TNFRSF17 Human, His

What is TNFRSF17 and what are its alternative designations in scientific literature?

TNFRSF17 is a type I attached membrane protein of 184 amino acids that belongs to the tumor necrosis factor receptor superfamily. It is also referred to as B cell maturation antigen (BCMA) or CD269 in scientific publications. The protein possesses a conserved motif of six cysteines in the N-terminal region, forming a characteristic cysteine repeat motif that is typical of the extracellular domain of TNF receptors. This structural feature is critical for its functional interactions with ligands and subsequent downstream signaling . TNFRSF17 plays crucial roles in B cell biology, particularly in maintaining long-lived plasma cells and peripheral B cell populations.

What is the structural organization of TNFRSF17 and how does it relate to function?

TNFRSF17 exists as a homodimer in its native state, a structural characteristic that influences its biological activity . The protein contains the conserved cysteine-rich domains (CRDs) typical of TNF receptor family members, with the cysteine repeat motif in the extracellular domain being particularly important for ligand recognition. The protein's N-terminal region contains structural elements that facilitate receptor oligomerization, which is critical for signal transduction. Similar to other TNF receptor family members, TNFRSF17 likely contains a preligand binding assembly domain (PLAD) that facilitates receptor pre-assembly prior to ligand binding, though specific studies on TNFRSF17's PLAD are not as extensive as for other family members like CD95 and TNFR1 .

What is the tissue distribution pattern of TNFRSF17 and its implications for research?

TNFRSF17 exhibits a highly specific expression pattern primarily restricted to B-lineage cells. It is expressed on both resting and activated B cells, malignant B lymphocytes, and plasma cells . This restricted expression pattern makes TNFRSF17 particularly valuable as a target for studying B cell biology and related pathologies. When designing experiments involving TNFRSF17, researchers should consider this expression profile to select appropriate cell models. B cell lines or primary B cells isolated from peripheral blood or lymphoid tissues would be suitable experimental systems, while non-B cell lineages would serve as negative controls for expression studies.

How does TNFRSF17 contribute to normal B cell function?

TNFRSF17 plays a crucial role in maintaining the peripheral B cell population and ensuring the survival of long-lived bone marrow plasma cells . It functions as a receptor for BAFF (TNFSF13B) and APRIL (TNFSF13), two cytokines essential for B cell development and homeostasis. Upon ligand binding, TNFRSF17 initiates signaling cascades that promote B cell survival, differentiation, and antibody production. Interestingly, soluble BCMA can act as a decoy receptor for APRIL, potentially regulating the availability of this ligand for membrane-bound receptors . TNFRSF17 mRNA expression is stimulated by IL-4 and IL-6 in murine B cells, suggesting its regulation by cytokine networks involved in humoral immunity .

What is the relative binding affinity of TNFRSF17 for its ligands, and how can this be experimentally determined?

TNFRSF17 binds to two main ligands: APRIL (TNFSF13) and BAFF (TNFSF13B). Notably, the interaction between TNFRSF17 and APRIL demonstrates higher affinity compared to the TNFRSF17-BAFF interaction . This differential binding affinity has important implications for downstream signaling and biological outcomes. To experimentally determine binding affinities, researchers can employ surface plasmon resonance (SPR) using purified recombinant proteins. For cellular contexts, competitive binding assays with labeled ligands can quantify relative affinities. When investigating these interactions, researchers should account for potential effects of the His-tag on binding kinetics by including appropriate controls or by enzymatic tag removal prior to binding studies.

What are the key signaling pathways activated by TNFRSF17 and their experimental assessment?

Overexpression of TNFRSF17 in 293 cells activates multiple signaling pathways, including NF-kappa B, Elk-1, the c-Jun N-terminal kinase (JNK), and the p38 mitogen-activated protein kinase . These activations occur following TNFRSF17's association with TNF Receptor-Associated Factor (TRAF) 1, TRAF2, and TRAF3 . In breast cancer models, APRIL and BAFF-mediated activation of TNFRSF17 stimulates epithelial to mesenchymal transition and migration through the JNK signaling pathway . For experimental assessment of these pathways, researchers can utilize phospho-specific antibodies in Western blotting, luciferase reporter assays for transcription factor activation, and pharmacological inhibitors to confirm pathway specificity. RNA interference targeting specific TRAFs can further elucidate the contribution of individual adaptor proteins to TNFRSF17 signaling.

How does receptor oligomerization influence TNFRSF17 signaling capability?

