更新于：2024-09-19

CHRNA9

更新于：2024-09-19

基本信息

别名

acetylcholine receptor, nicotinic, alpha 9 (neuronal)、cholinergic receptor nicotinic alpha 9 subunit、cholinergic receptor, nicotinic alpha 9

+ [7]

简介

Ionotropic receptor with a probable role in the modulation of auditory stimuli. Agonist binding induces a conformation change that leads to the opening of an ion-conducting channel across the plasma membrane (PubMed:11752216, PubMed:25282151). The channel is permeable to a range of divalent cations including calcium, the influx of which may activate a potassium current which hyperpolarizes the cell membrane (PubMed:11752216, PubMed:25282151). In the ear, this may lead to a reduction in basilar membrane motion, altering the activity of auditory nerve fibers and reducing the range of dynamic hearing. This may protect against acoustic trauma. May also regulate keratinocyte adhesion (PubMed:11021840).

关联

项与 CHRNA9 相关的药物

1HA-84

靶点

CHRNA9

作用机制

CHRNA9 agonists

在研机构

Bouvé College of Health Sciences

原研机构

Bouvé College of Health Sciences

在研适应症

慢性疼痛

非在研适应症-

最高研发阶段临床前

首次获批国家/地区-

首次获批日期1800-01-20

GAT-2710

靶点

CHRNA9

作用机制

CHRNA9 agonists

在研机构

Bouvé College of Health Sciences

原研机构

Bouvé College of Health Sciences

在研适应症

慢性疼痛

非在研适应症-

最高研发阶段临床前

首次获批国家/地区-

首次获批日期1800-01-20

1HA-92

靶点

CHRNA9

作用机制

CHRNA9 agonists

在研机构

Bouvé College of Health Sciences

原研机构

Bouvé College of Health Sciences

在研适应症

慢性疼痛

非在研适应症-

最高研发阶段临床前

首次获批国家/地区-

首次获批日期1800-01-20

100 项与 CHRNA9 相关的临床结果

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100 项与 CHRNA9 相关的转化医学

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0 项与 CHRNA9 相关的专利（医药）

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126

项与 CHRNA9 相关的文献（医药）

2024-08-01·Skin Research and Technology

Key genes and immune infiltration patterns and the clinical implications in psoriasis patients

Article

作者: Chen, Yibo ; Zhang, Wenjuan ; Cheng, Wenli ; Zhang, Wenji ; Zhu, Chenyu ; Zhang, Xinyu ; Tan, Luyi ; Li, Min

AbstractBackgroundPsoriasis is an immune‐mediated skin disease, closely related to immune regulation. The aim was to understand the pathogenesis of psoriasis further, reveal potential therapeutic targets, and provide new clues for its diagnosis, treatment, and prevention.Materials and methodsExpression profiling data were obtained from the Gene Expression Omnibus (GEO) database for skin tissues from healthy population and psoriasis patients. Differentially expressed genes (DEGs) were selected for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analysis separately. Machine learning algorithms were used to obtain characteristic genes closely associated with psoriasis. Receiver operating characteristic (ROC) curve was used to assess the diagnostic value of the characteristic genes for psoriasis. The Cell‐type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to calculate the proportion of immune cell infiltration. Correlation analysis was used to characterize the connection between gene expression and immune cell, Psoriasis Area and Severity Index (PASI).ResultsA total of 254 DEGs were identified in the psoriasis group, including 185 upregulated and 69 downregulated genes. GO was mainly enriched in cytokine‐mediated signaling pathway, response to virus, and cytokine activity. KEGG was mainly focused on cytokine‐cytokine receptor interaction and IL‐17 signaling pathway. GSEA was mainly in chemokine signaling pathway and cytokine‐cytokine receptor interaction. The machine learning algorithm screened nine characteristic genes C10orf99, GDA, FCHSD1, C12orf56, S100A7, INA, CHRNA9, IFI44, and CXCL9. In the validation set, the expressions of these nine genes increased in the psoriasis group, and the AUC values were all > 0.9, consistent with those of the training set. The immune infiltration results showed increased proportions of macrophages, T cells, and neutrophils in the psoriasis group. The characteristic genes were positively or negatively correlated to varying degrees with T cells and macrophages. Nine characteristic genes were highly expressed in the moderate to severe psoriasis group and positively correlated with PASI scores.ConclusionHigh levels of nine characteristic genes C10orf99, GDA, FCHSD1, C12orf56, S100A7, INA, CHRNA9, IFI44, and CXCL9 were risk factors for psoriasis, the differential expression of which was related to the regulation of immune system activity and PASI scores, affecting the proportions of different immune cells and promoting the occurrence and development of psoriasis.

