CD36 Mouse

What is the CD36 humanized mouse model and how does it differ from wild-type mice?

The CD36 humanized (hCD36) mouse model is a genetically engineered strain where the sequences encoding the extracellular domains of the mouse Cd36 gene (specifically exons 4 to part of 15) are replaced with the corresponding human sequences (exons 3 to 14). This model expresses only human CD36 protein and not mouse CD36, while maintaining the normal distribution of lymphocyte subpopulations compared to wild-type mice .

The replacement methodology specifically targets the extracellular domains that are responsible for ligand recognition while maintaining the transmembrane and cytoplasmic domains of the mouse origin. This strategic design allows for human-specific antibody binding while preserving mouse-specific intracellular signaling pathways .

What are the main applications of CD36 mouse models in cancer research?

CD36 mouse models serve several critical functions in cancer research:

• Preclinical evaluation of immunotherapies: The humanized CD36 mouse model provides a validated platform for testing CD36-targeting antibodies and their efficacy in tumor growth inhibition .

• Mechanism studies: These models help investigate how CD36 participates in tumor immunity, metastatic invasion, and therapy resistance through various molecular mechanisms .

• Drug development pipeline: They bridge the gap between in vitro studies and clinical trials, allowing for assessment of pharmacodynamics, toxicology, and target validation .

• Metabolic pathway investigation: CD36's dual role in signaling and fatty acid transport makes these models valuable for studying how metabolic pathways influence tumor progression .

Data from these models has demonstrated that CD36-targeting antibodies can significantly inhibit tumor growth in colon cancer models, validating CD36 as a therapeutic target .

How does CD36 function as both a signaling receptor and a fatty acid transporter?

CD36 exhibits dual functionality that integrates cellular signaling and metabolism:

• As a signaling receptor: CD36 responds to damage-associated molecular patterns (DAMPs) and pathogen-associated molecular patterns (PAMPs), initiating signal transduction cascades that influence cellular responses. This signaling function is particularly important in immune cells like macrophages and T cells .

• As a fatty acid transporter: CD36 facilitates the uptake of long-chain fatty acids across the plasma membrane, influencing cellular metabolism. This function is critical in cells that rely heavily on fatty acid metabolism, such as macrophages, T cells, adipocytes, and cancer cells .

These dual functions allow CD36 to integrate metabolic states with immune cell activation and differentiation. For example, in tumor microenvironments, CD36-mediated fatty acid uptake can influence macrophage polarization and T cell function, thereby affecting anti-tumor immunity .

What are the key considerations when designing experiments with CD36 humanized mice?

When designing experiments with CD36 humanized mice, researchers should consider:

• Genetic background verification: Confirm the genotype of mice through PCR and sequencing to ensure proper humanization of the CD36 gene .

• Expression validation: Verify human CD36 expression at both mRNA and protein levels in relevant tissues (e.g., lung, peritoneal macrophages) using RT-PCR and flow cytometry .

• Control selection: Include appropriate controls such as wild-type mice and isotype antibody controls for accurate comparison .

• Sample size calculation: Determine adequate sample sizes based on expected effect sizes to ensure statistical power.

• Experimental endpoints: Define clear endpoints for tumor studies, such as tumor volume measurements and calculation of tumor growth inhibition (TGI) .

• Antibody selection: When testing CD36-targeting therapies, select antibodies with documented specificity for human CD36 and determine appropriate dosing schedules (e.g., three times weekly for six consecutive doses) .

• Immune profiling: Include assessment of immune cell populations to determine if the humanization affects immune composition or function .

What methodologies are most effective for evaluating CD36-targeting therapies in humanized mouse models?

Based on published research, the following methodologies have proven effective for evaluating CD36-targeting therapies:

For tumor studies:

• Subcutaneous tumor implantation: 5×10^5 murine colon cancer cells (e.g., MC38) implanted subcutaneously on the right dorsal side .

• Tumor volume monitoring: Measure tumors regularly using the formula: 0.5 × long diameter × (short diameter)^2 .

• Treatment regimen: Administer anti-CD36 antibodies intraperitoneally (i.p.), typically three times weekly for six consecutive doses .

For mechanistic studies:

• Flow cytometry analysis of tumor-infiltrating immune cells to assess changes in the immune microenvironment.

• Analysis of lipid metabolism in tumor and immune cells.

• RNA sequencing of tumor and immune cells to identify transcriptional changes associated with CD36 targeting.

How should researchers characterize CD36 expression and function in mouse tissues?

