TUBA1C Antibody

What is TUBA1C and why is it significant in cancer research?

TUBA1C is a subtype of α-tubulin involved in cell proliferation and cell cycle progression. It has been identified as an oncogenic protein overexpressed in most cancers, with this overexpression linked to poor prognosis and higher tumor grade. Studies have shown that TUBA1C is significantly associated with tumor mutation burden (TMB), microsatellite instability (MSI), the tumor microenvironment (TME), and immune cell infiltration patterns . The differential expression pattern of TUBA1C across cancer types makes it a potential diagnostic and prognostic biomarker, with highest expression observed in aggressive cancers like glioblastoma compared to lower expression in low-grade gliomas and minimal expression in normal tissues .

How does TUBA1C expression vary across different cancer types?

TUBA1C expression demonstrates significant variation across cancer types, with particularly high expression in glioblastoma multiforme (GBM), followed by lower expression in low-grade gliomas (LGG), and minimal expression in normal tissues . This expression pattern correlates with tumor grade in multiple cancer types. Immunohistochemical analysis has confirmed this gradient of expression, suggesting TUBA1C as a potential marker for tumor progression and malignancy. Research indicates that TUBA1C overexpression is associated with poorer prognosis across multiple cancer types, making it valuable for stratifying patients and predicting clinical outcomes .

What epitopes of TUBA1C are commonly targeted by research antibodies?

Research antibodies for TUBA1C typically target several key epitopes:

• The C-terminal region (AA 421-449) is a common target, with multiple validated antibodies available

• The N-terminal region contains important epitopes for antibody recognition

• Full-length protein antibodies that recognize multiple regions of TUBA1C

• Mid-region epitopes (AA 29-184) have also been developed for specific applications

The choice of epitope can affect antibody specificity and application suitability. C-terminal antibodies often show good specificity for TUBA1C, while some cross-reactivity with other alpha-tubulin family members may occur depending on the conservation of the targeted epitope sequence .

What are the validated research applications for TUBA1C antibodies?

TUBA1C antibodies have been validated for multiple research applications:

The optimal working dilution should be determined empirically by the investigator for each specific application and experimental condition .

What protocols are recommended for optimizing TUBA1C immunohistochemistry in cancer tissues?

For optimal immunohistochemistry results with TUBA1C antibodies in cancer tissues:

• Tissue preparation: Use 4-6 μm sections from formalin-fixed paraffin-embedded (FFPE) tissues

• Antigen retrieval: Heat-induced epitope retrieval in citrate buffer (pH 6.0) for 20 minutes

• Blocking: Use 3-5% normal serum from the same species as the secondary antibody

• Primary antibody incubation: Apply TUBA1C antibody at optimized dilution (typically 1:100-1:200) overnight at 4°C

• Detection system: Use appropriate HRP/DAB or fluorescence-based detection systems

• Controls: Include both positive controls (known TUBA1C-expressing tissues) and negative controls (primary antibody omitted)

• Scoring: Evaluate staining intensity (0-3+) and percentage of positive cells to generate H-scores

For tumor samples, it's critical to process all experimental samples simultaneously to ensure consistent staining intensity for accurate comparison .

What are the key considerations for validating TUBA1C antibody specificity?

Validating TUBA1C antibody specificity requires multiple approaches:

• Western blot analysis showing a band at the expected molecular weight (~50 kDa)

• Peptide competition assays demonstrating signal reduction when the antibody is pre-incubated with the immunizing peptide

• siRNA knockdown or CRISPR knockout of TUBA1C followed by antibody testing to confirm signal reduction

• Cross-reactivity testing with other tubulin family members, particularly other alpha-tubulins with high sequence homology

• Multiple antibody validation using different antibodies targeting distinct epitopes of TUBA1C

• Correlation of protein detection with mRNA expression data across tissues or cell lines

Researchers should be aware that some TUBA1C antibodies may cross-react with other tubulin family members due to sequence conservation, particularly in functional domains. Antibodies targeting the more variable C-terminal region often show higher specificity .

How does TUBA1C expression correlate with immune checkpoint molecules?

