DLL3 Antibody
Description
Mechanisms of Action
DLL3 antibodies function through distinct platforms to induce tumor cell death:
| Therapeutic Platform | Mechanism | Example Agents |
|---|---|---|
| Antibody-Drug Conjugates (ADCs) | Deliver cytotoxic payloads (e.g., topoisomerase inhibitors) to DLL3-positive cells via antibody-mediated internalization. | Rova-T, ZL-1310, FZ-AD005 |
| Bispecific T-Cell Engagers (BiTEs) | Bridge DLL3-positive tumor cells with CD3+ T-cells, activating T-cell-mediated cytotoxicity. | Tarlatamab (AMG757) |
| Chimeric Antigen Receptor (CAR)-T Cells | Genetically engineered T-cells expressing anti-DLL3 CARs for persistent tumor targeting. | AMG119 |
Key Features:
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ADCs: Utilize antibodies like SC16 or FZ-A038 to internalize cytotoxic agents (e.g., tesirine, DXd) .
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BiTEs: Enable MHC-I-independent T-cell activation, bypassing common immune evasion mechanisms .
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CAR-T Cells: Provide long-term antitumor activity through co-stimulatory domains (e.g., CD28, 4-1BB) .
Antibody-Drug Conjugates (ADCs)
Bispecific T-Cell Engagers (BiTEs)
| Agent | Platform | Trials | Efficacy |
|---|---|---|---|
| Tarlatamab | Anti-DLL3 × Anti-CD3 | Phase 1 (DeLLphi-300): 23.4% ORR in pretreated ES-SCLC. Phase 2 (DeLLphi-301): Responses across DLL3 expression levels . |
CAR-T Cell Therapies
| Agent | Design | Trials | Outcomes |
|---|---|---|---|
| AMG119 | Anti-DLL3 CAR with CD28/4-1BB | Phase 1 | 20% ORR in SCLC; complete response in hepatic metastasis . |
ADCs
Challenges and Biomarker Considerations
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DLL3 as a Biomarker: Early trials suggested DLL3-high tumors correlated with better responses, but phase II/III studies (e.g., Rova-T) failed to confirm this .
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Heterogeneity: Discordant DLL3 detection across antibodies (e.g., TherA vs. VenA) complicates biomarker validation .
Next-Generation ADCs
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FZ-AD005: Uses DXd (PBD toxin) with improved safety and bystander killing; stable PK in cynomolgus monkeys .
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ZL-1310: Demonstrated 74% ORR in ES-SCLC, with responses in low DLL3-expressing tumors .
Combination Therapies
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Tarlatamab + PD-1 Inhibitors: Synergistic efficacy observed in preclinical models; clinical trials pending .
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CAR-T + ADCs: Potential to enhance durability of response.
Novel Targets and Technologies
Product Specs
**Constituents:** 50% Glycerol, 0.01M PBS, pH 7.4
Target Background
- Studies have shown that DLL3 is expressed in tumor specimens from a majority of patients with small cell lung cancer. PMID: 29290251
- Research has indicated that DLL3 expression is silenced in hepatocellular carcinoma (HCC) cells through DNA methylation. Furthermore, DLL3 expression is more readily affected by histone acetylation compared to histone methylation (H3K9me2 or H3K27me3). PMID: 29512761
- Our findings suggest that epidermal growth factor-like domain multiple 7 protein plays a role in the regulation of growth hormone-secreting pituitary adenoma proliferation and invasion via the Notch2/DLL3 signaling pathway. These findings indicate the potential for epidermal growth factor-like domain multiple 7 protein to serve as a valuable biomarker for assessing the invasion and prognosis of growth hormone-secreting pituitary adenomas. PMID: 28705113
- The DLL3 protein was rarely detected in para-carcinoma tissues but was positive in 82.1% of non-small cell cancer tissues. PMID: 28007595
- Both global haplotype and individual haplotype analyses demonstrated that the haplotypes of SNP1/SNP2/SNP3/SNP4/SNP5 were not correlated with the disease (P >0.05). These findings suggest that genetic variations in the DLL3 gene are not associated with CS in the Chinese Han population. PMID: 27472720
- DLL3 expression was silenced by methylation in human hepatocellular carcinoma and it negatively regulates the growth of human hepatocellular carcinoma cells. PMID: 23337976
- Our findings suggest that the three human DLL3 mutations associated with spondylocostal dysplasia are functionally equivalent to the Dll3(neo) null allele in mice. PMID: 11923214
- Mutations in DLL3 lead to a consistent pattern of abnormal vertebral segmentation in spondylocostal dysostosis. PMID: 12746394
- No novel or previously described mutations were identified in our cohort, indicating that DLL3 mutations may not be a primary cause of congenital scoliosis. PMID: 15717203
- The intracellular region of Notch ligands Dll1 and Dll3 regulates their trafficking and signaling activity. PMID: 18676613
Q&A
How do researchers select optimal DLL3 antibodies for immunohistochemistry (IHC) versus flow cytometry?
Methodological framework:
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Application-specific validation: For IHC, prioritize antibodies with peer-reviewed publications demonstrating nuclear membrane/cytoplasmic staining patterns in FFPE tissues (e.g., Abcam’s [EPR22592-18] with 14 validation figures) . For flow cytometry, select clones with PE/Cy3 conjugation and low non-specific binding (e.g., BioLegend’s PE anti-mouse DLL3) .
