KLRD1 Antibody

What is KLRD1 and what is its biological function?

KLRD1 (Killer Cell Lectin Like Receptor D1), also known as CD94, is a type II transmembrane glycoprotein expressed predominantly on natural killer (NK) cells and some cytotoxic T-cells. It functions as a receptor for the recognition of MHC class I HLA-E molecules and can form disulfide-bonded heterodimers with NKG2 family members. The CD94-NKG2 complex interacts with Human Leukocyte Antigen (HLA)-E on target cells, regulating NK cell activation and cytotoxicity . This receptor plays a crucial role in immune surveillance, particularly in discriminating between healthy cells and those under cellular stress, infection, or malignant transformation. Understanding KLRD1 expression and function provides insights into innate immune responses and potential therapeutic targets in disease states.

Which cell types express KLRD1 and at what levels?

Single-cell analysis has revealed that KLRD1 is predominantly expressed in NK cells and CD8+ exhausted T cells (CD8Tex) across various cancers, including bladder cancer (BLCA), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), non-small cell lung cancer (NSCLC), and melanoma (SKCM) . Detailed examination across multiple datasets has consistently demonstrated significantly higher expression in NK cells compared to other immune cell populations. When designing experiments involving KLRD1, researchers should expect strong expression on CD3-CD56+ NK cells, variable expression on CD8+ T cell subsets, and minimal to no expression on most other leukocyte populations. The expression pattern varies somewhat by tissue type and activation state, with inflammation or malignancy potentially altering expression profiles.

What are the key considerations when selecting a KLRD1 antibody for research?

When selecting a KLRD1 antibody, researchers should consider several factors depending on their experimental application. For flow cytometry, monoclonal antibodies like clone 18d3 (for mouse) or DX22 (for human) are recommended due to their validated specificity and consistent performance . For Western blot applications, both monoclonal (e.g., clone 27D7) and polyclonal antibodies may be suitable, with polyclonals often providing better detection of denatured proteins . For immunohistochemistry, validated antibodies like LS-B14034 have demonstrated reliable tissue staining patterns .

Consider these key selection criteria:

• Species reactivity (human, mouse, etc.)

• Validated applications (FC, WB, IHC, IF)

• Epitope location (extracellular domain for flow cytometry)

• Clone type (recombinant antibodies offer greater consistency)

• Conjugation needs (fluorochrome for direct detection)

• Validation data availability

Recombinant antibody technology offers several advantages over traditional antibodies, including increased sensitivity, confirmed specificity, high repeatability, excellent batch-to-batch consistency, and sustainable supply .

How does KLRD1 expression correlate with cancer prognosis and therapeutic response?

KLRD1 exhibits significant differential expression across multiple cancer types, with particularly strong prognostic relevance in head and neck squamous cell carcinoma (HNSC). Research has demonstrated that KLRD1 serves as an independent prognostic factor in HNSC, where higher expression correlates with improved patient outcomes . This prognostic value likely stems from KLRD1's association with robust immune surveillance and response.

Immune infiltration analysis has revealed significant positive correlations between KLRD1 expression and key immune parameters:

The strong correlation with immune scores indicates that tumors with high KLRD1 expression typically exhibit greater immune cell infiltration, including T cells, B cells, NK cells, myeloid dendritic cells, and both M1 and M2 macrophages . This enriched immune microenvironment may explain the improved prognosis observed in high-KLRD1 cancers. Furthermore, drug sensitivity analyses suggest that tumors with higher KLRD1 expression may show enhanced sensitivity to cell division inhibitors, including TAK-715, CAY10603, and Tubastatin A, providing potential therapeutic opportunities .

What is the relationship between KLRD1 and immune checkpoint regulation?

KLRD1 plays a complex role in immune checkpoint regulation, particularly through its interactions with NKG2 family members. Analysis of KLRD1 in the context of immune checkpoint molecules has revealed significant differences in expression patterns between high and low KLRD1 expression groups in tumors .

