AHCYL1 Antibody

What is AHCYL1 and what functions make it relevant to cancer research?

AHCYL1, also known as IP3 receptor-binding protein released with IP3 (IRBIT), is a protein involved in multiple cellular functions including autophagy and apoptosis. Recent studies have revealed its significance in cancer biology:

• It functions as a negative regulator in Non-Small Cell Lung Cancer (NSCLC) tumorigenesis by modulating cell differentiation state

• Downregulation of AHCYL1 enhances stem-like properties in NSCLC cells, correlating with higher expression of stem markers POU5F1 and CD133

• AHCYL1 silencing increases tumorigenicity and angiogenesis in mouse xenograft models

• AHCYL1 expression is inversely correlated with proliferation marker Ki67 in NSCLC

• In colorectal cancer, tissues without AHCYL1 show weaker recruitment of natural killer cells, CD8+ T cells, and tumor-infiltrating lymphocytes, with poorer response to immunotherapy

The growing evidence suggests AHCYL1 acts as a tumor suppressor in multiple cancer types, making it an important research target.

What applications are most validated for AHCYL1 antibodies?

Based on commercially available antibodies and published research, AHCYL1 antibodies have been validated for multiple applications:

When planning experiments, researchers should consider cross-validating results using different detection methods to strengthen confidence in findings.

How should researchers choose between monoclonal and polyclonal AHCYL1 antibodies?

The choice depends on the experimental goals:

Monoclonal AHCYL1 Antibodies:

• Provide consistent lot-to-lot reproducibility (critical for longitudinal studies)

• Exhibit higher specificity for a single epitope

• Example: Cell Signaling Technology's AHCYL1/IRBIT (D3A5G) Rabbit mAb shows high specificity for endogenous AHCYL1 across human, mouse, rat, and monkey samples

• Ideal for targeted applications requiring high precision and reproducibility

Polyclonal AHCYL1 Antibodies:

• Recognize multiple epitopes, potentially providing stronger signals

• May offer broader detection across species variants

• Example: Proteintech's 10658-3-AP polyclonal antibody detects AHCYL1 in human, mouse, and rat samples across multiple applications

• Better for applications where signal amplification is crucial

For critical research, using both antibody types in parallel provides complementary validation.

What are the optimal sample preparation protocols for AHCYL1 detection?

For consistent and reliable AHCYL1 detection:

Western Blotting:

• Sample loading: 30 μg of protein per lane under reducing conditions

• Gel conditions: 5-20% SDS-PAGE gel at 70V (stacking)/90V (resolving) for 2-3 hours

• Transfer: Nitrocellulose membrane at 150 mA for 50-90 minutes

• Blocking: 5% non-fat milk in TBS for 1.5 hours at room temperature

• Primary antibody incubation: 0.5 μg/mL overnight at 4°C

Immunohistochemistry:

• Antigen retrieval: Heat-mediated in EDTA buffer (pH 8.0) or TE buffer (pH 9.0)

• Alternative: Citrate buffer (pH 6.0) can be used but may provide less optimal results

• Blocking: 10% goat serum

• Primary antibody: 2 μg/ml incubated overnight at 4°C

• Detection system: Biotin-streptavidin amplification with DAB chromogen shows good results

Immunofluorescence:

• Cell fixation: 4% paraformaldehyde followed by permeabilization

• Blocking: 10% normal goat serum

• Antibody dilution: 0.25-2 μg/mL range depending on cell type

What strategies should be employed to validate AHCYL1 antibody specificity?

Multiple validation approaches should be used in combination:

1. Knockdown/Knockout Controls:

• RNAi knockdown validation has been successfully used for AHCYL1 antibodies

• Example: HT-29 cells were stably transfected with AHCYL1 shRNA plasmid (Origene cat. MR208502L3V) to create knockdown controls

• Specificity confirmed by reduced/absent signal in knockdown/knockout cells

2. Multi-antibody Approach:

• Use antibodies targeting different epitopes of AHCYL1:

  • N-terminal targeting (ABIN6259835)

  • C-terminal targeting antibodies

  • Full-length protein antibodies

• Concordant results across different antibodies strengthen validity

3. Peptide Competition:

• Pre-incubate antibody with immunizing peptide

• Example: For antibodies like ABIN6259835, use the synthesized peptide derived from human AHCYL1 N-terminal region

• Loss of signal confirms specificity

4. Cross-species Validation:

• Test across multiple species where AHCYL1 is conserved

• AHCYL1 antibodies with validated reactivity across human, mouse, rat samples provide stronger confidence

How can researchers accurately interpret AHCYL1 subcellular localization patterns?

