ARG1 Antibody

What is ARG1 and what is its biological function?

ARG1 (Arginase 1) is a 35-40 kDa metabolic enzyme that belongs to the arginase family. It demonstrates dual functionality depending on cellular context:

• In hepatocytes: Functions as part of the urea cycle, catalyzing the conversion of arginine to ornithine and urea in the cytoplasm

• In immune cells: Degrades arginine, indirectly downregulating nitric oxide synthase (NOS) activity by depleting its substrate

ARG1 is expressed in multiple cell types, including:

• Erythrocytes

• Hepatocytes

• Neutrophils

• Smooth muscle cells

• Macrophages (particularly tumor-associated macrophages)

The protein is moderately active as a monomer but highly active as a 105 kDa homotrimer. Trimerization is promoted by nitrosylation of Cys303, creating a regulatory feedback loop with NOS .

What are the structural characteristics of human ARG1?

Human ARG1 has the following characteristics:

• Consists of 322 amino acids (Met1-Lys322)

• Enzyme region comprises amino acids 9-309

• Contains two manganese atoms essential for catalytic activity

• UniProt accession number: P05089

• Calculated molecular weight: 34.7 kDa, though observed at 35-40 kDa on Western blots

• Has three reported isoform variants:

  • The canonical form (322 aa)

  • A variant with an eight amino acid insertion after Gln43

  • A variant with a deletion of amino acids 204-289

Human ARG1 shares 87% amino acid identity with mouse and rat ARG1, making cross-reactivity possible with some antibodies .

How should I validate ARG1 antibody specificity for my experiments?

Validating ARG1 antibody specificity is critical for reliable research results. Consider these comprehensive approaches:

• Western blot validation:

  • Compare wild-type and ARG1 knockout cell lysates (e.g., HepG2 vs. ARG1 knockout HepG2 cells)

  • Include positive controls (e.g., human liver tissue lysate shows strong ARG1 expression)

  • Include negative controls (e.g., cell lines with low/no ARG1 expression)

  • Expected band size: ~35-36 kDa

• Cross-reactivity testing:

  • Test against recombinant ARG1 and ARG2 proteins to ensure isoform specificity

  • When using antibodies across species, validate with tissue from each target species

• Multi-method validation:

  • Compare results across different detection methods (Western blot, IHC, flow cytometry)

  • Use multiple antibodies targeting different epitopes of ARG1

• Function-blocking experiments:

  • Confirm biological relevance by testing if antibody-mediated neutralization affects ARG1 enzyme activity

For optimal validation, include appropriate controls in each experiment and document antibody specificity across your experimental conditions .

What is the recommended protocol for detecting ARG1 in tumor-associated myeloid cells by flow cytometry?

For reliable detection of ARG1 in tumor-associated myeloid cells by flow cytometry, follow this optimized protocol:

Materials needed:

• Fresh tumor tissue

• Tissue digestion buffer (collagenase, DNase)

• Flow cytometry antibodies for surface markers and ARG1

• Fixation/permeabilization buffers (e.g., Foxp3/Transcription Factor Staining Buffer set)

• Normal rat serum (5%)

Protocol:

• Tissue Processing:

  • Harvest tumor tissue and process immediately

  • Enzymatically digest tissue with collagenase and DNase

  • Filter through 70 μm cell strainer to obtain single-cell suspension

  • Wash cells and count viable cells

• Surface Marker Staining:

  • Resuspend cells (1×10^6 cells/sample) in staining buffer

  • Block Fc receptors (anti-CD16/CD32) for 15 minutes at 4°C

  • Add fluorochrome-labeled antibodies for myeloid markers:

    • Mouse: CD45, CD11b, Ly6G, Ly6C

    • Human: CD45, CD11b, CD15, HLA-DR

  • Incubate for 30 minutes at 4°C in the dark

  • Wash twice with FACS buffer

• Fixation and Permeabilization:

  • Resuspend cells in 200 μL fixation buffer (diluted 4-fold)

  • Incubate for 20 minutes at room temperature

  • Centrifuge (525 ×g, 3 min, 4°C)

  • Resuspend in 200 μL permeabilization buffer

  • Incubate for 10 minutes at room temperature

• Intracellular ARG1 Staining:

  • Prepare ARG1 antibody in permeabilization buffer (1:300 dilution)

