TNFRSF10B is encoded by the TNFRSF10B gene located on chromosome 8p21.3. Its precursor comprises 440 amino acids, including:
Extracellular cysteine-rich domains for ligand binding (TRAIL) .
A transmembrane domain anchoring the receptor to the cell membrane.
A cytoplasmic death domain essential for apoptosis signaling .
The mature protein migrates at ~45–50 kDa under reducing SDS-PAGE due to glycosylation . Isoform-specific differences exist, with splice variants influencing ligand affinity and apoptotic efficiency .
TNFRSF10B activation involves:
Ligand Binding: Trimeric TRAIL binds to extracellular domains, inducing receptor trimerization .
Death-Inducing Signaling Complex (DISC) Formation: Recruitment of FADD and procaspase-8, leading to caspase-8 activation .
Caspase Cascade: Initiates apoptosis via caspase-3/7 cleavage .
Key regulatory factors include decoy receptors (e.g., TRAIL-R3/R4) and inhibitors like c-FLIP, which modulate sensitivity to TRAIL-induced apoptosis .
Head and Neck Squamous Cell Carcinoma (HNSCC): HPV(+) tumors exhibit distinct TNFRSF10B genomic profiles, including fewer deletions and higher TRAIL-R2 expression, correlating with enhanced sensitivity to SMAC mimetics (e.g., birinapant) combined with TRAIL .
Glioblastoma: TRAIL-R2-targeted therapies show efficacy when combined with tumor-penetrating peptides (e.g., iRGD) .
Under hypoxic conditions, TNFRSF10B is upregulated (log2FC = 3.66 in hypoxia vs. 2.48 in normoxia), sensitizing cells to TRAIL-mediated apoptosis when combined with compounds like skyrin .
Condition | Log2 Fold Change (TNFRSF10B) | Adj. p-Value |
---|---|---|
Hypoxia | 3.66 | 0 |
Normoxia | 2.48 | 0.01 |
Data derived from proteomic analysis under hypoxia and normoxia .
AF631 (Polyclonal): Detects endogenous TNFRSF10B at ~45 kDa in Western blot (HepG2 lysates) .
MAB6311 (Clone 71908): Used in flow cytometry to quantify TRAIL-R2 surface expression .
Fc Chimera (Catalog #10140-T2): Neutralizes TRAIL activity (ED₅₀ = 0.75–6 ng/mL) by binding soluble TRAIL, blocking receptor activation .
Parameter | Specification |
---|---|
Molecular Weight | 40.4 kDa (calculated) |
Purity | >95% (SDS-PAGE) |
Storage | Lyophilized at -20°C/-70°C |
Data for recombinant Human TRAIL-R2 Fc chimera .
The LOVD database documents 80 unique TNFRSF10B variants linked to pathologies like HNSCC. Notable variants include shallow deletions in HPV(−) tumors and amplifications in HPV(+) cohorts .
TNFRSF10B (TNF receptor superfamily member 10b) is a member of the TNF-receptor superfamily that contains an intracellular death domain. This receptor can be activated by tumor necrosis factor-related apoptosis inducing ligand (TNFSF10/TRAIL/APO-2L) and transduces an apoptosis signal . The primary function of TNFRSF10B is mediating programmed cell death through activation of the extrinsic apoptotic pathway. When the receptor binds to its ligand TRAIL, it initiates a signaling cascade that ultimately leads to cell death, making it an important component of normal cellular turnover and immune surveillance against cancer cells .
TNFRSF10B is located on chromosome 8p21.3 in the human genome . The gene has numerous aliases used in scientific literature, including: DR5, CD262, KILLER, TRICK2, TRICKB, ZTNFR9, TRAILR2, TRICK2A, TRICK2B, TRAIL-R2, and KILLER/DR5 . These multiple designations reflect its discovery by different research groups and its various functional characteristics that have been identified over time.
TNFRSF10B contains an intracellular death domain that is critical for its pro-apoptotic function . Studies with FADD-deficient mice have demonstrated that FADD (Fas-associated death domain protein), a death domain containing adaptor protein, is required for the apoptosis mediated by TNFRSF10B . The protein has two isoforms produced by alternative splicing, as well as a non-coding transcript variant . The binding domain of TNFRSF10B demonstrates polar characteristics, which influences its interactions with ligands and potential inhibitors .
TNFRSF10B has been associated with multiple cancer types through various research studies. Based on publication data, the following cancer types have demonstrated significant associations with TNFRSF10B:
Cancer Type | Number of Published Papers |
---|---|
Breast Cancer | 23 |
Lung Cancer | 11 |
Colorectal Cancer | 10 |
Prostate Cancer | 7 |
Head and Neck Cancers | 7 |
von Hippel-Lindau Disease | 1 |
Cervical Cancer | 0 |
This publication distribution suggests that breast cancer has the strongest research focus regarding TNFRSF10B, followed by lung and colorectal cancers . These associations may involve abnormal protein expression, mutations, or alterations in TNFRSF10B signaling pathways that contribute to cancer development or progression.
TNFRSF10B polymorphisms have been significantly associated with cancer survival outcomes, particularly in non-small cell lung cancer (NSCLC). Research has identified four key SNPs in TNFRSF10B (rs11785599, rs1047275, rs4460370, and rs883429) that correlate with patient survival .
The T-allele of rs11785599 was associated with a 41% increased risk of death (95% CI = 1.16–1.70), while the other three TNFRSF10B risk alleles exhibited 35%, 29%, and 24% increased risk of death, respectively . Furthermore, haplotype analyses revealed that patients carrying the risk haplotype (TCTT) had a 78% increased risk of death compared to those with the low-risk haplotype (CGCC) . These findings suggest that germline genetic variations in TNFRSF10B could serve as biomarkers for predicting survival and potentially guide treatment decisions for NSCLC patients.
