KLRD1 Human

What cellular populations express KLRD1 and how is this best determined methodologically?

KLRD1 is primarily expressed on natural killer (NK) cells, which represent a significant component of the innate immune system. The expression of KLRD1 has been methodologically determined through various techniques including flow cytometry, RNA sequencing, and single-cell RNA sequencing .

To accurately determine KLRD1-expressing cells, researchers should consider:

• Flow cytometry using anti-CD94 antibodies for protein-level detection

• RNA-based methods (qRT-PCR, RNA-seq) for transcript quantification

• Cell mixture deconvolution from whole blood transcriptome data, which has been successfully used to estimate NK cell proportions in influenza studies

• Single-cell RNA sequencing to precisely identify specific immune cell subsets expressing KLRD1 within complex tissues

Cross-validation with multiple NK cell markers improves reliability when identifying KLRD1-expressing populations in complex samples.

What are the key protein interactions of KLRD1/CD94 and their functional significance?

KLRD1/CD94 forms heterodimeric complexes with NKG2 family members, creating receptors that regulate NK cell activity. Key protein interactions include:

• NKG2 family members: CD94 preferentially pairs with KLRC3 (encoding NKG2E and NKG2H), as demonstrated by significant correlation between KLRD1 and KLRC3 expression (r = 0.75, P = 1.3e−3) .

• HLA-E: The CD94/NKG2 complex recognizes HLA-E molecules on target cells, allowing NK cells to monitor MHC class I expression. In rhinovirus infection studies, KLRD1 expression significantly correlated with HLA-E expression (r = 0.76, p = 0.0028) .

• Cytotoxic machinery components: KLRD1 expression correlates with:

  • CCL5 (r = 0.78, P = 6e−4), released during cytotoxic granule exocytosis

  • Perforin (PRF1) and multiple granzymes (GZMA, GZMB, GZMH), which are critical for target cell killing

These interactions collectively enable NK cells to recognize and eliminate aberrant cells while sparing healthy ones, representing a crucial mechanism for immune surveillance.

How is KLRD1 expression regulated during viral infections?

KLRD1 expression undergoes dynamic regulation during viral infections, exhibiting tissue-specific patterns:

• Blood compartment: KLRD1 expression significantly decreases in peripheral blood within the first 48 hours of influenza infection in both discovery and validation cohorts . This reduction may reflect trafficking of KLRD1-expressing NK cells to infection sites.

• Respiratory epithelium: Conversely, KLRD1 expression significantly increases in nasal epithelium during infection with human rhinovirus (HRV) or respiratory syncytial virus (RSV) (effect size = 0.77, P = 0.0011) .

• Temporal dynamics: Expression changes occur rapidly after infection, with significant differences detectable within 8 hours post-infection .

Methodologically, studying these dynamics requires:

• Longitudinal sampling before and during infection

• Multi-tissue analysis (blood and infection sites)

• Integration of transcriptomic data with cellular analysis

• Statistical approaches accounting for individual variability

These expression patterns suggest that early responses by KLRD1-expressing cells at infection sites may help control viral spread and minimize disease severity.

What statistical approaches are recommended for analyzing KLRD1 expression data?

Rigorous statistical analysis of KLRD1 expression requires multi-faceted approaches:

These statistical frameworks ensure robust, reproducible findings when analyzing KLRD1 in clinical and research contexts.

How does KLRD1 expression vary across normal human tissues?

KLRD1 expression shows distinct patterns across human tissues, with significant implications for research design:

• Immune-rich tissues show highest expression:

  • Higher expression in lymphoid tissues (spleen, lymph nodes)

  • Moderate expression in tissues with significant resident immune populations (liver, lung)

  • Lower expression in immune-privileged sites

• Methodological considerations for tissue analysis:

  • RNA-seq data from GTEx provides reference expression levels across normal tissues

  • Tissue-specific analysis requires accounting for resident immune cell populations

  • Single-cell approaches help distinguish KLRD1 expression in tissue-resident vs. circulating immune cells

• Context-dependent expression:

  • Expression can change dramatically during inflammation or infection

  • Tissue-specific regulation may reflect specialized functions in different microenvironments

When designing tissue-specific studies, researchers should consider both baseline expression and potential changes during pathological states, with appropriate tissue-matched controls.

What is the role of KLRD1 in viral infection susceptibility, and how can this be experimentally validated?

