TNFRSF19 Antibody

What is TNFRSF19 and why is it significant in research?

TNFRSF19, also known as TROY, is a type I cell surface transmembrane protein belonging to the tumor necrosis factor (TNF) receptor superfamily. Unlike other members of this family, TNFRSF19 lacks a cytoplasmic death domain but contains a single TNF receptor-associated factor (TRAF)-binding site . Its significance lies in its involvement in various physiological and pathological processes, particularly in the central nervous system and cancer development. TNFRSF19 is expressed on migrating or proliferating progenitor cells of the hippocampus, thalamus, and cerebral cortex, suggesting its role in neuronal development . In cancer research, TNFRSF19 has emerged as a susceptibility gene for nasopharyngeal carcinoma and lung cancer, functioning as a potent inhibitor of the TGFβ signaling pathway, which allows tumor cells to evade growth-inhibitory signals .

What epitopes do commonly available TNFRSF19 antibodies target?

Commercial TNFRSF19 antibodies typically target either extracellular or intracellular domains of the protein. For instance, one well-characterized antibody targets the peptide CRPHRFKEDWGFQK, corresponding to amino acid residues 75-88 of mouse TROY (Accession Q9JLL3) in the extracellular N-terminus . Other antibodies may target the recombinant human TROY/TNFRSF19 spanning from Glu30 to Leu170 (Accession # AAF71828) . The selection of appropriate epitope-targeting antibodies depends on the experimental goals - extracellular epitope-targeting antibodies are ideal for detecting the protein in living cells, while intracellular epitope-targeting antibodies may be more suitable for fixed cell applications.

How does TNFRSF19 structure relate to its function?

TNFRSF19 is structured as a type I cell surface transmembrane protein featuring distinctive disulfide bonds that form "cysteine-rich domains" (CRDs). These 40 amino acid pseudo-repeats are defined by 3 intra-chain disulfides generated by 6 highly conserved cysteines . This structural arrangement is critical for its function. Unlike most TNF receptors, TNFRSF19 lacks a cytoplasmic death domain but contains a TRAF-binding site, which influences its signaling capabilities . Functionally, this structure allows TNFRSF19 to interact with specific partners such as the TGFβ receptor type I (TβRI). TNFRSF19 binds to the kinase domain of TβRI in the cytoplasm, preventing Smad2/3 association with TβRI and subsequent signal transduction . This mechanism explains how TNFRSF19 inhibits TGFβ signaling, allowing cancer cells to evade growth suppression.

What are the optimal conditions for using TNFRSF19 antibodies in Western blot applications?

For optimal Western blot results with TNFRSF19 antibodies, the following methodological approach is recommended:

• Sample preparation: Prepare cell lysates from appropriate sources; glioblastoma cell lines (U-87 MG), melanoma cell lines (Malme-3M), or brain tissue (rat or mouse) have shown good expression levels .

• Dilution ratio: Use anti-TNFRSF19 (extracellular) antibody at a 1:400 dilution for optimal signal-to-noise ratio .

• Validation controls: Include negative controls by pre-incubating the antibody with a TROY/TNFRSF19 blocking peptide to confirm specificity .

• Detection system: Use an appropriate secondary antibody and chemiluminescent or fluorescent detection system compatible with your primary antibody.

• Storage and handling: Store reconstituted antibody at 2-8°C for short-term use (up to 1 month) or at -20 to -70°C for long-term storage (up to 6 months) .

Following these methodological guidelines will enhance detection specificity and minimize background or non-specific binding problems that are commonly encountered.

How can researchers optimize immunohistochemistry protocols for TNFRSF19 detection in tissue samples?

Optimizing immunohistochemistry (IHC) protocols for TNFRSF19 detection requires careful attention to several methodological aspects:

• Fixation: Use 4% paraformaldehyde for optimal epitope preservation, as over-fixation may mask the TNFRSF19 epitope.

• Antigen retrieval: For formalin-fixed, paraffin-embedded tissues, heat-induced epitope retrieval using citrate buffer (pH 6.0) is recommended to expose the TNFRSF19 epitope.

• Blocking: Implement dual blocking approach - first block endogenous peroxidase activity using hydrogen peroxide, then block non-specific binding sites with serum from the same species as the secondary antibody.

• Antibody incubation: Use anti-TNFRSF19 antibody at experimentally determined optimal dilutions (typically starting at 1:200 and adjusting as needed). Incubate at 4°C overnight for maximum sensitivity.