Receptor oligomerization is a critical determinant of signaling capacity for TNF receptor family members, including TNFRSF17. While the search results don't specifically address TNFRSF17 oligomerization in detail, Table 2 indicates that related receptors like TACI (which shares ligands with TNFRSF17) form at least trimeric structures, as demonstrated through SDS-PAGE of immunoprecipitates, cross-linking studies, and FRET analysis . By analogy, TNFRSF17 likely forms similar oligomeric structures that facilitate signal transduction. The oligomerization state may affect which downstream adaptor proteins are recruited and which signaling pathways are activated. To study TNFRSF17 oligomerization, researchers could employ chemical cross-linking followed by SDS-PAGE, FRET analysis with fluorescently-tagged receptor constructs, or co-immunoprecipitation studies.

What approaches can distinguish between APRIL and BAFF-mediated TNFRSF17 signaling?

To distinguish between APRIL and BAFF-mediated TNFRSF17 signaling, researchers can implement several complementary approaches. First, selective neutralizing antibodies against either APRIL or BAFF can be used to block specific ligand interactions. Second, recombinant APRIL or BAFF proteins with point mutations that disrupt binding to TNFRSF17 can serve as negative controls. Third, competitive binding assays with soluble receptor domains can determine which ligand preferentially activates TNFRSF17 in different cellular contexts. Additionally, downstream signaling kinetics and pathway activation patterns may differ between the two ligands due to their different binding affinities, which can be monitored through time-course experiments analyzing phosphorylation of signaling proteins. Gene expression profiling following stimulation with either ligand can also reveal differential transcriptional responses.

How is TNFRSF17 implicated in multiple myeloma pathogenesis and monitoring?

Multiple myeloma patients show elevated serum BCMA (TNFRSF17) levels, which correlate with the proportion of plasma cells in bone marrow biopsies and clinical status . This makes serum BCMA levels a potential novel biomarker for predicting outcomes in multiple myeloma patients. Researchers investigating TNFRSF17 in multiple myeloma should consider both membrane-bound and soluble forms of the protein, as they may have distinct biological roles. For experimental approaches, ELISA assays can quantify soluble BCMA in patient serum, while flow cytometry can assess membrane expression on plasma cells. Correlation analyses between BCMA levels and clinical parameters (e.g., disease stage, treatment response) can provide insights into its utility as a biomarker. In vitro studies using multiple myeloma cell lines with manipulated TNFRSF17 expression can elucidate its role in plasma cell survival and proliferation.

What is the relationship between TNFRSF17 and autoimmune disorders?

TNFRSF17 expression is upregulated on peripheral blood mononuclear cells (PBMCs) from mice that develop Sjogren's-like syndrome, as well as in patients with Sjogren's syndrome, rheumatoid arthritis, and on B cells from systemic lupus erythematosus (SLE) patients . This upregulation suggests a potential role for TNFRSF17 in autoimmune pathogenesis, possibly through enhanced B cell survival and autoantibody production. When studying TNFRSF17 in autoimmune contexts, researchers should consider:

• Comparing expression levels between healthy donors and patients with various autoimmune conditions

• Analyzing correlations between TNFRSF17 expression and disease activity scores

• Examining the effects of standard immunosuppressive therapies on TNFRSF17 expression

• Testing whether blockade of TNFRSF17 or its ligands ameliorates disease in animal models

Flow cytometry with cell surface staining is ideal for assessing TNFRSF17 expression on specific immune cell subsets in these disorders.

What methodologies are optimal for studying TNFRSF17's role in breast cancer progression?

Studies have shown that both APRIL and BAFF increase epithelial to mesenchymal transition (EMT) and migratory capacity of breast cancer cells through TNFRSF17 and the JNK signaling pathway . Additionally, these ligands increase cancer stem cell numbers by enhancing the expression of pluripotency genes such as ALDH1A1, KLF4, and NANOG . To study TNFRSF17's role in breast cancer progression, researchers should employ:

• Cell migration assays (wound healing, Boyden chamber) following TNFRSF17 stimulation or knockdown

• EMT marker analysis (E-cadherin, vimentin, Snail, Twist) by immunoblotting and qRT-PCR

• Stemness assessment using the ALDEFLUOR assay, which measures ALDH activity in live cells by flow cytometry

• Sphere formation assays to evaluate self-renewal capacity

• Xenograft models with TNFRSF17-manipulated breast cancer cells to assess tumor-initiating potential

Co-expression analysis of APRIL, BAFF, BCMA (TNFRSF17), and pluripotency genes using publicly available datasets, such as MetaBRIC, can provide clinical correlations .

