AVIL Antibody

What is AVIL and why is it significant in biomedical research?

AVIL (Advillin) is a member of the gelsolin/villin family of actin regulatory proteins with significant structural similarity to villin. It functions primarily in controlling actin filament assembly, cell migration, and cell adhesion, making it a critical player in fundamental cellular processes. Research has revealed that AVIL is frequently overexpressed in cancer cells, particularly in glioblastoma (GBM) and rhabdomyosarcoma (RMS), where it drives tumorigenesis through multiple mechanisms . AVIL binds to actin and may play important roles in the development of neuronal cells that form ganglia . Its significance lies in both understanding fundamental cellular processes and as a potential therapeutic target in oncology.

What experimental applications are validated for AVIL antibodies?

AVIL antibodies have been validated for multiple experimental applications with specific methodological considerations for each:

For optimal results, researchers should consider antigen retrieval methods like heat-induced epitope retrieval using TRIS-EDTA-boric acid buffer (pH 8.4) for IHC applications, particularly when working with formalin-fixed, paraffin-embedded (FFPE) specimens .

How do I properly store and handle AVIL antibodies to maintain reactivity?

AVIL antibodies require specific storage and handling protocols to maintain their reactivity and specificity:

• Long-term storage: Maintain at -20°C in small aliquots to prevent repeated freeze-thaw cycles, which can degrade antibody quality

• Short-term use: Store at 4°C for up to one month for frequent usage

• Reconstitution: For lyophilized antibodies, reconstitute in 100 μl of sterile distilled H₂O with 50% glycerol

• Working solution preparation: When diluting for experiments, use fresh, high-quality buffers

• Contamination prevention: Work with aseptic techniques to prevent microbial growth

Research indicates that antibody stability decreases significantly after 3-5 freeze-thaw cycles, so preparing single-use aliquots upon receipt is strongly recommended for maintaining consistent experimental results .

What are the recommended protocols for AVIL detection in glioblastoma samples?

For robust AVIL detection in glioblastoma samples, researchers should implement a multi-faceted approach:

• Immunohistochemistry protocol optimization:

  • Deparaffinize tissue sections using a validated protocol (e.g., EZ Prep solution)

  • Perform heat-induced antigen retrieval for 64 minutes using TRIS-EDTA-boric acid pH 8.4 buffer

  • Block endogenous peroxidases (e.g., with CM1 for 8 minutes)

  • Incubate with AVIL antibody at 1:100 dilution for 60 minutes at room temperature

  • Use anti-rabbit HQ HRP detection system and appropriate chromogen (e.g., DAB)

  • Counterstain with hematoxylin for visualization

• Scoring system for AVIL expression:
  Implement a semiquantitative analysis on a scale of 0-3:

  • 0 = 0% cells positive

  • 1 = >0% <10% cells positive

  • 2 = >10% <50% cells positive

  • 3 = >50% cells positive

• Complementary validation approaches:

  • Confirm protein expression with Western blot using recommended dilutions

  • Correlate with mRNA expression data if available

  • Consider co-staining with prognostic markers (Ki67, cleaved caspase-3)

These protocols have been successfully implemented in research demonstrating the clinical significance of AVIL in glioblastoma, where AVIL protein expression showed a strong inverse correlation with patient survival (R = −0.82, p = 0.0012) .

How can I optimize Western blot conditions for detecting AVIL protein?

Optimizing Western blot conditions for AVIL detection requires careful attention to several parameters:

• Sample preparation:

  • Extract proteins using RIPA or NP-40 based buffers with protease inhibitors

  • For brain tissue samples, implement macrodissection techniques to isolate tumor regions

  • Maintain cold chain throughout extraction

• Gel selection and separation:

  • Use 8-10% polyacrylamide gels for optimal separation of the approximately 92-111 kDa AVIL protein

  • Consider gradient gels (4-12%) for improved resolution

• Transfer conditions:

  • For large proteins like AVIL, implement longer transfer times or utilize semi-dry transfer systems

  • Verify transfer efficiency with reversible staining before blocking

• Antibody conditions:

  • Primary antibody: Use dilutions between 1:500-1:2000

  • Incubation: Overnight at 4°C for optimal binding

  • Secondary antibody: Anti-rabbit HRP conjugated at manufacturer-recommended dilutions

  • Include appropriate positive controls (e.g., GBM cell lines known to express AVIL)

• Detection method:

  • Use enhanced chemiluminescence with exposure optimization

  • For quantitative analysis, consider fluorescence-based Western detection systems

Researchers should expect to observe AVIL at approximately 92-111 kDa, though the observed molecular weight may vary slightly between tissue types and experimental conditions .

