FREM1 Antibody is typically a polyclonal antibody produced in rabbits, rabbits, or other hosts, with reactivity against human, mouse, and rat proteins. Key features include:
Isoform Detection:
FREM1 Antibody detects multiple isoforms:
FREM1 is essential for epidermal adhesion during embryogenesis and maintains dermal-epidermal cohesion. Mutations in FREM1 cause Fraser syndrome (cryptophthalmos, renal defects) and bleb-like phenotypes in mice . Antibodies are used to study:
FREM1 is linked to HIV resistance in high-risk cohorts:
rs1552896 SNP: The minor allele correlates with HIV resistance in Kenyan sex workers and mother-child cohorts .
TILRR variant: A splice isoform modulates NF-κB signaling and immune cell infiltration (e.g., CD4+ T cells, M1 macrophages) .
FREM1 expression in breast cancer (BC) tissues:
High expression: Correlates with favorable outcomes (e.g., lower metastasis, ER+/PR+ status) .
Immune infiltration: Positively associates with CD8+ T cells and M1 macrophages, indicating anti-tumor immune responses .
FREM1 expression: Elevated in cervical epithelial tissues, suggesting a role in mucosal barrier integrity .
TILRR variant: Enhances IL-1R1 signaling, promoting pro-inflammatory responses that may limit HIV entry .
FREM1 and immune infiltration: High FREM1 expression correlates with CD4+/CD8+ T-cell infiltration and M1 macrophage polarization, indicating a tumor-suppressive microenvironment .
FREM1 and GATA4/SLIT3: Collaborative roles in lung lobulation and renal development, as shown in mouse models .
FREM1 is an extracellular matrix protein involved in the formation and organization of basement membranes, which are thin sheet-like structures that separate and support cells in many tissues. The protein interacts with FRAS1 and FREM2 during embryonic development as components of basement membranes. These basement membranes anchor epithelial cells to other embryonic tissues, including those that develop into connective tissues and kidneys . FREM1 has gained significance as a research target due to its associations with multiple conditions, including its identification as a diagnostic gene signal in heart failure progression and its potential role in conferring resistance to HIV infection . Additionally, mutations in FREM1 have been linked to Manitoba oculotrichoanal syndrome and bifid nose, renal agenesis, and anorectal malformations syndrome .
FREM1 antibodies are utilized in multiple research applications focusing on both basic science and translational medicine:
Western Blotting (WB): Detection of FREM1 protein expression in tissue and cell lysates with recommended working dilutions of 0.5-1 μg/mL
Immunohistochemistry (IHC-P): Visualization of FREM1 in paraffin-embedded tissue sections at approximately 10 μg/mL concentrations
Immunocytochemistry (ICC): Detection of FREM1 in cultured cells
FREM1 antibodies have been particularly valuable in cardiovascular research to investigate heart failure mechanisms and in HIV research to understand resistance mechanisms in mucosal tissues .
FREM1 shows a specific expression pattern that researchers should be aware of when planning experiments:
Embryonic tissues: FREM1 is widely expressed in regions of epithelial/mesenchymal interaction and epidermal remodeling during development
Adult tissues: FREM1 mRNA is highly expressed in tissues relevant for HIV-1 infection, with protein expression detected in the ectocervical mucosa of HIV-resistant women
Cardiovascular system: Significant expression has been observed in heart tissue, where FREM1 may serve as a diagnostic gene signal for heart failure
Immune context: FREM1 expression has been correlated with specific immune cell subtypes, showing positive correlation with resting mast cells (r = 0.353, P < 0.001) and negative correlation with neutrophils (r = −0.270, P < 0.001)
For immunohistochemical detection, researchers should anticipate signal in basement membrane regions where epithelial cells interface with underlying tissues.
FREM1 antibodies can be employed in sophisticated research designs to investigate heart failure mechanisms. Recent integrated bioinformatics approaches have identified FREM1 as a diagnostic gene signal in heart failure progression with exceptional potential (AUC = 0.953-1.000 in validation datasets) .
Methodological approach:
Tissue comparison analysis: Use FREM1 antibodies in immunohistochemistry to compare heart tissue from normal and heart failure subjects
Correlation with immune infiltrates: Combine FREM1 immunostaining with immune cell markers to verify the significant correlations observed with:
Resting mast cells (positive correlation, r = 0.353, P < 0.001)
Neutrophils (negative correlation, r = −0.270, P < 0.001)
T cell subtypes and macrophage populations
The following table summarizes immune cell populations significantly altered in heart failure that correlate with FREM1 expression:
Immune Cell Subtype | Change in Heart Failure | P-value | Correlation with FREM1 |
---|---|---|---|
CD8+ T cells | Increased | P = 0.0028 | Significant |
Resting mast cells | Increased | P < 0.001 | Positive (r = 0.353) |
CD4+ memory resting T cells | Decreased | P = 0.017 | Significant |
Regulatory T cells (Tregs) | Decreased | P = 0.047 | Significant |
Monocytes | Decreased | P < 0.001 | Significant |
M2 macrophages | Decreased | P < 0.001 | Significant |
CD4+ naive T cells | Altered | P = 0.027 | Significant |
M0 macrophages | Altered | P < 0.001 | Significant |
Neutrophils | Altered | P < 0.001 | Negative (r = -0.270) |
This approach allows researchers to investigate how FREM1 expression relates to immune cell infiltration and activation in heart failure pathogenesis .
