WIPI1 Antibody Autophagy Antibody
- Known as:
- WIPI1 Antibody Autophagy Antibody
- Catalog number:
- AUT-7041
- Product Quantity:
- 0.1 mg
- Category:
- -
- Supplier:
- Zyagen
- Gene target:
- WIPI1 Antibody Autophagy
Related genes to: WIPI1 Antibody Autophagy Antibody
- Gene:
- WIPI1 NIH gene
- Name:
- WD repeat domain, phosphoinositide interacting 1
- Previous symbol:
- -
- Synonyms:
- FLJ10055, WIPI49, ATG18, ATG18A
- Chromosome:
- 17q24.2
- Locus Type:
- gene with protein product
- Date approved:
- 2005-11-15
- Date modifiied:
- 2016-03-01
Related products to: WIPI1 Antibody Autophagy Antibody
Related articles to: WIPI1 Antibody Autophagy Antibody
- Modulation of autophagy in cancer treatment has attracted considerable interest, as it can contribute to cell death. Several studies have shown that inhibition of casein kinase 1α (CK1α) induces autophagy-mediated cell death in various cancer cell lines. As the role of CK1α in autophagy regulation and cell death in prostate cancer (CaP) cell lines remains unclear, this study aimed to investigate it. - Source: PubMed
Publication date: 2026/04/14
Behrouj HamidZabihi ShahrbanooAsl Mehrsa Alsadat TaghaviNoorbakhsh NegarMovahedpour AhmadVeisi AliZarezade VahidSabaghan MohamadAzadbakht Omid - Autophagy has a critical involvement in the initiation and progression of various cancers, including colorectal cancer (CRC). The feasibility of using autophagy-related genes (ATGs) as prognostic tools for CRC patients is yet to be determined. - Source: PubMed
Miao DazhuangSong YushuiZhou LiangLiang GuanyingWang YanHe WeiHuang LuyuLu HongnanJiang ShixiongJia YunheLi ZhiweiTong Jinxue - Ischemic heart disease is the main cause of death worldwide. Classic cardiac biomarkers, such as troponin, which are released due to myocyte necrosis, are widely used for diagnosis, but they provide limited information about the initial underlying cellular processes involved in myocardial infarction. Autophagy is now considered fundamental in the pathophysiology of cardiac ischemia and related reperfusion injury. This systematic review aims to identify and highlight candidate autophagy-related biomarkers in cardiac ischemia and infarction with potential benefits for early diagnosis, prognosis, and therapy. A comprehensive literature search was conducted up to 1 June 2025. We included studies that examined biomarkers involved in the autophagy process in cardiac ischemia/infarction, which involved humans and animal models. A total of 14 eligible articles were reviewed. Thirteen autophagy-related biomarkers were identified, including LC3-II/I, Beclin-1, ATG5, ATG7, p62, WIPI1, FGF21, CHRF, Rubicon, IL-1β, IL-18, and adiponectin. These biomarkers have a dynamic pattern, and they exhibited time-dependent changes during the different stages of myocardial infarction. Autophagy biomarkers present a promising understanding of the molecular mechanism of early myocardial ischemia and infarction. Integration of autophagy biomarkers with the classic markers should improve risk stratification, therapeutic decision-making, and prognosis in patients with ischemic heart disease. - Source: PubMed
Publication date: 2026/02/24
Radaelli DavideAlshaeb AsmaAl-Habash IbrahimBelakaposka Srpanova ViktorijaJakovski ZlatkoSinagra GianfrancoMihic Anita GalicD'Errico Stefano - Macroautophagy (hereafter referred to as autophagy) requires the coordinated action of approximately 20 (autophagy related) genes. Duplication of genes has had a major impact on the evolution of the autophagy pathway among major lineages. One duplication hotspot is in vertebrates. However, the exact duplication timing, post-duplication evolutionary divergence patterns, and its relation to functional differences among paralogs have not been investigated in detail. Here, we demonstrate that most genes were likely duplicated by whole-genome duplication events near the root of vertebrates. We compared the sequence and gene expression divergence between paralogs and categorized the evolutionary fates (i.e., how ancestral function is divided between paralogs). Within the paralog pairs that evolved most asymmetrically, namely , ( and ), and , one paralog likely retained the ancestral function, allowing the other to evolve under less constraint. While no obvious asymmetry was observed between and in non-mammalian vertebrates, experienced marked sequence divergence and expression level reduction in mammals, suggesting a shift in balance. Expression patterns among the ( and ), ( and ), and ( and ) pairs were more consistent with hypofunctionalization/dosage sharing, such that ancestral function depends on both paralogs. We also demonstrate that both and can support autophagy, whereas only , but not , has autophagic function and discuss the relationship between autophagic function and evolutionary divergence. The present detailed analysis of gene duplication in vertebrates provides a critical timeline for interpreting functional differentiation between homologs.: ATG: autophagy related; BLAST: Basic Local Alignment Search Tool; DKO: double knockout; GFP: green fluorescent protein; GLMM: generalized linear mixed model; KO: knockout; LC3: MAP1LC3; MEF: mouse embryonic fibroblast; ns: non-significant; PAML: Phylogenetic Analysis by Maximum Likelihood; RPKM: reads per kilobase per million mapped reads; SVA: surrogate variable analysis; TMM: trimmed mean of M values; TMR: tetramethylrhodamine; WT: wild type. - Source: PubMed
Publication date: 2026/01/24
Zhang SidiKoyama-Honda IkukoHiratsuka DaikiMizushima Noboru - Major Depressive Disorder (MDD) is linked to increased neurodegenerative risk. Emerging evidence implicates ferroptosis in neuropsychiatric disorders, prompting investigation of its role in MDD through key gene identification. Three microarray datasets from the GEO database were analysed. Weighted gene co-expression network analysis (WGCNA) identified MDD-related module genes (MRGs) while ferroptosis-related genes (FRGs) were extracted from the FerrDb database. Overlapping genes between MRGs and FRGs were prioritised for mechanistic exploration. Functional enrichment (GO/KEGG) and protein-protein interaction (PPI) network analyses (via Cytoscape and CytoHubba) highlighted hub genes. Machine learning algorithms were applied to develop a diagnostic model, validated through nomogram analysis, calibration curves, decision curve analysis (DCA), ROC curves (AUC evaluation), gene set enrichment analysis (GSEA), and DGIdb-based drug prediction. Differential expression analysis identified 1878 MDD-associated genes (715 downregulated, 1163 upregulated). Four FRGs-MAPK14, WIPI1, DUSP1, and ULK1-emerged as diagnostic biomarkers, showing significant immune cell infiltration correlations (e.g., neutrophils, dendritic cells) and enrichment in pathways like MAPK signalling. The study highlights ferroptosis-related genes (ULK1, MAPK14, WIPI1, DUSP1) as potential diagnostic and therapeutic targets in MDD, linked to neuroimmune interactions and cellular stress responses. These findings underscore MDD's pathophysiological complexity and may guide strategies for managing MDD and neurodegenerative comorbidities. - Source: PubMed
Huang ShenghuiXie ShoupinFeng FeiWan YanyanMa YanpingWang YafengZhang FanChen XinhongTang PingLi Hailong