In high KLRD1 expression environments, researchers have observed upregulation of:

• Immune-stimulatory genes (C10orf54, TMEM173)

• Immune-inhibitory genes

• Chemokines (CXCL9-17)

• HLA molecules (HLA-A-C, PVRL2)

• Immune regulatory molecules (CD40LG, TMIGD2, TNFRSF13B, TNFSF14)

This expression pattern corresponds to a complex immune regulatory landscape characterized by increased leukocyte and stromal fractions, enhanced lymphocyte infiltration, greater TCR and BCR diversity, and a strong interferon-gamma response . In the cancer immunity cycle, KLRD1 shows positive association with immune cell trafficking but exhibits negative correlations with other steps such as immune cell priming, activation, and cancer cell killing. This dichotomy suggests that while KLRD1 may facilitate immune cell recruitment to tumors, its role in subsequent immune processes is more nuanced and potentially context-dependent.

How can single-cell analysis provide insights into KLRD1 function?

Single-cell analysis has revolutionized our understanding of KLRD1 expression patterns and functional significance across diverse cell populations. Studies have demonstrated that KLRD1 is predominantly expressed in NK cells and CD8+ exhausted T cells (CD8Tex) across multiple cancer types, with particularly high expression in NK cells . This cell type-specific distribution provides crucial context for interpreting bulk tissue analyses of KLRD1.

Single-cell approaches offer several methodological advantages for KLRD1 research:

• Cell population identification: Single-cell RNA sequencing combined with protein detection (CITE-seq) can simultaneously measure KLRD1 expression and identify specific cell subsets expressing the receptor.

• Functional state assessment: Single-cell analysis can correlate KLRD1 expression with functional states, revealing whether KLRD1+ cells exhibit cytotoxic, exhausted, or regulatory phenotypes.

• Receptor-ligand interaction mapping: By analyzing co-expression patterns of KLRD1 with NKG2 family members and HLA-E across cells, researchers can identify potential interaction networks.

• Spatial context integration: Combining single-cell transcriptomics with spatial technologies allows visualization of KLRD1+ cells within the tissue microenvironment, revealing their proximity to target cells and other immune populations.

• Trajectory analysis: Pseudotime analysis of single-cell data can track changes in KLRD1 expression during cell differentiation or activation, providing insights into its regulation.

These approaches have confirmed KLRD1's predominant expression in NK cells compared to CD8Tex cells across multiple cancer datasets, highlighting its potential as both a biomarker and therapeutic target in precision oncology .

What are the optimal protocols for using KLRD1 antibodies in flow cytometry?

Flow cytometry remains the gold standard for analyzing KLRD1 expression on specific cell populations. For optimal results, researchers should follow these methodological guidelines:

• Sample preparation:

  • For peripheral blood: Isolate PBMCs using density gradient centrifugation

  • For tissues: Create single-cell suspensions using appropriate dissociation protocols that preserve surface antigens

  • Maintain cells at 4°C throughout processing to minimize receptor internalization

• Antibody selection and panel design:

  • Choose validated anti-KLRD1 antibodies specifically designated for flow cytometry (e.g., clone 18d3 for mouse or DX22 for human samples)

  • Include markers for cell identification (CD3, CD56 for NK cells)

  • Add NKG2 family antibodies to assess heterodimer formation

  • Consider including activation markers (CD69, HLA-DR) to correlate with functional state

• Staining protocol:

  • Wash 1×10^6 cells in flow cytometry buffer (PBS with 1-2% FBS)

  • Block Fc receptors (10 minutes at 4°C)

  • Add anti-KLRD1 antibody at optimal concentration (typically 1-5 μg/ml)

  • Incubate for 30 minutes at 4°C protected from light

  • Wash twice with buffer

  • For indirect staining, add fluorochrome-conjugated secondary antibody

  • Include viability dye to exclude dead cells

• Controls:

  • Fluorescence minus one (FMO) controls

  • Isotype controls matched to antibody class and conjugate

  • Positive control (NK cells from healthy donors)

  • Negative control (cell populations known not to express KLRD1)

• Analysis strategy:

  • Gate on lymphocytes based on FSC/SSC

  • Exclude doublets and dead cells

  • Identify NK cells (CD3-CD56+) and T cell subsets (CD3+)

  • Analyze KLRD1 expression on each population

  • Report both percentage of positive cells and median fluorescence intensity

When working with fixed or frozen samples, researchers should validate antibody performance as fixation can affect epitope recognition, particularly for KLRD1 .

