EDNRA antibodies target the endothelin receptor type A, a 427-amino-acid transmembrane protein (48.7 kDa) expressed in vascular smooth muscle cells, pericytes, and tumor microenvironments . EDNRA binds ET-1 with high affinity, activating pathways like PI3K-AKT, WNT, and Hedgehog, which are implicated in cancer progression and immune regulation .
EDNRA antibodies are validated for:
Western Blot (WB): Detects EDNRA in human, mouse, and rat tissues .
Immunohistochemistry (IHC): Identifies EDNRA in gastric cancer (STAD), myeloma bone marrow, and vascular smooth muscle cells .
Immunofluorescence (IF): Visualizes EDNRA co-localization with immune markers (e.g., renin in kidney cells) .
Flow Cytometry (FCM): Quantifies EDNRA expression in transfected cell lines .
Gastric Cancer (STAD): High EDNRA expression correlates with advanced T stage (HR = 1.719, P = 0.011), poor survival (HR = 1.638, P = 0.004), and immune infiltration (NK cells: R = 0.599, P < 0.001) .
Colorectal Cancer: EDNRA upregulation drives tumor progression via STAT3 signaling and predicts poor prognosis .
Myeloma: EDNRA+ mesenchymal cells expand in tumor-infiltrated bone marrow, promoting disease progression .
EDNRA regulates macrophage infiltration (R = 0.653, P < 0.05) and synergizes with immune checkpoints (PDCD1LG2, HAVCR2) to suppress antitumor immunity .
EDNRA mediates ET-1-induced vasoconstriction and retinal ganglion cell death in hypertension models .
| Characteristic | HR (95% CI) | P-value |
|---|---|---|
| EDNRA (High vs. Low) | 1.638 (1.174–2.286) | 0.004 |
| T stage (T3&T4 vs. T1&T2) | 1.719 (1.131–2.612) | 0.011 |
| Macrophage infiltration | 2.183 (0.971–4.910) | 0.059 |
EDNRA Antagonists: Inhibit tumor growth in CRC and ovarian cancer .
Immune Checkpoint Synergy: EDNRA correlates with PD-1/CTLA-4 blockade resistance, suggesting combinatorial targeting .
Current antibodies exhibit variable cross-reactivity (e.g., Alomone’s #AER-001 works best in rodents ). Future studies should optimize human-specific clones and explore EDNRA’s role in immunotherapy resistance.
EDNRA (endothelin receptor type A) is a G-protein coupled receptor that functions as a receptor for endothelin-1. In humans, the canonical protein has 427 amino acid residues with a molecular mass of 48.7 kDa and is primarily localized in the cell membrane. Up to five different isoforms have been reported, and the protein undergoes post-translational modifications, particularly glycosylation. EDNRA is a member of the G-protein coupled receptor 1 family and serves as a marker for Deep-Layer Corticothalamic And 6B Neurons, Cerebral Cortex MGE Interneurons, and Gray Matter CGE Interneurons .
EDNRA antibodies are employed in multiple experimental techniques:
| Application | Typical Dilution | Sample Type | Special Considerations |
|---|---|---|---|
| Western Blot | 1:100-1:1000 | Cell/tissue lysates | Use PVDF membranes, BSA blocking |
| IHC | 1:100 | Paraffin sections | Overnight incubation at 4°C |
| IF | 1:50-1:200 | Fixed cells/tissues | Careful membrane permeabilization |
| ELISA | 1:100-1:500 | Serum, cell supernatants | Validate specificity |
| Flow Cytometry | 1:50-1:100 | Cell suspensions | Surface vs. intracellular protocols |
Over 90 citations in scientific literature describe EDNRA antibody use in research contexts .
Proper validation requires:
Positive controls using tissues or cell lines with known EDNRA expression
Negative controls with tissues/cells lacking EDNRA expression
Technical controls including primary antibody omission and isotype controls
Specificity testing using EDNRA knockdown or knockout samples
Cross-reactivity assessment across species if performing comparative studies
Application-specific validation (different for WB, IHC, IF, etc.)
