LUM Antibody

What is Lumican (LUM) and why is it important in research?

Lumican is a small leucine-rich proteoglycan that serves as a crucial component of the extracellular matrix. As revealed in recent studies, Lumican plays significant roles in multiple biological processes including tissue organization, cell migration, and cancer progression. The importance of Lumican in research stems from its demonstrated involvement in pathological conditions, particularly in colorectal adenocarcinoma (COAD) where high LUM expression has been identified as an independent determinant of poor prognosis . Additionally, research has shown that LUM is closely associated with immune infiltration mechanisms and the miR200 family, potentially promoting epithelial-to-mesenchymal transition in cancer progression . These findings position LUM as an important target for studies focused on extracellular matrix biology and cancer research.

What applications are LUM antibodies typically used for in research settings?

LUM antibodies serve multiple research applications in laboratory settings. Based on validated protocols, these antibodies are primarily used in:

• Western Blotting (WB): For detecting and quantifying LUM protein expression in tissue or cell lysates

• Immunohistochemistry (IHC): For visualizing LUM distribution in tissue sections

• Enzyme-Linked Immunosorbent Assay (ELISA): For quantitative measurement of LUM in solution

• Flow Cytometry: For analyzing LUM expression in cell populations

Each application requires specific optimization parameters, including dilution ratios, incubation conditions, and detection systems. When working with LUM antibodies in these contexts, researchers should be mindful that the observed molecular weight in experimental conditions (70 kDa) may differ from the calculated molecular weight (52.588 kDa), potentially due to post-translational modifications or glycosylation patterns .

How do storage conditions affect LUM antibody performance?

Proper storage conditions are critical for maintaining LUM antibody functionality and experimental reproducibility. For lyophilized LUM antibodies, storage at -20°C is recommended for up to one year from the date of receipt . After reconstitution, the antibody remains stable at 4°C for approximately one month. For longer-term storage post-reconstitution, the antibody should be aliquoted to avoid repeated freeze-thaw cycles and stored at -20°C for up to six months .

Research indicates that repeated freeze-thaw cycles significantly diminish antibody binding capacity through protein denaturation and aggregation. To preserve antibody functionality, it is advisable to:

• Divide reconstituted antibody into single-use aliquots

• Store aliquots in sterile, nuclease-free tubes with minimal air space

• Record dates of reconstitution and aliquoting

• Monitor antibody performance periodically using positive controls

These measures help ensure experimental consistency and reliable results across studies.

What reconstitution protocols are recommended for lyophilized LUM antibodies?

Proper reconstitution of lyophilized LUM antibodies is essential for optimal performance. The recommended protocol involves adding 0.2 ml of distilled water to achieve a concentration of 500 μg/ml . Each vial typically contains stabilizing agents such as 4 mg Trehalose, 0.9 mg NaCl, and 0.2 mg Na₂HPO₄ to maintain antibody integrity .

For optimal reconstitution:

• Allow the lyophilized antibody to equilibrate to room temperature (approximately 20-25°C) before opening

• Briefly centrifuge the vial to collect all material at the bottom

• Add the recommended volume of sterile distilled water directly to the lyophilized powder

• Gently rotate or invert the vial to ensure complete dissolution without foaming

• Allow the solution to stand for 5-10 minutes at room temperature

• For applications requiring specific buffers, reconstitute in sterile water first, then dilute in the appropriate buffer

After reconstitution, the antibody solution should appear clear without particulate matter. Any visible precipitation indicates potential denaturation or aggregation, which may compromise experimental results.

How can researchers validate LUM antibody specificity for cross-species applications?

Cross-species reactivity validation is a critical consideration when using LUM antibodies across different experimental models. While commercial antibodies may claim reactivity with multiple species (such as human, mouse, and rat), independent validation is essential . Cross-reactivity validation should include:

• Sequence homology analysis: Human LUM shares 88.4% and 86.9% amino acid sequence identity with mouse and rat LUM, respectively, suggesting potential cross-reactivity . Researchers should examine the immunogen sequence used for antibody generation against sequences from target species.

