PDIA5 Antibody

What is PDIA5 and why is it important in research?

PDIA5, also known as protein disulfide isomerase-related protein (PDIR), is a member of the PDI gene family that exhibits chaperone-like activity. It was first identified in 1995 and is naturally expressed in the brain, liver, kidney, and lungs . PDIA5 functions as part of multi-protein complexes engaging with other chaperones to assist in folding newly synthesized proteins. It participates in protein folding and maintaining cell function by ensuring proper protein structure through disulfide bond formation . PDIA5 is particularly important in research because its overexpression is associated with poor prognosis in multiple cancer types, making it a potential biomarker and therapeutic target .

What are the key applications for PDIA5 antibodies in research?

PDIA5 antibodies are versatile tools with multiple research applications:

• Western Blotting (WB): For protein expression quantification and validation

• Immunohistochemistry (IHC): For tissue localization studies

• Immunocytochemistry (ICC): For cellular localization analysis

• Immunoprecipitation (IP): For protein-protein interaction studies

• ELISA: For quantitative protein detection

• Immunofluorescence (IF): For co-localization studies with other proteins

Most commercially available antibodies have been validated for WB and IHC applications with human samples, with some also showing reactivity with mouse and rat tissues .

How can I validate a PDIA5 antibody before using it in my experiments?

Methodological validation should include:

• Positive control testing: Use cell lines known to express PDIA5 like HepG2, HeLa, or U251 glioma cells

• Western blot analysis: Confirm a single band at approximately 60 kDa (predicted size)

• Knockdown verification: Use siRNA against PDIA5 to confirm specificity of antibody signal

• Cross-reactivity assessment: Test the antibody against related PDI family members

• Application-specific validation: For IHC, include positive control tissues like liver samples

What are the optimal conditions for using PDIA5 antibodies in Western blotting?

Based on research protocols, optimal Western blotting conditions for PDIA5 detection include:

• Sample preparation: Complete cell lysis in RIPA buffer with protease inhibitors

• Protein loading: 20-30 μg of total protein per lane

• Gel percentage: 12% SDS-PAGE for optimal separation

• Transfer conditions: Semi-dry or wet transfer to PVDF membrane

• Blocking: 5% non-fat milk or BSA in TBST for 1 hour

• Primary antibody dilution: 1:1000-1:2000 for most commercial antibodies

• Incubation time: Overnight at 4°C for optimal signal

• Secondary antibody: Anti-rabbit HRP (1:5000-1:6000)

• Detection: Enhanced chemiluminescence (ECL)

• Expected molecular weight: ~60 kDa

How should I design experiments to investigate PDIA5's role in cancer progression?

A comprehensive experimental approach should include:

• Expression analysis:

  • Compare PDIA5 expression in tumor vs. normal tissues using IHC

  • Correlate expression with clinical parameters and survival data

  • Analyze expression in different cancer grades and molecular subtypes

• Functional studies:

  • PDIA5 knockdown using siRNA or CRISPR-Cas9

  • Overexpression studies using PDIA5 expression vectors

  • Assessing proliferation, invasion, and colony formation abilities

• Mechanistic investigations:

  • Co-culture experiments with immune cells (e.g., macrophages)

  • Analysis of downstream pathways (e.g., UPR signaling via ATF6α)

  • Investigation of immune checkpoint molecule expression changes

• In vivo validation:

  • Xenograft models with PDIA5-modulated cell lines

  • Correlation with immune infiltration in animal models

How does PDIA5 influence the tumor immune microenvironment?

PDIA5 plays a multifaceted role in tumor immune regulation:

What is the relationship between PDIA5 and response to immunotherapy?

Research indicates PDIA5 may be a predictive biomarker for immunotherapy response:

• Clinical correlation data:

  • Patients with high PDIA5 expression show better response to anti-PD-1 and anti-CTLA-4 therapies

  • In anti-PD-L1 cohorts, high PDIA5 expression correlates with significant clinical survival benefits

  • Complete response rates are higher in patients with high PDIA5 expression (19.35% vs. 6.7% in low PDIA5)

• Molecular mechanisms:

  • PDIA5 positively associates with T cell-inflamed gene expression profile (GEP) and cytolytic activity (CYT)

  • These factors enhance anti-tumor activity and are associated with response to PD-1 inhibitors

  • PDIA5 correlates with CD274 (PD-L1) expression in immunotherapy cohorts

• Predictive algorithms:

  • PDIA5 expression levels can be incorporated into algorithms predicting immunotherapy response in multiple cancer types

How does PDIA5 interact with the unfolded protein response (UPR) pathway in cancer?

The interaction between PDIA5 and UPR in cancer involves:

• ATF6α activation mechanism:

  • PDIA5 cleaves disulfide bonds of UPR sensor ATF6, leading to its reduction

  • This reduction induces the UPR pathway activation

• Therapeutic resistance:

  • The PDIA5/ATF6 signaling axis correlates with resistance to chemotherapy in leukemia cells

  • This suggests a pro-survival effect of PDIA5 in cancers through UPR modulation

• Cell survival regulation:

  • UPR pathway activation via PDIA5 regulates tumor cell survival mechanisms

  • This creates a potential vulnerability that could be exploited therapeutically

What are the best approaches for analyzing PDIA5 expression in tumor samples?

