TNFRSF9/4-1BB Recombinant Monoclonal Antibody

What is TNFRSF9/4-1BB and where is it expressed in human tissues?

TNFRSF9 (also known as 4-1BB, CD137, ILA, or CDw137) is a type II membrane glycoprotein with a molecular weight of approximately 30 kDa that belongs to the tumor necrosis factor receptor superfamily. Expression patterns vary significantly between resting and activated states. In humans, inducible expression is predominantly found on activated CD4+ and CD8+ T cells after stimulation. TNFRSF9 expression has also been documented on natural killer (NK) cells, dendritic cells (DCs), monocytes, and even some non-immune cells like hepatoma cells and blood vessels from individuals with malignant tumors . Notably, TNFRSF9 expression increases in human peripheral blood mononuclear cells following exposure to DNA-damaging agents such as mitomycin . Western blot analysis typically detects TNFRSF9 at approximately 32 and 40 kDa in human lymphoid tissues and cell lines .

How does TNFRSF9 interact with its ligand (TNFSF9/4-1BBL), and what cellular responses result from this interaction?

TNFRSF9 interacts with its cognate ligand TNFSF9 (4-1BB ligand/CD137 ligand), a type II glycoprotein with a mass of 34 kDa that is expressed on activated T cells, macrophages, monocytes, dendritic cells, B cells, and B lymphomas . This interaction initiates bidirectional signaling in both the TNFRSF9-expressing cell and the TNFSF9-expressing cell.

For TNFRSF9-expressing cells (primarily activated T cells), binding triggers complex signaling cascades mediated through TNF receptor-associated factors (TRAFs), particularly TRAF1 and TRAF2 . These pathways promote:

• Enhanced expression of anti-apoptotic proteins (Bcl-2, Bcl-XL, Bfl-1)

• Suppression of pro-apoptotic proteins like Bim

• Increased proliferation and cytokine production

• Extended survival of activated T cells, particularly CD8+ T cells

Importantly, TNFRSF9 engagement on regulatory T cells can have context-dependent effects, sometimes enhancing and other times inhibiting their immunosuppressive activity . For TNFSF9-expressing cells (typically antigen-presenting cells), reverse signaling increases antigen-presenting capacity and modulates inflammatory responses .

What are the validated detection methods for TNFRSF9 in different experimental systems?

Multiple validated techniques exist for detecting TNFRSF9 expression, each with specific sample preparation requirements and detection sensitivity:

Western Blot Analysis: Effective for detecting TNFRSF9 in cell lysates and tissue samples under reducing conditions. Research has validated detection in HDLM-2 human Hodgkin's lymphoma cell lines and human tonsil tissue, with specific bands appearing at approximately 32 and 40 kDa . Optimal results require:

• 2 μg/mL of anti-TNFRSF9 antibody

• PVDF membrane

• Reducing conditions

• Appropriate immunoblot buffer systems (e.g., Immunoblot Buffer Group 1)

Flow Cytometry: Particularly useful for detecting TNFRSF9 on cell surfaces in transfected cell lines and primary immune cells. Recommended protocol:

• Cell concentration: approximately 106 cells per sample

• Antibody concentration: 0.25 μg per 106 cells

• Use of appropriate negative controls and gating strategies based on marker expression

• Validated in HEK293 cells transfected with human TNFRSF9 and activated human PBMCs

Immunocytochemistry/Immunofluorescence: Effective for visualizing TNFRSF9 cellular localization. Optimal conditions include:

• 8-25 μg/mL antibody concentration

• Room temperature incubation (3 hours)

• Fluorescent-conjugated secondary antibodies

• DAPI counterstaining for nuclear visualization

• Validated in PBMCs treated with PHA (positive control) and HEK293 cells (negative control)

How should researchers design experiments to assess TNFRSF9 agonist antibody function in T cell activation assays?

When designing T cell activation assays to evaluate TNFRSF9 agonist antibody function, researchers should consider the following methodological approach:

• Experimental Setup:

  • Use purified T cells (CD4+ and CD8+ separately for differential analysis)

  • Include appropriate controls:

    • Isotype control antibody (negative control)

    • Anti-CD3/CD28 stimulation (positive control)

    • Combined anti-CD3/CD28 with TNFRSF9 agonist (to assess co-stimulatory effects)

• Key Parameters to Measure:

  • Proliferation (CFSE dilution or thymidine incorporation)

  • Cytokine production (IFN-γ, TNF-α, IL-2 by ELISA or intracellular staining)

  • Expression of activation markers (CD25, CD69 by flow cytometry)