What are the key considerations for Western blot detection of KLRD1?

Western blot analysis of KLRD1 requires careful optimization due to its glycosylation and heterodimeric nature. Follow these methodological guidelines:

• Sample preparation:

  • Lyse cells using RIPA buffer with protease inhibitors

  • For membrane protein enrichment, consider membrane fractionation

  • KLRD1 has a molecular weight of approximately 30 kDa

  • Include positive controls (NK cell lines) and negative controls

• Protein separation and transfer:

  • Use 10-12% SDS-PAGE gels for optimal resolution

  • For detecting heterodimers, consider non-reducing conditions

  • Transfer to PVDF membrane (preferred over nitrocellulose for KLRD1)

  • Confirm transfer efficiency with reversible staining

• Antibody selection and optimization:

  • Test multiple antibodies (e.g., clone 27D7, ZG-0396F) targeting different epitopes

  • Determine optimal antibody concentration through titration (typically 1:500 to 1:2000)

  • For polyclonal antibodies, pre-absorption with immunizing peptide can confirm specificity

• Detection system optimization:

  • Use HRP-conjugated secondary antibodies with ECL detection

  • For low abundance, consider signal amplification systems

  • Validate specificity using KLRD1 knockout/knockdown samples

  • For glycosylation analysis, treat samples with glycosidases before loading

• Quantification and analysis:

  • Normalize KLRD1 expression to appropriate housekeeping proteins

  • Use densitometry software for quantitative comparisons

  • Include full blot images with molecular weight markers in publications

When interpreting results, remember that KLRD1 forms heterodimers with NKG2 family members, which may affect its migration pattern on gels and recognition by certain antibodies .

How should researchers approach immunohistochemical detection of KLRD1?

Immunohistochemical detection of KLRD1 provides valuable spatial information about its expression in tissue context. For reliable results, follow these methodological approaches:

• Tissue preparation options:

  • FFPE sections: Fix tissues in 10% neutral buffered formalin (24-48 hours)

  • Frozen sections: Snap freeze in OCT compound and cut at 5-8 μm

• Antigen retrieval optimization:

  • Test both citrate buffer (pH 6.0) and EDTA buffer (pH 9.0)

  • KLRD1 typically requires high-pH EDTA buffer for optimal retrieval

  • Optimize retrieval time (usually 20-30 minutes)

• Blocking and antibody selection:

  • Block endogenous peroxidase with 3% H₂O₂

  • Apply protein block with serum matching secondary antibody species

  • Select validated antibodies for IHC applications (e.g., LS-B14034)

  • Determine optimal antibody dilution through titration experiments

  • Consider overnight incubation at 4°C for maximum sensitivity

• Detection systems:

  • Polymer-based detection systems provide better signal-to-noise ratio

  • For low-expressing samples, consider tyramide signal amplification

  • For multiplex detection, use sequential chromogenic or fluorescent systems

• Controls and validation:

  • Positive tissue control: Include lymph node or tonsil sections

  • Technical negative control: Omit primary antibody

  • Biological negative control: Use tissues known not to express KLRD1

  • Validate staining pattern with orthogonal techniques (flow cytometry, RNA-seq)

• Analysis approaches:

  • Assess membrane/cytoplasmic staining pattern

  • Quantify using standard scoring systems (H-score, percentage positive)

  • For digital pathology, use appropriate algorithms for membrane marker detection

  • Consider dual staining with lineage markers to confirm cell types

The interpretation of KLRD1 IHC should account for its predominant expression on immune cells rather than epithelial or stromal components, particularly NK cells and specific T cell subsets .

What are common technical issues with KLRD1 antibodies and how can they be resolved?

