Recombinant Mouse FERM domain-containing protein 4A (Frmd4a), partial

What is the basic structure and function of the FRMD4A protein?

FRMD4A is a scaffolding protein belonging to the FERM domain-containing protein family. It is localized in the cytoplasm and cytoskeleton, where it binds molecules in the undercoat of cell-to-cell adherens junctions . The protein plays critical roles in:

• Regulation of cell polarity in epithelial cells and neurons

• Cell structure maintenance

• Transport processes

• Signal transduction pathways

FRMD4A contains conserved domains that facilitate its interaction with other cellular components. The FERM domain (Four-point-one, Ezrin, Radixin, Moesin) is particularly important for mediating protein-protein interactions at the interface between the plasma membrane and the cytoskeleton.

How is FRMD4A expression regulated in different tissues?

FRMD4A is expressed in multiple tissues throughout the body, with notably higher expression levels in the brain . In normal epidermal tissue, FRMD4A is primarily expressed in the basal layer of human epidermis . The protein shows differential expression patterns during development and in various physiological states.

Research has shown:

• Upregulation in squamous cell carcinoma cells

• Expression in neural tissues during development

• Tissue-specific regulation that may be influenced by various transcription factors

When designing experiments to study FRMD4A expression, researchers should consider using tissue-specific controls and evaluating expression across multiple developmental timepoints for comprehensive understanding.

What is the role of FRMD4A in cancer progression, particularly in head and neck squamous cell carcinoma?

FRMD4A has been identified as significantly upregulated in head and neck squamous cell carcinoma (HNSCC), with high expression levels correlating with increased risks of relapse . Functional studies have revealed several critical aspects of FRMD4A's role in cancer:

• FRMD4A silencing decreases growth and metastasis of human SCC xenografts in skin and tongue models

• It reduces SCC proliferation and intercellular adhesion

• Attenuation of FRMD4A stimulates caspase-3 activity and increases expression of terminal differentiation markers

• FRMD4A appears to influence the Hippo signaling pathway, as its attenuation causes nuclear accumulation of YAP (Yes-associated protein)

• Treatment with HSP90 inhibitor 17-DMAG or ligation of CD44 with hyaluronan causes nuclear depletion of FRMD4A and reduced SCC growth and metastasis

These findings suggest FRMD4A may represent a novel therapeutic target in HNSCC treatment strategies. For researchers investigating cancer pathways, examining the interaction between FRMD4A and the Hippo signaling pathway may provide valuable insights into mechanisms of cancer progression.

How does FRMD4A contribute to Alzheimer's disease pathology?

FRMD4A has been identified as a genetic risk factor for late-onset Alzheimer's disease through genome-wide haplotype association studies . Several key findings illuminate its potential role:

• Specific haplotypes within FRMD4A on Chr.10p13 have been consistently associated with Alzheimer's disease risk (OR: 1.68; 95% CI: 1.43–1.96; P=1.1 × 10^-10)

• FRMD4A polymorphisms are associated with plasma Aβ42/Aβ40 ratio, with the best signal at P=5.4 × 10^-7

• The protein interacts with Arf6, which controls APP processing

• FRMD4A mutations can disrupt tau secretion by activating cytohesin-Arf6 signaling

This suggests FRMD4A may influence amyloid precursor protein (APP) metabolism and contribute to the development of Alzheimer's disease pathology. Researchers studying Alzheimer's disease mechanisms should consider investigating FRMD4A's impact on both amyloid and tau pathways.

What neurodevelopmental conditions are associated with FRMD4A mutations?

Mutations in the FRMD4A gene have been associated with several neurodevelopmental conditions, including:

• Corpus callosum anomalies (abnormal genu and splenium of corpus callosum)

• Global developmental delay and intellectual disability

• Macrocephaly or microcephaly (reported cases show both phenotypes)

• Ataxia

• Non-epileptic seizures

A case report identified compound heterozygous missense mutations in FRMD4A [c.1830G>A, p.(Met610Ile) and c.2973G>C, p.(Gln991His)] in a 3-year-old boy with these features . The differences in head circumference phenotypes (macrocephaly versus microcephaly) between reported cases suggest phenotypic variability, though intellectual disability/global developmental delay and ataxia appear to be consistent features.