  • Cell survival markers (Annexin V/PI staining)

  • Cytotoxicity (against target cells)

• Important Variables to Control:

  • Antibody concentration (dose-response relationships are critical)

  • Timing of antibody addition relative to TCR stimulation

  • Crosslinking requirements (some antibodies require crosslinking for optimal activity)

  • Duration of culture (short-term vs. long-term effects)

  • T cell subset composition and activation state

• Advanced Considerations:

  • Assess FcγR dependency of agonist activity using Fc-engineered variants

  • Evaluate effects on memory vs. naive T cell subsets

  • Monitor changes in gene expression profiles (particularly survival genes like Bcl-2, Bcl-XL)

  • Consider examining bidirectional signaling when APCs are present in the culture system

How do different epitope specificities of anti-TNFRSF9 antibodies affect their agonistic activities?

The epitope specificity of anti-TNFRSF9 antibodies significantly impacts their functional properties, presenting both research challenges and therapeutic opportunities. This relationship stems from several factors:

• Domain-Specific Effects: The extracellular portion of TNFRSF9 contains four cysteine-rich domains (CRDs), each with distinct roles in ligand binding and signal transduction. Antibodies targeting different CRDs display varying levels of agonistic activity:

  • CRD1 (membrane-distal domain): Antibodies binding this region often show stronger agonistic properties

  • CRD4 (membrane-proximal domain): Antibodies targeting this region may affect receptor clustering differently

• Clustering Mechanisms: Effective TNFRSF9 signaling requires receptor trimerization and higher-order clustering. Different epitope-binding antibodies vary in their ability to induce optimal clustering configurations. This explains why some antibodies with similar binding affinities demonstrate dramatically different functional outcomes .

• Fc-Dependency Variations: The requirement for FcγR-mediated crosslinking varies substantially between antibodies binding different epitopes:

  • Some epitope-specific antibodies absolutely require Fc-FcγR interactions for activity

  • Others maintain significant activity even with F(ab')2 fragments or Fc-silenced variants

• Ligand Competition or Synergy: Depending on the targeted epitope, antibodies may:

  • Competitively inhibit natural ligand (TNFSF9) binding

  • Allow simultaneous ligand binding, potentially leading to synergistic effects

  • Induce conformational changes affecting ligand binding affinity

These epitope-dependent variations present significant challenges for researchers, particularly when comparing results across different antibody clones or when translating preclinical findings to clinical applications. Researchers should carefully characterize the epitope specificity and functional properties of anti-TNFRSF9 antibodies in their experimental systems .

What mechanisms contribute to hepatotoxicity observed with some TNFRSF9 agonist antibodies in clinical trials?

Hepatotoxicity represents one of the most significant challenges limiting the clinical development of TNFRSF9 agonist antibodies, despite their promising anti-tumor efficacy. Several proposed mechanisms have been identified through research:

• FcγR-Dependent Mechanisms:

  • Agonistic anti-TNFRSF9 antibodies require crosslinking via FcγR for optimal activity

  • Liver-resident Kupffer cells express high levels of FcγRs, which may create a "hotspot" for antibody crosslinking and excessive local activation

  • This hypothesis is supported by observations that Fc-engineered variants with reduced FcγR binding show decreased hepatotoxicity while maintaining anti-tumor activity

• TNFRSF9 Expression on Liver-Resident Cells:

  • Hepatocytes and sinusoidal endothelial cells can express TNFRSF9 under inflammatory conditions

  • Direct activation of these cells may trigger inflammatory cascades and cellular damage

  • Studies have shown that TNFRSF9 expression increases on hepatic cells following initial inflammatory stimuli, creating a potential feedback loop

• Inflammatory Cytokine Release:

  • Systemic activation of TNFRSF9 on T cells and other immune populations triggers substantial inflammatory cytokine release

  • Elevated levels of IFN-γ, TNF-α, and IL-12 can directly mediate hepatocellular injury

  • This cytokine storm effect may be dose-dependent and more pronounced with higher-affinity antibodies

• Polyclonal T Cell Activation in the Liver:

  • The liver contains a significant population of resident T cells

  • Non-specific activation of these cells via TNFRSF9 may trigger local inflammation

  • Memory T cells, which express higher levels of TNFRSF9, are particularly susceptible to activation

These mechanistic insights have guided the development of next-generation TNFRSF9-targeting approaches, including tumor-targeted bispecific antibodies, conditional agonists, and antibodies with modified Fc regions to limit systemic activation while maintaining intratumoral efficacy .

