GLYAT Antibody

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

GLYAT (Glycine N-Acyltransferase) is an enzyme involved in glycine metabolism that has been implicated in the progression of various malignant tumors. Recent research has demonstrated that GLYAT is significantly downregulated in hepatocellular carcinoma (HCC) tissues compared to normal liver tissues . Its clinical relevance lies in its potential as both a diagnostic and prognostic biomarker, with decreased expression correlating with poorer outcomes in HCC patients . The significance of GLYAT extends beyond its role in metabolism, as it appears to influence tumor cell proliferation, invasion, and migration capabilities, making it a promising therapeutic target .

What detection methods are most effective for GLYAT expression analysis?

Multiple complementary techniques provide robust GLYAT expression analysis in research settings:

• RT-qPCR: Effective for quantifying GLYAT mRNA expression levels in cell lines and tissue samples with high sensitivity

• Western blotting: Recommended dilution of 1/1000 for protein detection using GLYAT antibodies

• Immunohistochemistry (IHC): Optimal dilutions range from 1/10 to 1/50 for paraffin-embedded sections

• Immunofluorescence (IF): Useful for cellular localization studies of GLYAT

• ELISA: Provides quantitative measurement of GLYAT in solution

For validation purposes, researchers should employ at least two independent methods when characterizing GLYAT expression, as demonstrated in comprehensive studies where RT-qPCR, Western blotting, and IHC collectively provided consistent evidence of GLYAT downregulation in HCC tissues .

How do GLYAT expression patterns differ across cell lines and tissue types?

Research indicates distinct GLYAT expression patterns across different cellular models:

• Normal liver cells: Higher GLYAT expression observed in LO2 cell line (normal human hepatic cell line)

• HCC cell lines: Significantly lower GLYAT expression in Huh 7, HepG2, PLC, and SK-HEP1 compared to normal liver cells

• Tissue samples: Consistent downregulation in HCC tissues compared to adjacent normal liver tissues, verified through multiple detection methods including RT-qPCR, Western blotting, and immunohistochemistry

Understanding these expression patterns is crucial for experimental design, as researchers should select appropriate cell lines based on their baseline GLYAT expression levels. For instance, Huh 7 cells have been used for knockdown experiments while HepG2 cells were utilized for overexpression studies in functional characterization of GLYAT .

How does GLYAT modulate the tumor immune microenvironment in HCC?

GLYAT expression significantly influences the immune landscape within HCC tumors through multiple mechanisms:

• Immune infiltration correlation: GLYAT expression shows positive correlation with resting mast cells, monocytes, M2 macrophages, M1 macrophages, naive CD4+ T cells, and activated NK cells, while negatively correlating with follicular helper T cells, memory B cells, resting dendritic cells, regulatory T cells (Tregs), and M0 macrophages

• Immune score impact: Low GLYAT expression groups demonstrate higher immune and ESTIMATE scores compared to high GLYAT expression groups, suggesting increased immune cell infiltration in tumors with reduced GLYAT expression

• NK cell activity: GLYAT expression positively correlates with activated NK cells, which are crucial for early immune responses against liver cancer. This suggests that decreased GLYAT may contribute to reduced anti-tumor immunity

• Regulatory T cell relation: Low GLYAT expression associates with increased Tregs, which induce immune tolerance and suppress tumor-specific T cell activity, potentially explaining the poorer prognosis in patients with low GLYAT expression

These findings collectively suggest that GLYAT downregulation may contribute to an immunosuppressive microenvironment conducive to tumor progression, highlighting potential avenues for combined therapeutic approaches targeting both GLYAT and immune checkpoints .

What mechanisms explain GLYAT's influence on HCC cell behavior?

The functional impact of GLYAT on HCC progression operates through several cellular mechanisms:

• Epithelial-mesenchymal transition (EMT): Previous research in breast cancer demonstrated that GLYAT downregulation enhances invasion, migration, and proliferation by modulating EMT, a finding potentially relevant to HCC given EMT's crucial role in intra- and extrahepatic metastasis

• Cell proliferation regulation: In vitro experiments have shown that GLYAT overexpression significantly inhibits the proliferation of hepatocellular cell lines, while knockdown enhances proliferative capacity

• Invasion and migration control: GLYAT overexpression markedly reduces the invasive and migratory abilities of HCC cells, suggesting a role in metastasis suppression

• Clinical correlation: The inhibitory effects of GLYAT on these malignant behaviors align with clinical observations where decreased GLYAT expression associates with higher histological grade and advanced clinical stage in HCC patients

How might GLYAT expression influence response to immunotherapy in HCC patients?

