S100A2, human, unlabelled
- Known as:
- S100A2, H. sapiens, unlabelled
- Catalog number:
- 201SA02_H
- Category:
- -
- Supplier:
- ProtEra
- Gene target:
- S100A2 human unlabelled
Related genes to: S100A2, human, unlabelled
- Gene:
- S100A2 NIH gene
- Name:
- S100 calcium binding protein A2
- Previous symbol:
- S100L
- Synonyms:
- CAN19
- Chromosome:
- 1q21.3
- Locus Type:
- gene with protein product
- Date approved:
- 1993-10-04
- Date modifiied:
- 2016-10-05
Related products to: S100A2, human, unlabelled
Related articles to: S100A2, human, unlabelled
- The increase in incidence of early-onset pancreatic cancer (EOPC) is of concern and poorly understood. The aim of this study was to investigate the clinical outcomes of surgically resected patients with EOPC and the potential molecular heterogeneity between EOPC and late age-onset disease. - Source: PubMed
Dreyer Stephan BBryce AdamFroeling FiekeJackson ShannonSantana LeonorDickson Euan JCoats MariaMcKay ColinHolroyd DavidBiankin Andrew VJamieson Nigel BChang David K - : Primary open-angle glaucoma (POAG) is a leading cause of irreversible blindness worldwide, characterized by progressive optic nerve degeneration and marked molecular heterogeneity. Increasing evidence indicates that metabolic dysregulation and immune remodeling contribute to POAG pathogenesis; however, the underlying regulatory networks and reliable diagnostic biomarkers remain incompletely defined. : Bulk transcriptomic and single-cell RNA sequencing (scRNA-seq) datasets of trabecular meshwork tissues were retrieved from Gene Expression Omnibus (GEO). Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify disease-associated modules. A machine learning framework was applied to construct classification models. Estimated immune-cell fractions were assessed using CIBERSORT, followed by pathway and transcription factor analyses. Single-cell analysis was conducted to examine the cell type-specific expression patterns. : A total of 195 differentially expressed genes were identified between POAG and control samples. WGCNA revealed a lactylation-related module strongly correlated with disease status. Machine learning identified and as candidate diagnostic biomarkers with consistent classification performance across datasets. Immune infiltration analysis suggested alterations in the immune microenvironment in POAG. Single-cell data showed that the model genes exhibited sparse but non-uniform expression across cell populations. : This integrative analysis prioritizes and as candidate diagnostic biomarkers for POAG and indicates potential associations with immune-metabolic regulatory mechanisms. - Source: PubMed
Publication date: 2026/03/31
Xu YuFu XinGong YajunZeng FangyuanTang MinHu SixianHuang GuangyiTu TianxianZhou Xiaolai - [This retracts the article DOI: 10.3727/096504020X16100888208039.]. - Source: PubMed
Publication date: 2026/04/22
- Despite advancements in multimodal therapies, oral squamous cell carcinoma (OSCC) continues to exhibit poor clinical outcomes, particularly in advanced and recurrent cases. Recent studies have identified the calcium-binding protein S100A2 as a critical mediator of OSCC progression and resistance to therapy. Our prior work demonstrated that cytoplasmic overexpression of S100A2 in oral cancer patients is associated with tumor recurrence and reduced survival. Given its reported role in promoting epithelial-to-mesenchymal transition (EMT), cellular proliferation, and invasiveness, we investigated the in vitro functional impact of S100A2 inhibition in OSCC. - Source: PubMed
Publication date: 2026/04/01
Kumar ManishPrasad Chandra PrakashChopra ChitrakshiThapa SoniaChauhan Shyam Singh - Cutaneous squamous cell carcinoma (cSCC) involves complex immune interactions. This study aimed to identify a T cell-related gene signature to characterize the immune landscape and aid in molecular diagnosis. We integrated single-cell RNA sequencing (scRNA-seq) and five bulk microarray datasets, utilizing an independent RNA-seq cohort for external validation. Feature genes were identified from the intersection of scRNA-seq-defined T cell-related genes (TRGs) and bulk differentially expressed genes using machine learning. A diagnostic nomogram was constructed, and its performance was assessed via ROC curves. In addition, immune infiltration, immunofluorescence staining, drug interactions, and clinical expression (qRT-PCR) were evaluated. Screening yielded 28 T cell-related DEGs enriched in extracellular matrix functions. machine learning selected a core signature: APOE, CYBA, and S100A2. The diagnostic model demonstrated high diagnostic performance in the studied cohorts (AUC > 0.9) across training and external validation cohorts. Clinically, qRT-PCR supported significant upregulation of CYBA and S100A2. APOE exhibited distinct immunomodulatory connectivity, correlating positively with Th17 cells and negatively with Tregs, whereas CYBA and S100A2 were associated with Treg infiltration. Immunofluorescence results revealed significantly elevated levels of S100A2 and Foxp3 in cSCC tissues compared to the control group. Pharmacogenetic analysis highlights the association of these genes, particularly the APOE gene, with drug response. This T cell-associated signature highlights the potential link between molecular diagnosis and immune characterization. Specifically, CYBA and S100A2 are identified as promising diagnostic candidate signatures, while APOE may reflect immunomodulatory heterogeneity. These findings offer insights for developing diagnostic strategies and targeted immunotherapies in cSCC. - Source: PubMed
Publication date: 2026/04/05
Xu TaoYao GuotaiWang YuLi WeiMou ShuangmengWang Zhongzhi