ITIH3 Antibody

What is ITIH3 and what are its primary biological functions?

ITIH3 is a heavy chain subunit of the alpha trypsin inhibitor complex precursor that plays an essential role in stabilizing the extracellular matrix by preventing hyaluronic acid depolymerization . The protein is encoded by the ITIH3 gene and functions as part of the inter-alpha-trypsin inhibitor (ITI) family. These proteins are known to be involved in various physiological processes, including inflammation, wound healing, and maintenance of tissue integrity.

Research has demonstrated that ITIH3 may serve an important role in tumor progression . Studies have shown that ITIH family genes are markedly downregulated in various human solid tumors, including colon, breast, and lung cancer, suggesting their potential role as tumor suppressor genes . This makes ITIH3 a protein of significant interest in cancer research, particularly in understanding tumor development mechanisms.

What are the standard methods for detecting ITIH3 in biological samples?

Detection of ITIH3 in biological samples typically employs several complementary techniques:

• Western Blotting: This technique remains the gold standard for ITIH3 protein expression analysis. Researchers commonly use anti-ITIH3 antibodies with appropriate loading controls such as GAPDH or Actin. For example, studies investigating ITIH3 in ovarian cancer cell lines used western blotting to assess relative protein expression levels in SKOV3, A2780, OVCAR3, and CAOV3 cells .

• Immunohistochemistry (IHC): For tissue samples, IHC is frequently employed using specialized antibodies such as goat-anti-ITI-H3 (L-15) antibody (1:200; cat. no. sc-33949; Santa Cruz Biotechnology, Inc.) . The protocol typically involves:

  • Fixing tissue sections with 4% paraformaldehyde at room temperature for 48 hours

  • Embedding in paraffin and slicing 4 μm sections

  • Incubating with primary antibody for 1 hour at room temperature

  • Using secondary antibodies (e.g., anti-goat, 1:500) for 20 minutes

  • Scoring based on both staining intensity and proportion of positively stained cells

• ELISA: For quantitative assessment of ITIH3 in serum samples, as demonstrated in studies examining ITIH3 as a biomarker in myasthenia gravis .

• Mass Spectrometry: Proteomic approaches like iTRAQ (isobaric tag for relative and absolute quantitation) have been used to identify differences in ITIH3 expression levels in experimental models .

What are the optimal conditions for ITIH3 antibody-based immunoprecipitation experiments?

Successful immunoprecipitation (IP) of ITIH3 requires careful optimization of experimental conditions. Based on research protocols:

• Antibody Selection: Use high-specificity anti-ITIH3 antibodies validated for IP applications. Researchers investigating ITIH3 in myasthenia gravis successfully employed immunoprecipitation of ITIH3 followed by proteomics to identify interaction partners .

• Buffer Composition:

  • Lysis buffer: RIPA buffer containing protease inhibitors

  • Washing buffer: PBS with 0.1% Tween-20

  • Elution buffer: Glycine-HCl (pH 2.5-3.0) followed by immediate neutralization

• Protocol Optimization:

  • Pre-clear lysates with protein A/G beads to reduce non-specific binding

  • Incubate antibodies with protein lysates overnight at 4°C with gentle rotation

  • Use appropriate negative controls (isotype-matched IgG)

  • Validate pull-down efficiency by western blotting using a different anti-ITIH3 antibody

• Downstream Analysis: For identification of ITIH3 interaction partners, mass spectrometry-based proteomics has proven effective, as demonstrated in studies identifying proteins crucial for neuromuscular transmission that interact with ITIH3 .

How should researchers design knockdown experiments to study ITIH3 function?

Designing effective ITIH3 knockdown experiments requires careful consideration of several factors:

• RNA Interference (RNAi) Design:

  • Target sequence selection: Design multiple siRNA/shRNA sequences targeting different regions of ITIH3 mRNA

  • Construct appropriate vectors for stable expression (e.g., lentiviral vectors with fluorescent markers)

  • Verify knockdown efficiency: Aim for >70% reduction in protein expression

• Validation of Knockdown Efficiency:

  • Western blotting is the standard method for confirming ITIH3 protein reduction

  • In published studies, successful ITIH3 RNAi cell lines showed protein expression levels at approximately 30% of those in parent cell lines and negative controls

  • Fluorescence verification: Successful transduction can be confirmed by cell fluorescence rates >80%

• Functional Assays Post-Knockdown:

  • Cell viability assays (e.g., CCK-8 assay for measuring drug sensitivity)

  • Real-time cell analysis using systems like xCELLigence RTCA

  • Flow cytometry for apoptosis analysis (Annexin V/PE staining)

  • Colony formation experiments to assess effects on cell proliferation

• In Vivo Model Development:

  • Consider xenograft models using ITIH3-knockdown cells to validate in vitro findings

  • Researchers have successfully established subcutaneous murine xenograft models using ITIH3 RNAi cells to evaluate the effects of treatments like cisplatin

What controls are essential when performing immunohistochemistry with ITIH3 antibodies?

