GTSE1 Antibody

What is GTSE1 and why is it important in cancer research?

GTSE1 is a microtubule-associated protein that regulates cell cycle progression, particularly during G2 and S phases. It has emerged as a significant oncogenic factor across multiple cancer types. GTSE1 promotes malignant progression by:

• Enhancing cell proliferation through modulation of cell cycle transition, particularly G1/S phase

• Promoting cell migration and invasion via regulation of epithelial-mesenchymal transition (EMT)

• Contributing to chemoresistance, particularly to cisplatin in clear cell renal cell carcinoma (ccRCC)

• Correlating with immune cell infiltration in tumor microenvironments

Research significance: GTSE1 overexpression correlates with poor clinical outcomes in multiple cancers, making it a valuable prognostic biomarker and potential therapeutic target .

What are the standard applications for GTSE1 antibodies in research?

GTSE1 antibodies are versatile tools employed across multiple research applications:

Methodological approach: Selection of application should be guided by research question. For protein level quantification, WB is preferred; for spatial distribution in tissues, IHC/IF is optimal; for cell-by-cell analysis in heterogeneous populations, flow cytometry is recommended .

What expression pattern does GTSE1 show in normal versus cancer tissues?

GTSE1 shows distinctive expression patterns that vary between normal and malignant tissues:

Normal tissues:

• Low expression in G1 phase cells of non-transformed cell lines

• Minimal detection during G1, with levels increasing during S phase and peaking in G2/M

• Primary expression in proliferating tissues

Cancer tissues:

• Significantly overexpressed in multiple cancer types, including:

  • Clear cell renal cell carcinoma (ccRCC)

  • Hepatocellular carcinoma (HCC)

  • Breast cancer

• Elevated expression across all cell cycle phases in transformed cells compared to normal cells

• Particularly notable: GTSE1 is abundant in G1 phase of cancer cells, whereas it's nearly undetectable in G1 of normal cells

Methodological significance: When designing experiments, researchers should account for cell cycle phase-specific expression patterns and use appropriate synchronization techniques to accurately compare GTSE1 levels between normal and cancer samples .

How can I validate GTSE1 antibody specificity for my experimental system?

Rigorous validation is crucial for reliable GTSE1 antibody-based experiments. Implement these methodological approaches:

• Positive and negative controls:

  • Positive: Cell lines with known GTSE1 expression (e.g., HeLa, SH-SY5Y, MCF-7, 786-O cells)

  • Negative: GTSE1 knockdown via siRNA or shRNA

  • G1-arrested non-transformed cells (very low GTSE1 expression)

• Multiple antibody validation:

  • Test antibodies targeting different epitopes (N-terminal vs. C-terminal)

  • Compare polyclonal vs. monoclonal antibodies when available

• Specific validation techniques:

  • Western blot: Verify single band at expected molecular weight (66-77 kDa, sometimes 100 kDa)

  • IHC/IF: Compare with RNA expression data from databases like TCGA

  • Peptide competition assay: Pre-incubate antibody with immunizing peptide to confirm specificity

• Cell cycle-specific validation:

  • Synchronize cells and confirm GTSE1 detection primarily in G2/S phases

  • Compare with cell cycle markers to confirm cell cycle-dependent expression pattern

Research applications demonstrate that proper validation can resolve discrepancies in reported molecular weights (66-77 kDa vs. 100 kDa) that may result from post-translational modifications or splice variants .

What methodological approaches help optimize GTSE1 detection in different sample types?

Successful GTSE1 detection requires optimization strategies tailored to sample type:

For Western blotting:

• Protein extraction: RIPA lysis buffer containing 0.1M PMSF and 1% protease/phosphatase inhibitors

• Sample preparation: Denature by boiling for 10min with 5x loading buffer

• Membrane selection: 0.45μm PVDF membranes show superior protein retention

• Primary antibody incubation: Overnight at 4°C after blocking with 5% nonfat milk

For IHC in tissue samples:

• Antigen retrieval: TE buffer pH 9.0 or citrate buffer pH 6.0

• Scoring system: Combine staining intensity (0-3+) with percentage of positive cells (0-4)

• Final scoring calculation: Negative (0), weak (1-4), moderate (5-8), strong (9-12)

For cell line immunofluorescence:

• Secondary antibody selection: Rhodamine-labeled anti-rabbit IgG works effectively

• Nuclear counterstain: DAPI for DNA visualization

Methodological insight: The expression pattern of GTSE1 is highly cell cycle-dependent, so researchers should consider cell synchronization or co-staining with cell cycle markers for accurate interpretation .

