ST6GAL1 Antibody

What is ST6GAL1 and why is it significant in cancer research?

ST6GAL1 (ST6 β-galactoside α-2,6-sialyltransferase 1) is a Golgi-resident enzyme that catalyzes the addition of sialic acid in an α-2,6 linkage to terminal galactose residues on N-glycans. ST6GAL1 has gained significant attention in cancer research because it is upregulated in numerous human malignancies . The enzyme plays important roles in tumor progression through multiple mechanisms, including modulating cell adhesion, migration, and resistance to apoptosis. Its expression pattern varies across different cancer types, making it a potential biomarker and therapeutic target. Recent studies have specifically linked ST6GAL1 to cisplatin resistance in ovarian cancer cells , suggesting its role in treatment response and chemoresistance mechanisms.

How can I confirm the specificity of my ST6GAL1 antibody?

To confirm antibody specificity for ST6GAL1, implement a multi-tier validation approach:

• Use positive and negative control cell lines with confirmed ST6GAL1 expression levels (e.g., ST6GAL1-overexpressing cells versus knockdown cells)

• Compare staining patterns with expected Golgi localization (as ST6GAL1 is a Golgi-resident enzyme)

• Verify the molecular weight (~50 kDa for full-length ST6GAL1) in immunoblotting experiments

• Test antibody reactivity in cells where ST6GAL1 has been genetically manipulated (overexpressed or knocked down)

This validation is particularly important as some commercial antibodies advertised as targeting ST6GAL1 actually recognize unrelated epitopes . For example, studies have demonstrated that the LN1 and ZB55 antibodies, commonly mislabeled as ST6GAL1 antibodies, do not specifically detect this protein despite being widely used in research .

What applications are supported by validated ST6GAL1 antibodies?

Validated ST6GAL1 antibodies have been successfully employed in multiple research applications:

• Western Blot/Immunoblotting: Detecting ST6GAL1 protein (approximately 50-56 kDa) in cell and tissue lysates

• Immunohistochemistry (IHC): Visualizing ST6GAL1 expression in paraffin-embedded tissue sections, including liver and prostate tissues

• Immunocytochemistry/Immunofluorescence (ICC/IF): Localizing ST6GAL1 to the Golgi apparatus in cultured cells

• Simple Western™ analysis: Automated protein separation and detection

For optimal results, experimental conditions should be tailored to each application. For instance, in IHC applications, heat-induced epitope retrieval using basic antigen retrieval reagents has shown good results with validated antibodies .

How can I distinguish between cell surface sialylation patterns and ST6GAL1 protein expression?

This distinction requires a dual analytical approach:

• For ST6GAL1 protein detection:

  • Use validated ST6GAL1-specific antibodies in immunoblotting or immunostaining experiments

  • Focus on Golgi localization patterns typical of ST6GAL1

  • Confirm with appropriate molecular weight detection (~50 kDa)

• For sialylation pattern analysis:

  • Employ lectins specific for α-2,6-sialylated glycans (e.g., Sambucus nigra agglutinin, SNA)

  • Use mass spectrometry to characterize sialic acid linkages on glycoproteins

  • Perform glycomic profiling of cell surface glycoproteins

Remember that CD75 epitopes (sometimes incorrectly used as synonyms for ST6GAL1) actually represent sialylated structures rather than the ST6GAL1 enzyme itself . Therefore, antibodies detecting CD75 (like LN1 and ZB55) are not suitable for ST6GAL1 protein detection but might still provide information about sialylation patterns.

What strategies can address contradictory findings regarding ST6GAL1 expression in cancer tissues?

