TNFRSF18 Antibody

What is TNFRSF18/GITR and what role does it play in immune regulation?

TNFRSF18, commonly known as GITR or CD357, is a member of the TNF receptor superfamily. It functions as a co-stimulatory receptor primarily expressed on various immune cells, particularly T cells. The receptor plays crucial roles in modulating immune responses by influencing T cell activation, proliferation, and survival.

GITR is part of the broader tumor necrosis factor receptor superfamily that regulates antigen presentation and adaptive immune activities. Unlike inhibitory immune checkpoints, GITR acts as a co-stimulatory molecule that can enhance anti-tumor immune responses when properly activated . The receptor's activation typically requires molecular clustering induced by its cognate ligand (GITR-L) or through antibody-mediated cross-linking, which triggers downstream signaling cascades essential for immune cell function .

What types of TNFRSF18 antibodies are available for research applications?

TNFRSF18 antibodies are available in multiple configurations to support diverse research applications:

By host species:

• Mouse-derived monoclonal antibodies (e.g., clone 6H8B9)

• Rabbit-derived polyclonal and monoclonal antibodies

• Recombinant human IgG antibodies

By reactivity:

• Human-specific TNFRSF18 antibodies

• Mouse-specific TNFRSF18 antibodies

• Cross-reactive antibodies with multiple species compatibility

By clonality:

• Monoclonal antibodies that recognize specific epitopes (e.g., AA 184-241, AA 26-162)

• Polyclonal antibodies that recognize multiple epitopes

By conjugation:

• Unconjugated primary antibodies

• HRP-conjugated antibodies for direct detection systems

• Other conjugates including biotin, fluorophores like Cy3, and DyLight488

How should researchers select the appropriate TNFRSF18 antibody epitope for their specific research question?

The selection of antibody epitope is critical and should be guided by the specific research question:

For structural studies:
Choose antibodies targeting specific domains:

• Extracellular domain antibodies (e.g., AA 26-162) for surface expression studies

• Antibodies targeting the ligand-binding region (e.g., AA 90-162) for interaction studies

• C-terminal domain antibodies (e.g., AA 184-241) for signaling research

For functional studies:

• For agonistic activities, select antibodies that bind regions conducive to receptor clustering

• For neutralizing studies, choose antibodies that disrupt ligand-receptor interactions

• For tracking receptor internalization, select antibodies to extracellular domains that remain bound during trafficking events

The epitope selection directly impacts the antibody's utility in different applications. For instance, antibodies recognizing the AA 184-241 region might be optimal for flow cytometry studies of surface expression, while those targeting functional domains may be better suited for activation or inhibition studies in functional assays .

How do TNFRSF18 agonistic antibodies induce receptor clustering and what factors influence this mechanism?

TNFRSF18 agonistic antibodies induce receptor activation through a complex mechanism involving:

Receptor clustering mechanisms:
TNFRSF receptors are normally activated by molecular clustering induced by their cognate cell membrane ligands. Antibodies can mimic this activation through:

• Direct bivalent binding: The inherent bivalency of antibodies allows them to bind two GITR molecules simultaneously, initiating receptor clustering

• Fc-mediated cross-linking: The most dominant factor in determining agonistic activities involves Fc interactions with Fc gamma receptors (FcγRs), particularly FcγRIIB

• Epitope-dependent effects: The specific binding epitope significantly determines the intrinsic agonistic activity of the antibody, with certain epitopes enabling more efficient clustering

The interaction between the antibody's Fc portion and FcγRIIB provides opportunities for multivalent interactions beyond the primary target. This cross-linking dramatically enhances receptor clustering and downstream signaling activation. Research suggests that Fc engineering approaches to optimize Fc binding to FcγRIIB, in combination with appropriate epitope selection, can significantly improve the agonistic activity of TNFRSF18 antibodies .

What are the critical considerations for using TNFRSF18 antibodies in cancer immunotherapy research models?

When using TNFRSF18 antibodies in cancer immunotherapy research, investigators should consider:

Balancing efficacy and toxicity:
A major challenge in clinical development of TNFRSF agonistic antibodies has been balancing their anti-tumor efficacy with potential toxicities. This requires careful experimental design and monitoring .

Target-specific optimization strategies:

• Leveraging interactions between antibodies and inhibitory Fc receptor FcγRIIB to optimize co-stimulation activities selectively in the tumor microenvironment

• Exploring cross-linking through tumor antigen binding with bispecific antibody approaches

Fc engineering considerations:

• The role of FcγRIIB in TNFRSF cross-linking and clustering bridged by agonistic antibodies is critical

• Multiple Fc engineering approaches can optimize FcγRIIB binding in the context of proper Fab and epitope selection

• Cross-linking antibody (xLinkAb) models may enhance efficacy while minimizing systemic toxicity

Experimental model selection:
Researchers should select models that appropriately recapitulate the human immune environment and tumor microenvironment to accurately assess antibody functionality and safety profiles.

