ERVFRD-1 Antibody, FITC conjugated

What is ERVFRD-1 and how is it involved in normal human biology?

ERVFRD-1 is an endogenous retroviral envelope glycoprotein with a canonical length of 538 amino acid residues and a mass of 59.5 kDa. It belongs to the Gamma type-C retroviral envelope protein family and is primarily localized in the cell membrane . The protein plays a major role in placental development and trophoblast fusion .

ERVFRD-1 has the characteristics of a typical retroviral envelope protein, featuring a cleavage site that separates the surface (SU) and transmembrane (TM) proteins, which form a heterodimer . It is expressed at notably high levels in the placenta, suggesting functional importance in human reproduction . The gene is part of a human endogenous retrovirus provirus on chromosome 6 that has inactivating mutations in the gag and pol genes, while the envelope glycoprotein gene appears to have been selectively preserved through evolution .

What detection methods are most effective when using FITC-conjugated ERVFRD-1 antibodies?

For FITC-conjugated ERVFRD-1 antibodies, the following detection methods are recommended:

When using these methods, researchers should optimize protocols by titrating antibody concentrations, as ERVFRD-1 expression varies significantly between tissue types, with particularly high expression in placental tissues . Flow cytometry can effectively quantify cell surface expression, while immunofluorescence and confocal microscopy are ideal for examining subcellular localization patterns, particularly in studying membrane fusion events in trophoblast research.

What controls should be included when using FITC-conjugated ERVFRD-1 antibodies?

Including appropriate controls is critical for reliable interpretation of results with FITC-conjugated ERVFRD-1 antibodies:

• Isotype Control: Use a FITC-conjugated antibody of the same isotype but with irrelevant specificity to assess non-specific binding.

• Negative Tissue Control: Include tissues known to express minimal ERVFRD-1 (non-placental tissues) to establish background signal levels .

• Positive Tissue Control: Placental tissue samples should be included as positive controls due to known high expression of ERVFRD-1 .

• Absorption Controls: Pre-incubate the antibody with purified ERVFRD-1 protein before application to verify specificity.

• Secondary-only Control: For indirect detection methods, include samples treated only with secondary reagents to assess non-specific binding.

These controls help distinguish true signal from autofluorescence or non-specific binding, particularly important in tissues with high autofluorescence like kidney tissue when studying KIRC .

How can ERVFRD-1 expression patterns in normal versus cancerous tissues be reliably quantified?

Quantification of ERVFRD-1 expression differences between normal and cancerous tissues requires rigorous methodological approaches:

• Digital Image Analysis: For immunofluorescence studies, use software like ImageJ with consistent thresholding parameters across all samples.

• Mean Fluorescence Intensity (MFI) Measurement: For flow cytometry, compare MFI values between normal and cancer samples with proper normalization to account for background fluorescence.

• Reference Gene Normalization: When quantifying at the transcript level alongside protein detection, normalize to multiple reference genes for accurate comparison.

• ROC Curve Analysis: Generate receiver operating characteristic curves to determine optimal cut-off values for distinguishing normal from cancerous tissues. In KIRC studies, ERVFRD-1 expression demonstrated significant discriminatory power with an area under the curve (AUC) of 0.952 (95% CI=0.932-0.972) .

Research has shown consistently lower ERVFRD-1 expression in KIRC compared to normal kidney tissues (p < 0.001) across multiple cohorts, making proper quantification essential for biomarker development .

What are the optimal fixation and permeabilization protocols for ERVFRD-1 immunofluorescence studies?

For optimal detection of ERVFRD-1 using FITC-conjugated antibodies, fixation and permeabilization protocols should be carefully selected:

For permeabilization:

• 0.1-0.5% Triton X-100 (5-10 minutes) for intracellular epitopes

• 0.1% Saponin for gentler permeabilization with less disruption of membrane structures

Since ERVFRD-1 is a membrane-localized protein, avoid excessive permeabilization which might disrupt membrane integrity and alter staining patterns . For placental tissues, which express high levels of ERVFRD-1, shorter fixation times may be sufficient, while tissues with lower expression (such as KIRC samples) may require optimized antigen retrieval methods .

How can FITC-conjugated ERVFRD-1 antibodies be used to investigate the relationship between ERVFRD-1 expression and immune cell infiltration in tumors?

ERVFRD-1 has shown significant involvement in tumor immunoregulation, particularly in KIRC. To investigate these relationships:

• Multiplex Immunofluorescence: Combine FITC-conjugated ERVFRD-1 antibodies with antibodies against immune cell markers (using different fluorophores) to assess co-localization. Research has shown close relationships between ERVFRD-1 expression and infiltration levels of mast cells and Treg cells (P < 0.001) .

