PRTN3 Antibody, FITC conjugated

What is PRTN3 and why is it significant in research?

PRTN3 (Proteinase 3) is a serine protease also known as Myeloblastin (EC 3.4.21.76), AGP7, C-ANCA antigen, Leukocyte proteinase 3, Neutrophil proteinase 4, and Wegener autoantigen. This protein is stored in its active form within neutrophil azurophilic granules and plays a significant role in regulating inflammation . Recent studies have identified PRTN3 as an important target for anti-neutrophil cytoplasmic autoantibody, and it has been found to be overexpressed in early-stage cancers, particularly lung adenocarcinoma (LUAD) . Its research significance extends beyond inflammatory diseases to cancer biomarker development, making it a versatile target for immunological investigations.

What are the key specifications of PRTN3 antibody, FITC conjugated?

The PRTN3 antibody, FITC conjugated, is a polyclonal antibody produced in rabbits against recombinant Human Myeloblastin protein (amino acids 1-170) . Its key specifications include:

The FITC conjugation enables direct fluorescent detection in various applications, eliminating the need for secondary antibodies in certain experimental protocols .

How should PRTN3 antibody be stored and handled to maintain optimal activity?

For optimal maintenance of PRTN3 antibody activity, proper storage and handling are crucial. Upon receipt, the antibody should be stored at -20°C or -80°C . It's supplied in liquid form in a buffer containing 50% glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative . Researchers should strictly avoid repeated freeze-thaw cycles as these can degrade antibody performance and reduce specificity.

When handling the antibody, maintain sterile conditions and use appropriate personal protective equipment. Before each use, allow the antibody to equilibrate to room temperature and gently mix by inversion rather than vortexing to prevent protein denaturation. For long-term experiments, consider aliquoting the stock solution into smaller volumes to minimize freeze-thaw cycles. Documentation of lot numbers and expiration dates is advisable for experimental reproducibility and troubleshooting.

How can PRTN3 antibody be utilized for studying lung adenocarcinoma biomarkers?

Recent research has demonstrated that PRTN3 protein is significantly overexpressed in lung adenocarcinoma (LUAD) tissues compared to normal or para-carcinoma tissues (P < 0.0001) . This makes PRTN3 antibodies valuable tools for studying LUAD biomarkers.

To utilize PRTN3 antibody for LUAD biomarker research, researchers can employ multiple methodologies:

• Immunohistochemistry (IHC): PRTN3 antibody can be used to detect and quantify PRTN3 expression in LUAD tissue arrays. Studies have shown that PRTN3 expression positively correlates with pathological grade, with stronger expression observed in G2 and G3 LUAD tissues compared to G1 and normal tissues .

• Immunofluorescence (IF) staining: PRTN3 antibody conjugated with FITC enables direct visualization of PRTN3 in LUAD cells. Research has confirmed PRTN3 presence throughout A549 cells and in the cytoplasm of H1299 cells .

• Western blotting: PRTN3 antibody can verify the presence of PRTN3 in cell lysates or recombinant proteins. This technique has been used to confirm plasma immune responses to PRTN3 in LUAD patients .

• ELISA development: For the detection of anti-PRTN3 autoantibodies in patient plasma, recombinant PRTN3 can be coated on plates, and FITC-conjugated antibodies can serve as positive controls in assay development .

These applications support the emerging role of anti-PRTN3 autoantibodies as potential early biomarkers for distinguishing LUAD from normal controls and benign pulmonary nodules, with significant diagnostic value (AUC = 0.782 for early LUAD from normal controls) .

What methodological approaches can be used for combining anti-PRTN3 autoantibody detection with conventional tumor markers?

Combining anti-PRTN3 autoantibody detection with conventional tumor markers like CEA (carcinoembryonic antigen) significantly improves diagnostic accuracy for conditions like lung adenocarcinoma. The methodological approach requires several key steps:

• Sample collection standardization: Collect plasma samples from patients with early- and advanced-stage LUAD, benign pulmonary nodules (BPN), and normal controls (NC) following standardized protocols to ensure consistency.