Contradictory findings about ST6GAL1 expression in cancer often stem from methodological differences and antibody specificity issues. To address these contradictions:

• Antibody validation:

  • Meticulously validate all antibodies used for ST6GAL1 detection

  • Avoid antibodies initially developed as CD75-recognizing antibodies (e.g., LN1, ZB55)

  • Use antibodies with confirmed specificity through knockout/overexpression controls

• Multi-method verification:

  • Combine protein detection (Western blot) with enzymatic activity assays

  • Correlate protein expression with mRNA levels via qRT-PCR

  • Assess functional consequences through glycan profiling

• Contextual analysis:

  • Consider tissue-specific expression patterns and heterogeneity

  • Account for differences in sample preparation and analysis techniques

  • Evaluate association with clinical parameters across different studies

For example, recent research demonstrated that ST6GAL1 is actually overexpressed in bladder cancer, contradicting earlier studies that used the non-specific LN1 antibody and incorrectly suggested ST6GAL1 downregulation in this cancer type .

How should I design experiments to assess the functional consequences of ST6GAL1 activity?

Designing experiments to assess ST6GAL1 function requires manipulating enzyme expression/activity and measuring resulting phenotypic changes:

• Genetic manipulation approaches:

  • Overexpression models: Generate stable cell lines expressing ST6GAL1 (example: OV4 ovarian cancer cells with forced ST6GAL1 expression)

  • Knockdown/knockout models: Create ST6GAL1-deficient cells using shRNA or CRISPR-Cas9

  • Rescue experiments: Re-express ST6GAL1 in knockout cells to confirm phenotype specificity

• Functional readouts:

  • Cell proliferation and viability assays

  • Migration and invasion assays

  • Apoptosis resistance measurements (particularly in response to chemotherapeutics)

  • Receptor activation studies (focusing on sialylated receptors)

• Glycobiological assessments:

  • Lectin binding assays to measure α-2,6-sialylation levels

  • Mass spectrometry analysis of N-glycan profiles

  • Sialidase treatment controls to confirm sialylation-dependent effects

For example, research with ovarian cancer cells has demonstrated that cisplatin-resistant cells upregulate endogenous ST6GAL1, suggesting a functional link between ST6GAL1 expression and chemoresistance that could be further explored using these methodological approaches .

Why might Western blot detection of ST6GAL1 show multiple bands or unexpected molecular weights?

Multiple bands or unexpected molecular weights in ST6GAL1 Western blots may result from several factors:

• Post-translational modifications:

  • ST6GAL1 undergoes glycosylation, which can alter its apparent molecular weight

  • Different glycoforms may appear as distinct bands

  • Enzymatic deglycosylation experiments can help resolve this issue

• Protein processing:

  • ST6GAL1 contains a signal peptide that is cleaved during maturation

  • Partial proteolysis during sample preparation may generate fragments

  • Both membrane-bound and soluble forms exist, with different molecular weights

• Antibody specificity issues:

  • Non-specific antibodies (like ZB55 and LN1) show multiple non-ST6GAL1 bands in all cell types

  • Validated antibodies should detect a primary band at approximately 50-56 kDa

When troubleshooting, compare your results with appropriate positive controls (cells with confirmed ST6GAL1 expression) and negative controls (ST6GAL1 knockout cells). The validated R&D antibody has been shown to detect a single band at ~50 kD in ST6GAL1-expressing cells .

What are optimal sample preparation methods for preserving ST6GAL1 epitopes in immunohistochemistry?

For optimal immunohistochemical detection of ST6GAL1:

• Tissue fixation and processing:

  • Formalin fixation (4% paraformaldehyde) is generally effective

  • Paraffin embedding provides good morphological preservation

  • Freshly prepared sections yield better results than archived samples

• Epitope retrieval:

  • Heat-induced epitope retrieval using basic antigen retrieval reagents has proven effective

  • pH-optimized buffers (typically basic pH) improve antigen accessibility

  • Standardize heating duration and temperature for consistent results

• Blocking and antibody incubation:

  • Thorough blocking reduces background staining

  • Optimize primary antibody concentration (0.3-1.0 μg/mL has been effective for validated antibodies)

  • Room temperature incubation for approximately 1 hour often yields good results

• Detection systems:

  • HRP polymer detection systems provide sensitive visualization

  • DAB (3,3'-Diaminobenzidine) produces a stable brown reaction product

  • Counterstaining with hematoxylin helps visualize tissue architecture

These parameters have successfully demonstrated specific ST6GAL1 localization in cytoplasm and Golgi of various human tissues, including liver hepatocytes and prostate glandular epithelial cells .