• Positive and negative control experiments: Include tissue or cell samples known to express or lack LUM from each target species.

• Western blot band pattern analysis: Compare band patterns and molecular weights across species, noting that differences in post-translational modifications may cause species-specific variations.

• Blocking peptide experiments: Use species-specific blocking peptides to confirm antibody specificity.

• Knockout/knockdown validation: When available, include samples with genetic ablation of LUM to confirm signal specificity.

What strategies can address the discrepancy between observed (70 kDa) and calculated (52.588 kDa) molecular weights of LUM?

The significant discrepancy between the observed molecular weight (70 kDa) and calculated molecular weight (52.588 kDa) of Lumican presents an important research consideration . This discrepancy is likely attributable to post-translational modifications, particularly glycosylation patterns that are characteristic of proteoglycans. To address this technical challenge:

• Differential deglycosylation experiments: Treat samples with enzymes specific for different glycosylation types (PNGase F for N-linked or O-glycosidase for O-linked glycosylation) before Western blot analysis.

• Gradient gel electrophoresis: Employ gradient gels (4-20%) to better resolve proteins with extensive modifications.

• 2D gel electrophoresis: Separate proteins by both isoelectric point and molecular weight to identify potential isoforms.

• Mass spectrometry validation: Confirm protein identity and characterize modifications using LC-MS/MS analysis of immunoprecipitated or gel-extracted bands.

• Species comparison: Analyze LUM molecular weight across species to identify conserved patterns of migration.

These approaches not only validate antibody specificity but also provide valuable information about tissue-specific or disease-related changes in LUM post-translational modifications.

How can researchers optimize LUM antibody-based immunoprecipitation protocols for studying protein-protein interactions?

Immunoprecipitation (IP) using LUM antibodies presents unique challenges due to Lumican's extracellular matrix localization and extensive post-translational modifications. For optimal IP protocol development:

• Lysis buffer optimization: Test different lysis conditions that effectively solubilize extracellular matrix components while preserving protein-protein interactions:

  • RIPA buffer supplemented with proteoglycin-specific solubilizers

  • Detergent combinations (e.g., NP-40 with low SDS concentration)

  • Inclusion of glycosidase inhibitors to preserve glycosylation states

• Crosslinking considerations: For transient interactions, consider formaldehyde or DSS (disuccinimidyl suberate) crosslinking before cell lysis.

• Antibody orientation strategies:

  • Direct coupling to beads using crosslinking chemistries to prevent heavy chain interference

  • Use of isotype-specific secondary antibodies for detection

  • Employment of antibody fragments (Fab or F(ab')₂) for reduced background

• Elution conditions: Optimize between harsh (reducing, denaturing) and mild (competing peptide) elution methods depending on downstream applications.

• Controls:

  • IgG-matched control precipitations

  • Knockout/knockdown samples for specificity validation

  • Pre-clearing steps to reduce non-specific binding

This methodical approach helps identify genuine LUM-interacting proteins while minimizing artifacts commonly encountered in IP experiments.

What are the critical considerations for using LUM antibodies in multiplexed immunofluorescence studies?

Multiplexed immunofluorescence involving LUM antibodies requires careful planning to ensure signal specificity and minimize cross-reactivity. Advanced considerations include:

• Antibody panel design:

  • Select antibodies raised in different host species to enable species-specific secondary antibodies

  • When using multiple rabbit antibodies (like the polyclonal Anti-Lumican/LUM Antibody ), employ sequential tyramide signal amplification with bleaching steps between rounds

• Epitope retrieval optimization:

  • Test multiple antigen retrieval methods (heat-induced vs. enzymatic)

  • Determine optimal pH conditions (citrate buffer pH 6.0 vs. EDTA buffer pH 9.0)

  • Evaluate retrieval duration impact on extracellular matrix proteins

• Control strategies:

  • Single-color controls to establish baseline signals

  • Fluorophore minus one (FMO) controls to assess spectral overlap

  • Blocking peptide controls for validation of LUM-specific signals

• Image acquisition parameters:

  • Sequential scanning to minimize bleed-through

  • Consistent exposure settings across experimental groups

  • Z-stack acquisition for three-dimensional analysis of extracellular matrix components

• Quantification approaches:

  • Colocalization analysis using Pearson's or Manders' coefficients

  • Intensity normalization procedures

  • Machine learning-based segmentation for complex tissue architecture

These considerations ensure reliable interpretation of LUM distribution in relation to other markers in complex tissue environments.