How do I resolve contradictory results in GTSE1 molecular weight detection?

GTSE1 antibodies detect varying molecular weights (66-77 kDa, sometimes 100 kDa), which can create interpretation challenges . To resolve such discrepancies:

• Understand biological factors affecting detection:

  • Phosphorylation status: GTSE1 becomes hyperphosphorylated in mitosis, increasing apparent molecular weight

  • Cell cycle stage: Different modifications occur at different cell cycle phases

  • Splice variants: Different isoforms may exist in different cell types

• Technical approach to resolution:

  • Use phosphatase treatment on some samples to determine if phosphorylation causes the shift

  • Include positive control lysates from characterized cell lines (HeLa, MCF-7)

  • Test multiple antibodies targeting different epitopes

  • Use gradient gels for better separation of higher molecular weight proteins

  • Consider using knockout/knockdown controls to verify specificity

• Analytical considerations:

  • Document exact experimental conditions when observing different molecular weights

  • Consider using mass spectrometry to identify the exact protein being detected

  • Cross-reference with transcriptomic data to identify potential splice variants

Research context: The electrophoretic mobility of GTSE1 increases during mitotic exit, suggesting dynamic post-translational modifications throughout the cell cycle .

How can GTSE1 antibodies be used to study cancer progression mechanisms?

GTSE1 antibodies enable mechanistic studies of cancer progression through multiple approaches:

• EMT regulation investigation:

  • Use GTSE1 antibodies alongside EMT markers (N-cadherin, β-catenin, Snail) to study correlation

  • Research demonstrates GTSE1 knockdown downregulates these EMT markers, while overexpression upregulates them

  • Methodological approach: Combine IF co-staining with protein quantification via WB

• Cell cycle dynamics:

  • GTSE1 knockdown delays G1/S phase transition

  • Methodological approach: Combine GTSE1 staining with EdU incorporation assays for DNA replication activity

• Migration and invasion studies:

  • GTSE1 functions as an EB1-dependent plus-end tracking protein (+TIP) regulating microtubule dynamics

  • Methodological approach: Use GTSE1 antibodies in combination with EB1 co-staining to visualize microtubule plus-end tracking activity

• Tumor microenvironment analysis:

  • GTSE1 expression correlates with immune cell infiltration

  • Methodological approach: Multiplex IHC to simultaneously detect GTSE1 and immune cell markers in tissue sections

Research data shows GTSE1 silencing significantly reduced colony formation (QGY-7703: 529.67 ± 59.53 vs. 262.67 ± 21.385, P = 0.002; SMMC-7721: 416.33 ± 21.962 vs. 139.00 ± 5.292, P = 0.001), while overexpression increased colony formation (QGY-7703: 102.33 ± 11.68 vs. 168.33 ± 9.29, P = 0.002) .

What methodologies are recommended for studying GTSE1-mediated drug resistance?

GTSE1 contributes to chemoresistance in multiple cancers, particularly cisplatin resistance in ccRCC . Recommended experimental approaches include:

• Drug sensitivity assays:

  • Compare IC50 values between GTSE1-high and GTSE1-low cells

  • Methodology: MTT/XTT assays, colony formation assays following drug treatment

  • Research indicates high GTSE1 correlates with chemo-resistance, while low GTSE1 increases drug sensitivity

• Mechanistic pathway investigation:

  • GTSE1 regulates p53-induced apoptosis

  • GTSE1 influences cell cycle checkpoints

  • Methodology: Combine drug treatment with apoptosis markers (Annexin V/PI staining) and cell cycle analysis

• Gene expression correlation analysis:

  • Analyze correlation between GTSE1 and DNA repair genes

  • Methodology: qRT-PCR validation of GTSE1-associated gene expression patterns

• Clinical correlation approaches:

  • Compare GTSE1 expression in pre-treatment versus relapsed patient samples

  • Research shows GTSE1 expression correlates with homologous recombination deficiency (HRD)

  • Methodology: IHC scoring in patient tissue microarrays before and after treatment

Research context: Functional enrichment analysis indicates GTSE1 and its co-expressed genes relate to cell cycle, DNA replication, and immunoreaction through multiple signaling pathways, including P53 and T-cell receptor signaling .

How can I use GTSE1 antibodies to study its relationship with tumor-infiltrating immune cells?