What controls should be included when validating AVIL antibody specificity?

Rigorous validation of AVIL antibody specificity requires comprehensive controls:

• Positive tissue/cell controls:

  • Glioblastoma cell lines (e.g., A172, U251) - known to express high levels of AVIL

  • Rhabdomyosarcoma tissue or cell lines - confirmed to overexpress AVIL

  • Sensory ganglia tissues - natural expression of advillin

• Negative tissue/cell controls:

  • Normal astrocyte cultures - express minimal AVIL

  • Non-neural tissues with limited AVIL expression

• Molecular validation controls:

  • AVIL knockdown/knockout cells using siRNA or CRISPR (siAVIL1 targeting 5′-GCTTCTGGCAAAGGATATT-3′ or siAVIL2 targeting 5′-GCATTCCTTGCTTGTTATA-3′)

  • AVIL overexpression constructs (e.g., AVIL cDNA clone from GeneCopoeia GC-OG11537)

  • Recombinant AVIL protein for antibody preabsorption tests

• Technical controls:

  • Secondary antibody-only controls to assess background

  • Isotype controls (rabbit IgG at equivalent concentrations)

  • Peptide competition assays using the specific immunogen peptide

Research demonstrates that effective AVIL antibody validation should show absence of signal after AVIL knockdown and increased signal with overexpression, confirming specificity. For example, studies have validated AVIL antibodies using knockdown approaches that showed complete absence of signal following efficient silencing .

How does AVIL expression correlate with clinical outcomes in glioblastoma patients?

AVIL expression demonstrates significant correlations with clinical outcomes in glioblastoma patients across multiple parameters:

• Survival correlation:

  • Strong inverse correlation between AVIL protein expression and patient survival (R = −0.82, p = 0.0012)

  • Kaplan-Meier analyses show poor prognosis associated with high AVIL protein expression (log-rank test p = 0.0005)

  • In REMBRANDT project data (343 glioma cases), elevated AVIL expression correlated with shorter survival (upregulated vs. intermediate, p = 1 × 10⁻⁵; upregulated vs. all other, p = 4 × 10⁻⁷, log-rank test)

• Prognostic stratification:

  • RNA expression analysis in TCGA data revealed:

    • High AVIL group (≥2-fold higher than average): median survival of 23.1 months

    • Low AVIL group: median survival of 75.1 months (p = 1 × 10⁻⁵, log-rank test)

  • Significant differences in disease-free survival between high and low AVIL expression groups (p < 0.01)

• Histopathologic correlation:

  • AVIL expression provides more significant prognostic stratification than traditional histopathologic classification and grading

  • Semiquantitative scoring of AVIL immunohistochemistry (0-3 scale) correlates with tumor aggressiveness

These findings suggest that AVIL expression assessment using validated antibodies may serve as a valuable prognostic biomarker in clinical neuro-oncology, potentially outperforming conventional histopathological approaches .

What role does AVIL play in tumor cell migration and invasion?

AVIL plays crucial roles in tumor cell migration and invasion through multiple mechanistic pathways:

• Cytoskeletal regulation:

  • As a member of the gelsolin/villin family, AVIL directly modulates actin dynamics

  • AVIL binds to filamentous actin through its conserved headpiece domain

  • Mutations in the headpiece domain (e.g., K808C and F819C) significantly reduce binding to actin and impair cell migration

• Experimental evidence of migration dependency:

  • Wound-healing assays showed dramatic reduction in cell movement when AVIL was silenced in GBM cell lines (A172 and U251)

  • Transwell invasion assays demonstrated significantly reduced invasiveness following AVIL knockdown

  • Live-cell imaging tracking individual cells confirmed reduced motility with AVIL silencing

• Metastatic potential:

  • AVIL overexpression increases migration rates in multiple cell types including astrocytes, U251, and U87 cells

  • The migration-promoting effects appear to be consistent across different cancer types, including rhabdomyosarcoma

• Molecular interactions:

  • AVIL potentially regulates FOXM1 stability, a transcription factor known to promote invasion and metastasis

  • Gene Set Enrichment Analysis (GSEA) following AVIL overexpression revealed enrichment in multiple oncogenic pathways that support invasion

These findings suggest that antibody-based detection of AVIL expression may help predict invasive potential of tumors, providing valuable prognostic information beyond simple proliferation markers .

