Ask about this productRelated genes to: NID2 antibody
- Gene:
- NID2 NIH gene
- Name:
- nidogen 2
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 14q22.1
- Locus Type:
- gene with protein product
- Date approved:
- 2001-06-25
- Date modifiied:
- 2015-11-23
Related products to: NID2 antibody
Related articles to: NID2 antibody
- Ovarian cancer (OC) is a highly invasive disease with a poor prognosis, underscoring the importance of identifying specific biomarkers in early screening to enhance the overall survival of patients with OC. In this study, quantitative methylation-specific PCR was used to investigate the methylation levels of the nidogen-2 (NID2) and cysteine dioxygenase 1 (CDO1) gene promoters in peripheral blood samples from 72 patients with OC and 75 healthy individuals. The results revealed significantly higher methylation levels of the NID2 and CDO1 genes in patients with OC compared with those in healthy controls. NID2 methylation demonstrated a sensitivity of 70.83% and a specificity of 96.00% in predicting OC, whereas CDO1 exhibited a sensitivity of 90.28% and a specificity of 69.33%. The positivity rate of NID2 methylation was elevated in patients with stage III-IV OC compared with those with stage I-II OC and was higher in high-grade serous carcinoma compared with that in ovarian clear cell carcinoma. Additionally, the positivity rate of CDO1 methylation could reach 84.6% in patients with stage I-II OC. Furthermore, the methylation levels of NID2 and CDO1 exhibited a positive correlation with carbohydrate antigen 125 (CA125) levels. Combining the detection of NID2 and CDO1 methylation with CA125 significantly enhanced the sensitivity and specificity of OC detection compared with CA125 detection alone. In conclusion, enhanced methylation of the NID2 and CDO1 genes has emerged as an independent risk factor for OC development. - Source: PubMed
Publication date: 2026/04/20
Wu ShuilianJin JingCao YuanyuanHe XiaofanHou QiangJiang Mingfeng - NID2 is a key component of the BM and plays an important role in ECM organization and tumor-associated microenvironmental remodeling. In this study, full-length recombinant NID2 was used as an antigen to immunize camels, and a nanobody phage display library was constructed from peripheral blood lymphocytes. Using phage display-based screening, nanobodies recognizing distinct epitopes within the NID2 G1G2 and rod-G3 domains were isolated and characterized. Epitope specificity and competition were further analyzed by BLI, allowing the identification of nonoverlapping nanobody pairs. Based on these results, two high-affinity nanobodies were selected to establish a nanobody-based sandwich ELISA for NID2 detection. This assay enabled the detection of recombinant NID2 at concentrations down to 10 ng·mL in human serum. Although the analytical sensitivity is lower than that of some commercial antibody-based ELISA kits, the nanobody-based format offers advantages in terms of recombinant production, scalability, and assay design flexibility. Collectively, this study provides a panel of domain-selective nanobodies against NID2 and establishes a nanobody-based sandwich ELISA as a methodological platform for future investigations of serum NID2 in diagnostic and translational research contexts. - Source: PubMed
Publication date: 2026/03/04
Wen JianchuanCui QianqianLan ZhongyunWang YingjunZhao ShuaiyingFeng WenxuanLiu YunfengHuang QitingZhang DongnaXu Jianfeng - Neuropsychiatric symptoms (NPS), commonly concomitant with Alzheimer's disease (AD), substantially impair the quality of life and accelerate disease progression, yet reliable biomarkers for early identification of individuals at high NPS risk remain elusive. In this study, we leveraged the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), incorporating longitudinal data from 509 participants diagnosed with mild cognitive impairment (MCI) or mild AD at baseline and followed up for 1 and 2 years. The dataset included cerebrospinal fluid (CSF) proteomic profiles comprising 6361 proteins, along with comprehensive data on NPS diagnosis, cognitive function, and AD pathology. LASSO regression and recursive feature elimination were applied to identify NPS-related CSF proteins, followed by random forest modeling to predict NPS risk at baseline, 1 year, and 2 years. Incorporating selected CSF proteins significantly improved NPS prediction compared to the reference model, with AUCs increasing from 0.64 to 0.76 at baseline, 0.63 to 0.80 at 1 year, and 0.63 to 0.81 at 2 years. Notably, Cyclin-Dependent Kinase-Like 2 (CDKL2), Nidogen 2 (NID2), and Lin-7 Homolog B (LIN7B) were consistently associated with NPS across all time points. Among them, CDKL2 and NID2 were significantly associated with AD biomarkers and cognitive scores, and their expression changes were independently validated in cerebrospinal fluid from a mouse model, highlighting their potential as stable predictive biomarkers. Our findings highlight CSF proteomic signatures that robustly predict NPS progression in individuals with MCI and mild AD, offering a framework for early risk stratification and precision intervention in NPS. - Source: PubMed
Han XueZhu ShouqiangZhang HengXia TianjiaoGu Xiaoping - Diabetes mellitus (DM), the ninth leading cause of death worldwide, is characterized by a relative or absolute deficiency of insulin, leading to increased production of advanced glycosylation end-products (AGEs), which further enhances oxidative and nitrosative stress, often leading to a variety of macrovascular and microvascular complications, such as diabetic nephropathy (DN), retinopathy, and neuropathy. Especially, diabetic patients with end stage renal disease (ESRD) usually have concomitant severe peripheral arterial disease. Unfortunately, there is still no effective therapeutic treatment for DM patients combined with DN and diabetic foot ulcer (DFU). Thus, we performed a series of bioinformatics analyses to investigated the molecular mechanisms involved in the occurrence of these two complications. We screened for differentially expressed genes (DEGs) from the Gene Expression Omnibus (GEO) database, namely GSE96804 and GSE134431, and conducted enrichment and protein-protein interaction analyses. Subsequently, we constructed animal models of these two diseases in vivo, and validated the predictions' accuracy using quantitative real-time PCR (qPCR) experiments to confirm the expression levels of mRNA. Finally, we conducted protein-chemical interactions and drug prediction. We identified 104 DEGs, with many of them being involved in inflammation or lipid metabolism. We obtained 7 hub genes closely related to DN and DFU, and verified through animal experiments that the expression trends of 5 of them (NID2, LUM, ECM, LTBP1 and LRRC2) were consistent with the results of bioinformatics analysis. Notably, our study showed that sex hormones including pirinixic acid, testosterone enanthate, and progesterone were predicted to be the most promising drugs, with the combined score of the three being the highest. This finding may potentially provide common therapeutic targets for DN and DFU. Additionally, it is important to understand these networks and hub genes to advance our understanding of the multifaceted complications of DM and the future development of drugs to treat these complications. - Source: PubMed
Publication date: 2025/12/12
Liu JiarongZou YunWang JiaoXu Jixiong - Immunotherapy has progressively gained prominence as a cornerstone therapeutic modality across diverse oncological contexts, with its clinical efficacy intricately linked to the dynamic interactions between the tumor microenvironment (TME) and neoplastic cells. Central to this paradigm is angiogenesis-a quintessential hallmark of cancer-which not only sustains tumor growth but also orchestrates immunomodulatory networks within the TME, thereby profoundly influencing therapeutic responsiveness. However, in the field of bladder cancer (BC), the relationship among angiogenesis and prognosis, immunotherapy response, and immune cell infiltration remains to be further explored. - Source: PubMed
Publication date: 2025/08/29
Cao JinxiaZheng Wang