CDCP1 ELISA kit
- Known as:
- CDCP1 Enzyme-linked immunosorbent assay test reagent
- Catalog number:
- DL-CDCP1-Hu
- Product Quantity:
- 96T
- Category:
- Elisa Kits
- Supplier:
- WDSTD
- Gene target:
- CDCP1 ELISA kit
Related genes to: CDCP1 ELISA kit
- Gene:
- CDCP1 NIH gene
- Name:
- CUB domain containing protein 1
- Previous symbol:
- -
- Synonyms:
- CD318, SIMA135
- Chromosome:
- 3p21.31
- Locus Type:
- gene with protein product
- Date approved:
- 2005-02-24
- Date modifiied:
- 2016-10-05
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- Carotid plaque (CP) is a surrogate marker of cardiovascular disease, and high-risk morphology significantly increases the risk of stroke. The aim of this study was to develop advanced machine learning (ML) models to predict the presence of CP in the general population. The study involved 693 participants from the Polish Longitudinal University Study - Bialystok PLUS, a representative sample of the local population. The analysis used 460 OLINK protein biomarkers. The data were analysed using the BORUTA algorithm based on the random forest classifier method. We identified 42 significant biomarkers associated with CP, the most important of which were GDF-15, CDCP1, CHIT1, FLT3LG, CDH2 and CRTAC1. Interestingly, the top 6 biomarkers had a highly speculative or unresolved association with atherosclerosis. Next, we developed an ML-based CP fingerprint comprising 25 biomarkers, which showed good internal cross-validated discrimination in subjects aged 30-70 years. We also generated a network of interactions for the 42 biomarkers using STRING database modules, and performed a functional analysis to assess the biological significance of the interactions detected. These results are hypothesis-generating and require external, prospective validation to identify cause-and-effect relationships. - Source: PubMed
Publication date: 2026/09/24
Szpakowicz AnnaLesiński WojciechTuchliński Jakub KRoszkowska UrszulaDubatówka MarlenaStachurska ZofiaKondraciuk MarcinRudnicki Witold RKamiński Karol A - Pancreatic ductal adenocarcinoma (PDAC) is associated with high mortality owing to late diagnosis, aggressive tumor biology, and limited clinically useful early diagnostic and prognostic biomarkers. This study provides an exploratory evaluation of the expression profile, survival associations, co-expressed genes, functional association networks, and regulatory relationships of () in pancreatic cancer using multi-platform bioinformatic approaches. We conducted a comprehensive multi-platform bioinformatic analysis using multiple publicly available datasets and platforms, including TCGA/GTEx, GEO, GEPIA3, HPA, CPTAC/UALCAN, TNMplot, Kaplan-Meier Plotter, DoSurvive, TIMER 3.0, STRING, TargetScan, miRDB, ENCORI and lncRNADisease. Gene expression patterns, survival associations, immune cell infiltration and regulatory non-coding RNA networks were systematically investigated. A STRING-derived protein functional association network was evaluated. expression patterns were additionally assessed in external GEO datasets, including GSE62165, GSE71729, and GSE183795. In summary, expression was elevated in pancreatic cancer compared with normal pancreatic tissues, was detectably expressed across multiple pancreatic cancer cell lines, and was increased in patient-derived PDAC samples. ROC analysis showed that expression discriminated PDAC tumor tissues from adjacent non-tumor pancreatic tissues, with an AUC of 0.795 (95% CI: 0.719-0.871) indicating exploratory transcriptomic discrimination rather than clinical diagnostic performance. Exploratory survival analyses showed that elevated expression was associated with unfavorable overall survival and disease-free outcomes, while multivariable Cox analyses showed that this association persisted after adjustment for the covariates available within the analyzed dataset. GEO-based analyses supported increased expression in early-stage pancreatic cancer samples, although metastatic expression patterns varied across datasets. Correlation and interaction analyses revealed positive associations between and PDAC-related genes, including , , , , and , as well as high-confidence STRING functional associations with V-ATPase components and RNASEK. Furthermore, was positively correlated with lncRNA UCA1 and negatively correlated with miR-582-5p. Collectively, these findings identify reproducible expression and survival-associated patterns involving MEAK7 across the analyzed datasets and provide a hypothesis-generating framework for further investigation of its potential biological role in PDAC. Experimental studies and prospectively characterized patient cohorts are required before any clinical, prognostic, diagnostic, or therapeutic implications can be established. - Source: PubMed