How can LUM antibodies be utilized to investigate the role of Lumican in colorectal cancer progression?

Research has established that high LUM expression correlates with poor prognosis in colorectal adenocarcinoma (COAD) . Investigating this relationship requires strategic application of LUM antibodies across multiple experimental platforms:

• Tissue microarray (TMA) analysis:

  • Compare LUM expression across tumor stages, histological subtypes, and anatomical locations

  • Correlate expression with patient survival data using Kaplan-Meier analysis

  • Implement multivariate COX analysis to determine if LUM expression is an independent prognostic factor

• Cell line model systems:

  • Analyze LUM expression in COAD cell lines with different metastatic potentials

  • Perform knockdown/overexpression studies followed by antibody-based validation

  • Examine secreted vs. cell-associated LUM using cellular fractionation and Western blotting

• 3D organoid cultures:

  • Investigate LUM distribution in patient-derived organoids using immunofluorescence

  • Compare staining patterns between normal and tumor-derived organoids

  • Monitor changes in LUM expression during organoid formation and growth

• Xenograft models:

  • Track LUM expression changes during tumor progression in vivo

  • Correlate with invasive front characteristics and metastatic behavior

  • Perform therapeutic targeting studies using LUM-specific approaches

These methodological approaches can elucidate the functional role of LUM in cancer progression and potentially identify new therapeutic targets.

What methodological approaches can investigate LUM's relationship with immune infiltration in tumors?

Recent research indicates that LUM expression is closely related to immune infiltration and correlates with regulatory T cells, tumor-associated macrophages, and dendritic cells . To methodically investigate this relationship:

• Spatial transcriptomics and multiplexed imaging:

  • Combine LUM antibody staining with immune cell markers

  • Analyze spatial relationships between LUM-rich regions and immune cell localization

  • Implement computational approaches to quantify cell-type specific associations

• Flow cytometry panels:

  • Design multi-parameter panels including LUM and immune cell markers

  • Analyze correlation between LUM expression and immune checkpoint molecules

  • Sort LUM-high vs. LUM-low populations for functional studies

• Single-cell analysis workflows:

  • Integrate antibody-based cell sorting with single-cell RNA sequencing

  • Identify cell populations co-expressing LUM and immune regulatory factors

  • Construct cellular interaction networks based on receptor-ligand pairs

• In vitro immune co-culture systems:

  • Establish tumor-immune cell co-cultures with varying LUM expression levels

  • Measure immune cell function (cytokine production, cytotoxicity) in relation to LUM

  • Test LUM antibody blocking effects on immune cell recruitment and function

These approaches can elucidate the mechanistic basis of LUM's influence on the tumor immune microenvironment and inform immunotherapy strategies.

How can researchers effectively investigate the relationship between LUM and the miR200 family in epithelial-to-mesenchymal transition?

Studies have suggested that LUM may promote cancer progression by targeting the miR200 family to facilitate epithelial-to-mesenchymal transition (EMT) . To rigorously investigate this relationship:

• Sequential immunoprecipitation approaches:

  • Perform RNA immunoprecipitation using LUM antibodies followed by miRNA profiling

  • Implement CLIP-seq (crosslinking immunoprecipitation-sequencing) to identify direct RNA-protein interactions

  • Validate findings using reporter constructs with miR200 family binding sites

• EMT model systems with LUM manipulation:

