ARHGAP11A Antibody

What are the key specifications of available ARHGAP11A antibodies?

Current commercial ARHGAP11A antibodies are predominantly rabbit polyclonal antibodies with diverse epitope targets. Here is a comparison of available antibodies and their specifications:

What applications are most validated for ARHGAP11A antibodies?

ARHGAP11A antibodies have been validated for multiple research applications with varying degrees of optimization:

• Immunohistochemistry (IHC): Extensively validated for cancer tissue analysis, particularly in LUAD studies. Recommended dilutions of 1:200-1:500 have shown optimal results for paraffin-embedded specimens .

• Western Blotting (WB): Successfully employed for protein expression analysis with recommended concentrations of 0.04-0.4 μg/mL .

• Immunofluorescence (IF): Validated for cellular localization studies, with optimal working concentration of 4 μg/ml in PFA-fixed, Triton X-100 permeabilized cells .

• Immunoprecipitation (IP): Some antibodies have been validated for protein interaction studies .

• ELISA: Selected antibodies have been validated for quantitative analysis .

For each application, method optimization is essential, with particular attention to antibody concentration, incubation time, and sample preparation protocols.

How should ARHGAP11A expression analysis be designed for cancer research studies?

When designing experiments to analyze ARHGAP11A expression in cancer:

• Sample selection: Include matched tumor and adjacent normal tissues whenever possible. In LUAD studies, this approach revealed significant upregulation of ARHGAP11A in tumor tissues (mean score: 7.717 vs. 2.714, P<0.0001) .

• Multiple detection methods: Employ complementary techniques to confirm expression patterns:

  • mRNA analysis (RT-PCR or RNA-seq)

  • Protein detection (IHC, Western blot)

  • Database validation (TCGA, Oncomine)

• Clinicopathological correlation: Analyze ARHGAP11A expression in relation to clinical parameters. Research has shown that high ARHGAP11A expression correlates with advanced pathological stage, T stage, and lymph node metastasis in LUAD .

• Scoring system standardization: For IHC studies, implement standardized scoring systems. Previous studies have successfully employed semi-quantitative scoring that evaluates both staining intensity and percentage of positive cells .

• Survival analysis: Perform Kaplan-Meier analysis and Cox regression to determine prognostic significance. Multivariate Cox analysis has identified high ARHGAP11A expression as an independent prognostic factor for poor outcomes in LUAD (HR=1.385; P<0.001) .

What controls and validation steps are critical when using ARHGAP11A antibodies?

Rigorous controls and validation are essential for reliable ARHGAP11A antibody-based research:

• Antibody specificity validation:

  • Western blot analysis to confirm single band at expected molecular weight (114 kDa)

  • Peptide competition assays to confirm binding specificity

  • siRNA knockdown or knockout validation

  • Use of multiple antibodies targeting different epitopes

• Positive and negative tissue controls:

  • Positive controls: Brain and testes tissues show high ARHGAP11A expression

  • Negative controls: Include primary antibody omission controls

  • Isotype controls to assess non-specific binding

• Cross-reactivity assessment:

  • Test antibody performance across intended species (consider predicted reactivity: Human: 100%, Mouse: 86%, Rat: 93%, Cow: 93%, Dog: 77%, Guinea Pig: 85%, Horse: 85%, Rabbit: 92%)

• Reproducibility testing:

  • Technical replicates to ensure consistent staining patterns

  • Biological replicates to account for heterogeneity

• Optimization protocols:

  • Titration experiments to determine optimal antibody concentration

  • Antigen retrieval method optimization for IHC applications

How does ARHGAP11A contribute to cancer progression mechanisms?

ARHGAP11A influences multiple cellular mechanisms promoting cancer progression:

• Cell cycle regulation: GSEA analysis has identified significant enrichment of cell cycle pathways in ARHGAP11A high-expression phenotypes (NES=2.54, P=0.000, FDR q=0.000) . ARHGAP11A knockdown has been shown to result in G1-phase cell-cycle arrest in basal-like breast cancer cells .

• p53 signaling modulation: ARHGAP11A interacts with the p53 pathway (NES=2.20, P=0.000, FDR q=0.000) . In human glioma cells, ARHGAP11A physically binds to p53 and promotes its function to induce cell-cycle arrest and apoptosis .

• Rho A/ROCK pathway activation: ARHGAP11A regulates the biological activity of Rho A through the ArhGAP11A/Rho A/ROCK pathway. In vitro experiments showed that ROCK inhibitor could inhibit Rho-mediated signal pathways and cause cell morphology changes similar to ARHGAP11A overexpression .

• DNA replication influence: GSEA identified significant enrichment of DNA replication pathways in the ARHGAP11A high-expression phenotype (NES=2.12, P=0.000, FDR q=0.001) .

• WNT signaling modulation: The WNT signaling pathway is enriched in the ARHGAP11A high-expression phenotype (NES=1.49, P=0.041, FDR q=0.147) .

What is known about ARHGAP11A's role in hypoxia-immune interactions in tumors?

ARHGAP11A functions as a critical mediator between hypoxia response and immune regulation in tumor microenvironments:

• Hypoxia-immune core gene function: ARHGAP11A is closely related to both immune processes and hypoxia response in lung adenocarcinoma, promoting tumor progression through this dual functionality .