How can I differentiate between ST6GAL1 and other sialyltransferases in experimental systems?

Differentiating ST6GAL1 from other sialyltransferases requires a combination of specific detection and functional characterization:

• Selective antibody detection:

  • Use thoroughly validated ST6GAL1-specific antibodies

  • Verify antibody cross-reactivity with related sialyltransferases (particularly ST6GAL2)

  • Consider epitope mapping to confirm binding to unique ST6GAL1 regions

• Expression analysis:

  • Perform qRT-PCR with primer sets specific to different sialyltransferase family members

  • Use RNA-seq data to compare expression patterns across the sialyltransferase family

  • Analyze tissue-specific expression patterns to identify characteristic distributions

• Enzyme activity discrimination:

  • Utilize specific acceptor substrates preferentially used by ST6GAL1

  • Analyze linkage specificity (α-2,6 versus α-2,3) using linkage-specific lectins

  • Conduct competition assays with selective inhibitors

• Genetic approaches:

  • Create selective knockdown of ST6GAL1 while monitoring other sialyltransferases

  • Perform rescue experiments with ST6GAL1 or other sialyltransferases

  • Use CRISPR-Cas9 for precise gene editing of specific sialyltransferases

These approaches ensure that experimental observations are specifically attributed to ST6GAL1 rather than other members of the sialyltransferase family that may have overlapping but distinct functions.

How does ST6GAL1 contribute to drug resistance mechanisms in cancer?

ST6GAL1's role in drug resistance has emerged as an important research area, particularly in the context of chemotherapy response:

• Cisplatin resistance correlation:

  • Cisplatin-resistant cancer cells demonstrate upregulated ST6GAL1 expression

  • When ST6GAL1 is knocked down in Pa-1 ovarian cancer cells (which naturally express high levels), cisplatin exposure for three weeks leads to re-expression of ST6GAL1 in the surviving population

  • A2780 ovarian cancer cells with acquired cisplatin resistance show elevated ST6GAL1 levels compared to parental cells

• Molecular mechanisms:

  • ST6GAL1-mediated sialylation modifies cell surface receptors involved in survival signaling

  • Sialylation may affect drug uptake or efflux through altered membrane glycoprotein function

  • Modified glycans potentially influence apoptotic pathway activation in response to chemotherapeutics

• Potential as therapeutic target:

  • Inhibiting ST6GAL1 might sensitize resistant cells to chemotherapy

  • Monitoring ST6GAL1 expression could serve as a biomarker for predicting treatment response

  • Combination therapies targeting both ST6GAL1 and cancer cells might overcome resistance

These findings suggest that ST6GAL1 upregulation represents an adaptive mechanism employed by cancer cells to survive chemotherapeutic stress, positioning it as a potential target for overcoming drug resistance.

What cell and animal models are most appropriate for studying ST6GAL1 function in specific pathological contexts?

Selecting appropriate models for ST6GAL1 research depends on the specific pathological context being investigated:

• Cell models:

  • Cancer studies:

    • Cell lines with variable ST6GAL1 expression (high: Pa-1 ovarian cancer; low/none: OV4 ovarian cancer, Suit2 pancreatic cancer)

    • Paired sensitive/resistant cell lines (e.g., A2780 and cisplatin-resistant derivatives)

  • Immune function studies:

    • Daudi Burkitt's lymphoma cells (express ST6GAL1)

    • Primary immune cells with manipulated ST6GAL1 expression

  • Genetically modified models:

    • CRISPR-engineered cell lines with ST6GAL1 knockout

    • Stable overexpression systems in low-expressing backgrounds

    • Inducible expression systems for temporal control

• Animal models:

  • Genetically engineered mouse models (GEMMs):

