CD274 Human

What is CD274 and what are its alternative names in scientific literature?

CD274, also known as Programmed death-ligand 1 (PD-L1), is alternatively referred to as cluster of differentiation 274 or B7 homolog 1 (B7-H1) in scientific literature. It is a 40 kDa type 1 transmembrane protein encoded by the CD274 gene in humans. This protein plays a critical role in immune system regulation, particularly in suppressing immune responses during specific physiological and pathological conditions such as pregnancy, tissue allografts, autoimmune disease, and various disease states including hepatitis . The molecule functions primarily by binding to its receptor, PD-1, which is found on activated T cells, B cells, and myeloid cells, thereby modulating activation or inhibition of immune responses .

How does CD274 function in the immune system and what is its mechanism of action?

CD274 (PD-L1) functions as a key immune checkpoint molecule that helps maintain immune homeostasis. When the PD-1 receptor on immune cells interacts with PD-L1, it transmits an inhibitory signal that reduces the proliferation of CD8+ T cells in lymph nodes. Additionally, PD-1 can control the accumulation of foreign antigen-specific T cells through apoptosis, mediated by downregulation of the Bcl-2 gene .

The mechanism involves:

• Foreign antigens accumulating in lymph nodes or spleen

• This triggers proliferation of antigen-specific CD8+ T cells

• Formation of PD-1/PD-L1 or B7.1/PD-L1 complexes

• Transmission of inhibitory signals

• Reduced T cell proliferation and potential apoptosis

This process is crucial in preventing excessive immune responses that could lead to tissue damage while allowing appropriate responses to pathogens and tumors.

What is the significance of CD274 copy number variations in cancer immunotherapy response?

CD274 copy number (CN) variations significantly impact patient response to immune checkpoint inhibitors (ICIs). Research has demonstrated that:

These findings suggest that CD274 CN assessment could serve as an important biomarker for patient selection and treatment optimization in cancer immunotherapy.

How do CD274 mRNA expression levels correlate with PD-L1 protein expression and clinical outcomes?

CD274 mRNA expression levels demonstrate strong correlation with PD-L1 protein expression and clinical outcomes in cancer patients. Studies using quantitative RT-PCR have found:

These findings suggest that CD274 mRNA quantification could potentially serve as an alternative or complementary approach to PD-L1 immunohistochemistry for predicting response to immune checkpoint inhibitors.

What methods are available for detecting CD274/PD-L1 expression, and what are their comparative advantages?

Multiple methods exist for detecting CD274/PD-L1 expression, each with distinct advantages:

Research has shown that CD274 mRNA levels measured by qRT-PCR closely correlate with PD-L1 IHC measured using FDA-approved assays , suggesting complementary roles for these techniques in research and clinical settings.

What is the significance of structural variations in CD274 UTR regions and how can they be detected?

Structural variations (SVs) in CD274 untranslated regions (UTRs) represent emerging biomarkers for immunotherapy response. These rare mutations in the 5' and 3'-UTR of the CD274 gene can induce immune escape mechanisms and predict response to immune checkpoint inhibitors.

Key findings include:

• SVs in CD274 UTR regions have been detected in various cancers with an incidence of 0.36% in a Chinese patient cohort (n=2249)

• The prevalence is significantly higher in liver and breast cancers compared to TCGA (The Cancer Genome Atlas) data

• These SVs can be detected using advanced liquid biopsy techniques such as cSMART2.0 technology, which offers higher capture efficiency and homogeneity

• Liquid biopsy results from circulating tumor DNA (ctDNA) show 100% concordance with genomic DNA results from tumor tissue detection

• Patients carrying SVs in CD274 UTR regions without driver gene mutations have shown response to immune checkpoint inhibitors

This research demonstrates that liquid biopsy can offer sensitive and accurate detection of these rare structural variants, potentially benefiting patients with advanced disease when tissue samples are unavailable.

How does intra-tumor heterogeneity impact PD-L1 expression assessment and what strategies can mitigate this challenge?

Intra-tumor heterogeneity poses significant challenges for accurate PD-L1 expression assessment, as highlighted by research showing variability in expression across different sample locations from the same tumor . This heterogeneity can lead to inconsistent results and potentially inappropriate treatment decisions.

Strategies to address this challenge include:

• Multiple sampling from different tumor regions when feasible

• Utilizing larger tissue specimens when available

• Complementing IHC with alternative detection methods such as mRNA expression analysis

• Implementing standardized scoring systems with clear cutoffs

• Second evaluation of PD-L1 expression by IHC in complex cases to address intra- and inter-observer discrepancies

• Considering digital pathology and machine learning approaches for more objective assessment

• Integrating multiple biomarkers (e.g., CD274 copy number, TMB) for a more comprehensive evaluation

Researchers should be aware that a single biopsy may not represent the entire tumor's PD-L1 status, and results should be interpreted with appropriate caution.

