St6galnac4-KO 基因敲除小鼠

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产品名称

St6galnac4-KO 基因敲除小鼠

产品编号

S-KO-04316

品系全称

C57BL/6JCya-St6galnac4em1/Cya

品系背景

C57BL/6JCya

品系编号

KOCMP-20448-St6galnac4-B6J-VA

品系状态

使用本品系发表的文献需注明: St6galnac4-KO 基因敲除小鼠 mice (Strain S-KO-04316) were purchased from Cyagen.
交付类型
周龄
性别
基因型
数量

基本信息

基因研究概述

质控标准

基因全称
ST6 (alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase 4
基因别称
SIAT7-D,ST6GalNAcIV,Siat7d
染色体号
Chr 2 (Mouse)
转录本 ID
NCBI: NM_001276425 | Ensembl: ENSMUST00000102818
修饰方式
全身性基因敲除
靶向范围
Exon 2~6
敲除长度
~9.9 kb
品系说明
该品系是基于策略设计时的数据库信息制作而成,建议您在购买前查询最新的数据库和相关文献,以获取最准确的表型信息。
表型提示
MGI:1341894Mice homozygous for a null allele exhibit no abnormal phenotype. Double homozygotes lacking St6galnac3 and St6galnac4 exhibit lymph node hemorrhage associated with structural disruption of high endothelial venule.
ST6GALNAC4,也称为sialyltransferase 6A (alpha-N-acetylneuraminyl-2,3-beta-galactosyl-1,3-N-acetylglucosaminyl) (ST6GalNAc IV) [1],是一种重要的糖基转移酶。ST6GALNAC4主要负责将唾液酸残基转移到含有N-乙酰半乳糖胺(GalNAc)的糖链上,这一过程在细胞表面的糖蛋白和糖脂的修饰中起着关键作用[2]。糖基化是一种重要的蛋白质翻译后修饰,参与调节蛋白质的功能、稳定性和细胞间的相互作用,影响多种生物学过程,包括细胞信号传导、细胞粘附、细胞迁移和免疫反应[3]。

ST6GALNAC4在多种癌症中表现出异常表达,与肿瘤的发生、发展和预后密切相关。例如,在肝细胞癌(HCC)中,ST6GALNAC4的表达水平显著升高,且与患者的预后不良相关[4]。研究发现,ST6GALNAC4的高表达与HCC患者的低生存率相关,且与免疫细胞浸润、肿瘤免疫表型、免疫检查点基因的表达以及多种药物的敏感性有关[5]。此外,ST6GALNAC4的敲低可以显著抑制肿瘤细胞的增殖、迁移和侵袭能力,并影响肝细胞癌细胞上免疫检查点的表达[5]。

ST6GALNAC4还与酒精对肝脏的影响相关。研究发现,在年轻的和年老的小鼠中,ST6GALNAC4的表达水平在酒精处理后发生了改变,且与肝脏的炎症和纤维化相关[6]。这表明ST6GALNAC4可能参与了酒精性肝病的发生和发展。

ST6GALNAC4的表达水平还与COVID-19和疟疾的感染相关。研究发现,ST6GALNAC4在COVID-19感染的患者中表达下调,而在疟疾感染的患者中表达上调[7]。这表明ST6GALNAC4可能参与了这两种感染的免疫反应。

此外,ST6GALNAC4还与甲状腺癌的侵袭性和肿瘤生成相关。研究发现,miR-4299通过直接靶向ST6GALNAC4来调节甲状腺癌的侵袭性和肿瘤生成[8]。

ST6GALNAC4还与其他癌症的预后相关。例如,在子宫体子宫内膜癌(UCEC)中,ST6GALNAC4是Treg细胞相关风险签名(TRRS)的一部分,与患者的预后不良相关[9]。在乳腺癌中,ST6GALNAC4是膜脂质生物合成相关风险模型的一部分,与患者的预后不良相关[10]。

综上所述,ST6GALNAC4是一种重要的糖基转移酶,参与调节蛋白质的糖基化,影响多种生物学过程。ST6GALNAC4在多种癌症中表现出异常表达,与肿瘤的发生、发展和预后密切相关。此外,ST6GALNAC4还与酒精性肝病、COVID-19、疟疾和甲状腺癌的发生和发展相关。ST6GALNAC4的研究有助于深入理解糖基化在癌症和其他疾病中的作用,为疾病的治疗和预防提供新的思路和策略。