  • Induce EMT through TGF-β treatment while monitoring LUM and miR200 expression

  • Perform LUM knockdown/overexpression and assess effects on EMT markers (E-cadherin, vimentin, ZEB1/2)

  • Use LUM antibodies to track protein localization changes during EMT progression

• Rescue experiments:

  • Test whether miR200 family mimics can rescue phenotypes caused by LUM overexpression

  • Examine if LUM antibody blockade affects miR200-dependent cellular processes

  • Develop miR200-resistant LUM constructs to dissect specific interaction effects

• In vivo validation approaches:

  • Generate xenograft models with manipulated LUM and miR200 expression

  • Analyze tumor sections using multiplexed immunofluorescence for EMT markers

  • Correlate findings with patient samples stratified by LUM expression levels

These methodological approaches can uncover the molecular mechanisms linking LUM to EMT through miR200 family regulation, potentially identifying new therapeutic opportunities.

How can researchers address non-specific binding issues when using LUM antibodies in complex tissue samples?

Non-specific binding presents a significant challenge when using LUM antibodies, particularly in tissues with abundant extracellular matrix. Methodological solutions include:

• Optimization of blocking protocols:

  • Compare protein-based (BSA, normal serum) vs. polymer-based blockers

  • Test combination blockers containing both proteins and detergents

  • Implement species-matched serum corresponding to secondary antibody source

• Antigen retrieval assessment:

  • Compare heat-induced vs. enzymatic retrieval methods

  • Optimize retrieval duration specifically for extracellular matrix proteins

  • Consider dual retrieval methods for complex tissue samples

• Antibody titration matrices:

  • Perform systematic dilution series (typically 1:100 to 1:5000)

  • Evaluate signal-to-noise ratio quantitatively across dilutions

  • Determine optimal antibody concentration for each specific application

• Advanced validation controls:

  • Include absorption controls using recombinant LUM protein

  • Implement LUM-depleted samples through immunodepletion

  • Use tissues from LUM knockout models when available

• Detection system optimization:

  • Compare direct vs. amplified detection methods

  • Evaluate enzyme-based vs. fluorescence-based visualization

  • Consider tyramide signal amplification for low abundance targets

These systematic approaches can significantly improve signal specificity in challenging samples.

What protocols can improve reproducibility when using LUM antibodies across different experimental batches?

Batch-to-batch variability presents a major challenge in antibody-based research. To enhance reproducibility when working with LUM antibodies:

• Standard operating procedure (SOP) development:

  • Document detailed protocols including specific reagent sources

  • Record lot numbers for all antibodies and critical reagents

  • Maintain consistent incubation times and temperatures across experiments

• Reference sample inclusion:

  • Include standardized positive control samples in each experimental batch

  • Maintain a tissue/cell reference bank for longitudinal comparisons

  • Consider developing an internal reference standard curve

• Normalization strategies:

  • Implement loading controls appropriate for the experimental system

  • Utilize housekeeping proteins for Western blot normalization

  • For IHC/IF, include reference tissues on each slide or run control slides in parallel

• Quality control checkpoints:

  • Develop acceptance criteria for positive and negative controls

  • Establish signal intensity ranges for standardized samples

  • Implement regular antibody validation tests

• Data analysis standardization:

  • Use consistent quantification methods across experimental batches

  • Employ blinded analysis for subjective evaluations

  • Document software versions and analysis parameters

These approaches build a robust framework for generating reproducible data using LUM antibodies across extended research timelines.

How can researchers optimize LUM antibody-based Western blotting protocols for detecting variable glycosylation patterns?

