C13 and N15-labeled, Human ADAM12 Protein
- Known as:
- C13 N15-labeled, Human ADAM12 Protein
- Catalog number:
- AD2-H9228
- Product Quantity:
- 20ug
- Category:
- -
- Supplier:
- acrobyosystems
- Gene target:
- C13 and N15-labeled Human ADAM12 Protein
Related genes to: C13 and N15-labeled, Human ADAM12 Protein
- Gene:
- ADAM12 NIH gene
- Name:
- ADAM metallopeptidase domain 12
- Previous symbol:
- -
- Synonyms:
- MCMPMltna, MLTN
- Chromosome:
- 10q26.2
- Locus Type:
- gene with protein product
- Date approved:
- 1998-12-01
- Date modifiied:
- 2016-10-05
Related products to: C13 and N15-labeled, Human ADAM12 Protein
Related articles to: C13 and N15-labeled, Human ADAM12 Protein
- Muscle fibrosis is a key pathological feature of Duchenne muscular dystrophy (DMD) and is closely associated with disease progression. Fibroadipogenic progenitors (FAPs) are major contributors to fibrosis, yet the precise mechanisms remain unclear. To investigate FAP dynamics and lineage specification, we generated dual-reporter mice (PRURD2) by crossing D2.B10-Dmdmdx/J (D2-mdx) mice with FAP and brown/beige adipose tissue (BAT) reporter lines. Corresponding control mice (PRURDBA) were established on the DBA/2J background. At 12 months, heart, diaphragm, and tibialis anterior (TA) muscles were collected for histological analysis. FAPs were isolated via FACS and subjected to single-cell RNA sequencing. PRURD2 mice exhibited increased fibrosis across all muscles compared to controls ( < 0.01) and a significant rise in PDGFRα-GFP + FAPs ( < 0.05). UMAP clustering identified 11 distinct FAP subpopulations, with the fibrosis-associated CD55 cluster enriched in PRURD2 mice. Pseudotime analysis showed lineage progression from progenitor clusters toward the fibrogenic CD55 cluster. CellChat analysis indicated increased interactions in PRURD2 mice involving fibrosis-related pathways like COLLAGEN, TGF-β, WNT, NOTCH, and ANGPTL. Additionally, fibrosis-related signaling pathways such as THY1, TWEAK, EPHA, EPHB, and SEMA6 showed increased interactions among FAP clusters in PRURD2 mice. Differential gene expression analysis revealed top upregulated genes including , , and . PRURD2 mice develop severe fibrosis in skeletal and cardiac muscle, driven by FAP-induced signaling pathways and genes. This model is valuable for understanding muscle fibrosis in DMD and developing anti-fibrotic therapies. - Source: PubMed
Publication date: 2026/04/24
Fusagawa HiroyoriLau JustinSharma SankalpLiu MengyaoSamimi YusefFranchet-Schaer GabrielFang AshleyFusagawa MinamiKim HubertFeeley Brian TLiu Xuhui - A disintegrin and metalloproteinase 12 (ADAM12) is known to be involved in chondrocyte proliferation and is upregulated in the synovial tissue of osteoarthritis (OA). However, the underlying mechanisms of ADAM12 on rheumatoid arthritis (RA) synovial cell proliferation remain unknown. Here, we investigated the role of ADAM12 in the proliferation of RA synovial fibroblasts (RASFs). The expression and localization of ADAM12 in RA synovial tissues were examined by immunohistochemistry and compared with OA and healthy control (HC) synovial tissues. The effect of inflammatory cytokines (TNF-α, TGF-β1, and PDGF-BB) on ADAM12 expression in RASFs from RA patients was examined by real-time RT-PCR. The effect of ADAM12 knock-down by ADAM12 siRNA and ADAM12 overexpression on cell proliferation of RASFs were examined by WST-1 assay. ADAM12 was identified predominantly in RA synovial tissue rather than OA and HC synovial tissues. Stimulation with TGF-β1 upregulated the expression of ADAM12 and cell proliferation of RASFs. ADAM12 siRNA suppressed TGF-β1-induced cell proliferation of RASFs, while ADAM12 overexpression promoted the cell proliferation of RASFs. These findings demonstrate that ADAM12 may have a key role in TGF-β1-induced cell proliferation of synovial fibroblasts in patients with RA. - Source: PubMed
Lin DetingHorita MasahiroWatanabe MasahitoHasei JoeOhtsuki TakashiOtsuka NoriakiIchikawa ChinatsuShimizu NoriyukiNaniwa ShuichiOzaki ToshifumiNishida Keiichiro - Increasing evidence suggests that disulfidptosis plays a crucial role in tumorigenesis and progression. This study aimed to identify biomarkers closely associated with disulfidptosis in anaplastic thyroid carcinoma (ATC). Utilizing ATC-related datasets (GSE65144, GSE9115, GSE27155, and GSE53072) in conjunction with disulfide bond-related genes (DRGs) identified in the literature, differentially expressed genes (DEGs) were screened from the GSE65144 and GSE9115 datasets. A total of 113 common DEGs were identified through cross-sectional analysis. Weighted gene co-expression network analysis (WGCNA) was employed to screen genes related to disulfidptosis and ATC, and five biomarkers-ATP1B3, TFF3, LGALS1, ADAM12, and COL1A2-were identified using machine learning algorithms. A nomogram model constructed based on these markers demonstrated high accuracy. In vitro validation revealed that ATP1B3 knockdown significantly inhibited tumor growth, indicating its potential anti-ATC activity. Furthermore, laser confocal microscopy, flow cytometry, and other experimental methods suggested a correlation between ATP1B3 and disulfidptosis. These findings highlight ATP1B3, TFF3, LGALS1, ADAM12, and COL1A2 as potential disulfidptosis-related biomarkers in ATC. This study provides a theoretical foundation for understanding the role of disulfidptosis in ATC pathogenesis and suggests that ATP1B3 may serve as a promising therapeutic target. - Source: PubMed