For comprehensive characterization of CD36 expression and function:

Expression analysis:

• RT-PCR: Use tissue-specific RNA extraction (e.g., from lung tissue) followed by RT-PCR with specific primers for human and mouse CD36 to confirm expression patterns .

• Flow cytometry: Analyze cell surface expression of CD36 in specific cell populations, particularly immune cells like macrophages and T cells .

• Immunohistochemistry: Perform tissue staining to localize CD36 expression in different organs and cell types.

Functional analysis:

• Fatty acid uptake assays: Use fluorescently labeled fatty acids to measure CD36-dependent uptake in isolated cells.

• Signaling pathway activation: Assess phosphorylation of downstream signaling molecules following CD36 ligation.

• Immune cell functional assays: Evaluate macrophage polarization, T cell activation, and cytokine production in response to CD36 ligands.

Genetic validation:

• Sanger sequencing: Perform full-length sequencing of CD36 CDS to confirm correct humanization .

• PCR genotyping: Use specific primers to discriminate between wild-type, heterozygous, and homozygous humanized mice .

How should researchers interpret differences in tumor responses between CD36 humanized and wild-type mice?

When interpreting differences in tumor responses:

• Establish baseline comparability: Before attributing differences to CD36 humanization, ensure that lymphocyte distributions and other immune parameters are comparable between humanized and wild-type mice .

• Consider antibody specificity: Differences may reflect the specificity of human CD36-targeting antibodies that cannot bind mouse CD36, rather than fundamental differences in CD36 function .

• Evaluate mechanism-specific parameters: Analyze whether observed differences correlate with changes in:

  • Lipid metabolism in tumors and immune cells

  • Immune cell infiltration and polarization

  • Angiogenesis and metastatic potential

• Contextualize with human data: Compare findings with human cancer samples to assess clinical relevance of observed differences in the mouse model.

• Account for off-target effects: Consider whether antibodies might have Fc-mediated effects independent of CD36 blockade.

Research has shown that anti-CD36 monoclonal antibodies can significantly inhibit tumor growth in CD36 humanized mice, indicating the therapeutic potential of CD36 targeting . When properly interpreted, these differences can provide insights into both the mechanistic role of CD36 in cancer and the potential clinical utility of CD36-targeting therapies.

What are the key considerations when analyzing CD36-dependent metabolic changes in immune cells?

When analyzing CD36-dependent metabolic changes in immune cells:

• Isolate specific cell populations: Use cell sorting or magnetic separation to analyze pure populations of immune cells (e.g., macrophages, T cells) from tissues or tumors.

• Assess fatty acid uptake and utilization:

  • Measure uptake of fluorescently labeled fatty acids

  • Quantify intracellular lipid droplet accumulation

  • Analyze fatty acid oxidation rates using oxygen consumption measurements

  • Assess the expression of genes involved in lipid metabolism

• Connect metabolism to function:

  • Correlate metabolic parameters with functional outputs (cytokine production, proliferation)

  • Use metabolic inhibitors to establish causality between CD36-dependent metabolism and function

  • Assess polarization states (M1/M2 for macrophages, Th1/Th2/Th17/Treg for T cells)

• Consider tissue context:

  • Different tissues have distinct metabolic environments that may influence CD36 function

  • The tumor microenvironment may specifically alter CD36-dependent metabolism

• Account for compensatory mechanisms:

  • Other fatty acid transporters may compensate for altered CD36 function

  • Changes in glucose metabolism may occur in response to altered lipid metabolism

CD36 integrates cell signaling and metabolic pathways, influencing immune cell differentiation, activation, and ultimately cell fate . These analyses can reveal how CD36 targeting might reprogram immune cells in the tumor microenvironment to enhance anti-tumor immunity.

How can researchers differentiate between the effects of CD36 on signaling versus fatty acid transport in experimental outcomes?

Differentiating between CD36's dual functions requires careful experimental design:

• Use domain-specific blocking antibodies:

  • Antibodies targeting different epitopes may preferentially block either signaling or transport functions

  • Compare the effects of antibodies known to block specific functions

• Employ parallel metabolic and signaling readouts:

  • Simultaneously measure fatty acid uptake and signaling pathway activation

  • Determine whether effects correlate more strongly with either function

• Utilize complementary approaches:

  • Fatty acid supplementation experiments to bypass transport defects

  • Specific signaling pathway inhibitors to block downstream effects

• Design structure-function studies:

  • Generate mice with mutations that selectively impair either signaling or transport function

  • Compare phenotypes to differentiate the contributions of each function

• Temporal analysis:

  • Signaling effects typically occur rapidly (minutes to hours)

  • Metabolic effects from altered fatty acid transport may take longer to manifest (hours to days)

CD36 functions as both a signaling receptor responding to DAMPs and PAMPs and as a long chain free fatty acid transporter, integrating cell signaling and metabolic pathways . Understanding which function predominates in specific contexts is crucial for targeted therapeutic development.