What is the relationship between CD274 copy number alterations and tumor mutational burden (TMB) in predicting immunotherapy response?

CD274 copy number alterations and tumor mutational burden (TMB) demonstrate an additive effect in predicting response to immune checkpoint inhibitors, functioning as complementary biomarkers:

This relationship suggests that immune evasion potential is higher in the CD274 CN high group, particularly when combined with high neoantigen burden as manifested in TMB high tumors. These findings support the value of assessing both biomarkers for optimal patient selection and treatment planning.

What are the optimal experimental conditions for recombinant human PD-L1 protein in binding assays?

For optimal experimental conditions using recombinant human PD-L1 protein in binding assays, researchers should consider:

• Immobilized PD-L1, His, Human at a concentration of 2 μg/mL (100 μl/well) can effectively bind PD-1 Fc Chimera with a linear range of 24-390 ng/mL

• Recombinant Human PD-L1(B7-H1) Fc Chimera produced in CHO cells is a 457 amino acid polypeptide chain with a molecular mass of 70-72 kDa as analyzed by reducing SDS-PAGE

• The protein should be obtained using chromatographic techniques to ensure purity and biological activity

• Validation of biological activity before experimental use is crucial for reliable results

• Buffer conditions, pH, and temperature should be optimized based on specific experimental goals

• Positive and negative controls should be included to validate binding specificity

These parameters provide a starting point for researchers designing PD-L1 binding assays, though optimization may be required for specific experimental systems.

How can liquid biopsy techniques be optimized for detecting CD274 structural variations?

Optimizing liquid biopsy techniques for detecting CD274 structural variations requires careful consideration of several methodological aspects:

• Technology Selection: Advanced technologies like cSMART2.0 have demonstrated higher capture efficiency and homogeneity for rare structural variants compared to conventional methods

• Sample Processing:

  • Rapid plasma separation after blood collection (within 2 hours) to minimize DNA degradation

  • Use of preservative tubes specifically designed for circulating DNA

  • Standardized DNA extraction protocols optimized for fragmented DNA

• Assay Design:

  • Custom capture probes targeting both 5' and 3' UTR regions of CD274

  • Inclusion of sufficient coverage of flanking regions to detect structural breaks

  • Molecular barcoding to reduce sequencing errors and improve sensitivity

• Validation Approach:

  • Confirmation with orthogonal methods (tissue testing, IHC, mIF) as demonstrated in studies showing 100% concordance between ctDNA and gDNA results

  • Establishment of analytical sensitivity and specificity thresholds

• Data Analysis:

  • Specialized bioinformatics pipelines for structural variant detection

  • Application of filters to distinguish true variants from sequencing artifacts

  • Integration with clinical data for interpretation

Implementation of these optimized approaches can enhance detection sensitivity for rare CD274 structural variants, particularly benefiting patients with advanced disease when tissue samples are unavailable.

What are the best practices for quantifying CD274 mRNA expression in clinical samples?

Quantifying CD274 mRNA expression in clinical samples requires rigorous methodological approaches to ensure reliable and reproducible results:

• Sample Selection and Handling:

  • Use formalin-fixed, paraffin-embedded (FFPE) tissue blocks with sufficient tumor content

  • Careful macrodissection to enrich for tumor cells when necessary

  • Standardized RNA extraction protocols optimized for FFPE material

• Primer and Probe Design:

  • Multiple primer sets targeting different exon junctions (exon 1-2, 3-4, and 5-6) provide comprehensive coverage

  • Use of TaqMan® probes rather than intercalating dyes for increased specificity

  • Inclusion of appropriate housekeeping genes for normalization

• Methodological Considerations:

  • Perform reverse transcription under standardized conditions

  • Include no-template and no-RT controls to detect contamination

  • Run samples in triplicate to ensure reproducibility

  • Include standard curves for absolute quantification when possible

• Data Analysis and Interpretation:

  • Determine optimal cutoff values based on correlation with clinical outcomes

  • In gastric cancer, a cutoff of 0.0722 effectively stratified responders from non-responders

  • In urothelial carcinoma, a cutoff of 0.0480 demonstrated significant association with treatment response

• Validation:

  • Correlation with PD-L1 protein expression by IHC

  • Association with clinical outcomes including objective response rate and progression-free survival

These best practices can help researchers obtain reliable CD274 mRNA expression data that correlates with protein expression and predicts clinical outcomes in immunotherapy-treated patients.

What are the challenges in harmonizing different PD-L1 assessment methods across research laboratories?

