CD247 Human

What is CD247 and what is its genomic organization in humans?

CD247, also known as CD3ζ, CD3H, CD3Q, CD3Z, IMD25, T3Z, and TCRZ, is located on human chromosome 1q24.2. It encodes the CD3ζ protein, a 16-kDa transmembrane protein expressed primarily in natural killer (NK) and T cells. The gene is composed of 8 spliced exons with a total length of 1472 kb. Its structure includes a coding region of 492 bp and a 906 bp 3' untranslated region (3'UTR) downstream .

The protein shows remarkable evolutionary conservation, with striking similarities between human, mouse, and bird ζ chains. This high degree of conservation indicates the critical functional importance of CD247 across species, with notable interspecific conservation in both the 5' and 3'UTR regions of ζ mRNA .

How does CD247 contribute to T cell receptor complex formation and function?

CD247 plays an essential role in the assembly and function of the T cell receptor (TCR)-CD3 complex. The complete TCR-CD3 complex contains seven chains: the TCR α and β chains, plus γ, δ, ε, and two ζ chains. The assembly process begins in the endoplasmic reticulum through a series of pairwise interactions involving CD3γ, CD3δ, and CD3ε dimers that associate with TCRα and TCRβ chains. The CD3ζζ homodimers are subsequently added to form a complete complex that can be exported from the endoplasmic reticulum .

Importantly, ζ2 dimers on the T cell membrane are only detected within the intact TCR-CD3 complex, highlighting their structural dependency. The CD247-encoded ζ chain is crucial for cell surface expression of the receptor and plays a fundamental role in T lymphocyte activation through this complex .

What bioinformatics approaches are most effective for analyzing CD247 expression in single-cell RNA sequencing data?

For effective analysis of CD247 expression in single-cell RNA sequencing (scRNA-seq) data, researchers should implement a systematic bioinformatics workflow as demonstrated in recent studies:

• Quality control and preprocessing: Begin with standard quality filtering of cells (already completed in datasets like GSE141259).

• Normalization: Use specialized normalization methods like SCTransform() function in the Seurat R package to normalize the scRNA-seq data.

• Dimensionality reduction and clustering: Perform Principal Component Analysis (PCA) using the RunPCA() function, followed by UMAP embedding and Louvain clustering calculation with RunUMAP() and FindClusters() functions. Resolution settings should be optimized for your dataset (e.g., 0.9 has been effective).

• Cell type identification: Use the FindAllMarkers() function to identify markers of clusters, then classify cell types based on established databases such as CellMarker and PanglaoDB.

• CD247 expression visualization: Implement DotPlot() and FeaturePlot() functions to visualize the expression and distribution of CD247 across identified cell populations .

This approach has successfully identified CD247 expression primarily in T cells and NK cells in both human and mouse lung tissue, with dynamic expression patterns observed during different disease stages .

What statistical methods are recommended for correlating CD247 expression with clinical parameters?

When correlating CD247 expression with clinical parameters, researchers should employ multiple statistical approaches tailored to different research questions:

These methods have revealed that low CD247 expression is significantly associated with worse lung function and poorer outcomes in idiopathic pulmonary fibrosis patients.

How does CD247 expression change during disease progression in pulmonary fibrosis models?

CD247 expression follows a dynamic pattern during disease progression in pulmonary fibrosis models, particularly in bleomycin-induced mouse models:

• Acute inflammatory phase: Initially, Cd247 expression in T cells increases during the acute inflammatory stage following bleomycin injection, reflecting the enhanced T cell activation and immune response to injury .

• Transition to fibrotic phase: As the disease progresses from inflammation to fibrosis, Cd247 expression in T cells begins to decrease .

• Established fibrotic phase: In the established fibrotic stage, Cd247 expression in T cells is significantly reduced compared to both the acute inflammatory phase and normal baseline levels .

This biphasic pattern suggests that CD247 may play different roles during the evolution of pulmonary fibrosis, potentially serving as an indicator of disease stage. The downregulation in the fibrotic phase aligns with clinical observations in human idiopathic pulmonary fibrosis (IPF) patients, where reduced CD247 expression correlates with disease severity and worse outcomes .

Single-cell RNA sequencing analysis has confirmed these findings, showing that Cd247 is predominantly expressed by T cells and NK cells in the mouse lung, with clear expression changes during different disease phases after bleomycin injury .