How can researchers troubleshoot inconsistent results in TNFRSF18 antibody-based detection assays?

When encountering inconsistent results with TNFRSF18 antibody-based assays, researchers should systematically evaluate:

Sample preparation factors:

• Ensure proper sample fixation for immunohistochemistry applications

• Verify cell preparation protocols for flow cytometry to maintain epitope integrity

• For protein analysis, confirm appropriate lysis buffers that preserve the target epitope

Technical optimization:

• Titrate antibody concentrations to determine optimal signal-to-noise ratios

• Adjust incubation conditions (time, temperature, buffer composition)

• For flow cytometry, ensure appropriate compensation and gating strategies

• For ELISA, optimize blocking and washing steps to reduce background

Antibody validation:

• Confirm antibody specificity using positive and negative controls

• Consider using multiple antibodies targeting different epitopes to verify results

• Validate results using complementary techniques (e.g., flow cytometry results with Western blot)

Biological variables:

• Account for differential expression of TNFRSF18 across cell activation states

• Consider potential receptor internalization or shedding affecting detection

• Evaluate potential cross-reactivity with similar family members

What are the optimal protocols for using TNFRSF18 antibodies in flow cytometry?

For optimal detection of TNFRSF18 by flow cytometry:

Sample preparation:

• Harvest cells gently to minimize receptor shedding

• Wash cells in cold PBS + 1% BSA or FBS

• If using fresh blood samples, perform red blood cell lysis

• Adjust cell concentration to 1-5 × 10⁶ cells/mL

Staining protocol:

• Block Fc receptors with 10% normal serum from the antibody host species

• Incubate with primary TNFRSF18 antibody at optimal dilution (determined experimentally)

• For unconjugated antibodies, wash and add appropriate secondary antibody

• Include viability dye to exclude dead cells

• Include appropriate isotype controls and FMO (fluorescence minus one) controls

Analysis considerations:

• Set appropriate compensation using single-stained controls

• Use isotype controls to determine positive staining thresholds

• Consider including known positive control samples (such as activated T cells)

• For activated cells, compare TNFRSF18 expression levels between resting and stimulated populations

TNFRSF18 expression can be significantly affected by cell activation status, so careful experimental design is crucial for meaningful interpretation .

How should researchers design functional assays to evaluate TNFRSF18 antibody agonistic activity?

When designing functional assays to evaluate TNFRSF18 antibody agonistic activity:

T cell activation assay design:

• Isolate primary T cells or use appropriate T cell lines

• Pre-coat plates with suboptimal anti-CD3 (for TCR stimulation)

• Add the TNFRSF18 agonistic antibody at varying concentrations

• Include appropriate controls:

  • Isotype control antibody

  • Known agonist positive control

  • Anti-CD28 as alternative co-stimulatory control

• Measure activation markers (CD25, CD69), proliferation (CFSE dilution), and cytokine production (IL-2, IFN-γ)

Considerations for Fc-dependent activity assessment:

• Test the antibody in presence/absence of FcγRIIB-expressing cells

• Include Fc-mutant versions of the antibody to determine Fc dependency

• Compare activities across different antibody isotypes with varying FcγR binding profiles

Evaluation in complex immune cell mixtures:

• Test antibody in PBMC cultures to assess effects on multiple cell types

• Measure changes in Treg suppressive function

• Assess dendritic cell maturation and function as secondary readouts

In vivo functional assessment:

• Design dose-response studies in appropriate animal models

• Monitor immune cell populations in peripheral blood, lymphoid organs, and tumor (if applicable)

• Assess changes in immune cell activation status and functional parameters

• Evaluate anti-tumor efficacy in tumor models

What analytical approaches can differentiate between the activities of different TNFRSF18 antibody clones?

To differentiate between activities of different TNFRSF18 antibody clones:

Epitope mapping approaches:

• Conduct competitive binding assays to determine if antibodies recognize overlapping or distinct epitopes

• Perform domain-specific truncation analyses to identify binding regions

• Use peptide arrays to identify specific binding sequences

Functional profiling:

• Compare dose-response curves for T cell activation

• Assess differences in receptor internalization kinetics

• Evaluate differential effects on distinct T cell subsets (conventional T cells vs. Tregs)

• Measure qualitative differences in downstream signaling activation

Cross-linking dependency analysis:

• Test antibodies in the presence/absence of cross-linking agents or FcγR-expressing cells

• Compare activities when presented in solution versus immobilized on surfaces

• Assess the impact of various Fc engineering modifications on each clone's activity

Data analysis and visualization:
Create comparison tables showing:

Such comparative analyses provide crucial insights into the mechanistic differences between antibody clones and guide selection for specific research applications .

