Ask about this productRelated genes to: PIRH2 antibody
- Gene:
- RCHY1 NIH gene
- Name:
- ring finger and CHY zinc finger domain containing 1
- Previous symbol:
- ZNF363
- Synonyms:
- CHIMP, DKFZp586C1620, PRO1996, RNF199, ARNIP, PIRH2, ZCHY
- Chromosome:
- 4q21.1
- Locus Type:
- gene with protein product
- Date approved:
- 2002-02-15
- Date modifiied:
- 2017-12-06
Related products to: PIRH2 antibody
Related articles to: PIRH2 antibody
- Autophagy is a fundamental cellular recycling process that maintains homeostasis during animal development and under nutrient-limiting conditions. In our previous work, we employed autophagy-dependent cell death (ADCD) in the obsolete Drosophila larval midgut as a model to identify the enzymes involved in protein modification via ubiquitination with potential roles in autophagy regulation. From a genetic screen we identified RING E3 ligase RCHY1 as a candidate regulator. Here, we demonstrate that RCHY1 is essential for autophagy regulation during larval midgut ADCD in Drosophila and promotes autophagic flux in HeLa cells. Loss of Rchy1 impaired autophagosome-lysosome fusion and led to the accumulation of amphisomes in larval midgut cells. Similarly, depletion of RCHY1 in HeLa cells disrupted autophagic flux and reduced autolysosome formation, indicating evolutionary conservation of its function. Collectively, our findings identify RCHY1 as a putative regulator of autophagy that facilitates autophagosome-lysosome fusion. - Source: PubMed
Publication date: 2026/04/15
Umargamwala RuchiManning JantinaCarosi Julian MDenton DonnaKumar Sharad - The turnaround of the tumor suppressor p53 protein, the guardian of the genome, is closely regulated to ensure avoidance of its untimely activation, which could lead to the demise of normal cells. Cancer cells often display mutations in the gene encoding for p53, which interferes with its normal function. The genomic series of colorectal cancer from the Cancer Genome Atlas (TCGA) was interrogated to discover genomic alterations and determine the mRNA expression of enzymes affecting p53 ubiquitination in colorectal cancers with wild-type and mutant . Genomic alterations of p53-regulating E3 ubiquitin ligases were uncommon in colorectal cancers, the most frequent being mutations in . Several p53-regulating E3 ligases were well expressed in subsets of colorectal cancers, two of which, MDM2 and TRIM24, displayed higher mRNA expressions than the normal colorectal epithelia. The former was particularly upregulated in wild-type colorectal cancers, and the latter was upregulated in both wild-type and mutant cancers. Upregulation of TRIM24 in mutant cancers was observed independently of the type of mutations (gain-of-function or other). Among E3 ligases used in proteolysis-targeting chimeras (PROTACs), VHL was upregulated together with its E2-conjugating enzyme UBE2S in colorectal cancers. This survey of p53-targeting ubiquitin ligases provides a roadmap for potential therapeutic strategies working by promoting the destruction of the mutant protein or reactivating its normal function in -mutated colorectal cancers and promoting p53 function by preventing degradation in wild-type cancers. - Source: PubMed
Publication date: 2026/02/26
Voutsadakis Ioannis A - Mutations in and functional inactivation of the Gorab gene cause gerodermia osteodysplastica (GO), a disease featuring wrinkled skin and osteoporosis, but the underlying mechanisms of skin aging remain incompletely understood. - Source: PubMed
Publication date: 2026/03/23
Li YanhongLiang WeiXu YanfengHan YunlinZhao WenjieWang SiyuanDeng WeiQin Chuan - Lung cancer is a highly malignant tumor and prone to recurrence and metastasis. Adenocarcinoma is the most common subtype. LIM zinc finger domain containing 2 (LIMS2) was reported to inhibit growth and metastasis of several tumors, while its role in lung adenocarcinoma remains unclear. This study aims to expound the function of LIMS2 in lung adenocarcinoma. The analysis from medical databanks showed that LIMS2 was lowly expressed in lung adenocarcinoma specimens, compared with the normal lung tissues, and our clinical data demonstrated that LIMS2 expression was associated with TNM stage of lung adenocarcinoma patients. Gain- and loss-of-function experiments revealed that LIMS2 suppressed proliferation, invasion, migration, epithelial-mesenchymal transition of lung adenocarcinoma cells, delayed xenograft and orthotopic growth, and blocked distant metastasis and lymph infiltration in nude mice. The medium supernatant from LIMS2-overexpressed lung adenocarcinoma cells intercepted the activation of fibroblasts from lung cancer. The co-IP results demonstrated that an E3 ubiquitin ligase ring finger and CHY zinc finger domain containing 1 (RCHY1) interacted with LIMS2, and mediated its K48 ubiquitination and degradation. LIMS2 overexpression reversed the promoting effects of RCHY1 on proliferation, migration and lung cancer-fibroblast activation of lung adenocarcinoma cells. In conclusion, decreased LIMS2 may mediate the tumor-promoting role of RCHY1 in lung adenocarcinoma cells. Implications: These findings may provide novel diagnostic markers and therapeutic targets for lung adenocarcinoma in clinic. - Source: PubMed
Publication date: 2026/02/06
Cao FengCao LeiLi YuTian GuoYou ZhunLiu MeiDing YawenLiu LeiLiu Liang - Understanding complex diseases requires models that can integrate diverse layers of biological data while yielding insights that are biologically interpretable. Although multi-omics integration with machine learning (ML) has advanced disease prediction and biomarker discovery, most existing approaches overlook the hierarchical and regulatory relationships that connect these molecular layers. Here, we present the Hierarchical Input Neural Network (HINN), a deep learning framework that incorporates known cross-omics relationships directly into its architecture, capturing the flow of information from genomics to epigenomics, transcriptomics, and downstream biological processes. By embedding these relationships, HINN improves both predictive performance and biological interpretability. We applied HINN to blood-derived multi-omics data from individuals with Alzheimer's disease or mild cognitive impairment to predict cognitive scores from standardized assessments. HINN outperformed both baseline and state-of-the-art models and pinpointed multi-omics biomarkers-including SNPs and promoter-region CpG sites in and -that were significantly correlated with plasma p-Tau181 levels. These features map to biologically relevant processes with potential implications for cognitive decline. Our findings demonstrate how combining deep learning with biological knowledge can uncover interpretable, blood-based biomarkers for cognitive decline due to complex diseases such as Alzheimer's. All code and data are openly available at https://github.com/bozdaglab/HINN. - Source: PubMed
Publication date: 2025/09/17
Vashishath YashuBeaver SarahSaeed FahadBozdag Serdar