MS4A7 Antibody

What cellular populations express MS4A7 and how can this be effectively visualized?

Immunohistochemistry remains the gold standard using validated antibodies such as HPA017418 (Sigma) at 1:50 dilution with overnight incubation at 4°C for optimal results in tissue sections . For synovial tissue analysis, digital quantification can be performed using QuPath software to calculate the percentage of MS4A7-positive cells within the tissue sample .

For co-localization studies, multiplex immunofluorescence using tyramide signal amplification protocols has proven effective, particularly for detecting MS4A7 alongside macrophage markers such as CD68, followed by DAPI counterstaining and digital scanning .

What applications are MS4A7 antibodies validated for in research settings?

MS4A7 antibodies have been validated for multiple research applications with varying protocols:

Researchers should note that optimization is typically required for each specific experimental system, and validation using positive controls (such as BV-2 cells for Western blot) is strongly recommended .

How should MS4A7 antibody specificity be validated prior to experimental use?

Establishing antibody specificity is critical for reliable MS4A7 research. A systematic validation approach should include:

• Positive control testing using tissues/cells with known MS4A7 expression (B cells, monocytes, BV-2 cells)

• Western blot analysis confirming detection of a single band at approximately 26.1 kDa (the reported molecular weight of MS4A7)

• Comparative analysis using multiple antibodies targeting different epitopes where possible

• Knockout/knockdown validation where the antibody signal should be absent or significantly reduced in MS4A7-deficient samples

• Cross-reactivity testing if working with non-human species, as MS4A7 has orthologs in canine, porcine, monkey, mouse and rat models

This validation workflow ensures that experimental findings can be confidently attributed to authentic MS4A7 detection rather than non-specific binding.

How does MS4A7 expression correlate with immune cell infiltration in tumor microenvironments?

MS4A7 expression demonstrates significant correlations with immune cell infiltration in tumor microenvironments, particularly in lung adenocarcinoma. Analysis using the TIMER database has revealed strong associations between MS4A7 expression and the abundance of macrophages and dendritic cells .

This correlation suggests MS4A7 may serve as a potential biomarker for immune infiltration patterns. When designing experiments to investigate these relationships:

• Multiplex immunohistochemistry combining MS4A7 staining with immune cell markers (CD68 for macrophages, CD11c for dendritic cells) provides spatial context

• Flow cytometry can quantify co-expression patterns in dissociated tumor samples

• Single-cell RNA sequencing offers the most comprehensive approach to define MS4A7-expressing populations within the tumor immune landscape

Notably, in lung adenocarcinoma tissues, MS4A7 expression has been found significantly downregulated in eight out of nine patient samples compared to adjacent normal tissue when assessed by RT-qPCR . This contradicts some earlier studies, highlighting the importance of context-specific analysis.

What are the optimal protocols for detecting MS4A7 in specific tissue types?

Detection protocols for MS4A7 must be tailored to specific tissue types for optimal results:

For synovial tissue:

• Use HPA017418 (Sigma) at 1:50 dilution with overnight incubation at 4°C

• Block with Dako Blocking solution (20 minutes at room temperature)

• Detect using EnVision HRP System and develop with DAB

• For digital analysis, scan using Nanozoomer S210 and quantify with QuPath software

For neurological tissues (studying microglia):

• Single-cell RNA sequencing has proven effective for identifying MS4A7+ microglial populations

• Sort cells based on canonical microglial markers before MS4A7 analysis to enrich target populations

• Include analysis of co-expressed genes like Tnf, Il1b, and Ifnar1 to characterize the proinflammatory signature

For lung tissue:

• RT-qPCR assays have successfully quantified MS4A7 expression differences between lung adenocarcinoma and normal adjacent tissue

• For immunohistochemistry, use Background Sniper blocking (20 minutes at room temperature) followed by HRP-polymer detection systems

How can MS4A7 expression be accurately quantified at the transcriptional level?

For accurate quantification of MS4A7 at the transcriptional level:

• RT-qPCR approaches require careful primer design spanning exon-exon junctions to avoid genomic DNA amplification. Normalization to multiple reference genes is essential for reliable quantification.

• For transcriptome-wide analysis, RNA-sequencing data processing should:

  • Convert counts data to TPM

  • Normalize using log2(TPM+1) transformation

  • Apply appropriate statistical tests (log-rank tests for survival differences)

  • Consider timeROC analysis for evaluating predictive model accuracy

• When comparing expression between tumors and normal tissues, paired samples from the same patient yield more reliable results by controlling for inter-individual variability, as demonstrated in lung adenocarcinoma studies .

How does MS4A7 function in neuroinflammatory conditions and what are the best approaches to study this role?

MS4A7+ microglia represent a distinct population associated with neuroinflammation, particularly in conditions like lupus with autoantibody-mediated neuroinflammation. These cells show significant transcriptional differences from homeostatic microglia, including:

• Upregulation of proinflammatory cytokines (Tnf, Il1b)

• Increased expression of the type I IFN receptor (Ifnar1)

• Enhanced expression of complement receptors (C3ar1, Cd93)

• Elevated levels of phagocytosis-associated proteins (Axl, Lyz2)

To effectively study MS4A7 in neuroinflammatory contexts:

Single-cell RNA sequencing provides the most comprehensive approach, allowing identification of MS4A7+ microglial clusters and comparison of their transcriptional profiles with homeostatic microglia. The MS4A7+ microglial signature shows similarities to disease-associated microglia (DAM), neuropsychiatric lupus erythematosus (NPSLE), and neurodegenerative microglia (MGnD) gene signatures .