Researchers frequently encounter technical challenges when working with KLRD1 antibodies. Here are systematic approaches to resolve common issues:

• Low or no signal in flow cytometry:

  Problem	Potential Causes	Solutions
  No KLRD1 signal	Antibody degradation, wrong clone	Use fresh aliquot, verify clone suitability
  Weak signal	Insufficient antibody, low expression	Increase concentration, check positive control
  High background	Non-specific binding	Optimize blocking, titrate antibody, use better wash
  Cell death affecting signal	Prolonged processing	Minimize processing time, add viability dye

• Multiple bands in Western blot:

  Problem	Potential Causes	Solutions
  Multiple bands	Protein degradation	Add additional protease inhibitors
  Higher MW bands	Glycosylation, heterodimers	Treat with glycosidases, use reducing conditions
  Lower MW bands	Degradation products	Optimize lysis conditions, fresh sample preparation
  Non-specific bands	Antibody cross-reactivity	Try different antibody clone, increase washing

• Poor tissue staining in IHC:

  Problem	Potential Causes	Solutions
  No staining	Ineffective antigen retrieval	Optimize pH and retrieval time
  High background	Insufficient blocking	Extend blocking time, optimize antibody dilution
  Variable results	Fixation inconsistency	Standardize fixation protocol
  Edge staining artifacts	Drying during protocol	Ensure sections remain hydrated

• Inconsistent results between experiments:

  • Use recombinant antibodies with better batch-to-batch consistency

  • Standardize protocols with detailed SOPs

  • Include consistent positive and negative controls

  • Consider using antibody cocktails prepared in larger volumes

• Discrepancies between detection methods:

  • Different epitope accessibility between techniques

  • Validate with multiple antibody clones

  • Correlate protein data with mRNA expression

  • Consider native vs. denatured protein confirmation

When reporting results, include detailed methodological information including antibody clone, catalog number, dilution, and detection method to facilitate reproducibility across laboratories .

How should researchers interpret KLRD1 expression in the context of immune profiling?

Interpreting KLRD1 expression data requires careful contextualization within the broader immune landscape. Follow these analytical approaches:

• Cellular context interpretation:

  • KLRD1 expression should always be analyzed in the context of cell phenotype

  • In NK cells: High expression typically indicates mature, functional NK cells

  • In T cells: Expression often marks specialized cytotoxic subsets

  • Consider co-expression with NKG2 family members to identify functional heterodimers

• Correlation with immune activation states:

  • Compare KLRD1 expression with activation markers (CD69, HLA-DR, CD25)

  • Assess relationship with exhaustion markers (PD-1, TIM-3, LAG-3)

  • Analyze cytokine production capacity of KLRD1+ vs. KLRD1- cells

  • Examine cytotoxic potential through granzyme/perforin expression

• Tissue-specific interpretation frameworks:

  • In tumor microenvironment: Correlate with tumor-infiltrating lymphocyte density

  • In inflammatory conditions: Assess relationship with disease activity

  • In peripheral blood: Compare with reference ranges from healthy donors

  • In lymphoid organs: Evaluate distribution patterns and co-localization

• Integrative analysis approaches:

  • Correlate KLRD1 protein expression with mRNA levels

  • Integrate with other immune checkpoint molecules

  • Analyze in context of immune cell activation and cytokine profiles

  • Assess relationship with clinical parameters and outcomes

• Visualization and reporting standards:

  • Use consistent gating strategies for flow cytometry

  • Generate heat maps showing KLRD1 correlation with other immune markers

  • Create dimensionality reduction plots (t-SNE, UMAP) to visualize KLRD1+ populations

  • Report both percentage and intensity of expression

In cancer studies, high KLRD1 expression is typically associated with increased immune activity, particularly in the C1 and C2 immune subtypes characterized by interferon-gamma signaling and heightened anti-tumor responses . These expression patterns should be interpreted in light of the complex role KLRD1 plays in both inhibitory and activating immune functions depending on its binding partners.

What approaches should be used to validate KLRD1 antibody specificity?