  • Add 5% heat-inactivated normal rat serum

  • Incubate cells with antibody for 30 minutes at room temperature

  • Wash twice with permeabilization buffer

  • Resuspend in FACS buffer for analysis

• Gating Strategy:

  • Gate on viable CD45+ cells

  • Identify myeloid subsets:

    • Polymorphonuclear MDSCs: CD11b+Ly6G+Ly6Clow (mouse) or CD11b+CD15+HLA-DRlow (human)

    • Monocytic MDSCs: CD11b+Ly6G-Ly6Chigh (mouse) or CD11b+CD14+HLA-DRlow (human)

  • Assess ARG1 expression within each myeloid population

Critical considerations:

• Optimize antibody concentrations for each tissue type

• Keep antibody cocktails at 4°C in the dark

• Include fluorescence minus one (FMO) controls

• Use fresh tissue whenever possible for optimal results

How can I optimize ARG1 immunohistochemistry (IHC) staining in tissue samples?

Optimizing ARG1 IHC staining requires attention to several critical parameters:

Sample Preparation:

• Fix tissues in 10% neutral buffered formalin for 24 hours

• Process and embed in paraffin following standard protocols

• Cut sections at 4-5 μm thickness for optimal antibody penetration

Antigen Retrieval Optimization:

• Test multiple methods:

  • Heat-induced epitope retrieval (HIER) in citrate buffer (pH 6.0)

  • HIER in EDTA buffer (pH 9.0)

  • Enzymatic retrieval with proteinase K

• Optimize retrieval time (typically 15-20 minutes)

Antibody Selection and Dilution:

• Test both monoclonal and polyclonal antibodies

  • Monoclonal: Higher specificity (e.g., EPR6671(B), ARG1/1125, ARG1/1126)

  • Polyclonal: Potentially higher sensitivity but requires validation

• Determine optimal dilution through titration series:

  • Start with 1:50-1:200 range for IHC applications

  • Include both positive control (liver tissue) and negative control tissues

Signal Detection System:

• For brightfield microscopy: Use polymer-based detection systems

• For fluorescence: Select fluorophores with minimal spectral overlap when multiplexing

• When co-staining with other markers (e.g., CD11b, F4/80), optimize sequential staining protocol

Key Controls:

• Positive tissue control: Human or mouse liver (high ARG1 expression)

• Negative tissue control: ARG1-negative tissues

• Technical negative control: Omit primary antibody

• Isotype control: Use matching isotype to assess non-specific binding

Automated vs. Manual Staining:

• Automated platforms provide better reproducibility

• Manual staining allows more flexibility for optimization

• Document all protocol parameters regardless of method

For dual staining of ARG1 with macrophage markers, sequential staining often yields better results than simultaneous incubation with both antibodies .

How is ARG1 expression in myeloid cells linked to immune suppression in cancer?

ARG1 expression in myeloid cells represents a key immunosuppressive mechanism in the tumor microenvironment:

Mechanistic Basis:

• ARG1-expressing myeloid cells deplete L-arginine from the local environment

• L-arginine is essential for T cell activation, proliferation, and function

• Arginine depletion leads to:

  • Decreased T cell receptor ζ-chain expression

  • Impaired T cell proliferation

  • Reduced production of effector cytokines

  • Cell cycle arrest at G0/G1 phase

Tumor-Promoting Functions:

• ARG1 activities beyond T cell suppression include:

  • Promoting wound healing-like tissue remodeling

  • Supporting tumor angiogenesis

  • Converting arginine to ornithine, which feeds polyamine synthesis needed for tumor cell proliferation

Clinical Significance:

• High ARG1 expression in pancreatic cancer correlates with worse patient survival

• ARG1 expression is significantly enriched in tumor-associated macrophages compared to macrophages in normal tissues

• ARG1-expressing myeloid cells are found across multiple cancer types including:

  • Pancreatic ductal adenocarcinoma

  • Renal cell carcinoma

  • Breast cancer

  • Colon cancer

  • Lung cancer

Experimental Evidence:

• Genetic deletion of Arg1 in macrophages using Cre-loxP technology:

  • Delayed formation of invasive pancreatic cancer

  • Increased CD8+ T cell infiltration into tumors

  • Triggered compensatory mechanisms (epithelial cells upregulated ARG1)

• Pharmacological inhibition of arginase with CB-1158:

  • Further increased CD8+ T cell infiltration

  • Sensitized tumors to anti-PD1 immune checkpoint blockade

  • Overcame compensatory mechanisms observed with genetic deletion

This research suggests that targeting ARG1 may represent a promising strategy to enhance anti-tumor immunity and improve immunotherapy outcomes .

