Ask about this productRelated genes to: SHP2 antibody
- Gene:
- PTPN11 NIH gene
- Name:
- protein tyrosine phosphatase non-receptor type 11
- Previous symbol:
- NS1
- Synonyms:
- BPTP3, SH-PTP2, SHP-2, PTP2C, SHP2
- Chromosome:
- 12q24.13
- Locus Type:
- gene with protein product
- Date approved:
- 1993-03-03
- Date modifiied:
- 2019-04-23
Related products to: SHP2 antibody
Related articles to: SHP2 antibody
- Chinese yam possesses anti-type 2 diabetes mellitus (T2DM) potential. However, existing research has focused on its polysaccharides rather than its abundant peptide components. Therefore, this study integrated peptidomics with network pharmacology and molecular docking to explore the potential anti-T2DM mechanisms of Chinese yam peptides. Firstly, this study revealed that crude peptides extracted from Chinese yam possessed a potential hypoglycemic activity, with an IC of 568.87 μg/mL against α-glucosidase. Secondly, peptidomics identified 558 peptides with the sequences ranging from 3 to 25 residues. Thirdly, network pharmacology was conducted on 15 candidate peptides selected through bioactivity prediction and safety evaluation. These peptides shared 466 common targets with T2DM, with seven core targets identified through topological network analysis: , , , , , , and . Enrichment analysis revealed that these targets were significantly associated with PI3K-Akt and MAPK signaling pathways. Fourthly, molecular docking confirmed the strong binding affinities between the 15 bioactive peptides and seven core targets, particularly the high-affinity binding of peptides SIDLYENRL and RAPDDLDTRL to . Collectively, these findings demonstrate that Chinese yam peptides possess potential hypoglycemic activity and may ameliorate T2DM through the regulation of insulin signaling via PI3K-Akt activation and the modulation of inflammation via the MAPK pathway. - Source: PubMed
Publication date: 2026/07/25
Ma Hui-KeLi Xin-YuShen LiangJi Hong-Fang - This study explores the role of the src homology-2domain-containing protein tyrosine phosphatase-2 (SHP2)-discoid domain receptor 1 (DDR1)-extracellular signal-regulated kinase (ERK) signaling axis in neuropathic pain following spinal cord injury (SCI). Rats were transfected with LV-shSHP2 before SCI modeling. Hind limb function and paw withdrawal threshold were assessed using the Basso-Beattie-Bresnahan (BBB) scale, and Von Frey filaments, respectively. The effects of SHP2 knockdown on microglial activation and DDR1/SHP2/ERK pathway were examined by Western blotting and immunofluorescence. To further validate the regulatory mechanism of SHP2 in SCI, lipopolysaccharide (LPS)-activated BV-2 microglial cells were subjected to SHP2/DDR1 knockdown, or DDR1 overexpression. Results showed that SCI induced motor deficits, mechanical allodynia, and upregulation of spinal SHP2, DDR1, and p-ERK/ERK ratio, alongside microglial activation. These changes were reversed by LV-shSHP2 treatment. In LPS treated BV-2 cells, DDR1 overexpression promoted cell activation and ERK phosphorylation, while counteracting the effects of LV-shSHP2; however, DDR1 knockdown produced the opposite effects. A direct interaction between SHP2 and DDR1 was confirmed. In conclusion, SHP2 knockdown suppresses microglial hyperactivation and alleviates SCI-induced neuropathic pain by downregulating the DDR1-ERK signaling pathway, during which SHP2-DDR1 interaction has been confirmed as a key regulatory mechanism. Targeting this specific interaction axis may offer a novel therapeutic strategy for neuropathic pain management by selectively disrupting microglial activation. - Source: PubMed
Zhang WeiXu Zhenwei - Juvenile myelomonocytic leukemia (JMML) rarely manifests with extramedullary involvement beyond spleen, liver, or skin; testicular infiltration at diagnosis is unreported. We describe a Novel Case of bilateral testicular leukemic infiltration as the initial presentation of NRAS-mutant JMML in a toddler, with rapid remission following azacitidine bridging and haploidentical HSCT. - Source: PubMed
Publication date: 2026/07/23