• Single-cell Analysis Workflow:

  • Disaggregate tumor tissue into single-cell suspensions

  • Stain with FITC-conjugated ERVFRD-1 antibody alongside immune cell markers

  • Perform flow cytometry or mass cytometry analysis

  • Use dimensionality reduction techniques (tSNE, UMAP) to visualize relationships

• Spatial Analysis: Employ techniques like multiplexed immunofluorescence or imaging mass cytometry to maintain spatial context. This approach has revealed that ERVFRD-1 expression patterns correlate with distinct immune microenvironments in KIRC .

Analysis using ssGSEA (single-sample Gene Set Enrichment Analysis) techniques has revealed correlations between ERVFRD-1 expression and immune cell infiltration scores, suggesting functional relationships in the tumor microenvironment that can be further investigated at the protein level using FITC-conjugated antibodies .

What approaches can resolve contradictory data regarding ERVFRD-1 expression in different cancer types?

Researchers investigating ERVFRD-1 across cancer types may encounter contradictory findings. To resolve these discrepancies:

• Tissue-Specific Context Analysis: ERVFRD-1 shows different expression patterns across cancer types. For example, pan-cancer analysis revealed generally low expression in multiple cancers including BLCA, BRCA, CESC, and KIRC, yet its prognostic significance varies . Use FITC-conjugated antibodies with identical protocols across multiple cancer types for direct comparison.

• Isoform-Specific Detection: Design experiments to distinguish between potential ERVFRD-1 isoforms:

  • Use antibodies targeting different epitopes

  • Combine with RT-PCR to identify transcript variants

  • Compare results with computational predictions of isoform expression

• Methylation-Expression Correlation: Analyze methylation patterns alongside protein expression using:

  • Bisulfite sequencing of the ERVFRD-1 promoter region

  • Correlation analysis between methylation levels and FITC signal intensity

  • MethSurv database analysis to evaluate DNA methylation status

• Multi-omics Integration Framework:

This integrated approach has helped clarify that in KIRC, lower ERVFRD-1 expression correlates with poorer outcomes, despite its role in other cancers potentially being different .

How can FITC-conjugated ERVFRD-1 antibodies be optimized for studying the role of ERVFRD-1 in cell fusion mechanisms?

ERVFRD-1 (syncytin-2) plays a crucial role in trophoblast fusion. To study these mechanisms:

• Live Cell Imaging Protocol:

  • Use cell-permeable nuclear dyes in combination with FITC-conjugated ERVFRD-1 antibody fragments

  • Employ spinning disk confocal microscopy with environmental control

  • Capture time-lapse images at 5-minute intervals for 24-48 hours

  • Analyze membrane dynamics during fusion events

• Fusion Assay Quantification:

  • Seed differentially labeled cells (one population with FITC-ERVFRD-1 antibody)

  • Measure fusion index: (number of nuclei in syncytia/total number of nuclei) × 100

  • Track ERVFRD-1 localization before, during, and after fusion events

• Mutation-Function Analysis:

  • Generate cells expressing wild-type or mutant ERVFRD-1

  • Label with FITC-conjugated antibodies targeting preserved epitopes

  • Quantify fusion efficiency relative to ERVFRD-1 surface expression levels

Research has demonstrated that ERVFRD-1 exhibits fusogenic properties, with in vitro experiments showing that cells transfected with syncytin-2 displayed altered tumorigenic potential when engrafted into mice, suggesting complex roles beyond simple membrane fusion .

What methodological approaches can determine if ERVFRD-1 is a suitable target for immunotherapy in KIRC?

To evaluate ERVFRD-1 as an immunotherapy target in KIRC:

• Epitope Accessibility Assessment:

  • Use FITC-conjugated ERVFRD-1 antibodies of different epitope specificities

  • Quantify binding to live, non-permeabilized cells from patient-derived xenografts

  • Determine which epitopes are accessible in the native tumor environment

• Immune Response Characterization:

  • Co-culture KIRC cells with immune effector cells

  • Add FITC-conjugated ERVFRD-1 antibodies to monitor target engagement

  • Assess cytokine production and cytotoxicity

• Predictive Biomarker Analysis:

  • Correlate ERVFRD-1 expression (measured by FITC signal intensity) with:

    • Tumor Mutation Burden (TMB)

    • PD-L1 expression

    • Immune cell infiltration scores

    • Response to immune checkpoint inhibitors (retrospective analysis)

• In vivo Targeting Validation:

  • Develop ERVFRD-1-targeted constructs (CAR-T, BiTEs, ADCs)

  • Use FITC-conjugated antibodies to confirm target engagement

  • Monitor efficacy in preclinical models

Research suggests ERVFRD-1 involvement in tumor immunoregulation, showing close relationships with immune cell infiltration, particularly mast cells and Treg cells . The TIDE algorithm can be employed to predict potential immune checkpoint blockade responses based on ERVFRD-1 expression patterns .