What molecular pathways interact with CD247 in T cell function during inflammatory responses?

CD247 participates in multiple interconnected molecular pathways critical for T cell function during inflammatory responses:

• T cell receptor signaling pathway: CD247 is a fundamental component of the TCR-CD3 complex, which initiates signaling cascades upon antigen recognition. Protein-protein interaction (PPI) network analysis has identified key binding partners that connect CD247 to downstream signaling elements .

• T cell activation and differentiation pathways: Gene Ontology (GO) enrichment analysis of CD247-associated genes reveals significant involvement in T cell activation, T cell differentiation, and leukocyte chemotaxis processes .

• Immune checkpoint regulation: CD247 expression correlates with pathways involved in immune checkpoint regulation, including PD-L1 expression and PD-1 checkpoint pathways .

• Cytokine signaling networks: CD247 expression levels influence IL-17 signaling pathway and Th17 cell differentiation, suggesting a role in modulating pro-inflammatory responses .

• Immunoregulatory functions: Low CD247 expression is associated with reduced T cell general activity, decreased Th1 cell function, reduced tumor-infiltrating lymphocytes (TIL), decreased cytolytic activity, and increased T cell exhaustion. Simultaneously, low CD247 correlates with increased dendritic cell activity, elevated M2 macrophage presence, and enhanced neutrophil responses .

These findings suggest that CD247 serves as a critical node connecting TCR signaling to broader inflammatory and immune regulatory networks, with its decreased expression potentially contributing to immune dysregulation in disease states.

How effective is CD247 as a prognostic biomarker for idiopathic pulmonary fibrosis?

CD247 has demonstrated substantial potential as a prognostic biomarker for idiopathic pulmonary fibrosis (IPF) across multiple datasets and clinical parameters:

• Disease severity correlation: CD247 expression is significantly downregulated in IPF patients compared to controls and shows a strong positive correlation with diffusion capacity of the lung for carbon monoxide (Dlco% predicted) in both blood and lung tissue samples .

• Longitudinal predictive value: The positive association between CD247 expression and lung function remains consistent during follow-up at 8 and 12 months in blood samples (GSE132607 dataset), suggesting robust longitudinal predictive capability .

• Risk assessment: Low CD247 expression serves as a risk factor for Dlco% predicted decline ≥15% over 12 months (Dlco15) in blood samples, providing valuable prognostic information for disease progression .

• Endpoint prediction: Low CD247 expression significantly associates with higher rates of composite end point (CEP) events (death or decline in FVC >10% over six months) in the GSE93606 dataset, maintaining its predictive power at follow-up visits at 1, 3, 6, and 12 months .

• Survival prediction: Reduced CD247 expression significantly correlates with shorter transplant-free survival (TFS) time in the GSE27957 and GSE28042 datasets .

• Predictive accuracy: Time-dependent ROC curve analysis revealed areas under the curve (AUC) of 0.736 at 1 year and 0.741 at 2 years for composite endpoint prediction. For transplant-free survival, AUCs were 0.889, 0.787, and 0.702 at 1, 2, and 3 years respectively in the GSE27957 dataset .

These findings collectively suggest that CD247 expression in blood samples provides valuable prognostic information for IPF patients, potentially aiding in risk stratification and treatment planning.

What methodological considerations should be addressed when validating CD247 as a biomarker in clinical samples?

When validating CD247 as a biomarker in clinical samples, researchers should address several key methodological considerations:

• Sample type selection: While CD247 has shown prognostic value in blood samples, its performance varies across sample types. For example, CD247 was not significantly associated with mortality in bronchoalveolar lavage fluid (BALF) samples in the GSE70866 dataset . Researchers should carefully select and justify sample types based on clinical accessibility and marker performance.

• Standardized expression measurement: Implement consistent techniques for measuring CD247 expression, whether using microarray, RT-PCR, or RNA sequencing. Consider platform-specific normalization techniques to ensure comparability across studies.

• Cutoff value determination: Use objective methods such as the Youden index or R package "survminer" to establish optimal cutoff values for categorizing high versus low CD247 expression .

• Confounding factors assessment: Account for potential variables that might affect CD247 expression, including demographic factors, comorbidities, medications, and immune status. These should be systematically recorded and adjusted for in analysis.