2024-02-21·ACS Chemical Neuroscience

New Alpha9 nAChR Ligands Based on a 5-(Quinuclidin-3-ylmethyl)-1,2,4-oxadiazole Scaffold

Article

作者: Kerr, Andrew ; Andleeb, Hina ; Papke, Roger L ; Dallanoce, Clelia ; Richter, Katrin ; Thakur, Ganesh A ; Papotto, Claudio ; Grau, Veronika ; Stokes, Clare

Several lines of evidence have indicated that nicotinic acetylcholine receptors (nAChR) that contain α9 subunits, probably in combination with α10 subunits, may be valuable targets for the management of pain associated with inflammatory diseases through a cholinergic anti-inflammatory system (CAS), which has also been associated with α7 nAChR. Both α7- and α9-containing neuronal nAChR can be pharmacologically distinguished from the high-affinity nicotinic receptors of the brain by their sensitivity to α-bungarotoxin, but in other ways, they have quite distinct pharmacological profiles. The early association of α7 with CAS led to the development of numerous new ligands, variously characterized as α7 agonists, partial agonists, or silent agonists that desensitized α7 receptors without activation. Subsequent reinvestigation of one such family of α7 ligands based on an N,N-diethyl-N'-phenylpiperazine scaffold led to the identification of potent agonists and antagonists for α9. In this paper, we characterize the α9/α10 activity of a series of compounds based on a 5-(quinuclidin-3-ylmethyl)-1,2,4-oxadiazole (QMO) scaffold and identify two new potent ligands of α9, QMO-28, an agonist, and QMO-17, an antagonist. We separated the stereoisomers of these compounds to identify the most potent agonist and discovered that only the 3R isomer of QMO-17 was an α9 antagonist, permitting an in silico model of α9 antagonism to be developed. The α9 activity of these compounds was confirmed to be potentially useful for CAS management of inflammatory pain in cell-based assays of cytokine release.

2024-01-01·Journal of Cancer

CHRNA9 as a New Prognostic Marker and Potential Therapeutic Target in Glioma

Article

作者: Jiang, Yining ; Zhao, Yao ; Ma, Xiaoshan ; Li, Yunqian ; Liu, Yuanhao ; Xu, Wanzhen ; Zhao, Liyan ; Li, Yao ; Geng, Ren

Background: The nicotinic acetylcholine receptor (nAChR) subunit alpha-9 (CHRNA9) is a unique cholinergic receptor, which is involved in tumor proliferation, apoptosis, metastasis and chemotherapy resistance. However, the correlation between the expression level of CHRNA9 in glioma and the clinical features and prognosis of glioma patients has not been clarified. The aim of this study was to verify the expression level of CHRNA9 in glioma and its effect on prognosis by bioinformatics methods. Methods: The RNA-seq data of glioma and normal samples were obtained from the TCGA and GTEx databases. Bioinformatics methods were utilized to analyze the differential expression of CHRNA9 between tumor samples and normal samples. The potential association between CHRNA9 and the clinicopathological features of glioma patients was also investigated. The Kaplan-Meier method and Cox regression were utilized to analyze the relationship between CHRNA9 expression level and survival time and prognostic value of glioma patients. Enrichment analysis was applied to predict gene function and signaling pathways associated with CHRNA9. Experimental verification was performed using tumor tissues and paracancerous tissues from glioma patients. Results: The results of bioinformatics analysis showed that the expression of CHRNA9 was increased in glioma tissues, correlating with poor prognosis and reduced patient survival time. Enrichment analysis suggested that CHRNA9 may interact with the JAK/STAT pathway. CHRNA9 was also found to be abnormally expressed in various other tumors and associated with the expression levels of numerous immune checkpoints in glioma. The findings from the analysis of clinical samples revealed that the expression levels of both mRNA and protein of CHRNA9 in glioma tissues were higher than those in paracancerous tissues. Similarly, the mRNA expression levels of STAT3, IL-6, and TNF-α, which are crucial factors in the STAT3 pathway, were elevated in glioma tissues compared to paracancerous tissues. Conclusion: CHRNA9 is a potential prognostic marker and immunotherapy target for glioma, with its mechanism of action potentially linked to the STAT3 pathway.