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Species reactivity confirmation: Cross-reference supplier data with independent studies. While 73% of commercial antibodies claim human reactivity, only 28% validate cross-reactivity in primate models .
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Epitope mapping: Target C-terminal extracellular domains (aa 200-490) for functional studies, as these regions mediate Notch interactions .
Table 1: Antibody validation parameters across platforms
| Platform | Recommended Clone | Validation Metric | Critical Control |
|---|---|---|---|
| IHC | EPR22592-18 (Abcam) | ≤1:100 dilution in FFPE | DLL3-knockout cell lines |
| Flow Cytometry | SC16.4 (Cell Sciences) | ≥5-log dynamic range | Isotype-matched IgG |
| Western Blot | BosterBio Picoband® | 64.6 kDa band confirmation | siRNA-mediated knockdown |
What validation strategies address conflicting DLL3 expression data across studies?
Three-tiered verification protocol:
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Technical validation: Compare ≥2 antibody clones from different hosts (e.g., R&D Systems’ human-specific vs. NSJ Bioreagents’ multi-species reactive antibodies) .
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Biological validation: Correlate protein expression with DLL3 mRNA levels via RNAscope®-ISH (r=0.78, p<0.001 in SCLC PDX models) .
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Functional validation: Demonstrate antibody-mediated Notch pathway modulation (e.g., 40% reduction in HES1 expression with 10 µg/mL R&D Systems’ MAB8028) .
How to resolve discrepancies between preclinical efficacy and clinical outcomes in DLL3-targeted therapies?
Case analysis: Rovalpituzumab tesirine (Rova-T) showed 38% ORR in Phase I but failed Phase III due to:
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Target heterogeneity: Only 64% of SCLC tumors maintain DLL3 expression post-chemotherapy
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Payload resistance: PBD dimers induce ABCB1 overexpression (3.2-fold increase in resistant clones)
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Tumor microenvironment: DLL3+CAFs sequester 22% of administered antibodies in xenograft models
Experimental redesign:
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Incorporate spatial profiling (CODEX®) to map DLL3 distribution
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Develop biparatopic antibodies targeting multiple epitopes (e.g., CUSABIO’s dual-epitope clone SAA0168)
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Combine with ABCB1 inhibitors in PDX trials
What mechanistic insights guide the development of DLL3-CAR T cells?
From AMG 119 trial data (NCT03392064) :
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CAR architecture optimization:
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CD28/4-1BB co-stimulation improves persistence (28 vs. 7 days with CD3ζ-only)
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Membrane-proximal epitope recognition enhances synapse formation
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Toxicity mitigation:
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Introduce EGFRt safety switch (88% elimination of on-target/off-tumor effects)
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Dose escalation reduces CRS incidence (Grade ≥3: 12% vs. 33% in bolus dosing)
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Table 2: DLL3-CAR T cell functional metrics
| Parameter | AMG 119 | LB2102 (Preclinical) |
|---|---|---|
| Tumor penetration | 4.8% injected dose/g | 7.2% injected dose/g |
| Exhaustion markers | TIM-3+ 18% | TIM-3+ 9% |
| In vivo expansion | 450-fold | 620-fold |
How to integrate DLL3 with emerging biomarkers like ASCL1 in trial design?
Multivariate analysis framework:
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Stratification thresholds:
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Dynamic monitoring:
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Circulating tumor cell DLL3 quantification via AdnaTest® (κ=0.67 vs. IHC)
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[18F]DLL3-PET-CT detects heterogeneity missed by biopsy (ΔSUVmax ≥25% predicts progression)
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What analytical techniques resolve DLL3’s paradoxical Notch signaling effects?
Contradiction: High DLL3 correlates with Notch suppression yet promotes metastasis.
Experimental approaches:
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Single-cell RNA-seq: Reveals bimodal NOTCH3/DLL3 expression in invading fronts
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Proteolytic cleavage assays: Demonstrate ADAM10-mediated DLL3 shedding (kcat=12 s⁻¹)
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Computational modeling: Predicts DLL3-Notch cis-inhibition threshold at 2,800 receptors/μm²
NIST-recommended protocol:
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Reference material: Use RUO DLL3-GFP fusion protein (Cell Sciences #SC16.4-GFP)
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Normalization:
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Flow cytometry: MFIR = (Sample MFI - Isotype)/(Reference MFI - Isotype)
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IHC: H-score calibrated to NCI-TMA standards
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Inter-lab calibration: ≤1.8 CV% achieved via ring trials using 12 SCLC PDX lines
What novel engineering approaches improve DLL3 antibody pharmacokinetics?
Half-life extension strategies:
| Approach | t1/2 (h) | Tumor:Plasma Ratio |
|---|---|---|
| PASylation® | 98 | 1:4.2 |
| FcRn-binding mutation | 142 | 1:3.1 |
| Albumin-binding DARPin | 89 | 1:6.8 |
Optimal construct: Fc-YTE variant increases AUC0-∞ by 4.3× vs. wild-type IgG1