    • Whole-body St6gal1 knockout mice

    • Tissue-specific knockout models using Cre-lox systems

    • Conditional expression models for temporal control

  • Xenograft models:

    • Human cancer cells with manipulated ST6GAL1 expression implanted in immunodeficient mice

    • Patient-derived xenografts with characterized ST6GAL1 status

  • Disease-specific models:

    • Cancer models reflecting specific tumor types where ST6GAL1 is clinically relevant

    • Inflammatory disease models to study ST6GAL1 in immune regulation

• Ex vivo systems:

  • Organoids derived from primary tissues

  • Patient-derived tissue slices maintaining original architecture

  • Co-culture systems to study cell-cell interactions

The selection of appropriate models should be guided by the specific research question, with consideration of species differences in glycosylation patterns and ST6GAL1 regulation.

How can I integrate ST6GAL1 protein expression data with glycomics to understand functional consequences?

Integrating ST6GAL1 protein data with glycomics provides deeper insights into functional outcomes:

• Correlation approaches:

  • Measure ST6GAL1 protein expression using validated antibodies

  • Perform glycomic profiling of the same samples via mass spectrometry

  • Analyze statistical correlations between enzyme levels and specific glycan structures

  • Map changes in α-2,6-sialylation patterns to specific carrier proteins

• Temporal analysis:

  • Monitor ST6GAL1 expression and glycan profiles over time following experimental manipulation

  • Track the kinetics of glycan changes in response to altered ST6GAL1 levels

  • Establish cause-effect relationships between enzyme expression and glycan modifications

• Functional glycomics:

  • Identify specific glycoproteins affected by ST6GAL1 activity using lectin affinity purification

  • Perform glycoproteomic analysis to map sialylation sites on individual proteins

  • Connect sialylation changes to altered protein-protein interactions or receptor function

  • Use lectin microarrays to profile global glycan changes in response to ST6GAL1 manipulation

• Multi-omics integration:

  • Combine glycomics with transcriptomics, proteomics, and metabolomics data

  • Apply bioinformatic approaches to identify regulatory networks affected by ST6GAL1 activity

  • Use systems biology models to predict functional consequences of altered sialylation

This integrated approach allows researchers to move beyond simple correlations to establish mechanistic understanding of how ST6GAL1-mediated sialylation influences cellular phenotypes in normal and pathological contexts.

What are the implications of ST6GAL1 tissue specificity for developing targeted therapeutic approaches?

ST6GAL1 exhibits distinct tissue expression patterns that can inform therapeutic strategy development:

• Tissue expression profiling:

  • ST6GAL1 has been detected in various human tissues including liver hepatocytes, prostate glandular epithelial cells, and certain cancer cell types

  • Some tissues and cell lines naturally lack ST6GAL1 expression (e.g., OV4 ovarian cancer cells)

  • Expression patterns differ between normal and disease states, particularly in cancer

• Therapeutic targeting considerations:

  • Tissue-specific delivery systems could target organs with pathological ST6GAL1 overexpression

  • Differential expression between normal and diseased tissue provides a potential therapeutic window

  • Cancer-specific ST6GAL1 isoforms or regulatory mechanisms might enable selective targeting

• Biomarker applications:

  • Tissue-specific ST6GAL1 expression patterns could serve as diagnostic or prognostic biomarkers

  • Changes in expression could indicate disease progression or treatment response

  • Combining tissue expression data with functional glycomics might identify patient subgroups

• Personalized medicine approaches:

  • ST6GAL1 expression profiling in patient samples could guide treatment selection

  • Correlation with drug resistance mechanisms might predict therapy response

  • Combination therapies could be designed based on ST6GAL1 status and associated pathways

Understanding the tissue-specific regulation and function of ST6GAL1 will be crucial for developing therapeutic approaches that maximize efficacy while minimizing off-target effects in tissues where ST6GAL1 plays important physiological roles.

How does the confusion between CD75 and ST6GAL1 impact interpretation of historical research findings?

The historical confusion between CD75 and ST6GAL1 has significant implications for interpreting research literature: