ST6GALNAC1 Antibody, HRP conjugated

What is ST6GALNAC1 and what is its biological significance?

ST6GALNAC1 (ST6 N-Acetylgalactosaminide Alpha-2,6-Sialyltransferase 1) is a sialyltransferase enzyme that catalyzes the synthesis of cancer-related sialyl-Tn (STn) antigen, which is critical for cell mobility . This enzyme acts specifically on the O-linked glycosylation pathway, adding sialic acid residues in an α-2,6 linkage to the GalNAc residue of the Tn antigen. The resulting STn antigen has been implicated in various cancer types and is associated with increased cancer aggressiveness and poor prognosis .

ST6GALNAC1 has a calculated molecular weight of 69 kDa, though the observed molecular weight in experimental conditions typically ranges between 66-69 kDa . The enzyme is encoded by the ST6GALNAC1 gene (NCBI Gene ID: 55808), and its expression has been documented in various tissues, with notable overexpression in several cancer types including colorectal, gastric, breast, and prostate cancers .

How does ST6GALNAC1 antibody with HRP conjugation differ from unconjugated versions?

ST6GALNAC1 antibody with HRP (Horseradish Peroxidase) conjugation provides direct enzymatic labeling, eliminating the need for secondary antibody incubation in detection protocols. This conjugation offers several methodological advantages over unconjugated antibodies:

• Simplified workflow with fewer incubation and washing steps

• Reduced background signal by eliminating potential cross-reactivity of secondary antibodies

• Enhanced sensitivity for low-abundance target detection

• Direct compatibility with chromogenic substrates like TMB (3,3',5,5'-Tetramethylbenzidine) and DAB (3,3'-Diaminobenzidine)

• Reduced total assay time in Western blots, ELISA, and immunohistochemistry applications

When selecting between conjugated and unconjugated antibodies, researchers should consider specific experimental requirements including detection sensitivity needs, available instrumentation, and the complexity of the target tissue or sample.

What are the optimal sample preparation techniques for ST6GALNAC1 detection in different tissue types?

Optimal sample preparation for ST6GALNAC1 detection varies by tissue type and application:

For Western Blot applications:

• Extract proteins using RIPA buffer supplemented with protease inhibitors

• For colorectal tissues, homogenize samples in cold buffer (150 mM NaCl, 50 mM Tris-HCl pH 7.4, 1% NP-40, 0.1% SDS) with protease inhibitors

• Load 20-40 μg of total protein per lane

• Use fresh or properly stored (-80°C) samples to prevent degradation

For Immunohistochemistry:

• Use formalin-fixed, paraffin-embedded (FFPE) tissue sections (4-6 μm thick)

• Perform antigen retrieval with TE buffer pH 9.0 (optimal for ST6GALNAC1)

• Alternative: citrate buffer pH 6.0 may be used for certain tissue types

• Block endogenous peroxidase activity with 3% hydrogen peroxide before primary antibody incubation

• For human skin tissue, recommended dilution ranges from 1:50 to 1:500

Different tissue types show variable ST6GALNAC1 expression, with positive detection documented in mouse colon and small intestine tissues, rat colon and small intestine tissues, and human skin samples .

How can ST6GALNAC1 antibody be used to investigate cancer stem cell populations?

ST6GALNAC1 plays a crucial role in cancer stem cell (CSC) biology, making its antibody detection valuable for CSC research. Methodological approaches include:

• CSC identification and isolation:

  • Use ST6GALNAC1 antibody in combination with established CSC markers (CD44, ALDH1)

  • Employ flow cytometry sorting of STn-positive cells to enrich for CSC populations

  • Validate isolated populations using sphere-forming assays and in vivo tumor initiation tests

• Functional analysis of CSC properties:

  • Assess sphere-forming ability of ST6GALNAC1-high versus ST6GALNAC1-low populations

  • Measure chemoresistance profiles, particularly to 5-FU, in sorted populations

  • Evaluate tumor-initiating capacity through limiting dilution xenograft experiments

Research has demonstrated that ST6GALNAC1 is highly expressed in colorectal cancer stem cells (CR-CSCs/CICs) and that its overexpression enhances the expression of sialyl-Tn (STn) antigen carried by the CSC marker CD44 . This overexpression correlates with increased sphere-forming ability and resistance to chemotherapeutic agents like 5-FU . In contrast, knockdown of ST6GALNAC1 significantly decreases the proportion of CR-CSCs/CICs, reducing their tumor-forming potential in xenograft models and increasing drug sensitivity .

