Expression and Tumor-Promoting Effect of Tyrosine Phosphatase Receptor Type N (PTPRN) in Human Glioma

Protein Tyrosine Phosphatase Receptors N and N2 Control Pituitary Melanotroph Development and POMC Expression

The neuroendocrine marker genes Ptprn and Ptprn2 encode protein tyrosine phosphatase receptors N and N2, 2 members of protein tyrosine phosphatase receptors void of enzymatic activity, and whose function and mechanism of action have not been elucidated. To explore the role(s) of Ptprn and Ptprn2 on the hypothalamic-pituitary-adrenal axis, we used mice in which both genes were knocked out (DKO). The focus in this study was on corticotrophs and melanotrophs from the anterior and intermediate lobes of the pituitary gland, respectively. In both sexes, DKO caused an increase in the expression of the corticotroph/melanotroph genes Pomc and Tbx19 and the melanotroph-specific gene Pax7. We also found in vivo and in vitro increased synthesis and release of beta-endorphin, alpha-melanocyte-stimulating hormone, and ACTH in DKO mice, which was associated with increased serum corticosterone levels and adrenal mass. DKO also increased the expression of other melanotroph-specific genes, but not corticotroph-specific genes. The dopaminergic pathway in the hypothalamus and dopaminergic receptors in melanotrophs were not affected in DKO mice. However, hyperplasia of the intermediate lobe was observed in DKO females and males, accompanied by increased proopiomelanocortin immunoreactivity per cell. These results indicate that protein tyrosine phosphatase receptor type N contributes to hypothalamic-pituitary-adrenal function by being involved in processes governing postnatal melanotroph development and Pomc expression.

NREP, transcriptionally upregulated by HIF-1α, aggravates breast cancer cell growth and metastasis by promoting glycolysis

Breast cancer (BC) poses a great threat to women's health. Neuronal regeneration related protein (NREP) is a multifunctional protein that is involved in embryonic development, regeneration, and human disease. However, the biological function of NREP in tumors is rarely reported and its role in BC remains unknown. Bioinformatics analysis showed that NREP is highly expressed and closely correlated with poor survival in BC patients. Under hypoxic conditions, NREP was upregulated in BC cells, and this promotion was reversed by hypoxia-inducible factor HIF-1α suppression. Luciferase reporter system and chromatin immunoprecipitation assays confirmed that HIF-1α directly binds to the promoter of NREP to increase the transcriptional activity of NREP. NREP suppression inhibited cell proliferation, arrested the cell cycle at the G1/S phase, and promoted apoptosis and caspase-3 activity in BC cells. Suppression of NREP decreased the tube formation ability of HUVECs. In addition, NREP downregulation showed an inhibition effect on cell migration, invasion, and EMT of BC cells. In NREP overexpressed cells, all these changes were reversed. In vivo, animal experiments also confirmed that NREP promotes BC tumor growth and metastasis. In addition, NREP promoted cellular glycolysis and enhanced the levels of glucose consumption, ATP, lactate production, and glucose transporters expression in NREP-overexpressed BC cells. In summary, our results demonstrated that NREP could be transcriptional activated by HIF-1α, which may aggravate BC tumor growth and metastasis by promoting cellular glycolysis. This result suggested that NREP may play an essential part in BC progression.

Development and validation of an inflammatory response-related prognostic model and immune infiltration analysis in glioblastoma

Background

Despite receiving standard treatment, the prognosis of glioblastoma (GBM) patients is still poor. Considering the heterogeneity of each patient, it is imperative to identify reliable risk model that can effectively predict the prognosis of each GBM patient to guide the personalized treatment.

Methods

Transcriptomic gene expression profiles and corresponding clinical data of GBM patients were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Inflammatory response-related genes were extracted from Gene Set Enrichment Analysis (GSEA) website. Univariate Cox regression analysis was used for prognosis-related inflammatory genes (P<0.05). A polygenic prognostic risk model was constructed using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Validation was performed through CGGA cohort. Overall survival (OS) was compared by Kaplan-Meier analysis. A nomogram was plotted to accurately predict the prognosis for each patient. GSEA was used for the pathway enrichment analysis. The single sample GSEA (ssGSEA) algorithm was implemented to conduct the immune infiltration analysis. The potential role of oncostatin M receptor (OSMR) in GBM was investigated through the in vitro experiment.

Results

A prognostic risk model consisting of 4 genes (PTPRN, OSMR, MYD88, and EFEMP2) was developed. GBM patients in the high-risk group had worse OS. The time-dependent ROC curves showed an area under the curve (AUC) of 0.782, 0.765, and 0.784 for 1-, 2-, and 3-year survival in TCGA cohort, while the AUC in the CGGA cohort was 0.589, 0.684, and 0.785 at 1, 2, and 3 years, respectively. The risk score, primary-recurrent-secondary (PRS) type, and isocitrate dehydrogenase (IDH) mutation could predict the prognosis of GBM patients well. The nomogram accurately predicted the 1-, 2-, and 3-year OS for each patient. Immune cell infiltration was associated with the risk score and the model could predict immunotherapy responsiveness. The expression of the prognostic gene was correlated with the sensitivity to antitumor drugs. Interference of OSMR inhibited proliferation and migration and promoted apoptosis of GBM cells.

Conclusions

The prognostic model based on 4 inflammatory response-related genes had reliable predictive power to effectively predict clinical outcome in GBM patients and provided the guide for the personalized treatment.

