PTGS2 Antibody, FITC conjugated

What is PTGS2 and why is it important to study?

PTGS2 is an inducible enzyme that catalyzes the conversion of arachidonic acid to prostaglandin H2, which is subsequently converted into various prostaglandins by downstream enzymes. Unlike its constitutively expressed counterpart PTGS1 (COX-1), PTGS2 is induced in response to inflammatory stimuli such as cytokines, growth factors, and cellular stress . PTGS2 plays crucial roles in inflammation, pain, fever, angiogenesis, and tumor growth, making it a significant target for research across multiple disease models .

What applications are FITC-conjugated PTGS2 antibodies suitable for?

FITC-conjugated PTGS2 antibodies are particularly suitable for flow cytometry, immunocytochemistry/immunofluorescence (ICC/IF), and can also be used for Western blot applications . The fluorescent properties of FITC make these antibodies especially valuable for applications requiring direct visualization of PTGS2 expression in cells or tissues without the need for secondary antibody incubation steps.

How should FITC-conjugated PTGS2 antibodies be stored for optimal performance?

FITC-conjugated antibodies require special storage considerations to maintain their fluorescent properties. They should be aliquoted and stored in the dark at 2-8°C, protected from prolonged exposure to light . Repeated freeze/thaw cycles should be avoided. Before opening, it is recommended to spin the vial, and the antibody solution should be gently mixed before use .

What controls should be included when using PTGS2 antibodies in experiments?

For rigorous experimental design, include both positive and negative controls. For positive controls, use cell lines or tissues known to express PTGS2, such as macrophages stimulated with IL-1β . For negative controls, use samples where PTGS2 is not expressed or is knocked down. Additionally, an isotype control (matching the host species and immunoglobulin class) should be included to control for non-specific binding, especially in flow cytometry and immunofluorescence applications.

How can I quantify PTGS2 protein expression in tissue lysates?

Western blot analysis can effectively quantify the glycosylated form of PTGS2 (gPTGS2) in tissue lysates. In a study examining colorectal cancer specimens, researchers detected gPTGS2 in 96/100 CRC samples with a median of 156.86 pg and a range of 0.00–1515.64 pg of protein in 30 μg of tissue lysate . This method demonstrated high reproducibility with a Pearson's correlation of r = 0.907 (p < 0.0000000000000000000000217) when replicated .

How can I differentiate between tumor-derived and stroma-derived PTGS2 in cancer tissue samples?

Distinguishing tumor-derived from stroma-derived PTGS2 requires specialized immunohistochemistry (IHC) approaches. Research has shown that tumor and stromal cells contribute differently to total PTGS2 levels in tissue samples. To differentiate:

• Perform IHC using anti-PTGS2 antibodies on serial tissue sections

• Score tumor epithelial-derived and stroma-derived fractions separately

• For more specific quantification of macrophage-derived PTGS2, implement multiplex IHC:

  • Use consecutive destaining, stripping, and reprobing techniques on the same tissue slices

  • Test specific marker combinations (e.g., CD68–iNOS–PTGS2 for M1 macrophages or Arg1–MRC1–CD163–PTGS2 for M2 macrophages)

Studies have demonstrated a moderate correlation (Pearson coefficient 0.422, p = 0.0000586) between CD68/PTGS2 and a weaker correlation (0.316, p = 0.00324) for CD163/PTGS2 in colorectal cancer tissues .

What methodological approaches can address the influence of photobleaching on FITC-conjugated PTGS2 antibody experiments?

FITC is susceptible to photobleaching, which can affect experimental outcomes, particularly in long-duration imaging studies. To mitigate photobleaching effects:

• Minimize exposure to excitation light during sample preparation and imaging

• Use anti-fade mounting media containing anti-photobleaching agents

• Adjust imaging parameters to use minimal excitation light intensity without compromising signal detection

• Consider time-series correction algorithms if quantitative analysis is required

• For extended imaging sessions, use reference standards to normalize signal intensity across time points

How can I optimize multiplex immunofluorescence protocols to study PTGS2 co-localization with macrophage markers?