• Immune cell infiltration correlation: High ARHGAP11A levels positively correlate with increased immune cell infiltration in tumor tissues based on ESTIMATE algorithm analysis . Specifically:

  • Weak positive correlation with CD8+ T cells and CD4+ T cells (R=0.267, 0.283 respectively, p<0.001)

  • Moderate positive correlation with B cells, macrophages, neutrophils, and dendritic cells (R=0.377, 0.394, 0.490, 0.479 respectively, all p<0.001)

• Hypoxia adaptation mechanisms: Tumor cells utilize ARHGAP11A to adapt to hypoxic conditions by initiating adaptive behaviors including angiogenesis, proliferation, and invasion .

• Immune escape facilitation: ARHGAP11A has been found to effectively mediate immune escape in lung adenocarcinoma, creating a microenvironment conducive to cancer growth despite immune cell presence .

• Multifaceted TME regulation: The regulation of the tumor microenvironment by ARHGAP11A involves complex interactions between immunity and hypoxia responses, presenting potential targets for therapeutic intervention .

What signaling pathways are significantly associated with ARHGAP11A in cancer?

Gene Set Enrichment Analysis (GSEA) has identified multiple signaling pathways significantly associated with ARHGAP11A expression in cancer, particularly in LUAD:

These pathway enrichments suggest that ARHGAP11A impacts multiple cancer-related processes, with particularly strong associations to cell cycle regulation, p53 signaling, and DNA replication mechanisms .

How can non-specific binding issues with ARHGAP11A antibodies be addressed?

Non-specific binding represents a common challenge when working with ARHGAP11A antibodies. Several methodological approaches can minimize these issues:

• Antibody selection optimization:

  • Use affinity-purified antibodies, such as those purified against the specific antigen

  • Consider antibodies validated across multiple applications

  • Review literature for antibodies with demonstrated specificity

• Blocking protocol enhancement:

  • Extend blocking time (1-2 hours at room temperature)

  • Test alternative blocking agents (5% BSA, 5% milk, commercial blocking buffers)

  • Include 0.1-0.3% Triton X-100 in blocking solutions for membrane permeabilization

• Washing optimization:

  • Increase number of washes (minimum 3-5 washes of 5-10 minutes each)

  • Add 0.05-0.1% Tween-20 to washing buffers

  • Consider higher salt concentrations in wash buffers for stubborn non-specific binding

• Antibody dilution optimization:

  • Perform titration experiments to determine optimal concentration

  • For IHC applications, starting dilutions of 1:200-1:500 have been validated

  • For Western blot, concentrations of 0.04-0.4 μg/mL have shown specificity

• Sample preparation improvements:

  • Optimize fixation protocols (duration, fixative type)

  • For paraffin-embedded tissues, test different antigen retrieval methods

  • Freshly prepare all solutions to minimize contamination issues

What strategies enable accurate quantification of ARHGAP11A expression in research models?

Accurate quantification of ARHGAP11A expression requires multi-faceted approaches:

• mRNA quantification methods:

  • RT-qPCR with validated primers spanning exon-exon junctions

  • RNA-seq with appropriate normalization methods

  • Comparative analysis using multiple housekeeping genes for normalization

• Protein quantification approaches:

  • Western blot with densitometry analysis

  • ELISA using validated antibodies

  • Mass spectrometry for absolute quantification

• IHC scoring systems:

  • Implement H-score system (intensity × percentage of positive cells)

  • Digital image analysis using specialized software

  • Blinded assessment by multiple pathologists

• Normalization strategies:

  • Use matched normal-tumor pairs when possible

  • Include reference tissues with known expression levels

  • Apply appropriate statistical corrections for batch effects

• Validation across platforms:

  • Correlate mRNA and protein expression data

  • Compare in vitro and in vivo expression patterns

  • Validate findings using public databases (TCGA, Oncomine)

How should ARHGAP11A antibodies be stored and handled to maintain optimal activity?

Proper storage and handling of ARHGAP11A antibodies is critical for maintaining their activity and specificity:

• Temperature considerations:

  • Store at -20°C for long-term storage as recommended for most ARHGAP11A antibodies

  • Avoid repeated freeze-thaw cycles by preparing small aliquots

  • For short-term use (up to 1 week), 2-8°C storage is acceptable

• Buffer composition:

  • Most ARHGAP11A antibodies are supplied in PBS with stabilizers:

    • PBS with 0.02% sodium azide and 50% glycerol pH 7.3

    • Buffered aqueous glycerol solution

    • PBS with 0.09% sodium azide and 2% sucrose

• Handling precautions:

  • Work with antibodies on ice when preparing dilutions

  • Use sterile techniques to prevent contamination

  • Return to appropriate storage promptly after use

  • Note hazard warnings (sodium azide is POISONOUS AND HAZARDOUS)

• Reconstitution protocols:

  • Follow manufacturer's specific reconstitution instructions

  • Document date of reconstitution and calculate expiration

  • For concentrated formats, ensure complete dissolution before use

• Monitoring stability:

  • Include positive controls with each experiment to verify activity

  • Document lot numbers and performance characteristics

  • Consider fresh antibody if signal deterioration is observed