AHCYL1 exhibits complex localization patterns that require careful interpretation:

Expected Localization Patterns:

• Predominantly cytoplasmic localization with some nuclear presence

• In normal tissues, strong AHCYL1 labeling is observed in the epithelial lining of distal airways (bronchioles)

Analytical Considerations:

• Co-localization studies: Combine AHCYL1 antibody with subcellular markers for:

  • Endoplasmic reticulum

  • Nuclear membrane

  • Cytoskeletal elements

• Cell type-specific variations:

  • Well-differentiated cells typically show stronger AHCYL1 expression

  • Poorly differentiated cells with worse prognosis show weak AHCYL1 staining

• Technical considerations:

  • Fixation methods can affect observed localization patterns

  • Paraformaldehyde fixation preserves most AHCYL1 epitopes

  • Use Z-stack confocal microscopy to resolve true subcellular distribution

For quantitative analysis, researchers should develop scoring systems that account for both intensity and distribution patterns.

What are the most informative cell and tissue models for studying AHCYL1 function in cancer?

Based on published research, these models provide robust systems for AHCYL1 investigation:

Cell Line Models:

• A549 and H1299 NSCLC cell lines (well-characterized for AHCYL1 knockdown studies)

• HT-29 colorectal cancer cells (validated for AHCYL1 knockdown and functional studies)

• HeLa cells (consistently express detectable AHCYL1 levels suitable for antibody validation)

Tissue Models:

• Lung adenocarcinoma tissues (show variable AHCYL1 expression with clinical correlation)

• Colorectal cancer tissues (AHCYL1 deletion correlates with shorter survival)

• Normal bronchiolar epithelium (strong AHCYL1 expression as positive control)

Animal Models:

• NOD scid mice xenograft models with AHCYL1-silenced cancer cells

  • A549 KD-AL1-4 derived tumors show significantly larger size compared to controls

  • Enhanced angiogenesis observed in AHCYL1-depleted tumors

For comprehensive analysis, researchers should include both models that naturally express high and low levels of AHCYL1.

How does AHCYL1 expression correlate with clinical cancer outcomes and biomarker potential?

Multiple studies have identified significant correlations between AHCYL1 and clinical outcomes:

Lung Cancer:

• AHCYL1 expression is inversely correlated with Ki67 (Spearman's correlation p=0.002)

• Lower AHCYL1 expression associated with recurrence in lung adenocarcinoma patients

• Gender association: Higher AHCYL1 expression observed in female vs. male patients

• Tumorigenic effects of AHCYL1 silencing were stronger in male mice, suggesting gender-dependent tumor suppressor role

Colorectal Cancer:

• AHCYL1 deletion correlates with shorter survival in CRC patients

• Tissues without AHCYL1 show reduced recruitment of NK cells, CD8+ T cells, and TILs

• AHCYL1 knockdown promoted tumor growth in CRC mouse models

• Prognostic model based on AHCYL1 and related genes showed high predictive performance for immunotherapy response (C-index of 0.74)

These findings suggest AHCYL1 has potential as a prognostic biomarker and predictor of immunotherapy response across multiple cancer types.

What are the recommended troubleshooting steps for weak or nonspecific AHCYL1 antibody signals?

When encountering signal issues with AHCYL1 antibodies, consider these methodological adjustments:

For Weak Signals:

• Optimized Antigen Retrieval:

  • For FFPE tissues, test both EDTA buffer (pH 8.0) and citrate buffer (pH 6.0)

  • Extend retrieval time to 20-30 minutes

• Signal Amplification:

  • Implement biotin-streptavidin amplification system for IHC

  • For IF, try tyramide signal amplification

• Antibody Concentration Adjustment:

  • For Western blot: Test concentration range from 0.04-1.0 μg/mL

  • For IHC: Increase from standard 1:200-1:500 to 1:50-1:100 dilution

• Extended Incubation:

  • Increase primary antibody incubation from overnight to 48 hours at 4°C

  • Use humidified chamber to prevent evaporation

For Nonspecific Signals:

• Stringent Blocking:

  • Extend blocking time to 2 hours

  • Try different blockers (BSA, serum, commercial blockers)

• Antibody Validation:

  • Test on known positive and negative controls

  • Include peptide competition controls

• Buffer Optimization:

  • Increase salt concentration in wash buffers

  • Add 0.1-0.3% Triton X-100 to reduce background

• Sample-specific Adjustments:

  • For highly autofluorescent tissues, use Sudan Black B treatment

  • For tissues with high endogenous peroxidase, extend H₂O₂ quenching

What considerations are important when studying AHCYL1 in stem cell contexts?

