ACTR3 Antibody

What is ACTR3 and why is it important in cancer research?

ACTR3 (actin-related protein 3) is a vital component of the Arp2/3 complex that functions as an actin-regulatory protein . This complex plays a crucial role in actin polymerization, which drives cell motility and affects cellular morphology. In cancer research, ACTR3 has gained importance due to its upregulation in multiple cancer types, including pancreatic ductal adenocarcinoma (PDAC), gastric cancer, hepatocellular carcinoma (HCC), squamous cell carcinoma, and colorectal cancer .

The significance of ACTR3 in cancer research stems from its role in promoting tumor development, particularly through enhanced cell migration and invasion capabilities . Studies have demonstrated that ACTR3 expression levels correlate with disease-free survival, suggesting its potential as a prognostic biomarker . Additionally, ACTR3's involvement in epithelial-mesenchymal transition (EMT), a critical process in cancer metastasis, makes it a valuable target for understanding cancer progression mechanisms .

What detection methods are most effective for ACTR3 expression analysis?

Several complementary detection methods have proven effective for ACTR3 expression analysis in research settings:

Western Blotting: This remains the gold standard for ACTR3 protein detection. Studies typically use antibody dilutions of 1:2,000 for ACTR3 primary antibodies . For optimal results, proteins should be extracted with radioimmunoprecipitation assay (RIPA) lysis buffer and subjected to 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis before transfer to polyvinylidene difluoride membranes .

mRNA Expression Analysis: High-throughput RNA sequencing and microarray analysis have successfully identified differential ACTR3 expression in cancer tissues. This approach has revealed significant upregulation (as high as 7-fold) of ACTR3 in PDAC tissues compared to non-cancerous pancreatic tissues .

Bioinformatic Analysis: Databases such as GEPIA2 provide valuable resources for analyzing ACTR3 mRNA levels across large patient cohorts. This approach has been used to validate ACTR3 upregulation in 179 PDAC tissues compared to 171 adjacent non-cancerous tissues .

For comprehensive analysis, combining protein-level detection (Western blotting) with mRNA expression analysis yields the most reliable results for ACTR3 expression profiling.

How should researchers design knockdown experiments for ACTR3 functional studies?

Designing effective ACTR3 knockdown experiments requires careful consideration of several methodological aspects:

siRNA Selection and Validation: Small interfering RNAs (siRNAs) targeting ACTR3 have proven effective for transient knockdown . It is recommended to test multiple siRNA sequences individually and as pooled siRNAs to identify those with highest knockdown efficiency. Western blotting should be used to validate knockdown at the protein level .

Transfection Protocol: Lipofectamine 3000 (or similar reagents) has been successfully employed for transient transfection of ACTR3 siRNAs into cancer cell lines . Researchers should optimize transfection conditions for each cell line to maximize knockdown efficiency while minimizing cytotoxicity.

Appropriate Controls: Including negative control (NC) siRNAs with scrambled sequences is essential for comparative analysis . This controls for non-specific effects of the transfection procedure.

Functional Assays: Following ACTR3 knockdown, researchers should implement multiple functional assays to comprehensively assess phenotypic changes:

• Transwell migration and invasion assays to evaluate metastatic potential

• Western blotting for EMT markers (E-cadherin, N-cadherin, vimentin, Snail)

• F-actin distribution analysis to assess cytoskeletal changes

The pooled siRNA approach often yields the highest knockdown efficiency and should be considered when robust suppression is required .

What are the optimal antibody conditions for ACTR3 detection in Western blotting?

