EPS8L3 Antibody, FITC conjugated

What is EPS8L3 and why is it significant in cancer research?

EPS8L3 is a protein belonging to the epidermal growth factor receptor (EGFR) kinase substrate 8 family. It has garnered significant research interest due to its overexpression in hepatocellular carcinoma (HCC) tissues compared to adjacent non-tumorous tissues . Research has demonstrated that EPS8L3 promotes cancer cell proliferation by downregulating p21/p27 expression and enhances migratory and invasive capabilities by upregulating matrix metalloproteinase-2 expression . Its association with poor clinical prognosis in liver cancer patients makes it a potentially valuable biomarker and therapeutic target . Unlike other EPS8 family members, EPS8L3 shows specifically elevated expression in liver tumors, with similar upregulation observed in cholangiocarcinoma, colon adenocarcinoma, esophageal carcinoma, pancreatic adenocarcinoma, and rectum adenocarcinoma .

What applications are FITC-conjugated EPS8L3 antibodies most suitable for?

FITC-conjugated EPS8L3 antibodies are particularly valuable for fluorescence-based applications including:

• Immunofluorescence microscopy (IF/ICC) - For visualizing EPS8L3 localization in fixed cells and tissues with green fluorescence detection. Standard IF/ICC protocols employ 1:100-1:500 dilutions for optimal results .

• Flow cytometry - For quantitative analysis of EPS8L3 expression levels in cell populations.

• High-content screening - For automated image analysis in drug discovery or genetic screens targeting EPS8L3 pathways.

• FLISA (Fluorescence-Linked Immunosorbent Assay) - As an alternative to traditional ELISA with enhanced sensitivity.

These antibodies complement non-conjugated versions that are typically used for Western blotting (recommended at 1:1000 dilution) and standard immunohistochemistry (1:50-1:200 dilution) .

How do I validate the specificity of an EPS8L3 antibody for my research?

Validating antibody specificity is crucial for experimental reliability. For EPS8L3 antibodies, implement the following validation approach:

• Positive and negative control tissues: Use liver cancer tissues (high expression) versus normal liver tissues (low expression) as demonstrated in multiple studies .

• Western blot verification: Confirm detection of the expected 67 kDa band corresponding to EPS8L3 .

• siRNA knockdown validation: Use EPS8L3-targeted siRNAs to create knockdown cell lines and verify reduced antibody signal intensity. Previous studies have established effective siRNA sequences for this purpose .

• Cross-reactivity assessment: Test the antibody against other EPS8 family members, particularly EPS8, which is an important paralog of EPS8L3 .

• Standard validation metrics: Check if the antibody has received "Enhanced" or "Supported" validation status through protein array analysis, recombinant expression validation, or mass spectrometry validation .

How can I distinguish between the roles of EPS8L3 and other EPS8 family members in my experimental system?

Distinguishing the specific functions of EPS8L3 from other EPS8 family members requires a systematic approach:

• Selective gene modulation: Establish separate knockdown and overexpression models for EPS8L3 and other family members (particularly EPS8) using validated siRNAs or lentiviral constructs. Previous research has confirmed that knockdown of EPS8L3 doesn't significantly affect the expression of other family members .

• Comparative expression analysis: Implement qRT-PCR to quantify relative expression levels of all EPS8 family members across your experimental conditions. TCGA data analysis has shown no significant correlations between EPS8L3 mRNA expression and other family members in HCC .

• Protein interaction studies: Use co-immunoprecipitation to identify differential protein interaction partners. Unlike EPS8, EPS8L3's effects on EGFR-ERK pathway activation may not depend on the formation of an EPS8L3-SOS1-ABI1 complex .

• Functional rescue experiments: Perform rescue experiments where one family member is knocked down and another is overexpressed to determine functional redundancy or specialization.

• Domain-specific analysis: Create chimeric constructs swapping functional domains between EPS8L3 and other family members to identify critical regions for specific functions.