How can researchers design tumor-targeted TNFRSF9 agonist approaches to improve therapeutic index?

Designing tumor-targeted TNFRSF9 agonist approaches involves multiple sophisticated strategies to enhance anti-tumor efficacy while minimizing systemic toxicity:

• Bispecific Antibody Approaches:

  • Create bispecific antibodies targeting both TNFRSF9 and tumor-associated antigens (TAAs)

  • This restricts full agonistic activity to the tumor microenvironment where both targets are present

  • Design considerations include:

    • Selecting TAAs with high tumor specificity and minimal expression in healthy tissues

    • Optimizing binding affinity for both targets (typically lower affinity for TNFRSF9 and higher for TAA)

    • Determining optimal antibody formats (e.g., IgG-like vs. fragment-based constructs)

    • Engineering Fc functions to modulate FcγR engagement based on desired activity profile

• Conditional Activation Approaches:

  • Design antibodies that activate TNFRSF9 only under specific conditions found in the tumor microenvironment

  • Examples include:

    • pH-sensitive antibodies that change conformation at acidic tumor pH

    • Protease-activatable antibodies that require tumor-associated protease cleavage

    • Masking approaches where the binding domain is revealed only in the tumor context

• Fc Engineering Strategies:

  • Modify the Fc portion of anti-TNFRSF9 antibodies to control FcγR engagement patterns

  • Options include:

    • Silencing Fc to eliminate FcγR binding (reducing systemic activation)

    • Selectively engaging specific FcγR subtypes (e.g., FcγRIIb) to modulate activity

    • Creating tumor-selective Fc engagement through bispecific designs

• Combination with Local Delivery Methods:

  • Intratumoral injection to limit systemic exposure

  • Nanoparticle or liposome encapsulation for tumor-targeted delivery

  • Combination with radiation therapy to enhance local release and activation

• Novel Formats Beyond Traditional Antibodies:

  • TNFRSF9 ligand (TNFSF9) fusion proteins with tumor-targeting domains

  • Aptamer-based approaches with conditional activation properties

  • Cell-based delivery systems that release TNFRSF9 agonists locally within tumors

Researchers should employ rigorous preclinical testing of these approaches using both in vitro systems and in vivo models that recapitulate human TNFRSF9 biology to evaluate their potential for clinical translation.

What bidirectional signaling occurs between TNFRSF9 and TNFSF9, and how can this be leveraged in cancer immunotherapy research?

The TNFRSF9-TNFSF9 axis features complex bidirectional signaling that affects both the receptor-expressing cell (forward signaling) and the ligand-expressing cell (reverse signaling), presenting unique opportunities for cancer immunotherapy research:

• Forward Signaling Mechanisms (TNFRSF9 to T cells):

  • Engagement of TNFRSF9 on activated T cells recruits TRAF1 and TRAF2 to cytoplasmic domains

  • This activates downstream pathways including NF-κB, PI3K/Akt, and MAPK cascades

  • Functional outcomes include:

    • Enhanced proliferation and cytokine production (IFN-γ, TNF-α)

    • Increased expression of anti-apoptotic proteins (Bcl-2, Bcl-XL, Bfl-1)

    • Reduced activation-induced cell death

    • Preferential expansion of CD8+ memory T cells

    • Enhanced cytotoxic functions against tumor cells

• Reverse Signaling Mechanisms (TNFSF9 to APCs):

  • Engagement of TNFSF9 on antigen-presenting cells (APCs) triggers activation signals

  • This increases:

    • Antigen-presenting capacity

    • Production of pro-inflammatory cytokines (TNF-α, IL-6, IL-8, IL-12)

    • Expression of costimulatory molecules

    • Maturation of dendritic cells

  • Notably, TNFSF9 reverse signaling can also trigger apoptosis in some cell types, including certain tumor cells

• Research Applications Leveraging Bidirectional Signaling:

  • TNFRSF9 Agonist Plus TNFSF9-Targeting Approaches:

    • Simultaneously targeting both receptor and ligand may enhance anti-tumor immunity

    • Combined approaches could activate both T cells and APCs in the tumor microenvironment

    • Research designs should include individual and combined targeting to assess potential synergies

  • Engineered Cell Therapies:

    • CAR-T cells with integrated TNFRSF9 signaling domains for enhanced persistence

    • Dendritic cell vaccines engineered to express TNFSF9 for improved T cell priming

    • Cell-based delivery of TNFRSF9 agonists to the tumor microenvironment

  • Biomarker Applications:

    • Soluble forms of both TNFRSF9 and TNFSF9 are elevated in certain disease states

    • Monitoring these soluble forms during immunotherapy trials may provide predictive biomarkers

    • Research protocols should include assessments of both membrane-bound and soluble forms

Understanding and leveraging this bidirectional signaling could lead to more effective immunotherapeutic strategies that simultaneously enhance T cell effector functions and optimize APC-mediated antigen presentation within the tumor microenvironment.

