CBR1 Human

What is CBR1 and what are its primary physiological functions in human cells?

Carbonyl Reductase 1 (CBR1) is an NADPH-dependent monomeric cytosolic enzyme with broad specificity for carbonyl compounds . It belongs to the short-chain dehydrogenase/reductase (SDR) superfamily and plays critical roles in both xenobiotic and endogenous substrate metabolism.

The primary physiological functions of CBR1 include:

• Regulation of fatty acid metabolism, which current research suggests may be its principal function

• Metabolism of glucocorticoids, specifically catalyzing the NADPH-dependent production of 20β-dihydrocortisol (20β-DHF) from cortisol

• Reduction of various carbonyl-containing compounds including anthracyclines (daunorubicin, doxorubicin) and prostaglandins

• Detoxification of xenobiotics in drug metabolism pathways

CBR1 demonstrates tissue-specific expression patterns, being found primarily in the intestinal tract, liver, kidneys, skin, and ovaries . Research increasingly suggests CBR1 has tumor-suppressive properties in several cancer types, with high expression correlating with better prognosis in ovarian cancer . Additionally, CBR1 expression is upregulated in adipose tissue during obesity in humans, mice, and horses, suggesting a potential role in metabolic regulation .

For researchers investigating CBR1, it is essential to examine both its enzymatic function through activity assays and expression patterns through immunoblotting or RT-qPCR, as functions appear to be tissue-specific and context-dependent.

What experimental approaches are most effective for measuring CBR1 expression and activity in human samples?

Comprehensive investigation of CBR1 in human samples requires assessment of both expression and functional activity. The optimal methodology depends on sample type, research question, and available resources.

Expression Analysis Techniques:

Activity Assessment Techniques:

When designing CBR1 analysis experiments, researchers should consider:

• For clinical samples, implement stabilization protocols to preserve enzyme activity

• Include appropriate tissue-specific controls, as CBR1 expression varies considerably between tissues

• Correlate expression with activity measurements where possible

• In cancer studies, compare matched normal and tumor tissues

• Use selective inhibitors to confirm specificity of activity measurements

A comprehensive approach typically combines multiple complementary techniques. For instance, the study described in search result utilized stable CBR1-overexpressing cell lines with Western blot verification of expression, followed by functional assays to assess biological effects and proteomics to identify affected pathways.

How does CBR1 contribute to glucocorticoid metabolism in humans?

CBR1 plays a significant but previously underappreciated role in glucocorticoid metabolism through its ability to catalyze the NADPH-dependent reduction of cortisol to 20β-dihydrocortisol (20β-DHF) . This represents an alternative metabolic pathway to the classical 11β-HSD-mediated cortisol-cortisone interconversion system.

The key aspects of CBR1-mediated glucocorticoid metabolism include:

For researchers investigating CBR1-glucocorticoid interactions, appropriate methodologies include:

• In vitro enzyme assays with recombinant CBR1 and cortisol substrate

• LC-MS/MS quantification of 20β-DHF formation

• Cell-based systems with modulated CBR1 expression

• Glucocorticoid receptor activation assays to assess signaling consequences

The identification of this CBR1-mediated pathway introduces new perspectives on glucocorticoid regulation and potentially identifies a novel therapeutic target for conditions associated with glucocorticoid dysregulation.

What role does CBR1 play in cancer progression and what is the evidence for its tumor-suppressive effects?

CBR1 demonstrates significant tumor-suppressive properties across multiple cancer types, though its mechanisms of action appear complex and potentially context-dependent. Understanding these effects is crucial for developing potential therapeutic strategies targeting this pathway.

Evidence for Tumor-Suppressive Effects:

• Clinical Correlations: Studies show that reduced CBR1 expression is associated with worse prognosis in ovarian cancer patients . Conversely, higher CBR1 expression correlates with better outcomes, suggesting a protective effect.