• ELISA optimization:

  • Coat ELISA plates with purified recombinant PRTN3 protein

  • Use FITC-conjugated PRTN3 antibody as a positive control

  • Develop parallel assays for detecting both IgG and IgM anti-PRTN3 autoantibodies

  • Include CEA quantification for the same samples

• Statistical integration:

  • Apply binary logistic regression to combine anti-PRTN3 IgG, IgM autoantibodies, and CEA measurements

  • Calculate AUC values for different diagnostic combinations

Research has demonstrated that while CEA alone showed limited diagnostic value for early LUAD (AUC = 0.524, 95% CI: 0.445-0.603), the combination with anti-PRTN3 IgG and IgM autoantibodies significantly improved diagnostic performance (AUC = 0.778, 95% CI: 0.716-0.839) . This methodological approach enhances the capability to distinguish early LUAD from both normal controls and benign pulmonary nodules, addressing a critical clinical need for early cancer detection.

How does PRTN3 antibody perform in different research applications compared to other neutrophil markers?

PRTN3 antibody offers unique advantages in various research applications compared to other neutrophil markers. While many neutrophil markers like myeloperoxidase (MPO) and elastase are widely used, PRTN3 has shown particular value in cancer research and autoimmune disease investigations.

In immunofluorescence applications, FITC-conjugated PRTN3 antibody provides direct visualization capabilities without requiring secondary antibodies, enabling more straightforward multiplexing with other markers . When used in lung adenocarcinoma research, anti-PRTN3 autoantibody detection has demonstrated superior diagnostic performance compared to conventional tumor markers like CEA .

What are the optimal conditions for using PRTN3 antibody in immunofluorescence studies?

For optimal immunofluorescence studies using FITC-conjugated PRTN3 antibody, implement the following protocol:

• Cell preparation:

  • Culture target cells (e.g., A549 or H1299 for lung cancer studies) on glass coverslips to 70-80% confluency

  • Fix cells with 4% paraformaldehyde for 15 minutes at room temperature

  • Permeabilize with 0.1% Triton X-100 for 10 minutes if intracellular staining is required

• Blocking and antibody incubation:

  • Block with 5% normal serum in PBS for 1 hour at room temperature

  • Dilute FITC-conjugated PRTN3 antibody to the optimal working concentration (typically 1:50 to 1:200, requiring optimization for each lot)

  • Incubate cells with diluted antibody for 1-2 hours at room temperature or overnight at 4°C in a humidified chamber protected from light

• Nuclear counterstaining and mounting:

  • Counterstain nuclei with DAPI (1:1000) for 5 minutes

  • Mount coverslips using anti-fade mounting medium

• Controls and validation:

  • Include positive control cells known to express PRTN3 (neutrophils or LUAD cell lines)

  • Include negative controls omitting primary antibody

  • For specificity validation, perform preabsorption experiments by incubating the antibody with recombinant PRTN3 before staining

Research has shown that in A549 cells, PRTN3 staining appears throughout the entire cell, while in H1299 cells, PRTN3 predominantly localizes to the cytoplasm . When LUAD plasma containing anti-PRTN3 autoantibodies was preabsorbed with recombinant PRTN3, immunofluorescence signals significantly decreased, confirming specificity .

How should researchers optimize ELISA protocols for detecting anti-PRTN3 autoantibodies?

Optimizing ELISA protocols for detecting anti-PRTN3 autoantibodies requires careful attention to multiple parameters:

• Antigen coating optimization:

  • Determine optimal coating concentration of recombinant PRTN3 protein (typically 1-5 μg/ml)

  • Evaluate different coating buffers (carbonate buffer pH 9.6 vs. PBS pH 7.4)

  • Test coating times and temperatures (overnight at 4°C vs. 2 hours at 37°C)

• Sample preparation:

  • Standardize plasma/serum dilution (start with 1:100 and titrate as needed)

  • Compare fresh vs. frozen samples to assess stability

  • Consider adding blocking agents to sample diluent to reduce background

• Detection system optimization:

  • For IgG detection: Test different anti-human IgG secondary antibodies

  • For IgM detection: Evaluate specific anti-human IgM secondary antibodies

  • When using FITC-conjugated PRTN3 antibody as a positive control, determine appropriate dilution series

• Validation and standardization:

  • Include PRTN3 antibody as a positive control for standard curve generation

  • Use samples from confirmed LUAD, BPN, and normal controls for threshold determination

  • Calculate intra-assay and inter-assay coefficients of variation (target CV < 10%)

Research has demonstrated that optimized anti-PRTN3 autoantibody ELISA can achieve significant diagnostic value, with AUC values of 0.782 (95% CI: 0.739-0.825) for distinguishing early LUAD from normal controls and 0.761 (95% CI: 0.715-0.807) for differentiating early LUAD from benign pulmonary nodules . These metrics establish clear benchmarks for protocol optimization.

What experimental controls are critical when using PRTN3 antibody in Western blotting?

When performing Western blotting with PRTN3 antibody, implementing appropriate controls is essential for result validation and troubleshooting:

• Positive controls:

  • Recombinant PRTN3 protein at known concentrations (1-10 ng)

  • Commercially available monoclonal anti-PRTN3 antibody as reference standard

  • Neutrophil lysates or LUAD cell lines (A549, H1299) known to express PRTN3

• Negative controls:

  • Cell lines lacking PRTN3 expression

  • Primary antibody omission control (apply only secondary antibody)

  • Isotype control (irrelevant antibody of same isotype)

• Specificity validation controls:

  • Peptide competition assay: Pre-incubate PRTN3 antibody with excess recombinant PRTN3 protein before blotting

  • Compare different PRTN3 antibody clones targeting different epitopes

  • For FITC-conjugated antibodies, include appropriate fluorescence detection controls

• Loading and transfer controls:

  • Housekeeping protein detection (β-actin, GAPDH)

  • Total protein staining (Ponceau S, SYPRO Ruby)

  • Transfer efficiency verification with prestained molecular weight markers

Research has shown that when performing Western blotting for detecting anti-PRTN3 autoantibodies in plasma samples, the inclusion of monoclonal anti-PRTN3 antibody as a positive control is critical for quality control purposes . This approach has successfully demonstrated significantly stronger reactions to PRTN3 recombinant protein in plasma samples from LUAD patients compared to those from BPN patients and normal controls .

How can researchers troubleshoot weak or non-specific signals when using FITC-conjugated PRTN3 antibody?

When encountering weak or non-specific signals with FITC-conjugated PRTN3 antibody, implement the following systematic troubleshooting approach:

• Addressing weak signal issues:

  • Verify antibody concentration and consider increasing concentration within manufacturer's recommended range

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

  • Check for FITC photobleaching; minimize exposure to light during all procedures

  • Verify storage conditions and potential antibody degradation (avoid repeated freeze-thaw cycles)

  • For flow cytometry or microscopy, adjust gain/PMT/exposure settings

• Resolving non-specific signal problems:

  • Optimize blocking conditions (increase blocking agent concentration or time)

  • Add 0.1-0.5% detergent (Tween-20 or Triton X-100) to washing buffers

  • Filter buffers to remove particles that might cause autofluorescence

  • Use longer/more frequent washing steps

  • Prepare fresh fixative solutions to reduce autofluorescence

• Verification and controls:

  • Perform antibody titration to identify optimal signal-to-noise ratio

  • Include cellular autofluorescence controls (unstained cells)

  • Conduct preabsorption experiments with recombinant PRTN3 protein

  • Compare staining patterns with published results (cytoplasmic in H1299 cells vs. whole-cell distribution in A549 cells)

• Technical considerations:

  • For microscopy, verify filter sets are appropriate for FITC detection (excitation ~495 nm, emission ~520 nm)

  • Use antifade mounting media to preserve fluorescence

  • Consider spectral overlap if multiplexing with other fluorophores

Research has demonstrated that preabsorption of LUAD plasma with recombinant PRTN3 significantly reduced IF signals in LUAD cells, confirming specific binding . This approach can help distinguish between specific and non-specific signals when troubleshooting immunofluorescence experiments.

