HCN4

更新于：2025-05-07

基本信息

别名

HCN4、hyperpolarization activated cyclic nucleotide gated potassium channel 4、hyperpolarization activated cyclic nucleotide-gated potassium channel 4

+ [1]

简介

Hyperpolarization-activated ion channel that are permeable to Na(+) and K(+) ions with very slow activation and inactivation (PubMed:10228147, PubMed:10430953, PubMed:20829353). Exhibits higher selectivity for K(+) over Na(+) ions (PubMed:10228147). Contributes to the native pacemaker currents in heart (If) that regulate the rhythm of heart beat (Probable) (PubMed:10228147, PubMed:16407510, PubMed:19165230). Contributes to the native pacemaker currents in neurons (Ih) (Probable). May mediate responses to sour stimuli (By similarity).

关联

100 项与 HCN4 相关的临床结果

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100 项与 HCN4 相关的转化医学

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0 项与 HCN4 相关的专利（医药）

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757

项与 HCN4 相关的文献（医药）

2025-08-01·Tissue and Cell

MiR-1 alleviates chronic heart failure through HCN2/HCN4 axis in vitro

Article

作者: Zeng, Jun ; Gu, Wanjie ; Yin, Haiyan ; Pan, Zhe ; Luo, Yishan

OBJECTIVEChronic heart failure (CHF) is a complex and progressive condition. This study aimed to investigate the potential regulatory effect of miR-1 on CHF through the hyperpolarization-activated cyclic nucleotide-gated channels 2 and 4 (HCN2/HCN4) axis.METHODThe expression of miR-1 was examined in individuals diagnosed with CHF. The patients' level of NT-proBNP was evaluated. A cellular model using H9c2 cells subjected to oxygen-glucose deprivation/reoxygenation (OGD/R) was established. RT-qPCR and western blot were performed to determine the levels of miR-1, HCN2, or HCN4. Elisa was used to measure the levels of TNF-α and IL-6. The potential target of miR-1 on HCN2 and HCN4 was verified using the dual luciferase assay. Overexpression of miR-1 or HCN was employed to explore the specific mechanism of miR-1 and HCN on CHF. The MTT assay was used to evaluate cell viability, while apoptosis was quantified through flow cytometry.RESULTSIn both patients with CHF and OGD/R-treated H9c2 cells, miR-1 levels were found to be reduced. The overexpression of miR-1 notably suppressed the secretion of TNF-α and IL-6 (P < 0.05). Overexpression of miR-1 also markedly increased cell viability (P < 0.01) and reduced apoptosis (P < 0.05) in OGD/R-treated H9c2 cells. Using miRNA-target prediction databases and luciferase reporter assays, we identified HCN2 and HCN4 as direct targets of miR-1. Moreover, overexpression of HCN2 and HCN4 counteracted the protective effects of miR-1, as evidenced by a significant reduction in cell viability (P < 0.01) and an increase in apoptosis (P < 0.05).CONCLUSIONThis study suggests that miR-1 regulates cell viability and apoptosis in CHF through the HCN2/HCN4 axis, highlighting its potential as a therapeutic target for CHF.

2025-04-01·American Journal of Physiology-Heart and Circulatory Physiology

Tissue elasticity modulates cardiac pacemaker cell automaticity

Article

作者: Fan, Jinqi ; Choi, Young Hwan ; Ramirez, Rafael J ; Cho, Hee Cheol ; Leng, Jing

The major achievement of this work is development of a robust and straightforward approach to model cardiac conduction system cells with a range of cardiac tissue elasticity with a goal to understand the impact of tissue stiffness on cardiac pacing. Our data provide a framework for further investigation of the heart rhythm in health and disease in the context of fibrosis.

2025-04-01·International Journal of Biological Macromolecules

A comprehensive multi-omics study reveals potential prognostic and diagnostic biomarkers for colorectal cancer

Article

作者: Dash, Tirtharaj ; Sarkar, Angshuman ; Mahajan, Mohita ; Mondal, Sukanta ; Dhabalia, Subodh

BACKGROUND AND OBJECTIVEColorectal cancer (CRC) is a complex disease with diverse genetic alterations and causes 10 % of cancer-related deaths worldwide. Understanding its molecular mechanisms is essential for identifying potential biomarkers and therapeutic targets for its effective management.METHODSWe integrated copy number alterations (CNA) and mutation data via their differentially expressed genes termed as candidate genes (CGs) computed using bioinformatics approaches. Then, using the CGs, we perform Weighted correlation network analysis (WGCNA) and utilise several hazard models such as Univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO) Cox and multivariate Cox to identify the key genes involved in CRC progression. We used different machine-learning models to demonstrate the discriminative power of selected hub genes among normal and CRC (early and late-stage) samples.RESULTSThe integration of CNA with mRNA expression identified over 3000 CGs, including CRC-specific driver genes like MYC and APC. In addition, pathway analysis revealed that the CGs are mainly enriched in endocytosis, cell cycle, wnt signalling and mTOR signalling pathways. Hazard models identified four key genes, CASP2, HCN4, LRRC69 and SRD5A1, that were significantly associated with CRC progression and predicted the 1-year, 3-years, and 5-years survival times. WGCNA identified seven hub genes: DSCC1, ETV4, KIAA1549, NOP56, RRS1, TEAD4 and ANKRD13B, which exhibited strong predictive performance in distinguishing normal from CRC (early and late-stage) samples.CONCLUSIONSIntegrating regulatory information with gene expression improved early versus late-stage prediction. The identified potential prognostic and diagnostic biomarkers in this study may guide us in developing effective therapeutic strategies for CRC management.

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