What are the optimal fixation and permeabilization conditions for EPS8L3 immunofluorescence with FITC-conjugated antibodies?

Optimal visualization of EPS8L3 using FITC-conjugated antibodies requires careful attention to fixation and permeabilization protocols:

• Fixation options:

  • Paraformaldehyde (4%, 10-15 minutes at room temperature) provides good structural preservation while maintaining EPS8L3 antigenicity

  • Methanol fixation (100%, 10 minutes at -20°C) may enhance detection of certain EPS8L3 epitopes but can disrupt membrane structures

  • Combination fixation (2% PFA followed by methanol) can be tested for challenging samples

• Permeabilization conditions:

  • For PFA-fixed samples: 0.1-0.3% Triton X-100 for 5-10 minutes

  • For methanol-fixed samples: Additional permeabilization is typically unnecessary

  • For difficult-to-permeabilize samples: Consider saponin (0.1-0.5%) which is reversible and may better preserve certain epitopes

• Antigen retrieval considerations:

  • For formalin-fixed paraffin-embedded tissues: Heat-induced epitope retrieval in citrate buffer (pH 6.0) is often necessary

  • For frozen sections: Antigen retrieval is typically not required but can be tested if signal is weak

• Blocking optimization:

  • 5% normal serum (species matching secondary antibody) with 1% BSA in PBS for 30-60 minutes

  • Include 0.1% Tween-20 to reduce non-specific membrane binding of FITC-conjugated antibodies

The optimal protocol should be empirically determined for each cell type or tissue of interest, as EPS8L3 localization patterns may vary between different cancer types.

How can I resolve signal discrepancies between EPS8L3 antibody immunofluorescence data and RNA expression levels?

Signal discrepancies between protein detection and RNA expression are common challenges in EPS8L3 research. To systematically address this:

• Technical validation:

  • Verify antibody specificity using multiple detection methods (WB, IHC, IF)

  • Test multiple antibodies targeting different EPS8L3 epitopes

  • Implement enhanced validation techniques as described in the Human Protein Atlas protocols

• Biological explanations:

  • Post-transcriptional regulation: EPS8L3 may be subject to miRNA regulation or RNA stability mechanisms

  • Post-translational modifications: Investigate potential phosphorylation, ubiquitination, or other modifications affecting antibody recognition

  • Protein half-life: Determine EPS8L3 protein turnover rate using cycloheximide chase assays

  • Subcellular localization changes: RNA levels may remain constant while protein localization shifts affect detection

• Quantitative assessment approach:

  • Implement parallel qRT-PCR and quantitative immunofluorescence in the same samples

  • Analyze correlation between transcript levels and protein signal intensities across multiple samples

  • Consider single-cell approaches to identify potential cell population heterogeneity

• Data integration strategy:

  • Apply consistency evaluation metrics similar to those used by the Human Protein Atlas, categorizing results into high, medium, low, or very low consistency

  • Implement multivariate analysis to identify factors contributing to discrepancies

What is the optimal protocol for multiplexing FITC-conjugated EPS8L3 antibodies with other fluorophore-conjugated antibodies?

When multiplexing FITC-conjugated EPS8L3 antibodies with other fluorophore-labeled antibodies, follow these methodological guidelines:

• Fluorophore selection strategy:

  • Choose spectrally distinct fluorophores to avoid bleed-through (FITC: Ex/Em ~495/519 nm)

  • Recommended combinations: FITC (green) + Cy3/TRITC (red) + Cy5 (far-red) + DAPI (blue, nuclear)

  • Avoid fluorophores with overlapping emission spectra with FITC (e.g., BODIPY, Alexa Fluor 488)

• Sequential staining protocol:

  • For multiple primary antibodies from the same host species: Implement sequential staining with complete blocking between rounds

  • Apply the FITC-conjugated EPS8L3 antibody last in the sequence to minimize photobleaching during lengthy protocols

  • Consider using Fab fragment blocking between steps if using multiple rabbit antibodies

