Comprehensive analysis of lncRNA-miRNA-mRNA ceRNA network and key genes in granulosa cells of patients with biochemical primary ovarian insufficiency

Liu, Biting; Liu, Li; Sulaiman, Zubaidan; Wang, Chunyan; Wang, Lian; Zhu, Jihui; Liu, Shupeng; Cheng, Zhongping

doi:10.1007/s10815-023-02937-2

Cited by 4 publications

(2 citation statements)

References 47 publications

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“…Augmenting this discovery, the investigation also identified five hub miRNAs—hsa-miR-27a-3p, hsa-miR-24-3p, hsa-miR-22-3p, hsa-miR-129-5p, and hsa-miR-17-5p. Intriguingly, these findings suggest a regulatory nexus wherein the expression of these key genes appears to be orchestrated by two central hub miRNAs: hsa-miR-27a-3p and hsa-miR-17-5p 60 . These findings not only augment our understanding of the intricate molecular landscape associated with POF but also herald a paradigm shift in diagnostic possibilities.…”

Section: Discussionmentioning

confidence: 94%

The shared mechanism and potential diagnostic markers for premature ovarian failure and dry eye disease

Long,

Wu,

Jiang

et al. 2024

Sci Rep

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Premature ovarian failure (POF), which is often comorbid with dry eye disease (DED) is a key issue affecting female health. Here, we explored the mechanism underlying comorbid POF and DED to further elucidate disease mechanisms and improve treatment. Datasets related to POF (GSE39501) and DED (GSE44101) were identified from the Gene Expression Omnibus (GEO) database and subjected to weighted gene coexpression network (WGCNA) and differentially expressed genes (DEGs) analyses, respectively, with the intersection used to obtain 158 genes comorbid in POF and DED. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses of comorbid genes revealed that identified genes were primarily related to DNA replication and Cell cycle, respectively. Protein–Protein interaction (PPI) network analysis of comorbid genes obtained the 15 hub genes: CDC20, BIRC5, PLK1, TOP2A, MCM5, MCM6, MCM7, MCM2, CENPA, FOXM1, GINS1, TIPIN, MAD2L1, and CDCA3. To validate the analysis results, additional POF- and DED-related datasets (GSE48873 and GSE171043, respectively) were selected. miRNAs-lncRNAs-genes network and machine learning methods were used to further analysis comorbid genes. The DGIdb database identified valdecoxib, amorfrutin A, and kaempferitrin as potential drugs. Herein, the comorbid genes of POF and DED were identified from a bioinformatics perspective, providing a new strategy to explore the comorbidity mechanism, opening up a new direction for the diagnosis and treatment of comorbid POF and DED.

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Section: Discussionmentioning

confidence: 94%

The shared mechanism and potential diagnostic markers for premature ovarian failure and dry eye disease

Long,

Wu,

Jiang

et al. 2024

Sci Rep

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“…Research have shown that PTPRD (protein tyrosine phosphatase receptor type D) [656], PDGFB (platelet derived growth factor subunit B) [642], DAPK1 [751], hsa-mir-4432 [1693], SMARCA4 [1694] and TRIM28 [1695] participates in hypertension. IGF2BP1 [994], hsa-mir-17-5p [1696] and SMARCA4 [1697] plays an important role in the infertility. TRIM28 [1698] expression have been observed in pain.…”

Section: Go and Pathway Enrichment Analyses Of Degsmentioning

confidence: 99%

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

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Endometriosis is a common cause of endometrial-type mucosa outside the uterine cavity with symptoms such as painful periods, chronic pelvic pain, pain with intercourse and infertility. However, the early diagnosis of endometriosis is still restricted. The purpose of this investigation is to identify and validate the key biomarkers of endometriosis. Next generation sequencing (NGS) dataset GSE243039 was obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) between endometriosis and normal control samples were identified. After screening of DEGs, gene ontology (GO) and REACTOME pathway enrichment analyses were performed. Furthermore, a protein-protein interaction (PPI) network was constructed and modules were analysed using the Human Integrated Protein-Protein Interaction rEference (HIPIE) database and Cytoscape software, and hub genes were identified. Subsequantely, a network between miRNAs and hub genes, and network between TFss and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve (ROC) analysis was used to validate the hub genes. A total of 958 DEGs, including 479 up regulated genes and 479 down regulated genes, were screened between endometriosis and normal control samples. GO and REACTOME pathway enrichment analyses of the 958 DEGs showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and muscle contraction. Further analysis of the PPI network and modules identified 10 hub genes, including VCAM1, SNCA, PRKCB, ADRB2, FOXQ1, MDFI, ACTBL2, PRKD1, DAPK1 and ACTC1. Possible target miRNAs, including hsa-mir-3143 and hsa-mir-2110, and target TFs, including TCF3 and CLOCK, were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network. This investigation used bioinformatics techniques to explore the potential and novel biomarkers. These biomarkers might provide new ideas and methods for the early diagnosis, treatment, and monitoring of endometriosis.

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Building a Human Ovarian Antioxidant ceRNA Network “OvAnOx”: A Bioinformatic Perspective for Research on Redox-Related Ovarian Functions and Dysfunctions

Tatone,

Di Emidio,

Battaglia

et al. 2024

Antioxidants

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The ovary is a major determinant of female reproductive health. Ovarian functions are mainly related to the primordial follicle pool, which is gradually lost with aging. Ovarian aging and reproductive dysfunctions share oxidative stress as a common underlying mechanism. ROS signaling is essential for normal ovarian processes, yet it can contribute to various ovarian disorders when disrupted. Therefore, balance in the redox system is crucial for proper ovarian functions. In the present study, by focusing on mRNAs and ncRNAs described in the ovary and taking into account only validated ncRNA interactions, we built an ovarian antioxidant ceRNA network, named OvAnOx ceRNA, composed of 5 mRNAs (SOD1, SOD2, CAT, PRDX3, GR), 10 miRNAs and 5 lncRNAs (XIST, FGD5-AS1, MALAT1, NEAT1, SNHG1). Our bioinformatic analysis indicated that the components of OvAnOx ceRNA not only contribute to antioxidant defense but are also involved in other ovarian functions. Indeed, antioxidant enzymes encoded by mRNAs of OvAnOx ceRNA operate within a regulatory network that impacts ovarian reserve, follicular dynamics, and oocyte maturation in normal and pathological conditions. The OvAnOx ceRNA network represents a promising tool to unravel the complex dialog between redox potential and ovarian signaling pathways involved in reproductive health, aging, and diseases.

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Comprehensive analysis of lncRNA-miRNA-mRNA ceRNA network and key genes in granulosa cells of patients with biochemical primary ovarian insufficiency

Cited by 4 publications

References 47 publications

The shared mechanism and potential diagnostic markers for premature ovarian failure and dry eye disease

The shared mechanism and potential diagnostic markers for premature ovarian failure and dry eye disease

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next generation sequencing data analysis

Building a Human Ovarian Antioxidant ceRNA Network “OvAnOx”: A Bioinformatic Perspective for Research on Redox-Related Ovarian Functions and Dysfunctions

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