VatanParast Yousef - Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, driven by late-stage diagnosis, metastatic progression, and therapeutic resistance. Src homology region 2 domain-containing phosphatase 2 (SHP2) has emerged as a critical regulator of oncogenic signaling in gastric tumorigenesis, yet its therapeutic targeting remains underexplored. In this study, we evaluated the anti-cancer efficacy of NSC 57774, a novel SHP2 inhibitor, using integrated bioinformatics and functional assays in AGS gastric cancer cells. Analysis of The Cancer Genome Atlas (TCGA) and UALCAN datasets revealed marked upregulation of SHP2 and multiple receptor tyrosine kinases in gastric cancer tissues. NSC 57774 potently inhibited cell proliferation and migration, demonstrating selective cytotoxicity towards cancer cells over non-cancerous fibroblasts. Mechanistically, NSC 57774 disrupted key oncogenic pathways including MAPK/ERK, AKT and STAT3 in a concentration- and time-dependent manner, with higher doses achieving more sustained pathway suppression. NSC 57774 suppressed NF-κB inflammatory signaling at early timepoints and induced cleaved caspase-3 across all treatment groups at 72 hours, indicative of pro-apoptotic activity. A paradoxical late-phase increase in phospho-p38 was observed at 72 hours, consistent with a compensatory pro-apoptotic stress response. Comparative analysis revealed that NSC 57774 outperformed the commercial SHP2 inhibitor NSC 87877 and doxorubicin in reducing viability and migration of gastric cancer cells. Collectively, these findings position NSC 57774 as a promising candidate for targeted gastric cancer therapy, capable of disrupting multiple signaling pathways involved in tumor progression, metastasis, and inflammation, warranting further preclinical and clinical investigation. - Source: PubMed
Publication date: 2026/07/30
Khoder GhaliaGhemrawi RoseSammani NourHarati RaniaHamad MohamadMuhammad Jibran SualehMousa WalaaKhair Mostafa - Gene network enrichment analysis (GNEA) offers a robust approach for interpreting the complex molecular mechanisms underlying phenotypic variability. Despite its utility, prevailing GNEA methodologies are predominantly optimized for binary phenotypes, leading to substantial information loss when applied to continuous biological traits such as drug sensitivity, cancer progression, etc. Additionally, traditional enrichment strategies often exhibit conceptual inconsistency between their null models and test hypotheses, as they rely on permuting phenotype labels rather than genes. To address these limitations, we introduce cell line-specific gene network enrichment analysis (CellGNEA), a computational strategy designed to identify pathway-level molecular interactions associated with continuous phenotypes in a cell line-specific manner. CellGNEA constructs gene regulatory networks tailored to individual cell lines and assesses molecular interplays within these networks by integrating multiple network-derived metrics, including clustering coefficient, PageRank, and regulatory effects. Associations between gene networks and continuous phenotypes are quantified using a Kolmogorov-Smirnov-based statistic, with statistical significance determined via a gene permutation strategy that aligns the null model with the tested hypothesis. Monte Carlo simulation studies indicate that CellGNEA exhibits robustness and enhanced sensitivity in detecting network enrichment linked to continuous phenotypes. Applications of CellGNEA to drug sensitivity-specific gene networks enable the identification of leukemia-related pathways with molecular interactions significantly associated with therapeutic response. Notably, our analysis revealed that imatinib, quizartinib, and ruxolitinib consistently correlate with network-level remodeling across acute myeloid leukemia, myelodysplastic syndrome, and chronic myeloid leukemia pathways, and identified resistance-associated genes including PTPN11, MS4A1, and BTK. Overall, CellGNEA establishes a systematic, scalable framework for functional network analysis of continuous phenotypes, facilitating comprehensive characterization of cell line-specific biological properties and providing valuable insights for systems biology and precision medicine. - Source: PubMed
Park HeewonImoto SeiyaMiyano Satoru