What are common technical challenges in TNFRSF9 detection assays and how can they be addressed?

Researchers frequently encounter technical challenges when detecting TNFRSF9 in various experimental systems. These challenges and their solutions include:

• Low Basal Expression Levels:

  • Challenge: TNFRSF9 is often minimally expressed on resting cells, making detection difficult.

  • Solutions:

    • Pre-activate T cells with anti-CD3/CD28 or PHA for 24-48 hours before analysis

    • Use high-sensitivity detection methods such as enzyme-amplified flow cytometry

    • Consider analyzing TNFRSF9 mRNA levels using qRT-PCR when protein levels are below detection limits

    • For tissue samples, focus on areas with activated immune cells rather than resting regions

• Non-Specific Antibody Binding:

  • Challenge: Some anti-TNFRSF9 antibodies show cross-reactivity or high background.

  • Solutions:

    • Always include proper isotype controls and negative cell lines (e.g., HEK293 parental cells)

    • Titrate antibody concentration to find optimal signal-to-noise ratio

    • For flow cytometry, use viability dyes to exclude dead cells which often bind antibodies non-specifically

    • For Western blotting, validate specific bands using TNFRSF9-transfected cell lysates as positive controls

• Glycosylation Variability:

  • Challenge: TNFRSF9 is a glycoprotein with variable glycosylation patterns, causing inconsistent band patterns.

  • Solutions:

    • When performing Western blot, expect bands between 32-40 kDa depending on glycosylation state

    • Consider deglycosylation treatments (PNGase F) to obtain more uniform band patterns

    • Use reducing conditions for Western blot analysis to improve consistency

• Soluble TNFRSF9 Interference:

  • Challenge: Soluble forms of TNFRSF9 can interfere with membrane-bound detection.

  • Solutions:

    • For flow cytometry, wash samples thoroughly to remove soluble receptor

    • When measuring functional responses, consider pre-clearing culture supernatants

    • Design experiments to measure both membrane-bound and soluble forms

• Sample Preparation Effects:

  • Challenge: Freezing/thawing or enzymatic dissociation can affect TNFRSF9 epitopes.

  • Solutions:

    • For flow cytometry, prefer mechanical dissociation over enzymatic methods when possible

    • Validate detection methods using both fresh and frozen samples to understand potential variations

    • Process samples consistently to maintain comparability across experiments

These technical insights are derived from validated experimental protocols and represent established solutions to common challenges in TNFRSF9 research .

How should researchers evaluate and compare different anti-TNFRSF9 antibody clones for specific research applications?

Systematic evaluation of anti-TNFRSF9 antibody clones is essential for selecting the optimal reagent for specific research applications. This comprehensive evaluation should include:

• Binding Characteristics Assessment:

  • Affinity Determination:

    • Measure binding kinetics (kon, koff, KD) using surface plasmon resonance

    • Compare EC50 values across antibody clones using titration in flow cytometry

    • Assess binding under varying conditions (temperature, pH, buffer composition)

  • Epitope Mapping:

    • Determine which domain(s) of TNFRSF9 are recognized by each antibody

    • Evaluate competition with the natural ligand (TNFSF9)

    • Assess cross-reactivity with orthologs from other species if cross-species research is planned

• Functional Activity Profiling:

  • Agonistic Potential:

    • Measure T cell proliferation induced by each antibody clone

    • Quantify cytokine production (IFN-γ, IL-2, TNF-α)

    • Assess survival-promoting effects through apoptosis assays

    • Evaluate impact on cytotoxic activity of CD8+ T cells

  • Crosslinking Requirements:

    • Compare activity of whole IgG versus F(ab')2 fragments

    • Test dependency on FcγR-mediated crosslinking

    • Evaluate activity with different crosslinking methods (soluble vs. plate-bound)

• Application-Specific Validation:

  • For Flow Cytometry:

    • Determine optimal antibody concentration for staining

    • Evaluate performance in different fixation/permeabilization protocols

    • Assess compatibility with multicolor panels (spectral overlap)

  • For Western Blotting:

    • Compare performance under reducing and non-reducing conditions

    • Determine sensitivity limits with titrated protein amounts

    • Evaluate band patterns across different cell types and tissues

  • For In Vivo Applications:

    • Assess half-life and biodistribution

    • Evaluate potential immunogenicity

    • Determine optimal dosing schedule

• Comparative Analysis Framework:

  • Create a standardized assessment matrix scoring each antibody on:

    • Specificity (signal:noise ratio in relevant systems)

    • Sensitivity (minimum detectable expression level)

    • Reproducibility (inter-assay variability)

    • Versatility (performance across multiple applications)

    • Agonistic/antagonistic functional effects

  • Document batch-to-batch variability through repeated testing

  • Consider practical factors including cost, availability, and formulation stability

This systematic approach enables researchers to make informed selections of anti-TNFRSF9 antibodies that are optimally suited to their specific experimental goals and technical requirements .

What are emerging strategies to overcome clinical challenges with TNFRSF9-targeted immunotherapies?

• Tumor-Restricted Activation Strategies:

  • Development of bispecific antibodies that simultaneously target TNFRSF9 and tumor-associated antigens

  • Engineering of antibodies that become activated only within the tumor microenvironment (e.g., protease-activated antibodies, pH-sensitive antibodies)

  • Local administration approaches to limit systemic exposure

• Fc Engineering Approaches:

  • Creation of antibodies with modified Fc regions that selectively engage specific FcγR subtypes

  • Development of Fc-null variants that require alternative clustering mechanisms

  • Engineering of antibodies with controlled half-life to manage exposure

• Combination Therapy Optimization:

  • Identifying synergistic combinations with checkpoint inhibitors at doses below toxicity thresholds

  • Sequential administration protocols to prime the immune system before TNFRSF9 engagement

  • Combination with targeted therapies that may enhance TNFRSF9 expression selectively on tumor-infiltrating lymphocytes

• Novel Delivery Systems:

  • Nanoparticle-based delivery systems with tumor-targeting properties

  • Cell-based delivery approaches using engineered immune cells

  • Localized delivery methods such as intratumoral injection or implantable devices

• Biomarker-Guided Patient Selection:

  • Identification of patient populations less susceptible to toxicity

  • Development of predictive biomarkers for efficacy and safety

  • Real-time monitoring approaches to guide dosing and management

These innovative approaches represent the cutting edge of TNFRSF9-targeted immunotherapy research and offer promising paths to overcome the clinical challenges encountered with first-generation agonist antibodies .

How can emerging technologies advance our understanding of TNFRSF9 biology and therapeutic applications?

Emerging technologies are dramatically expanding our ability to investigate TNFRSF9 biology and develop more effective therapeutic approaches:

• Single-Cell Analysis Technologies:

  • Single-cell RNA sequencing to identify differential responses to TNFRSF9 engagement across immune cell subpopulations

  • Mass cytometry (CyTOF) for high-dimensional phenotyping of TNFRSF9-expressing cells in complex tissues

  • Spatial transcriptomics to map TNFRSF9 expression patterns within the tumor microenvironment

  • These approaches provide unprecedented resolution of cellular heterogeneity and context-specific responses

• Advanced Protein Engineering Platforms:

  • Directed evolution techniques to generate novel TNFRSF9-targeting proteins with unique properties

  • Structure-guided design of antibodies targeting specific epitopes to modulate receptor clustering

  • Computational protein design to create entirely new protein scaffolds for TNFRSF9 targeting

  • These technologies enable rational design of next-generation therapeutics with optimized properties

• Intravital Imaging Technologies:

  • Multiphoton microscopy to visualize TNFRSF9-expressing cell dynamics in living tissues

  • Bioluminescence resonance energy transfer (BRET) to monitor receptor clustering and signaling in real-time

  • Intravital imaging with fluorescent reporters to track cellular responses to TNFRSF9 engagement

  • These approaches provide unprecedented insights into the spatiotemporal dynamics of TNFRSF9 biology

• Genome Editing and Screening Technologies:

  • CRISPR-Cas9 screening to identify genetic modifiers of TNFRSF9 signaling

  • Knock-in reporter systems to monitor endogenous TNFRSF9 expression and trafficking

  • Precise genetic engineering to create humanized mouse models with improved translational relevance

  • These technologies enable systematic dissection of TNFRSF9 signaling networks and biology

• Artificial Intelligence and Machine Learning Applications:

  • Predictive modeling of TNFRSF9 agonist activity based on structural parameters

  • Pattern recognition in large-scale clinical datasets to identify biomarkers of response

  • Integration of multi-omics data to understand system-level responses to TNFRSF9 targeting

  • These computational approaches accelerate discovery and optimize therapeutic development