Optimizing multiplex immunofluorescence for PTGS2 and macrophage markers requires:

• Sequential antibody staining with careful ordering:

  • Begin with the lowest abundance target (often PTGS2)

  • Follow with higher abundance targets (CD68, CD163)

• Implement proper tyramide signal amplification (TSA) for each target

• Complete antibody stripping between rounds using optimized buffer systems

• Use spectral unmixing to reduce fluorophore bleed-through

• Include single-stained controls for each antibody to facilitate accurate spectral unmixing

Research has shown that quantifying cells expressing these antigens in overlapping areas of equal extension can validate co-localization observations, with correlation coefficients of 0.422 for CD68/PTGS2 and 0.316 for CD163/PTGS2 in colorectal cancer tissues .

What are the key considerations when using WGCNA (Weighted Gene Co-expression Network Analysis) to identify PTGS2 as a biomarker in disease states?

WGCNA is a powerful bioinformatic approach for identifying disease-associated gene modules. When using WGCNA to study PTGS2:

• Optimize the soft-threshold power parameter (e.g., power=13, scale-free R² = 0.85 has been effective in arteriovenous fistula studies)

• Identify modules with highest correlation to disease phenotype (e.g., blue and red modules)

• Intersect hub genes from relevant modules with oxidative stress-related differentially expressed genes (OSDEGs)

• Validate findings using independent datasets and experimental approaches

• Confirm PTGS2 expression patterns in clinical samples using the FITC-conjugated antibodies

This approach has successfully identified PTGS2 as an essential biomarker in arteriovenous fistulas (AVFs) failure in hemodialysis patients .

How can I investigate the role of inflammatory mediators like IL-1β in PTGS2 induction using FITC-conjugated antibodies?

To study IL-1β-mediated PTGS2 induction:

• Experimental design:

  • Culture target cells (e.g., fibroblasts, cancer cell lines) in serum-free conditions for 48 hours

  • Treat with IL-1β (0.1 ng/mL is typically effective) for 24 hours

  • Include appropriate controls (untreated, other cytokines like IL8/CXCL8 at 10 ng/mL)

• Detection approach:

  • Process cells for flow cytometry using FITC-conjugated PTGS2 antibodies

  • Analyze median fluorescence intensity as a measure of PTGS2 expression

  • Alternatively, prepare lysates for Western blotting to quantify total PTGS2 protein

• Validation strategies:

  • Confirm IL-1β specificity using neutralizing antibodies or receptor antagonists

  • Use PTGS2 inhibitors (e.g., NS398) as negative controls

  • Perform dose-response and time-course studies to characterize induction kinetics

Note: Table represents typical response patterns based on research literature

What steps should be taken when FITC-conjugated PTGS2 antibody shows weak or no signal?

When encountering weak signals with FITC-conjugated PTGS2 antibodies:

• Evaluate antibody viability:

  • Check storage conditions (light exposure, temperature fluctuations)

  • Verify expiration date

  • Test antibody using a known positive control

• Optimize protocol parameters:

  • Increase antibody concentration (titrate from 1:100 to 1:50 or higher)

  • Extend incubation time (4°C overnight instead of 1-2 hours)

  • Improve permeabilization for intracellular targets

  • Optimize fixation (overfixation can mask epitopes)

• Enhance detection sensitivity:

  • Use higher gain settings on flow cytometer/microscope

  • Apply signal amplification methods

  • Reduce background with additional blocking steps

• Consider target expression levels:

  • Stimulate cells with IL-1β (0.1 ng/mL for 24h) to induce PTGS2 expression

  • Verify PTGS2 expression using alternative methods (qPCR, Western blot)

How can I resolve high background issues when using FITC-conjugated PTGS2 antibodies in tissue sections?

High background is a common challenge with fluorescent antibodies in tissue sections. To address this:

• Implement rigorous blocking:

  • Use 5-10% serum from the same species as the secondary antibody

  • Add 0.1-0.3% Triton X-100 for permeabilization

  • Include background-reducing agents (e.g., 0.1% BSA, 0.05% Tween-20)

• Optimize antibody dilution:

  • Perform titration experiments to identify optimal antibody concentration

  • Test dilutions ranging from 1:50 to 1:500

• Reduce autofluorescence:

  • Treat sections with Sudan Black B (0.1-0.3% in 70% ethanol)

  • Apply copper sulfate solution (10mM in 50mM ammonium acetate buffer)

  • Use commercial autofluorescence quenchers

• Improve washing procedures:

  • Increase wash duration and frequency

  • Use PBS with 0.05-0.1% Tween-20

  • Perform washes on orbital shaker

The specificity of PTGS2 antibodies is crucial, as research shows they do not cross-react with COX-1, ensuring specific detection of PTGS2 protein .