What are common challenges in developing and validating CD36 humanized mouse models?

Researchers developing CD36 humanized mouse models frequently encounter these challenges:

• Genetic engineering precision:

  • Ensuring exact replacement of mouse domains with human counterparts

  • Avoiding unintended genomic alterations during engineering

  • Confirming removal of selection markers (e.g., Neo cassette) that might affect expression

• Expression validation:

  • Verifying human CD36 expression patterns match endogenous mouse patterns

  • Ensuring appropriate tissue-specific expression levels

  • Detecting potential compensatory changes in related pathways

• Functional equivalence:

  • Confirming that humanized CD36 maintains all native functions

  • Assessing whether subtle differences in protein structure affect ligand binding

  • Ensuring compatibility with mouse signaling partners

• Breeding difficulties:

  • Potential fertility issues in homozygous mice

  • Maintaining colony health and genetic stability over generations

  • Avoiding genetic drift through proper breeding strategies

• Antibody validation:

  • Limited availability of well-characterized anti-human CD36 antibodies

  • Confirming antibody specificity and efficacy in the humanized model

  • Determining appropriate dosing regimens for in vivo studies

These challenges require rigorous validation steps, including genetic sequencing, mRNA and protein expression analysis, and functional testing to ensure the humanized model accurately represents human CD36 biology while maintaining normal mouse physiology .

How can researchers address variability in tumor growth and treatment responses in CD36 mouse models?

To address variability in tumor studies with CD36 mouse models:

• Standardize experimental conditions:

  • Use mice of consistent age (6-8 weeks) and sex

  • Maintain uniform housing conditions (SPF barrier facility, individually ventilated cages)

  • Allow for proper acclimatization periods (7 days) before experimentation

• Optimize tumor cell preparation:

  • Standardize cell culture conditions and passage numbers

  • Verify cell viability before implantation (>95% viable)

  • Use consistent cell numbers for implantation (e.g., 5×10^5 cells)

• Implement rigorous randomization:

  • Randomize mice once tumors reach a predefined volume (e.g., 100 mm³)

  • Ensure groups have comparable baseline tumor volumes

  • Use appropriate randomization methods (e.g., stratified randomization)

• Establish clear measurement protocols:

  • Train multiple researchers on tumor measurement techniques

  • Use standardized formulae for volume calculation

  • Implement blinded measurements when possible

  • Maintain consistent measurement schedules

• Calculate appropriate sample sizes:

  • Perform power analyses based on preliminary data

  • Include extra mice to account for potential losses

  • Consider historical variability in the specific tumor model

• Address outliers systematically:

  • Establish pre-defined criteria for excluding outliers

  • Document all exclusions transparently

  • Consider causes of outlier responses for biological insights

By implementing these approaches, researchers can minimize experimental variability and increase the reliability of results from CD36 mouse model studies .

What technical pitfalls should researchers be aware of when analyzing CD36 expression and function?

Researchers should be vigilant about these technical pitfalls:

• Antibody specificity issues:

  • Cross-reactivity between human and mouse CD36 antibodies

  • Epitope masking due to protein interactions or conformational changes

  • Batch-to-batch variability in antibody performance

• RNA analysis challenges:

  • Designing primers that specifically distinguish human from mouse CD36

  • Accounting for potential splice variants

  • Ensuring RNA quality from tissues with high lipid content

• Protein extraction complications:

  • CD36 is a membrane protein requiring specific extraction protocols

  • Potential for protein aggregation during preparation

  • Loss of protein during membrane fraction isolation

• Flow cytometry considerations:

  • CD36 expression can be affected by cell isolation procedures

  • Appropriate compensation when using multiple fluorophores

  • Consistent gating strategies across experiments

• Functional assay limitations:

  • Fatty acid uptake assays may be influenced by other transporters

  • Ensuring specificity in signaling pathway activation

  • Accounting for cell health and viability in functional readouts

• Tissue heterogeneity:

  • Variations in CD36 expression across different regions of the same tissue

  • Changes in expression during different disease stages

  • Cell type-specific expression patterns that may be lost in bulk analysis

To overcome these pitfalls, researchers should include appropriate controls, validate methods across multiple platforms, and confirm key findings using complementary approaches .