The variable glycosylation of Lumican presents unique challenges for Western blot analysis. Optimized protocols should account for these variations:

• Sample preparation modifications:

  • Test different lysis buffers optimized for glycoproteins

  • Include deglycosylation controls (PNGase F, O-glycosidase)

  • Prepare samples with and without reducing agents to preserve structure-dependent epitopes

• Gel system optimization:

  • Employ gradient gels (4-20%) to resolve heterogeneously glycosylated species

  • Consider using specialized gel systems designed for glycoprotein separation

  • Optimize running conditions (voltage, time, temperature) for high molecular weight forms

• Transfer considerations:

  • Test different transfer methods (wet, semi-dry, high MW protocols)

  • Optimize transfer duration for complete transfer of high molecular weight species

  • Validate transfer efficiency using reversible staining methods

• Detection strategy refinement:

  • Compare antibodies targeting different LUM epitopes

  • Implement dual detection with glycan-specific and protein-specific antibodies

  • Consider enhanced chemiluminescence substrates for improved sensitivity

• Post-detection analysis:

  • Document all visible bands and their relative intensities

  • Consider total LUM quantification vs. specific glycoform analysis

  • Implement densitometry methods that account for broad or diffuse bands

These optimizations help capture the biological complexity of LUM expression and modification across experimental systems.

How can LUM antibodies be integrated into advanced imaging techniques for extracellular matrix research?

Emerging imaging technologies offer new opportunities for studying LUM in its native context. Strategic integration of LUM antibodies includes:

• Super-resolution microscopy applications:

  • Implement STORM or PALM imaging using directly labeled LUM antibodies

  • Examine nanoscale distribution of LUM within collagen fibrils

  • Study co-localization with other matrix components at unprecedented resolution

• Intravital imaging approaches:

  • Develop fluorescently labeled LUM antibody fragments for in vivo imaging

  • Monitor dynamic changes in LUM distribution during tissue remodeling

  • Track LUM in disease models using window chamber techniques

• Expansion microscopy protocols:

  • Adapt protocols for extracellular matrix proteins like LUM

  • Optimize antibody penetration in expanded hydrogels

  • Investigate 3D relationships between LUM and cellular components

• Correlative light and electron microscopy:

  • Develop gold-conjugated LUM antibodies for immunoelectron microscopy

  • Implement CLEM workflows to correlate functional and ultrastructural data

  • Examine LUM distribution at the ultrastructural level

• Light sheet microscopy applications:

  • Optimize clearing protocols compatible with LUM antibody epitopes

  • Visualize LUM distribution throughout intact tissue volumes

  • Quantify spatial relationships across multiple scales

These advanced imaging approaches provide unprecedented insights into LUM biology in complex tissue environments.

What considerations are important when using LUM antibodies in therapeutic research contexts?

As research suggests LUM could be a potential target in cancer therapy , several considerations apply when using LUM antibodies in therapeutic research:

• Antibody functional classification:

  • Characterize antibodies as neutralizing vs. non-neutralizing

  • Determine if antibodies affect LUM-receptor interactions

  • Assess impact on LUM-dependent signaling pathways

• Internalization and trafficking studies:

  • Evaluate if LUM antibodies trigger receptor internalization

  • Track intracellular fate using pH-sensitive fluorophores

  • Assess potential for antibody-drug conjugate applications

• Immune effector function analysis:

  • Test antibody capability to engage complement or Fc receptors

  • Evaluate antibody-dependent cellular cytotoxicity potential

  • Assess impact on immune cell recruitment to LUM-expressing tissues

• In vivo pharmacology considerations:

  • Determine antibody half-life and tissue distribution

  • Optimize dosing regimens based on target engagement

  • Evaluate combination approaches with standard therapies

• Toxicity and off-target effect profiling:

  • Assess cross-reactivity with other proteoglycans

  • Evaluate impact on normal tissue homeostasis

  • Determine potential compensatory mechanisms after LUM targeting

These methodological considerations provide a framework for translating fundamental LUM biology into therapeutic applications.

How can LUM antibodies be incorporated into Fabrack-CAR T cell technology for cancer immunotherapy?