Validating antibody specificity is critical for reliable KLRD1 research. Implement these methodological approaches:

• Genetic validation approaches:

  • Test antibody reactivity in KLRD1 knockout/knockdown models

  • Examine staining in cell lines with confirmed KLRD1 expression vs. negative lines

  • Use CRISPR-edited cells with epitope modifications

  • Verify specificity in cells from KLRD1-deficient transgenic animals

• Biochemical validation methods:

  • Perform peptide competition assays with immunizing peptide

  • Test reactivity against recombinant KLRD1 protein

  • Conduct immunoprecipitation followed by mass spectrometry

  • Perform Western blotting with multiple antibodies targeting different epitopes

• Orthogonal technique validation:

  • Correlate protein expression with mRNA levels (qPCR, RNA-seq)

  • Compare detection across multiple techniques (flow, IHC, WB)

  • Verify expression patterns match known biology (e.g., high in NK cells)

  • Confirm expected molecular weight and post-translational modifications

• Systematic application-specific controls:

  Application	Positive Control	Negative Control	Additional Validation
  Flow Cytometry	NK cells	Granulocytes	Fluorescence minus one (FMO)
  Western Blot	NK cell lysate	HeLa cell lysate	Recombinant protein spike-in
  IHC	Tonsil, lymph node	Brain tissue	Absorption controls
  ELISA	Recombinant KLRD1	Unrelated protein	Dilution linearity test

• Cross-reactivity assessment:

  • Test against closely related family members (other C-type lectins)

  • Examine species cross-reactivity if relevant

  • Validate in tissues with complex protein mixtures

  • Check for non-specific binding to Fc receptors

• Documentation and reporting:

  • Document all validation experiments in publications

  • Provide catalog numbers and clone information

  • Include images of full blots with molecular weight markers

  • Share detailed protocols for reproducibility

This comprehensive validation approach ensures confidence in KLRD1 detection and facilitates reliable interpretation of experimental results across different research contexts .

How is KLRD1 being investigated as a potential immunotherapy target?

KLRD1 (CD94) has emerged as a promising immunotherapy target, particularly through its association with NKG2 family members. Current research is exploring several therapeutic approaches:

• Antibody-based strategies:

  • Development of monoclonal antibodies that block KLRD1-HLA-E interactions

  • Creation of bispecific antibodies targeting KLRD1 and tumor antigens

  • Antibodies targeting NKG2A (which forms heterodimers with KLRD1) have shown efficacy in preclinical models

  • These approaches aim to enhance NK cell-mediated anti-tumor activity by blocking inhibitory signals

• Small molecule development:

  • Identification of small molecules like arachidonyltrifluoromethane that modulate KLRD1 signaling

  • Design of drugs targeting the KLRD1-NKG2 interface

  • Development of protein-protein interaction inhibitors specific to KLRD1 pathways

  • Drug sensitivity analyses have identified cell division inhibitors showing enhanced efficacy in KLRD1-high tumors

• Adoptive cell therapy modifications:

  • Engineering NK cells with optimized KLRD1/NKG2 expression profiles

  • CAR-NK cells incorporating KLRD1-based recognition domains

  • T cell therapies with modified KLRD1 signaling to enhance tumor recognition

  • Ex vivo expansion protocols optimizing KLRD1+ NK cell populations

• Combination therapy approaches:

  • Combining KLRD1-targeting with established checkpoint inhibitors (anti-PD-1, anti-CTLA-4)

  • Sequential therapy approaches leveraging KLRD1 biology

  • Rational combinations based on immune subtype profiles associated with KLRD1 expression

  • Integration with conventional cancer treatments (radiation, chemotherapy)

These therapeutic strategies show particular promise in head and neck squamous cell carcinoma (HNSC), where KLRD1 has demonstrated significant prognostic value and association with immune infiltration . The complex role of KLRD1 in immune regulation requires careful consideration when developing targeted approaches, as its function varies depending on binding partners and cellular context.

What is the relationship between KLRD1 and other immune checkpoint molecules?

