TNS4 Antibody

What is TNS4 and why is it significant in cancer research?

TNS4 (tensin 4), also known as CTEN (C-terminal tensin-like protein), is a 76.8 kilodalton protein that belongs to the tensin family. Unlike other tensin family members (TNS1, TNS2, and TNS3), TNS4 has the smallest molecular mass and lacks the N-terminal common region found in other family members . TNS4 plays crucial roles in various cellular processes including proliferation, migration, cell adhesion, and apoptosis . Its significance in cancer research stems from its aberrant expression in multiple malignancies, including head and neck squamous cell carcinoma (HNSCC), gastric cancer, breast carcinoma, lung cancer, and colorectal cancer, where elevated TNS4 levels are associated with poor clinical outcomes .

What applications are most appropriate for TNS4 antibody use in experimental settings?

TNS4 antibodies are versatile tools for cancer research with multiple experimental applications:

The choice of application depends on your specific research question, sample type, and available facilities .

What are the recommended positive and negative controls for TNS4 antibody experiments?

Proper controls are essential for reliable TNS4 antibody experiments:

Positive Controls:

• Human gastric cancer cell lines (demonstrated high TNS4 expression)

• HNSCC cell lines (particularly UM1 and UM5, which show higher TNS4 expression than UM2 and UM6)

• MKN1, MKN7, MKN45, MKN74, NUGC3, NUGC4, and Kato III cell lines (for gastric cancer research)

Negative Controls:

• Normal epithelial cells (NHOK and NHEK show significantly lower TNS4 expression)

• Adjacent normal tissue (when working with patient samples)

• TNS4 knockdown cells (generated through siRNA or CRISPR technology)

• Isotype controls (using matched immunoglobulin with no specific target)

Including these controls allows for proper validation of antibody specificity and experimental reliability .

How can researchers effectively use TNS4 antibodies to study its role in hypoxia-driven cancer progression?

Hypoxia-inducible factor 1α (HIF-1α) has been identified as a transcriptional regulator of TNS4 expression, making the hypoxia-TNS4 axis an important area of cancer research . To study this relationship:

• Hypoxia Chamber Experiments: Culture cells under normoxic and hypoxic conditions (typically 1-2% O₂), then use TNS4 antibodies in Western blots to quantify expression changes.

• ChIP Assays: Utilize chromatin immunoprecipitation with HIF-1α antibodies to identify binding at the TNS4 promoter region, followed by qPCR to quantify enrichment.

• Dual Immunofluorescence: Co-stain tissue sections with TNS4 and HIF-1α antibodies to visualize spatial correlation, particularly at tumor margins and hypoxic regions.

• HIF-1α Manipulation: Use HIF-1α inhibitors or siRNA knockdown followed by TNS4 antibody detection to establish causality. Research has shown that HIF-1α depletion affects TNS4 expression even under normoxic conditions, suggesting complex regulatory relationships .

• Proximity Ligation Assays: To detect potential protein-protein interactions between HIF-1α and TNS4 or other components in the hypoxic response pathway.

These approaches can help elucidate how hypoxic tumor microenvironments drive TNS4 expression and subsequent malignant progression .

What methodologies are most effective for studying TNS4's interaction with integrin complexes?

TNS4 promotes the interaction between integrin α5 and integrin β1, thereby activating focal adhesion kinase (FAK) . To investigate these interactions:

• Co-immunoprecipitation (Co-IP): Use TNS4 antibodies to pull down protein complexes, followed by Western blotting for integrin α5, integrin β1, and FAK. This reveals direct or indirect protein interactions.

• Reverse Co-IP: Immunoprecipitate with integrin antibodies and probe for TNS4 to confirm interactions from both perspectives.

• Proximity Ligation Assay (PLA): This technique allows visualization of protein-protein interactions (<40 nm apart) in situ, providing spatial information about where TNS4-integrin complexes form within cells.

• FRET Analysis: Fluorescence resonance energy transfer using fluorescently tagged TNS4 and integrin components can detect direct interactions at nanometer resolution.

• GST Pull-down Assays: Using recombinant TNS4 domains to identify specific regions involved in integrin binding.

• Integrin Activation Assays: Combine TNS4 manipulation (overexpression/knockdown) with measurements of active integrin using conformation-specific antibodies or fibronectin binding assays.

These approaches have revealed that TNS4 overexpression enhances integrin α5β1 interaction, promoting FAK activation and subsequent oncogenic signaling cascades .

