HAO2 Antibody, FITC conjugated

What is HAO2 and what is its significance in hepatocellular carcinoma research?

HAO2 (Hydroxyacid oxidase 2) is a peroxisomal enzyme also known as HAOX2 with EC classification 1.1.3.15, functioning as an (S)-2-hydroxy-acid oxidase . Recent studies have identified HAO2 as a potential tumor suppressor gene in hepatocellular carcinoma (HCC) . Experimental evidence indicates that HAO2 is significantly underexpressed in HCC tissues and cell lines compared to paracancerous tissues . Patients with low HAO2 expression demonstrate poorer disease-free survival rates, suggesting its potential value as a prognostic biomarker .

HAO2's tumor-suppressive functions have been experimentally validated through multiple methodological approaches. When overexpressed in HCC cell lines (specifically BEL-7405 and Hep3B), HAO2 demonstrates inhibitory effects on cell proliferation, migration, and invasion capabilities . This inhibitory effect has been confirmed through CCK-8 assays, colony formation assays, and EdU incorporation assays, all showing statistically significant decreases in proliferation markers . The mechanism appears to involve negative regulation by miR-615-5p, which targets the HAO2 3'UTR region .

What are the key specifications of HAO2 Antibody, FITC conjugated?

The HAO2 Antibody, FITC conjugated (product code: CSB-PA882145LC01HU) is a polyclonal antibody raised in rabbits against recombinant Human Hydroxyacid oxidase 2 protein (amino acids 2-200) . The antibody has the following specifications:

This antibody is specifically designed to target human HAO2, making it suitable for investigating HAO2 expression patterns in human tissue samples and cell lines .

How does FITC conjugation affect antibody performance in HAO2 detection?

FITC (Fluorescein isothiocyanate) conjugation provides direct fluorescent visualization capabilities but significantly impacts antibody performance characteristics in several ways. Research has established a negative correlation between FITC-labeling index and binding affinity for target antigens . This phenomenon occurs because excessive FITC labeling can alter the antibody's structural conformation or obstruct binding sites critical for antigen recognition .

When using FITC-conjugated HAO2 antibodies, researchers should consider this important trade-off: antibodies with higher FITC-labeling indices typically demonstrate increased detection sensitivity but may simultaneously exhibit increased non-specific binding, resulting in background staining that complicates data interpretation . For optimal experimental design, researchers should carefully titrate FITC-conjugated HAO2 antibodies to determine the optimal concentration that balances detection sensitivity with specificity .

To mitigate these effects, controls are essential in experimental design:

• Include appropriate isotype controls at the same concentration as the HAO2 antibody

• Validate staining patterns using alternative detection methods

• Consider the inclusion of blocking steps to reduce non-specific binding

• Optimize fixation and permeabilization protocols for each specific application

What sample preparation considerations are important when using HAO2 Antibody, FITC conjugated?

Proper sample preparation is critical for successful HAO2 detection using FITC-conjugated antibodies. For cellular samples, fixation and permeabilization must be optimized to maintain the antigen epitope while allowing antibody access. Based on antibody characteristics and experimental requirements, researchers should consider:

• Fixation method selection: Formaldehyde (4%) provides good structural preservation while maintaining HAO2 antigenicity. Methanol fixation may be preferred for certain applications but requires validation for HAO2 epitope preservation.

• Buffer composition: The HAO2 antibody is stored in a buffer containing 50% glycerol and 0.01M PBS at pH 7.4 . This suggests optimal binding near physiological pH, and researchers should maintain consistent pH conditions during sample preparation and staining.

• Blocking protocols: To reduce non-specific binding, implement a 30-60 minute blocking step using 5-10% normal serum from the same species as the secondary antibody (if using indirect methods) or from a species unrelated to your experimental system.

• Permeabilization considerations: For intracellular HAO2 detection, mild detergents like 0.1-0.5% Triton X-100 or 0.05-0.1% saponin may be necessary. The optimal detergent concentration should be determined empirically.

• Storage impact: Samples should be prepared fresh when possible, as the HAO2 antigen may degrade during extended storage periods. If storage is necessary, maintain samples at -80°C and avoid repeated freeze-thaw cycles .

What methodological approaches can optimize HAO2 detection in hepatocellular carcinoma research?

For researchers investigating HAO2's role in hepatocellular carcinoma, several methodological strategies can enhance detection and characterization:

• Multi-parametric flow cytometry: When using HAO2 Antibody, FITC conjugated, design panels that include markers for cell proliferation (Ki-67), apoptosis (Annexin V), and relevant tumor markers. This approach allows correlation of HAO2 expression with cellular phenotypes and states. To minimize spectral overlap with FITC (excitation ~490nm, emission ~520nm), select compatible fluorophores for additional markers, such as PE-Cy7, APC, or BV650.

