LAD1 Antibody

What is LAD1 and what are the key applications of LAD1 antibodies in research?

LAD1 (Ladinin 1) refers to a 57 kDa anchoring filament protein that functions as a component of the basement membrane zone, contributing to the stability of epithelial layers with underlying mesenchyme. It's also an autoantigen associated with linear IgA disease .

LAD1 antibodies are primarily used in several key applications:

• Western blotting (1:2000-1:16000 dilution)

• Immunohistochemistry (1:500-1:2000 dilution)

• Immunofluorescence

• ELISA

These applications enable researchers to detect and quantify LAD1 expression in various tissues and cell types, with validated reactivity in human and mouse samples .

How do LAD1 antibodies help distinguish between normal and pathological tissue samples?

LAD1 antibodies are valuable tools for distinguishing normal from pathological tissues, particularly in cancer research. Studies have demonstrated significantly lower LAD1 protein expression in normal lung tissues compared to primary tumors in lung adenocarcinoma (LUAD) .

Immunohistochemistry (IHC) staining with LAD1 antibodies reveals:

• Differential expression between paired normal and tumor tissues

• Increased expression correlating with higher tumor stages and grades

• Distinct extracellular matrix patterns in diseased states

When conducting comparative analysis, researchers should optimize staining protocols using TE buffer pH 9.0 for antigen retrieval, though citrate buffer pH 6.0 may serve as an alternative .

What are the key differences between LAD1 (Ladinin 1) and LAD-1 (Leukocyte Adhesion Deficiency Type 1)?

Despite similar nomenclature, these represent distinct biological entities:

Researchers must clearly specify which LAD1 entity they're investigating to avoid confusion, as antibody-based studies may target either the protein or be used in evaluating the immunodeficiency syndrome .

How can LAD1 antibodies be optimized for dual immunofluorescence studies with other basement membrane markers?

For dual immunofluorescence studies combining LAD1 with other basement membrane markers:

• Protocol optimization:

  • Begin with sequential staining rather than simultaneous staining to avoid epitope masking

  • Use LAD1 antibody at 1:500-1:1000 for immunofluorescence applications

  • Select fluorophore-conjugated secondary antibodies with minimal spectral overlap

  • Include proper blocking (5-10% serum from secondary antibody host species)

• Compatible co-markers:

  • Basement membrane markers (laminin, collagen IV, nidogen)

  • Epithelial adhesion molecules (integrins, desmosomes)

  • Cell junction proteins for co-localization studies

• Validation approach:

  • Run single-marker controls alongside dual staining

  • Confirm specificity with peptide competition assays

  • Include known positive tissues such as human colon tissue where LAD1 expression is well-characterized

What insights can LAD1 antibodies provide in cancer research, particularly regarding metastasis and prognosis?

LAD1 antibodies have emerged as valuable tools in cancer research, particularly for studying metastatic potential and prognostic outcomes:

These findings suggest LAD1 antibodies can serve as tools for identifying patients with potentially more aggressive disease and for mechanistic studies of cancer progression.

How can researchers use LAD1 antibodies to investigate the relationship between LAD1 expression and β2 integrin function in LAD-1 patients?

While LAD1 (Ladinin 1) and LAD-1 (Leukocyte Adhesion Deficiency Type 1) are distinct entities, researchers investigating their potential relationship can employ LAD1 antibodies in several sophisticated approaches:

• Co-immunoprecipitation studies:

  • Use LAD1 antibodies to pull down associated protein complexes

  • Probe for β2 integrin family members (CD18, CD11a, CD11b)

  • Assess differences between normal samples and LAD-1 patient samples

• Proximity ligation assays:

  • Combine LAD1 antibodies with anti-CD18 or anti-CD11a/b antibodies

  • Visualize potential protein-protein interactions in situ

  • Compare normal vs. LAD-1 patient-derived cells

• Comparative expression analysis:

  • Quantify LAD1 expression in neutrophils and other leukocytes from:

    • Healthy controls

    • LAD-1 patients with moderate phenotype (1%-30% CD18 expression)

    • LAD-1 patients with severe phenotype (<1% CD18 expression)

This approach would help determine whether basement membrane alterations (involving LAD1) might contribute to or result from impaired neutrophil adhesion in LAD-1 patients.

What are the optimal fixation and antigen retrieval methods for LAD1 immunohistochemistry in different tissue types?