Recent research reveals significant correlations between GTSE1 expression and immune infiltration . Methodological approaches include:

• Multiplex immunohistochemistry:

  • Simultaneous detection of GTSE1 and immune cell markers in tissue sections

  • Research markers: T cells (CD8+, CD4+), macrophages (M0, M1, M2), dendritic cells, neutrophils

• Flow cytometry-based approaches:

  • Combine GTSE1 staining with immune cell markers for single-cell analysis

  • Methodology: Dual or triple staining protocols to correlate GTSE1 with specific immune populations

• Correlation analysis with immune checkpoint molecules:

  • Research demonstrates relationships between GTSE1 and immune checkpoint expression

  • Methodology: Use parallel sections for GTSE1 and checkpoint protein staining

Research data shows significant correlations between GTSE1 expression and:

• B cells (r = 0.278, p = 1.9e−06)

• CD8+ T cells (r = 0.165, p = 5.43e−04)

• CD4+ T cells (r = 0.251, p = 4.89e−08)

• Macrophages (r = 0.165, p = 4.44e−04)

• Neutrophils (r = 0.285, p = 5.47e−10)

• Dendritic cells (r = 0.33, p = 4.99e−13)

High GTSE1 expression correlates with increased infiltration of T cells (CD8+, follicular helper, Tregs), monocytes, macrophages (M0, M1, M2), resting dendritic cells, and neutrophils .

What controls are essential when using GTSE1 antibodies for cancer biomarker studies?

Robust controls are critical for reliable GTSE1 biomarker studies:

• Tissue controls:

  • Positive controls: Use tissues with confirmed high GTSE1 expression (e.g., ccRCC tissues, HCC tissues)

  • Negative controls: Normal adjacent tissues with low proliferative activity

  • Internal controls: Proliferating vs. non-proliferating regions within the same sample

• Cell line controls:

  • Positive: HeLa, SH-SY5Y, MCF-7, 786-O, Caki-1, RCC-4, SW839, 769-P, OS-RC-2

  • Negative/low expression: HK-2 (human renal tubular epithelial cell line)

  • Validation controls: GTSE1 knockdown and overexpression cell lines

• Technical controls:

  • Antibody validation: Omit primary antibody, use isotype control

  • Quantification controls: Include calibration standards for densitometry analysis

  • Reproducibility controls: Technical and biological replicates

• Cell cycle-specific controls:

  • G1-arrested cells: Very low GTSE1 expression

  • G2/M-enriched cells: High GTSE1 expression

  • Methodology: Use cell synchronization techniques (e.g., nocodazole treatment) to prepare phase-specific controls

Methodological approach: When scoring GTSE1 expression in tissue samples, combine staining intensity (0-3+) with percentage of positive cells (0-4) for a comprehensive score .

How can I optimize GTSE1 antibody performance for challenging sample types?

When working with challenging samples, consider these optimization strategies:

• Formalin-fixed, paraffin-embedded (FFPE) tissues:

  • Extended antigen retrieval: TE buffer pH 9.0 or citrate buffer pH 6.0

  • Signal amplification: Consider tyramide signal amplification for low abundance detection

  • Background reduction: Extended blocking (5% BSA or 10% normal serum)

  • Antibody concentration: Test higher concentrations (1:20-1:50) with extended incubation

• Archived or degraded samples:

  • Target epitope selection: C-terminal antibodies may perform better in partially degraded samples

  • Use polymer detection systems for enhanced sensitivity

  • Consider dual antibody approach: Use two antibodies targeting different epitopes

• Cell lines with variable expression:

  • Cell synchronization: Enrich for G2/S phase cells to maximize GTSE1 detection

  • Adapt lysis conditions: RIPA buffer with 0.1M PMSF and 1% protease/phosphatase inhibitors

  • Optimize protein loading: Higher amounts for low-expressing samples

• Multiplexed detection:

  • Sequential immunostaining with careful antibody stripping between rounds

  • Spectral unmixing for fluorescent detection of multiple markers

  • Consider using antibodies raised in different host species to avoid cross-reactivity

Research context: IHC scoring systems should account for both intensity and percentage of positive cells for comprehensive assessment of GTSE1 expression .

What are the technical considerations for quantifying GTSE1 expression in translational research?