GLYAT expression appears to have significant implications for immunotherapy response prediction:

• Immune checkpoint correlation: GLYAT expression exhibits negative correlations with most immune checkpoint genes (except IDO2), suggesting that patients with low GLYAT may have higher expression of immune checkpoint molecules

• Immunophenoscore analysis: HCC patients with low GLYAT expression demonstrate characteristics that predict better response to immune checkpoint inhibitors (ICIs) targeting PD-1 and CTLA-4

• Therapeutic implications: These findings suggest that inhibition of GLYAT expression might potentially enhance the efficacy of ICIs, offering a promising avenue for combination therapy approaches

• Patient stratification potential: GLYAT expression could potentially serve as a biomarker for identifying HCC patients most likely to benefit from immunotherapy, though this requires validation in prospective clinical trials

What are the optimal experimental conditions for GLYAT antibody applications?

Researchers should consider the following application-specific conditions when using GLYAT antibodies:

• Western blotting: Recommended dilution of 1/1000; researchers should verify the expected molecular weight of approximately 33.9 kDa as calculated for human GLYAT

• Immunohistochemistry (paraffin sections): Optimal dilutions range from 1/10 to 1/50; researchers should establish their own optimal concentration through titration experiments

• Immunofluorescence: Available with specific antibodies such as the D-12 mouse monoclonal antibody recognizing epitope 150-177 of human GLYAT

• Immunoprecipitation: Several antibodies are validated for this application, including the D-12 mouse monoclonal antibody

• ELISA: Multiple antibodies are suitable for ELISA applications, though optimal working concentrations should be determined experimentally

For all applications, proper controls should be included, and storage recommendations (typically aliquoting and storing at -20°C while avoiding repeated freeze/thaw cycles) should be strictly followed to maintain antibody performance .

What approaches should be used for GLYAT gene manipulation in functional studies?

For effective GLYAT gene manipulation in functional studies, researchers have successfully utilized several approaches:

• RNA interference via shRNA: Successful GLYAT knockdown has been achieved using short hairpin RNA targeting specific sequences (e.g., 5′-GGAAACAGCATTTACAGATTC-3′) delivered via lentiviral vectors with GFP reporters

• Lentiviral overexpression: For gain-of-function studies, recombinant lentivirus carrying the human GLYAT overexpression plasmid with GFP markers has been employed

• CRISPR/Cas9 genome editing: GLYAT CRISPR/Cas9 knockout plasmids are available for human applications, providing alternative gene editing approaches

• HDR-based modification: Homology-directed repair plasmids for GLYAT are available for precise gene editing applications

• Double Nickase approach: This alternative CRISPR strategy for GLYAT modification offers reduced off-target effects compared to standard CRISPR/Cas9

Selection methods typically employ puromycin (2 μg/mL) for 48 hours post-transduction to establish stable cell lines. Validation of gene manipulation effectiveness should combine both protein-level (Western blotting) and transcript-level (RT-qPCR) assessments to confirm successful modification .

How should researchers design controls for GLYAT antibody validation?

Rigorous antibody validation requires comprehensive controls:

• Positive tissue controls: Normal liver tissue serves as an excellent positive control for GLYAT antibody validation due to its high endogenous expression

• Negative tissue controls: Tissues known to have minimal GLYAT expression or isotype-matched controls on target tissues

• Specificity validation: Compare staining patterns with multiple antibodies targeting different GLYAT epitopes; the D-12 antibody targets amino acids 150-177, while other antibodies may target different regions

• Peptide competition assays: Pre-incubation of the antibody with the immunizing peptide should abolish specific staining

• Genetic manipulation controls: GLYAT overexpression and knockdown samples provide excellent validation tools; comparing antibody signal between Huh 7-ctrl versus Huh 7-sh cells or HepG2-ctrl versus HepG2-oe cells can confirm specificity

• Cross-reactivity assessment: Particularly important when studying related family members like GLYATL1, researchers should verify that the antibody does not cross-react with GLYATL1, which has been studied using specific antibodies like the B-12 mouse monoclonal that recognizes epitope 265-279 of human GLYATL1

These validation approaches ensure experimental reproducibility and reliable interpretation of results when working with GLYAT antibodies.