For optimal ACTR3 detection in Western blotting, researchers should consider the following technical parameters:

Antibody Dilutions and Incubation:

• Primary ACTR3 antibody: 1:2,000 dilution has been validated in pancreatic cancer research

• Incubation time: Overnight at 4°C after blocking with 5% non-fat milk for 2 hours at room temperature

• Secondary antibody: Horseradish peroxidase-conjugated antibodies at 1:5,000 dilution with 2-hour incubation at room temperature

Protein Extraction and Loading:

• RIPA lysis buffer is recommended for protein extraction

• 10% SDS-PAGE gels provide appropriate separation for ACTR3 protein (~47 kDa)

• PVDF membranes are preferred for protein transfer

Controls and Normalization:

• GAPDH (1:20,000 dilution) serves as an effective loading control

• When studying EMT in relation to ACTR3, include antibodies for EMT markers: vimentin (1:1,000), E-cadherin (1:1,000), N-cadherin (1:1,000), and Snail (1:1,000)

Signal Development and Quantification:

• Enhanced chemiluminescence (ECL) detection systems provide clear visualization

• For quantitative analysis, normalization to GAPDH expression is essential for accurate comparison between samples

These optimized conditions enable consistent and reliable detection of ACTR3 protein levels in experimental samples.

How can researchers effectively correlate ACTR3 expression with clinical outcomes?

Researchers can establish meaningful correlations between ACTR3 expression and clinical outcomes through several methodological approaches:

Expression Analysis Methods:

• Utilize bioinformatics platforms such as GEPIA2 for large-scale data analysis

• Validate findings using multiple independent cohorts when possible

• Combine mRNA expression data with protein-level analysis when tissue samples are available

Statistical Approaches:

• Kaplan-Meier survival analysis with log-rank tests to evaluate prognostic significance

• Cox proportional hazards regression to identify independent prognostic factors

• Establish appropriate cutoff values to define "high" versus "low" ACTR3 expression groups

Correlation with Pathological Parameters:

• Analyze relationships between ACTR3 expression and tumor grade, stage, and metastatic status

• Investigate associations with other established prognostic markers

What methodologies should be used to study ACTR3's role in EMT?

To effectively investigate ACTR3's role in epithelial-mesenchymal transition (EMT), researchers should implement the following methodological approaches:

Protein Expression Analysis:

• Western blotting to assess canonical EMT markers following ACTR3 manipulation:

  • Epithelial markers: E-cadherin (increased after ACTR3 knockdown)

  • Mesenchymal markers: N-cadherin and vimentin (decreased after ACTR3 knockdown)

  • EMT transcription factors: Snail (decreased after ACTR3 knockdown)

Cytoskeletal Structure Assessment:

• Immunofluorescence staining for F-actin distribution to visualize cytoskeletal reorganization

• Analysis of cell morphology changes following ACTR3 modulation

Functional EMT Assays:

• Transwell migration and invasion assays to quantify metastatic potential

• Wound healing assays to assess collective cell migration

• 3D culture systems to evaluate morphological changes in a more physiologically relevant context

Molecular Mechanism Investigation:

• Co-immunoprecipitation to identify ACTR3 interaction partners

• Gene expression profiling to identify downstream effectors

• Pathway analysis to place ACTR3 within the broader EMT regulatory network

Research has demonstrated that ACTR3 knockdown significantly inhibits the invasive and migratory capacity of cancer cells while altering the expression of EMT markers, confirming its role in promoting metastasis through EMT induction .

How can researchers investigate ACTR3's relationship with tumor-infiltrating immune cells?

Investigating the relationship between ACTR3 and tumor-infiltrating immune cells requires specialized methodological approaches:

Correlation Analysis Using Bioinformatic Platforms:

• Utilize the TIMER 2.0 platform to analyze associations between ACTR3 expression and immune cell infiltration

• Assess correlations with various immune cell populations, including CD4+ T cells, CD8+ T cells, B cells, neutrophils, and macrophages

• Consider tumor purity as a confounding factor in correlation analyses

Co-expression Analysis of Immune Cell Markers:

• Use databases like GEPIA to analyze co-expression relationships between ACTR3 and specific immune cell markers

• Focus on markers for distinct immune cell populations:

  • T cell subsets: STAT1 (Th1), STAT6 (Th2), STAT3 (Th17), CCR8 (Treg)