Accurate GTSE1 quantification requires careful technical considerations:

• Standardized scoring methods for IHC:

  • Staining intensity: Score as 0 (negative), 1+ (weak), 2+ (moderate), 3+ (strong)

  • Percentage of positive cells: 0 (0%), 1 (1%-25%), 2 (26%-50%), 3 (51%-75%), 4 (76%-100%)

  • Final score calculation: 0 (negative), 1-4 (weak), 5-8 (moderate), 9-12 (strong)

• Western blot quantification:

  • Loading controls: GAPDH is commonly used

  • Densitometry: Use linear range of detection

  • Normalization: Account for cell cycle distribution differences between samples

• Transcriptional analysis integration:

  • Correlation between protein and mRNA levels

  • qRT-PCR primers: GTSE1 (F: CCACCGGGATGTTCTCCCT, R: TTCAGCCCCAACTTGTTTGGA)

  • Normalization gene: GAPDH (F: ACCCAGAAGACTGTGGATGG, R: CAGTGAGCTTCCCGTTCAG)

• Statistical analysis approaches:

  • Survival analysis: Kaplan-Meier with log-rank test using high vs. low GTSE1 expression

  • Correlation analysis: Spearman's method for analyzing relationships with immune markers

  • Multivariate analysis: Cox regression to assess independent prognostic value

Research application: In ccRCC tissue microarray analysis, GTSE1 IHC scoring successfully distinguished expression differences between tumor and normal tissues, correlating with clinical parameters and prognosis .

How might GTSE1 antibodies be used in developing targeted cancer therapies?

GTSE1 antibodies can facilitate several approaches to therapeutic development:

• Target validation strategies:

  • Use antibodies to confirm GTSE1 overexpression in patient-derived samples

  • Correlate expression with treatment response in retrospective studies

  • Develop tissue microarray screening to identify patient populations most likely to benefit

• Mechanism-based drug development:

  • Screen for compounds that modulate GTSE1 expression or function

  • Use antibodies to monitor GTSE1 downregulation in drug screens

  • Investigate the interaction between GTSE1 and p53 for targeted intervention

• Combination therapy approaches:

  • Study GTSE1 expression in relation to immune checkpoint inhibitor response

  • Research shows GTSE1 correlates with immune cell infiltration, suggesting potential for immunotherapy combinations

  • Use GTSE1 antibodies to monitor changes during treatment with chemotherapy agents like cisplatin

• Biomarker development:

  • Standardize GTSE1 IHC protocols for patient stratification

  • Develop multiplexed assays combining GTSE1 with other prognostic markers

  • Create companion diagnostic approaches for future GTSE1-targeted therapies

Research significance: The association between GTSE1 and cisplatin resistance in ccRCC suggests potential as a predictive biomarker for treatment response and as a target to overcome resistance .

What are the methodological challenges in developing GTSE1 as a clinical biomarker?

Developing GTSE1 as a clinical biomarker faces several technical and biological challenges:

• Antibody standardization issues:

  • Different antibodies target different epitopes with varying specificity

  • Need for standardized protocols across laboratories

  • Validation across multiple sample types and preservation methods

• Expression pattern complexity:

  • Cell cycle-dependent expression complicates interpretation

  • Heterogeneous expression within tumors requires careful sampling

  • Need to establish clinically relevant cutoff values for "high" vs. "low" expression

• Technical standardization needs:

  • Automated vs. manual scoring systems

  • Digital pathology integration for quantitative assessment

  • Quality control measures for clinical laboratory implementation

• Biological context considerations:

  • GTSE1's multiple biological functions (cell cycle, migration, EMT) require careful interpretation

  • Integration with other biomarkers for comprehensive assessment

  • Accounting for tumor microenvironment influences on expression

Research context: Studies have demonstrated GTSE1's prognostic value in multiple cancers, including ccRCC and HCC, but standardized clinical protocols need development .

How can researchers integrate GTSE1 data with other -omics approaches for comprehensive cancer profiling?

Integrative approaches combining GTSE1 with other -omics data offer powerful insights:

• Multi-omics integration strategies:

  • Correlate GTSE1 protein expression (antibody-based) with transcriptomic data

  • Integrate with genomic alterations affecting the GTSE1 locus

  • Combine with epigenomic profiles to understand regulatory mechanisms

• Pathway analysis approaches:

  • Research shows GTSE1 associates with cell cycle, DNA replication, and immune response pathways

  • Study relationships with P53 signaling and T-cell receptor signaling pathways

  • Correlate with homologous recombination deficiency (HRD) status

• Single-cell analysis techniques:

  • Combine GTSE1 antibody-based detection with single-cell RNA sequencing

  • Study heterogeneity of expression within tumors

  • Relate to cell states and differentiation hierarchies

• Clinical data integration:

  • Correlate GTSE1 expression with treatment response data

  • Develop predictive models combining GTSE1 with other molecular and clinical factors

  • Network analysis to identify key interacting partners for combination targeting

Research application: GTSE1 functional enrichment analysis has already identified associations with cell cycle regulation, DNA replication, and immune response pathways, providing a foundation for integrated multi-omics approaches .