Proper controls are critical for reliable ITIH3 immunohistochemistry results:

• Primary Controls:

  • Positive tissue controls: Include tissues known to express ITIH3 (e.g., normal liver)

  • Negative tissue controls: Include tissues known not to express ITIH3

  • No primary antibody control: Perform parallel staining omitting the primary antibody

  • Isotype control: Use non-specific antibody of the same isotype as the ITIH3 antibody

• Technical Controls:

  • Independent evaluation by multiple pathologists (preferably blinded to the research)

  • Standard tissue processing and antigen retrieval methods

  • Consistent antibody concentrations and incubation times

• Scoring System Standardization:

  • Implement a reproducible scoring system like the one used in ovarian cancer studies:

    • Cell proportion score (0-4)

    • Staining intensity score (0-3)

    • Final immunoreactive score (IRS) as their product

  • Establish clear thresholds for negative, weak, and strong expression

• Validation of Results:

  • Confirm IHC findings with alternative methods (western blotting, qPCR)

  • Use multiple antibodies targeting different epitopes of ITIH3 when possible

How does ITIH3 expression affect chemotherapy resistance in ovarian cancer?

ITIH3 has emerged as a significant factor in chemotherapy resistance, particularly affecting cisplatin (DDP) sensitivity in ovarian cancer:

What methodological approaches can be used to study the relationship between ITIH3 and the Bcl-2 family proteins?

Investigating the interaction between ITIH3 and Bcl-2 family proteins requires comprehensive methodological approaches:

• Protein Expression Analysis:

  • Western blotting to quantify expression levels of:

    • Anti-apoptotic proteins: Bcl-2, Bcl-xL

    • Phosphorylated Bcl-2 (P-Bcl-2, Thr56)

    • Pro-apoptotic proteins: Bak

    • Downstream effectors: Cleaved caspase 3, caspase 3, cleaved PARP

  • Immunoprecipitation followed by western blotting to detect direct protein-protein interactions

• Functional Assays:

  • Apoptosis analysis using Annexin V/PE staining and flow cytometry to assess the effect of ITIH3 expression on cell death following cisplatin treatment

  • Cell viability assays (CCK-8) to determine IC50 values in cells with different ITIH3 expression levels

  • Real-time cell analysis using systems like xCELLigence RTCA to monitor dynamic changes in cell proliferation following treatment

• Pharmacological Intervention:

  • Use of specific inhibitors like the Bcl-2 inhibitor ABT-737 to determine if blocking anti-apoptotic proteins can reverse the effects of ITIH3 silencing

  • Dose-response experiments to establish optimal inhibitor concentrations

• In Vivo Validation:

  • Subcutaneous murine xenograft models comparing:

    • Control cells (e.g., SKOV3-NC)

    • ITIH3-silenced cells (e.g., SKOV3-ITIH3 RNAi)

  • Treatment protocols involving multiple cisplatin injections (typically 0, 2, 5, and 8 injections)

  • Analysis of tumor volume and protein expression patterns in harvested tumors

What is the recommended methodology for evaluating ITIH3 as a predictive biomarker in cancer treatment?

Evaluating ITIH3 as a predictive biomarker requires a systematic approach:

How can researchers optimize ITIH3 detection as a biomarker in myasthenia gravis?

Optimizing ITIH3 detection as a biomarker in myasthenia gravis requires specialized approaches:

• Serum Analysis Protocols:

  • Collection standardization: Use serum separator tubes and process within 2 hours

  • Storage conditions: Aliquot and store at -80°C to avoid repeated freeze-thaw cycles

  • ELISA validation: Optimize antibody concentrations and establish standard curves

  • Machine learning approaches have successfully identified ITIH3 as a potential serum biomarker reflective of disease activity

• Correlation with Clinical Metrics:

  • Compare ITIH3 serum levels with validated disease activity scores

  • Establish baseline levels in healthy controls

  • Monitor ITIH3 levels longitudinally to assess treatment responses

  • Conduct subgroup analyses to identify patient populations where ITIH3 is most indicative of treatment outcomes

• Structural Validation:

  • Perform immunostaining of muscle specimens to localize ITIH3

  • Compare ITIH3 localization at neuromuscular endplates between myasthenia gravis patients and controls

  • This approach provides structural evidence supporting serological findings

• Protein Interaction Studies:

  • Conduct immunoprecipitation of ITIH3 followed by proteomic analysis

  • Identify interaction partners with roles in neuromuscular transmission

  • Validate interactions using co-immunoprecipitation and co-localization studies

What are the key methodological considerations when investigating ITIH3 at neuromuscular junctions?