  • Myeloid cells: CD11b (neutrophils), PTGS2 and IRF5 (M1 macrophages), VSIG4 and MS4A4A (M2 macrophages)

Experimental Validation:

• Immunohistochemistry on serial sections to visualize ACTR3 expression and immune cell infiltration in the same tumor regions

• Flow cytometry to quantify immune cell populations in relation to ACTR3 expression levels

• In vitro co-culture systems to assess functional interactions between ACTR3-expressing tumor cells and immune cells

Research has revealed that ACTR3 expression positively correlates with infiltration of CD4+ T cells, CD8+ T cells, B cells, neutrophils, and macrophages in hepatocellular carcinoma , suggesting its potential role in modulating the tumor immune microenvironment.

What advanced techniques can be used to study ACTR3's influence on actin polymerization in cancer cells?

Studying ACTR3's influence on actin polymerization in cancer cells requires sophisticated techniques that capture both molecular dynamics and structural changes:

Live Cell Imaging Approaches:

• Fluorescent protein tagging of ACTR3 and actin to visualize their dynamic interactions

• Time-lapse microscopy to track actin polymerization rates and patterns following ACTR3 manipulation

• Förster resonance energy transfer (FRET) to detect direct molecular interactions between ACTR3 and actin monomers

Super-resolution Microscopy:

• Structured illumination microscopy (SIM) or stimulated emission depletion (STED) microscopy to resolve fine actin filament structures

• Single-molecule localization microscopy to map ACTR3 distribution along actin filaments

Biochemical Assays for Actin Dynamics:

• Pyrene-actin polymerization assays to quantify polymerization rates in the presence or absence of ACTR3

• Actin branching assays to assess the functional activity of the Arp2/3 complex

• Actin crosslinking and co-sedimentation assays to evaluate ACTR3's effect on filament stability

Molecular Perturbation Approaches:

• CRISPR-Cas9 gene editing to create ACTR3 knockout or knockin cell lines

• Domain-specific mutations to identify critical regions involved in actin binding and regulation

• Small molecule inhibitors of the Arp2/3 complex to pharmacologically modulate ACTR3 function

Research has shown that knockdown of ACTR3 causes redistribution of F-actin and morphological changes in pancreatic cancer cells , suggesting its direct influence on cytoskeletal organization during cancer progression.

How can gene set enrichment analysis (GSEA) be applied to understand ACTR3's role in cancer pathways?

Gene set enrichment analysis (GSEA) provides powerful insights into ACTR3's involvement in cancer-related pathways when applied with the following methodological considerations:

Dataset Selection and Preparation:

• Use RNA-sequencing data from cell lines with ACTR3 knockdown/overexpression compared to controls

• Alternatively, stratify patient samples into high vs. low ACTR3 expression groups based on RNA-seq or microarray data

• Apply appropriate normalization techniques to minimize technical variation

Pathway Database Selection:

• Utilize established databases such as KEGG, Reactome, or MSigDB for comprehensive pathway coverage

• Consider cancer-specific gene sets focusing on EMT, metastasis, and actin cytoskeleton regulation

• Include immune-related pathways given ACTR3's correlation with immune cell infiltration

Analysis Parameters:

• Set appropriate false discovery rate (FDR) thresholds (typically <0.05 or <0.25 for exploratory analysis)

• Calculate normalized enrichment scores (NES) to quantify pathway enrichment

• Generate enrichment plots for visualization of significantly altered pathways

Integrative Analysis:

• Correlate enriched pathways with phenotypic changes observed in functional assays

• Identify key genes driving pathway enrichment as potential mechanistic links

• Validate selected genes/pathways using targeted approaches (qPCR, Western blotting)

GSEA has been successfully applied to demonstrate that ACTR3 is involved in multiple cancer-related pathways promoting the development of hepatocellular carcinoma . This approach can reveal both expected pathways (cytoskeletal organization) and unexpected connections to cellular processes such as metabolism or immune regulation.