Researchers employ multiple methodological approaches to study TNFRSF10B in cancer contexts:
When designing experiments to evaluate TNFRSF10B inhibitors, researchers should consider a comprehensive approach that includes both computational and laboratory methodologies:
In-silico analysis: Begin with computational modeling of TNFRSF10B protein structure and virtual screening of potential inhibitors. This should include evaluation of binding interactions within the protein's polar binding pocket .
Drug property assessment: Evaluate candidate molecules for drug-related properties including absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles. Screen for potential toxicity, mutagenicity, irritant effects, and carcinogenicity .
Binding validation: Employ techniques such as surface plasmon resonance or isothermal titration calorimetry to validate predicted binding interactions between TNFRSF10B and candidate inhibitors.
Functional assays: Develop cell-based assays to measure the impact of inhibitors on TNFRSF10B-mediated apoptosis, using appropriate cancer cell lines relevant to the cancer type being studied.
In-vivo testing: Progress to animal models to assess the efficacy and safety of promising inhibitors, with particular focus on models that recapitulate the cancer type of interest (e.g., head and neck cancer models) .
Several statistical approaches are appropriate for analyzing TNFRSF10B genetic variation data:
Research has revealed important insights into how TNFRSF10B haplotypes affect treatment response in cancer patients. In non-small cell lung cancer (NSCLC), data stratified by treatment showed that risk haplotypes exhibited statistically significantly increased risk of death among patients who had surgery only, while showing no statistically significant effects among patients who had surgery and adjuvant chemotherapy . This suggests that TNFRSF10B haplotypes may have predictive value for determining which patients might benefit from adjuvant chemotherapy following surgery.
The differential effect of haplotypes across treatment groups indicates potential gene-treatment interactions that could be exploited for personalized medicine approaches. Researchers investigating this phenomenon should design studies that specifically test for treatment-by-genotype interactions and consider the molecular mechanisms through which TNFRSF10B variants might affect response to specific therapeutic agents .
Translating TNFRSF10B research findings into clinical applications requires several strategic approaches:
Biomarker development: Validated germline biomarkers based on TNFRSF10B polymorphisms and haplotypes may have important clinical implications for optimizing patient-specific treatment . Researchers should focus on prospective validation studies in diverse patient populations.
Drug development pipeline: Novel designed molecules targeting TNFRSF10B that fulfill the properties of competent drugs and lack toxicity should progress through preclinical and clinical testing phases . Researchers should ensure these candidate compounds demonstrate favorable pharmacological properties.
Functional validation: In-vivo experimentation in animal models is critical to validate the effect of targeted protein interactions, which may lead to approved drugs for conditions such as head and neck cancer .
Translational studies: Design studies that bridge the gap between basic science findings and clinical applications, focusing on how TNFRSF10B-based biomarkers can guide treatment decisions in real-world clinical settings.
Phylogenetic considerations: Utilize the high homology (>80%) between human and primate TNFRSF10B to inform prediction of protein functions and family relationships, which can aid in drug development .
When investigating TNFRSF10B protein interactions, researchers should consider multiple complementary approaches:
Computational prediction: Utilize computational tools to predict potential interacting partners based on structural complementarity, sequence homology, and functional pathways. This serves as a starting point for wet-lab validation .
Yeast two-hybrid (Y2H) screening: This method can identify direct binary interactions between TNFRSF10B and potential partners, though it may produce false positives and requires confirmation through secondary methods.
Co-immunoprecipitation (Co-IP): This technique allows for the pull-down of protein complexes containing TNFRSF10B from cell lysates, providing evidence of interactions within the cellular context.
Proximity ligation assays (PLA): These assays can visualize and quantify protein-protein interactions in situ, offering spatial information about where interactions occur within cells.
Functional and expressional studies: Combine interaction data with functional studies to establish the biological significance of identified interactions .
Addressing contradictory findings in TNFRSF10B research requires a systematic approach:
TNFRSF10B contains an intracellular death domain, which is essential for transmitting apoptotic signals . The receptor is activated by binding to its ligand, tumor necrosis factor-related apoptosis-inducing ligand (TNFSF10/TRAIL/APO-2L) . Upon activation, TNFRSF10B recruits the adaptor molecule FADD (Fas-Associated protein with Death Domain), which in turn recruits and activates caspase-8 . This leads to the formation of the death-inducing signaling complex (DISC), initiating a cascade of caspase activations that ultimately result in apoptosis .
The ability of TNFRSF10B to induce apoptosis makes it a critical player in maintaining cellular homeostasis and preventing tumor development . Dysregulation of TNFRSF10B signaling has been implicated in various cancers, including squamous cell carcinoma of the head and neck and laryngeal squamous cell carcinoma . Additionally, TNFRSF10B is involved in the regulation of immune responses and inflammation .
Given its role in apoptosis, TNFRSF10B is a potential target for cancer therapy . Strategies to enhance TNFRSF10B signaling could promote the selective killing of cancer cells while sparing normal cells . Research has shown that endoplasmic reticulum stress can regulate the expression and localization of TNFRSF10B, influencing its ability to induce apoptosis and affect chemotherapy resistance in cancers such as triple-negative breast cancer (TNBC) .
Human recombinant TNFRSF10B is produced using recombinant DNA technology, allowing for the study of its structure, function, and therapeutic potential in a controlled laboratory setting . This recombinant protein is used in various research applications, including the investigation of apoptotic pathways, cancer biology, and drug development .