TUBA1C expression shows significant correlations with multiple immune checkpoint molecules across cancer types:

TUBA1C expression has been specifically correlated with CD274 (PD-L1), HAVCR2, CTLA4, LAG3, PDCD1LG2, PDCD1, SIGLEC15, and TIGIT expression . These correlations suggest TUBA1C may influence or be influenced by the same regulatory mechanisms controlling immune checkpoint expression, potentially contributing to tumor immune evasion strategies .

How can TUBA1C antibodies be used to study the tumor microenvironment?

TUBA1C antibodies serve as valuable tools for investigating the tumor microenvironment through:

• Multiplex immunohistochemistry or immunofluorescence to simultaneously visualize TUBA1C expression and immune cell infiltration patterns

• Flow cytometry analysis of dissociated tumor tissues to correlate TUBA1C expression with specific immune cell populations

• Cell sorting followed by functional assays to assess how TUBA1C-expressing cells influence immune cell function

• Proximity ligation assays to detect potential physical interactions between TUBA1C and immune regulatory proteins

• Tissue microarray analysis to evaluate correlations between TUBA1C expression and stromal/immune cell markers across large patient cohorts

Research has shown that TUBA1C expression correlates with immune and stromal scores in several cancers. For example, TUBA1C expression positively correlates with immune scores in GBM, LGG, PCPG and THCA, but negatively correlates in ESCA . These findings suggest cancer type-specific relationships between TUBA1C and the tumor immune microenvironment.

What is the relationship between TUBA1C and response to immune checkpoint blockade therapy?

TUBA1C expression may serve as a predictive biomarker for immune checkpoint blockade (ICB) therapy response:

• Higher TUBA1C expression correlates with better responses to ICB therapy in LGG, LIHC, LUAD, and LUSC (p < 0.001, p < 0.001, p < 0.001, and p = 0.011, respectively)

• TUBA1C expression positively correlates with tumor mutation burden (TMB) in 15 cancer types, including UCS, UCEC, STAD, SKCM, and others

• TUBA1C expression positively correlates with microsatellite instability (MSI) in ACC, UCEC, SARC and COAD, while negatively correlating in OV, LUSC, LUAD and LGG

• Single-cell analysis reveals differential TUBA1C expression across ICB response groups in malignant cells

These findings suggest that TUBA1C expression analysis could potentially help identify patients more likely to benefit from immunotherapy, particularly in specific cancer types where stronger correlations have been observed between TUBA1C and ICB response markers .

How does TUBA1C influence immune cell infiltration in the tumor microenvironment?

TUBA1C has been shown to have complex relationships with immune cell infiltration that vary by cancer type:

These correlations suggest TUBA1C may influence the recruitment or function of specific immune cell populations within the tumor microenvironment . The mechanisms may involve effects on cytokine production, chemokine signaling pathways, or direct interactions with immune cell receptors, though further research is needed to elucidate the precise mechanisms .

What molecular mechanisms connect TUBA1C to cancer progression and immune evasion?

Several molecular mechanisms potentially link TUBA1C to cancer progression and immune evasion:

• TUBA1C influences hallmark cancer pathways, with significant differences in pathway activities between high and low expression groups

• Comparative analysis between different TUBA1C expression groups reveals alterations in immune-related pathways that may contribute to immune evasion

• TUBA1C may orchestrate an immunosuppressive tumor microenvironment particularly in clear cell renal cell carcinoma (ccRCC)

• Interaction between TUBA1C and immune regulatory modules affects antigen presentation, immune inhibition/stimulation, and chemokine signaling

• TUBA1C expression correlates with PD-L1 (CD274) expression in malignant cells, suggesting potential co-regulatory mechanisms

Understanding these mechanisms requires integration of multiple approaches, including transcriptomic analysis, protein interaction studies, and functional assays following TUBA1C manipulation .

How can TUBA1C be targeted in combination with immunotherapy approaches?

