Ask about this productRelated genes to: PPM1G antibody
- Gene:
- PPM1G NIH gene
- Name:
- protein phosphatase, Mg2+/Mn2+ dependent 1G
- Previous symbol:
- -
- Synonyms:
- PP2CG, PP2Cgamma
- Chromosome:
- 2p23.3
- Locus Type:
- gene with protein product
- Date approved:
- 1997-11-11
- Date modifiied:
- 2015-11-20
Related products to: PPM1G antibody
Related articles to: PPM1G antibody
- The activation of type I interferon (IFN-I) signaling is crucial for defending host cells against viral infections. A comprehensive IFN-I response necessitates the activation of several cellular factors, among them Interferon Regulator Factor 7 (IRF7). Nonetheless, the mechanisms governing IRF7 inactivation in response to viral infection remain largely unknown. Here, we illustrate that Cluster of differentiation 97 (CD97), a G protein-coupled receptor, interacts with PPM1G via intracellular Arg-819 and Arg-822 residues. PPM1G then recruits and dephosphorylates IRF7, leading to its inhibition. CD97-mediated inactivation of IRF7 impedes its translocation into the nucleus and subsequent activation of IFN-I, ultimately promoting the viral replication. Moreover, mice lacking CD97 display heightened resistance to viral infection. The compound sanguinarine (SANG) hinders viral replication by dampening CD97 expression. This study provides a basis for CD97 as a potential antiviral target and SANG as a candidate antiviral small molecule drug. - Source: PubMed
Publication date: 2026/03/03
Chang HuasongQi WenjingYang RukunHou PeiliKang RanLiu XiaoyuLi YingyingWang HongmeiHe Hongbin - This study aimed to identify a novel prognostic signature derived from an EGFR Tyrosine kinase inhibitors (TKI-resistant) macrophage subpopulation and to evaluate its clinical and therapeutic relevance in HCC. We utilized single-cell RNA sequencing data from HCC patients. An EGFR-TKI resistance score was calculated across all cell types. Macrophages, which exhibited the highest resistance score, were sub-clustered to identify the most resistant subpopulation. Marker genes from this sub-cluster were intersected with differentially expressed genes (DEGs) from the TCGA-LIHC cohort. A robust prognostic model was constructed. The model's performance was rigorously validated, and the signature was further characterized through multi-omics analysis and its correlation with immune checkpoint blockade (ICB) response and drug sensitivity. scRNA-seq analysis unequivocally identified macrophages as possessing the highest EGFR-TKI resistance score. We identified seven key prognostic genes: SLC41A3, DCAF13, PPM1G, NDC80, FAM83D, FUCA2, and UQCRH. A risk model built on these seven genes effectively stratified patients into high- and low-risk groups with significantly different overall survival (OS) in the TCGA cohort, a finding successfully validated in the independent GSE76427 cohort. A clinical nomogram integrating the risk score demonstrated excellent predictive accuracy, with AUC values for 1-, 3-, and 5-year OS of 0.816, 0.781, and 0.799, respectively. The low-risk group was associated with a favorable immune-infiltrated phenotype and was predicted to be more sensitive to immunotherapy. Conversely, the high-risk group exhibited distinct genomic features and was predicted to be more sensitive to specific targeted agents, including Navitoclax and Sorafenib. We identified and validated a novel 7-gene prognostic signature derived from a subpopulation of EGFR-TKI-resistant macrophages. This signature accurately predicts patient survival, offers insights into the molecular mechanisms of therapy resistance in HCC, and provides a promising tool for improved patient stratification and the development of personalized treatment strategies. - Source: PubMed
Li XiaominLi ZhilongZhai JinfangZou Binbin - Panitumumab shows limited clinical benefit in colorectal cancer (CRC), and reliable predictive biomarkers to guide patient selection remain lacking. To address this gap, we investigated molecular determinants of therapeutic response using tumor samples from patients with primary and metastatic CRC. By integrating PIMS-based metastatic classification, NPOT interaction profiling and quantitative proteomics, this study aimed to identify response-associated pathways and potential prognostic biomarkers that could support improved stratification for panitumumab therapy. - Source: PubMed
Quartier AngeliqueSanin Ahmed YNagelschmitz JuliaSchneider JustineShi WenjieWartmann ThomasDölling MaximilianStelter FrederikeAndric MihailoCroner Roland SEftekhari PierreKahlert Ulf D - Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with the poorest prognosis. The frequent development of chemoresistance is a major therapeutic challenge, yet the underlying mechanisms remain unclear. Here, we found that PPM1G was upregulated in TNBC, and high PPM1G expression was significantly correlated with poor prognosis in TNBC patients who received chemotherapy. Overexpression of PPM1G enhanced, whereas its knockdown suppressed, cancer stem cell-like properties and chemoresistance of TNBC both in vitro and in vivo. Mechanistic investigations revealed that PPM1G interacted with NDR1 and dephosphorylated it at Thr444, which in turn reduced the YAP phosphorylation level at Ser127, finally inducing YAP nuclear translocation and enhancing its transcriptional activity. Moreover, treatment with a YAP inhibitor Verteporfin significantly attenuated the PPM1G-induced chemoresistance both in vitro and in vivo. Overall, our study elucidated a role of the PPM1G/NDR1/YAP axis in TNBC chemoresistance. We proposed that PPM1G may serve as a predictive biomarker for the treatment response of TNBC to YAP inhibitor. - Source: PubMed
Publication date: 2025/10/08
Huang WeilingChen XuWeiWu HaomingZhang ChaoZhong WenjingLi XingOuyang YingChen XiangfuSong LibingWang XiHu KunpengXiong Zhenchong - Porcine reproductive and respiratory syndrome virus (PRRSV) is a major swine pathogen that causes significant economic losses worldwide. The nucleocapsid (N) protein, the most abundant viral protein in infected cells, plays roles beyond its structural function, influencing various host cellular processes. Here, we report the identification of 301 cellular protein candidates interacting with PRRSV N using EGFP immunoprecipitation combined with label-free quantitative mass spectrometry. The analysis underscores the versatile nature of the N protein in targeting a wide range of cellular proteins and processes across multiple subcellular compartments. We observed strong enrichment of ribosomal proteins, nucleolar proteins involved in ribosome biogenesis, splicing factors, RNA helicases, and DNA-binding proteins involved in chromatin remodeling and DNA damage response. Additionally, we identified proteins involved in viral RNA sensing and intrinsic antiviral mechanisms that may contribute to the immunosuppressive properties of the viral protein. Several interactions were validated and further characterized for RNA dependence, including MYBBP1A, NCL, IGF2BP1, UPF3B, G3BP1, EIF2S1, RFC4, ABCF1, PPM1G, NSUN2, and NOP2. Notably, RTCB and MYBBP1A were identified as host dependency factors for PRRSV infection. Our findings expand the current understanding of PRRSV-host interactions and reveal novel N-interacting proteins that may contribute to viral pathogenesis and immune evasion. - Source: PubMed
Publication date: 2025/09/25
Kovanich DuangnapaKetsuwan KunjimasHengphasatporn KowitThepparit ChutimaSittipaisankul PotchamanWongkongkathep PiriyaSirisereewan ChaitawatTechakriengkrai NavaponNedumpun TeerawutShigeta YasuteruPisitkun TrairakSuradhat Sanipa