Investigating ITIH3 at neuromuscular junctions presents unique methodological challenges:

• Tissue Sampling and Processing:

  • Obtain muscle biopsies from appropriate anatomical sites

  • Utilize both frozen sections (for optimal antigen preservation) and paraffin-embedded sections

  • Employ specialized fixation protocols to preserve neuromuscular junction integrity

• Co-localization Studies:

  • Use dual or triple immunofluorescence labeling with:

    • Anti-ITIH3 antibodies

    • Markers of post-synaptic apparatus (e.g., α-bungarotoxin for acetylcholine receptors)

    • Pre-synaptic markers (e.g., synaptophysin)

  • Analyze using confocal microscopy for precise localization

• Functional Correlation:

  • Correlate ITIH3 localization patterns with electrophysiological parameters

  • Compare staining patterns between:

    • Patients with active disease

    • Patients in remission

    • Healthy controls

  • Assess changes in ITIH3 distribution following therapeutic interventions

• Molecular Interaction Analysis:

  • Investigate ITIH3 interactions with specific components of neuromuscular transmission

  • Apply proximity ligation assays to validate protein-protein interactions in situ

  • Conduct laser capture microdissection followed by proteomics to analyze the neuromuscular junction-specific interactome

How should researchers address conflicting results between ITIH3 mRNA and protein expression levels?

Discrepancies between ITIH3 mRNA and protein expression represent a common challenge requiring systematic troubleshooting:

• Validation of Detection Methods:

  • Confirm specificity of primers for mRNA detection (qRT-PCR)

  • Validate antibody specificity using positive and negative controls

  • Employ multiple antibodies targeting different epitopes of ITIH3

  • Consider using different housekeeping genes/proteins as references

• Post-transcriptional Regulation Assessment:

  • Investigate potential microRNA-mediated regulation of ITIH3

  • Assess mRNA stability using actinomycin D chase experiments

  • Examine alternative splicing patterns that might affect antibody recognition sites

• Protein Stability Analysis:

  • Measure ITIH3 protein half-life using cycloheximide chase assays

  • Investigate proteasomal and lysosomal degradation pathways

  • Examine post-translational modifications that might affect antibody recognition

• Contextual Interpretation:

  • Consider tissue/cell-specific regulatory mechanisms

  • Examine potential disease-specific alterations in ITIH3 processing

  • Account for temporal dynamics in gene expression versus protein accumulation

What are the critical parameters for optimizing ITIH3 antibody specificity in multi-omics research?

Ensuring antibody specificity is crucial for reliable ITIH3 detection across multi-omics approaches:

• Antibody Validation Process:

  • Genetic approaches: Test antibodies in ITIH3 knockout/knockdown models

  • Peptide competition assays: Pre-incubate antibodies with specific peptides

  • Orthogonal validation: Compare results across multiple antibodies

  • Cross-reactivity assessment: Test against related ITIH family members

• Application-Specific Optimization:

  • Western blotting: Optimize blocking agents, antibody dilutions, and incubation times

  • Immunohistochemistry: Compare different antigen retrieval methods

  • Immunoprecipitation: Test various lysis and washing buffers

  • Flow cytometry: Optimize fixation and permeabilization protocols

• Multi-omics Integration Considerations:

  • Ensure consistent sample processing across platforms

  • Apply statistical methods to account for platform-specific biases

  • Validate key findings using orthogonal techniques

  • Implement appropriate normalization strategies for cross-platform comparisons

• Reporting Standards:

  • Document detailed antibody information (manufacturer, catalog number, lot, dilution)

  • Report all validation experiments performed

  • Share negative control data alongside positive results

  • Acknowledge potential limitations in antibody specificity

How might researchers design experiments to explore ITIH3's potential as a therapeutic target?

Exploring ITIH3 as a therapeutic target requires a comprehensive research strategy:

• Target Validation Approaches:

  • Conduct gain-of-function experiments: Overexpress ITIH3 in resistant cancer cell lines to determine if sensitivity to cisplatin can be restored

  • Perform structure-function analyses: Identify critical domains of ITIH3 involved in mediating chemosensitivity

  • Develop conditional knockout models to evaluate tissue-specific effects of ITIH3 modulation

• High-Throughput Screening Strategies:

  • Design cell-based assays to identify compounds that modulate ITIH3 expression or activity

  • Develop reporter systems to monitor ITIH3 promoter activity

  • Utilize CRISPR activation/inhibition screens to identify regulators of ITIH3

• Combination Therapy Approaches:

  • Expand on findings with Bcl-2 inhibitors like ABT-737

  • Test synergistic effects of ITIH3 modulation with other chemotherapeutic agents

  • Investigate potential for personalized treatment strategies based on ITIH3 expression levels

• Translational Models:

  • Develop patient-derived xenograft models with varying ITIH3 expression levels

  • Establish organoid cultures to test interventions in more physiologically relevant systems

  • Design early-phase clinical trials with ITIH3 expression as a stratification factor

What methodological innovations could enhance the study of ITIH3 in complex tissue microenvironments?