What are effective strategies for analyzing PTGS2 expression heterogeneity in tumor samples using FITC-conjugated antibodies?

Tumor heterogeneity presents unique challenges for PTGS2 analysis. Effective strategies include:

• Spatial analysis approaches:

  • Implement whole-slide imaging to capture entire tissue sections

  • Use computational segmentation to distinguish tumor from stromal regions

  • Apply hot-spot analysis to identify regions of highest PTGS2 expression

• Heterogeneity quantification methods:

  • Calculate coefficients of variation across multiple regions

  • Apply spatial statistics (Moran's I, Geary's C) to characterize distribution patterns

  • Use H-score methodology, considering both intensity and percentage of positive cells

• Multi-parameter analysis:

  • Combine PTGS2-FITC with markers for specific cell populations

  • Include proliferation markers to correlate with tumor aggressiveness

  • Incorporate hypoxia markers to evaluate microenvironmental influence

• Validation approaches:

  • Compare findings across multiple tumor regions

  • Correlate with RNA expression data from microdissected regions

  • Validate with alternative detection methods (e.g., RNAscope)

Research has demonstrated that the correlation coefficient of tumor PTGS2 compared with stromal PTGS2 was 0.334 (Spearman's rank, p < 0.001), suggesting distinct mechanisms of PTGS2 induction in different cell populations within the same sample .

How should PTGS2 expression data be normalized for comparative analysis across different experimental conditions?

Proper normalization is essential for valid comparisons of PTGS2 expression:

• Western blot quantification:

  • Normalize to housekeeping proteins (β-actin, GAPDH, β-tubulin)

  • Use total protein normalization methods (Ponceau S, REVERT staining)

  • Include recombinant PTGS2 protein standards for absolute quantification

• Flow cytometry analysis:

  • Normalize to isotype control (matched IgG-FITC)

  • Calculate fold change relative to unstimulated controls

  • Use standardized beads to calibrate fluorescence intensity

• Immunohistochemistry/immunofluorescence:

  • Score relative to internal positive controls

  • Implement digital pathology algorithms for consistent quantification

  • Consider ratio of tumor to stromal expression for comprehensive evaluation

• qPCR validation:

  • Use multiple reference genes validated for stability in your experimental system

  • Apply geometric averaging of multiple reference genes (GeNorm approach)

  • Calculate relative expression using the 2^-ΔΔCt method

Research has demonstrated that gPTGS2 can be reliably quantified in tissue lysates with high sensitivity, showing nearly undetectable levels in normal mucosa (median = 0.00 pg) compared to significant expression in colorectal cancer tissues (median = 156.86 pg) .

What statistical approaches are most appropriate for analyzing PTGS2 expression correlation with clinical outcomes?

For correlating PTGS2 expression with clinical outcomes:

• Univariate analyses:

  • Kaplan-Meier survival analysis with log-rank test for time-to-event outcomes

  • Cox proportional hazards models for calculating hazard ratios

  • ROC curve analysis to determine optimal cutoff values for PTGS2 expression

• Multivariate analyses:

  • Multiple Cox regression incorporating established prognostic factors

  • Propensity score matching to reduce confounding

  • Competing risk analysis when multiple outcome events are possible

• Advanced modeling approaches:

  • Machine learning algorithms for pattern recognition

  • Random forest models for identifying variable importance

  • Nomogram development to predict individual patient outcomes

• Validation strategies:

  • Internal validation using bootstrap or cross-validation

  • External validation with independent patient cohorts

  • Time-dependent ROC curves to assess predictive accuracy

Research has identified PTGS2 as a potential biomarker for arteriovenous fistulas failure through WGCNA analysis, suggesting its utility in predicting clinical outcomes .

How can I develop a multiplex flow cytometry panel incorporating FITC-conjugated PTGS2 antibody for comprehensive immune cell phenotyping?