How should researchers address discrepancies between mRNA and protein expression data for ACTR3?

When faced with discrepancies between ACTR3 mRNA and protein expression data, researchers should implement the following methodological approaches:

Technical Validation:

• Verify antibody specificity using positive and negative controls

• Confirm primer specificity for qPCR through sequencing or melt curve analysis

• Repeat experiments with alternative detection methods for both mRNA (RNA-seq vs. qPCR) and protein (Western blot vs. immunohistochemistry)

Biological Explanations:

• Consider post-transcriptional regulation mechanisms:

  • microRNA targeting ACTR3 mRNA

  • RNA-binding proteins affecting mRNA stability

  • Alternative splicing yielding isoforms not detected by standard primers

• Evaluate post-translational modifications and protein degradation:

  • Proteasomal degradation rates

  • Protein half-life under different cellular conditions

  • Epitope masking affecting antibody recognition

Temporal Considerations:

• Analyze time-course data to identify potential delays between mRNA upregulation and protein accumulation

• Pulse-chase experiments to determine ACTR3 protein turnover rates

Spatial Analysis:

• Assess subcellular localization which might affect extraction efficiency

• Consider tissue heterogeneity and cell type-specific expression patterns

When interpreting such discrepancies, remember that while mRNA levels of ACTR3 significantly predict disease-free survival in PDAC patients , protein-level confirmation provides stronger mechanistic evidence for ACTR3's functional role in cancer progression.

What are the common pitfalls in ACTR3 knockdown experiments and how can they be addressed?

Researchers should be aware of several common pitfalls in ACTR3 knockdown experiments and implement these strategies to address them:

Incomplete Knockdown:

• Pitfall: Partial ACTR3 suppression may yield ambiguous phenotypes

• Solution: Test multiple siRNA sequences and use pooled siRNAs for maximum knockdown efficiency

• Validation: Quantify knockdown at both mRNA and protein levels to ensure >70% reduction

Off-target Effects:

• Pitfall: siRNAs may affect expression of genes other than ACTR3

• Solution: Use multiple independent siRNA sequences targeting different regions of ACTR3 mRNA

• Validation: Perform rescue experiments by expressing siRNA-resistant ACTR3 constructs

Transient Nature of siRNA Knockdown:

• Pitfall: Short-term knockdown may be insufficient for observing certain phenotypes

• Solution: For long-term studies, consider stable knockdown using shRNA or CRISPR-Cas9

• Monitoring: Track ACTR3 expression levels throughout the experimental timeframe

Cell Type-Specific Effects:

• Pitfall: Results from one cell line may not generalize across different cancer types

• Solution: Validate findings in multiple cell lines representing diverse cancer subtypes

• Comparison: Include both PANC-1 and MIA-PaCa-2 cells as has been done successfully in previous studies

Compensatory Mechanisms:

• Pitfall: Cells may upregulate related proteins to compensate for ACTR3 loss

• Solution: Monitor expression of other Arp2/3 complex components after ACTR3 knockdown

• Extension: Consider simultaneous knockdown of multiple components when investigating complex functions

Addressing these pitfalls is crucial as ACTR3 knockdown studies have provided key insights into its role in cancer cell migration, invasion, and EMT regulation .

How can researchers optimize immunohistochemical detection of ACTR3 in tissue samples?