How does the isotype of TNFRSF18 antibodies influence experimental outcomes?

The isotype of TNFRSF18 antibodies significantly impacts experimental outcomes through:

FcγR engagement profiles:
Different isotypes (IgG1, IgG2a/b, IgG4) exhibit distinct binding affinities for activating and inhibitory FcγRs, directly affecting:

• Cross-linking efficiency and consequent receptor clustering

• Potential for antibody-dependent cellular cytotoxicity (ADCC)

• Complement activation

• In vivo half-life and tissue distribution

For TNFRSF18 agonistic antibodies, the interaction with inhibitory FcγRIIB is particularly important for optimal cross-linking and agonistic activity . Mouse IgG1 antibodies typically have lower affinity for activating FcγRs compared to mouse IgG2a, resulting in different functional profiles in vivo.

Species-specific considerations:

• Human IgG1 and mouse IgG2a have strong affinity for activating FcγRs

• Human IgG4 and mouse IgG1 generally have reduced FcγR binding

• Human IgG2 shows selective engagement patterns

Researchers should select antibody isotypes based on:

• The desired mechanism of action (pure agonism vs. additional effector functions)

• The experimental model (human vs. mouse systems)

• The availability of FcγR-expressing cells in the experimental system

What controls are essential when validating new TNFRSF18 antibodies for research applications?

Proper validation of TNFRSF18 antibodies requires comprehensive controls:

Specificity controls:

• TNFRSF18 knockout or knockdown cells/tissues (negative control)

• TNFRSF18 overexpression systems (positive control)

• Pre-absorption with recombinant TNFRSF18 protein

• Comparison with established reference antibodies

• Testing on cells known to express or not express TNFRSF18

Technical controls:

• Isotype-matched control antibodies to assess non-specific binding

• Secondary antibody-only controls (for unconjugated primaries)

• Titration series to determine optimal working concentration

• Multiple application testing (if claiming multi-application utility)

Biological controls:

• Resting vs. activated T cells (TNFRSF18 is upregulated upon activation)

• Different T cell subsets (conventional T cells vs. Tregs)

• Tissues with known expression patterns

• Cross-species reactivity testing if claimed

Functional validation:

• Correlation of binding with functional outcomes

• Comparison of agonistic/antagonistic effects with known standards

• Validation in physiologically relevant models

Documentation of these validation steps provides critical evidence of antibody performance and reliability for specific research applications .

How can researchers engineer TNFRSF18 antibodies with optimized cross-linking capabilities for enhanced agonistic function?

Engineering TNFRSF18 antibodies with enhanced agonistic function involves:

Fc engineering approaches:

• Enhancing FcγRIIB binding:

  • Introducing specific amino acid substitutions in the Fc region

  • Creating Fc variants with selective FcγRIIB engagement

  • Optimizing the antibody's Fc glycosylation pattern

• Cross-linking antibody (xLinkAb) models:

  • Developing bispecific antibodies that bind both TNFRSF18 and tumor-associated antigens

  • Creating higher valency formats (e.g., IgG-scFv fusions) for enhanced clustering

Structural optimization strategies:

• Epitope selection targeting receptor domains that facilitate clustering

• Optimizing antibody flexibility through hinge region modifications

• Developing antibody fragments with enhanced penetration into tissues while maintaining clustering capability

Comparative efficacy assessment:
Engineered antibodies should be assessed against conventional formats to quantify improvements in:

• Receptor clustering efficiency

• Downstream signaling activation

• T cell proliferation and cytokine production

• Anti-tumor activity in relevant models

• Safety profile and potential off-target effects

What are the most effective methods for monitoring TNFRSF18 receptor dynamics following antibody engagement?

To effectively monitor TNFRSF18 receptor dynamics following antibody engagement:

Real-time imaging approaches:

• Live-cell confocal microscopy with fluorescently labeled antibodies

• FRET-based assays to monitor receptor-receptor interactions

• Single-molecule tracking to observe individual receptor movements

• Total internal reflection fluorescence (TIRF) microscopy for surface clustering visualization

Biochemical and molecular techniques:

• Proximity ligation assays to detect closely associated receptor molecules

• Immunoprecipitation followed by native PAGE to preserve receptor complexes

• Cross-linking studies to capture transient interaction partners

• Pulse-chase experiments to track receptor internalization and trafficking

Signaling activation indicators:

• Phospho-specific Western blotting for downstream signaling components

• Reporter cell lines expressing TNFRSF18-responsive promoter elements

• Calcium flux assays for immediate signaling readouts

• Transcriptional profiling to identify gene expression changes

Experimental design considerations:

• Include appropriate time courses (seconds to hours)

• Compare different antibody clones and formats

• Assess effects of Fc receptor availability

• Evaluate impact of simultaneous TCR engagement

• Control for potential artifacts due to antibody labeling

What emerging technologies are advancing TNFRSF18 antibody research?