• Functional Evidence:

  • Overexpression of CBR1 in ovarian cancer cell lines (OVCAR-3 and SK-OV-3) significantly inhibits cell proliferation

  • Growth of OVCAR-3 and SK-OV-3 cells expressing hCBR1-tGFP was demonstrably slower than wild-type or negative control cells

  • An inverse correlation exists between CBR1 expression levels and cell proliferation rates

• Molecular Mechanisms:

  • Reduced CBR1 expression is accompanied by decreased E-cadherin expression and activation of matrix metalloproteinases, promoting cancer cell proliferation and tumorigenesis

  • CBR1 may exert antitumor effects by activating caspase pathways, inducing apoptosis

  • Proteomic analysis revealed CBR1 overexpression affects multiple signaling pathways, with the eIF2 signaling pathway being particularly impacted (z-score +1.387)

• Cancer Type Specificity: Beyond ovarian cancer, CBR1 has demonstrated tumor-suppressive effects in:

  • Cervical cancer

  • Uterine sarcoma

  • Non-small cell lung carcinoma

Experimental Models for Studying CBR1 in Cancer:

The research methodology employed in study provides an excellent framework for investigating CBR1 in cancer:

• Generation of stable CBR1-overexpressing cancer cell lines

• Verification of expression using immunoblot analysis

• Proliferation assays to assess functional effects

• Proteomics analysis (LC-MS/MS) to identify affected pathways

• Pathway analysis using tools like Ingenuity Pathway Analysis (IPA)

For researchers, it's important to note that CBR1 effects may vary by cancer type and context. The strong evidence for tumor-suppressive effects suggests potential therapeutic strategies aimed at upregulating CBR1 expression or activating its downstream pathways could be beneficial in specific cancer contexts.

How does CBR1 overexpression affect intracellular signaling pathways in cancer cells?

CBR1 overexpression significantly alters multiple intracellular signaling pathways in cancer cells, potentially explaining its observed tumor-suppressive effects. Comprehensive proteomics analysis has revealed specific pathways and protein networks affected by modulated CBR1 expression.

Key Affected Signaling Pathways:

The eIF2 signaling pathway emerged as the most significantly affected by CBR1 overexpression based on Ingenuity Pathway Analysis (IPA) of proteomics data . This pathway ranked highest among the top 20 canonical pathways altered in CBR1-overexpressing cells.

The eIF2 (eukaryotic Initiation Factor 2) signaling pathway:

• Regulates global protein synthesis

• Controls integrated stress responses

• Influences cell survival decisions

• Modulates cell cycle progression

The positive z-score (+1.387) calculated by IPA indicates activation of the eIF2 pathway in CBR1-overexpressing cells . This suggests CBR1 promotes cellular stress responses that may contribute to the observed growth inhibition.

Protein-Level Changes:

• Of 939 proteins quantified in the proteomics analysis, 155 proteins showed significant correlation with CBR1 expression (FDR-adjusted P-value <0.05)

• Among the 23 proteins associated with eIF2 signaling, 17 had positive correlation coefficients with CBR1 expression

• These protein alterations collectively suggest broad reprogramming of protein synthesis and stress response networks

Methodological Approach:

The researchers employed a sophisticated experimental approach to identify these pathway changes:

• LC-MS/MS proteomics of whole cell lysates from control and CBR1-overexpressing cells

• Label-free quantification for protein abundance measurement

• Statistical correlation analysis (Spearman's rank correlation) to identify proteins significantly associated with CBR1 expression

• Pathway enrichment analysis using IPA to identify affected canonical pathways

This methodological framework provides a robust template for researchers investigating how CBR1 or other proteins of interest affect cellular signaling networks.

Research Implications:

Understanding the signaling pathways affected by CBR1 has significant implications:

• Provides mechanistic insight into CBR1's tumor-suppressive effects

• Identifies potential therapeutic targets that could synergize with CBR1 modulation

• Offers biomarkers for assessing CBR1 pathway activation in clinical samples

• Creates a framework for understanding how CBR1 influences other cellular processes

What role does CBR1 play in adipose tissue during obesity and what are the metabolic implications?

CBR1 expression is significantly upregulated in adipose tissue during obesity, a finding consistently observed across multiple species including humans, mice, and horses . This alteration appears to have important metabolic implications, particularly regarding glucocorticoid metabolism and adipose tissue function.