Advancing ITIH3 research in complex tissue microenvironments requires cutting-edge methodological approaches:

• Spatial Transcriptomics and Proteomics:

  • Apply technologies like Visium, Slide-seq, or CODEX to visualize ITIH3 expression patterns in relation to other cell types

  • Develop multiplexed imaging approaches to simultaneously visualize ITIH3 and its interaction partners

  • Integrate single-cell sequencing with spatial information to map ITIH3 expression at cellular resolution

• 3D Culture Systems:

  • Utilize organoid models to study ITIH3 in more physiologically relevant contexts

  • Develop co-culture systems incorporating multiple cell types (e.g., tumor cells with stromal components)

  • Apply microfluidic organ-on-chip approaches to model dynamic interactions

• In Situ Protein Interaction Mapping:

  • Implement proximity labeling techniques (BioID, APEX) to identify ITIH3 interaction partners in live cells

  • Apply FRET/BRET approaches to monitor real-time protein interactions

  • Develop conditional interaction screening methods to identify context-specific binding partners

• Live Imaging Innovations:

  • Generate fluorescently tagged ITIH3 constructs for real-time visualization

  • Apply optogenetic approaches to manipulate ITIH3 function with spatial and temporal precision

  • Develop biosensors to monitor ITIH3-dependent signaling events in living systems

What is the current consensus on best practices for ITIH3 detection across different research applications?

Current best practices for ITIH3 detection vary by application but should adhere to these general principles:

• Antibody Selection and Validation:

  • Use antibodies validated for the specific application (western blotting, IHC, IP)

  • Verify specificity through appropriate controls (ITIH3 knockdown/knockout)

  • Consider using multiple antibodies targeting different epitopes

  • For IHC, the goat-anti-ITI-H3 (L-15) antibody (1:200; cat. no. sc-33949; Santa Cruz Biotechnology, Inc.) has been successfully employed in published research

• Protocol Optimization by Application:

  • Western blotting: Standard protocols with GAPDH or Actin as loading controls

  • Immunohistochemistry: 4% paraformaldehyde fixation, paraffin embedding, and standardized scoring systems

  • ELISA: Validated for serum biomarker studies, particularly in myasthenia gravis research

  • Proteomics: iTRAQ approaches have successfully identified ITIH3 expression changes in drug resistance models

• Data Interpretation Guidelines:

  • Consider tissue/disease-specific expression patterns

  • Interpret results in the context of relevant biological pathways (e.g., Bcl-2 family proteins for cancer studies)

  • Correlate with clinical parameters when available

  • Recognize the limitations of individual detection methods

• Reporting Standards:

  • Document detailed methodological information to ensure reproducibility

  • Include all relevant controls in publications

  • Share raw data when possible to facilitate meta-analyses

  • Acknowledge potential limitations in antibody specificity or assay sensitivity

How can researchers integrate ITIH3 findings into broader disease mechanisms and clinical applications?

Integrating ITIH3 research into broader disease contexts requires strategic approaches:

• Pathway Integration Strategies:

  • Map ITIH3 interactions within established signaling networks

  • Identify convergent pathways between ITIH3 and known disease mechanisms

  • For cancer research, focus on integrating ITIH3 within apoptotic regulation networks, particularly the Bcl-2 family pathway

  • For neuromuscular diseases, examine connections between ITIH3 and established neuromuscular junction components

• Biomarker Development Pipeline:

  • Progress from discovery (proteomics) to validation (targeted assays)

  • Establish standardized detection methods for clinical laboratories

  • Determine appropriate reference ranges in healthy populations

  • Conduct prospective studies to validate predictive value

• Therapeutic Target Assessment:

  • Evaluate druggability of ITIH3 or its regulatory pathways

  • Consider indirect approaches (e.g., modulating Bcl-2 family proteins in ITIH3-low tumors)

  • Develop combination strategies incorporating ITIH3 status

  • Design clinical trials with appropriate biomarker stratification

• Translational Research Framework:

  • Establish clinically annotated biobanks with ITIH3 characterization

  • Develop preclinical models that recapitulate human ITIH3 biology

  • Create interdisciplinary collaborations spanning basic science to clinical application

  • Implement machine learning approaches to integrate ITIH3 data with other disease parameters