To investigate FREM1's role in HIV resistance, researchers should employ a multi-faceted approach combining genetic, protein expression, and functional analyses. Genetic evidence has associated the minor allele of SNP rs1552896 in FREM1 with resistance to HIV infection (OR = 2.67, 95% CI: 1.47-4.84) .
Recommended methodological framework:
Genetic screening: Genotype rs1552896 and other FREM1 polymorphisms in study populations with differential HIV susceptibility
Protein localization: Perform immunohistochemistry using FREM1 antibodies on ectocervical mucosal biopsies, where FREM1 protein has been shown to be expressed in HIV-resistant women
Expression quantification: Use Western blotting and qRT-PCR to quantify FREM1 protein and mRNA levels in relevant tissues
Functional assays: Develop in vitro models of HIV entry and infection in cells with modulated FREM1 expression
Researchers should be aware that FREM1 has a splice variant called TILRR (Toll-like interleukin-1 receptor regulator) that is an integral component of innate immune responses . Both forms should be investigated, as TILRR can stimulate innate immune responses and its expression increases in monocytes and hardened plaques after myocardial infarction .
Successful immunohistochemical detection of FREM1 requires careful optimization based on tissue type and fixation method:
For paraffin-embedded tissues:
Antigen retrieval: Use citric acid-based antigen retrieval methods as demonstrated in successful studies of FREM1 expression
Antibody concentration: Begin with 10 μg/mL for paraffin sections and adjust based on signal-to-noise ratio
Incubation conditions: Overnight incubation at 4°C often yields better results than shorter incubations at room temperature
Detection systems: For tissues with lower expression levels, amplification systems such as tyramide signal amplification may be necessary
Controls: Include both positive controls (tissues known to express FREM1) and negative controls (either primary antibody omission or isotype controls)
For basement membrane visualization, dual immunofluorescence with antibodies against collagen or other basement membrane components can help localize FREM1 in relation to the basement membrane structure .
Non-specific binding is a common challenge when working with antibodies against extracellular matrix proteins like FREM1. Researchers can employ these strategies to improve specificity:
Antibody selection: Choose affinity-purified antibodies, such as those raised against specific peptides near the carboxy terminus of human FREM1
Blocking optimization: Extend blocking steps (2-3 hours at room temperature) using 5-10% normal serum from the species in which the secondary antibody was raised
Buffer adjustment: Add 0.1-0.3% Triton X-100 for intracellular epitopes or reduce detergent concentration for membrane proteins
Cross-adsorption: If cross-reactivity with related proteins (FRAS1, FREM2) is suspected, pre-adsorb the antibody with recombinant related proteins
Validation approaches: Confirm specificity through multiple methods:
Testing in tissues from FREM1 knockout models
Peptide competition assays
Comparing staining patterns with multiple antibodies targeting different FREM1 epitopes
For Western blotting applications, increasing the washing duration and stringency can help reduce background signals.
Emerging research has revealed significant correlations between FREM1 expression and immune cell populations, suggesting new research opportunities:
Immune cell correlation studies: Use flow cytometry with FREM1 antibodies to analyze FREM1 expression in sorted immune cell populations, especially focusing on:
Functional impact assessment: Investigate how FREM1 modulates immune cell function by:
Analyzing cytokine production in cells with differential FREM1 expression
Assessing migration and adhesion properties of immune cells in the presence of recombinant FREM1
Evaluating FREM1's role in immune cell recruitment to sites of inflammation
TILRR variant studies: Specifically investigate the TILRR splice variant of FREM1, which has been shown to regulate immune inflammation and stimulate innate immune responses
The relationship between FREM1 and immune cells is particularly relevant for both cardiovascular disease and infectious disease research, as FREM1 appears to influence inflammatory responses in multiple contexts.
Integrated bioinformatics approaches have identified FREM1 as a promising diagnostic gene signal for heart failure with exceptional performance metrics. Researchers can explore its biomarker potential using these approaches:
Biomarker validation studies: Design studies to validate FREM1 as a diagnostic biomarker by:
Measuring FREM1 expression in large cohorts of heart failure patients versus controls
Correlating FREM1 levels with disease severity, progression, and outcomes
Comparing FREM1's diagnostic value to established biomarkers (BNP, NT-proBNP)
Multi-omics integration: Combine antibody-based protein detection with:
Transcriptomic data (RNA-seq)
Genetic information (relevant SNPs)
Proteomic profiles
Development of diagnostic assays: Create standardized ELISA or other immunoassays specifically optimized for FREM1 detection in clinical samples
Machine learning approaches have already shown the value of FREM1 as a diagnostic signal. In validation studies, FREM1 demonstrated remarkable diagnostic performance with AUC values of 0.953 (95% CI: 0.904-1.000) and 1.000 (95% CI: 1.000-1.000) in two independent datasets . This exceptional performance suggests that antibody-based detection of FREM1 could provide valuable clinical diagnostic information.