Multiple complementary approaches provide comprehensive analysis:

• Transcriptomic analysis:

  • RNA-seq data from databases like TCGA and CGGA

  • Single-cell RNA sequencing to identify cell-specific expression patterns

  • qRT-PCR for targeted validation in clinical samples

• Protein expression analysis:

  • Western blotting for semi-quantitative protein level assessment

  • Immunohistochemistry for spatial distribution in tissue sections

  • Multiplex immunofluorescence for co-localization with immune cell markers

• Bioinformatic approaches:

  • TIMER 2.0 analysis for immune cell infiltration correlation

  • GSVA for gene ontology enrichment analysis

  • Correlation analysis with immune pathways and checkpoints

• Clinical correlation:

  • Integration with patient survival data using Kaplan-Meier analyses

  • Correlation with molecular subtypes and pathological grades

How can I investigate PDIA5's role in immune cell recruitment and function?

A systematic approach includes:

• Co-culture systems:

  • Cancer cells (with PDIA5 overexpression or knockdown) co-cultured with immune cells

  • Functional assays measuring migration, cytokine production, and phenotypic changes

  • Analysis of downstream signaling in both cancer and immune cells

• Flow cytometry analysis:

  • Assessment of immune cell phenotypes in PDIA5-modulated systems

  • Measurement of immune activation markers and cytokine production

  • Cell sorting for further molecular analysis

• Multiplex immunohistochemistry:

  • Simultaneous detection of PDIA5 and immune cell markers in tissue samples

  • Spatial relationship analysis between PDIA5-expressing cells and immune infiltrates

  • Correlation with clinical outcomes and tumor characteristics

• CIBERSORT analysis:

  • Computational estimation of immune cell populations in PDIA5-high vs. PDIA5-low tumors

  • Identification of specific immune cell types associated with PDIA5 expression

How can PDIA5 expression data be used to predict patient response to immunotherapy?

Implementation strategies include:

• Biomarker development:

  • Standardized IHC protocols for PDIA5 detection in clinical samples

  • Establishment of expression thresholds that correlate with therapy response

  • Integration with existing biomarkers like PD-L1 expression and tumor mutational burden

• Predictive algorithms:

  • Development of multivariate models incorporating PDIA5 expression

  • Integration with T cell-inflamed gene expression profile (GEP) and cytolytic activity (CYT)

  • Validation in prospective clinical trials

• Patient stratification strategies:

  • Higher complete response rates observed in high PDIA5 expression groups (19.35% vs. 6.7%)

  • Lower progressive disease rates in high PDIA5 groups (39.44% vs. 58.64%)

  • Development of combination therapy approaches based on PDIA5 status

What are the challenges in developing therapeutic strategies targeting PDIA5?

Key considerations include:

• Target specificity:

  • PDIA5 belongs to a family of related proteins with similar functions

  • Development of highly specific inhibitors to avoid off-target effects

  • Potential compensatory mechanisms within the PDI family

• Delivery challenges:

  • For CNS tumors like gliomas, blood-brain barrier penetration

  • Targeted delivery systems to minimize systemic toxicity

  • Combination with existing standard-of-care therapies

• Biomarker integration:

  • Identification of patient subgroups most likely to benefit

  • Development of companion diagnostics for PDIA5-targeted therapies

  • Monitoring for acquired resistance mechanisms

• Immune modulation complexity:

  • PDIA5 influences multiple immune cell types and functions

  • Potential paradoxical effects in different tumor microenvironments

  • Interaction with concurrent immunotherapies

How can I resolve non-specific binding issues with PDIA5 antibodies?

Methodological approaches to improve specificity:

• Antibody selection optimization:

  • Use antibodies targeting unique regions of PDIA5 to minimize cross-reactivity

  • Consider monoclonal antibodies for higher specificity in complex applications

  • Validate with multiple antibodies targeting different epitopes

• Protocol optimization:

  • Increase blocking concentration (5-10% BSA or milk)

  • Optimize primary antibody concentration through titration experiments

  • Increase washing duration and frequency

  • Use additives like 0.1% Tween-20 to reduce non-specific binding

• Sample preparation improvements:

  • Fresh tissue preparation and proper fixation for IHC

  • Complete protein denaturation for Western blotting

  • Appropriate antigen retrieval methods for fixed tissues

• Controls implementation:

  • Include PDIA5 knockdown samples as negative controls

  • Use recombinant PDIA5 protein as a positive control

  • Pre-absorption with immunizing peptide to confirm specificity

What are the best practices for quantifying PDIA5 expression in tissue samples?

Quantification methodologies include:

• Western blot quantification:

  • Normalization to loading controls (β-actin, GAPDH)

  • Densitometric analysis with appropriate software

  • Standard curves using recombinant PDIA5 protein for absolute quantification

• IHC scoring systems:

  • H-score methodology (intensity × percentage of positive cells)

  • Semi-quantitative scoring (0, 1+, 2+, 3+)

  • Digital image analysis for more objective quantification

  • Pathologist validation of scoring methods

• Multi-parameter analysis:

  • Co-staining with cell type-specific markers

  • Correlation with immune infiltrate markers like CD68

  • Spatial distribution analysis in different tumor regions

• Reference standards:

  • Inclusion of known positive controls in each experiment

  • Consistent imaging and analysis parameters

  • Inter-observer validation for subjective scoring methods