How can TNFRSF17 expression be evaluated in relation to therapy response in hormone-dependent cancers?

The GEO archive contains datasets like GDS3116 that provide paired transcriptome data from letrozole (aromatase inhibitor) treated patients before and after therapy, along with their response status . Using such resources, researchers can analyze TNFRSF17 expression changes in relation to therapy response. Methodological approaches include:

• Comparing pre- and post-treatment TNFRSF17 expression levels in responders versus non-responders

• Correlating TNFRSF17 expression with changes in estrogen-responsive genes

• Developing predictive models incorporating TNFRSF17 expression for therapy response

• Using transcription factor analysis tools like ISMARA to identify regulatory factors controlling TNFRSF17 expression during treatment

For experimental validation, patient-derived xenografts or organoids treated with hormone therapy can be assessed for TNFRSF17 expression changes and correlated with growth inhibition.

What are optimal experimental conditions for using recombinant TNFRSF17-Fc chimera?

When working with recombinant TNFRSF17-Fc chimera proteins, researchers should consider several factors to ensure optimal experimental outcomes. The protein should be stored according to manufacturer recommendations, typically at -80°C for long-term storage with aliquoting to avoid freeze-thaw cycles. Working solutions can be prepared at concentrations of 100-500 ng/ml in appropriate assay buffers, similar to the 100 ng/ml concentration used in APRIL and BAFF treatment experiments . Functional validation should include binding assays with known ligands (APRIL and BAFF) using techniques such as ELISA or surface plasmon resonance. When designing experiments, include appropriate controls such as isotype-matched Fc chimera proteins and consider the potential effects of the Fc portion on cellular interactions or receptor clustering.

How can researchers assess TNFRSF17-mediated effects on stem cell properties?

To evaluate TNFRSF17's impact on stem cell properties, particularly in cancer models, researchers can employ the ALDEFLUOR assay as described in the literature. This method involves incubating cells (e.g., 6 million cells/ml) with the ALDEFLUOR reagent, a fluorescent substrate for aldehyde dehydrogenase (ALDH), for approximately 45 minutes at 37°C . Control samples should include the specific ALDH inhibitor dimethylamino benzaldehyde (DEAB). Flow cytometry can then be used to measure the fluorescent reaction product, which is proportional to ALDH activity, using identical instrument settings for test and control samples . Additionally, researchers should assess expression of pluripotency genes such as ALDH1A1, KLF4, and NANOG using qRT-PCR or immunoblotting following TNFRSF17 stimulation or inhibition . Sphere formation assays in low-attachment conditions can provide functional validation of stemness properties.

What approaches can determine if TNFRSF17 falls into the category I or category II TNF receptor classification?

TNF receptors are categorized based on their response to soluble ligand trimers. Category I TNFRs (like TNFR1 and LTβR) are robustly activated by soluble ligand trimers, while Category II TNFRs (including 4-1BB, CD27, CD40, CD95, OX40, TNFR2) require membrane-bound or aggregated ligands for efficient signaling . To determine TNFRSF17's classification, researchers should:

• Compare cellular responses to soluble versus membrane-bound ligands

• Assess activation of downstream signaling pathways (NF-κB, JNK) after stimulation with different ligand forms

• Evaluate receptor clustering using microscopy techniques following exposure to soluble and membrane-bound ligands

• Examine the effects of artificially clustered soluble ligands (e.g., using antibody cross-linking)

Based on the literature, TNFRSF17 (BCMA) appears similar to other TNFRs that efficiently interact with soluble BAFF trimers but may require higher-order clustering for optimal signaling .

How can TNFRSF17 pre-ligand assembly be studied experimentally?

Pre-ligand assembly domains (PLADs) have been identified in several TNF receptor family members, primarily in the N-terminal CRD1 . To study potential PLAD-mediated assembly of TNFRSF17, researchers can employ several complementary approaches:

• Size exclusion chromatography to analyze the oligomeric state of the recombinant extracellular domain

• Cross-linking studies using chemical cross-linkers followed by SDS-PAGE analysis

• FRET analysis with fluorescently tagged receptor constructs

• Co-immunoprecipitation of differently tagged TNFRSF17 variants

• Mutagenesis of potential PLAD residues in the N-terminal region

Additionally, researchers could generate dimeric fusion proteins of the putative PLAD domain with glutathione S-transferase or Fc fragments, similar to approaches used with TNFR1, to test their ability to inhibit TNFRSF17 signaling, which would suggest competition for pre-ligand assembly .