KLRD1 functions within a complex network of immune checkpoint molecules, with interactions that significantly impact immune response regulation. Research has revealed several important relationships:

• Co-expression patterns:
  Analysis of KLRD1-high versus KLRD1-low tumor environments has revealed differential expression of multiple immune regulatory molecules. Tumors with high KLRD1 expression frequently show upregulation of both stimulatory and inhibitory immune checkpoint genes including:

  • Stimulatory molecules: C10orf54, TMEM173, CD40LG, TMIGD2

  • Inhibitory molecules: Various checkpoint receptors

  • Chemokines: CXCL9-17 family

  • HLA molecules: HLA-A-C, PVRL2

• Functional interactions:
  KLRD1 can exhibit both inhibitory and activating functions depending on its binding partners:

  • With NKG2A: Forms inhibitory complexes that suppress NK cell activity

  • With NKG2C/E: Can form activating complexes promoting cytotoxicity

  • These complexes interact with HLA-E, influencing NK cell tolerance versus activation

• Regulatory relationships:
  KLRD1 expression is associated with distinct immune regulatory landscapes:

  • High KLRD1: Corresponds with increased leukocyte fractions, enhanced lymphocyte infiltration, greater TCR and BCR diversity

  • Low KLRD1: Associated with reduced immune diversity and altered genomic stability

  • Particularly strong associations exist with C1 and C2 immune subtypes featuring interferon-gamma signaling

• Therapeutic implications:
  Understanding KLRD1's relationship with other checkpoints suggests potential combination approaches:

  • Blocking both KLRD1/NKG2A and PD-1 pathways may provide synergistic benefits

  • Sequential targeting based on expression dynamics could optimize response

  • Immune subtype-specific approaches leveraging KLRD1 networks may enhance precision

These complex interactions highlight why KLRD1-targeting strategies must consider the broader immune checkpoint network rather than focusing on KLRD1 in isolation .

What are the emerging technologies for studying KLRD1 in the tumor microenvironment?

Advanced technologies are revolutionizing how researchers study KLRD1 in the tumor microenvironment, providing unprecedented insights into its expression, regulation, and function:

• Spatial transcriptomics and proteomics:

  • Technologies like Visium, CODEX, and IMC (Imaging Mass Cytometry) enable visualization of KLRD1 expression within the spatial context of tumors

  • These approaches reveal KLRD1+ cell distribution relative to tumor cells, vasculature, and other immune populations

  • Multiplexed approaches can simultaneously map KLRD1 with dozens of other markers to create comprehensive spatial atlases

• Single-cell multi-omics:

  • CITE-seq combines protein (including KLRD1) and transcriptome measurement at single-cell resolution

  • TEA-seq adds epigenetic profiling to understand KLRD1 regulation

  • These technologies reveal heterogeneity within KLRD1+ populations and identify novel cell states

  • Single-cell analysis has confirmed KLRD1's predominant expression in NK cells across multiple cancer types

• Live imaging technologies:

  • Intravital microscopy with fluorescently tagged antibodies allows real-time tracking of KLRD1+ cells

  • Light-sheet microscopy provides 3D visualization of KLRD1+ cell-tumor interactions

  • These approaches reveal dynamic behaviors of KLRD1+ cells in the tumor microenvironment

• Functional genomics platforms:

  • CRISPR screens in primary NK cells to identify regulators of KLRD1 expression

  • Pooled perturbation screens to map KLRD1 signaling networks

  • These techniques uncover novel molecular mechanisms controlling KLRD1 function

• Organoid co-culture systems:

  • Patient-derived tumor organoids co-cultured with KLRD1+ NK cells

  • Microfluidic systems for high-throughput assessment of KLRD1-mediated killing

  • These models provide physiologically relevant systems to study KLRD1 biology

• AI-enhanced analysis frameworks:

  • Machine learning algorithms to integrate multi-omics KLRD1 data

  • Deep learning for image analysis of KLRD1 immunohistochemistry

  • Network analysis tools to place KLRD1 in broader immune signaling contexts

These technologies are enabling researchers to move beyond correlative observations to mechanistic understanding of how KLRD1 functions within the complex tumor microenvironment, potentially informing more effective therapeutic strategies targeting this receptor system .