NPR3, transcriptionally regulated by POU2F1, inhibits osteosarcoma cell growth through blocking the PI3K/AKT pathway

Li, Shuo; Guo, Ruirong; Peng, Zhibin; Quan, Bingxuan; Hu, Yu; Wang, Yiwen; Wang, Yansong

doi:10.1016/j.cellsig.2021.110074

Cited by 13 publications

(14 citation statements)

References 25 publications

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“…NLGN4Y, a type I membrane protein that belonging to the family of neuroligins, was highly expressed in lung adenocarcinoma patients with poor survival (45). NPR3 (natriuretic peptide receptor 3), could inhibit cancer cells growth in osteosarcoma via blocking the PI3K/AKT pathway (46). CPA3 (carboxypeptidase A3), was demonstrated to be involved in the histone hyperacetylation signaling pathway activated during differentiation of prostate epithelial cancer cells (47).…”

Section: Discussionmentioning

confidence: 99%

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Ma¹,

Li²,

Liu³

et al. 2021

Pathol. Oncol. Res.

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Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4+ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

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Section: Discussionmentioning

confidence: 99%

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Ma¹,

Li²,

Liu³

et al. 2021

Pathol. Oncol. Res.

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“…In osteosarcoma, NPR3 acts as a tumor suppressor. In BC, NP3R can be used as a prognostic marker ( 28 ). Moreover, ANO6 is involved in the pathogenesis of many diseases, such as cancer, hemorrhagic disease, and bone dysplasia ( 29 ).…”

Section: Discussionmentioning

confidence: 99%

Development of a Novel Immune-Related Gene Prognostic Index for Breast Cancer

et al. 2022

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ObjectiveTo construct an immune-related gene prognostic index (IRGPI) for breast cancer (BC) and investigate its prognostic specificity and the molecular and immune characteristics.MethodsBC hub genes were identified from The Cancer Genome Atlas and immune-related databases using weighted gene co-expression network analysis (WGCNA). IRGPI was constructed using univariate, LASSO, and multivariate regression analyses, and was validated with GSE58812 and GSE97342 in the Gene Expression Omnibus database (GEO). At the same time, we evaluated the predictive ability of IRGPI for different BC subtypes. Subsequently, the molecular and immune characteristics, clinical relevance, and benefits of immune checkpoint inhibitor treatment were analyzed for different IRGPI subgroups.ResultsIRGPI consisted of six genes: SOCS3, TCF7L2, TSLP NPR3, ANO6, and HMGB3. The IRGPI 1-, 5-, and 10-years area under curve (AUC) values were 0.635, 0.752, and 0.753, respectively, indicating that IRGPI has good potential in predicting the long-term survival of BC patients, consistent with the results in the GEO cohort. IRGPI showed good predictive power in four different breast cancer subtypes: ER positive, PR positive, HER2 positive and triple-negative (P<0.01). Compared with the low-IRGPI group, the high-IRGPI group had a worse prognosis and a lower degree of immune infiltrating cells (p < 0.05). IRGPI showed specificity in distinguishing age, TNM stage, ER, and HER2 statuses, and our study found that the high-IRGPI group had low tumor immune dysfunction and exclusion (TIDE), microsatellite instability (MSI), and T cell dysfunction scores (p < 0.05). In addition, compared with the TIDE and TIS models, showed that the AUCs of IRGPI were better during the 5-year follow-up.ConclusionIRGPI can be used as an independent prognostic indicator of breast cancer, providing a method for monitoring the long-term treatment of BC.

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Section: Discussionmentioning

confidence: 99%

“…Moreover, previous study also showed that it played an important role in modulating intravascular volume and vascular tone and could protect cardiomyocytes from apoptosis. Thus, NPR3 might be a viable therapeutic target to decrease cancer and cardiovascular diseases risk in OSA patients ( Lin et al, 2016 ; Li et al, 2021 ). PDIA was reported to be able to intercept the endoplasmic reticulum stress-related apoptotic cellular death and its expression is significantly up-regulated in response to cellular stress ( Mahmood et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea

Liu

Hao²,

Li³

et al. 2022

Front. Genet.

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Background: The molecular mechanisms underlying obstructive sleep apnea (OSA) and its comorbidities may involve mitochondrial dysfunction. However, very little is known about the relationships between mitochondrial dysfunction-related genes and OSA.Methods: Mitochondrial dysfunction-related differentially expressed genes (DEGs) between OSA and control adipose tissue samples were identified using data from the Gene Expression Omnibus database and information on mitochondrial dysfunction-related genes from the GeneCards database. A mitochondrial dysfunction-related signature of diagnostic model was established using least absolute shrinkage and selection operator Cox regression and then verified. Additionally, consensus clustering algorithms were used to conduct an unsupervised cluster analysis. A protein–protein interaction network of the DEGs between the mitochondrial dysfunction-related clusters was constructed using STRING database and the hub genes were identified. Functional analyses, including Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA), were conducted to explore the mechanisms involved in mitochondrial dysfunction in OSA. Immune cell infiltration analyses were conducted using CIBERSORT and single-sample GSEA (ssGSEA).Results: we established mitochondrial dysfunction related four-gene signature of diagnostic model consisted of NPR3, PDIA3, SLPI, ERAP2, and which could easily distinguish between OSA patients and controls. In addition, based on mitochondrial dysfunction-related gene expression, we identified two clusters among all the samples and three clusters among the OSA samples. A total of 10 hub genes were selected from the PPI network of DEGs between the two mitochondrial dysfunction-related clusters. There were correlations between the 10 hub genes and the 4 diagnostic genes. Enrichment analyses suggested that autophagy, inflammation pathways, and immune pathways are crucial in mitochondrial dysfunction in OSA. Plasma cells and M0 and M1 macrophages were significantly different between the OSA and control samples, while several immune cell types, especially T cells (γ/δ T cells, natural killer T cells, regulatory T cells, and type 17 T helper cells), were significantly different among mitochondrial dysfunction-related clusters of OSA samples.Conclusion: A novel mitochondrial dysfunction-related four-gen signature of diagnostic model was built. The genes are potential biomarkers for OSA and may play important roles in the development of OSA complications.

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NPR3, transcriptionally regulated by POU2F1, inhibits osteosarcoma cell growth through blocking the PI3K/AKT pathway

Cited by 13 publications

References 25 publications

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Development of a Novel Immune-Related Gene Prognostic Index for Breast Cancer

Construction of a mitochondrial dysfunction related signature of diagnosed model to obstructive sleep apnea

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