Based on published research, optimal EDNRA immunohistochemistry involves:
Fixation in neutral formaldehyde
Paraffin embedding with 4 μm sectioning
Streptavidin-peroxidase immunohistochemical method for enhanced staining
Overnight incubation at 4°C with anti-EDNRA (1:100 dilution)
Light counterstaining with hematoxylin
Evaluation by two independent pathologists assessing both staining intensity and percentage of stained cells in representative areas
Multiple bands in EDNRA Western blots may result from:
Presence of multiple protein isoforms (up to 5 have been documented)
Post-translational modifications, particularly glycosylation
Proteolytic degradation during sample preparation
Non-specific binding or cross-reactivity with related receptors
Recommendations include using fresh samples with protease inhibitors, optimizing reducing conditions, and comparing patterns with positive control samples.
| Method | Advantages | Limitations | Best Applications |
|---|---|---|---|
| qPCR | High sensitivity, quantitative | Measures mRNA not protein | Gene expression studies |
| Western Blot | Detects protein, shows isoforms | Semi-quantitative | Protein expression screening |
| ELISA | Highly quantitative | Limited spatial information | Secreted or soluble forms |
| IHC/IF | Spatial information, cell-specific | Semi-quantitative | Tissue localization studies |
| Flow Cytometry | Single-cell resolution | Requires cell suspensions | Cell surface expression |
EDNRA expression has significant prognostic value in various cancers. Research has shown that EDNRA expression levels are associated with patient's age and tumor stage. Receiver Operating Characteristic (ROC) curve analysis has demonstrated the diagnostic value of EDNRA in cancer detection. Kaplan-Meier and Cox regression analyses have validated the survival and prognostic significance of EDNRA expression, which has been further confirmed through immunohistochemistry cohort studies .
EDNRA expression shows significant correlations with immune cell infiltration in tumor microenvironments:
| Immune Cell Type | Correlation with EDNRA | p-value |
|---|---|---|
| Mast cells | Positive | <0.001 |
| Memory CD4+ T cells | Positive | <0.001 |
| M2 macrophages | Positive | <0.001 |
| NK cells | Positive | 0.032 |
| Monocytes | Positive | 0.035 |
| M1 macrophages | Positive | 0.024 |
| Plasma cells | Positive | 0.007 |
| Memory B cells | Positive | 0.001 |
These correlations have been established using advanced computational methods including CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) .
EDNRA plays a critical role in tumor immune suppression by modulating the secretion of EV PD-L1, thus affecting T cell activity and reducing the efficacy of immune checkpoint blockade therapy. Research has demonstrated that inhibiting EDNRA with drugs such as macitentan can enhance antitumor immunity and improve immunotherapy outcomes. Patients with lower EDNRA expression levels generally demonstrate superior responses to immunotherapy treatments .
Gene Set Enrichment Analysis has identified several key signaling pathways associated with EDNRA in cancer progression, including:
JAK-STAT signaling pathway
TGF-β signaling pathway
These pathways are critical for understanding how EDNRA influences tumor development, immune response modulation, and potential therapeutic targets .
Effective EDNRA knockdown for mechanistic studies can be accomplished using lentiviral shRNA vectors. Published research has successfully employed:
shRNA sequence 1: TCTTCATTTAAGCCGTATATT
shRNA sequence 2: GCTCAGGATCATTTACCAGAA
The lentiviral vector pLVX-shRNA1 with cloning sites BamHI-EcoR1 has been effectively used for EDNRA knockdown studies. This approach has demonstrated that EDNRA knockdown inhibits proliferation and migration in cancer cell lines including MDA-MB-231 and HepG2 .
Several bioinformatic resources have proven valuable for EDNRA research:
| Database/Tool | URL | Primary Application |
|---|---|---|
| TIMER | https://cistrome.shinyapps.io/timer/ | Immune infiltration analysis |
| CIBERSORT | https://cibersort.stanford.edu/ | Calculating immune cell proportions |
| TISIDB | http://cis.hku.hk/TISIDB/index.php | Tumor-immune system interactions |
| GSEA | - | Pathway enrichment analysis |
| ImmuCellAI | http://bioinfo.life.hust.edu.cn/web/ImmuCellAI/ | Immune cell infiltration estimation |
These tools enable comprehensive analysis of EDNRA's role in various cancers and immune responses .
Critical factors include:
Fixation protocols (duration and fixative type)
Antigen retrieval methods (heat-induced vs. enzymatic)
Antibody concentration and incubation conditions
Detection system sensitivity
Sample processing and storage conditions
Endogenous enzyme activities interfering with detection
Optimization strategies should include testing multiple antigen retrieval methods, antibody titration, and appropriate positive and negative controls.
Specificity confirmation methods include:
Testing in tissues with known EDNRA expression patterns
Comparing results with multiple antibodies targeting different EDNRA epitopes
Using EDNRA knockout/knockdown samples as negative controls
Peptide competition assays to verify epitope specificity
Western blot analysis to confirm detection of appropriate molecular weight bands
Cross-validation with orthogonal detection methods (e.g., mRNA expression)