• Controls: Include positive controls (tissues known to express TNFRSF19, such as glioblastoma samples) and negative controls (omitting primary antibody or using isotype controls).

• Signal amplification: Consider using tyramide signal amplification for low-abundance targets.

• Counterstaining: Use hematoxylin for nuclear visualization but avoid overstaining, which may mask specific signals.

Researchers should validate antibody specificity through multiple approaches, including genetic knockouts or western blot correlation, particularly when performing quantitative analysis of TNFRSF19 expression .

What are the critical considerations for developing a flow cytometry protocol to detect TNFRSF19?

Developing a robust flow cytometry protocol for TNFRSF19 detection requires addressing several critical methodological considerations:

• Antibody selection: Choose antibodies that target the extracellular domain of TNFRSF19, as these are suitable for live cell detection .

• Cell preparation: Optimize dissociation procedures to preserve the extracellular epitopes. Enzymatic dissociation should be carefully timed to avoid cleaving surface proteins.

• Viability staining: Include a viability dye (e.g., propidium iodide or 7-AAD) to exclude dead cells, which can give false-positive results due to non-specific antibody binding.

• Blocking strategy: Implement Fc receptor blocking to prevent non-specific binding, especially when working with immune cells or cell lines with high Fc receptor expression.

• Titration: Determine the optimal antibody concentration through titration experiments to maximize the signal-to-noise ratio.

• Compensation controls: Use appropriate single-color controls when performing multiparameter flow cytometry to correct for spectral overlap.

• Gating strategy: Develop a consistent gating strategy that includes forward/side scatter to identify cell populations of interest, followed by gating on viable cells before analyzing TNFRSF19 expression.

• Validation: Confirm specificity using TNFRSF19 knockdown or knockout cells as negative controls.

This methodological approach ensures accurate detection of TNFRSF19-positive populations while minimizing artifacts that could lead to data misinterpretation.

How can TNFRSF19 antibodies be used to investigate the protein's role in TGFβ signaling inhibition?

Investigating TNFRSF19's role in TGFβ signaling inhibition requires sophisticated experimental approaches using well-characterized antibodies:

• Co-immunoprecipitation studies: Use anti-TNFRSF19 antibodies to pull down protein complexes, followed by Western blot analysis for TGFβ receptor type I (TβRI), to confirm direct interaction. Research has shown that TNFRSF19 specifically binds to the kinase domain of TβRI in the cytoplasm .

• Proximity ligation assays: Employ anti-TNFRSF19 and anti-TβRI antibodies to visualize and quantify protein-protein interactions in situ, providing spatial information about where in the cell these interactions occur.

• Phosphorylation status analysis: Monitor Smad2/3 phosphorylation levels using phospho-specific antibodies in the presence or absence of TNFRSF19. Studies have demonstrated that TNFRSF19 prevents Smad2/3 association with TβRI and subsequent signal transduction .

• ChIP-seq analysis: Use anti-TNFRSF19 antibodies in chromatin immunoprecipitation followed by sequencing to identify potential regulatory regions affected by TNFRSF19-mediated TGFβ signaling inhibition.

• Functional rescue experiments: Combine TNFRSF19 knockdown with domain-specific mutants to identify which regions are essential for TGFβ signaling inhibition.

These methodological approaches can help elucidate the molecular mechanisms by which TNFRSF19 functions as a negative regulator of TGFβ receptor-induced signaling, providing insights into how tumor cells might evade growth-inhibitory signals .

What methods can resolve contradictory findings regarding TNFRSF19 expression in different cancer types?

Resolving contradictory findings regarding TNFRSF19 expression across cancer types requires a multi-dimensional methodological approach:

• Single-cell RNA sequencing: Apply scRNA-seq to distinguish cell type-specific expression patterns within heterogeneous tumor samples, revealing whether contradictory findings result from differential expression across cell populations.

• Tissue microarray analysis: Employ standardized tissue microarrays with anti-TNFRSF19 antibodies to systematically compare expression across multiple cancer types and stages while controlling for technical variables.

• Isoform-specific detection: Develop and validate antibodies targeting specific TNFRSF19 isoforms to determine whether contradictions stem from differential isoform expression.

• Epigenetic profiling: Combine TNFRSF19 antibody-based protein detection with DNA methylation and histone modification analysis to characterize epigenetic regulation that might explain tissue-specific expression patterns.

• Clinical correlation analysis: Integrate TNFRSF19 expression data with patient outcomes across multiple independent cohorts. Research has shown that elevated TNFRSF19 expression correlates with poor prognosis in gliomas across multiple cohorts .