Harmonization of PD-L1 assessment methods across research laboratories faces several significant challenges:

• Antibody Clone Variability:

  • Different commercial antibodies with varying sensitivity and specificity

  • Each antibody may have unique binding epitopes and staining patterns

• Scoring System Inconsistencies:

  • Multiple scoring systems exist (Tumor Proportion Score, Combined Positive Score, etc.)

  • Different cutoff values for positivity across cancer types and drug approvals

• Technical Variability:

  • Differences in fixation protocols affecting epitope preservation

  • Variations in staining platforms and detection systems

  • Antigen retrieval methods impacting staining intensity

• Interpretation Subjectivity:

  • Intra- and inter-observer discrepancies requiring second evaluations in complex cases

  • Challenges in distinguishing tumor cells from immune cells in some samples

• Sample Heterogeneity:

  • Expression heterogeneity among different sample locations

  • Variations between primary tumors and metastatic sites

  • Differences between archival and fresh biopsies

Potential solutions include:

• Development of standardized protocols with detailed SOPs

• Regular proficiency testing among laboratories

• Use of digital pathology with validated algorithms

• Integration of complementary methodologies (IHC, mRNA, genomic)

• Development of reference standards for calibration

Addressing these challenges is essential for reliable biomarker assessment and appropriate patient selection for immunotherapy across different research settings.

How do CD274 copy number alterations influence immune cell infiltration and the tumor microenvironment?

CD274 copy number alterations significantly impact immune cell infiltration and the tumor microenvironment, with important implications for immunotherapy response:

• Immune Cell Recruitment and Activation:

  • CD274 amplification can lead to overexpression of PD-L1, creating an immunosuppressive environment

  • Despite this suppression, tumors with CD274 gains often show increased immune cell infiltration, particularly CD8+ T cells

  • This creates a paradoxical situation where abundant but functionally suppressed T cells are present

• Correlation with Other Immune Markers:

  • CD274 CN gains are significantly enriched in TMB-High tumors (≥10 mutations/Mb)

  • This association suggests that high mutational burden may drive immune recognition, while CD274 amplification represents a counterbalancing immune evasion mechanism

• Response to Immune Checkpoint Blockade:

  • Tumors with CD274 CN gains (≥ specimen ploidy +2) show significantly better response to immune checkpoint inhibitors

  • This improved response likely results from releasing T cell suppression in an already primed immune microenvironment

  • The combination of CD274 CN gain and high TMB creates optimal conditions for immunotherapy response, with median OS of 24.9 months compared to 7.7 months in patients with both markers low

• Potential Mechanisms:

  • CD274 amplification may initially develop as an immune evasion strategy in immunologically "hot" tumors

  • Blocking the PD-1/PD-L1 axis can effectively reactivate suppressed T cells already present in the tumor microenvironment

  • The effectiveness of this approach explains why CD274 CN gain serves as a positive predictor of immunotherapy response

These findings highlight the complex relationship between genomic alterations, immune regulation, and clinical outcomes in cancer immunotherapy.

What are the emerging technologies for detecting PD-L1 expression beyond traditional immunohistochemistry?

Several emerging technologies are expanding PD-L1 detection capabilities beyond traditional immunohistochemistry:

• Digital Multiplex Immunohistochemistry/Immunofluorescence:

  • Allows simultaneous detection of multiple markers including PD-L1

  • Preserves spatial context while quantifying co-expression patterns

  • Enables detailed characterization of the tumor microenvironment

  • Validated in studies comparing with conventional IHC and genomic methods

• Mass Cytometry/Imaging Mass Cytometry:

  • Uses metal-tagged antibodies and mass spectrometry for highly multiplexed detection

  • Can simultaneously measure >40 parameters including PD-L1 expression

  • Provides single-cell resolution with spatial information

  • Eliminates spectral overlap issues of fluorescence-based methods

• Transcriptomic Approaches:

  • Targeted mRNA quantification using qRT-PCR with multiple exon-spanning primers

  • NanoString nCounter technology for direct digital counting of mRNA molecules

  • RNA sequencing for comprehensive transcriptome analysis

  • Spatial transcriptomics for location-specific expression profiling

• Genomic Profiling:

  • Next-generation sequencing for CD274 copy number analysis

  • Detection of structural variations in UTR regions using liquid biopsy approaches

  • Integration with other genomic markers (TMB, MSI status)

• Circulating Biomarkers:

  • Liquid biopsy techniques like cSMART2.0 for detecting CD274 structural variations in ctDNA

  • Analysis of soluble PD-L1 in patient serum

  • Examination of PD-L1 expression on circulating tumor cells or exosomes

These technologies are expanding our understanding of PD-L1 biology and improving biomarker strategies for immunotherapy patient selection and monitoring.