CBR1 Expression Changes in Obesity:

The research indicates a consistent pattern of CBR1 upregulation in adipose tissue in obesity across species, suggesting this represents a conserved and potentially important metabolic adaptation . This regulation appears to be adipose-specific rather than a systemic response, highlighting the tissue-specific nature of CBR1 regulation.

Metabolic Implications:

• Glucocorticoid Metabolism:

  • Increased CBR1 expression would enhance conversion of cortisol to 20β-dihydrocortisol (20β-DHF)

  • 20β-DHF functions as a weak agonist of the glucocorticoid receptor

  • This may create a local buffering system to modulate glucocorticoid effects in adipose tissue

• Adipocyte Function:

  • Glucocorticoids are key regulators of adipogenesis and adipocyte metabolism

  • Altered local glucocorticoid signaling through the CBR1 pathway could influence:

    • Adipocyte differentiation

    • Lipid storage and mobilization

    • Adipokine production

    • Inflammatory status

• Fatty Acid Metabolism:

  • Given that a primary function of CBR1 appears to be regulation of fatty acid metabolism , its upregulation in obesity may represent an adaptive response to increased lipid flux

  • This could influence both systemic and local lipid homeostasis

Research Significance:

The obesity-associated upregulation of CBR1 in adipose tissue has several important implications for researchers:

• It identifies a novel pathway potentially contributing to obesity-related metabolic dysregulation

• It suggests CBR1 could represent a therapeutic target for obesity-related disorders

• It establishes a connection between obesity and altered glucocorticoid metabolism through the CBR1 pathway

• It highlights the importance of tissue-specific enzyme regulation in metabolic disease

For investigators studying obesity and metabolic disease, examination of CBR1 expression and the 20β-DHF pathway may provide new insights into the complex pathophysiology of these conditions and potentially identify novel therapeutic approaches.

What methodological challenges exist in studying CBR1-mediated drug metabolism?

Researching CBR1-mediated drug metabolism presents several significant challenges that researchers must address to obtain reliable and physiologically relevant data. These challenges span from experimental design to data interpretation.

Analytical and Technical Challenges:

• Substrate Specificity Overlap:

  • CBR1 shares substrate specificity with other reductases

  • Challenge: Distinguishing CBR1-specific metabolism from other enzymes

  • Solution: Use selective CBR1 inhibitors, CBR1 knockout/knockdown models, or immunodepletion techniques

• Enzyme and Metabolite Stability:

  • CBR1-generated metabolites may be unstable under certain conditions

  • Challenge: Preserving integrity throughout analysis

  • Solution: Optimize sample processing, use stabilizing agents, develop sensitive analytical methods

• Cofactor Requirements:

  • CBR1 is NADPH-dependent, requiring optimization of cofactor availability

  • Challenge: Ensuring sufficient NADPH without inhibiting product formation

  • Solution: Implement NADPH regenerating systems, optimize cofactor concentrations

Biological System Challenges:

• Tissue Heterogeneity:

  • CBR1 expression varies across tissues and cell types

  • Challenge: Obtaining representative data from heterogeneous samples

  • Solution: Consider cell-specific approaches, microdissection, or cell sorting

• Interindividual Variability:

  • Genetic and environmental factors affect CBR1 expression and function

  • Challenge: Accounting for variation between samples

  • Solution: Increase sample sizes, include genetic characterization, document patient history

• Disease State Effects:

  • Pathological conditions may alter CBR1 expression (as seen in cancer and obesity)

  • Challenge: Distinguishing disease-specific changes from normal variation

  • Solution: Use paired normal/disease samples, stratify by disease state

Experimental Design Considerations:

• Model Selection:

  • Different experimental systems have varying relevance

  • Challenge: Choosing appropriate models for specific research questions

  • Options: Human liver microsomes vs. cytosolic fractions (CBR1 is cytosolic), primary cells vs. cell lines, recombinant systems vs. native tissue preparations

• Reaction Conditions:

  • Enzymatic activity is sensitive to experimental conditions

  • Challenge: Creating physiologically relevant yet experimentally controlled conditions

  • Solution: Optimize pH, temperature, buffer composition; validate with known CBR1 substrates

• Quantification Approaches:

  • Metabolite detection requires sensitive and specific methods

  • Challenge: Accurately quantifying metabolites, especially minor ones

  • Solution: Develop LC-MS/MS methods with appropriate internal standards, optimize extraction procedures

For researchers studying CBR1-mediated drug metabolism, addressing these challenges requires multidisciplinary approaches combining analytical chemistry, molecular biology, and pharmacology. The optimal strategy typically involves using multiple complementary methods to confirm findings and validate CBR1-specific effects.

How can genetic variations in CBR1 affect enzyme function and disease susceptibility?

Genetic variations in the CBR1 gene can significantly influence enzyme function, drug metabolism, and potentially disease susceptibility. Understanding these variations is essential for personalized medicine approaches and risk stratification.

Types of CBR1 Genetic Variations:

• Single Nucleotide Polymorphisms (SNPs):

  • Coding region SNPs that alter amino acid sequence

  • Promoter region SNPs affecting gene expression

  • Intronic SNPs potentially impacting splicing

  • 3'UTR SNPs affecting mRNA stability or microRNA binding sites

• Copy Number Variations (CNVs):

  • Duplications or deletions affecting CBR1 gene dosage

  • Larger structural variations potentially involving regulatory elements

• Epigenetic Variations:

  • Differential promoter methylation patterns

  • Histone modification variations affecting expression

Functional Consequences of CBR1 Variants:

Genetic variations can impact CBR1 function through several mechanisms:

• Altered Enzyme Kinetics:

  • Changes in substrate binding affinity (Km)

  • Modifications to catalytic efficiency (Vmax)

  • Shifts in substrate specificity

• Expression Level Changes:

  • Increased or decreased CBR1 protein levels

  • Tissue-specific expression alterations

  • Changes in regulation under different physiological conditions

• Protein Stability Modifications:

  • Altered thermal stability of the enzyme

  • Changes in protein half-life

  • Modified interaction with cellular components

Disease and Therapeutic Implications:

• Cancer Susceptibility and Progression:

  • Given CBR1's tumor-suppressive properties , variants affecting expression or function may influence cancer risk

  • Alterations could impact prognosis and treatment response

  • Potential biomarker for stratification

• Drug Metabolism Variability:

  • CBR1 metabolizes various drugs including anthracyclines (daunorubicin, doxorubicin)

  • Variants could alter efficacy or toxicity profiles

  • Potential for pharmacogenetic-guided dosing

• Metabolic Disease:

  • CBR1's role in glucocorticoid metabolism and its upregulation in obesity suggest variants could influence metabolic health

  • May affect individual susceptibility to obesity-related complications

  • Could alter response to metabolic interventions

Research Methodologies:

For investigators studying CBR1 genetic variations, recommended approaches include:

• Genotyping Strategies:

  • Targeted SNP analysis for known variants

  • Next-generation sequencing for comprehensive variant detection

  • Whole-genome approaches for novel variant discovery

• Functional Characterization:

  • Site-directed mutagenesis to recreate variants in expression systems

  • Enzyme kinetic studies with variant proteins

  • Cellular models expressing variant forms

• Clinical Translation:

  • Association studies linking variants to clinical outcomes

  • Pharmacogenetic studies in treatment cohorts

  • Development of predictive algorithms based on genetic profile

Understanding CBR1 genetic variations can ultimately contribute to precision medicine approaches by enabling individualized risk assessment and treatment strategies based on genetic profile.

What experimental models are most appropriate for studying CBR1 function in human disease?

Selection of appropriate experimental models is critical for advancing understanding of CBR1 function in human disease. Each model system offers distinct advantages and limitations that should be considered based on specific research questions.

Cellular Models:

The approach used in research paper provides an excellent template, where stable CBR1-overexpressing ovarian cancer cell lines were generated to study effects on proliferation and signaling pathways.