How can AVIL antibodies be used to study oncogene addiction mechanisms?

AVIL antibodies serve as critical tools for investigating oncogene addiction mechanisms through multiple experimental approaches:

• Cell survival dependency studies:

  • AVIL antibodies can quantify expression levels before and after knockdown experiments

  • Research shows GBM cells die when AVIL is silenced, while normal astrocytes (low AVIL) remain unaffected

  • This differential effect demonstrates classical oncogene addiction, where cancer cells become dependent on AVIL overexpression

• Xenograft model analyses:

  • AVIL antibodies enable immunohistochemical assessment of tumor formation in animal models

  • Studies using U251 intracranial xenograft models showed that silencing AVIL prevented tumor formation

  • Control animals developed significant tumor volumes within 4 weeks, while shAVIL animals showed minimal or no tumor formation by MRI

• Transformation capacity assessment:

  • Antibodies help monitor AVIL levels during transformation experiments

  • AVIL overexpression induced focus formation in NIH3T3 cells at greater rates than established oncogenic factors (EGFR vIII mutant, shRNA targeting TP53, or shRNA targeting RB)

  • Astrocytes overexpressing AVIL formed colonies in soft agar assays and developed tumors when injected into nude mice, confirming transformation

• Pathway interaction studies:

  • AVIL antibodies facilitate co-immunoprecipitation experiments to identify interactions

  • Research identified that AVIL functionally interacts with actin through its headpiece domain

  • Mutations in this domain (K808C and F819C) disrupted these interactions and reduced oncogenic potential

These methodologies underscore how AVIL antibodies enable comprehensive investigation of oncogene addiction mechanisms, potentially guiding development of targeted therapies for cancers dependent on AVIL overexpression .

How do different AVIL antibodies compare in their epitope recognition and experimental performance?

Different AVIL antibodies demonstrate variable epitope recognition and performance characteristics that researchers should consider when selecting reagents:

Performance considerations:

• Epitope accessibility: Antibodies targeting different regions may perform differently depending on protein folding and complex formation

• Cross-reactivity: Antibodies against highly conserved domains may cross-react with related proteins in the gelsolin/villin family

• Application-specific performance: Some antibodies excel in certain applications but perform poorly in others

Researchers in the field have found that antibodies recognizing the C-terminal region (including the headpiece domain) are particularly valuable for functional studies, as this region mediates critical actin-binding interactions required for AVIL's oncogenic properties .

What are the key considerations when developing an immunohistochemical scoring system for AVIL in tumor samples?

Developing a robust immunohistochemical scoring system for AVIL in tumor samples requires attention to several critical factors:

• Standardized staining protocol:

  • Consistent antigen retrieval methods (e.g., TRIS-EDTA-boric acid pH 8.4 buffer for 64 minutes)

  • Antibody concentration optimization (typically 1:100 dilution)

  • Standardized incubation times (60 minutes at room temperature)

  • Consistent detection systems (anti-rabbit HQ HRP and chromogen)

• Scoring system design:

  • Semiquantitative analysis based on percentage of positive cells:

    • 0 = 0% cells positive

    • 1 = >0% <10% cells positive

    • 2 = >10% <50% cells positive

    • 3 = >50% cells positive

  • Consider both staining intensity and distribution

  • Evaluate subcellular localization patterns

• Quality control measures:

  • Include known positive and negative controls with each staining batch

  • Implement blinded scoring by multiple pathologists to ensure reproducibility

  • Calculate inter-observer concordance statistics

  • Document representative images for each score level

• Clinical correlation methodology:

  • Correlate scores with patient survival data using Kaplan-Meier analyses

  • Calculate hazard ratios through multivariate analyses

  • Determine optimal cutoff values using receiver operating characteristic curves

  • Assess prognostic value independent of established markers

Research has validated that AVIL immunohistochemical scoring following these principles provides significant prognostic information. For example, high AVIL protein expression determined through such scoring systems demonstrated significant correlation with poor prognosis (log-rank test p = 0.0005) .

How can AVIL mutation studies be integrated with antibody-based detection methods?