What are promising areas for expanding the utility of CD36 mouse models beyond cancer research?

CD36 mouse models hold significant potential for research in multiple fields beyond cancer:

• Cardiovascular disease research:

  • Investigating CD36's role in atherosclerosis progression

  • Testing therapeutics targeting foam cell formation

  • Studying platelet activation in thrombotic disorders

• Metabolic disorders:

  • Examining CD36's contribution to insulin resistance

  • Investigating non-alcoholic fatty liver disease pathogenesis

  • Studying adipose tissue inflammation and obesity complications

• Neurodegenerative diseases:

  • Exploring CD36's role in microglial function and neuroinflammation

  • Investigating connections between lipid metabolism and neurodegenerative processes

  • Studying CD36-mediated amyloid-β clearance in Alzheimer's disease

• Infectious diseases:

  • Examining CD36's role in pathogen recognition and immune responses

  • Investigating host-pathogen interactions mediated by CD36

  • Testing therapeutics that modulate CD36-dependent immune responses

• Developmental biology:

  • Studying CD36's role in tissue development and organogenesis

  • Investigating embryonic metabolic programming

  • Examining the impact of maternal-fetal lipid transport

The dual functionality of CD36 as both a signaling receptor and a fatty acid transporter positions these models as valuable tools for investigating the integration of metabolic and immune pathways across multiple disease contexts .

How might CD36 humanized mouse models contribute to personalized medicine approaches?

CD36 humanized mouse models can advance personalized medicine in several ways:

• Biomarker identification:

  • Correlating CD36 expression levels with treatment responses

  • Identifying downstream molecular signatures that predict responsiveness

  • Developing companion diagnostics for CD36-targeting therapies

• Patient-derived xenograft (PDX) studies:

  • Engrafting patient tumors into CD36 humanized mice

  • Testing patient-specific responses to CD36-targeting therapies

  • Identifying patient subgroups most likely to benefit from treatment

• Genetic variant modeling:

  • Creating models with specific CD36 polymorphisms found in patient populations

  • Studying how genetic variations affect drug responses

  • Developing targeted approaches for patients with specific CD36 variants

• Combination therapy optimization:

  • Testing CD36-targeting therapies with other immunotherapies or standard treatments

  • Identifying synergistic combinations for specific cancer types

  • Optimizing dosing regimens to maximize efficacy while minimizing toxicity

• Metabolism-based stratification:

  • Classifying tumors based on CD36-dependent metabolic signatures

  • Tailoring treatments to specific metabolic vulnerabilities

  • Monitoring metabolic adaptations during treatment

These approaches could help stratify patients for clinical trials of CD36-targeting therapies and optimize treatment strategies based on individual patient characteristics .

What technological advances could enhance the value of CD36 mouse models for preclinical research?

Several technological advances could significantly enhance CD36 mouse model research:

• Advanced genetic engineering:

  • Inducible humanization systems to control CD36 expression temporally

  • Tissue-specific humanization to study organ-specific effects

  • Combined humanization of multiple related receptors/pathways

• Imaging technologies:

  • In vivo imaging of CD36-mediated fatty acid uptake

  • Multiplex imaging of signaling pathway activation

  • Intravital microscopy to observe cell-cell interactions in real-time

• Single-cell analysis platforms:

  • Single-cell RNA sequencing to identify cell-specific responses

  • Single-cell metabolomics to track metabolic changes at cellular resolution

  • Spatial transcriptomics to map CD36 expression and activity within tissues

• Organoid and ex vivo systems:

  • CD36 humanized mouse-derived organoids for high-throughput screening

  • Ex vivo tissue cultures to bridge in vitro and in vivo studies

  • Microfluidic systems to study dynamic interactions

• Multi-omics integration:

  • Combined analysis of transcriptomics, proteomics, and metabolomics data

  • Systems biology approaches to model CD36-dependent processes

  • Machine learning algorithms to identify complex patterns in multi-omics data

• Improved antibody development:

  • Bispecific antibodies targeting CD36 and other relevant receptors

  • Structure-guided antibody design based on CD36-ligand interactions

  • Development of antibodies with enhanced tissue penetration

These technological advances would enable more comprehensive and precise studies of CD36 biology, potentially accelerating the development of CD36-targeting therapeutics for cancer and other diseases .