KLRD1 plays a critical role in viral infection susceptibility, particularly for respiratory viruses:

• Predictive biomarker potential:

  • Lower baseline expression of KLRD1 predicts increased susceptibility to symptomatic influenza infection

  • KLRD1 expression differentiated between symptomatic shedders and asymptomatic nonshedders with high accuracy (AUROC = 0.91, 95% CI 0.75–1.0)

• Inverse correlation with disease severity:

  • Baseline KLRD1 expression significantly inversely correlates with total symptom scores in influenza (r = −0.79, P = 5.2e−4)

  • Similar inverse correlation observed in rhinovirus infection (r = −0.6, P = 0.031)

• Experimental validation approaches:

  • Human challenge studies with controlled viral inoculation

  • Longitudinal sampling before, during, and after infection

  • Ex vivo functional assays with sorted KLRD1-high vs. KLRD1-low NK cells

  • Genetic manipulation studies using CRISPR-Cas9 to modify KLRD1 expression

  • Animal models with humanized immune systems

These findings support a model where early responses by KLRD1-expressing NK cells may help control viral infections, with potential applications for identifying high-risk individuals and developing targeted interventions.

How does KLRD1 expression correlate with immune cell infiltration in the tumor microenvironment?

KLRD1 expression serves as a key indicator of specific immune infiltration patterns in the tumor microenvironment:

• Association with NK cell infiltration:

  • KLRD1 expression primarily reflects NK cell presence in tumors

  • Higher KLRD1 in head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), and kidney renal clear cell carcinoma (KIRC) suggests greater NK cell infiltration

• Relationship with cytotoxic activity:

  • KLRD1 expression correlates with cytotoxic granule-associated genes (CCL5, PRF1, GZMA, GZMB, GZMH)

  • This correlation suggests functional cytotoxic activity within the tumor microenvironment

• Methodological approaches for analysis:

  • Computational deconvolution using CIBERSORT, TIMER, and ESTIMATE algorithms

  • Integration of gene expression with spatial information through multiplex immunohistochemistry

  • Single-cell RNA sequencing to characterize KLRD1+ cell subpopulations within tumors

• Clinical implications:

  • Higher KLRD1 expression correlates with better prognosis in several cancers, likely reflecting effective immune surveillance

  • KLRD1 expression patterns may help identify patients likely to respond to immunotherapies

Understanding these relationships can inform therapeutic strategies aimed at enhancing NK cell infiltration and function in the tumor microenvironment.

What are the differential expression patterns of KLRD1 across cancer types and their clinical significance?

KLRD1 exhibits remarkable heterogeneity in expression across cancer types with important clinical implications:

• Cancer types with decreased KLRD1 expression compared to normal tissues:

  • Breast invasive carcinoma (BRCA)

  • Cholangiocarcinoma (CHOL)

  • Colon adenocarcinoma (COAD)

  • Liver hepatocellular carcinoma (LIHC)

  • Lung adenocarcinoma (LUAD)

  • Lung squamous cell carcinoma (LUSC)

  • Prostate adenocarcinoma (PRAD)

  • Thyroid carcinoma (THCA)

  • Uterine corpus endometrial carcinoma (UCEC)

• Cancer types with increased KLRD1 expression compared to normal tissues:

  • Head and neck squamous cell carcinoma (HNSC)

  • Kidney chromophobe (KICH)

  • Kidney renal clear cell carcinoma (KIRC)

• Prognostic significance:

  • KLRD1 acts as a protective factor in multiple cancers including:

    • Adrenocortical carcinoma (ACC)

    • Cervical squamous cell carcinoma (CESC)

    • Head and neck squamous cell carcinoma (HNSC)

    • Low-grade glioma (LGG)

    • Skin cutaneous melanoma (SKCM)

• Independent prognostic value:

  • In HNSC, KLRD1 remains an independent predictor of survival in multivariate analysis after adjusting for M stage, radiation therapy, and age

  • This independence from standard clinical factors enhances its potential utility in prognostic models

These expression patterns likely reflect the complex interplay between tumor immunogenicity, immune infiltration, and cancer-specific immune evasion mechanisms, with significant implications for immunotherapy approaches.

How can single-cell RNA sequencing be optimally utilized to study KLRD1 expression in complex tissues?

Single-cell RNA sequencing (scRNA-seq) offers unprecedented resolution for studying KLRD1 expression:

• Sample preparation considerations:

  • Fresh tissue processing preferred over frozen when possible

  • Enzymatic dissociation protocols should be optimized to preserve NK cell viability

  • Consider enrichment strategies for rare KLRD1-expressing populations

• Platform selection:

  • Droplet-based methods (10x Genomics) for surveying thousands of cells

  • Plate-based methods for deeper sequencing of specific populations

  • CITE-seq for simultaneous protein (CD94) and transcript (KLRD1) measurement

• Data processing pipeline:

  • Filtering, standardization, and normalization of raw data

  • Selection of highly variable genes

  • Linear dimensionality reduction followed by clustering to identify cellular subpopulations

• Analysis strategies:

  • Integration with reference datasets to annotate cell types

  • Trajectory analysis to understand differentiation pathways

  • Receptor-ligand interaction analysis between KLRD1+ cells and other cells

  • Spatial reconstruction to infer cellular neighborhoods

• Validation approaches:

  • Flow cytometry confirmation of identified populations

  • Functional assays on sorted populations based on scRNA-seq findings

  • Spatial techniques (Visium, MERFISH) to validate cellular interactions

Multiple scRNA-seq datasets (LIHC_GSE140228, HNSC_GSE139324, NSCLC_GSE127465) have been successfully analyzed to characterize KLRD1-expressing cells in tumor samples , demonstrating the power of this approach.