How can ARG1 antibodies be utilized to study T cell responses to immunomodulatory vaccines?

ARG1 antibodies provide valuable tools for studying T cell responses to immunomodulatory vaccines (IMVs), particularly in understanding immune regulatory mechanisms:

Monitoring ARG1-Specific T Cells:

• ARG1-specific CD4+ and CD8+ memory T cells exist in both healthy individuals and cancer patients

• These T cells can recognize and target ARG1-expressing myeloid cells in the tumor microenvironment

• ARG1 antibodies enable identification and isolation of these cells for functional studies

Assessment of Immune Modulatory Vaccines:

• IMVs represent a novel cancer treatment approach that can stimulate anti-regulatory T cells (anti-Tregs)

• ARG1 antibodies can assess whether ARG1-based IMVs activate ARG1-specific CD8+ T cells

• Flow cytometry protocols using ARG1 antibodies can measure:

  • Expansion of ARG1-specific T cells following vaccination

  • Functional activation markers on these cells

  • Cytotoxic capabilities against ARG1-expressing myeloid targets

Experimental Approach:

• Generate and validate ARG1-specific T cell clones

• Use ARG1 antibodies to confirm specificity of these clones for ARG1-expressing cells

• Assess cytolytic effector capabilities of ARG1-specific T cells

• Monitor changes in ARG1-expressing myeloid populations following IMV treatment

• Correlate myeloid cell changes with clinical outcomes

Multiparameter Analysis:

• Combine ARG1 antibody staining with other markers to comprehensively profile the tumor microenvironment:

  • Myeloid markers: CD11b, F4/80, Ly6G, Ly6C

  • T cell markers: CD3, CD8, CD4, activation markers

  • Functional markers: cytokines, granzymes

• This approach can reveal how ARG1-targeted IMVs reshape the tumor immune landscape

This research direction offers potential for developing more effective cancer immunotherapies by targeting the immunosuppressive tumor microenvironment .

What is known about ARG1 isoform expression and how does this impact antibody selection?

Understanding ARG1 isoform complexity is critical for proper antibody selection and experimental interpretation:

ARG1 Isoform Diversity:

• Human ARG1 exists in multiple isoforms produced by alternative splicing:

  • Canonical isoform: 322 amino acids (35-40 kDa)

  • Isoform with 8 amino acid insertion after Gln43

  • Isoform with deletion of amino acids 204-289

• In knockout validation studies, faint bands sometimes remain at the ARG1 molecular weight, potentially representing isoforms not targeted by the knockout strategy

Tissue-Specific Expression Patterns:

• Liver expresses the highest levels of ARG1 (canonical form)

• Immune cells (neutrophils, macrophages) may express different isoform profiles

• In pancreatic cancer models, epithelial cells (particularly Tuft cells) can upregulate ARG1 expression as a compensatory mechanism when myeloid ARG1 is deleted

• ARG2 (mitochondrial arginase) may be upregulated in certain cell populations when ARG1 is inhibited

Antibody Selection Considerations:

• Epitope location relative to isoform variations:

  • Antibodies targeting regions within amino acids 204-289 will not detect the truncated isoform

  • Antibodies targeting the N-terminus may detect all known isoforms

• Clone-specific differences:

  • Clone 658934 (MAB5868) detects a band at approximately 40 kDa

  • Clone EPR6671(B) detects a band at approximately 36 kDa

  • Polyclonal antibodies may detect multiple isoforms simultaneously

Experimental Validation Approach:

• Use recombinant protein controls representing different isoforms

• Test antibody against ARG1 knockout samples, noting any residual bands

• Compare reactivity across multiple antibody clones targeting different epitopes

• Document isoform-specific expression in your experimental system

Technical Implications:

• Western blot may show variable banding patterns depending on tissue source and antibody clone

• In flow cytometry, different antibody clones may yield varying signal intensities in different cell populations

• For immunohistochemistry, antibody selection may affect which cell types show positive staining

Understanding these nuances is essential for accurate interpretation of ARG1 expression data, particularly in complex systems like the tumor microenvironment .