参考文献:
1. An, Yahang, Liu, Weifeng, Yang, Yanhui, Chu, Zhijie, Sun, Junjun. 2024. Identification and validation of a novel nine-gene prognostic signature of stem cell characteristic in hepatocellular carcinoma. In Journal of applied genetics, 66, 127-140. doi:10.1007/s13353-024-00850-7. https://pubmed.ncbi.nlm.nih.gov/38441798/
2. Zillich, Lea, Wagner, Josephin, McMahan, Rachel H, Kovacs, Elizabeth J, Lohoff, Falk W. . Multi-omics analysis of alcohol effects on the liver in young and aged mice. In Addiction biology, 28, e13342. doi:10.1111/adb.13342. https://pubmed.ncbi.nlm.nih.gov/38017640/
3. Dai, Tianxing, Li, Jing, Liang, Run-Bin, Lu, Xu, Wang, Guoying. 2023. Identification and Experimental Validation of the Prognostic Significance and Immunological Correlation of Glycosylation-Related Signature and ST6GALNAC4 in Hepatocellular Carcinoma. In Journal of hepatocellular carcinoma, 10, 531-551. doi:10.2147/JHC.S400472. https://pubmed.ncbi.nlm.nih.gov/37034303/
4. Lambert, Nzungize, Kengne-Ouafo, Jonas A, Rissy, Wesonga Makokha, Awe, Olaitan I, Dillman, Allissa. 2022. Transcriptional Profiles Analysis of COVID-19 and Malaria Patients Reveals Potential Biomarkers in Children. In bioRxiv : the preprint server for biology, , . doi:10.1101/2022.06.30.498338. https://pubmed.ncbi.nlm.nih.gov/35794887/
5. Miao, Xiaolong, Jia, Li, Zhou, Huimin, Feng, Xiaobin, Zhao, Yongfu. 2015. miR-4299 mediates the invasive properties and tumorigenicity of human follicular thyroid carcinoma by targeting ST6GALNAC4. In IUBMB life, 68, 136-44. doi:10.1002/iub.1467. https://pubmed.ncbi.nlm.nih.gov/26715099/
6. Liu, Jinhui, Geng, Rui, Yang, Sheng, Cai, Lixin, Bai, Jianling. 2021. Development and Clinical Validation of Novel 8-Gene Prognostic Signature Associated With the Proportion of Regulatory T Cells by Weighted Gene Co-Expression Network Analysis in Uterine Corpus Endometrial Carcinoma. In Frontiers in immunology, 12, 788431. doi:10.3389/fimmu.2021.788431. https://pubmed.ncbi.nlm.nih.gov/34970268/
7. Fan, Wanting, Tang, Jianming, Xu, Huixia, Wu, Donglei, Zhang, Zheng. 2023. Early diagnosis for the onset of peri-implantitis based on artificial neural network. In Open life sciences, 18, 20220691. doi:10.1515/biol-2022-0691. https://pubmed.ncbi.nlm.nih.gov/37671094/
8. Kaur, Kirtan, Lesseur, Corina, Deyssenroth, Maya A, Marsit, Carmen J, Chen, Jia. 2022. PM2.5 exposure during pregnancy is associated with altered placental expression of lipid metabolic genes in a US birth cohort. In Environmental research, 211, 113066. doi:10.1016/j.envres.2022.113066. https://pubmed.ncbi.nlm.nih.gov/35248564/
9. Xu, Yingkun, Jin, Yudi, Gao, Shun, Jiang, Linshan, Liu, Shengchun. 2022. Prognostic Signature and Therapeutic Value Based on Membrane Lipid Biosynthesis-Related Genes in Breast Cancer. In Journal of oncology, 2022, 7204415. doi:10.1155/2022/7204415. https://pubmed.ncbi.nlm.nih.gov/36059802/
10. Dong, Ying, Zhang, Ting, Li, Xining, Yu, Feng, Guo, Yue. 2018. Comprehensive analysis of coexpressed long noncoding RNAs and genes in breast cancer. In The journal of obstetrics and gynaecology research, 45, 428-437. doi:10.1111/jog.13840. https://pubmed.ncbi.nlm.nih.gov/30362198/