What are the most effective methods for studying FRMD4A function in vitro?

When investigating FRMD4A function in vitro, several methodological approaches have proven effective:

• Gene Silencing Techniques:

  • siRNA or shRNA-mediated knockdown to assess loss-of-function effects

  • CRISPR-Cas9 gene editing for complete knockout models

• Recombinant Protein Expression:

  • Expression of tagged FRMD4A constructs (e.g., GFP-tagged) to visualize subcellular localization

  • Domain-specific mutants to identify functional regions

• Cell-Based Assays:

  • Proliferation assays to assess impact on cell growth

  • Migration and invasion assays to evaluate metastatic potential

  • Intercellular adhesion assays

  • Caspase activity assays to measure apoptotic effects

  • Terminal differentiation marker expression analysis

• Protein Interaction Studies:

  • Co-immunoprecipitation to identify binding partners

  • Proximity ligation assays to confirm protein-protein interactions in situ

  • Yeast two-hybrid screening for novel interactors

Research has specifically demonstrated successful application of these techniques in studying FRMD4A's role in cancer progression, showing that silencing FRMD4A reduced SCC proliferation and intercellular adhesion while stimulating caspase-3 activity .

What animal models are appropriate for studying FRMD4A in vivo?

Several animal models have proven valuable for in vivo FRMD4A research:

• Mouse Models:

  • Xenograft models using human SCC cells with manipulated FRMD4A expression have been successfully used to study cancer progression and metastasis

  • Frmd4a knockout or conditional knockout mice can help understand developmental roles

  • Mouse models with specific mutations that mimic human FRMD4A variants found in patients

• Zebrafish Models:

  • Zebrafish carrying the frmd4a gene (ZDB-GENE-050419-154) are useful for studying developmental aspects due to transparent embryos and rapid development

  • Morpholino-based knockdown or CRISPR-Cas9 gene editing in zebrafish can reveal developmental phenotypes

• Experimental Considerations:

  • When designing xenograft experiments, consider both subcutaneous implantation and orthotopic models (e.g., tongue for HNSCC studies) as demonstrated in previous research

  • Include appropriate controls for genetic background effects

  • For neurodevelopmental studies, comprehensive behavioral testing alongside structural brain imaging may reveal important phenotypes

The choice of model should align with specific research questions, with consideration for tissue-specific expression patterns and phenotypic readouts relevant to the disease or developmental process being studied.

How can researchers effectively quantify FRMD4A expression in tissue samples?

Accurate quantification of FRMD4A expression in tissue samples requires multiple complementary approaches:

• Protein Detection Methods:

  • Immunohistochemistry (IHC) for localization in tissue sections, particularly useful for observing expression in specific cell types (e.g., basal layer of epidermis)

  • Western blotting for semi-quantitative protein level determination

  • ELISA for more precise quantification

  • Mass spectrometry for absolute quantification and post-translational modification analysis

• mRNA Detection Methods:

  • RT-qPCR for relative quantification of transcript levels

  • RNA-seq for comprehensive transcriptome analysis and alternative splicing detection

  • In situ hybridization to visualize spatial expression patterns in tissues

• Methodological Considerations:

  • Use multiple antibodies targeting different epitopes to confirm specificity

  • Include appropriate positive and negative control tissues

  • Consider analysis of different splice variants that may have distinct functions

  • Normalize expression data to appropriate reference genes/proteins that are stable in the tissue of interest

• Data Analysis Approach:

  • Employ quantitative image analysis for IHC data

  • Use statistical methods appropriate for expression data distribution

  • Consider analyzing expression correlation with clinical outcomes or other molecular markers

When working with clinical samples, correlating FRMD4A expression with patient outcomes (as demonstrated in HNSCC studies showing association with relapse risk ) can provide valuable prognostic insights.