What are the most effective protocols for studying ERVFRD-1 methylation status in correlation with protein expression?

To correlate ERVFRD-1 methylation with protein expression:

• Integrated Methylation-Expression Analysis Pipeline:

  • Bisulfite sequencing of ERVFRD-1 promoter and gene body

  • Immunofluorescence with FITC-conjugated ERVFRD-1 antibodies on serial sections

  • Correlation analysis between methylation beta values and fluorescence intensity

• Cell Line Demethylation Experiments:

  • Treat KIRC cell lines with demethylating agents (5-aza-2'-deoxycytidine)

  • Monitor changes in ERVFRD-1 expression using FITC-conjugated antibodies

  • Quantify expression changes via flow cytometry

• CpG Site-Specific Analysis:

• Single-Cell Correlation Analysis:

  • Perform single-cell bisulfite sequencing

  • Match with single-cell protein quantification using FITC-conjugated antibodies

  • Develop computational methods to integrate these data types

The MethSurv database can be used to evaluate DNA methylation status of ERVFRD-1 and its prognostic value, as demonstrated in KIRC research . This approach can uncover the underlying epigenetic mechanisms controlling ERVFRD-1 expression and potentially explain the observed lower expression in KIRC tumors compared to normal kidney tissues.

How can FITC-conjugated ERVFRD-1 antibodies be integrated into multiplexed imaging systems for spatial biomarker analysis?

For advanced spatial profiling of ERVFRD-1 in the tumor microenvironment:

• Cyclic Immunofluorescence (CycIF) Protocol:

  • Apply FITC-conjugated ERVFRD-1 antibody in the first cycle

  • Image and record coordinates

  • Chemically inactivate fluorescence

  • Repeat with antibodies against immune markers, basement membrane components, etc.

  • Computational alignment and analysis of 30+ markers on the same tissue section

• CODEX System Integration:

  • Conjugate ERVFRD-1 antibodies with DNA barcodes

  • Perform multiplexed detection with other markers

  • Use computational analysis to identify cellular neighborhoods and spatial relationships

• Spatial Transcriptomics Correlation:

  • Perform immunofluorescence with FITC-conjugated ERVFRD-1 antibodies

  • Execute spatial transcriptomics on adjacent sections

  • Register images and correlate protein expression with gene expression domains

These approaches enable researchers to examine ERVFRD-1's relationship with the tumor microenvironment, particularly relevant given findings showing ERVFRD-1's involvement in tumor immunoregulation and its correlation with infiltration levels of specific immune cell populations in KIRC .

What experimental design is optimal for investigating ERVFRD-1's role in prognostic assessment models for KIRC?

To develop and validate ERVFRD-1 as a prognostic marker:

• Cohort Design Requirements:

  • Training cohort: minimum 200 KIRC cases with complete follow-up

  • Validation cohort: independent set of 100+ cases

  • Controls: matched normal kidney tissue

  • Stratification by clinical parameters (T stage, M stage, etc.)

• Multivariate Biomarker Panel Development:

  • Quantify ERVFRD-1 expression using FITC-conjugated antibodies via tissue microarray analysis

  • Combine with established markers (pathologic T, age) based on Cox regression analysis

  • Construct and validate nomogram as demonstrated in previous research

• Survival Analysis Framework:

• Validation Methods:

  • Internal: bootstrap resampling

  • External: independent cohorts

  • Calibration plots

  • Time-dependent ROC curves

  • Concordance index (C-index)

What are the optimal approaches for addressing cross-reactivity concerns with FITC-conjugated ERVFRD-1 antibodies?

Ensuring antibody specificity is crucial for reliable research outcomes:

• Cross-Reactivity Assessment Protocol:

  • Test on cells with CRISPR-mediated ERVFRD-1 knockout

  • Evaluate binding to tissues from other species with known ERVFRD-1 homologs

  • Screen against related human endogenous retroviral proteins

• Absorption Controls Implementation:

  • Pre-absorb antibody with recombinant ERVFRD-1 protein

  • Include graduated concentrations of competing antigens

  • Quantify reduction in signal intensity

• Epitope Mapping:

  • Use overlapping peptide arrays to precisely identify binding epitopes

  • Select antibodies targeting unique regions not shared with other ERV proteins

  • Verify epitope conservation across experimental models

• Western Blot Validation Standards:

  • Confirm single band at expected molecular weight (59.5 kDa)

  • Account for post-translational modifications (glycosylation, cleavage)

  • Include positive control (placental lysate) and negative control tissues

ERVFRD-1 belongs to the Gamma type-C retroviral envelope protein family and shares sequence similarities with other ERV proteins, making specificity validation particularly important . Additionally, post-translational modifications including protein cleavage and glycosylation can affect antibody binding and should be considered when validating specificity .