• Quantitative immunofluorescence microscopy: For spatial analysis of HAO2 expression in tissue sections, implement:

  • Z-stack imaging (0.5-1μm intervals) to capture the full cellular distribution of HAO2

  • Deconvolution processing to enhance resolution of subcellular localization

  • Co-staining with peroxisomal markers to confirm expected localization patterns

  • Automated image analysis using appropriate software (ImageJ/FIJI with custom macros) for unbiased quantification

• Validation through complementary techniques: Research indicates significant HAO2 underexpression in HCC tissues . To validate antibody-based findings:

  • Parallel qRT-PCR analysis of HAO2 mRNA levels

  • Western blot confirmation using non-conjugated HAO2 antibodies

  • siRNA knockdown or CRISPR-based genetic approaches as negative controls

• Pathological correlation: Integrate HAO2 expression data with clinical parameters and pathological features:

  • Design tissue microarrays with adequate statistical power

  • Implement standardized scoring systems for HAO2 immunoreactivity

  • Correlate HAO2 expression with disease-free survival metrics

How can researchers investigate the HAO2/miR-615-5p regulatory relationship using FITC-conjugated antibodies?

The negative regulatory relationship between miR-615-5p and HAO2 presents an important research direction in understanding HCC pathogenesis . To investigate this relationship using HAO2 Antibody, FITC conjugated:

• Dual-detection experimental design: Implement protocols that simultaneously assess miR-615-5p and HAO2 protein levels:

  • Combine in situ hybridization for miR-615-5p with immunofluorescence for HAO2

  • Utilize flow cytometry sorting based on HAO2-FITC signal followed by miR-615-5p quantification by RT-qPCR

  • Perform sequential tissue section analysis comparing miR-615-5p and HAO2 distribution patterns

• Perturbation experiments: Modulate miR-615-5p levels and evaluate HAO2 protein expression:

  • Transfect cells with miR-615-5p mimics or inhibitors, then quantify HAO2-FITC signal by flow cytometry

  • Create stable cell lines with inducible miR-615-5p expression systems to monitor dynamic HAO2 regulation

  • Implement CRISPR-based editing of the miR-615-5p binding site in the HAO2 3'UTR

• Visualization of spatiotemporal dynamics: Track the inverse relationship between miR-615-5p and HAO2 in cell models:

  • Use time-lapse microscopy following miR-615-5p induction

  • Implement fluorescence recovery after photobleaching (FRAP) to assess HAO2 protein dynamics

  • Utilize proximity ligation assays to investigate potential physical interactions within the regulatory complex

• Quantification strategies: When using flow cytometry, calculate the median fluorescence intensity (MFI) ratio between HAO2-FITC signal in experimental vs. control conditions. Research indicates this ratio should decrease following miR-615-5p mimic transfection, consistent with the observed negative correlation (r = -0.5231, p < 0.01) between miR-615-5p and HAO2 mRNA levels in HCC tissues .

What quality control measures are essential for reliable HAO2 Antibody, FITC conjugated experiments?

To ensure experimental reliability and reproducibility with HAO2 Antibody, FITC conjugated, researchers should implement these critical quality control measures:

• Antibody validation requirements:

  • Confirm specificity using positive and negative control tissues/cells with known HAO2 expression levels

  • Validate antibody performance using alternative detection methods (western blot, immunoprecipitation)

  • Assess lot-to-lot variation through standardized testing protocols

  • Determine the FITC-labeling index, as higher indices can reduce binding affinity while potentially increasing sensitivity

• Instrument standardization for flow cytometry:

  • Implement routine calibration using standardized fluorescent beads

  • Establish consistent voltage settings for FITC detection channel

  • Include compensation controls when using multiple fluorophores

  • Document laser output and detector sensitivity measurements

• Experimental controls:

  • Include appropriate isotype controls at identical concentrations to the HAO2 antibody

  • Implement fluorescence-minus-one (FMO) controls for multiparameter flow cytometry

  • Include biological negative controls (tissues/cells with HAO2 knockdown)

  • Prepare technical replicates to assess procedural variation

• Data quality metrics:

  • Signal-to-noise ratio calculation for each experiment

  • Coefficient of variation across technical and biological replicates

  • Statistical analysis appropriate for data distribution characteristics

  • Explicit reporting of all quality control measures in publications

How can HAO2 Antibody, FITC conjugated be utilized in xenograft tumor models?