• Functional validation: Perform gain- and loss-of-function studies in different cancer models to determine context-dependent functions.

This comprehensive approach can help reconcile seemingly contradictory findings by revealing tissue-specific regulatory mechanisms and functions of TNFRSF19 across different cancer types.

How can researchers investigate the relationship between TNFRSF19 and immune checkpoint expression in tumor microenvironments?

Investigating the relationship between TNFRSF19 and immune checkpoint expression requires sophisticated methodological approaches:

• Multiplex immunofluorescence: Employ multiplexed antibody panels to simultaneously detect TNFRSF19 and various immune checkpoint proteins (PD-1, PD-L1, etc.) within the tumor microenvironment, enabling spatial correlation analysis.

• Single-cell proteomics: Use mass cytometry (CyTOF) with antibodies against TNFRSF19 and immune checkpoint molecules to quantify co-expression patterns at the single-cell level.

• Transcriptomic correlation analysis: Analyze RNA-seq data from tumor samples to identify correlations between TNFRSF19 and immune checkpoint gene expression. Research has demonstrated that gliomas with high TNFRSF19 expression exhibit significantly increased expression of 28 immune checkpoint proteins, including PD-L1 .

• In vitro co-culture systems: Establish co-culture systems with TNFRSF19-expressing tumor cells and immune cells to assess how TNFRSF19 modulates immune checkpoint expression and function.

• TNFRSF19 manipulation studies: Perform TNFRSF19 knockdown or overexpression followed by analysis of immune checkpoint levels to establish causality rather than mere correlation.

• Checkpoint inhibitor response correlation: Correlate TNFRSF19 expression levels with response to immune checkpoint inhibitor therapy in preclinical models and clinical samples.

This methodological framework can elucidate whether TNFRSF19 directly influences the immunosuppressive tumor microenvironment through modulation of checkpoint expression, potentially informing combination therapeutic strategies .

How does TNFRSF19 expression correlate with glioma malignancy and patient prognosis?

TNFRSF19 expression demonstrates significant correlations with glioma malignancy and patient outcomes based on multiple independent cohorts:

These findings consistently demonstrate that TNFRSF19 serves as a negative prognostic marker in gliomas, with its expression correlating with malignant phenotypes and poor clinical outcomes. This suggests TNFRSF19 may play a pivotal role in glioma progression and could serve as a potential therapeutic target or biomarker.

What is the methodological approach for investigating TNFRSF19's relationship with tumor immune microenvironment?

Investigating TNFRSF19's relationship with the tumor immune microenvironment requires a structured methodological approach:

• Immune cell profiling: Use single-sample Gene Set Enrichment Analysis (ssGSEA) to quantify the presence of immune cell populations in relation to TNFRSF19 expression levels. Research has revealed that high levels of immunosuppressive cells (MDSCs, neutrophils, M2 macrophages) are associated with gliomas exhibiting elevated TNFRSF19 expression .

• Stromal component analysis: Employ methodologies such as MCP-counter and ssGSEA to evaluate endothelial cells and fibroblasts in relation to TNFRSF19 expression. Studies have shown gliomas with elevated TNFRSF19 levels demonstrate higher fibroblast presence compared to those with lower levels .

• Immune checkpoint correlation: Analyze the expression of immune checkpoint genes in relation to TNFRSF19 levels. Research has demonstrated that within TCGA data, gliomas with high TNFRSF19 expression exhibit increased expression of 28 immune checkpoint proteins, including PD-L1 .

• Spatial analysis of immune infiltrates: Use multiplex immunohistochemistry to examine the spatial distribution of immune cells in relation to TNFRSF19-expressing cells within the tumor microenvironment.

• Functional validation: Perform TNFRSF19 knockdown or overexpression studies to assess causative effects on immune cell recruitment and function.

This comprehensive approach can elucidate how TNFRSF19 may contribute to shaping the immunosuppressive microenvironment within tumors, potentially informing immunotherapeutic strategies .

How can TNFRSF19 antibodies be used to study the protein's involvement in central nervous system myelin inhibition?

Studying TNFRSF19's role in central nervous system (CNS) myelin inhibition using antibodies requires specific methodological approaches:

• Receptor complex analysis: Use co-immunoprecipitation with anti-TNFRSF19 antibodies to isolate and analyze the tri-receptor complex formation with NgR and LINGO-1, which is known to reconstitute the activation of RhoA in myelin inhibition pathways .