• Longitudinal validation: As demonstrated in the GSE132607 and GSE93606 datasets, validate biomarker performance across multiple time points to confirm consistent prognostic value .

• Multivariate models: Develop and validate multivariate models that incorporate CD247 along with established clinical predictors to demonstrate added predictive value over current standards.

• External validation: Test CD247's performance in independent cohorts with different demographic characteristics to establish generalizability of findings.

• Biological context integration: Consider CD247's functional role in immune cell populations when interpreting expression values, as cell type composition can influence aggregate expression measures in complex samples .

By addressing these methodological considerations, researchers can enhance the robustness and clinical utility of CD247 as a biomarker for disease severity and prognosis.

How can protein-protein interaction networks inform therapeutic targeting of CD247-related pathways?

Protein-protein interaction (PPI) networks provide valuable insights for therapeutic targeting of CD247-related pathways:

• Identification of key interaction partners: STRING database analysis has revealed experimentally determined CD247-binding proteins that form an interconnected network (average node degree: 3.71, PPI enrichment p-value: <1.62e-16) . These binding partners represent potential alternative targets when direct CD247 modulation is challenging.

• Pathway enrichment across the network: The CD247-centered PPI network shows significant enrichment in critical immune pathways including T cell receptor signaling, Th17 cell differentiation, and PD-1/PD-L1 checkpoint regulation . These pathway connections suggest potential for combination therapies targeting multiple nodes in the network.

• Co-expression correlation strategies: The Multi-Experiment Matrix (MEM) database has confirmed strong co-expression correlations between CD247 and its network genes across different tissue types (blood, lung tissue, and BALF) . Therapeutics could potentially target highly correlated genes when direct CD247 modulation is not feasible.

• Differential network analysis in disease states: Comparing PPI networks between patients with high versus low CD247 expression reveals differential activation of inflammatory and immune pathways . This suggests that therapeutic approaches may need to be tailored based on a patient's CD247 expression status.

• Cell type-specific targeting opportunities: Single-cell RNA sequencing has demonstrated that CD247 is predominantly expressed in T cells and NK cells , suggesting these cell populations as primary targets for CD247-centered therapeutic strategies.

By integrating PPI network analysis with expression data across different tissues and disease states, researchers can identify critical nodes and pathways for therapeutic intervention that may restore normal immune function in conditions with dysregulated CD247 expression.

What are the challenges in translating CD247 research findings from animal models to human clinical applications?

Translating CD247 research findings from animal models to human clinical applications presents several significant challenges:

• Species-specific expression patterns: While CD247 shows high evolutionary conservation, there are species-specific differences in expression regulation and function. For example, in mouse models, Cd247 expression in T cells increases during acute inflammation after bleomycin injection but decreases in the fibrotic stage . Confirming similar dynamic patterns in human disease progression requires careful validation.

• Temporal dynamics of expression: Animal models allow for precise temporal tracking of CD247 expression changes throughout disease development, which is challenging to replicate in human studies where patients typically present at varied disease stages. This complicates determination of whether CD247 changes are causes or consequences of disease progression.

• Sample accessibility limitations: In animal models, researchers can directly access lung tissue at multiple time points, whereas human studies are often limited to peripheral blood samples or occasional lung biopsies. The GSE27957 dataset demonstrated that while blood CD247 measurements show prognostic value, tissue-specific expression may provide different insights .

• Complex immune microenvironment: CD247 functions within a complex immune network that may differ between species. The ssGSEA and CIBERSORT analyses in human samples showed that low CD247 expression correlates with lower T cell activity but higher inflammation from other immune cells . This complex interplay may not be fully recapitulated in animal models.

• Therapeutic targeting challenges: The critical role of CD247 in normal immune function means that therapeutic modulation must be precisely calibrated to restore normal levels without causing immunosuppression or hyperactivation. Determining this therapeutic window requires careful translation from preclinical to clinical studies.

• Biomarker threshold determination: While animal models can help establish conceptual relationships between CD247 and disease outcomes, clinical implementation requires establishment of standardized thresholds with high sensitivity and specificity in human populations, accounting for normal variation and technical factors.

Addressing these challenges requires integrated approaches combining mechanistic studies in animal models with careful validation in well-characterized human cohorts across multiple timepoints and tissue types.