Integrating AVIL mutation studies with antibody-based detection requires sophisticated methodological approaches:

• Epitope-specific antibody selection:

  • Choose antibodies that recognize regions away from common mutation sites

  • Consider using multiple antibodies recognizing different domains

  • For known mutations, develop mutation-specific antibodies when feasible

• Functional domain analysis:

  • Target antibodies against critical functional domains like the headpiece region

  • Research has identified six key residues in the AVIL headpiece that affect actin binding

  • Mutations in K808C and F819C significantly reduce actin binding capacity and oncogenic potential

• Combined genomic and proteomic approaches:

  • Sequence AVIL gene from tumor samples to identify mutations

  • Correlate mutation status with protein expression patterns detected by antibodies

  • Perform immunoprecipitation followed by mass spectrometry to identify post-translational modifications

• Experimental validation protocols:

  • Generate expression vectors containing wild-type and mutant AVIL

  • Perform rescue experiments in AVIL-silenced cells

  • Compare antibody detection patterns between wild-type and mutant proteins

  • Assess functional outcomes (proliferation, migration) for correlation with antibody signals

Research demonstrates that mutant AVIL proteins (K808C and F819C) with reduced actin binding fail to promote cell proliferation and migration at rates comparable to wild-type AVIL, highlighting how mutation studies can be integrated with functional and antibody-based analyses .

What are common pitfalls in AVIL antibody-based experiments and how can they be addressed?

Researchers frequently encounter specific challenges when working with AVIL antibodies:

• Nonspecific binding issues:

  • Problem: Background staining in Western blots or IHC

  • Solution: Optimize blocking conditions (5% BSA often more effective than milk for phospho-proteins)

  • Validation: Include knockdown controls to confirm specificity

• Variable detection of isoforms:

  • Problem: Multiple bands or inconsistent molecular weight detection

  • Solution: Select antibodies raised against regions common to all known isoforms

  • Validation: Compare with recombinant protein standards of known molecular weight

• Fixation-sensitive epitopes:

  • Problem: Poor IHC staining despite positive Western blot results

  • Solution: Test multiple antigen retrieval methods (heat-induced epitope retrieval with TRIS-EDTA-boric acid pH 8.4 buffer recommended)

  • Optimization: Adjust fixation time for fresh samples or test different antibody clones

• Cross-reactivity with related proteins:

  • Problem: Signal in tissues known to lack AVIL expression

  • Solution: Validate antibody specificity with peptide competition assays

  • Alternative: Confirm results with orthogonal methods (qRT-PCR, mass spectrometry)

• Batch-to-batch variability in polyclonal antibodies:

  • Problem: Inconsistent results between antibody lots

  • Solution: Purchase larger quantities of a single lot for long-term studies

  • Recommendation: Validate each new lot against previous standards and controls

Research demonstrates the importance of thorough validation, as exemplified in studies where AVIL antibody specificity was confirmed through multiple approaches, including siRNA knockdown experiments showing complete absence of signal following efficient silencing .

How should researchers interpret discrepancies between AVIL mRNA and protein expression data?

Interpreting discrepancies between AVIL mRNA and protein expression requires methodological rigor and consideration of multiple biological factors:

These considerations are essential for accurate interpretation, as demonstrated in research where AVIL protein expression proved more clinically relevant than mRNA expression for predicting patient outcomes in glioblastoma .

What is the optimal workflow for validating a new AVIL antibody in cancer research applications?

A comprehensive workflow for validating new AVIL antibodies in cancer research should follow these sequential steps:

• Initial characterization:

  • Verify immunogen sequence conservation across species of interest

  • Check for potential cross-reactivity with related proteins in silico

  • Determine optimal antibody concentration through titration experiments

  • Assess performance across applications (Western blot, IHC, IF, IP) using standard protocols

• Specificity validation:

  • Perform Western blot on cell lines with known AVIL expression (GBM cells as positive controls, normal astrocytes as negative controls)

  • Conduct knockdown experiments using established siRNAs (siAVIL1 targeting 5′-GCTTCTGGCAAAGGATATT-3′ or siAVIL2 targeting 5′-GCATTCCTTGCTTGTTATA-3′)

  • Compare with existing validated antibodies if available

  • Perform peptide competition assays to confirm epitope specificity

• Application-specific optimization:

  • For IHC: Test multiple antigen retrieval methods and fixation protocols

  • For IF: Optimize fixation and permeabilization conditions

  • For IP: Determine optimal buffer conditions and bead types

  • Establish semiquantitative scoring systems for IHC applications

• Functional validation:

  • Correlate antibody signal with known biological functions of AVIL

  • Test ability to detect changes in expression following experimental manipulation

  • Verify correlation with clinical parameters in patient samples

  • Assess reproducibility across multiple experiments and users

This rigorous validation workflow ensures reliable antibody performance in challenging research applications and has been successfully employed in studies investigating AVIL's role in glioblastoma and rhabdomyosarcoma tumorigenesis .