Publication date: 2026/04/22
Teng WeidongGuo YawenDing LinglingZhou AoniGuo YehaoHe JiantongZhang LirongYu HaolanTao ZekaiWang JiafengXu JiajieTan ZhuoJiang Liehao - Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, and cervical lymph node metastasis significantly impacts patient prognosis. This study aimed to develop interpretable artificial intelligence models based on transcriptomics to predict PTC occurrence and cervical lymph node metastasis, while exploring the heterogeneity of risk factors across different regions. We obtained 419 samples from the GEO database, originating from Asia, Europe, and America, comprising 158 normal samples, 203 PTC samples, and 58 metastatic samples. After comparing multiple machine learning algorithms, deep neural networks (DNN) demonstrated superior performance and were used to construct the PTC diagnostic and metastasis predictive models. The optimized PTC diagnostic model achieved an AUC of 0.987 with an accuracy of 0.945, while the PTC metastasis predictive model reached an AUC of 0.998 with an accuracy of 0.987. Model interpretation using SHapley Additive exPlanations (SHAP) and Kolmogorov-Arnold Networks (KAN) methods identified SYT1, REN, CNTN5, and ADAM12 as critical features for PTC diagnosis, whereas COL9A1, CYP4F3, and GAD1 were key predictors for PTC metastasis. Stratification analysis revealed regional differences in risk factors for PTC occurrence, while factors promoting PTC metastasis exhibited commonalities across different regions. Pathway enrichment analysis indicated that regulation of hormone levels and cell population proliferation were common pathways involved in both PTC occurrence and metastasis. Finally, we developed online predictive platforms based on the Streamlit framework to facilitate transparent model exploration and risk estimation. These tools are publicly accessible research-use prototypes intended for model demonstration and interpretability visualization. Because they require standardized gene-expression inputs and have not undergone prospective clinical validation, they should not be used as standalone tools for clinical diagnosis, risk stratification, or treatment decision-making. Overall, our findings identify candidate transcriptomic markers associated with PTC occurrence and lymph node metastasis and provide a basis for future translational evaluation. - Source: PubMed
Publication date: 2026/04/18
Zhang ZhigangLiu HongyuZhao ZhengTan GuoyuZhao YangLiu Xun - Colorectal cancer (CRC) remains a major global health challenge, primarily due to late-stage diagnosis and high metastatic potential. Effective management requires novel diagnostic and prognostic strategies, with a growing focus on molecular biomarkers. A Disintegrin and Metalloproteinase (ADAM) proteins, characterized by unique proteolytic activity, play a fundamental role in tumorigenesis by regulating tumor growth, epithelial-mesenchymal transition (EMT), and metastasis. Based on recent investigations, among all ADAMs, ADAM8, ADAM9, ADAM12, ADAM15, and ADAM17 have been proved to play an important role in the CRC pathogenesis. Thus, this review underscores the potential of selected ADAM family members as promising candidates for biomarkers of CRC. Elevated ADAM8, ADAM9, ADAM12 and ADAM17 levels were observed in CRC tissues and correlated with more advanced tumor stage, while increased serum ADAM15 concentrations associated with the presence distant metastases. Moreover, ADAM9, ADAM12, ADAM15 and ADAM17 levels were associated with poorer survival, whereas ADAM8 overexpression was found to be independent prognostic factor for CRC patients' survival. In addition, the measurement of serum ADAM15 concentrations, especially in combination with well-established tumor marker-CEA improved the diagnosis of patients with this malignancy. In conclusion, selected ADAM are critical contributors to the development and progression of CRC, affecting tumor growth, EMT, and metastasis. ADAM8, ADAM9, ADAM12, ADAM15 and ADAM17 were identified as promising biomarkers for the assessment of CRC progression and proved to be prognostic indicators for patients' survival. Further validation through large prospective studies and standardized assays is necessary to establish their potential in clinical practice. - Source: PubMed
Publication date: 2026/04/01
Romanowicz AdriannaŁukaszewicz-Zając MartaMroczko Barbara