Implantation failure and embryo loss contribute to subfertility in female mice mutant for chromatin remodeler Cecr2†

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

Background

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.

Methods

Next-generation sequencing dataset GSE243039 was obtained from the Gene Expression Omnibus 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 analyzed using the Human Integrated Protein–Protein Interaction rEference database and Cytoscape software, and hub genes were identified. Subsequently, a network between miRNAs and hub genes, and network between TFs and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve analysis was used to validate the hub genes.

Results

A total of 958 DEGs, including 479 upregulated genes and 479 downregulated 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 (transcription factor 3) and clock (clock circadian regulator), were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network.

Conclusions

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.

Chromatin remodeling factor CECR2 forms tissue-specific complexes with CCAR2 and LUZP1

Chromatin remodeling complexes alter chromatin structure to control access to DNA and therefore control cellular processes such as transcription, DNA replication, and DNA repair. CECR2 is a chromatin remodeling factor that plays an important role in neural tube closure and reproduction. Loss-of-function mutations in Cecr2 result primarily in the perinatal lethal neural tube defect exencephaly, with non-penetrant mice that survive to adulthood exhibiting subfertility. CECR2 forms a complex with ISWI proteins SMARCA5 and/or SMARCA1, but further information on the structure and function of the complex is not known. We therefore have identified candidate components of the CECR2-containing remodeling factor (CERF) complex in embryonic stem (ES) cells through mass spectroscopy. Both SMARCA5 and SMARCA1 were confirmed to be present in CERF complexes in ES cells and testis. However, novel proteins CCAR2 and LUZP1 are CERF components in ES cells but not testis. This tissue specificity in mice suggests these complexes may also have functional differences. Furthermore, LUZP1, loss of which is also associated with exencephaly, appears to play a role in stabilizing the CERF complex in ES cells. Keywords: CECR2, LUZP1, CCAR2, Chromatin remodeling factor, Neural tube defects.