AHCYL1 has emerging roles in stem cell biology that require specific experimental approaches:

Experimental Design Considerations:

• Stem Cell Marker Co-expression Analysis:

  • Co-stain for AHCYL1 with stem markers POU5F1 and CD133, which show increased expression in AHCYL1-silenced cells

  • Use multiplex immunofluorescence to quantify co-expression patterns

• Functional Assays:

  • Sphere formation assays: AHCYL1-silenced cells form significantly more spheres, indicating enhanced self-renewal capacity

  • Limiting dilution assays provide quantitative measurement of stemness

• Differentiation Dynamics:

  • Monitor AHCYL1 expression during differentiation from stem to mature cell states

  • Markers MUC5B and SFTPC show decreased expression in AHCYL1-silenced cells, suggesting less differentiated state

• Metabolic Profiling:

  • AHCYL1-depleted cells show altered SAM/SAH ratio, suggesting changes in methylation capacity

  • Consider measuring methionine cycle metabolites to correlate with stemness properties

Interpretation Challenges:

• AHCYL1's effects on stemness appear independent of cell proliferation rate

• Gender-specific effects may influence stemness outcomes

• Changes in stemness may be partially independent of histone methylation status

Understanding these nuances is critical for correctly interpreting AHCYL1's role in stem cell biology and cancer stem cell phenotypes.

What are the recommended positive control samples for AHCYL1 antibody validation?

Based on validated antibody testing data, these samples consistently show reliable AHCYL1 expression:

Cell Line Controls:

• HeLa cells: Consistently express detectable AHCYL1 levels

• 293T cells: Show strong band in Western blot analysis

• Jurkat cells: Validated for Western blot detection

Tissue Controls:

• Human thymus tissue: Shows consistent AHCYL1 expression

• Mouse brain tissue: Shows specific staining pattern in IHC

• Normal bronchiolar epithelium: Shows strong AHCYL1 labeling, particularly at the epithelial lining of distal airways

• Rat pancreas tissue: Validated for Western blot detection

Expression Systems:

• Recombinant AHCYL1 expression systems can serve as positive controls

• For antibodies targeting specific epitopes, synthetic peptides derived from the corresponding regions

For comprehensive validation, include samples representing different expression levels (high, medium, low) to establish detection range.

How can researchers effectively use AHCYL1 antibodies in multiplex immunostaining techniques?

Successful multiplex approaches require careful planning:

Antibody Selection:

• Choose AHCYL1 antibodies raised in different host species from other target antibodies

• Example: Combine rabbit anti-AHCYL1 (HPA042589) with mouse antibodies against other targets

• Verify minimal cross-reactivity between secondary antibodies

Multiplexing Protocols:

• Sequential staining approach:

  • Complete AHCYL1 staining with one fluorophore

  • Block residual primary antibody binding sites

  • Proceed with second primary antibody

• Combined co-staining approach:

  • Verified combinations include AHCYL1 with Ki67 (provides inverse correlation data)

  • AHCYL1 with CD8+ T cells in tumor environment

• Tyramide signal amplification multiplex:

  • Allows use of antibodies from same species

  • Requires microwave treatment between rounds

Analysis Considerations:

• Use spectral unmixing to resolve overlapping fluorophores

• Include single-stain controls for each fluorophore

• Quantify co-localization using appropriate statistical methods (Pearson's coefficient, Manders' coefficient)

What quantification methods are recommended for AHCYL1 expression analysis in tissue samples?