Optimal LAD1 immunodetection requires tissue-specific protocol adjustments:

For challenging samples, consider these troubleshooting approaches:

• For high background: Increase blocking time (2-3 hours with 5% BSA)

• For weak signal: Increase antibody concentration or incubation time (overnight at 4°C)

• For inconsistent results: Use positive control tissues (human colon cancer tissue)

The 16136-1-AP LAD1 antibody has been successfully validated for IHC applications in human colon cancer tissue with these protocols .

How should researchers design siRNA knockdown experiments to study LAD1 function in cell proliferation and migration?

Based on published research methodologies, the following protocol is recommended for effective LAD1 knockdown studies:

• siRNA design and validation:

  • Target at least 3 different regions of LAD1 mRNA

  • Include proper negative controls (scrambled siRNA)

  • Validate knockdown efficiency via Western blot (recommended dilution 1:2000-1:16000)

  • Aim for >70% reduction in protein expression

• Functional assays:

  • Cell proliferation: Count cells at 24h, 48h, and 72h post-transfection

  • Cell cycle analysis: Perform flow cytometry with propidium iodide staining

  • Migration assessment: Conduct wound-healing assays with regular measurements at 12-24h intervals

  • EMT marker evaluation: Western blot analysis of E-cadherin, N-cadherin, and vimentin

• Data analysis recommendations:

  • Perform each experiment in triplicate

  • Calculate statistical significance using appropriate tests (t-test or ANOVA)

  • Consider rescue experiments by reintroducing LAD1 expression to confirm specificity

Published data shows LAD1 knockdown significantly reduces proliferation and migration in lung adenocarcinoma cell lines, providing a methodological foundation for similar studies in other cancer types .

What controls should be included when using LAD1 antibody for analyzing clinical samples from patients with suspected Leukocyte Adhesion Deficiency?

When analyzing clinical samples for LAD-1 diagnosis using antibody-based methods, a comprehensive control strategy is essential:

• Essential controls:

  • Positive controls: Include known LAD1-expressing tissues (colon epithelium)

  • Negative controls: Primary antibody omission and isotype controls

  • Reference range controls: Samples from healthy donors matched for age/sex

  • Disease-specific controls:

    • Moderate LAD-1 phenotype (1%-30% CD18 expression)

    • Severe LAD-1 phenotype (<1% CD18 expression)

• Analytical validation:

  • Run parallel assays for CD11a, CD11b, and CD18 expression by flow cytometry

  • Include functional assays (neutrophil chemotaxis, zymosan test) regardless of normal β2-integrin expression levels

  • For suspected LAD-1/variant syndrome with normal integrin expression, unopsonized zymosan particle testing is recommended

• Interpretation guidelines:

  • Consider LAD1 syndrome unlikely if CD18 and associated molecules show normal expression

  • Note that normal protein expression doesn't exclude functional defects

  • In cases with high clinical suspicion but normal expression, proceed to functional testing

This approach ensures accurate diagnosis and avoids misclassification of patients with normal protein expression but functional defects.

How does LAD1 expression correlate with tumor progression in different cancer types?

LAD1 expression shows significant correlations with tumor progression across multiple parameters:

While the strongest evidence comes from lung adenocarcinoma studies, researchers should investigate whether similar patterns exist in other solid tumors to determine if LAD1 represents a pan-cancer progression marker.

What is the current understanding of using LAD1 antibodies to monitor treatment response in Leukocyte Adhesion Deficiency Type 1?

LAD1 antibodies can be valuable tools for monitoring treatment response in LAD-1 patients:

• Treatment monitoring applications:

  • Hematopoietic stem cell transplantation (HSCT): Track restoration of CD18/CD11 expression post-transplant

  • Ustekinumab therapy: Monitor inflammatory markers and immune cell function

  • Gene therapy approaches: Assess β2 integrin expression recovery

• Clinical response indicators:
  LAD1 antibodies help monitor:

  • Resolution of infections

  • Reduction in inflammation

  • Decreased tissue damage

  • Neutrophil adhesion normalization

• Novel therapeutic developments:

  • Ustekinumab (anti-IL-12/IL-23) has shown promise in LAD-1 treatment

  • Clinical trial NCT023366142 at the NIH Clinical Center is evaluating safety and tolerability

  • LAD1 antibodies are instrumental in monitoring interleukin pathway modulation effects on integrin expression and function

How can LAD1 antibodies help distinguish between different phenotypes of Leukocyte Adhesion Deficiency Type 1?