• Controls and validation:

  • Single-stain controls: Essential for setting appropriate imaging parameters

  • Fluorescence minus one (FMO) controls: For accurate gating in flow cytometry applications

  • Absorption/emission spectral scans: Verify the absence of unexpected spectral overlap

  • Colocalization analysis: Apply appropriate statistical measures (Pearson's, Mander's coefficients)

• Imaging considerations:

  • Image acquisition: Capture each channel separately to minimize crosstalk

  • Linear range verification: Ensure signal is within the linear detection range for each channel

  • Photobleaching mitigation: Minimize exposure times, use anti-fade mounting media, image FITC channel first

How should I optimize EPS8L3 antibody concentration for detecting different expression levels in various cancer cell lines?

Optimizing EPS8L3 antibody concentration requires a systematic titration approach adapted to expression levels across different cancer cell lines:

• Initial range-finding titration:

  • Starting with manufacturer-recommended dilutions (typically 1:100-1:500 for IF/ICC)

  • Test a logarithmic series of dilutions (e.g., 1:50, 1:100, 1:200, 1:400, 1:800)

  • Include high-expressing (HCC cells) and low-expressing (normal hepatocytes) controls

• Signal-to-noise ratio optimization:

  • Calculate signal-to-background ratios for each concentration

  • Implement automated image analysis to quantify specific signal intensity versus background

  • Select the concentration that maximizes specific signal while minimizing background

  • For weakly expressing samples, longer incubation times (overnight at 4°C) may be preferable to higher antibody concentrations

• Cell-line specific considerations:

  • Hepatocellular carcinoma lines (HCCLM3, Huh7, HepG2, SNU449): Higher EPS8L3 expression demonstrated in previous studies

  • Normal hepatic cell lines: Expected to show minimal expression

  • Other cancer types with known EPS8L3 overexpression: Cholangiocarcinoma, colon adenocarcinoma, esophageal carcinoma, pancreatic adenocarcinoma

• Validation across detection methods:

  • Cross-validate optimal concentrations between IF/ICC, flow cytometry, and other applications

  • Correlate staining intensity with quantitative Western blot results

What are the best approaches for quantitative analysis of EPS8L3 expression using fluorescence microscopy?

Rigorous quantitative analysis of EPS8L3 expression via fluorescence microscopy requires:

• Standardized image acquisition protocol:

  • Fixed exposure settings across all samples

  • Consistent microscope parameters (objective, numerical aperture, binning)

  • Reference standards included in each imaging session

  • Z-stack acquisition to capture total cellular expression

• Image processing workflow:

  • Background subtraction using appropriate controls

  • Flat-field correction to account for illumination non-uniformities

  • Cell segmentation based on nuclear and/or membrane markers

  • Subcellular compartment segmentation (cytoplasmic, membrane, nuclear regions)

• Quantification parameters:

  • Mean fluorescence intensity (MFI) per cell

  • Integrated density (area × mean intensity)

  • Nuclear/cytoplasmic intensity ratio

  • Subcellular distribution patterns

  • Colocalization metrics with relevant markers (e.g., EGFR)

• Statistical analysis approach:

  • Population-level analysis (distribution of single-cell measurements)

  • Hierarchical analysis (cells → fields → samples → experimental groups)

  • Appropriate statistical tests based on data distribution

  • Correlation with functional parameters or clinical outcomes

How can FITC-conjugated EPS8L3 antibodies be utilized in studying the EGFR-ERK pathway activation in cancer models?