What methodological considerations are important when investigating ST6GALNAC1's role in the Akt signaling pathway?

When investigating ST6GALNAC1's role in the Akt signaling pathway, researchers should implement the following methodological approaches:

• Pathway activation analysis:

  • Use phospho-specific antibodies against key Akt pathway components (p-Akt, p-S6)

  • Employ Western blotting with controlled loading (40-50 μg total protein) and phosphatase inhibitors

  • Normalize phosphorylated protein signals to total protein levels

• Mechanistic interaction studies:

  • Perform co-immunoprecipitation to detect ST6GALNAC1 interactions with galectin-3

  • Use chemical inhibitors of the PI3K/Akt pathway (LY294002, wortmannin) to validate pathway dependence

  • Implement RNAi knockdown of galectin-3 to assess its requirement in ST6GALNAC1-mediated Akt activation

• Functional readouts:

  • Measure cell survival under stress conditions

  • Assess chemoresistance profiles with and without pathway inhibition

  • Quantify CSC phenotypes (sphere formation, marker expression) after pathway manipulation

Research has shown that ST6GALNAC1 overexpression activates the Akt pathway in cooperation with galectin-3, and this activation can be disrupted by galectin-3 knockdown . This mechanistic relationship appears critical for maintenance of cancer stem cell properties and drug resistance, suggesting potential therapeutic approaches.

How can ST6GALNAC1 antibody be used to analyze the regulation of this enzyme by microRNAs?

To analyze microRNA-mediated regulation of ST6GALNAC1, researchers can implement these methodological approaches:

• Expression correlation analysis:

  • Use qRT-PCR to quantify expression levels of ST6GALNAC1 mRNA and candidate miRNAs (miR-21-5p, miR-30e-5p, miR-26b-5p)

  • Perform Western blotting with ST6GALNAC1 antibody to correlate protein levels with miRNA expression

  • Analyze paired normal/tumor samples to establish inverse expression relationships

• Functional validation:

  • Transfect cells with miRNA mimics or inhibitors of candidate miRNAs

  • Measure changes in ST6GALNAC1 expression at both mRNA (qRT-PCR) and protein levels (Western blot)

  • Evaluate STn antigen levels using flow cytometry or immunofluorescence after miRNA manipulation

• Direct binding confirmation:

  • Perform luciferase reporter assays using ST6GALNAC1 3'UTR constructs

  • Introduce mutations in predicted miRNA binding sites to confirm specificity

  • Use RNA immunoprecipitation (RIP) to detect miRNA:mRNA complexes

Research has identified several miRNAs including miR-21-5p, miR-30e-5p, and miR-26b-5p as potential regulators of ST6GALNAC1 in colorectal cancer . These miRNAs show upregulated expression in tumor samples and high binding affinity to the seed region of ST6GALNAC1 . Integration of computational predictions with experimental validation can provide comprehensive insights into the regulatory network controlling ST6GALNAC1 expression.

What controls should be included when using ST6GALNAC1 antibody in cancer research applications?

Robust experimental design with appropriate controls is critical when using ST6GALNAC1 antibody:

For colorectal cancer research specifically, paired normal and tumor tissues from the same patient provide ideal comparative controls. Additionally, inclusion of cell lines with known ST6GALNAC1 expression status (high vs. low) helps validate experimental findings and antibody specificity. When analyzing patient samples, control for clinical variables including cancer stage and treatment history, as ST6GALNAC1 expression has shown stage-specific prognostic value (significant for Stage III and IV but not Stage I and II colorectal cancer) .

What are the optimal dilution and incubation conditions for ST6GALNAC1 antibody across different applications?