How do FRMD4A mutations specifically impact neuronal development and polarization?

FRMD4A plays a critical role in neuronal development and polarization through several mechanisms:

• Cell Polarity Regulation:

  • FRMD4A functions as a scaffolding protein that regulates cell polarity in neurons

  • Its interaction with cytoskeletal components is essential for establishing neuronal polarity during development

  • Mutations disrupt these interactions, potentially affecting neuronal migration and axon/dendrite specification

• Molecular Pathway Involvement:

  • FRMD4A likely interfaces with conserved polarity complexes (Par, Crumbs, Scribble)

  • It may regulate membrane protein trafficking needed for polarized growth

  • The protein potentially influences small GTPase signaling that directs cytoskeletal rearrangements

• Corpus Callosum Development:

  • Patient data shows FRMD4A mutations associated with corpus callosum anomalies

  • This suggests a role in axon guidance across the midline during brain development

  • Mutations may disrupt interhemispheric connectivity by affecting growth cone dynamics

• Experimental Approaches to Study These Effects:

  • Primary neuronal cultures with FRMD4A knockdown/mutation to assess polarity establishment

  • Time-lapse microscopy of developing neurons to track morphological changes

  • Analysis of axon/dendrite specification markers in mutant conditions

  • In vivo brain imaging in animal models with FRMD4A mutations

The compound heterozygous mutations [c.1830G>A, p.(Met610Ile) and c.2973G>C, p.(Gln991His)] identified in patients alter protein side chains and likely disrupt FRMD4A function and interactions with other molecules , potentially explaining the observed neurodevelopmental phenotypes.

What is the relationship between FRMD4A and the Hippo signaling pathway in tissue homeostasis?

The relationship between FRMD4A and the Hippo signaling pathway represents an important area of investigation with implications for both normal development and disease:

• Observed Molecular Interactions:

  • FRMD4A attenuation causes nuclear accumulation of YAP (Yes-associated protein), a key effector of the Hippo pathway

  • This suggests FRMD4A may normally function to regulate YAP localization and activity

  • The interaction potentially links cell polarity regulation to growth control mechanisms

• Functional Consequences:

  • Hippo pathway dysregulation affects cell proliferation, apoptosis, and differentiation

  • FRMD4A's influence on YAP may explain its role in cancer progression

  • This relationship could be relevant to developmental processes requiring coordinated growth control

• Experimental Evidence:

  • Treatment with HSP90 inhibitor 17-DMAG causes nuclear depletion of FRMD4A and nuclear accumulation of YAP

  • This treatment reduces SCC growth and metastasis, suggesting therapeutic potential

  • The molecular mechanism linking FRMD4A to YAP regulation remains incompletely characterized

• Research Approaches:

  • Co-immunoprecipitation studies to identify direct vs. indirect interactions

  • Phosphorylation analysis of YAP in FRMD4A mutant conditions

  • Transcriptional reporter assays for YAP target genes with FRMD4A manipulation

  • Investigation of upstream Hippo kinases (MST1/2, LATS1/2) in relation to FRMD4A

Understanding this relationship more fully could provide insights into both normal tissue homeostasis mechanisms and potential therapeutic approaches for conditions like cancer where Hippo pathway dysregulation contributes to pathology.

How do specific FRMD4A polymorphisms affect amyloid-beta metabolism in Alzheimer's disease?