• Functional blocking studies: Apply TROY-Fc fusion proteins or antibodies targeting specific extracellular domains to block neuronal response to myelin inhibitors in a dominant-negative manner. Research has shown that overexpression of a truncated form of TROY lacking its intracellular domain can block neuronal response to myelin inhibitors .

• RhoA activation assays: Monitor RhoA activation in response to myelin inhibitory molecules in the presence or absence of anti-TNFRSF19 blocking antibodies.

• Neurite outgrowth assays: Quantify neurite extension in primary neuronal cultures grown on inhibitory substrates (e.g., myelin, Nogo, MAG) while manipulating TNFRSF19 function with domain-specific antibodies.

• In vivo CNS injury models: Apply TNFRSF19 function-blocking antibodies in spinal cord injury or optic nerve crush models to assess potential for enhanced axonal regeneration.

• Cell-specific expression analysis: Use antibodies for immunohistochemical detection of TNFRSF19 in various neural cell types following CNS injury to map expression patterns temporally and spatially.

These approaches can help elucidate how TNFRSF19 functions as a substitute for p75NTR in the inhibitory receptor complex and its potential as a therapeutic target for promoting CNS regeneration after injury .

What are the methodological considerations for developing therapeutic antibodies targeting TNFRSF19?

Developing therapeutic antibodies targeting TNFRSF19 requires addressing several critical methodological considerations:

• Epitope selection: Target functional domains of TNFRSF19 that are crucial for its interaction with binding partners. Since TNFRSF19 binds to the kinase domain of TGFβ receptor type I (TβRI), antibodies disrupting this interaction could restore TGFβ signaling and growth inhibition in cancer cells .

• Antibody format optimization: Evaluate various antibody formats (IgG, Fab, scFv, bispecific) to determine optimal tissue penetration, half-life, and effector function recruitment, particularly for targeting the blood-brain barrier in glioma applications.

• Functional screening assays: Develop high-throughput assays measuring TGFβ signaling restoration (Smad2/3 phosphorylation) or RhoA activation to screen antibody candidates for biological activity rather than mere binding.

• Cross-reactivity assessment: Thoroughly evaluate cross-reactivity with other TNF receptor superfamily members to ensure specificity, as structural homology between family members can lead to off-target effects.

• Cancer subtype stratification: Determine which cancer subtypes show TNFRSF19 dependency through comprehensive screening, as expression levels vary across tumor types .

• Combination strategy testing: Evaluate synergistic potential with immune checkpoint inhibitors, as research has shown correlation between TNFRSF19 expression and increased immune checkpoint protein levels .

• Predictive biomarker development: Establish companion diagnostic approaches to identify patients most likely to benefit from anti-TNFRSF19 therapy based on expression levels and pathway activation.

These methodological considerations address the complexity of developing effective TNFRSF19-targeting therapeutic antibodies while maximizing potential clinical benefit.

How can researchers investigate the role of TNFRSF19 in cancers beyond glioblastoma and nasopharyngeal carcinoma?

Investigating TNFRSF19's role in other cancer types requires a systematic multi-modal approach:

• Pan-cancer expression analysis: Perform comprehensive analysis of TNFRSF19 expression across The Cancer Genome Atlas (TCGA) and other large-scale datasets to identify additional cancer types with significant TNFRSF19 dysregulation.

• Genetic association studies: Conduct genome-wide association studies to determine if TNFRSF19 genetic variants are linked to cancer susceptibility in additional tumor types beyond nasopharyngeal carcinoma and lung cancer .

• Pathway analysis in diverse cancer models: Investigate whether the TGFβ signaling inhibition mechanism is conserved across different cancer types using cancer cell lines with varied tissue origins .

• Development of conditional knockout models: Generate tissue-specific TNFRSF19 knockout models to evaluate its role in tumor initiation and progression across various cancer types.

• Drug sensitivity correlation: Analyze whether TNFRSF19 expression correlates with response to specific therapeutic agents across cancer types, potentially revealing new contexts for targeting this pathway.

• Multi-omics integration: Combine transcriptomic, proteomic, and phosphoproteomic data to characterize TNFRSF19-associated signaling networks in different tumor contexts.

• Immunotherapy response association: Evaluate whether TNFRSF19 expression predicts immunotherapy response across cancer types, given its association with immune checkpoint expression in gliomas .

This comprehensive approach would extend our understanding of TNFRSF19 beyond its established roles in glioblastoma and nasopharyngeal carcinoma, potentially revealing new therapeutic opportunities across cancer types.