Publication date: 2026/08/25
Uyaner Kan MeltemAyan Durmus - Multiple sclerosis (MS) disease activity and treatment response may be influenced by systemic health factors, including cardiometabolic disease (CMD). This study evaluated how CMD influences inflammatory protein profiles and whether CMD modifies the effect of disease-modifying therapy (DMT). A retrospective study was conducted within a single academic MS center. All participants underwent commercial multi-analyte proteomic testing (Octave® Bioscience). CMD was defined as hypertension, type 2 diabetes mellitus, and/or dyslipidemia. Four groups were analyzed: untreated without CMD, untreated with CMD, DMT-treated without CMD, and DMT-treated with CMD. A multivariable variability index (MVI) was calculated across 18 age- and sex-adjusted proteins, and CMD burden (one, two, or three conditions) was assessed. A total of 287 MS individuals were included (84% White, 78% female). Among untreated individuals, those with CMD demonstrated significantly higher concentrations of proteins associated with acute MS disease activity, including MIP 3-alpha (CCL20) (p = 0.0078), CUB domain-containing protein 1 (CDCP1) (p = 0.0176), and TRAIL-R1 (TNFRSF10A) (p = 0.0002). In treated individuals, CMD was associated with higher levels of monokine induced by gamma interferon (CXCL9) (p = 0.0025), NfL (p = 0.0201), serpin family A member 9 (p = 0.0291), and TRAIL-R1 (p = 0.0002), as well as lower levels of protogenin (p = 0.0376). MVI values were elevated in both CMD groups. CMD was associated with higher odds of prior relapse and/or MRI activity within two years before proteomic testing (OR 5.48, 95% CI: [1.18-25.40], p = 0.0227). Protein concentrations increased with greater CMD burden. Clinically measurable proteins associated with acute MS disease activity are elevated in individuals with CMD and increase with comorbidity burden, in both DMT-treated and untreated groups. - Source: PubMed
Publication date: 2026/09/10
Okuda Darin TBurgess Katy WWright Crystal MJones-McCreary Morgan CHuddleston Isabella JSantoyo Jose RPunnen Tom GSguigna Peter VTardo Lauren MLebrun-Frénay ChristineStüve OlafTran Diem HMoog Tatum M - Acute inflammatory relapses in primary CNS demyelinating diseases, including relapsing multiple sclerosis (RMS), MOG-antibody-associated disease (MOGAD), and neuromyelitis optica spectrum disorder (NMOSD), drive hospitalization, disability, and socioeconomic burden. Blood-based biomarkers are increasingly used for relapse detection and treatment monitoring. - Source: PubMed
Publication date: 2026/09/07
Chumakova Anastasia PDemetriou MichaelSy Michael - The spatial organization of membrane proteins is an underexplored dimension of cell surface biology. Spatial proximity shapes cellular function and therapeutic targetability, yet efforts to identify tumour-associated antigens (TAAs) have largely focused on expression alone. Here, we developed an industrialized surface protein proximity-mapping workflow to interrogate TAAs within their membrane microenvironments. Using this workflow, we generated 248 proximity maps across 12 receptor tyrosine kinases and 28 tumour cell systems. The resulting atlas enabled the development of MetaMap, a correlation-based analytical framework that defines spatial protein communities and infers conserved proximity relationships among non-targeted proteins, and establishes the concept of tumour-associated proximity antigens (TAPAs), a class of co-targets defined by disease-specific spatial proximity to TAAs rather than expression alone. Integrating these proximity-derived relationships within a multimodal prioritization framework, we identified and validated EGFR-CDCP1 as a TAA-TAPA pair that enhances tumour cell killing across therapeutic modalities. Together, this work advances disease-associated membrane proximity as a guiding principle for the design of precision multispecific therapeutics. - Source: PubMed
Publication date: 2026/09/09
Scandore CodyMalone Clare FMay Christopher Kde Regt Anna KGuernsey JeffMa HayleyDephoure NoahSetter BenHowell Rebecca AJohnson Kendall RFarr Carol LRomero SophiaVignale LydiaVittum TaliDawson EmmaHabtetsion TsadikNardi FrancescaWoodruff BrianMathay MartinSwanson JuliaRusnak MikaelaTon QuynhFarahani Payam EGene Robert WMisurelli JasonCaldwell ZachXu HengyuHornsby MichaelGavin Marc AKlock Heath EEryilmaz ErtanHolland Pamela MLesley Scott AOslund Rob CFadeyi Olugbeminiyi O