The relationship between FRMD4A polymorphisms and amyloid-beta metabolism in Alzheimer's disease is complex and multifaceted:

• Genetic Association Evidence:

  • Genome-wide haplotype association studies identified FRMD4A as a risk factor for late-onset Alzheimer's disease

  • Specific polymorphisms are strongly associated with plasma Aβ42/Aβ40 ratio (best signal at P=5.4 × 10^-7)

  • This suggests FRMD4A variants influence APP processing or Aβ clearance mechanisms

• Molecular Mechanisms:

  • FRMD4A interacts with Arf6, which controls APP processing

  • The protein may influence cytohesin-Arf6 signaling, affecting tau secretion

  • This provides a potential mechanistic link to both amyloid and tau pathology in AD

• Experimental Evidence:

  • Several FRMD4A SNPs show significant associations with Aβ plasma concentrations in non-demented populations

  • Nine SNPs reached significance after Bonferroni correction for association with Aβ42/Aβ40 ratio

  • The strongest association was observed with rs7921545 (meta-analyzed z-score approach)

• Analytical Approaches:

  • To study these effects, researchers should consider:

    • Cell-based assays measuring APP processing with different FRMD4A variants

    • In vivo models expressing human FRMD4A risk variants to assess Aβ dynamics

    • Correlation studies between FRMD4A genotypes and CSF/plasma biomarkers in patients

    • Structural biology approaches to understand how polymorphisms affect protein function

This research area has significant potential for identifying new therapeutic targets in Alzheimer's disease, as modulating FRMD4A function might influence amyloid metabolism through novel mechanisms distinct from direct secretase targeting.

What are the challenges in distinguishing phenotypic effects of different FRMD4A mutations?

Researchers face several significant challenges when attempting to distinguish the phenotypic effects of different FRMD4A mutations:

• Phenotypic Variability:

  • Case reports show contradictory phenotypes (e.g., macrocephaly vs. microcephaly) with different FRMD4A mutations

  • The same core features (developmental delay, intellectual disability, ataxia) appear consistent across cases

  • This variability complicates genotype-phenotype correlation studies

• Mutation Characterization Challenges:

  • Different prediction algorithms may yield conflicting pathogenicity assessments

  • The p.(Met610Ile) mutation was predicted to be benign by PolyPhen-2, SIFT, and Provean, while p.(Gln991His) was predicted to be damaging

  • Functional studies are needed to validate computational predictions

• Complex Genetic Architecture:

  • Compound heterozygosity (as seen in reported cases) makes it difficult to attribute specific phenotypic features to individual mutations

  • Possible interactions with other genetic modifiers may influence phenotypic expression

  • The large size of the FRMD4A gene (23 exons) increases the complexity of comprehensive genetic screening

• Research Strategies to Address These Challenges:

  • Detailed clinical phenotyping across multiple cases with the same mutation

  • Development of isogenic cell lines with specific mutations for direct comparison

  • Animal models expressing human mutations to assess developmental trajectories

  • Structure-function studies to determine how different domains contribute to protein activity

  • Analysis of different mutations' effects on interaction partners (protein-protein interaction networks)

How should researchers interpret contradictory findings about FRMD4A function across different experimental systems?

When confronted with contradictory findings about FRMD4A function across different experimental systems, researchers should consider several methodological and biological factors:

• Context-Dependent Functions:

  • FRMD4A may have distinct roles in different cell types or tissues (e.g., epithelial cells versus neurons)

  • Developmental timing may influence protein function and pathway interactions

  • Disease states may alter normal protein functions or reveal conditional phenotypes

• Technical Considerations:

  • Different antibodies may have varying specificities and recognize different FRMD4A epitopes or isoforms

  • The use of tagged constructs (e.g., GFP-FRMD4A) might affect protein localization or function

  • Knockdown efficiency and off-target effects vary between siRNA/shRNA approaches

• Experimental System Limitations:

  • In vitro systems may not recapitulate the complex microenvironment of tissues

  • Overexpression systems may create artifactual interactions or phenotypes

  • Animal models may have species-specific differences in FRMD4A function or regulation

• Recommended Analytical Approach:

  • Triangulate findings using multiple complementary techniques

  • Consider dose-dependent effects – partial vs. complete loss of function

  • Validate key findings across different cell types or model systems

  • Carefully document experimental conditions that may influence outcomes

  • Design experiments to directly test contradictory hypotheses

The multifunctional nature of FRMD4A as both a scaffolding protein in cell polarity and a potential regulator of signaling pathways (e.g., Hippo, Arf6) suggests its effects may be highly context-dependent, explaining some apparent contradictions in research findings.

