Ask about this productRelated genes to: PAIP1 Blocking Peptide
- Gene:
- PAIP1 NIH gene
- Name:
- poly(A) binding protein interacting protein 1
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 5p12
- Locus Type:
- gene with protein product
- Date approved:
- 2003-12-16
- Date modifiied:
- 2014-11-19
Related products to: PAIP1 Blocking Peptide
Related articles to: PAIP1 Blocking Peptide
- E3 ligases and RNA-binding protein-mediated dysregulation of proinflammatory cytokines leads to autoimmune and inflammatory diseases. However, whether RNA-binding E3 ligases can regulate specific proinflammatory cytokine expression remains unclear. Here we found that the RNA-binding E3 ligase MKRN2 selectively inhibits the expression of interleukin-6 (IL-6) in lipopolysaccharide-activated macrophages. LysM-CreMkrn2 mice showed increased amounts of IL-6 in the serum after lipopolysaccharide treatment and exhibited increased severity of experimental colitis, which was associated with increased IL-6. Expression of MKRN2 negatively correlated with expression of IL-6 in clinical samples from individuals with ulcerative colitis and rheumatoid arthritis. Mechanistically, after binding to Il6 messenger RNA, MKRN2 linked K29 polyubiquitin chains to the Lys 179 residue of PAIP1, a translation initiation coactivator, which blocked PAIP1-eIF4A interaction and thus inhibited the translational efficiency of Il6 mRNA. Our findings provide mechanistic insight and potential therapeutic strategies for inflammatory autoimmune diseases by disrupting translation of specific proinflammatory cytokines. - Source: PubMed
Publication date: 2025/06/16
Yu ZhouLi XuelianHuang JiayingPan JueyuCheng JialeLiu PingYang MingjinChen TaoyongZhang QianZhou YumeiWu JiachengHan TaotaoLi JingnanXu YueWen MingyueZhang XuanWang ChunmeiCao Xuetao - Poly (A) binding protein interacting protein 1 (PAIP1) has been shown to causally contribute to the development and progression of cancer. However, the mechanisms of the PAIP1 regulation in tumor cells remain poorly understood. - Source: PubMed
Publication date: 2024/10/03
Zheng JianfengZhang XiaoyuXue YaqiangShao WenhuaWei YaxunMi SisiYang XiaojieHu LinanZhang YiLiang Ming - Polyadenylate-binding protein-interacting protein 1 (PAIP1) is a protein that modulates translation initiation in eukaryotic cells. Studies have shown that PAIP1 was overexpressed in various type of cancers, and drives cancer progression by promoting cancer cell proliferation, invasion, and migration. In our previous study, we identified that PAIP1 was overexpressed in breast cancer, and the expression was correlated with poor prognosis. However, the biological function of PAIP1 in breast cancer has not been clearly understood. In this study, we constructed PAIP1 specifically silenced breast cancer cells. Then, cell proliferation, cell cycle distribution, and apoptosis were detected in PAIP1 knockdown cells. RNA-seq analysis was performed to predict the downstream target of PAIP1, and the molecular mechanism was explored. As a results, we found that knockdown of PAIP1 repressed cell proliferation, induced cell cycle arrest, and triggers apoptosis. Xenograft mouse model showed that knockdown of PAIP1 inhibits cell growth in vivo. RNA-seq predicted that CCNE2 mRNA was one of the downstream targets of PAIP1. In addition, we identified that knockdown of PAIP1-inhibited cell proliferation through modulating cyclin E2 expression. Mechanically, knockdown of PAIP1 reduces the expression of cyclin E2 by regulating the mRNA stability of cyclin E2. Moreover, in breast cancer tissues, we found that the expression of PAIP1 was positively correlated with cyclin E2. Taken together, our findings establish the role and mechanism of PAIP1 in breast cancer progression, indicating that PAIP1 would be a new therapeutic target for breast cancer treatment. - Source: PubMed
Publication date: 2024/09/11
Yang WenqingWang QingkunLi QiHan YueZhang YuZhu LuZhu LianhuaPiao Junjie - To explore the mechanism of Qigui-Yishen decoction in delaying renal fibrosis in mice by regulating thrombin regulatory protein (Thrombomodulin, TM) and plasminogen activator inhibitor-1 (PAI-1) based on network pharmacology. - Source: PubMed
Publication date: 2024/06/15
Lu XunWan Xiao-Wen - Cervical cancer is one of the most severe threats to women worldwide and holds fourth rank in lethality. It is estimated that 604, 127 cervical cancer cases have been reported in 2020 globally. With advancements in high throughput technologies and bioinformatics, several cervical candidate genes have been proposed for better therapeutic strategies. In this paper, we intend to prioritize the candidate genes that are involved in cervical cancer progression through a fractal time series-based cross-correlations approach. we apply the chaos game representation theory combining a two-dimensional multifractal detrended cross-correlations approach among the known and candidate genes involved in cervical cancer progression to prioritize the candidate genes. We obtained 16 candidate genes that showed cross-correlation with known cancer genes. Functional enrichment analysis of the candidate genes shows that they involve GO terms: biological processes, cell-cell junction assembly, cell-cell junction organization, regulation of cell shape, cortical actin cytoskeleton organization, and actomyosin structure organization. KEGG pathway analysis revealed genes' role in Rap1 signaling pathway, ErbB signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling pathway, Acute myeloid leukemia, chronic myeloid leukemia, Breast cancer, Thyroid cancer, Bladder cancer, and Gastric cancer. Further, we performed survival analysis and prioritized six genes CDH2, PAIP1, BRAF, EPB41L3, OSMR, and RUNX1 as potential candidate genes for cervical cancer that has a crucial role in tumor progression. We found that our study through this integrative approach an efficient tool and paved a new way to prioritize the candidate genes and these genes could be evaluated experimentally for potential validation. We suggest this may be useful in analyzing the nucleotide sequences and protein sequences for clustering, classification, class affiliation, etc. - Source: PubMed
Publication date: 2024/05/28
Mallikarjuna TThummadi N BVindal VaibhavManimaran P