How do ARG1 inhibitors affect the efficacy of immune checkpoint blockade therapy?

ARG1 inhibition represents a promising strategy to enhance immune checkpoint blockade therapy, with several key mechanisms and experimental findings:

Mechanistic Rationale:

• ARG1-expressing myeloid cells deplete arginine from the tumor microenvironment (TME)

• T cells require arginine for:

  • Proper T cell receptor signaling

  • Proliferation following activation

  • Production of effector cytokines

  • Metabolic fitness and survival in the TME

• Checkpoint inhibitors (e.g., anti-PD1) can activate T cells, but these cells remain dysfunctional in an arginine-depleted environment

Experimental Evidence:

• In pancreatic cancer models:

  • Genetic deletion of Arg1 in macrophages increased CD8+ T cell infiltration but showed compensatory mechanisms

  • The arginase inhibitor CB-1158 (INCB001158) treatment:

    • Further increased CD8+ T cell infiltration beyond genetic knockout

    • Sensitized previously resistant tumors to anti-PD1 checkpoint blockade

    • Overcame compensatory mechanisms seen with genetic targeting

• In Lewis lung carcinoma models:

  • CB-1158 as monotherapy decreased tumor growth

  • Combination of CB-1158 with anti-PD1 showed enhanced anti-tumor effects compared to either treatment alone

Clinical Development:

• CB-1158 (INCB001158) inhibits both human and mouse arginase

• Phase I clinical trials have evaluated CB-1158 in patients with advanced or metastatic solid tumors

• The compound has entered clinical testing both as monotherapy and in combination with checkpoint inhibitors

Potential Resistance Mechanisms:

• ARG1 upregulation in non-myeloid cells (e.g., epithelial cells, Tuft cells)

• Compensatory ARG2 expression in certain myeloid populations

• Alternative immunosuppressive pathways (IDO, TGF-β, etc.)

• These mechanisms suggest that targeting multiple immunosuppressive pathways simultaneously may be necessary

Biomarker Development:

• ARG1 antibodies are valuable tools for:

  • Patient selection based on myeloid ARG1 expression

  • Pharmacodynamic monitoring during treatment

  • Assessment of resistance mechanisms

This research direction highlights the importance of targeting metabolic immune evasion mechanisms in combination with checkpoint blockade to improve cancer immunotherapy outcomes .

What are common issues when using ARG1 antibodies and how can they be resolved?

Researchers frequently encounter several technical challenges when working with ARG1 antibodies. Here are common issues and evidence-based solutions:

Issue: Weak or Absent Signal in Western Blot

Potential causes and solutions:

• Protein degradation: ARG1 is sensitive to freeze-thaw cycles

  • Solution: Add protease inhibitors to lysis buffer; extract protein freshly

  • Use reducing conditions consistently (ARG1 detection works best under reducing conditions)

• Sample preparation: Different buffer groups affect detection

  • Solution: For Western blot, Immunoblot Buffer Group 1 or 8 shows optimal results with ARG1 antibodies

• Antibody binding conditions: Some epitopes require specific conditions

  • Solution: Optimize primary antibody incubation time (overnight at 4°C often yields better results than shorter incubations)

Issue: Non-specific Bands in Western Blot

Potential causes and solutions:

• Cross-reactivity with ARG2: Some antibodies detect both isoforms

  • Solution: Validate antibody specificity using recombinant ARG1 and ARG2 proteins

• Detection of alternative isoforms: Multiple bands may represent actual isoforms

  • Solution: Use ARG1 knockout controls to identify specific vs. non-specific bands

  • Expected band size: 35-40 kDa (canonical form)

• High background: Non-specific binding

  • Solution: Increase blocking time (5% milk or BSA in TBS-T); include 0.1% Tween-20 in wash buffer; increase wash frequency

Issue: Inconsistent Staining in Immunohistochemistry

Potential causes and solutions:

• Fixation artifacts: Overfixation can mask epitopes

  • Solution: Limit fixation time to 24 hours; optimize antigen retrieval method (heat-induced epitope retrieval in citrate buffer pH 6.0 works well for many ARG1 antibodies)

• Tissue-specific differences: ARG1 expression varies by tissue

  • Solution: Include appropriate positive controls (liver tissue); use optimal antibody dilution (typically 1:50-1:200 for IHC)