What statistical approaches are recommended for analyzing anti-PRTN3 autoantibody data in biomarker studies?

For robust analysis of anti-PRTN3 autoantibody data in biomarker studies, researchers should implement the following statistical approaches:

• Descriptive statistics and normality testing:

  • Calculate means, medians, standard deviations, and interquartile ranges

  • Test for normal distribution using Shapiro-Wilk or Kolmogorov-Smirnov tests

  • Apply appropriate transformations (log, square root) if data is not normally distributed

• Comparative analyses:

  • For normally distributed data: Use Student's t-test (two groups) or ANOVA (multiple groups)

  • For non-parametric data: Use Mann-Whitney U test (two groups) or Kruskal-Wallis test (multiple groups)

  • Apply Bonferroni or False Discovery Rate corrections for multiple comparisons

• Diagnostic performance assessment:

  • Generate Receiver Operating Characteristic (ROC) curves

  • Calculate Area Under the Curve (AUC) with 95% confidence intervals

  • Determine optimal cutoff values using Youden's index

  • Calculate sensitivity, specificity, positive and negative predictive values

• Multivariate approaches:

  • Apply binary logistic regression to combine multiple biomarkers (e.g., anti-PRTN3 IgG, IgM, and CEA)

  • Perform principal component analysis or factor analysis to identify patterns

  • Consider machine learning approaches for complex biomarker panels

In published research, binary logistic regression successfully combined anti-PRTN3 IgG and IgM autoantibodies with CEA, achieving an AUC of 0.783 (95% CI: 0.730-0.835) for distinguishing LUAD from normal controls, significantly improving upon CEA's performance alone (AUC = 0.540) . For early LUAD diagnosis, this statistical approach increased diagnostic performance from an AUC of 0.524 to 0.778 , demonstrating the value of appropriate statistical integration methods.

How can researchers interpret discrepancies between IgG and IgM anti-PRTN3 autoantibody profiles?

When interpreting discrepancies between IgG and IgM anti-PRTN3 autoantibody profiles, researchers should consider several biological and methodological factors:

• Immunological time course interpretation:

  • IgM antibodies typically appear first in an immune response and gradually decrease as IgG antibodies develop

  • Lower diagnostic value of IgM compared to IgG antibodies may reflect this temporal relationship in the immune response

  • IgM production is often reduced during the development of an IgG response and plays a less prominent role in long-term immunity

• Disease specificity analysis:

  • Anti-PRTN3 IgG autoantibodies have been found to be elevated in both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC)

  • Anti-PRTN3 IgM autoantibodies appear to be more specific to LUAD, enabling differentiation between LUAD and LUSC (AUC = 0.651)

  • These differences can inform diagnostic strategy design for different cancer subtypes

• Technical considerations:

  • Verify detection antibody specificity (anti-human IgG vs. anti-human IgM)

  • Evaluate potential cross-reactivity between detection systems

  • Consider different optimal dilutions for IgG versus IgM detection (IgM may require lower dilutions)

• Clinical correlation:

  • Correlate discrepancies with clinical parameters (disease stage, treatment response)

  • Analyze longitudinal samples when available to track isotype evolution

  • Stratify results by patient demographics and risk factors

By systematically analyzing these factors, researchers can gain insights into the biological significance of isotype-specific immune responses to PRTN3. The observed differences between IgG and IgM antibodies may reflect not only technical variabilities but also meaningful biological distinctions in cancer-associated immune responses.

What are the emerging applications of PRTN3 antibodies in cancer immunotherapy research?