LAD1 antibodies, particularly those targeting CD18, CD11a, and CD11b, are crucial for phenotypic classification of LAD-1:

• Phenotypic characterization:

  • Severe phenotype: <1% of normal CD18 expression on neutrophils

    • Clinical features: Delayed umbilical stump separation (>30 days), omphalitis, persistent leukocytosis (>15,000/μL), severe destructive gingivitis

  • Moderate phenotype: 1%-30% of normal CD18 expression

    • Clinical features: Normal umbilical separation, lower risk of life-threatening infections, longer life expectancy, but still with leukocytosis and periodontal disease

• Flow cytometric analysis approach:

  • Monitor expression of multiple markers: CD18, CD11a, CD11b

  • Examine expression on different leukocyte populations

  • Compare with age-matched controls for accurate interpretation

• Correlation with genetic findings:

  • Different ITGB2 variants (encoding CD18) may correlate with specific expression patterns

  • The degree of protein expression reduction typically correlates with mutation severity

  • Both flow cytometry and genetic testing provide complementary diagnostic information

This approach allows researchers to accurately classify patients, predict disease severity, and select appropriate treatment strategies based on phenotypic classification.

What are common sources of false positives/negatives when using LAD1 antibodies, and how can researchers address these issues?

Researchers should be aware of several potential pitfalls when using LAD1 antibodies:

• Common false positive sources:

  • Cross-reactivity with similar basement membrane proteins

  • Excessive antibody concentration

  • Insufficient blocking

  • Endogenous peroxidase activity in IHC applications

  Solutions:

  • Validate antibody specificity with knockdown/knockout controls

  • Titrate antibody concentration (start with recommended 1:2000-1:16000 for WB, 1:500-1:2000 for IHC)

  • Extend blocking time (2 hours with 5% BSA)

  • Include proper quenching steps for endogenous enzymes

• Common false negative sources:

  • Inadequate antigen retrieval

  • Epitope masking by fixation

  • Antibody degradation

  • Sample processing issues

  Solutions:

  • Test multiple antigen retrieval methods (TE buffer pH 9.0 recommended)

  • Use fresher tissue samples with controlled fixation time

  • Aliquot antibodies to prevent freeze-thaw cycles

  • Include known positive controls (human colon tissue)

• Technical validation approaches:

  • Run parallel assays with alternative LAD1 antibody clones

  • Confirm specificity with peptide competition assays

  • Include gradient dilution series to establish optimal concentration

  • Document lot-to-lot variability when using polyclonal antibodies

How should researchers interpret discrepancies between LAD1 mRNA and protein expression in experimental data?

When facing discrepancies between LAD1 mRNA and protein levels, consider these analytical approaches:

• Common mechanisms for mRNA-protein discordance:

  • Post-transcriptional regulation (miRNAs targeting LAD1)

  • Post-translational modifications affecting protein stability

  • Differential mRNA stability or translation efficiency

  • Technical limitations in detection methods

• Systematic investigation strategy:

  • Temporal analysis: Measure both mRNA and protein at multiple timepoints

  • Half-life assessment: Determine protein turnover rate using cycloheximide chase

  • Translation efficiency: Ribosome profiling or polysome fractionation

  • Proteasomal inhibition: Test if protein levels increase with MG132 treatment

• Integrated data interpretation framework:

  • Consider tissue/cell type-specific regulation mechanisms

  • Assess whether discrepancies correlate with specific cellular states

  • Evaluate potential clinical significance (e.g., if protein levels better predict outcomes)

  • Design functional studies focused on the most relevant parameter (mRNA or protein)

This comprehensive approach helps determine whether discrepancies represent technical artifacts or biologically meaningful regulatory mechanisms.

What methodological considerations are important when comparing LAD1 antibody results across different experimental platforms?

Cross-platform comparison of LAD1 antibody data requires careful methodological standardization:

• Platform-specific optimization:

  Platform	Key Considerations	Recommended Controls
  Western Blot	Loading controls, transfer efficiency	Recombinant LAD1 protein standard
  IHC	Fixation method, antigen retrieval	Tissue microarrays with known expression
  Flow Cytometry	Surface vs. intracellular protocol	Fluorescence minus one (FMO) controls
  IF	Fixation method, permeabilization	Signal-to-noise ratio measurement

• Standardization approaches:

  • Use the same antibody clone and lot number when possible

  • Include calibration standards across experiments

  • Normalize to consistent reference samples

  • Establish quantitative reporting metrics (e.g., H-score for IHC)

• Data integration strategies:

  • Develop conversion factors between platforms when necessary

  • Use statistical methods that account for platform-specific variance

  • Consider meta-analysis approaches for integrating multiple datasets

  • Document all methodological details for transparent reporting

By addressing these considerations, researchers can ensure that observed differences reflect true biological variation rather than technical artifacts, enabling more reliable cross-study comparisons and meta-analyses.