Research demonstrates that overexpression of HAO2 reduces the tumorigenicity of HCC cells in nude mice xenograft models . To effectively utilize HAO2 Antibody, FITC conjugated in such studies:

• Experimental design considerations:

  • Establish cohorts with appropriate statistical power (minimum n=8 per group)

  • Include both HAO2-overexpressing and control groups (e.g., OV-HAO2 vs. OV-NC)

  • Monitor tumor volume and weight as primary endpoints

  • Consider survival analysis as a secondary endpoint

• Tissue processing methodology:

  • Harvest tumors at defined timepoints (early, mid, and late stages)

  • Implement standardized fixation protocols optimized for HAO2 epitope preservation

  • Prepare sections at consistent thickness (5-7μm recommended)

  • Process paired samples for both immunofluorescence and molecular analysis

• HAO2 distribution analysis:

  • Quantify HAO2-FITC signal intensity across tumor sections using standardized image acquisition parameters

  • Map HAO2 expression patterns relative to proliferative zones, necrotic regions, and tumor margins

  • Correlate HAO2 expression with tumor growth characteristics

  • Compare in vivo expression patterns with in vitro cell line findings

• Functional assessment:

  • Implement ex vivo flow cytometry of enzymatically dissociated tumors to quantify HAO2-positive cell populations

  • Correlate HAO2 expression with proliferation markers (Ki-67, BrdU incorporation)

  • Assess apoptotic indices in regions with differential HAO2 expression

  • Evaluate tumor microenvironment characteristics in relation to HAO2 levels

How can researchers address background fluorescence issues with HAO2 Antibody, FITC conjugated?

Background fluorescence presents a significant challenge when working with FITC-conjugated antibodies. Research indicates that FITC-labeled antibodies with higher labeling indices may exhibit increased non-specific staining . To address this issue:

• Optimization strategies:

  • Titrate antibody concentration to determine the optimal signal-to-noise ratio

  • Implement extended washing steps (minimum 3x wash cycles with gentle agitation)

  • Utilize detergents (0.05-0.1% Tween-20) in wash buffers to reduce non-specific binding

  • Consider alternative buffers if high background persists (PBS with 1-2% BSA or PBS with 0.1-0.5% gelatin)

• Sample-specific considerations:

  • For tissues with high autofluorescence (liver, brain), implement quenching steps:

    • 0.1-1% Sudan Black B treatment for 20 minutes

    • 10mM CuSO₄ in 50mM ammonium acetate buffer (pH 5.0) for 30-60 minutes

    • Commercial autofluorescence quenching reagents

  • For fixed cells, reduce aldehyde-induced fluorescence with sodium borohydride treatment (1mg/mL for 5-10 minutes)

• Technical adaptations:

  • Consider confocal microscopy with spectral unmixing capabilities

  • Implement deconvolution algorithms for improved signal separation

  • Utilize longer wavelength detection settings for FITC (520-530nm rather than 510-520nm)

  • Apply post-acquisition background subtraction using appropriate controls

• Alternative detection strategies:

  • If background issues persist, consider indirect detection methods using unconjugated primary HAO2 antibody

  • Implement signal amplification techniques such as tyramide signal amplification

  • Consider alternative conjugates (Alexa Fluor 488 often provides improved signal-to-noise compared to FITC)

What strategies can improve detection of low HAO2 expression in clinical samples?

HAO2 is reported to be underexpressed in HCC tissues , necessitating optimized methods for reliable detection of low abundance targets:

• Signal amplification approaches:

  • Tyramide signal amplification (TSA): Can increase sensitivity 10-100 fold

  • Implement avidin-biotin complex (ABC) methods prior to FITC-conjugated streptavidin

  • Consider sequential multilayer staining approaches for cumulative signal enhancement

  • Utilize photomultiplier tube (PMT) settings optimized for low signal detection

• Sample preparation enhancements:

  • Optimize antigen retrieval methods:

    • Heat-induced epitope retrieval (HIER) with citrate buffer (pH 6.0) or Tris-EDTA (pH 9.0)

    • Enzymatic retrieval with proteinase K (1-5 μg/mL for 5-10 minutes)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Implement blocking of endogenous peroxidase activity if using HRP-based detection

• Instrument optimization:

  • For flow cytometry: Increase PMT voltage in small increments while monitoring negative control

  • For confocal microscopy: Adjust pinhole size, gain, and laser power for optimal signal capture

  • For fluorescence microscopy: Utilize cameras with enhanced sensitivity and implement longer exposure times

• Complementary methodological approaches:

  • RNAscope for sensitive detection of HAO2 mRNA as validation of protein findings

  • Proximity ligation assay (PLA) for detecting protein interactions even at low expression levels

  • Single-cell analysis approaches to identify rare HAO2-expressing subpopulations

How can researchers validate the specificity of HAO2 Antibody, FITC conjugated in their experimental system?

