The G-Protein Coupled Estrogen Receptor (GPER/GPR30) in ovarian granulosa cell tumors

Heublein, Sabine; Ebinger, K; Mayr, Doris; Friese, Klaus; Jeschke, Udo; Lenhard, Miriam

doi:10.1055/s-0034-1388389

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…4A-C). These findings were consistent with previous research on the role of endocrine GPCRs in OV (19), showing that GPCRs are involved in many aspects of tumorigenesis, including the promotion of aberrant growth, increased cell viability, angiogenesis and metastasis (20,21). In addition, results from Fig.…”

Section: Resultssupporting

confidence: 93%

A prognosis‑predictive nomogram of ovarian cancer with two immune‑related genes: CDC20B and PNPLA5

et al. 2020

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Ovarian carcinoma (OV) is one of the most lethal gynecological malignancies globally, and the overall 5-year survival rate of OV was 47% in 2018 according to American data. To increase the survival rate of patients with OV, many researchers have sought to identify biomarkers that act as both prognosis-predictive markers and therapy targets. However, most of these have not been suitable for clinical application. The present study aimed at constructing a predictive prognostic nomogram of OV using the genes identified by combining The Cancer Genome Atlas (TCGA) dataset for OV with the immune score calculated by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Firstly, the algorithm was used to calculate the immune score of patients with OV in the TCGA-OV dataset. Secondly, differentially expressed genes (DEGs) between low and high immune score tissues were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was performed to predict the functions of these DEGs. Thirdly, univariate, multivariate and Lasso Cox's regression analyses were carried out step by step, and six prognosis-related DEGs were identified. Then, Kaplan-Myer survival curves were generated for these genes and validated by comparing their expression levels to further narrow the range of DEGs and to calculate the risk score. Two genes were identified, cell division cycle 20B and patatin-like phospholipase domain containing 5, which were both shown to have higher expression levels in OV tissues and to be significantly associated with the prognosis of OV. Next, a nomogram was created using these two genes and age, and using the receiver operating characteristic (ROC) curve and calibration curve, the effectiveness of the nomogram was validated. Finally, an external validation was conducted for this nomogram. The ROC showed that the areas under the curve (AUCs) of the 3-and 5-year overall survival predictions for the nomogram were 0.678 and 0.62, respectively. Moreover, the ROC of the external validation model showed that the AUCs of the 3-and 5-year were 0.699 and 0.643, respectively, demonstrating the effectiveness of the generated nomogram. In conclusion, the present study has identified two immune-related genes as biomarkers that reliably predict overall survival in OV. These biomarkers might also be potential molecular targets of immune therapy to treat patients with OV.

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Section: Resultssupporting

confidence: 93%

A prognosis‑predictive nomogram of ovarian cancer with two immune‑related genes: CDC20B and PNPLA5

et al. 2020

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“…0.7 and 0.2% of the housekeeping gene expression, respectively, detected by ddPCR), while relatively high LHCGR gene expression levels (34% of RPS7 gene expression) were found by both qPCR and ddPCR (table 2; supplementary table S1; supplementary table S2). These genes are expressed at different levels in cultured hGLC (Myers et al, 2008), as well as in ovarian tissues (Heublein et al, 2014;Jeppesen et al, 2012), ovarian cancer cells (Heublein et al, 2013) and granulosa cell lines (Casarini et al, 2016a;Sasson et al, 2003). LHCGR transcripts per cell are about 50-fold higher than FSHR transcripts, which, in turn, are about 3.4-fold higher than the very poorly expressed GPER transcripts.…”

Section: Discussionmentioning

confidence: 99%

Comparison of real-time quantitative Polymerase Chain Reaction (PCR) and digital droplet PCR for quantification of hormone membrane receptorFSHR, GPERandLHCGRtranscripts in human primary granulosa lutein cells