Optimal conditions for ST6GALNAC1 antibody use vary by application:

For Western Blot:

• Recommended dilution: 1:500-1:1000

• Primary antibody incubation: 4°C overnight in 5% non-fat milk or BSA in TBST

• Secondary detection: Anti-rabbit HRP (if using unconjugated primary) at 1:3000-1:5000

• For direct HRP-conjugated antibody: Adjust dilution to 1:1000-1:3000

• Development: Standard ECL detection with 1-5 minute exposure

For Immunohistochemistry:

• Recommended dilution: 1:50-1:500

• Primary antibody incubation: 1-2 hours at room temperature or overnight at 4°C

• Substrate development: DAB for 5-10 minutes, monitoring for signal development

• Counterstain: Hematoxylin for 30-60 seconds for nuclear visualization

For ELISA:

• Coating antibody: 1-10 μg/ml in carbonate buffer pH 9.6

• Detection antibody (HRP-conjugated): Begin with 1:1000 and optimize

• Substrate: TMB with 5-15 minute development time

Each application requires optimization based on specific sample types and experimental conditions. Titration experiments are recommended to determine the optimal antibody concentration that provides specific signal with minimal background. The balance between signal intensity and specificity is particularly important when evaluating cancer tissues with variable ST6GALNAC1 expression levels.

How should experiments be designed to evaluate STn antigen presentation in relation to ST6GALNAC1 expression?

To comprehensively evaluate the relationship between ST6GALNAC1 expression and STn antigen presentation, researchers should design experiments incorporating these methodological elements:

• Parallel detection methods:

  • Use ST6GALNAC1 antibody to detect enzyme expression levels

  • Employ STn-specific antibodies (clone TKH2) for glycan detection

  • Implement dual immunofluorescence to co-localize enzyme and glycan

• Carrier protein identification:

  • Perform immunoprecipitation with anti-STn antibody followed by Western blotting

  • Analyze precipitated samples by mass spectrometry for carrier protein identification

  • Validate findings with Western blotting for specific carrier proteins (e.g., CD44)

• Functional manipulation:

  • Create ST6GALNAC1 overexpression and knockdown models

  • Quantify changes in STn levels using flow cytometry and Western blotting

  • Assess biological consequences (migration, invasion, chemoresistance)

Research has identified CD44 as a specific carrier of STn antigen in ST6GALNAC1-overexpressing cells, with a molecular weight of approximately 130 kDa . This finding links ST6GALNAC1 activity directly to modification of cancer stem cell markers, providing mechanistic insight into how ST6GALNAC1 may influence cancer stem cell properties through glycosylation of key surface proteins.

How should researchers interpret discrepancies between ST6GALNAC1 expression and STn antigen levels in tumor samples?

When encountering discrepancies between ST6GALNAC1 expression and STn antigen levels, researchers should consider several methodological approaches for reconciliation:

• Enzymatic redundancy analysis:

  • Evaluate expression of other sialyltransferases capable of synthesizing STn

  • Assess enzyme activity rather than just expression levels

  • Consider post-translational modifications affecting enzyme function

• Substrate availability assessment:

  • Analyze expression of Tn antigen (the substrate for ST6GALNAC1)

  • Evaluate expression of glycosyltransferases involved in competing pathways

  • Consider glycosidase activity that might degrade STn after formation

• Technical considerations:

  • Use multiple antibody clones targeting different epitopes of ST6GALNAC1

  • Implement orthogonal detection methods (protein, mRNA, enzyme activity)

  • Consider sample preparation variables affecting epitope accessibility

Research has demonstrated that STn production is not always directly correlated with ST6GALNAC1 expression levels in colorectal cancer, suggesting the involvement of other sialyltransferases in STn antigen production . Integrated in silico analysis has highlighted that STn production may not be entirely reliant on deregulated sialyltransferase expression in colorectal cancer, and that other mechanisms including the Siglec-15/Sia axis may be involved .

What statistical approaches are most appropriate for analyzing correlations between ST6GALNAC1 expression and clinical outcomes?

When analyzing correlations between ST6GALNAC1 expression and clinical outcomes, researchers should implement these statistical approaches:

• Survival analysis methods:

  • Kaplan-Meier survival curves with log-rank test for comparing ST6GALNAC1-positive vs. negative cases

  • Cox proportional hazards regression for multivariate analysis with clinical covariates

  • Time-dependent ROC curve analysis to evaluate predictive performance

• Expression threshold determination:

  • Receiver Operating Characteristic (ROC) curve analysis to establish optimal cutoff values

  • Qualitative categorization (positive vs. negative) based on percentage of stained cells

  • Quartile or median-based stratification for continuous expression data

• Stratified analysis approaches:

  • Stage-specific survival analysis (separate analyses for early vs. late-stage disease)

  • Treatment-stratified analysis to assess predictive vs. prognostic value

  • Integration with other molecular markers for composite prognostic scoring

How can researchers distinguish between direct effects of ST6GALNAC1 and downstream consequences of STn antigen modification?