How does TNFRSF17 receptor oligomerization compare with other TNF receptor family members?

TNFRSF17 receptor oligomerization can be compared to other TNF receptor family members using the data in Table 2 from the search results . While specific information about TNFRSF17 oligomerization is not directly provided, related receptors show various oligomerization states and mechanisms. For instance, some receptors like CD27, P75NGFR, and fractions of CD40 and 41BB form dimers through disulfide linkages . Others like TACI (which shares ligands with TNFRSF17) form at least trimers, as demonstrated through various techniques including SDS-PAGE of immunoprecipitates, cross-linking, and FRET . To experimentally compare TNFRSF17 oligomerization with other family members, researchers should employ multiple complementary techniques, including those mentioned in the table: SDS-PAGE analysis of immunoprecipitated receptors, cross-linking studies, FRET analysis, and size exclusion chromatography. This comparative approach would provide insights into whether TNFRSF17 follows patterns similar to other BAFF/APRIL receptors or has unique oligomerization properties.

What are the methodological considerations for studying TNFRSF17 in different cellular systems?

When studying TNFRSF17 in different cellular systems, researchers must consider several methodological factors to ensure robust and reproducible results:

• Expression level assessment: Quantify endogenous TNFRSF17 expression in the cellular system of interest using flow cytometry, Western blotting, or qRT-PCR before initiating functional studies.

• Ligand selection: Consider the differential binding affinities of APRIL versus BAFF when designing stimulation experiments .

• Signal pathway analysis: Include both early (minutes to hours) and late (hours to days) timepoints when assessing signaling responses, as TNFRSF17 activation affects both immediate signaling cascades (e.g., JNK, p38, NF-κB) and longer-term gene expression changes .

• Cellular context: Account for the expression of other BAFF/APRIL receptors (TACI, BAFFR) that might influence ligand availability and signaling outcomes.

• Experimental controls: Include receptor-blocking antibodies or soluble receptor domains as negative controls to confirm the specificity of observed effects.

For heterologous expression systems, consider using inducible expression systems to control TNFRSF17 levels and avoid potential artifacts from continuous overexpression.

How can researchers investigate potential therapeutic targeting of the TNFRSF17 pathway?

To investigate therapeutic targeting of the TNFRSF17 pathway, researchers can employ several strategic approaches:

• Blocking strategies:

  • Develop neutralizing antibodies against the extracellular domain of TNFRSF17

  • Design soluble decoy receptors based on the TNFRSF17 extracellular domain to sequester ligands

  • Create small molecule inhibitors targeting the TNFRSF17-ligand interaction interface

  • Develop ligand traps using fusion proteins

• Signaling inhibition:

  • Target downstream signaling components specific to TNFRSF17 pathways

  • Employ JNK inhibitors, which have been shown to block TNFRSF17-mediated effects in breast cancer models

• Preclinical testing:

  • Establish relevant disease models where TNFRSF17 plays a documented role

  • For multiple myeloma, use patient-derived xenografts that maintain TNFRSF17 expression

  • For autoimmune models, consider transgenic mice with altered TNFRSF17 expression

• Biomarker development:

  • Correlate serum soluble TNFRSF17 levels with disease progression and treatment response

  • Develop companion diagnostics to identify patients most likely to benefit from TNFRSF17-targeted therapies

The success of therapeutic approaches targeting other TNF receptor family members provides precedent for this strategy.

What computational approaches can predict TNFRSF17 involvement in gene regulatory networks?

Computational approaches to predict TNFRSF17 involvement in gene regulatory networks can utilize both publicly available datasets and novel analysis methods:

• Co-expression analysis: Analyze co-expression patterns between TNFRSF17, its ligands, and other genes across large datasets, as demonstrated in the MetaBRIC study of 2509 samples, which examined co-expression of APRIL, BAFF, BCMA, androgen receptor, and pluripotency genes .

• Transcription factor analysis: Employ web resources like ISMARA to predict transcription factor modifications through gene transcript changes, as was done in the analysis of letrozole-treated patient data .

• Network inference algorithms: Apply algorithms such as WGCNA (Weighted Gene Co-expression Network Analysis) to identify gene modules associated with TNFRSF17 expression across different conditions.

• Pathway enrichment analysis: Conduct Gene Ontology and pathway enrichment analyses on genes correlated with TNFRSF17 to identify biological processes potentially regulated by this receptor.

• Machine learning approaches: Develop predictive models that can identify potential regulatory relationships between TNFRSF17 and other genes based on expression patterns across multiple datasets.