PRTN3 antibodies are emerging as valuable tools in cancer immunotherapy research, with several promising directions:

• Chimeric Antigen Receptor (CAR) T-cell development:

  • PRTN3's differential expression in cancer tissues, particularly lung adenocarcinoma, makes it a potential target for CAR-T therapy

  • FITC-conjugated PRTN3 antibodies can facilitate cell sorting and enrichment during CAR-T manufacturing

  • Epitope mapping using different PRTN3 antibody clones helps identify optimal target regions for CAR design

• Antibody-drug conjugate (ADC) development:

  • High PRTN3 expression in LUAD tissues supports its potential as an ADC target

  • PRTN3 antibodies can be conjugated to cytotoxic payloads for targeted drug delivery

  • FITC-conjugated antibodies provide a platform for proof-of-concept studies on internalization kinetics

• Immune checkpoint modulation:

  • Investigating interactions between PRTN3 and tumor immune microenvironment

  • Studying whether anti-PRTN3 autoantibodies affect natural killer cell or macrophage activity

  • Exploring combination approaches with established checkpoint inhibitors

• Liquid biopsy enhancement:

  • Integrating anti-PRTN3 autoantibody detection with circulating tumor DNA analysis

  • Developing multiplexed detection platforms combining anti-PRTN3 with other autoantibodies

  • Using machine learning algorithms to enhance diagnostic accuracy of combined biomarker panels

The significantly improved diagnostic performance when combining anti-PRTN3 autoantibodies with conventional tumor markers (increasing AUC from 0.524 to 0.778 for early LUAD diagnosis) suggests that integrated approaches will be particularly valuable for advancing cancer immunotherapy research and improving early detection capabilities.

How might standardization of PRTN3 antibody applications enhance multi-center research collaboration?

Standardization of PRTN3 antibody applications across research institutions would significantly enhance multi-center collaboration through several mechanisms:

• Reference material and calibration standardization:

  • Establish international reference preparations of recombinant PRTN3 protein

  • Develop calibrated positive control antibodies with defined binding characteristics

  • Create standardized protocols for antibody titration and validation

• Assay harmonization protocols:

  • Implement detailed standard operating procedures (SOPs) for:

    • ELISA protocols with defined cutoff determination methods

    • Immunofluorescence staining with standardized image acquisition parameters

    • Western blotting with consistent sample preparation and loading controls

  • Define acceptable ranges for assay performance metrics (CVs, signal-to-noise ratios)

• Data reporting and interpretation frameworks:

  • Adopt consistent statistical methodologies for ROC analysis and cutoff determination

  • Implement standardized reporting formats for sensitivity, specificity, and AUC values

  • Establish common definitions for assay positivity and borderline results

• Quality assurance programs:

  • Develop external quality assessment (EQA) schemes for anti-PRTN3 antibody testing

  • Implement proficiency testing for laboratories participating in multi-center studies

  • Create biorepositories of reference samples representing diverse patient populations

What novel technical approaches might enhance PRTN3 detection sensitivity in challenging samples?

Enhancing PRTN3 detection sensitivity in challenging samples requires innovative technical approaches that overcome current limitations:

• Signal amplification strategies:

  • Tyramide signal amplification (TSA) for immunohistochemistry and immunofluorescence applications

  • Poly-HRP conjugated detection systems for ELISA and Western blotting

  • Quantum dot conjugation of antibodies for enhanced photostability and brightness

  • Digital ELISA platforms (e.g., Single Molecule Array technology) for ultra-sensitive protein detection

• Sample preparation optimization:

  • Selective enrichment of PRTN3-expressing cells from heterogeneous populations

  • Affinity purification of PRTN3 from complex biological samples

  • Optimized fixation protocols preserving epitope accessibility while reducing autofluorescence

  • Removal of interfering substances through specific pre-treatment methods

• Advanced imaging and detection technologies:

  • Super-resolution microscopy for detailed subcellular localization

  • Multiplex immunofluorescence combining PRTN3 with other biomarkers

  • Mass cytometry (CyTOF) for single-cell proteomics including PRTN3 detection

  • Proximity ligation assay (PLA) for detecting PRTN3 protein-protein interactions

• Computational and analytical enhancements:

  • Machine learning algorithms for automated image analysis and signal quantification

  • Deconvolution algorithms for improved signal-to-noise ratio

  • Multivariate data integration combining PRTN3 with complementary biomarkers

  • Bayesian statistical approaches for improved diagnostic accuracy