For rigorous quantitative analysis of AHCYL1:

IHC Scoring Systems:

• In validated studies, AHCYL1 IHC staining has been scored on a 1-4 scale :

  • Score 1: 5% positive cells

  • Score 2: 20% positive cells

  • Score 3: 45% positive cells

  • Score 4: 30% positive cells

• Group samples as "low" or "high" AHCYL1 expression for correlation with clinical parameters

Digital Pathology Approaches:

• Whole slide imaging: Scan entire tissue sections for unbiased quantification

• Machine learning algorithms: Train to recognize AHCYL1 staining patterns and intensity

• Multiplex spatial analysis: Quantify AHCYL1 in relation to microenvironmental features

Correlation Analysis:

• Inverse correlation between AHCYL1 and Ki67 provides internal validation

• Correlate with other markers like POU5F1, CD133, MUC5B, and SFTPC

• Analyze relationship with immune cell infiltration (NK cells, CD8+ T cells, TILs)

Statistical Methods:

• Use Spearman's correlation for non-parametric analysis of marker associations

• Kaplan-Meier survival analysis to correlate expression with clinical outcomes

• Multivariate analysis to account for confounding variables

How can AHCYL1 antibodies be used to investigate angiogenesis in cancer models?

AHCYL1 has been linked to angiogenesis regulation, offering several experimental approaches:

In Vivo Angiogenesis Assessment:

• AHCYL1-depleted cancer cells showed increased vessel density in xenograft models

• Quantify vessel density visually in regions surrounding tumor injection sites

• Correlate with increased VEGF-A protein levels observed in AHCYL1-depleted cells

Methodological Approach:

• Tumor Xenograft Studies:

  • Inject AHCYL1 wild-type and knockdown cells subcutaneously

  • After tumor formation (approximately 7 days), analyze vascular patterns

  • Quantify vessel density using appropriate vessel markers (CD31, CD34)

• Molecular Correlation:

  • Use AHCYL1 antibodies in combination with VEGF-A antibodies

  • Quantify inverse relationship between AHCYL1 and angiogenic factors

• Matrigel Plug Assay:

  • Embed AHCYL1-manipulated cells in Matrigel

  • Implant subcutaneously and assess vessel infiltration

  • Compare vessel formation between AHCYL1-expressing and depleted conditions

Analysis Considerations:

• Account for gender differences (AHCYL1 effects appear stronger in males)

• Correlate angiogenesis with tumor growth metrics

• Consider three-dimensional vessel architecture, not just density

What are the considerations for using AHCYL1 antibodies in immunotherapy response prediction?

AHCYL1's emerging role in immune response makes it valuable for immunotherapy research:

Clinical Correlations:

• AHCYL1 deletion correlates with weaker ability to recruit NK cells, CD8+ T cells, and TILs

• Tissues without AHCYL1 show poorer response to immunotherapy

• Low-risk group (based on AHCYL1-related gene signature) associates with lower tumor mutational burden (TMB) and higher immunotherapy response

Experimental Design:

• Immune Infiltration Analysis:

  • Use AHCYL1 antibodies in multiplex with immune cell markers

  • Quantify spatial relationships between AHCYL1 expression and immune cell density

• Predictive Model Development:

  • Combine AHCYL1 expression with other markers in predictive nomograms

  • Validated models have achieved C-index of 0.74 for immunotherapy response prediction

• Functional Validation:

  • Compare checkpoint inhibitor response in AHCYL1 high vs. low tumors

  • Correlate AHCYL1 expression with PD-L1, PD-1, and CTLA-4 expression

Methodological Considerations:

• Include both hot (immune-rich) and cold (immune-poor) tumors in analysis

• Control for confounding factors like tumor type, stage, and previous treatments

• Consider AHCYL1 in context of broader tumor immune microenvironment

How should researchers approach gender-specific differences in AHCYL1 expression and function?

Multiple studies have identified gender-dependent aspects of AHCYL1 biology:

Observed Gender Differences:

• Higher AHCYL1 expression in samples from female versus male cancer patients

• Stronger tumorigenic effects of AHCYL1 silencing in male mice

• Potential gender-dependent role as a tumor suppressor

Recommended Research Approaches:

• Sex-disaggregated Experimental Design:

  • Analyze male and female samples separately

  • Include sufficient statistical power for both sexes

  • Report sex-specific results even when differences are not observed

• Hormonal Context Investigation:

  • Examine potential interactions between AHCYL1 and hormone receptors

  • Consider hormonal status in clinical sample analysis

  • Test AHCYL1 expression under different hormonal conditions in vitro

• Comparative Survival Analysis:

  • Stratify survival analyses by sex

  • Determine if AHCYL1 has differential prognostic value based on gender

  • Include gender as a variable in multivariate analysis models

Methodological Considerations:

• Document estrous/menstrual cycle stage in female samples when possible

• Consider using hormone-depleted serum conditions for in vitro studies

• Apply matched case-control designs when comparing across sexes