NHL13 Antibody

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Description

Antibody Structure and Function

Immunoglobulins, the class of proteins to which NHL13 would belong, consist of two heavy chains and two light chains arranged in a "Y" shape . Key structural features include:

  • Variable (V) Region: Composed of 110–130 amino acids, this region determines antigen specificity via hypervariable regions (CDRs) that bind epitopes .

  • Constant (C) Region: Dictates effector functions (e.g., complement-dependent cytotoxicity) and classifies antibodies into IgM, IgG, IgA, IgD, or IgE .

Related NHL Antibodies

The search results emphasize antibodies targeting NHL, such as:

AntibodyTargetMechanismClinical Status
PRO131921CD20ADC/CDCCPhase I (completed)
hL243γ4PHLA-DRT-cell engagementPreclinical
CMG1A46CD3/CD19/CD20Trispecific T-cell activationPhase I/II

Key Insights:

  • PRO131921: A third-generation anti-CD20 antibody with enhanced ADC/CDCC activity compared to rituximab. Phase I trials showed tumor shrinkage correlated with drug exposure (AUC) .

  • hL243γ4P: A humanized IgG4 antibody with improved binding avidity (EC₅₀: 7 nM vs. 16.5 nM for parental mAb) .

  • Trispecific Antibodies: Next-generation agents like CMG1A46 target multiple antigens to enhance efficacy and reduce immune evasion .

Research Gaps

The absence of NHL13 Antibody in the search results suggests:

  1. Early Development Stage: NHL13 may be in preclinical studies or under proprietary research.

  2. Alternative Nomenclature: Potential confusion with existing antibodies (e.g., "NHL13" might refer to a non-standard naming convention).

  3. Limited Public Data: No peer-reviewed publications or clinical trial records were identified, indicating restricted access to NHL13-related information.

Product Specs

Buffer
Preservative: 0.03% ProClin 300
Components: 50% Glycerol, 0.01M PBS, pH 7.4
Form
Liquid
Lead Time
14-16 Weeks (Made-to-Order)
Synonyms
NHL13 antibody; At2g27080 antibody; NDR1/HIN1-like protein 13 antibody
Target Names
NHL13
Uniprot No.

Target Background

Function
This antibody is essential for plant immunity against the bacterial pathogen *Pseudomonas syringae* pv. *tomato* DC3000 (Pst DC3000).
Gene References Into Functions
  • Mutational analysis demonstrates that NHL13 is required for effective plant immunity, as evidenced by enhanced disease susceptibility in *nhl13* mutant plants. [NHL13] PMID: 26206852
Database Links

KEGG: ath:AT2G27080

STRING: 3702.AT2G27080.1

UniGene: At.68415

Subcellular Location
Cell membrane; Single-pass membrane protein.

Q&A

What is the mechanism of action for anti-CD20 antibodies in NHL research?

Anti-CD20 antibodies target the CD20 antigen expressed on B cells, functioning through multiple mechanisms including antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and direct induction of apoptosis. These antibodies bind specifically to CD20-expressing cells, including malignant B cells in NHL, facilitating their elimination through immune-mediated processes . The evolution of antibody design has led to increased cytotoxicity potential compared to first-generation antibodies like rituximab .

How do researchers establish appropriate preclinical models for antibody testing in NHL?

Effective preclinical models include SCID mouse models with human lymphoma cell lines engineered to express reporter genes like luciferase for bioluminescent tracking of disease progression. Researchers typically establish minimal-tumor-burden disseminated models to reflect early disease intervention scenarios. Methodologically sound approaches incorporate multiple controls including untreated specimens, free radioisotope controls, unlabeled antibody, and non-CD20 specific antibodies to validate target specificity . These models allow researchers to assess both single-dose and multiple-dose regimens across various therapeutic approaches.

What are the key pharmacokinetic parameters that influence antibody efficacy in NHL?

The relationship between drug exposure and clinical efficacy is critical in antibody research. Analysis demonstrates a statistically significant correlation between higher normalized drug exposure (normalized AUC) and tumor shrinkage (p = 0.0035) . Researchers should implement comprehensive sampling strategies that include pre- and post-infusion timepoints throughout treatment and extended follow-up periods. This pharmacokinetic analysis provides essential data for optimizing dosing strategies and predicting clinical responses.

How does radiolabeling impact the therapeutic efficacy of anti-CD20 antibodies?

Radiolabeled antibodies demonstrate distinct efficacy profiles depending on the radioisotope utilized. Comparative studies between alpha-emitter labeled antibodies (213Bi-rituximab) and beta-emitter labeled antibodies (131I-tositumomab, 90Y-rituximab) reveal important distinctions:

Treatment ApproachSurvival RateTumor-Free RateClinical Significance
Untreated controls0%0%Baseline for comparison
925-kBq 90Y-rituximab0%0%Limited efficacy despite beta emission
3,700 kBq 213Bi-rituximab75%~70%Alpha emission shows high curative potential
2,035 kBq 131I-tositumomab62.5%75%Alternative beta emitter with significant efficacy

Alpha-emitter labeled antibodies demonstrate curative potential in micrometastatic settings, though evidence suggests "a longer-lived α-emitter may be of greater efficacy" than shorter-lived isotopes like 213Bi .

What biological differences influence response variation between indolent and aggressive NHL subtypes?