Sperduti

Anzivino

Villani³

et al. 2020

Preprint

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Background: Quantitative real time polymerase chain reaction (qPCR) and droplet digital PCR (ddPCR) are methods used for gene expression analysis in several contexts, including reproductive endocrinology.Objectives: Herein, we compared qPCR and ddPCR technologies for gene expression analysis of hormone membrane receptor-encoding genes, such as follicle-stimulating hormone (FSHR), G protein-coupled estrogen (GPER) and choriogonadotropin receptors (LHCGR), as well as the commonly used RPS7 housekeeping gene, in order to identify the most reliable method to be applied for gene expression analysis in the context of human reproduction. Methods.Total RNA was extracted from human primary granulosa cells of donor patients undergoing assisted reproduction and used for gene expression analysis by qPCR and ddPCR, after finding the optimal annealing temperature.Results: Both techniques provided results reflecting the low number of FSHR and GPER transcripts, although ddPCR detected also unspecific transcripts in using RPS7 primers and quantified the low-expressed genes with major accuracy, thanks to its higher reaction efficiency. The absolute FSHR and GPER transcript number was also determined by ddPCR, resulting in 50-to 170-fold lower amount than LHCGR transcripts. Conclusion:These results suggest that ddPCR is the candidate technology for analysis of genes with relatively low expression levels and provides useful insights for characterizing hormone receptor expression levels in the context of reproductive endocrinology.

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“…THRa2 in the nucleus showed positive correlation to ERa (cc = 0.247, p = 0.002) and to PRA (cc = 0.219, p = 0.007). In addition to the classical estrogen receptors, also the GPER [27][28][29] showed positive correlation to THRa staining in the nucleus (cc = 0.219, p = 0.007) and to THRa2 in the nucleus (cc = 0.252, p = 0.002).…”

Section: Correlation Analysesmentioning

confidence: 93%

THR alpha and its subtypes alpha1 and alpha2 are prognostic markers for survival of ovarian cancer patients

Ditsch¹,

Heublein²,

Jeschke³

et al. 2019

Preprint

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Background Ovarian cancer is most lethal in comparison to all other gynecological cancer cases. Within this study, we aimed to investigate the expression of the thyroid hormone receptor alpha and its influence on patient survival in ovarian cancer (OvCa). Methods The presence of the thyroid hormone receptors THRα, THRα1 and -2 were investigated in 156 ovarian cancer samples using immunohistochemistry (IHC) using semi-quantitative immunoreactivity (IR) scores and correlated to clinical, pathological data, subtype of ovarian cancer, clinical data, staining of 20 already described OvCa marker proteins and overall survival (OS). Results Patients with clear cell OvCa showed the highest THRα expression and nuclear THRα expression is associated with reduced survival in this group. In contrast, nuclear expressed THRα1 is a positive prognosticator for all OvCa patients. Nuclear THRα2 is a positive prognosticator for OvCa patients of the serous subtype. Cytoplasmic expression of THRα2 accompanies with reduced OS in all OvCa patients, whereas cytoplasmic expression of THRα1 is associated with reduced OS in mucinous OvCa patients only. In addition, THRα expression correlates to gonadotropin receptors, steroid hormone receptors, TA-MUC1 and glycodelin. Conclusion Thyroid hormones promote ovarian cancer cell proliferation. The further investigation of thyroid hormones and its specific receptors offer the possibility to investigate new endocrine targets against ovarian cancer.

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The G-Protein Coupled Estrogen Receptor (GPER/GPR30) in ovarian granulosa cell tumors

Cited by 3 publications

References 14 publications

A prognosis‑predictive nomogram of ovarian cancer with two immune‑related genes: <em>CDC20B</em> and <em>PNPLA5</em>

A prognosis‑predictive nomogram of ovarian cancer with two immune‑related genes: <em>CDC20B</em> and <em>PNPLA5</em>

Comparison of real-time quantitative Polymerase Chain Reaction (PCR) and digital droplet PCR for quantification of hormone membrane receptorFSHR, GPERandLHCGRtranscripts in human primary granulosa lutein cells

THR alpha and its subtypes alpha1 and alpha2 are prognostic markers for survival of ovarian cancer patients

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