How can FITC-conjugated ERVFRD-1 antibodies contribute to understanding the evolutionary conservation of ERVFRD-1 function?

To investigate evolutionary aspects of ERVFRD-1:

• Cross-Species Comparison Methodology:

  • Test FITC-conjugated human ERVFRD-1 antibodies on tissues from evolutionary related species

  • Map epitope conservation using sequence alignment tools

  • Correlate binding affinity with functional conservation

• Phylogenetic Analysis Protocol:

  • Identify ERVFRD-1 orthologs in mouse and chimpanzee

  • Compare tissue expression patterns using species-appropriate antibodies

  • Analyze cellular localization patterns across species

• Functional Conservation Assessment:

  • Compare fusion activity in trophoblast models from different species

  • Correlate expression patterns with placentation strategies

  • Examine immune regulatory functions across species

This research direction is particularly relevant as ERVFRD-1 gene orthologs have been reported in mouse and chimpanzee species , suggesting evolutionary conservation of function that may provide insights into both normal physiology and pathological roles in cancer.

What protocols can best investigate the relationship between ERVFRD-1 and tumor mutation burden in immunotherapy response prediction?

To explore ERVFRD-1's potential role in predicting immunotherapy responses:

• Integrated Biomarker Analysis Workflow:

  • Quantify ERVFRD-1 expression using FITC-conjugated antibodies via flow cytometry or immunofluorescence

  • Determine tumor mutation burden (TMB) through next-generation sequencing

  • Calculate correlation coefficients between ERVFRD-1 expression and TMB

  • Apply the TIDE algorithm to predict immune checkpoint blockade responses

• Patient Stratification Approach:

  • Divide patients into quadrants based on ERVFRD-1 expression and TMB

  • Track clinical outcomes and treatment responses

  • Identify optimal cut-off values for both markers

• Multiparametric Flow Cytometry Protocol:

  • Panel design: FITC-ERVFRD-1, immune checkpoint markers, T-cell activation markers

  • Gating strategy focused on tumor and immune cell populations

  • Correlation analysis with genomic markers and clinical outcomes

Research has shown that using the ggstatsplot R package can analyze the correlation between TMB enrichment scores and ERVFRD-1 expression, while the TIDE algorithm can predict potential immunotherapy responses based on ERVFRD-1 expression patterns . These computational approaches can be validated and extended using protein-level analyses with FITC-conjugated antibodies.

What methodological approaches best examine the impact of ERVFRD-1 on cellular signaling pathways in KIRC progression?

To investigate ERVFRD-1's role in signaling pathways:

• Phospho-Proteomics Integration:

  • Sort cells based on ERVFRD-1 expression using FITC-conjugated antibodies

  • Perform phospho-proteomic analysis on sorted populations

  • Map activated signaling pathways using pathway enrichment tools

• Live Cell Signaling Analysis:

  • Use FITC-conjugated ERVFRD-1 antibodies alongside calcium indicators or FRET-based reporters

  • Monitor real-time signaling changes in relation to ERVFRD-1 expression

  • Quantify signaling dynamics in single cells

• Pathway Inhibition Matrix:

• GO, KEGG, and GSEA Analysis Framework:

  • Perform differential gene expression analysis between high and low ERVFRD-1 expressing cells

  • Conduct GO term enrichment to identify biological processes

  • Apply KEGG pathway analysis to map molecular interactions

  • Execute GSEA to identify enriched gene sets

Previous research using GO, KEGG, and GSEA analyses revealed significant involvement of ERVFRD-1 in tumor immunoregulation in KIRC . These computational findings can be validated at the protein level using FITC-conjugated antibodies in combination with signaling pathway analysis.

What are the most effective troubleshooting strategies for weak or non-specific FITC-ERVFRD-1 antibody signals?