FITC-conjugated EPS8L3 antibodies provide valuable tools for investigating EPS8L3's role in EGFR-ERK pathway activation:

• Dynamic interaction studies:

  • Live-cell imaging to track EPS8L3 interactions with EGFR following EGF stimulation

  • FRET (Fluorescence Resonance Energy Transfer) analysis using FITC-EPS8L3 antibodies paired with acceptor fluorophore-labeled EGFR antibodies

  • Photobleaching approaches to assess mobility and binding kinetics

• Pathway activation visualization:

  • Dual immunofluorescence to correlate EPS8L3 localization with phosphorylated ERK

  • Triple staining to simultaneously detect EPS8L3, EGFR, and downstream effectors

  • Time-course experiments following EGF stimulation to map the temporal relationship between EPS8L3 redistribution and ERK activation

• Mechanistic investigations:

  • Colocalization analysis of EPS8L3 with markers of EGFR internalization

  • Quantification of EGFR dimerization in the presence/absence of EPS8L3

  • Combined use with inhibitors of specific pathway components

• Correlation with functional outcomes:

  • Integration with proliferation assays (Ki-67, EdU incorporation)

  • Parallel analysis of EPS8L3 expression and invasive capacity (matrix degradation assays)

  • Correlation of EPS8L3 subcellular distribution with p21/p27 downregulation

Research has shown that EPS8L3 affects EGFR-ERK pathway activation specifically by modulating EGFR dimerization and internalization, potentially through mechanisms independent of the EPS8L3-SOS1-ABI1 complex formation typically associated with EPS8 .

What role does EPS8L3 play in modulating the tumor microenvironment, and how can this be studied using fluorescence techniques?

Emerging evidence suggests EPS8L3 may influence the tumor microenvironment (TME), which can be investigated using FITC-conjugated antibodies:

• Multicellular 3D model approaches:

  • Organoid cultures with fluorescently labeled cell populations

  • Tumor spheroid invasion assays with simultaneous EPS8L3 detection

  • Patient-derived xenografts with multiplex immunofluorescence imaging

• Cellular interaction studies:

  • Co-culture systems combining EPS8L3-expressing tumor cells with stromal components

  • Time-lapse imaging to track dynamic interactions between cell types

  • Extracellular vesicle labeling to study EPS8L3-mediated communication

• Matrix remodeling assessment:

  • Correlation of EPS8L3 expression with matrix metalloproteinase-2 activity using fluorogenic substrates

  • Simultaneous visualization of EPS8L3 and ECM components (collagen, fibronectin)

  • Mechanical property mapping through traction force microscopy

• Immune cell interaction analysis:

  • Multiplex immunofluorescence to assess spatial relationships between EPS8L3+ tumor cells and immune populations

  • Function-blocking experiments to determine if EPS8L3 modulates immune cell recruitment or activity

  • Correlation of EPS8L3 expression patterns with immune infiltration signatures

Given EPS8L3's established role in promoting invasive capabilities through upregulation of matrix metalloproteinase-2 , these approaches could reveal additional mechanisms by which EPS8L3 contributes to tumor progression through TME modulation.

What are the future directions for EPS8L3 research in cancer biology?

The current body of knowledge about EPS8L3 points to several promising research directions:

• Therapeutic targeting strategies:

  • Development of specific EPS8L3 inhibitors, similar to approaches using EPS8-NLS peptides in other cancer models

  • Evaluation of EPS8L3 as a biomarker for response to EGFR-targeted therapies

  • Investigation of synthetic lethality approaches in EPS8L3-overexpressing tumors

• Mechanistic investigations:

  • Further elucidation of the precise structural requirements for EPS8L3's effect on EGFR dimerization and internalization

  • Comparative analysis of EPS8L3 versus EPS8 signaling mechanisms across cancer types

  • Identification of the complete EPS8L3 interactome in different cellular contexts

• Translational applications:

  • Development of EPS8L3 as a prognostic or predictive biomarker in multiple cancer types

  • Evaluation of circulating EPS8L3 as a liquid biopsy marker

  • Analysis of EPS8L3 expression in therapy-resistant tumor populations

• Technical advances:

  • Development of higher-specificity antibodies and nanobodies targeting distinct EPS8L3 epitopes

  • Application of super-resolution microscopy techniques to better characterize EPS8L3's subcellular localization

  • Integration of spatial transcriptomics with protein-level detection to resolve expression discrepancies