Animal Models:

Research finding highlights the relevance of comparative studies across species (humans, mice, horses), particularly for metabolic research.

Ex Vivo Systems:

Systems Biology Approaches:

The proteomics approach used in study exemplifies how systems biology can reveal novel insights, identifying 155 proteins significantly correlated with CBR1 expression and highlighting the eIF2 signaling pathway.

Model Selection Considerations:

• Research Question Specificity:

  • For basic enzymatic characterization: Recombinant protein or stable cell lines

  • For cancer research: Models reflecting the relationship between CBR1 expression and tumor growth

  • For metabolic studies: Models capturing CBR1's role in glucocorticoid metabolism

• Species Differences:

  • Consider that CBR1 provides the major route of cortisol metabolism in horses

  • Mouse models may not fully recapitulate human CBR1 regulation patterns

• Validation Strategy:

  • Use multiple complementary models to strengthen findings

  • Validate key findings in human samples when possible

  • Consider both loss-of-function and gain-of-function approaches

For comprehensive CBR1 research, a multi-model approach is typically most informative, beginning with well-controlled cellular systems and extending to more complex models as mechanisms are elucidated.

What specific protocols are most effective for generating stable CBR1-overexpressing cell lines for research?

Based on successful approaches documented in the research literature, establishing stable CBR1-overexpressing cell lines requires careful consideration of several key factors including vector design, selection methodology, and validation procedures.

Vector Design and Construction:

The approach described in research paper provides an effective template:

• Expression Construct Components:

  • Human CBR1 (hCBR1) coding sequence

  • Reporter tag for visualization and detection (e.g., turbo green fluorescent protein [tGFP])

  • Strong constitutive promoter (e.g., CMV)

  • Selection marker (e.g., antibiotic resistance gene)

• Vector Considerations:

  • Mammalian expression vector with appropriate regulatory elements

  • Inclusion of fusion tags (N- or C-terminal) that preserve enzyme function

  • Consideration of codon optimization for target cell type

• Control Vectors:

  • Empty vector controls or reporter-only constructs (e.g., tGFP alone)

  • These controls are essential for distinguishing effects of CBR1 overexpression from those of vector components

Transfection and Selection:

• Cell Line Selection:

  • Choose cell lines relevant to research question (e.g., OVCAR-3 and SK-OV-3 for ovarian cancer research)

  • Consider baseline CBR1 expression levels

  • Ensure cells are amenable to stable transfection

• Transfection Method:

  • Lipid-based transfection for most mammalian cell lines

  • Electroporation for hard-to-transfect cells

  • Viral transduction for higher efficiency

• Selection Strategy:

  • Antibiotic selection based on resistance marker

  • Begin selection 24-48 hours post-transfection

  • Maintain selection until resistant colonies emerge

  • Consider single-cell cloning to obtain homogeneous populations

Validation of Stable Cell Lines:

Research paper demonstrates essential validation steps:

• Expression Verification:

  • Immunoblot analysis using anti-CBR1 antibodies to confirm overexpression

  • Fluorescence microscopy for tagged constructs to assess expression pattern

  • RT-qPCR for mRNA expression quantification

• Functional Validation:

  • Enzyme activity assays to confirm functional overexpression

  • Substrate metabolism studies

  • Proliferation assays to assess biological effects

• Stability Assessment:

  • Regular testing of expression levels over multiple passages

  • Periodic reselection if expression decreases

  • Cryopreservation of early-passage validated cells

Experimental Considerations:

• Creating Multiple Independent Lines:

  • Generate multiple stable lines with varying expression levels

  • This allows dose-dependent analysis of CBR1 effects

• Wild-type Controls:

  • Always include wild-type parental cells in experiments

  • This controls for cell line-specific effects

• Quantitative Analysis:

  • Measure relative CBR1 expression levels using image analysis software

  • This allows correlation of expression levels with observed phenotypes

Following this protocol framework should enable researchers to generate stable CBR1-overexpressing cell lines suitable for investigating various aspects of CBR1 biology, including effects on cell proliferation, pathway analysis, and drug metabolism studies.