Optimizing immunohistochemical (IHC) detection of ACTR3 in tissue samples requires attention to several critical methodological aspects:

Tissue Preparation and Processing:

• Fixation: Formalin fixation for 24-48 hours followed by paraffin embedding is standard

• Section thickness: 4-5 μm sections provide optimal balance between structural integrity and antibody penetration

• Antigen retrieval: Heat-induced epitope retrieval using citrate buffer (pH 6.0) or EDTA buffer (pH 9.0) should be tested to determine optimal conditions

Antibody Selection and Validation:

• Verify antibody specificity using Western blotting prior to IHC application

• Test multiple commercially available antibodies to identify those with highest specificity and sensitivity

• Use positive control tissues with known ACTR3 expression (e.g., cancer tissues with confirmed high expression)

Staining Protocol Optimization:

• Antibody dilution: Perform titration experiments (typically 1:100 to 1:500 range)

• Incubation conditions: Test both overnight at 4°C and 1-2 hours at room temperature

• Detection system: HRP-polymer detection systems generally provide better signal-to-noise ratio than avidin-biotin methods

Quantification Approaches:

• Implement standardized scoring systems (H-score or Allred score)

• Consider digital image analysis for quantitative assessment of staining intensity and distribution

• Evaluate both cytoplasmic and membrane-associated ACTR3 staining

Multi-marker Analysis:

• Perform multiplex IHC to simultaneously detect ACTR3 and EMT markers (E-cadherin, vimentin)

• Use serial sections to correlate ACTR3 expression with immune cell infiltration markers

These optimized protocols enable reliable detection of ACTR3 in clinical samples, facilitating investigation of its prognostic significance across different cancer types .

What are promising approaches for targeting ACTR3 therapeutically in cancer?

Several promising therapeutic approaches are emerging for targeting ACTR3 in cancer treatment strategies:

RNA Interference-Based Therapeutics:

• siRNA delivery using lipid nanoparticles has shown efficacy in preclinical models

• Development of chemically modified siRNAs with improved stability and tissue penetration

• Consideration of tumor-specific delivery systems to minimize off-target effects in normal tissues

Small Molecule Inhibitors:

• Design of selective ACTR3 inhibitors that disrupt its interaction with other Arp2/3 complex components

• Screening of compound libraries to identify molecules that interfere with ACTR3's actin-regulatory function

• Structure-based drug design targeting critical functional domains of ACTR3

Combination Therapy Approaches:

• Pairing ACTR3 inhibition with conventional chemotherapeutics to enhance efficacy

• Combining with EMT inhibitors to synergistically block metastatic progression

• Integration with immunotherapies given ACTR3's correlation with immune cell infiltration

Pathway-Based Interventions:

• Targeting upstream regulators of ACTR3 expression

• Inhibiting downstream effectors in the ACTR3 signaling cascade

• Modulating EMT-related pathways affected by ACTR3 activity

Research has demonstrated that ACTR3 knockdown significantly inhibits cancer cell migration and invasion while affecting EMT marker expression , suggesting that therapeutic targeting could potentially reduce metastatic spread. As ACTR3 has been identified as a potential therapeutic target for PDAC metastasis , these approaches warrant further investigation in preclinical and eventually clinical settings.

How might single-cell analysis advance our understanding of ACTR3's role in tumor heterogeneity?

Single-cell analysis offers transformative opportunities for understanding ACTR3's role in tumor heterogeneity through several methodological approaches:

Single-Cell RNA Sequencing (scRNA-seq):

• Reveal cell-specific expression patterns of ACTR3 within heterogeneous tumor populations

• Identify rare cell subpopulations with distinctive ACTR3 expression profiles

• Map ACTR3 co-expression networks at single-cell resolution to uncover cell state-specific regulatory mechanisms

Spatial Transcriptomics:

• Preserve spatial context while analyzing ACTR3 expression patterns

• Correlate ACTR3 expression with specific tumor microenvironmental niches

• Identify spatial relationships between ACTR3-expressing tumor cells and infiltrating immune cells

CyTOF and Multiparameter Flow Cytometry:

• Simultaneously measure ACTR3 protein levels alongside other cancer-related proteins

• Characterize cell populations based on ACTR3 expression and functional markers

• Track changes in ACTR3-expressing subpopulations during disease progression or treatment

Single-Cell ATAC-Seq:

• Identify cell-specific chromatin accessibility patterns that regulate ACTR3 expression

• Map enhancer elements controlling ACTR3 in different cellular contexts

• Link epigenetic landscape to ACTR3 expression heterogeneity

The integration of these single-cell approaches could reveal whether specific tumor cell subpopulations with high ACTR3 expression drive metastatic behavior, potentially explaining why ACTR3 expression correlates with poor prognosis and shorter disease-free survival in cancer patients . This understanding could ultimately lead to more precise targeting strategies that address tumor heterogeneity.