When encountering signal issues with FITC-conjugated ERVFRD-1 antibodies:

• Signal Optimization Protocol:

  • Titrate antibody concentration (1:50, 1:100, 1:200, 1:500)

  • Extend incubation time (1 hour, 2 hours, overnight at 4°C)

  • Test different fixation methods (paraformaldehyde, methanol, acetone)

  • Implement antigen retrieval (citrate buffer pH 6.0, EDTA buffer pH 9.0)

• Autofluorescence Reduction Techniques:

  • Treat sections with 0.1% Sudan Black B in 70% ethanol (20 minutes)

  • Use commercially available autofluorescence quenchers

  • Employ spectral unmixing during imaging

• Antibody Quality Control Checklist:

  • Verify antibody storage conditions (4°C, protected from light)

  • Check for FITC degradation (exposure to light, improper pH)

  • Confirm antibody lot consistency with validation data

  • Use fresh reagents for each experiment

• Tissue-Specific Optimization:

  • For KIRC samples: Implement extended antigen retrieval

  • For placental tissue: Reduce antibody concentration due to high expression

  • For cultured cells: Optimize fixation to preserve membrane localization

Since ERVFRD-1 has generally low expression in KIRC tumors compared to normal tissue , signal optimization is particularly important when studying this protein in cancer contexts.

How can researchers design robust validation experiments to confirm ERVFRD-1 antibody specificity?

To ensure antibody specificity:

• Comprehensive Validation Framework:

  • Positive control: placental tissue (known high expression)

  • Negative control: tissues with minimal ERVFRD-1 expression

  • Genetic controls: CRISPR knockout/knockdown validation

  • Competitive binding assays: pre-absorption with recombinant protein

• Multi-platform Confirmation Approach:

  • Compare FITC-antibody results with RNA-seq data

  • Validate with alternative antibody clones targeting different epitopes

  • Confirm with orthogonal techniques (Western blot, ELISA)

• Cross-reactivity Assessment Matrix:

• Western Blot Confirmation Standards:

  • Expected molecular weight: 59.5 kDa for canonical ERVFRD-1

  • Account for post-translational modifications

  • Include positive control (placental lysate)

Proper validation is essential since ERVFRD-1 belongs to a family of related endogenous retroviral proteins with potential for cross-reactivity .

What emerging technologies could enhance ERVFRD-1 detection and functional analysis in cancer research?

Emerging approaches for ERVFRD-1 research include:

• Advanced Imaging Methodologies:

  • Super-resolution microscopy: Resolve ERVFRD-1 localization at nanometer scale

  • Light-sheet microscopy: 3D imaging of ERVFRD-1 in tumor spheroids

  • Expansion microscopy: Physical tissue expansion for improved resolution

  • Live-cell lattice light-sheet: Dynamic visualization of ERVFRD-1 trafficking

• Single-Cell Multi-omics Integration:

  • CITE-seq combining ERVFRD-1 antibody detection with transcriptomics

  • Single-cell Western blot for protein validation

  • Spatial proteomics to map ERVFRD-1 interactions

• CRISPR-Based Functional Screens:

  • CRISPRa/CRISPRi libraries targeting ERVFRD-1 regulatory elements

  • CRISPR base editing to study specific mutations

  • Prime editing for precise genomic modifications

• In Situ Sequencing Applications:

  • Visualize ERVFRD-1 mRNA alongside protein using padlock probes

  • Multiplex RNA and protein detection in tissue sections

  • Spatial transcriptomics correlation with protein expression

These technologies could help clarify ERVFRD-1's role in regulating immunological activity within the tumor microenvironment and its potential as a biomarker for diagnosis, immunotherapy, and prognosis assessment of KIRC .

How might research into ERVFRD-1's involvement in KIRC inform potential therapeutic interventions?

Based on current knowledge, potential therapeutic applications include:

• Immunotherapy Target Development:

  • Design chimeric antigen receptor T cells (CAR-T) targeting ERVFRD-1

  • Develop bispecific T-cell engagers (BiTEs) linking T cells to ERVFRD-1+ cells

  • Create antibody-drug conjugates for targeted delivery

  • Evaluate immune checkpoint inhibitor combinations

• Epigenetic Modulation Approach:

  • Target methylation status of ERVFRD-1 regulatory regions

  • Develop small molecules to modulate ERVFRD-1 expression

  • Test combination with existing epigenetic drugs

• Precision Medicine Framework:

  • Stratify patients based on ERVFRD-1 expression

  • Design clinical trials with ERVFRD-1 as a biomarker

  • Develop companion diagnostics using FITC-conjugated antibodies

  • Integrate into existing nomogram models with pathologic T and age

• Functional Screening Pathway:

  • High-throughput drug screening in models with varied ERVFRD-1 expression

  • Synthetic lethality approaches with ERVFRD-1 expression status

  • Identification of downstream vulnerabilities in ERVFRD-1-regulated pathways