Systems-based modeling approaches reveal a left-shift in exposure-response curves for indolent compared to aggressive NHL subtypes. This increased sensitivity in indolent NHL correlates with lower tumor proliferation rates and reduced baseline T-cell infiltration . Understanding these intrinsic biological differences enables rational design of subtype-specific dosing strategies. Research protocols should stratify patients by disease subtype and collect biospecimens for correlative analyses to further elucidate these mechanisms.

How does tumor burden affect the therapeutic window for antibody interventions?

Timing of antibody therapy relative to tumor burden critically impacts outcomes. In preclinical models, treatment initiated 4 days after tumor inoculation (representing minimal disease burden) demonstrates significantly higher cure rates compared to intervention in established disease . This therapeutic window phenomenon suggests early intervention strategies may be more effective, particularly for approaches like radioimmunotherapy. Clinical trial designs should consider disease burden as a stratification factor when evaluating novel antibody therapeutics.

What controls and experimental designs are essential for rigorous antibody efficacy studies?

Methodologically sound antibody research requires comprehensive control systems including:

  • Untreated control groups to establish baseline disease progression

  • Free radioisotope controls to confirm antibody-dependent effects

  • Unlabeled antibody controls to assess antibody contribution independent of conjugates

  • Non-specific antibody controls (e.g., anti-HER2/neu antibodies) to confirm target specificity

  • Comparison with established therapies (e.g., rituximab) as positive controls

Additionally, implementing both single and multiple dosing regimens provides critical insights into optimal treatment protocols. Studies demonstrate that "redosing of 213Bi-rituximab was more effective than single dosing," highlighting the importance of evaluating various administration schedules .

How can quantitative systems pharmacology approaches enhance antibody development?

Digital twin modeling represents an advanced methodological approach for antibody characterization. This technique involves developing virtual patients that represent biological, pharmacological, and tumor-related parameters observed in clinical trials . This approach provides several advantages:

Modeling ApplicationMethodological BenefitResearch Implication
Exposure-response characterizationPredicts clinical outcomes across dose rangesOptimizes dosing regimens
Subtype sensitivity analysisIdentifies biological determinants of responseEnables precision medicine approaches
Mechanism investigationTests hypotheses about cellular dynamicsGuides biomarker development
Parameter inferenceLinks patient characteristics to outcomesIdentifies predictive factors

These models suggest that "intratumor expansion of pre-existing T-cells, rather than an influx of systemically expanded T-cells, underlies the antitumor activity" of certain bispecific antibodies .

What pharmacokinetic sampling strategies maximize informational yield in early-phase trials?

Optimal pharmacokinetic assessment requires strategic sampling across multiple timepoints:

  • Pre- and post-infusion samples on all treatment days

  • Serial samples at 24 hours post-initial dose

  • Weekly sampling during treatment phase

  • Extended sampling for up to one year post-treatment

  • Concurrent anti-therapeutic antibody assessment using bridging electrochemiluminescence assays

This comprehensive approach enables correlation between exposure metrics and clinical outcomes, as demonstrated in the PRO131921 study where "normalized AUC levels were higher among responders and subjects displaying tumor shrinkage versus subjects progressing or showing no regression (p = 0.030)" .

How does dose escalation methodology influence safety and efficacy determination?

Early-phase trials typically employ a 3+3 dose escalation design to systematically evaluate safety while collecting efficacy signals. The PRO131921 study exemplifies this approach, with patients receiving escalating doses from 25 mg/m² to 800 mg/m² . This methodology enables:

  • Systematic safety assessment at each dose level

  • Pharmacokinetic data collection across the dosing spectrum

  • Identification of minimum effective dose

  • Determination of maximum tolerated dose

  • Early efficacy signal detection

Premedication protocols with acetaminophen and diphenhydramine should be standardized to manage potential infusion reactions and optimize tolerability.

What biomarker strategies can predict response to anti-CD20 therapy?

Biomarker development should focus on parameters that demonstrate predictive value:

Biomarker CategorySpecific ParametersMethodological Approach
Tumor parametersSize, proliferation rate, CD20 expression densityImmunohistochemistry, flow cytometry
Immune parametersBaseline T-cell infiltration, NK cell functionImmunophenotyping, functional assays
Pharmacological parametersNormalized AUC, maximum concentrationSerial blood sampling, drug level assessment
Genetic parametersFc receptor polymorphisms, tumor mutationsGenomic sequencing, SNP analysis

Digital twin modeling suggests that "the inferred digital twin parameters from clinical responders and nonresponders show that the potential biological difference that can influence response include tumor parameters (tumor size, proliferation rate, and baseline T-cell infiltration)" .

How do emerging bispecific antibody approaches compare with traditional anti-CD20 monotherapy?

Bispecific antibodies represent an evolution beyond traditional anti-CD20 approaches, with distinct mechanistic advantages:

  • Engagement of both tumor cells (via CD20) and T cells (via CD3)

  • Facilitation of T cell-mediated killing independent of natural T cell recognition

  • Potential to overcome resistance mechanisms to traditional antibody approaches

  • Differential activity in indolent versus aggressive disease subtypes

Research models suggest these approaches may provide enhanced efficacy through "intratumor expansion of pre-existing T-cells," representing a novel mechanism compared to traditional antibody approaches . Clinical trial designs should incorporate correlative studies to validate these mechanistic hypotheses.

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