Therapeutic potential of exosomes/miRNAs in polycystic ovary syndrome induced by the alteration of circadian rhythms.

Polycystic ovary syndrome (PCOS) is a reproductive dysfunction associated with endocrine disorders and is most common in women of reproductive age. Clinical and/or biochemical manifestations include hyperandrogenism, persistent anovulation, polycystic ovary, insulin resistance, and obesity. Presently, the aetiology and pathogenesis of PCOS remain unclear. In recent years, the role of circadian rhythm changes in PCOS has garnered considerable attention. Changes in circadian rhythm can trigger PCOS through mechanisms such as oxidative stress and inflammation; however, the specific mechanisms are unclear. Exosomes are vesicles with sizes ranging from 30-120nm that mediate intercellular communication by transporting microRNAs (miRNAs), proteins, mRNAs, DNA, or lipids to target cells and are widely involved in the regulation of various physiological and pathological processes. Circadian rhythm can alter circulating exosomes, leading to a series of related changes and physiological dysfunctions. Therefore, we speculate that circadian rhythm-induced changes in circulating exosomes may be involved in PCOS pathogenesis. In this review, we summarize the possible roles of exosomes and their derived microRNAs in the occurrence and development of PCOS and discuss their possible mechanisms, providing insights into the potential role of exosomes for PCOS treatment.

Identification of Core Genes Shared by Endometrial Cancer and Ovarian Cancer Using an Integrated Approach.

Ovarian cancer (OC) is one of the most commonly diagnosed cancers among women. Moreover, Endometrial cancer (EC) is a usual genital tract cancer in females; however, the hub genes and molecular pathways shared by these two cancers have not been surveyed yet. So, this study aimed to identify the common candidate genes or biomarkers and molecular pathways in OC and EC. Differences in the expressed genes between these two microarray data sets were detected. Pathway enrichment analysis and gene ontology (GO) was also performed and protein-protein interactions (PPI) network analysis was done using Cytoscape and the most important genes were identified by the Cytohubba plugin. We found that 154 common DEGs shared by OC and EC were also detected. 10 hub proteins were identified as follows: CDC20, BUB1, CENPF, KIF11, CCNB2, FOXM1, TTK, TOP2A, DEPDC1, and NCAPG. The most important and significant miRNAs were identified to be hsa-mir-186-5p, hsa-mir-192-5p, hsa-mir-215-5p, and hsa-mir-193b-3p regulated expressions of the DEGs.  This investigation demonstrated that these hub genes and their miRNA might be key genes with great effects on OC and EC. However, more studies are needed for a better understanding of the role of these hub genes and their function in these two cancers.