• Detection system sensitivity: Some systems have lower sensitivity

  • Solution: Use polymer-based detection systems for increased sensitivity; avoid avidin-biotin systems with liver tissue (endogenous biotin)

Issue: Low Detection in Flow Cytometry

Potential causes and solutions:

• Incomplete fixation/permeabilization: Critical for intracellular antigens

  • Solution: Use specialized buffers like Foxp3/Transcription Factor Staining Buffer set; ensure adequate permeabilization time (minimum 10 minutes)

• Antibody competition with other intracellular markers: Epitope blocking

  • Solution: Optimize staining sequence; add 5% normal serum to reduce non-specific binding

• Cell viability issues: Dead cells can cause high background

  • Solution: Include viability dye; perform Ficoll purification for blood samples; process tissues rapidly

Issue: Batch-to-Batch Variability

Potential causes and solutions:

• Antibody production differences: Even monoclonal antibodies can vary

  • Solution: Validate each new lot against a previous lot using positive control samples

  • Document lot numbers and maintain reference samples for comparison

• Storage conditions: Antibody degradation

  • Solution: Aliquot antibodies to avoid freeze-thaw cycles; store according to manufacturer recommendations (typically -20°C)

These troubleshooting approaches are based on published methods and can significantly improve ARG1 detection across various experimental platforms .

How can I optimize ARG1 co-staining with other markers for multiparameter analysis?

Optimizing co-staining protocols for ARG1 with other markers requires careful consideration of multiple technical factors:

Antibody Panel Design:

• Epitope accessibility considerations:

  • ARG1 is an intracellular antigen requiring permeabilization

  • Surface markers should be stained before fixation/permeabilization when possible

  • Some surface epitopes may be sensitive to permeabilization (e.g., certain CD markers)

• Fluorophore selection strategy:

  • Assign brightest fluorophores (PE, APC) to lower abundance targets

  • ARG1 expression can be high in positive cells but completely absent in others, making it suitable for fluorophores with intermediate brightness

  • Avoid spectral overlap between ARG1 and markers expressed by the same cells

Optimized Co-staining Protocol:

• Critical optimization steps:

  • Titrate each antibody individually before combining

  • Validate the complete panel using FMO (Fluorescence Minus One) controls

  • Include single-stained controls for compensation

  • Test fixation impact on all fluorochromes in your panel

Common Marker Combinations:

• Myeloid-focused panel:

  • Surface: CD45, CD11b, Ly6G, Ly6C, F4/80, CD206

  • Intracellular: ARG1, iNOS (for M1/M2 polarization assessment)

  This combination allows assessment of ARG1 expression across myeloid subsets and polarization states

• Tumor microenvironment panel:

  • Surface: CD45, CD3, CD8, CD4, CD11b, PD-1

  • Intracellular: ARG1, Granzyme B, IFN-γ

  This panel enables correlation between ARG1+ myeloid cells and T cell functionality

Technical Validation:

To confirm successful co-staining, include these controls:

• ARG1-high tissue (liver) as positive control

• Non-immune tissue as negative control

• Isotype controls for both ARG1 and co-stained markers

• FMO controls to set accurate positive/negative boundaries

When analyzing co-expression data, use bivariate plots (e.g., ARG1 vs. CD11b) rather than sequential gating to better visualize relationships between markers .

How does ARG1 expression change during aging and inflammation?

ARG1 expression undergoes significant changes during aging and inflammation, with important implications for immune regulation:

Age-Related Changes in ARG1 Expression:

Experimental data from mouse models reveals distinct age-dependent changes:

These findings indicate that aging is associated with higher baseline and stimulus-induced ARG1 expression, particularly in the central nervous system .

Inflammation-Dependent Regulation:

• Acute inflammation:

  • Early increase in ARG1 expression in neutrophils and macrophages

  • ARG1 upregulation peaks around 24-48 hours after inflammatory stimulus

  • Functions as a counter-regulatory mechanism to limit excessive inflammation

• Chronic inflammation:

  • Sustained ARG1 expression in myeloid cells

  • Shifts macrophage polarization toward M2-like (alternatively activated) phenotype

  • Associated with tissue repair but may promote fibrosis and impair immunity

• Infection models:

  • Sepsis induces strong polarization of macrophages toward ARG1-expressing phenotype

  • Time-dependent changes in ARG1 expression correlate with disease progression

  • Coincides with increased expression of other M2 markers (MR, Fizz1)