Recent innovations in universal CAR T cell technology, such as the Fabrack-CAR system, present opportunities for using LUM antibodies in targeted immunotherapy applications . Methodological considerations include:

• Meditope-enabling of LUM antibodies:

  • Adapt LUM antibodies to contain the meditope-binding pocket

  • Validate retained binding specificity after engineering

  • Optimize antibody production and quality control

• Target validation strategies:

  • Confirm LUM expression patterns in target tumors

  • Evaluate accessibility of LUM in solid tumor microenvironments

  • Assess potential off-tumor binding to normal tissues

• Functional testing protocols:

  • Implement CD107a degranulation assays to measure T cell activation

  • Quantify IFNγ production as a measure of effector function

  • Develop viability assays to assess tumor cell killing efficiency

• Combination targeting approaches:

  • Test simultaneous targeting of LUM with other tumor antigens

  • Evaluate sequential administration strategies

  • Assess synergistic potential with immune checkpoint inhibitors

• In vivo model development:

  • Establish xenograft models with variable LUM expression

  • Implement humanized mouse models for improved translational relevance

  • Develop imaging strategies to track both CAR T cells and target engagement

These approaches could expand the application of LUM-targeted therapies to include cellular immunotherapy, potentially addressing limitations of current treatment modalities.

What statistical approaches are recommended when analyzing LUM expression data across patient cohorts?

Research has successfully applied these methods to demonstrate that high LUM expression is an independent determinant of poor prognosis in colorectal adenocarcinoma, with ROC curve analysis confirming the diagnostic value (AUC = 0.790) . When implementing these approaches, researchers should consider sample size requirements, adjust for multiple comparisons, and validate findings in independent cohorts.

How can researchers resolve contradictory findings regarding LUM function across different experimental systems?

Contradictory findings regarding LUM function are not uncommon in the literature, often stemming from differences in experimental systems, antibodies used, or biological contexts. A methodical approach to resolving these contradictions includes:

• Systematic comparison of experimental conditions:

  • Document differences in cell lines, tissue sources, and model systems

  • Compare antibody clones, epitopes, and validation methods

  • Analyze differences in microenvironmental factors between studies

• Meta-analysis approaches:

  • Implement formal meta-analysis of published data when sufficient studies exist

  • Develop standardized effect size measurements for cross-study comparison

  • Assess publication bias through funnel plot analysis

• Collaborative validation studies:

  • Design multi-center studies using standardized reagents and protocols

  • Implement blinded sample exchange between laboratories

  • Develop consensus analysis pipelines for raw data processing

• Context-dependent function framework:

  • Test if LUM functions are tissue-specific or disease-state dependent

  • Evaluate temporal dynamics of LUM expression and function

  • Consider interactions with tissue-specific extracellular matrix components

• Advanced systems biology approaches:

  • Integrate transcriptomic, proteomic, and functional data across experimental systems

  • Implement computational modeling to predict context-dependent functions

  • Develop testable hypotheses to explain apparent contradictions

These approaches acknowledge the context-dependent nature of many biological processes and provide a framework for reconciling seemingly contradictory findings.

What approaches can distinguish between causative and correlative relationships in LUM expression studies?

Distinguishing causation from correlation represents one of the most significant challenges in LUM research. Methodological approaches to address this challenge include:

• Genetic manipulation experiments:

  • Implement CRISPR/Cas9-mediated knockout of LUM

  • Develop inducible expression systems for temporal control

  • Create point mutations affecting specific LUM functions

• Rescue experiment designs:

  • Test whether adding back wild-type LUM restores phenotypes

  • Develop domain-specific mutants to map functional regions

  • Implement structure-function studies based on protein engineering

• Temporal analysis strategies:

  • Establish time-course experiments to determine order of events

  • Use live-cell imaging with LUM antibodies to track dynamic changes

  • Implement pulse-chase approaches to study protein turnover

• Pathway perturbation approaches:

  • Use specific inhibitors to block downstream pathways

  • Implement epistasis analyses through multiple gene manipulations

  • Test whether LUM antibody neutralization affects specific pathways

• Translational validation strategies:

  • Correlate experimental findings with patient data

  • Develop prognostic models incorporating LUM and related factors

  • Validate causal relationships in multiple independent cohorts

These approaches move beyond correlation to establish mechanistic understanding of LUM function across biological contexts and disease states.