Strategies for targeting TUBA1C in combination with immunotherapy include:

• In silico knockout analysis of TUBA1C suggests potential synergy with immune checkpoint blockade, particularly in kidney cancer models

• Analysis using the DepMap database indicates TUBA1C dependency in kidney cancer cell lines, suggesting it as a potential therapeutic target

• Somatic mutation data analysis reveals that TUBA1C mutation status may influence sensitivity to anti-PD-L1 therapy

• Drug sensitivity prediction using GDSC and CTRP databases suggests differential responses to various therapeutics based on TUBA1C expression

• Potential approaches include developing TUBA1C-targeting agents (small molecules, antibodies) for combination with immune checkpoint inhibitors

Experimental design for such combination approaches should include both in vitro models (cell lines with TUBA1C knockdown/overexpression) and in vivo models (syngeneic mouse models with TUBA1C manipulation) to assess effects on tumor growth and immune infiltration when combined with immunotherapy agents .

What are the methodological considerations for TUBA1C gene function studies in cancer research?

For comprehensive TUBA1C functional studies:

• Gene manipulation approaches:

  • CRISPR-Cas9 knockout in cancer cell lines (available through DepMap for 26 kidney cancer cell lines)

  • siRNA or shRNA knockdown for transient or stable suppression

  • Overexpression systems using lentiviral vectors

• Phenotypic assessments:

  • Proliferation, migration, invasion assays

  • Cell cycle analysis

  • Apoptosis measurement

  • In vivo tumor growth in mouse models

• Immunological impact analysis:

  • Co-culture systems with immune cells

  • Cytokine production measurement

  • Immune checkpoint molecule expression analysis

  • T cell killing assays

• Bioinformatic approaches:

  • In silico knockout prediction using deep learning models

  • Pathway analysis using GSVA (Gene Set Variation Analysis)

  • Multi-omics integration with TUBA1C expression data

• Clinical correlation:

  • Tissue microarray analysis with TUBA1C antibodies

  • Correlation with treatment response data

  • Patient stratification based on TUBA1C expression

These methodological approaches have been successfully applied to elucidate TUBA1C function in multiple cancer contexts, particularly in understanding its role in orchestrating the immunosuppressive tumor microenvironment in clear cell renal cell carcinoma .

How might single-cell analysis enhance our understanding of TUBA1C in the tumor microenvironment?

Single-cell analysis offers unprecedented opportunities to understand TUBA1C's role in cancer:

• Recent studies have utilized single-cell RNA sequencing to examine TUBA1C expression variations in malignant cells following immune checkpoint blockade therapy

• This approach allows for cell type-specific analysis of TUBA1C expression and its relationship with other immune regulatory genes like CD274 (PD-L1)

• Future research could employ spatial transcriptomics to map TUBA1C expression within the tumor architecture and correlate it with immune cell localization

• Single-cell protein analysis (CyTOF or CODEX) could reveal co-expression patterns of TUBA1C with other cancer and immune markers at the protein level

• Integration of single-cell data with clinical outcomes could identify specific cellular populations where TUBA1C expression has the strongest prognostic or predictive value

These approaches would provide unprecedented resolution in understanding how TUBA1C influences the tumor microenvironment and potentially identify new therapeutic strategies targeting TUBA1C-expressing cell populations .

What are the challenges in developing TUBA1C as a cancer biomarker?

Developing TUBA1C as a cancer biomarker faces several challenges:

• Standardization of detection methods:

  • Variability in antibody performance across different samples and techniques

  • Need for quantitative assessment methods with reproducible cutoff values

• Biological complexity:

  • Cancer type-specific relationships with prognosis and immune parameters

  • Potential confounding by other tubulin family members

  • Differences between mRNA and protein expression correlations

• Clinical validation requirements:

  • Prospective studies needed to confirm predictive value

  • Large cohorts required for biomarker validation across cancer subtypes

  • Integration with existing biomarker panels

• Technical considerations:

  • Pre-analytical variables affecting TUBA1C detection

  • Need for comparison across multiple detection platforms

  • Development of clinically applicable assays

Addressing these challenges requires multi-institutional collaboration, standardized protocols, and rigorous biostatistical approaches to establish TUBA1C as a reliable biomarker for cancer diagnosis, prognosis, or treatment selection .