Interventional studies using captopril treatment in DNRAb+ mouse models have demonstrated reversal of the MS4A7+ microglial phenotype, suggesting therapeutic potential. Analysis frameworks should include:

• Cluster proportion analysis between treatment groups

• Detailed examination of differentially expressed genes

• Pathway analysis focusing on inflammation, phagocytosis, and type I IFN signaling

What are the contradictory findings regarding MS4A7 expression in cancer prognosis and how should these be experimentally addressed?

Significant contradictions exist in the literature regarding MS4A7's prognostic value across different cancer types:

• Some studies suggest high MS4A7 expression predicts poor survival

• Others indicate low expression in lung adenocarcinoma correlates with worse outcomes

To experimentally address these contradictions:

• Multi-cohort validation is essential, analyzing MS4A7 expression across different patient populations using consistent methodologies

• Integration of multiple data types (protein expression by IHC, mRNA by RT-qPCR, and DNA/RNA sequencing data)

• Stratification of patients based on tumor subtypes, stages, and treatment histories

• Careful consideration of analysis platforms - the contradictory findings may stem from different databases and analytical approaches

A thorough experimental design should include:

• Paired tumor-normal samples

• Multiple technical approaches (IHC, RT-qPCR, RNA-seq)

• Independent validation cohorts

• Correlation with detailed clinical outcomes

• Analysis of MS4A7 in the context of the broader tumor immune microenvironment

What methodological approaches can differentiate MS4A7 from other MS4A family members in complex experimental systems?

The MS4A gene family comprises multiple members with structural similarities, creating challenges for specific detection. Advanced approaches to ensure MS4A7 specificity include:

• Antibody epitope mapping: Select antibodies targeting unique regions of MS4A7 not conserved in other family members. The commercial antibody HPA017418 (Sigma) has been validated for specific MS4A7 detection .

• Primer/probe design for qPCR and hybridization applications:

  • Target unique exon sequences or exon-exon junctions

  • Validate specificity using overexpression systems of individual family members

  • Include multiple primer sets targeting different regions of MS4A7

• Mass spectrometry-based approaches: For absolute confirmation, MS-based proteomics can identify peptides unique to MS4A7 versus other family members.

• Biological validation: Expression patterns can provide indirect confirmation, as MS4A7 is primarily expressed in B cells and monocytes, while other family members have distinct expression profiles .

When studying model systems, researchers should be aware of potential functional redundancy among MS4A family members and design experiments that can distinguish MS4A7-specific effects from broader family functions.

How can single-cell technologies be optimized for studying MS4A7 in heterogeneous tissue environments?

Single-cell technologies offer unprecedented opportunities to characterize MS4A7 expression and function at cellular resolution:

For optimizing single-cell RNA sequencing approaches:

• Sample preparation is critical - gentle tissue dissociation methods preserve cellular integrity while maximizing yield

• For microglial studies, density gradient separation or magnetic-based enrichment can enhance detection of MS4A7+ populations

• Analysis should focus on identifying marker genes co-expressed with MS4A7 to define functional subpopulations

• Trajectory analysis can elucidate potential transitions between MS4A7- and MS4A7+ states

For spatial transcriptomics/proteomics:

• Multiplex imaging using validated MS4A7 antibodies alongside lineage and functional markers

• Digital spatial profiling to quantify MS4A7 expression while preserving tissue architecture

• Integration of spatial and single-cell data for comprehensive characterization

When analyzing data, clustering approaches should be carefully optimized to distinguish true biological variation from technical noise, as demonstrated in studies of Ms4a7+ microglia in neuroinflammatory models .

What is the relationship between MS4A7 and immune regulation in inflammatory disease states?

MS4A7's role in immune regulation appears context-dependent across inflammatory conditions:

In neuroinflammatory models associated with lupus autoantibodies, Ms4a7+ microglia show a distinct proinflammatory signature characterized by:

• Upregulation of Tnf and Il1b expression

• Increased type I IFN receptor (Ifnar1) expression

• Enhanced complement receptor expression

• Elevated phagocytic activity markers

The transcriptional profile of these cells resembles disease-associated microglia observed in neurodegenerative conditions, suggesting MS4A7 may mark a conserved reactive state across different CNS pathologies .

To investigate causal relationships between MS4A7 and inflammatory regulation:

• Genetic manipulation through CRISPR-Cas9 editing of MS4A7 in relevant cell types

• Pharmacological intervention targeting pathways identified in MS4A7+ cells

• In vivo models examining disease progression in MS4A7-deficient backgrounds

• Correlation of MS4A7 expression with clinical parameters in patient cohorts

The therapeutic potential of MS4A7 modulation is suggested by captopril treatment studies, where attenuation of the MS4A7+ microglial phenotype correlated with improved outcomes .