Emerging technologies transforming TNFRSF18 antibody research include:

Advanced antibody engineering platforms:

• Structure-guided antibody design based on TNFRSF18 crystal structures

• High-throughput screening systems for identifying optimal agonistic clones

• Site-specific conjugation technologies for precise payload delivery

• Computational approaches to predict and optimize antibody-receptor interactions

Novel functional assessment tools:

• Organoid and 3D culture systems for more physiologically relevant testing

• Microfluidic systems for analyzing cell-cell interactions in controlled environments

• Advanced intravital imaging for real-time visualization of antibody activities in vivo

• Single-cell approaches to characterize heterogeneous responses across immune populations

Combination therapy approaches:

• Rational design of TNFRSF18 antibodies with complementary checkpoint inhibitors

• Development of multi-specific antibodies targeting TNFRSF18 and other immunomodulatory receptors

• Integration with cellular therapies like CAR-T cells

• Combination with cancer vaccines to enhance tumor-specific responses

The future of TNFRSF18 antibody research lies in developing increasingly sophisticated reagents with enhanced specificity, potency, and safety profiles through these emerging technologies and approaches.

What is the recommended protocol for ELISA-based quantification of TNFRSF18 using antibodies?

ELISA Protocol for TNFRSF18 Quantification:

Materials:

• Anti-TNFRSF18 capture antibody (e.g., clones targeting AA 26-115)

• Biotinylated or HRP-conjugated detection antibody (ideally targeting a different epitope)

• Recombinant TNFRSF18 protein standards

• High-binding 96-well plates

• Blocking buffer (1% BSA in PBS)

• Wash buffer (0.05% Tween-20 in PBS)

• TMB substrate and stop solution

• Plate reader capable of measuring absorbance at 450nm

Procedure:

• Plate coating:

  • Dilute capture antibody to optimal concentration (typically 1-5 μg/mL) in coating buffer

  • Add 100 μL per well and incubate overnight at 4°C

  • Wash 3 times with wash buffer

• Blocking:

  • Add 300 μL blocking buffer per well

  • Incubate for 1-2 hours at room temperature

  • Wash 3 times with wash buffer

• Sample addition:

  • Prepare standards using recombinant TNFRSF18 (typical range: 0-1000 pg/mL)

  • Dilute samples appropriately in blocking buffer

  • Add 100 μL of standards and samples in duplicate

  • Incubate for 2 hours at room temperature

  • Wash 5 times with wash buffer

• Detection:

  • Add 100 μL of diluted detection antibody

  • Incubate for 1-2 hours at room temperature

  • Wash 5 times with wash buffer

  • If using biotinylated detection, add streptavidin-HRP and incubate for 30 minutes

  • Wash 5 times with wash buffer

• Development and analysis:

  • Add 100 μL TMB substrate solution

  • Incubate for 5-30 minutes (monitor color development)

  • Add 50 μL stop solution

  • Read absorbance at 450nm with 570nm correction

  • Calculate concentrations using standard curve

This protocol can be optimized based on specific antibody pairs and sample types being analyzed.

How should researchers approach multiplexed analysis incorporating TNFRSF18 antibodies with other immune markers?

When conducting multiplexed analysis with TNFRSF18 antibodies:

Panel design considerations:

• Select TNFRSF18 antibodies validated for multiplexed applications

• Choose compatible fluorophores or tags based on:

  • Available instrument configuration

  • Spectral overlap minimization

  • Relative abundance of targets (brightest fluorophores for least abundant markers)

• Include markers to identify relevant cell populations (e.g., CD3, CD4, CD8 for T cells)

• Add functional markers to correlate with TNFRSF18 expression (e.g., activation markers, cytokines)

Technical optimization steps:

• Conduct antibody titrations in single-stain format before multiplexing

• Test for potential antibody interactions or blocking effects

• Optimize staining buffers and conditions for all markers

• Perform compensation controls for each fluorophore

• Include FMO controls to set accurate gates

• Consider live/dead discrimination and doublet exclusion

Analysis approaches:

• Conventional manual gating strategies

• Unsupervised clustering algorithms (e.g., t-SNE, UMAP)

• Supervised machine learning for population identification

• Correlation analyses between TNFRSF18 and other markers

Application-specific considerations: