Combination of Estradiol with Leukemia Inhibitory Factor Stimulates Granulosa Cells Differentiation into Oocyte-Like Cells.
Soudabe YousefiMaryam AkbarzadehJafar SoleimaniradKobra HamdiLaya FarzadiAalie GhasemzadehMahdi MahdipourReza RahbarghaziMohammad NouriPublished in: Advanced pharmaceutical bulletin (2020)
Purpose: Previous studies have documented that cumulus granulosa cells (GCs) can trans-differentiation into different non-ovarian cells, showing their multipotentiality to repopulate the injured cells in ovarian tissue. The current experiment is aimed to assess the differentiation capacity of human cumulus GCs toward the oocyte-like phenotype in vitro. Methods: GCs were isolated from healthy female volunteers subjected to in vitro fertilization or intra-cytoplasmic sperm injection (IVF-ICSI). The effect of different media supplemented with leukemia inhibitory factors (LIFs), 5 ng/mL estradiol, and 0.005 IU/mL follicle-stimulating hormone (FSH) were investigated to the differentiation of GCs toward oocyte-like phenotype via monitoring the expression of Oct3/4 and GATA-4 using flow cytometry analysis. The expression of genes such as FIGLA, NOBOX, and SYCP3 was measured by real-time polymerase chain reaction (PCR) assay. We also assess morphological adaptation by using bright-field microscopic imaging. Results: Exposure of GCs to LIFs increased the number of cells expressing stemness factor Oct3/4 coincided with the suppression of GATA-4 after 7 days (P < 0.05). We found that the transcript level of all genes FIGLA, Nobox, and SYCP-3 decreased in cells after treatment with a FSH (P < 0.05). According to our data, the incubation of GCs with estradiol increased the expression of genes related to the oocyte-like phenotype. Conclusion: Our finding revealed that the combination of LIFs and estradiol could induce the GCs' oogenesis capacity and thereby is possibly suggested as a therapeutic strategy during the occurrence of gynecological disorders.
Keyphrases
- induced apoptosis
- cell cycle arrest
- poor prognosis
- stem cells
- cell death
- flow cytometry
- acute myeloid leukemia
- signaling pathway
- machine learning
- transcription factor
- gene expression
- bone marrow
- endoplasmic reticulum stress
- type diabetes
- cell proliferation
- adipose tissue
- oxidative stress
- artificial intelligence
- deep learning
- atomic force microscopy
- drug induced
- rna seq
- pregnancy outcomes
- single molecule
- high speed