Developing a comprehensive multiplex flow cytometry panel requires:

• Strategic panel design:

  • Assign FITC to PTGS2 based on expected expression level (reserve brighter fluorophores for lower-expressed targets)

  • Select compatible fluorophores with minimal spectral overlap

  • Include markers for major immune cell populations (CD3, CD4, CD8, CD19, CD14, CD56)

  • Add activation/functional markers (HLA-DR, CD69, cytokines)

• Optimization steps:

  • Perform single-stain controls for compensation

  • Titrate each antibody individually

  • Test fluorescence minus one (FMO) controls

  • Validate on known positive and negative populations

• Analysis strategy:

  • Implement hierarchical gating to identify major populations

  • Use dimensionality reduction techniques (tSNE, UMAP) for visualization

  • Apply clustering algorithms to identify novel PTGS2+ subpopulations

  • Correlate PTGS2 expression with functional parameters

• Quality control measures:

  • Include viability dye to exclude dead cells

  • Monitor instrument performance with tracking beads

  • Standardize protocols for consistent results across experiments

How can PTGS2 antibodies be used to evaluate the efficacy of cyclooxygenase inhibitors in preclinical models?

PTGS2 antibodies provide valuable tools for evaluating COX inhibitor efficacy:

• Experimental design approach:

  • Establish baseline PTGS2 expression in target tissues/cells

  • Administer COX inhibitors at various doses and durations

  • Include selective (e.g., NS398) and non-selective inhibitors for comparison

  • Collect samples at strategic timepoints to assess acute and chronic effects

• Readout parameters:

  • Measure PTGS2 protein levels by Western blot or flow cytometry

  • Assess prostaglandin production by ELISA or mass spectrometry

  • Evaluate downstream signaling pathway activation

  • Monitor phenotypic changes (inflammation, cell proliferation)

• In vivo model considerations:

  • Use FITC-conjugated antibodies for flow cytometry of dissociated tissues

  • Perform ex vivo imaging of intact tissues

  • Consider pharmacokinetic/pharmacodynamic relationships

  • Correlate PTGS2 inhibition with physiological outcomes

Research has shown that NS398, a PTGS2 inhibitor, affects hemodynamics, smooth muscle cell proliferation, migration, and oxidative stress in mouse arteriovenous fistula models, demonstrating the utility of these approaches .

What are the key considerations when designing experiments to investigate the relationship between PTGS2 expression and macrophage polarization?

Investigating PTGS2 in macrophage polarization requires:

• Macrophage polarization protocol:

  • Derive macrophages from primary monocytes or cell lines

  • Induce M1 polarization (IFN-γ + LPS) and M2 polarization (IL-4 + IL-13)

  • Include unstimulated (M0) macrophages as baseline controls

  • Validate polarization with established markers (CD80/CD86 for M1; CD163/CD206 for M2)

• PTGS2 assessment strategy:

  • Use FITC-conjugated PTGS2 antibodies for flow cytometry

  • Perform time-course analysis to track expression dynamics

  • Quantify both percentage of positive cells and expression intensity

  • Correlate with functional readouts (cytokine production, phagocytic activity)

• Mechanistic investigations:

  • Apply selective PTGS2 inhibitors to determine functional consequences

  • Use siRNA/shRNA approaches for genetic validation

  • Rescue experiments with prostaglandin supplementation

  • Investigate upstream regulators and downstream effectors

Research has revealed correlations between PTGS2 and macrophage markers (CD68, CD163) in colorectal cancer tissues, with Pearson correlation coefficients of 0.422 and 0.316 respectively, supporting the biological relevance of these investigations .

How can FITC-conjugated PTGS2 antibodies be integrated into live-cell imaging studies to monitor dynamic regulation of PTGS2 expression?

Integrating FITC-conjugated PTGS2 antibodies into live-cell imaging requires:

• Cell preparation considerations:

  • Use membrane-permeabilizing agents that maintain cell viability

  • Consider chimeric antibody fragments with enhanced cell penetration

  • Optimize antibody concentration to minimize potential functional interference

  • Implement nuclear or membrane staining for cell identification

• Imaging parameters:

  • Use spinning disk or light sheet microscopy for reduced phototoxicity

  • Establish minimal laser power settings that maintain adequate signal-to-noise ratio

  • Implement environmental controls (temperature, CO2, humidity)

  • Design time-lapse intervals to capture relevant dynamics while minimizing exposure

• Analysis approaches:

  • Track single-cell PTGS2 expression over time

  • Correlate with morphological changes or co-expressed markers

  • Implement automated image analysis pipelines for unbiased quantification

  • Use photobleaching correction algorithms for extended imaging sessions

• Validation strategies:

  • Compare with fixed-time point analyses

  • Confirm specificity with PTGS2 knockout controls

  • Verify that antibody binding doesn't alter normal PTGS2 function

  • Correlate imaging results with biochemical assays