ZPR1

Last update 08 May 2025

Basic Info

Synonyms

Zinc finger protein 259, Zinc finger protein ZPR1, ZNF259

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Introduction

Acts as a signaling molecule that communicates proliferative growth signals from the cytoplasm to the nucleus. It is involved in the positive regulation of cell cycle progression (PubMed:29851065). Plays a role for the localization and accumulation of the survival motor neuron protein SMN1 in sub-nuclear bodies, including gems and Cajal bodies. Induces neuron differentiation and stimulates axonal growth and formation of growth cone in spinal cord motor neurons. Plays a role in the splicing of cellular pre-mRNAs. May be involved in H(2)O(2)-induced neuronal cell death.

100 Clinical Results associated with ZPR1

100 Translational Medicine associated with ZPR1

0 Patents (Medical) associated with ZPR1

136

Literatures (Medical) associated with ZPR1

01 May 2025·Veterinary Microbiology

ZCCHC3 inhibits PEDV proliferation by degrading nuclear coat proteins via the proteasome pathway

Article

Author: Wang, Jun ; Wang, Shuangyang ; Shen, Haixiao ; Li, Liang ; Lin, Haichen ; Bo, Zongyi ; Sun, Huihui ; Zhang, Zuyao ; Sun, Pei ; Li, Yangfan ; Li, Jie ; Bi, Ruimin ; Wang, Xuan

Porcine epidemic diarrhea virus (PEDV) infection in pigs is characterized by vomiting, dehydration, and diarrhoea. The structural proteins of PEDV play crucial roles in viral entry, release, assembly, outgrowth, and host immune regulation. Similar to other viruses, PEDV primarily relies on host cellular mechanisms for productive infection. However, the host factors associated with PEDV infection remain undefined. Therefore, an in-depth understanding of the pathogenic mechanisms of PEDV is essential for comprehending this disease. Zinc-containing finger CCHC-type protein 3 (ZCCHC3) is an antiviral factor known to interact with RIG-I and cGAS, inhibiting the replication of pseudorabies virus (PRV). In this study, we investigated the role of porcine ZCCHC3 in PEDV proliferation. We first demonstrated that the expression of ZCCHC3 in LLC-PK1 cells is downregulated upon PEDV infection. Overexpression of ZCCHC3 inhibited PEDV replication, whereas knockdown of ZCCHC3 increased viral titer and N protein levels. Further studies revealed that ZCCHC3 interacts and co-localizes with N proteins, and that ZCCHC3-mediated antiviral effects depend on its zinc finger protease activity. Taken together, these findings provide valuable insights into the role of ZCCHC3 in PEDV proliferation and enhance our understanding of host-virus interactions.

01 Oct 2024·Irish Journal of Medical Science (1971 -)

Zinc finger 259 gene polymorphisms in Egyptian patients with metabolic syndrome and its association with dyslipidemia

Article

Author: Amr, Khaleda Sayed ; Refeat, Miral ; Zaki, Moushira Erfan ; Ellakwa, Doha El-Sayed ; Banksle, Hala Mohamed

BACKGROUNDZinc finger protein 1 (ZPR1), encoded by the ZNF259 gene, plays crucial roles in transcriptional regulation and cell cycle progression. Despite its known functions, its specific involvement in Metabolic Syndrome (MetS) remains debated. Genome-wide association studies have identified several genes, including ZNF259, implicated in lipid metabolism and associated with MetS. Single nucleotide polymorphisms (SNPs) in ZNF259 have been linked to altered lipid metabolism during the development of MetS. This study aims to investigate the association between MetS in Egyptian patients and three specific ZNF259 SNPs: rs964184, rs2075294, and rs2075290. The objective is to explore how these SNPs correlate with MetS development, other health outcomes, and their interaction with dyslipidemia biomarkers.METHODS200 Egyptian participants were enrolled, and divided into two groups: 100 patients diagnosed with dyslipidemia and 100 healthy controls. The study involved comprehensive assessments, including lipid profile analysis, anthropometric measurements, and genotyping of rs964184, rs2075290, and rs2075294 in the ZNF259 gene using Real-Time Polymerase Chain Reaction (PCR).RESULTSThe findings indicate that rs964184 SNP correlates significantly with elevated plasma triacylglycerol (TG) levels, while rs2075290 and rs2075294 are associated with higher total serum cholesterol (TC) and TG levels. Among these SNPs, rs2075294 showed the highest predictive value (area under the curve of 0.748), followed by rs2075290 (0.738), and rs964184 (0.583), suggesting rs2075294 as the most influential SNP in MetS prediction.CONCLUSIONThis study underscores the predictive role of ZNF259 SNPs in MetS risk among Egyptians. Future research should further explore the implications of ZNF259 in MetS pathogenesis and its potential as a biomarker for personalized health interventions.

21 Sep 2024·British Journal of Cancer

ESCCPred: a machine learning model for diagnostic prediction of early esophageal squamous cell carcinoma using autoantibody profiles

Article

Author: Li, Tiandong ; Ye, Hua ; Shi, Jianxiang ; Shen, Yajing ; Sun, Guiying ; Zou, Yuanlin ; Wang, Keyan ; Song, Caijuan ; Dai, Liping ; Fang, Zhaoyang ; Cheng, Yifan ; Wang, Peng

BACKGROUNDEsophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically ideal biomarkers for early diagnosis. The objective of this study was to develop and validate a user-friendly diagnostic tool for early ESCC detection.METHODSThe study encompassed three phases: discovery, verification, and validation, comprising a total of 1309 individuals. Serum autoantibodies were profiled using the HuProt^TM human proteome microarray, and autoantibody levels were measured using the enzyme-linked immunosorbent assay (ELISA). Twelve machine learning algorithms were employed to construct diagnostic models, and evaluated using the area under the receiver operating characteristic curve (AUC). The model application was facilitated through R Shiny, providing a graphical interface.RESULTSThirteen autoantibodies targeting TAAs (CAST, FAM131A, GABPA, HDAC1, HDGFL1, HSF1, ISM2, PTMS, RNF219, SMARCE1, SNAP25, SRPK2, and ZPR1) were identified in the discovery phase. Subsequent verification and validation phases identified five TAAbs (anti-CAST, anti-HDAC1, anti-HSF1, anti-PTMS, and anti-ZPR1) that exhibited significant differences between ESCC and control subjects (P < 0.05). The support vector machine (SVM) model demonstrated robust performance, with AUCs of 0.86 (95% CI: 0.82-0.89) in the training set and 0.83 (95% CI: 0.78-0.88) in the test set. For early-stage ESCC, the SVM model achieved AUCs of 0.83 (95% CI: 0.79-0.88) in the training set and 0.83 (95% CI: 0.77-0.90) in the test set. Notably, promising results were observed for high-grade intraepithelial neoplasia, with an AUC of 0.87 (95% CI: 0.77-0.98). The web-based implementation of the early ESCC diagnostic tool is publicly accessible at https://litdong.shinyapps.io/ESCCPred/ .CONCLUSIONThis study provides a promising and easy-to-use diagnostic prediction model for early ESCC detection. It holds promise for improving early detection strategies and has potential implications for public health.

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ZPR1

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