Ask about this productRelated genes to: FEZF1 Blocking Peptide
- Gene:
- FEZF1 NIH gene
- Name:
- FEZ family zinc finger 1
- Previous symbol:
- ZNF312B
- Synonyms:
- -
- Chromosome:
- 7q31.32
- Locus Type:
- gene with protein product
- Date approved:
- 2006-08-14
- Date modifiied:
- 2016-04-25
Related products to: FEZF1 Blocking Peptide
Related articles to: FEZF1 Blocking Peptide
- Z. Sun, S. Gao, L. Xuan, and X. Liu, "Long Non-Coding RNA FEZF1-AS1 Induced Progression of Ovarian Cancer via Regulating miR-130a-5p/SOX4 Axis," Journal of Cellular and Molecular Medicine 24, no. 7 (2020): 4275-4285. https://doi.org/10.1111/jcmm.15088. The above article, published online on 05 March 2020 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Stefan Constantinescu; and John Wiley & Sons Ltd. A third party reported multiple instances of image duplications between this article and previously published articles. All images in Figure 2C had previously been published in [Zhu et al. 2019 (https://doi.org/10.1038/s41467-023-41612-z)] and reported as different samples. All images in Figures 3A, 3B, 4C, and 4D had previously been published in Li et al. 2017 [(https://doi.org/10.1038/cddis.2017.119)] and reported as different samples. The GAPDH band in Figure 5D and all bands in Figure 5H had previously been published in [Liu et al. 2017 (https://doi.org/10.1186/s12943-017-0625-8)] and all those images were manipulated and rotated. Furthermore, multiple images in Figure 5E had previously been published in Liu et al. 2017, where further manipulation and rotation had been applied to these images. An investigation by the publisher confirmed these concerns and discovered additional instances of image duplication from other articles. Data in Figure 2D had previously been published in [Liang et al. 2018 (https://doi.org/10.1038/s41419-018-0582-1)], [Wang et al. 2019 (https://doi.org/10.18632/aging.102081)] and [Liang et al. 2020 (https://doi.org/10.1186/s12943-020-01206-5)]. Images in Figure 2C had previously been published in [Zhu et al. 2019 (https://doi.org/10.1038/s41467-018-07998-x)] and these images had been rotated. Multiple images in Figure 5E that were also previously published in Liu et al. 2017, were also later published in [Li et al. 2021 (https://doi.org/10.2147/OTT.S302800)]. The retraction has been agreed to because the evidence of image re-use and manipulation with multiple previously published articles fundamentally compromises the editors' confidence in the results presented. The authors did not respond to our notice regarding the retraction. - Source: PubMed
- Lung cancer is one of the most common malignancies, characterized by a wide prognosis spectrum, different histological subtypes, and a high mortality rate. Hemostatic system imbalance in patients with lung cancer often leads to increased mortality. Intracellular RNAs that share common miRNA binding sites create a competing endogenous RNA (ceRNA) network that plays an important role in gene expression regulation. The emerging role of ceRNAs in tumor development is increasingly being recognized; however, their connection to hemostatic system imbalance in lung squamous cell carcinoma (LUSC) remains unclear. In this study, RNA-seq data of LUSC and normal tissues were downloaded from the TCGA data portal. Differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs) between LUSC and corresponding paracancerous tissues were analyzed using the DESeq2 package in R statistical software. Hemostasis-related genes linked to coagulation and complement cascades (hsa04610) and platelet activation (hsa04611) pathways were identified using the KEGGREST package. The ceRNA network associated with system hemostasis was constructed using differentially expressed RNAs (DERNAs), including mRNAs, lncRNAs, and miRNAs. The GO and KEGG enrichment analysis of DEmRNAs was conducted using the enrichR package. Hazard ratio (HR) and Kaplan-Meier curve were employed to assess the prognostic value of DERNAs using the survival and survminer packages. A ceRNA network comprising 100 hemostasis-related genes, 5 miRNAs, and 57 lncRNAs was constructed. Of these, 19 hemostasis genes, one miRNA (miR-23-3p), and 6 lncRNAs (LINC01615, LINC00707, LINC00702, FEZF1-AS1, DLX6-AS1, CLRN1-AS1) were significantly associated with prognosis in LUSC. Based on correlation analysis, MEF2C-AS1/miR-429/F8, RAP1A, GNAI2, C3AR1, F13A1, P2RY12, LCP2, C1QC axis and CASC11, CASC9, PVT1, BBOX1-AS1/ miR-23b-3p/ PLAU axis may represent key pathways involved in hemostatic system imbalance and the pathogenesis of LUSC. Our analysis revealed a complex ceRNA network associated with system hemostasis and the prognosis of LUSC. These findings may contribute to the development of personalized therapies and valuable prognostic biomarkers for LUSC patients. - Source: PubMed
Publication date: 2025/12/17
Mirazimi YasinGharechahi Javad - Osteosarcoma (OS) faces a high metastatic burden, limited effective treatments, and a lack of specific therapeutic targets. - Source: PubMed
Publication date: 2025/12/03
Han YanlongYe ZiangWang Li - Brain-derived neurotrophic factor (BDNF) is highly expressed in the hypothalamus where it exerts regulatory functions over neurogenesis, reproduction, energy balance, and metabolism. Analyzing a hypothalamic single-nucleus transcriptomic, we identified Fezf1 ventromedial hypothalamic (VMH) neurons as an important source of BDNF. During development, Fezf1 neurons are involved in the organization of the olfactory bulb, and mutations on this gene are responsible for Kallmann syndrome; however, in adult life, little is known about the functions of Fezf1 neurons. - Source: PubMed
Publication date: 2025/11/11
Cabral-da-Silva DayanaZanesco Ariane MValdivieso-Rivera FernandoGallo-Ferraz Ana LSimões Marcela RBombassaro BrunaSponton Carlos HVelloso Licio A - [This corrects the article DOI: 10.3389/fgene.2025.1514205.]. - Source: PubMed
Publication date: 2025/10/07
Yang XiaopingYuan ZuohuiGou LingzhuCheng LongWang ZiruiWu PingfanWang XiaochunMa XueniMa TiantianYu YiWu ZhipingZhang Dekui