Tissue-Specific Patterns:

Inflammation-induced ARG1 expression shows tissue-specific patterns:

• Lung: Pronounced ARG1 upregulation in alveolar macrophages and recruited myeloid cells during inflammatory lung diseases

• CNS: Microglia and infiltrating macrophages upregulate ARG1 early after CNS injuries

• Peritoneum: Peritoneal macrophages show strong ARG1 induction following inflammatory stimuli

Mechanistic Regulators:

Key molecular pathways regulating inflammation-induced ARG1 expression include:

• C/EBPβ pathway: Transcription factor that drives ARG1 expression

• IL-4/IL-13 signaling: Classical inducers of ARG1 in alternatively activated macrophages

• Oncogenic KRAS signaling: In pancreatic cancer, epithelial KRAS drives myeloid ARG1 expression

Functional Consequences:

Age and inflammation-associated ARG1 expression impacts:

• T cell responses (inhibitory when elevated)

• Wound healing (promoted)

• Pathogen clearance (potentially impaired)

• Response to immunotherapy (reduced efficacy with high ARG1)

Understanding these dynamic changes in ARG1 expression provides insights into age-related immune dysfunction and inflammatory disease mechanisms .

What role does ARG1 play in immune cell polarization beyond M1/M2 classification?

ARG1's role in immune cell polarization extends beyond traditional M1/M2 classification, revealing a more nuanced function in diverse immune contexts:

Beyond Binary M1/M2 Classification:

While ARG1 is traditionally considered an M2 macrophage marker, research demonstrates that:

• Spectrum of activation states:

  • Macrophages exist along a continuum rather than discrete M1/M2 states

  • ARG1 expression can occur in macrophages that simultaneously express some M1 markers

  • The tissue microenvironment shapes complex activation profiles that don't fit neatly into M1/M2 categories

• Temporal dynamics:

  • ARG1 expression shows dynamic regulation during inflammatory responses

  • Initial inflammatory (M1-like) phase may be followed by ARG1 upregulation

  • These temporal patterns reflect changing functional priorities rather than distinct cell types

Cell Type-Specific ARG1 Functions:

ARG1 expression extends to multiple immune cell populations with distinct functional implications:

• Neutrophils:

  • Constitutively express ARG1 in cytoplasmic granules

  • Release ARG1 into extracellular environment upon activation

  • Contribute to immunosuppression in cancer differently than macrophages

• Myeloid-derived suppressor cells (MDSCs):

  • Both polymorphonuclear and monocytic MDSCs express ARG1

  • ARG1 serves as a key effector molecule for MDSC immunosuppressive function

  • Different MDSC subsets may regulate ARG1 through distinct signaling pathways

• Group 2 innate lymphoid cells (ILC2s):

  • Express ARG1 during lung inflammatory conditions

  • Contribute to tissue repair functions

  • Represent a non-myeloid source of ARG1 in certain disease contexts

• Dendritic cells:

  • Can express ARG1 under certain conditions

  • May contribute to regulation of T cell responses

  • ARG1 expression correlates with tolerogenic DC phenotypes

Disease-Specific Polarization Patterns:

ARG1 expression patterns vary across disease contexts:

• Cancer microenvironment:

  • Complex myeloid polarization states with ARG1 co-expressed with various other markers

  • Tumor-specific signals promote unique myeloid phenotypes not seen in other inflammatory conditions

  • Epithelial cells (especially Tuft cells) can express ARG1 as a compensatory mechanism

• CNS injury and disease:

  • ARG1 expression in microglia/macrophages after CNS injuries

  • Associated with beneficial functions (tissue repair) in contrast to its detrimental role in cancer

  • Temporal regulation differs from peripheral inflammation models

• Sepsis progression:

  • ARG1 expression increases in lung tissue and peritoneal cells

  • Coincides with expression of other M2 markers (MRC1, Fizz1)

  • Represents part of a coordinated response to systemic inflammation

Therapeutic Implications:

Understanding ARG1's complex role in immune polarization has therapeutic relevance:

• Target ARG1 selectively in specific cell populations

• Consider temporal aspects of ARG1 expression when designing intervention strategies

• Combine ARG1 targeting with other immunomodulatory approaches for optimal effects

This nuanced understanding of ARG1 in immune polarization helps design more effective immunotherapeutic strategies across various disease contexts .