CBL9 Antibody

What is CA9 and why is it significant in cancer research?

Carbonic Anhydrase IX (CA9) catalyzes the reversible reaction of CO₂ + H₂O = HCO₃⁻ + H⁺, which is fundamental to many physiological processes including respiration, renal tubular acidification, and bone resorption . In cancer research, CA9 is particularly significant because:

• It is predominantly expressed in carcinoma cells under hypoxic conditions

• It serves as one of the most reliable markers for hypoxia in solid tumors

• It is strongly associated with renal cell carcinoma (RCC), making it valuable for diagnostic applications

• Its expression correlates with tumor aggressiveness and poor prognosis in several cancer types

What are the available formats of CA9 antibodies for research applications?

Several formats of CA9 antibodies are available for different research applications:

• Monoclonal antibodies (e.g., Clone #303123) for consistent results across experiments

• PE-conjugated antibodies optimized for flow cytometry applications

• Unconjugated antibodies (e.g., #MAB21881) suitable for various applications including immunohistochemistry and Western blotting

• Antibodies targeting specific epitopes within the CA9 protein (Pro59-Asp414 region is common)

The selection of format depends on the specific experimental requirements, target cell types, and detection methods employed.

How to validate CA9 antibody specificity before experimental use?

Validating antibody specificity is crucial for reliable results:

• Confirm recognition of target protein via direct ELISAs with recombinant CA9

• Test for cross-reactivity with related proteins (e.g., other carbonic anhydrase family members)

• Include appropriate isotype controls in flow cytometry experiments (e.g., Catalog # IC003P as used for CA9 PE-conjugated antibody)

• Validate using cell lines with known CA9 expression patterns (e.g., U-87 MG human glioblastoma cells)

• Consider western blot analysis to confirm binding to protein of correct molecular weight

What are the optimal protocols for CA9 detection in flow cytometry?

For optimal flow cytometry detection of CA9:

• Harvest cells using non-enzymatic dissociation methods when possible to preserve membrane proteins

• Resuspend cells at concentration of 1 × 10^6 cells/mL in flow cytometry buffer

• Use appropriate antibody dilutions (determined through titration experiments)

• Include proper controls: unstained cells, isotype control (e.g., Catalog # IC003P for PE-conjugated antibodies)

• Analyze using appropriate laser and filter combinations (for PE-conjugated antibodies: 488 nm excitation, 575 nm emission filter)

• Follow manufacturer's staining protocol for membrane-associated proteins

The U-87 MG human glioblastoma/astrocytoma cell line has been validated for CA9 detection by flow cytometry and can serve as a positive control for protocol optimization .

How can CA9 antibodies be integrated into immunotherapy research?

CA9 antibodies have multiple applications in immunotherapy research:

• Development of dual-antigen T cell engagers targeting CA9 for solid tumors

• Creation of adenovirus-based immune checkpoint vaccines that elicit anti-tumor effects in renal carcinoma

• Design of DC vaccines incorporating CA9 targeting to induce dual-targeting CTLs

• Enhancement of conditionally replicative adenovirus effects through CAIX promoter control

When designing such experiments, researchers should:

• Validate antibody binding to native CA9 on target cells

• Ensure antibody cross-reactivity is considered if using animal models

• Test antibody function in the specific immunotherapeutic format before proceeding to complex experiments

What computational approaches can improve CA9 antibody specificity design?

Recent advances in computational modeling offer powerful tools for antibody design:

• Biophysics-informed models can be trained on experimentally selected antibodies to associate distinct binding modes with specific ligands

• High-throughput sequencing combined with machine learning enables prediction beyond experimentally observed sequences

• Counter-selection computational approaches can efficiently eliminate off-target antibodies

• Models can disentangle different binding contributions from a single experiment, allowing discrimination between closely related ligands

The integration of these computational methods with phage display experiments has demonstrated the ability to design antibodies with customized specificity profiles, either with specific high affinity for particular target ligands or with cross-specificity for multiple target ligands .

How do different selection strategies affect CA9 antibody development?

Selection strategies significantly impact antibody development outcomes:

• Phage Display Selection: Enables screening of large antibody libraries against immobilized targets

  • Can involve multiple rounds with amplification between rounds

  • Pre-selection steps help deplete binders to unwanted targets

  • Sequencing before and after each selection round provides valuable data for computational modeling

• Negative Selection: Critical for developing highly specific antibodies

  • Pre-incubation with structurally similar proteins removes cross-reactive antibodies

  • Computational approaches can enhance this process beyond traditional experimental methods

• Parameterized Models: Allow for customized antibody design

  • Energy functions associated with each binding mode can be optimized

  • For cross-specific antibodies: jointly minimize functions for desired ligands

  • For specific antibodies: minimize function for desired ligand while maximizing for undesired ligands

How to address discrepancies in CA9 detection across different applications?

When facing inconsistent CA9 detection results:

• Epitope Accessibility Issues:

  • CA9 is a transmembrane protein; epitope masking may occur in certain applications

  • Solution: Try antibodies targeting different epitopes of CA9

  • For fixed samples, optimize antigen retrieval methods

• Expression Level Variations:

  • CA9 expression is highly influenced by hypoxia

  • Solution: Standardize culture conditions and oxygen levels

  • Consider using hypoxia-mimicking agents (e.g., CoCl₂) for positive controls

• Sample Preparation Effects:

  • Different fixation methods may affect epitope recognition

  • Solution: Compare multiple fixation protocols

  • Test both cell surface and intracellular staining protocols for flow cytometry

• Detection Method Sensitivity:

  • Flow cytometry typically offers higher sensitivity than immunohistochemistry

  • Solution: Adjust antibody concentration based on application

  • Consider signal amplification methods for less sensitive applications

What data analysis approaches are recommended for CA9 quantification?

For robust CA9 quantification in research settings:

• Flow Cytometry Analysis:

  • Report both percentage of positive cells and median fluorescence intensity

  • Use appropriate gating strategies based on isotype controls

  • Consider ratio of signal to background for more accurate comparisons between samples

• Image-Based Analysis:

  • Employ digital image analysis software for objective quantification

  • Use intensity thresholding based on negative controls

  • Consider analysis of subcellular localization patterns

• Expression Correlation Studies:

  • Correlate CA9 levels with other hypoxia markers (e.g., HIF-1α)

  • Assess relationship between CA9 expression and clinical parameters

  • Use appropriate statistical methods based on data distribution

Antibody Cross-Reactivity Profile

Note: Cross-reactivity testing performed via direct ELISA

CA9 Antibody Applications in Research