To distinguish between direct effects of ST6GALNAC1 and consequences of STn antigen modification, implement these methodological approaches:

• Structure-function analysis:

  • Generate catalytically inactive ST6GALNAC1 mutants through site-directed mutagenesis

  • Compare biological effects of wild-type vs. inactive enzyme expression

  • Assess protein-protein interactions independent of enzymatic activity

• Glycan-specific interventions:

  • Use STn-blocking antibodies without affecting ST6GALNAC1 expression

  • Employ exogenous glycosidases to cleave STn without altering ST6GALNAC1

  • Introduce competing glycosyltransferases to modify glycan patterns

• Carrier protein manipulation:

  • Identify specific STn carrier proteins (e.g., CD44) through immunoprecipitation and mass spectrometry

  • Generate carrier protein mutants lacking glycosylation sites

  • Assess whether carrier protein knockdown eliminates ST6GALNAC1-mediated effects

Research has demonstrated that CD44 serves as a carrier protein for STn antigen in ST6GALNAC1-overexpressing cells . This finding suggests that some biological effects attributed to ST6GALNAC1 may be mediated specifically through modification of CD44, a known cancer stem cell marker. Additionally, the activation of the Akt pathway in ST6GALNAC1-overexpressing cells involves cooperation with galectin-3, suggesting complex downstream signaling networks beyond simple glycan modification .

What are the common technical challenges in detecting ST6GALNAC1 in clinical samples and how can they be addressed?

Common technical challenges in ST6GALNAC1 detection and their solutions include:

When working with clinical samples, pre-analytical variables such as cold ischemia time, fixation duration, and storage conditions can significantly impact ST6GALNAC1 detection. Implementing standardized processing protocols and including appropriate technical controls in each experiment can help address these challenges.

How can researchers validate the specificity of ST6GALNAC1 antibody in their experimental system?

To validate the specificity of ST6GALNAC1 antibody, researchers should implement these methodological approaches:

• Genetic manipulation approaches:

  • Perform siRNA knockdown of ST6GALNAC1 (proven effective with siRNA1 and siRNA3)

  • Create CRISPR/Cas9 knockout cell lines or models

  • Develop overexpression systems with tagged ST6GALNAC1 constructs

• Multiple detection methods:

  • Compare antibody detection with mRNA expression (qRT-PCR)

  • Confirm molecular weight (66-69 kDa) on Western blots

  • Use multiple antibodies targeting different epitopes of the same protein

• Technical validation:

  • Include known positive tissues (colon, small intestine) and negative controls

  • Perform absorption controls by pre-incubating antibody with recombinant antigen

  • Analyze parallel samples with commercial antibodies from different vendors

Research has demonstrated successful validation of ST6GALNAC1 antibody specificity through siRNA knockdown experiments, with siRNA1 and siRNA3 showing significant reduction in both mRNA expression and protein levels . This approach confirms that the antibody is detecting the intended target and not cross-reacting with related proteins.

What optimization strategies should be employed when adapting ST6GALNAC1 antibody protocols for different cancer types?

When adapting ST6GALNAC1 antibody protocols for different cancer types, researchers should implement these optimization strategies:

• Tissue-specific protocol adjustments:

  • Optimize fixation based on tissue density (12-24h for soft tissues, 24-48h for dense tissues)

  • Adjust antigen retrieval conditions based on tissue type (extend time for fibrotic tissues)

  • Modify blocking solutions to address tissue-specific background (add 0.1-0.3% Triton X-100 for high-fat tissues)

• Expression-based adaptations:

  • Adjust antibody concentration based on expected expression levels

  • High expression (breast, gastric cancers): 1:500-1:1000 dilution

  • Low expression (some colorectal cancers): 1:50-1:200 dilution

  • Extend primary antibody incubation for low-expressing tissues (overnight at 4°C)

• Detection system optimization:

  • For tissues with high endogenous peroxidase: extend quenching step (10-15 min with 3% H₂O₂)

  • For autofluorescent tissues: consider chromogenic rather than fluorescent detection

  • For dense tissues: implement signal amplification systems (polymer-based detection)

Research has shown variable ST6GALNAC1 expression across cancer types, with overexpression documented in gastric, breast, and prostate cancer cell lines , while colorectal cancer shows a more complex pattern with significant downregulation in some studies . These differences necessitate cancer-type specific protocol optimization to achieve reliable results.