Ask about this productRelated genes to: RRP1B Blocking Peptide
- Gene:
- RRP1B NIH gene
- Name:
- ribosomal RNA processing 1B
- Previous symbol:
- KIAA0179
- Synonyms:
- Nnp1, RRP1, PPP1R136
- Chromosome:
- 21q22.3
- Locus Type:
- gene with protein product
- Date approved:
- 2003-12-15
- Date modifiied:
- 2014-11-19
Related products to: RRP1B Blocking Peptide
Related articles to: RRP1B Blocking Peptide
- Aberrant lipid metabolism is a hallmark of hepatocellular carcinoma (HCC), yet the regulatory mechanisms governing lipid droplet (LD) dynamics and their contribution to tumor progression remain poorly understood. Here, we developed an ultrasensitive phosphoproteomic platform using high-affinity HPDA@Ti nanospheres to map LD-associated phosphorylation events across six HCC cell lines. By correlating phosphoproteomic signatures with LD morphology, we identified distinct regulatory signatures associated with LD size and abundance. Functional perturbation screens identified two distinct phosphoprotein modules controlling LD size: silencing , , , , and reduced LD size in Huh1 cells, whereas silencing , , , , , and enlarged LDs in Huh7 cells. Notably, we identified EPB41L3 as a critical metabolic-metastatic link; its loss decreased LD size and accelerated HCC migration and invasion, correlating with poor clinical prognosis. Crucially, we identified five key phosphorylation sites on EPB41L3 essential for its function; substituting these with alanine completely abolished its regulatory control over both LD size and HCC metastatic potential. Together, these findings delineate a phosphorylation-based regulatory network controlling the LD architecture and metastatic potential in HCC. Our study not only identifies potential therapeutic targets but also establishes a generalizable phosphoproteomic framework for interrogating lipid signaling in cancer metabolism. - Source: PubMed
Publication date: 2026/05/29
Mao Jian-WenXia YanLuo Xue-YangWang ShupeiGong JingyiXu JindianChen WeiweiWu JiaqiLi ZimengLuo JiahuiZhang HongyeLu QingWu DuojiaoWu Wei-ZhongWang JiaxiHuang Li-Hao - Intron-containing mRNAs are cotranscriptionally spliced and assembled into messenger ribonucleoprotein (mRNP) particles, a process monitored by surveillance pathways. Here, we combined biochemical and structural approaches to elucidate the mechanisms by which mRNPs are sorted between two opposing fates: nuclear degradation and cytoplasmic export. While the human GANP-PCID2 complex is known to connect mRNPs to nuclear export, our data indicate that the LENG8-PCID2 complex operates as an mRNP decay connector, coupling nuclear mRNPs to the RNA-degrading exosome via the PAXT adaptor complex. Both recognize the mRNP component UAP56, but LENG8-PCID2 uniquely associates with early splicing factors through a direct interaction with U1A and RRP1B. Similarly, the Thp3-Csn12 ortholog in budding yeast couples the early splicing factors Mud2-Bbp with the nuclear exosome. The spliceosome-exosome mRNP decay pathway we uncovered reveals molecular principles that remain strikingly conserved across evolution, despite the fundamental differences in splicing and decay between humans and budding yeast. - Source: PubMed
Publication date: 2026/05/15
Abbas Daniel KBonneau FabienWilkinson Max ESchüssler SteffenBasquin JérômeConti Elena - Serum lipid levels, which are influenced by both genetic and environmental factors, are key determinants of cardiometabolic health and are influenced by both genetic and environmental factors. Improving our understanding of their underlying biological mechanisms can have important public health and therapeutic implications. Although psychosocial factors, including depression, anxiety, and perceived social support, are associated with serum lipid levels, it is unknown if they modify the effect of genetic loci that influence lipids. We conducted a genome-wide gene-by-psychosocial factor interaction (G×Psy) study in up to 133,157 individuals to evaluate if G×Psy influences serum lipid levels. We conducted a two-stage meta-analysis of G×Psy using both a one-degree of freedom (1df) interaction test and a joint 2df test of the main and interaction effects. In Stage 1, we performed G×Psy analyses on up to 77,413 individuals and promising associations (P < 10) were evaluated in up to 55,744 independent samples in Stage 2. Significant findings (P < 5 × 10) were identified based on meta-analyses of the two stages. There were 10,230 variants from 120 loci significantly associated with serum lipids. We identified novel associations for variants in four loci using the 1df test of interaction, and five additional loci using the 2df joint test that were independent of known lipid loci. Of these 9 loci, 7 could not have been detected without modeling the interaction as there was no evidence of association in a standard GWAS model. The genetic diversity of included samples was key in identifying these novel loci: four of the lead variants displayed very low frequency in European ancestry populations. Functional annotation highlighted promising loci for further experimental follow-up, particularly rs73597733 (MACROD2), rs59808825 (GRAMD1B), and rs11702544 (RRP1B). Notably, one of the genes in identified loci (RRP1B) was found to be a target of the approved drug Atenolol suggesting potential for drug repurposing. Overall, our findings suggest that taking interaction between genetic variants and psychosocial factors into account and including genetically diverse populations can lead to novel discoveries for serum lipids. - Source: PubMed
Publication date: 2025/06/20
Bentley Amy RBrown Michael RMusani Solomon KSchwander Karen LWinkler Thomas WSims MarioKilpeläinen Tuomas OAschard HuguesBartz Traci MBielak Lawrence FChai Jin-FangChitrala Kumaraswamy NaiduFranceschini NoraGraff MariaelisaGuo XiuqingHartwig Fernando PHorimoto Andrea R V RLim EliseLiu YongmeiManning Alisa KNolte Ilja MNoordam RaymondRichard Melissa ASmith Albert VSung Yun JuVojinovic DinaWang RujiaWang YujieFeitosa Mary FHarris Sarah ELyytikäinen Leo-PekkaPistis GiorgioRauramaa Rainervan der Most Peter JWare ErinWeiss StefanWen WanqingYanek Lisa RArking Dan EArnett Donna KBallantyne ChristieBoerwinkle EricChen Yii-Der IdaDaviglus Martha Lde Las Fuentes Lisade Vries Paul SDelaney Joseph A CFretts Amanda MEkunwe LynetteFaul Jessica DGallo Linda CHeikkinen SamiHomuth GeorgIkram M ArfanIsasi Carmen RJonas Jost BrunoKeltikangas-Järvinen LiisaKomulainen PirjoKraja Aldi TKrieger Jose ELauner Lenore Liu JianjunLohman KurtLuik Annemarie IManichaikul Ani WMarques-Vidal PedroMilaneschi YuriMwasongwe Stanford EO'Connell Jeffrey RRice KennethRich Stephen SSchreiner Pamela JSchwettmann LarsShikany James MShu Xiao-OuSmith Jennifer ASnieder HaroldSotoodehnia NonaTai E ShyongTaylor Kent DTinker LesleyTsai Michael YUitterlinden André Gvan Duijn Cornelia Mvan Heemst DianaWaldenberger MelanieWallace Robert BWee Hwee-LinWeir David RWei Wen-BinWillems van Dijk KoWilson GregoryYao JieYoung Kristin LZhang XiaoyuZhao WeiZhu XiaofengZonderman Alan BDeary Ian JGieger ChristianGrabe Hans JörgenLakka Timo ALehtimäki TerhoOldehinkel Albertine JPreisig MartinWang Ya-XingZheng WeiEvans Michele KProvince MichaelGauderman JamesGudnason VilmundurHartman Catharina AHorta Bernardo LKardia Sharon L RKooperberg CharlesLiu Ching-TiMook-Kanamori Dennis OPenninx Brenda WjhPereira Alexandre CPeyser Patricia APsaty Bruce MRotter Jerome ISim XuelingNorth Kari ERao Dabeeru CBierut LauraMiller Clint LMorrison Alanna CRotimi Charles NFornage MyriamFox Ervin R - Epsilon toxin (ETX), a potential agent of biological and toxic warfare, causes the death of many ruminants and threatens human health. It is