What statistical approaches are most appropriate for analyzing FRMD4A genetic association data in disease cohorts?

When analyzing FRMD4A genetic association data in disease cohorts, researchers should consider these statistical approaches and considerations:

• Association Testing Strategies:

  • Single-SNP analysis using logistic regression models adjusted for relevant covariates (age, sex, population structure)

  • Haplotype-based approaches have proven effective in identifying FRMD4A associations with Alzheimer's disease that might be missed in traditional GWAS

  • Gene-based tests that aggregate multiple variants (e.g., SKAT, burden tests) for rare variant analysis

• Study Design Considerations:

  • Multi-stage replication approaches as demonstrated in FRMD4A Alzheimer's studies (initial discovery followed by independent replication cohorts)

  • Meta-analysis using fixed or random effects models depending on heterogeneity

  • Careful matching of cases and controls to minimize bias

• Specific Statistical Methods:

  • For quantitative traits (e.g., Aβ plasma levels), general linear models under additive genetic models adjusted for relevant covariates

  • Inverse-variance weighting (fixed-effects meta-analysis) to investigate homogeneity of effects across studies

  • z-score transformations for biomarker data to normalize distributions across centers/studies

• Multiple Testing Correction:

  • Bonferroni correction for multiple testing (as applied in FRMD4A-Aβ association studies)

  • False discovery rate (FDR) approaches for less conservative correction

  • Permutation-based approaches to establish empirical significance thresholds

• Data Visualization:

  • Forest plots for meta-analysis results

  • Manhattan plots for genome-wide significance

  • Linkage disequilibrium (LD) plots to understand haplotype structure

The FRMD4A Alzheimer's disease association study demonstrated the value of these approaches, identifying significant associations that were consistently replicated across multiple cohorts and validated through biomarker correlations .

What are the best approaches for integrating FRMD4A functional data with clinical observations?

Integrating FRMD4A functional data with clinical observations requires sophisticated approaches to bridge laboratory findings and patient outcomes:

• Translational Research Frameworks:

  • Correlate FRMD4A expression levels or mutation status with patient outcomes (as demonstrated in HNSCC studies linking expression to relapse risk)

  • Develop and validate predictive models incorporating FRMD4A biomarkers

  • Design functional studies based on patterns observed in clinical cohorts

• Biomarker Development:

  • Evaluate FRMD4A expression or downstream effectors as potential prognostic/predictive biomarkers

  • Assess FRMD4A-associated plasma Aβ ratios as potential Alzheimer's disease biomarkers

  • Develop assays suitable for clinical implementation (reproducible, standardized)

• Genotype-Phenotype Correlation:

  • Create detailed phenotyping protocols for patients with FRMD4A variants

  • Compare clinical features across mutation types using standardized assessments

  • Develop databases integrating genetic, molecular, and clinical data

• Methodological Integration Strategies:

  • Patient-derived cell models (iPSCs, organoids) to study mutation effects in relevant cell types

  • Humanized animal models expressing patient-specific mutations

  • Systems biology approaches to contextualize FRMD4A within broader pathway networks

• Statistical and Computational Approaches:

  • Machine learning models to identify patterns in complex datasets

  • Bayesian networks to infer causal relationships between molecular findings and clinical outcomes

  • Pathway enrichment analysis to contextualize FRMD4A functions

This integration is particularly important for neurodevelopmental disorders associated with FRMD4A mutations, where understanding the connection between molecular dysfunction and clinical manifestations could guide development of targeted interventions or therapies.