What in vivo models would be most appropriate for studying ACTR3's role in metastasis?

Selecting appropriate in vivo models is crucial for advancing our understanding of ACTR3's role in metastasis, with several methodological considerations:

Orthotopic Xenograft Models:

• Implantation of ACTR3-manipulated cancer cells into natural organ sites (e.g., pancreas for PDAC studies)

• Advantages: Provides physiologically relevant microenvironment; allows assessment of local invasion

• Analysis: Monitor primary tumor growth, local invasion, and distant metastasis formation using imaging techniques

Experimental Metastasis Models:

• Tail vein or intrasplenic injection of cancer cells with modified ACTR3 expression

• Advantages: Focuses specifically on later stages of metastatic cascade; allows quantification of metastatic burden

• Analysis: Evaluate lung/liver colonization efficiency through histological examination and molecular detection methods

Genetically Engineered Mouse Models (GEMMs):

• Development of conditional ACTR3 knockout or overexpression in tissue-specific cancer models

• Advantages: Allows study of ACTR3's role in spontaneous tumor development and progression

• Analysis: Monitor tumor initiation, growth kinetics, EMT markers, and metastatic spread

Patient-Derived Xenograft (PDX) Models:

• Implantation of patient tumor fragments with varying ACTR3 expression levels

• Advantages: Maintains tumor heterogeneity and architecture; better reflects human disease

• Analysis: Correlate ACTR3 expression with metastatic potential and treatment response

Zebrafish Models:

• Injection of fluorescently labeled cancer cells with ACTR3 modification into zebrafish embryos

• Advantages: Allows real-time visualization of cell migration and invasion; high-throughput screening potential

• Analysis: Track cancer cell dissemination through transparent zebrafish tissues

Current research on ACTR3 has been limited to in vitro studies , with authors acknowledging the need for animal models to verify findings. As noted: "The role of ACTR3 should be verified in animal models in future studies" . These in vivo approaches would address this research gap and provide more comprehensive insights into ACTR3's role in metastasis.

How can multi-omics approaches enhance our understanding of ACTR3's regulatory networks?

Multi-omics approaches offer powerful strategies for comprehensively mapping ACTR3's regulatory networks in cancer through integrated methodological frameworks:

Integrative Genomics:

• Combine DNA sequencing, RNA-seq, and ChIP-seq to identify genetic alterations affecting ACTR3 expression

• Correlate copy number variations or mutations with ACTR3 expression levels

• Map transcription factor binding sites in ACTR3 promoter regions across cancer types

Proteomics and Interactomics:

• Apply mass spectrometry-based proteomics to identify ACTR3 interaction partners

• Use proximity labeling techniques (BioID, APEX) to capture transient interactions in living cells

• Construct protein-protein interaction networks centered on ACTR3 and the Arp2/3 complex

Phosphoproteomics:

• Identify phosphorylation sites on ACTR3 that regulate its function

• Map kinase-substrate networks affecting ACTR3 activity

• Correlate phosphorylation patterns with cellular phenotypes related to migration and invasion

Metabolomics Integration:

• Investigate metabolic changes associated with ACTR3 expression alterations

• Connect ACTR3-mediated cytoskeletal changes with cellular energy metabolism

• Identify metabolic vulnerabilities in ACTR3-overexpressing cancer cells

Systems Biology Modeling:

• Develop computational models incorporating multi-omics data to predict ACTR3 function

• Use network analysis to identify critical nodes in ACTR3-regulated pathways

• Simulate perturbations to identify potential therapeutic targets