crucial to understand the toxic mechanism of such a highly lethal and rapid course toxin. In this study, we detected the effects of ETX on the proteome and phosphoproteome of MDCK cells after 10 min and 30 min. A total of 44 differentially expressed proteins (DEPs) and 588 differentially phosphorylated proteins (DPPs) were screened in the 10 min group, while 73 DEPs and 489 DPPs were screened in the 30 min group. ETX-induced proteins and phosphorylated proteins were mainly located in the nucleus, cytoplasm, and mitochondria, and their enrichment pathways were related to transcription and translation, virus infection, and intercellular junction. Meanwhile, the protein-protein interaction network screened out several hub proteins, including SRSF1/2/6/7/11, SF3B1/2, NOP14/56, ANLN, GTPBP4, THOC2, and RRP1B. Almost all of these proteins were present in the spliceosome pathway, indicating that the spliceosome pathway is involved in ETX-induced cell death. Next, we used RNAi lentiviruses and inhibitors of several key proteins to verify whether these proteins play a critical role. The results confirmed that SRSF1, SF3B2, and THOC2 were the key proteins involved in the cytotoxic effect of ETX. In addition, we found that the common upstream kinase of these key proteins was SRPK1, and a reduction in the level of SRPK1 could also reduce ETX-induced cell death. This result was consistent with the phosphorylated proteomics analysis. In summary, our study demonstrated that ETX induces phosphorylation of SRSF1, SF3B2, THOC2, and SRPK1 proteins on the spliceosome pathway, which inhibits normal splicing of mRNA and leads to cell death. - Source: PubMed
Publication date: 2024/09/14
Yue NanHuang JingDong MingxinLi JiaxinGao ShanWang JingWang YingshuangLi DongxueLuo XiLiu TingtingHan SongyangDong LinaChen MingWang JinglinXu NaKang LinXin Wenwen - Multiple myeloma (MM) is an incurable hematological malignancy with poor survival. Accumulating evidence reveals that lactylation modification plays a vital role in tumorigenesis. However, research on lactylation-related genes (LRGs) in predicting the prognosis of MM remains limited. Differentially expressed LRGs (DELRGs) between MM and normal samples were investigated from the Gene Expression Omnibus database. Univariate Cox regression and LASSO Cox regression analysis were applied to construct gene signature associated with overall survival. The signature was validated in two external datasets. A nomogram was further constructed and evaluated. Additionally, Enrichment analysis, immune analysis, and drug chemosensitivity analysis between the two groups were investigated. qPCR and immunofluorescence staining were performed to validate the expression and localization of PFN1. CCK-8 and flow cytometry were performed to validate biological function. A total of 9 LRGs (TRIM28, PPIA, SOD1, RRP1B, IARS2, RB1, PFN1, PRCC, and FABP5) were selected to establish the prognostic signature. Kaplan-Meier survival curves showed that high-risk group patients had a remarkably worse prognosis in the training and validation cohorts. A nomogram was constructed based on LRGs signature and clinical characteristics, and showed excellent predictive power by calibration curve and C-index. Moreover, biological pathways, immunologic status, as well as sensitivity to chemotherapy drugs were different between high- and low-risk groups. Additionally, the hub gene PFN1 is highly expressed in MM, knocking down PFN1 induces cell cycle arrest, suppresses cell proliferation and promotes cell apoptosis. In conclusion, our study revealed that LRGs signature is a promising biomarker for MM that can effectively early distinguish high-risk patients and predict prognosis. - Source: PubMed
Publication date: 2024/07/02
Sun ChengZhang WanqiuLiu HaoDing YangyangGuo JingjingXiong ShudaoZhai ZhiminHu Wei