Common and female-specific roles of protein tyrosine phosphatase receptors N and N2 in mice reproduction

Simultaneous knockout of the neuroendocrine marker genes Ptprn and Ptprn2, which encode the protein tyrosine phosphatase receptors N and N2, causes infertility in female mice while males are fertile. To elucidate the mechanism of the sex-specific roles of Ptprn and Ptprn2 in mouse reproduction, we analyzed the effects of their double knockout (DKO) on the hypothalamic-pituitary-gonadal axis. In DKO females, delayed puberty and lack of ovulation were observed, complemented by changes in ovarian gene expression and steroidogenesis. In contrast, testicular gene expression, steroidogenesis, and reproductive organs development were not significantly affected in DKO males. However, in both sexes, pituitary luteinizing hormone (LH) beta gene expression and LH levels were reduced, as well as follicle-stimulating hormone beta gene and gonadotropin-releasing hormone (GnRH) gene, while the calcium-mobilizing and LH secretory actions of GnRH were preserved. Hypothalamic Gnrh1 and Kiss1 gene expression was also reduced in DKO females and males. In parallel, a significant decrease in the density of immunoreactive GnRH and kisspeptin fibers was detected in the hypothalamic arcuate nucleus of DKO females and males. The female-specific kisspeptin immunoreactivity in the rostral periventricular region of the third ventricle was also reduced in DKO females, but not in DKO males. These data indicate a critical role of Ptprn and Ptprn2 in kisspeptin-GnRH neuronal function and sexual dimorphism in the threshold levels of GnRH required to preserve reproductive functions.

Construction and validation of a cuproptosis-related prognostic model for glioblastoma

Background

Cuproptosis, a newly reported type of programmed cell death, takes part in the regulation of tumor progression, treatment response, and prognosis. But the specific effect of cuproptosis-related genes (CRGs) on glioblastoma (GBM) is still unclear.

Methods

The transcriptome data and corresponding clinical data of GBM samples were downloaded from the TCGA and GEO databases. R software and R packages were used to perform statistical analysis, consensus cluster analysis, survival analysis, Cox regression analysis, Lasso regression analysis, and tumor microenvironment analysis. The mRNA and protein expression levels of model-related genes were detected by RT-qPCR and Western blot assays, respectively.

Results

The expression profile of CRGs in 209 GBM samples from two separate datasets was obtained. Two cuproptosis subtypes, CRGcluster A and CRGcluster B, were identified by consensus cluster analysis. There were apparent differences in prognosis, tumor microenvironment, and immune checkpoint expression levels between the two subtypes, and there were 79 prognostic differentially expressed genes (DEGs). According to the prognostic DEGs, two gene subtypes, geneCluster A and geneCluster B, were identified, and a prognostic risk score model was constructed and validated. This model consists of five prognostic DEGs, including PDIA4, DUSP6, PTPRN, PILRB, and CBLN1. Ultimately, to improve the applicability of the model, a nomogram was established. Patients with GBM in the low-risk cluster have a higher mutation burden and predict a longer OS than in the high-risk group. Moreover, the risk score was related to drug sensitivity and negatively correlated with the CSC index.

Conclusion

We successfully constructed a cuproptosis-related prognostic model, which can independently predict the prognosis of GBM patients. These results further complement the understanding of cuproptosis and provide new theoretical support for developing a more effective treatment strategy.

PTPRN Serves as a Prognostic Biomarker and Correlated with Immune Infiltrates in Low Grade Glioma

BACKGROUND

Glioma is one of the most common malignant tumors of the central nervous system. Immune infiltration of tumor microenvironment was associated with overall survival in low grade glioma (LGG). However, effects of Tyrosine phosphatase receptor type N (PTPRN) on the progress of LGG and its correlation with tumor infiltration are unclear.

METHODS

Here, datasets of LGG were from The Cancer Genome Atlas (TCGA) and normal samples were from GTEx dataset. Gepia website and Human Protein Atlas (HPA) Database were used to analyze the mRNA and protein expression of PTPRN. We evaluated the influence of PTPRN on survival of LGG patients. MethSurv was used to explore the expression and prognostic patterns of single CpG methylation of PTPRN gene in LGG. The correlations between the clinical information and PTPRN expression were analyzed using logistic regression and Multivariate Cox regression. We also explored the correlation between PTPRN expression and cancer immune infiltration by TIMER. Gene set enrichment analysis (GSEA) was formed using TCGA RNA-seq datasets.

RESULTS

PTPRN mRNA and protein expression decreased in LGG compared to normal brain tissue in TCGA and HPA database. Kaplan-Meier analysis showed that the high expression level of PTPRN correlated with a good overall survival (OS) of patients with LGG. The Multivariate Cox analysis demonstrated that PTPRN expression and other clinical-pathological factors (age, WHO grade, IDH status, and primary therapy outcome) significantly correlated with OS of LGG patients. The DNA methylation pattern of PTPRN with significant prognostic value were confirmed, including cg00672332, cg06971096, cg01382864, cg03970036, cg10140638, cg16166796, cg03545227, and cg25569248. Interestingly, PTPRN expression level significantly negatively correlated with infiltrating level of B cell, CD4+ T cells, Macrophages, Neutrophils, and DCs in LGG. Finally, GSEA showed that signaling pathways, mainly associated with tumor microenvironment and immune cells, were significantly enriched in PTPRN high expression.

CONCLUSION

PTPRN is a potential biomarker and correlates with tumor immune infiltration in LGG.