How might AVIL antibodies be utilized in developing targeted cancer therapies?

AVIL antibodies offer significant potential in the development of targeted cancer therapies through multiple research pathways:

• Target validation studies:

  • AVIL antibodies can quantify expression across tumor types to identify high-expressing cancers

  • Immunohistochemical screening of patient-derived xenografts can prioritize cancer types for therapeutic development

  • AVIL dependency studies show cancer cells are "addicted" to AVIL overexpression, making it an ideal therapeutic target

• Therapeutic antibody development:

  • Investigate intracellular delivery mechanisms for AVIL-targeting antibodies

  • Explore antibody-drug conjugate approaches targeting AVIL-expressing cells

  • Develop conformation-specific antibodies that disrupt AVIL-actin interactions

• Functional domain targeting:

  • Identify critical epitopes in the headpiece domain that mediate actin binding

  • Design therapeutic agents that disrupt specific protein-protein interactions

  • Research shows mutations in the AVIL headpiece (K808C and F819C) significantly reduce oncogenic potential

• Biomarker applications:

  • Implement AVIL antibody-based companion diagnostics to identify patients likely to respond to AVIL-targeted therapies

  • Develop standardized immunohistochemical protocols for patient stratification

  • Monitor treatment response through serial assessment of AVIL expression

These approaches are supported by research demonstrating that silencing AVIL induced GBM cell death in vitro and prevented/reduced GBM xenograft formation in animal models, while normal astrocytes remained unaffected—suggesting a high therapeutic index for AVIL-targeted therapies .

What are emerging techniques for studying the interaction between AVIL and its binding partners?

Cutting-edge techniques for investigating AVIL-partner interactions include:

• Advanced co-immunoprecipitation approaches:

  • Proximity-dependent biotin identification (BioID) to identify proteins in close proximity to AVIL

  • AVIL antibody-based co-immunoprecipitation followed by mass spectrometry

  • Research has identified actin as a key binding partner through co-immunoprecipitation with Myc-tagged AVIL

• Live-cell interaction visualization:

  • Fluorescence resonance energy transfer (FRET) between AVIL and potential partners

  • Bimolecular fluorescence complementation (BiFC) to visualize protein interactions in situ

  • AVIL-GFP fusion proteins have been used to study subcellular localization patterns

• Structural biology approaches:

  • Hydrogen-deuterium exchange mass spectrometry to map interaction interfaces

  • Cryo-electron microscopy of AVIL-partner complexes

  • Computational modeling based on the known structural models of villin and advillin headpiece domains

• Functional genomics integration:

  • CRISPR-Cas9 screening to identify synthetic lethal interactions with AVIL

  • Transcriptome analysis following AVIL manipulation to identify regulatory networks

  • Gene Set Enrichment Analysis (GSEA) revealed enrichment of major oncogenic pathways following AVIL overexpression

These methodologies offer deeper insights into AVIL's molecular functions, as demonstrated in research where AVIL was shown to potentially regulate FOXM1 stability, linking it to broader oncogenic signaling networks .

How can researchers contribute to standardizing AVIL detection methods across laboratories?

Standardizing AVIL detection methods requires collaborative approaches to establish consensus protocols:

• Antibody standardization initiatives:

  • Establish reference standards for commercially available AVIL antibodies

  • Conduct multi-laboratory validation studies to assess reproducibility

  • Create shared repositories of validated protocols with detailed methodological parameters

• Quantitative assessment frameworks:

  • Develop digital pathology approaches for objective AVIL quantification

  • Establish standardized immunohistochemical scoring systems :

    • 0 = 0% cells positive

    • 1 = >0% <10% cells positive

    • 2 = >10% <50% cells positive

    • 3 = >50% cells positive

  • Implement automated image analysis algorithms for consistent evaluation

• Quality control program implementation:

  • Create proficiency testing programs for AVIL detection

  • Develop reference materials with known AVIL expression levels

  • Establish minimum validation requirements for publication-quality data

• Harmonized reporting standards:

  • Adopt standardized nomenclature for AVIL detection methods

  • Implement detailed reporting of antibody information (source, catalog number, lot, dilution)

  • Report all validation measures undertaken for novel applications