Antibody specificity validation is essential for generating reliable research data. For HAO2 Antibody, FITC conjugated:

• Comprehensive validation protocol:

  • Western blot analysis with recombinant HAO2 protein and tissue/cell lysates

  • Immunoprecipitation followed by mass spectrometry identification

  • RNA interference (siRNA or shRNA) to create HAO2-depleted samples as negative controls

  • CRISPR/Cas9-mediated HAO2 knockout validation system

  • Immunofluorescence pattern comparison with alternative HAO2 antibodies

• Specificity controls for immunostaining:

  • Peptide competition assay: Pre-incubate antibody with excess HAO2 immunogen peptide (2-200AA)

  • Absorption controls: Compare staining before and after HAO2 antibody pre-absorption

  • Tissue panel validation: Test antibody on tissues with known differential HAO2 expression

  • Cross-reactivity assessment with closely related proteins (HAO1)

• Flow cytometry validation metrics:

  • Compare staining pattern with isotype control at identical concentration

  • Implement fluorescence-minus-one (FMO) controls for multiparameter panels

  • Compare HAO2-FITC staining pattern across multiple cell types with known HAO2 expression

  • Verify staining pattern changes in response to experimental manipulations that alter HAO2 levels

• Quantitative verification approaches:

  • Correlation analysis between HAO2 protein levels (by FITC signal intensity) and mRNA levels (by qRT-PCR)

  • Dose-dependent staining with recombinant HAO2 protein

  • Multi-epitope targeting using antibodies against different HAO2 regions

  • Statistical analysis of staining reproducibility across independent experiments

How can HAO2 Antibody, FITC conjugated contribute to understanding the role of HAO2 in cancer progression?

Recent research has established HAO2 as a potential tumor suppressor in HCC with inhibitory effects on cell proliferation, migration, and invasion . HAO2 Antibody, FITC conjugated can advance this research through:

• Multi-parameter profiling approaches:

  • Design flow cytometry panels combining HAO2-FITC with markers for:

    • Cell cycle progression (PI, DAPI)

    • Apoptotic status (Annexin V, cleaved caspase-3)

    • Epithelial-mesenchymal transition (E-cadherin, Vimentin)

    • Cancer stem cell phenotypes (CD44, CD133)

  • Implement high-dimensional analysis methods (tSNE, UMAP) to identify cell subpopulations

• Spatial characterization in tumor architecture:

  • Apply multiplexed imaging to map HAO2 distribution relative to:

    • Tumor margin and invasive front

    • Hypoxic regions (using HIF-1α co-staining)

    • Tumor vasculature (CD31 co-staining)

    • Immune infiltrates (CD45, CD3, CD68 co-staining)

  • Implement digital pathology algorithms for quantitative spatial analysis

• Functional relationship investigations:

  • Utilize flow-based cell sorting of HAO2-high versus HAO2-low populations for:

    • Differential gene expression analysis

    • Chromatin accessibility profiling

    • Proteomic characterization

    • Functional assays (migration, invasion, sphere formation)

  • Correlate HAO2 expression with response to therapeutic agents

• Clinical translation approaches:

  • Develop quantitative scoring systems for HAO2 immunoreactivity in patient samples

  • Correlate HAO2 expression with clinical outcomes and disease-free survival

  • Investigate HAO2 as a predictive biomarker for treatment response

  • Examine HAO2 dynamics during disease progression and recurrence

What methodological considerations are important when investigating the interaction between HAO2 and miR-615-5p?

The negative regulatory relationship between miR-615-5p and HAO2 represents an important research area. When using HAO2 Antibody, FITC conjugated to study this interaction:

• Integrated experimental approaches:

  • Dual luciferase reporter systems to validate direct miR-615-5p binding to HAO2 3'UTR

  • Real-time monitoring of HAO2 protein levels following miR-615-5p modulation using live-cell imaging

  • Single-cell analysis correlating miR-615-5p and HAO2 expression at individual cell level

  • RNA immunoprecipitation to characterize the miR-615-5p-containing complexes

• Visualization strategies:

  • Implement fluorescence resonance energy transfer (FRET) approaches to study proximity of regulatory components

  • Utilize fluorescence correlation spectroscopy (FCS) to analyze molecular dynamics

  • Apply stimulated emission depletion (STED) microscopy for super-resolution imaging of regulatory complexes

  • Consider optogenetic approaches for temporal control of miR-615-5p activity

• Quantitative analysis framework:

  • Establish dose-response relationships between miR-615-5p levels and HAO2 protein expression

  • Implement mathematical modeling of the regulatory network

  • Utilize Bayesian statistical approaches for integrating multiple data types

  • Develop machine learning algorithms for pattern recognition in complex datasets

• Translational evaluation:

  • Analyze correlation patterns between miR-615-5p and HAO2 in clinical HCC samples

  • Stratify patient cohorts based on miR-615-5p/HAO2 expression ratios

  • Investigate potential therapeutic applications targeting the miR-615-5p/HAO2 axis

  • Develop biomarker panels incorporating both miR-615-5p and HAO2 expression metrics