What quantification methods are most appropriate for GLYAT expression analysis in clinical samples?

For accurate quantification of GLYAT expression in clinical samples, researchers should consider:

For prognostic applications, Kaplan-Meier analyses with appropriate cutoff values for GLYAT expression levels should be employed, as these have successfully demonstrated the correlation between decreased GLYAT expression and poorer progress in HCC .

How can researchers address the contradictory clinical correlations of GLYAT expression in HCC?

Some findings regarding GLYAT expression in HCC present apparent contradictions that researchers must address:

• Age correlation paradox: Higher GLYAT expression has been observed in patients over 65 years of age despite this demographic generally having poorer prognosis in HCC

• Gender correlation inconsistency: Lower GLYAT expression has been reported in women despite the lower incidence of HCC in females

• Prognostic variability: Individual variability in HCC prognosis necessitates the development of genomic clinicopathological prognostic models

To address these contradictions, researchers should:

• Perform multivariate analyses that account for confounding factors

• Stratify patient cohorts by additional clinical parameters beyond age and gender

• Develop nomograms that integrate GLYAT expression with other independent risk factors (such as T stage) to improve prognostic accuracy

• Conduct larger cohort studies with diverse patient populations to validate the robustness of GLYAT as a biomarker

• Investigate potential biological explanations for these paradoxical findings, such as hormone-dependent regulation of GLYAT expression

These approaches will help clarify whether these contradictions represent true biological phenomena or artifacts of study design.

What experimental approaches can integrate GLYAT research with immunotherapy studies?

To advance understanding of GLYAT's role in immunotherapy response, researchers should consider:

• Co-culture systems: Develop in vitro co-culture models of HCC cells (with varied GLYAT expression) and immune cells to study direct interactions and mechanisms

• Immune checkpoint blockade models: Evaluate the effect of GLYAT manipulation on response to anti-PD-1 or anti-CTLA-4 treatments in preclinical models

• Single-cell RNA sequencing: Apply this technology to characterize cell-specific effects of GLYAT expression on diverse immune cell populations within the tumor microenvironment

• Spatial transcriptomics: Investigate the spatial relationship between GLYAT-expressing cells and immune cell infiltrates in HCC tissue sections

• Patient-derived xenograft (PDX) models: Establish PDX models from patients with varying GLYAT expression levels to test immunotherapy response in vivo

• Clinical sample analysis: Retrospectively analyze GLYAT expression in samples from HCC patients who have received immunotherapy to correlate expression with treatment outcomes

These approaches would help validate the predictive value of GLYAT for immunotherapy response and potentially identify mechanisms by which GLYAT influences the tumor immune microenvironment.

How should researchers interpret GLYAT function in the context of metabolic alterations in HCC?

GLYAT's primary function in glycine metabolism suggests potential metabolic roles in HCC that require specific experimental approaches:

• Metabolomic profiling: Compare metabolite profiles between HCC cells with different GLYAT expression levels to identify altered metabolic pathways

• Isotope tracing experiments: Use labeled glycine to track changes in metabolic flux dependent on GLYAT expression

• Integration with genomic data: Correlate GLYAT expression with expression of other metabolic enzymes to identify potential compensatory mechanisms

• Functional metabolic assays: Measure parameters such as oxygen consumption rate, extracellular acidification rate, and ATP production in cells with modified GLYAT expression

• In vivo metabolic imaging: Apply techniques such as hyperpolarized MRI to assess metabolic alterations in animal models with varied GLYAT expression

Understanding GLYAT's metabolic functions may provide additional insights into its role in HCC progression and potentially identify metabolic vulnerabilities that could be therapeutically targeted. The integration of metabolomics with functional studies of GLYAT represents an important frontier in understanding its comprehensive role in liver cancer biology.