How can TNS4 antibodies be utilized to investigate downstream signaling pathways?

Research has shown that TNS4-mediated FAK activation enhances both PI3K/Akt and TGFβ signaling pathways . To investigate these signaling networks:

• Phospho-specific Antibody Arrays: Combine TNS4 manipulation with antibody arrays detecting multiple phosphorylated proteins to map affected pathways.

• Sequential Immunoblotting: After TNS4 knockdown or overexpression, use antibodies against phosphorylated and total forms of key signaling molecules (FAK, Akt, Smad2/3) to track activation status.

• Inhibitor Studies: Use specific inhibitors of FAK (e.g., FAKi), PI3K/Akt (e.g., LY294002), or TGFβ (e.g., LY2109761) pathways in combination with TNS4 manipulation to establish pathway dependencies.

• Transcriptional Reporter Assays: Employ luciferase reporters for TGFβ or PI3K/Akt pathway activity in TNS4-manipulated cells to quantify pathway activation.

• Multiplexed Immunofluorescence: Co-stain for TNS4 and activated (phosphorylated) signaling components to visualize pathway activation in relation to TNS4 expression in tissue sections.

Research has demonstrated that TNS4 overexpression augments p-Smad2 and p-Smad3 levels, which are attenuated by FAK inhibition, suggesting a TNS4-FAK-TGFβ signaling axis .

What are the optimal immunohistochemistry protocols for TNS4 detection in FFPE tissues?

Based on published methodologies, the following protocol has proven effective for TNS4 detection in formalin-fixed, paraffin-embedded (FFPE) tissues:

• Tissue Preparation:

  • 5μm sections on positively charged slides

  • Deparaffinization in xylene

  • Rehydration through graded alcohol series

• Antigen Retrieval:

  • Heat-induced epitope retrieval in 10mM citrate buffer (pH 6.0)

  • 121°C for 15 minutes in a pressure cooker or autoclave

  • Cool to room temperature gradually

• Blocking and Antibody Incubation:

  • Block endogenous peroxidase (3% H₂O₂, 10 minutes)

  • Protein blocking (5% normal serum, 30 minutes)

  • Primary TNS4 antibody incubation overnight at 4°C (typically 1:10 dilution for commercial antibodies like those from Atlas Antibodies)

  • Secondary detection with peroxidase-labeled polymer (EnVision+, rabbit)

• Visualization and Counterstaining:

  • Develop with DAB chromogen

  • Counterstain with hematoxylin

  • Dehydrate, clear, and mount

• Scoring System:

  • Evaluate both staining intensity (0-3) and percentage of positive cells

  • Calculate H-score or use a categorical system (negative, weak, moderate, strong)

This protocol has successfully demonstrated cytoplasmic localization of TNS4 with significantly higher expression in cancer cells compared to stromal cells in various malignancies .

How should quantitative PCR be optimized for TNS4 mRNA detection?

Quantitative reverse-transcription PCR (qRT-PCR) is a powerful method for measuring TNS4 mRNA expression. Based on published research protocols:

• Primer Design:

  • Forward primer: 5'-CACCATGAAGTTCGTGATG-3'

  • Reverse primer: 5'-CGGTATGAAGAGCTGTCC-3'

  • These target specific regions of TNS4 cDNA for optimal amplification

• Reference Gene Selection:

  • β-actin (ACTB) is commonly used (Forward: 5'-AGTTGCGTTACACCCTTTCTTGAC-3', Reverse: 5'-GCTCGCTCCAACCGACTGC-3')

  • Consider multiple reference genes (GAPDH, 18S rRNA) for more robust normalization

• PCR Conditions:

  • Initial denaturation: 95°C for 10 minutes

  • 40 cycles of: 95°C for 1 minute, 60°C for 1 minute, 72°C for 1 minute

  • Final extension: 72°C for 10 minutes

• Data Analysis:

  • Use the comparative Ct (2^-ΔΔCt) method for relative quantification

  • When determining cutoff points for high vs. low expression, use statistical approaches like minimum p-value method with cross-validation

This approach has successfully demonstrated significant differences in TNS4 expression between cancer tissues and adjacent normal mucosa, with a 23.52-fold higher expression reported in gastric cancer .

What factors should be considered when selecting TNS4 antibodies for specific applications?

Selecting the appropriate TNS4 antibody is critical for experimental success. Consider these factors:

For TNS4 research, antibodies targeting different regions can yield complementary information, as the protein's function may depend on specific domains. Commercial suppliers offer numerous options, with over 146 TNS4 antibodies available across 22 suppliers .

How should researchers interpret discrepancies between TNS4 mRNA and protein expression data?

Discrepancies between mRNA and protein levels of TNS4 are not uncommon and may arise from several factors:

• Post-transcriptional Regulation:

  • microRNAs targeting TNS4 mRNA

  • RNA-binding proteins affecting stability

  • Alternative splicing generating different isoforms

• Post-translational Modifications:

  • Ubiquitination and proteasomal degradation

  • Phosphorylation affecting protein stability

  • Interaction with stabilizing proteins (TNS4 interacts with E3 ubiquitin ligase, affecting EGFR degradation)

• Technical Considerations:

  • Different sensitivities of detection methods

  • Antibody specificity issues

  • Sampling heterogeneity (especially in tumor tissues)

• Temporal Dynamics:

  • Delays between transcription and translation

  • Different half-lives of mRNA versus protein

When facing such discrepancies, consider:

• Examining multiple time points

• Using multiple antibodies targeting different epitopes

• Employing protein degradation inhibitors

• Investigating potential regulatory mechanisms

• Correlating findings with functional outcomes rather than assuming linear relationships

A comprehensive approach integrating multiple techniques provides the most reliable picture of TNS4 biology in your experimental system.

What statistical approaches are recommended for analyzing TNS4 expression in relation to patient outcomes?

Based on published research methodologies, the following statistical approaches are recommended for TNS4 biomarker analysis:

• Expression Comparison:

  • Wilcoxon test for paired samples (cancer vs. adjacent normal)

  • Mann-Whitney U test for unpaired comparisons

  • ANOVA with post-hoc tests for multiple group comparisons (e.g., normal vs. dysplastic vs. tumor tissues)

• Cutoff Determination:

  • Minimum p-value approach in multivariate Cox models

  • Two-fold cross-validation to confirm cutoff robustness

  • ROC curve analysis to balance sensitivity and specificity

• Survival Analysis:

  • Kaplan-Meier method with log-rank test for visualization and comparison

  • Univariate Cox proportional-hazards model to assess prognostic significance

  • Multivariate Cox model including established prognostic factors to determine independent prognostic value

• Correlation with Clinicopathological Features:

  • Chi-square or Fisher's exact test for categorical variables

  • Spearman or Pearson correlation for continuous variables

  • Logistic regression for multivariate analysis of associations

How can researchers integrate TNS4 antibody data with other molecular markers for comprehensive cancer characterization?

Integration of TNS4 data with other molecular markers enables comprehensive tumor characterization:

• Multiplex Immunofluorescence:

  • Simultaneously stain tissue sections for TNS4 and markers of:

    • Proliferation (Ki-67, PCNA)

    • EMT (E-cadherin, N-cadherin, vimentin)

    • Signaling pathway activation (p-FAK, p-Akt, p-Smad2/3)

  • This approach reveals spatial relationships between TNS4 and other markers at single-cell resolution

• Multi-omics Integration:

  • Correlate TNS4 protein data with:

    • Transcriptomic data (RNA-seq)

    • Phosphoproteomic profiling

    • Genomic alterations (mutations, CNVs)

  • Use dimensionality reduction techniques (PCA, t-SNE) and clustering algorithms to identify patient subgroups

• Pathway Analysis:

  • Gene Set Enrichment Analysis (GSEA) to identify pathways associated with TNS4 expression

  • Research has shown enrichment of TGFβ signaling in TNS4-high tumors across multiple independent HNSCC cohorts

• Clinical Data Integration:

  • Combine TNS4 expression with:

    • TNM staging

    • Treatment response data

    • Other established biomarkers

  • Develop integrated prognostic models with superior predictive power

• Validation in Independent Cohorts:

  • Test integrated models across different patient populations

  • Consider both in-house cohorts and public datasets (TCGA, GEO)

This integrative approach has revealed important biological insights, such as the progressive increase of TNS4 expression from normal tissues to dysplastic tissues and ultimately to tumor tissues, suggesting its role in cancer progression .

What are the potential translational applications of TNS4 antibody-based research?

TNS4 antibody research has several promising translational applications:

These translational applications highlight the significant clinical potential of TNS4 antibody-based research in improving cancer patient management and outcomes.