What experimental designs are most effective for studying the functional role of KLRD1 in immune responses?

Comprehensive investigation of KLRD1's functional role requires multi-layered experimental designs:

• In vitro functional studies:

  • CRISPR-Cas9 mediated KLRD1 knockout in NK cells

  • Lentiviral overexpression systems for gain-of-function studies

  • Co-culture systems with target cells expressing variable levels of HLA-E

  • Cytotoxicity assays measuring target cell killing efficiency

  • Cytokine production assays following receptor engagement

• Ex vivo approaches:

  • Isolation and functional characterization of KLRD1-high vs. KLRD1-low NK cells

  • Correlation of KLRD1 expression with functional outputs (degranulation, cytokine production)

  • Antibody blocking studies to interrupt CD94/NKG2 interactions

• In vivo models:

  • Humanized mouse models receiving KLRD1-modified NK cells

  • Viral challenge studies with measurement of viral load and pathology

  • Sequential sampling to track dynamic changes in KLRD1 expression

• Human challenge studies:

  • Controlled viral infections in volunteers with varied KLRD1 expression

  • Frequent sampling of blood and mucosal surfaces

  • Correlation of KLRD1 expression with clinical outcomes and immune parameters

• Multi-omic integration:

  • Correlation of KLRD1 expression with epigenetic modifications

  • Chromatin accessibility analysis at the KLRD1 locus during immune responses

  • Proteomic analysis of KLRD1/CD94 interactome

These complementary approaches can establish causal relationships between KLRD1 expression and functional outcomes, moving beyond the correlative findings currently available.

How can KLRD1 be leveraged as a biomarker for infectious disease susceptibility?

KLRD1 shows significant promise as a biomarker for infectious disease susceptibility:

• Predictive capability:

  • Baseline KLRD1 expression differentiates between individuals who will develop symptomatic vs. asymptomatic infection following viral challenge

  • High diagnostic accuracy (AUROC = 0.91, 95% CI 0.75–1.0) demonstrated in validation cohorts

• Methodological implementation:

  • Blood-based assessment using qPCR or targeted RNA-seq panels

  • Development of standardized assays with established reference ranges

  • Integration with other immune parameters for improved predictive power

  • Longitudinal monitoring in high-risk populations

• Clinical applications:

  • Risk stratification during epidemic/pandemic outbreaks

  • Prioritization for prophylactic interventions

  • Personalized vaccination strategies

  • Early targeting of antiviral therapies

• Validation requirements:

  • Large prospective cohorts with diverse demographics

  • Multiple viral pathogens beyond influenza

  • Real-world implementation studies

  • Cost-effectiveness analysis for healthcare systems

The consistent inverse correlation between KLRD1 expression and symptom severity across different respiratory viruses (influenza and rhinovirus) suggests broad applicability as a biomarker for viral susceptibility.

What approaches should be used to investigate KLRD1 as a potential target for cancer immunotherapy?

Investigating KLRD1 as an immunotherapy target requires systematic exploration:

• Target validation strategies:

  • Comprehensive expression analysis across tumor types and patient subgroups

  • Correlation with established immuno-oncology biomarkers (PD-L1, TMB, MSI)

  • Functional studies demonstrating anti-tumor effects of KLRD1+ cells

  • Mechanistic studies of KLRD1/CD94 regulation in the tumor microenvironment

• Therapeutic modalities to consider:

  • Agonistic antibodies targeting the CD94/NKG2C activating complex

  • Antagonistic antibodies blocking inhibitory CD94/NKG2A interactions

  • Adoptive cell therapy with KLRD1-engineered NK cells

  • Bispecific engagers redirecting KLRD1+ cells to tumors

• Preclinical model development:

  • Humanized mouse models with reconstituted human NK cells

  • Patient-derived xenografts with human immune components

  • Syngeneic models expressing human KLRD1 orthologs

  • Ex vivo tumor slice cultures with autologous immune cells

• Biomarker development:

  • KLRD1 expression profiling in tumors and blood

  • Assessment of HLA-E expression on tumor cells

  • NK cell functional assays predicting response

  • Multiplex immunohistochemistry panels including KLRD1/CD94

The prognostic significance of KLRD1 in multiple cancer types (ACC, CESC, HNSC, LGG, SKCM) provides a strong rationale for exploring its therapeutic potential, particularly in cancers where it acts as a protective factor.