rbm47 Antibody, HRP conjugated

What is RBM47 and why is it important in biological research?

RBM47 (RNA Binding Motif Protein 47) is a multifunctional RNA-binding protein that plays crucial roles in regulating RNA stability, alternative splicing, and C-to-U RNA editing. RBM47 contains three RNA recognition motifs (RRMs) that are essential for its function in binding target mRNAs . The protein has dual significance in research: it demonstrates potent antiviral activity by stabilizing IFNAR1 mRNA to enhance interferon signaling, while also functioning as a tumor suppressor in several cancers . RBM47 is an interferon-stimulated gene (ISG) that can be induced by viral infection or interferon stimulation, making it an important component of the innate immune response .

What are the optimal conditions for using HRP-conjugated RBM47 antibodies in Western blotting?

For optimal Western blotting results with HRP-conjugated RBM47 antibodies:

• Sample preparation: Extract proteins using RIPA buffer with protease inhibitors

• Loading: Use 20-40 μg of total protein per lane

• Transfer: Transfer to PVDF membrane at 100V for 90 minutes

• Blocking: Block with 5% non-fat milk in TBST for 1 hour at room temperature

• Primary antibody: Dilute RBM47 antibody 1:100 to 1:1000 (optimize for specific antibody) and incubate overnight at 4°C

• Washing: Wash 3-5 times with TBST, 5 minutes each

• Secondary antibody: If using non-conjugated primary antibody, incubate with HRP-conjugated secondary antibody (1:5000) for 1 hour at room temperature; if using direct HRP-conjugated RBM47 antibody, this step is skipped

• Detection: Use enhanced chemiluminescence (ECL) substrate for visualization

• Expected band size: Human RBM47 appears at approximately 64 kDa

Studies have successfully used this method to detect RBM47 expression in various cell lines, including 293T, HFF, HUVEC, and THP-1 cells, particularly following IFN-α stimulation .

How should RBM47 antibodies be validated before experimental use?

Proper validation of RBM47 antibodies should include:

• Western blot analysis using:

  • Positive controls: Cell lines with confirmed RBM47 expression (e.g., IFN-α-stimulated cells)

  • Negative controls: RBM47 knockout cells or RBM47-silenced cells using validated shRNAs (such as sh47-1, sh47-2, or sh47-3)

  • Recombinant RBM47 protein for antibody specificity

• Immunoprecipitation followed by mass spectrometry:

  • Verify pull-down of RBM47 and check for expected interacting partners

• Immunofluorescence/immunohistochemistry validation:

  • Compare staining patterns to mRNA expression data

  • Include RBM47 knockout or knockdown controls

  • Cross-validate with multiple antibodies targeting different epitopes

• ELISA or dot blot with recombinant protein:

  • Establish detection limits and linear range of quantification

Research has shown that validation is particularly important for RBM47 antibodies as expression levels can vary significantly between tissues and following interferon stimulation .

How can RBM47 antibodies be optimized for RNA immunoprecipitation (RIP) assays to study RBM47-RNA interactions?

For optimizing RIP assays with RBM47 antibodies:

• Cross-linking protocol:

  • Use 1% formaldehyde for protein-RNA cross-linking (10 minutes at room temperature)

  • Quench with 0.125 M glycine for 5 minutes

• Lysis conditions:

  • Lyse cells in buffer containing 25 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1 mM EDTA, 1% NP-40, 5% glycerol with RNase inhibitors and protease inhibitors

  • Sonicate briefly to disrupt nuclear membranes without fragmenting RNA

• Immunoprecipitation:

  • Pre-clear lysate with protein A/G beads for 1 hour

  • Incubate with RBM47 antibody (5-10 μg) overnight at 4°C

  • Add protein A/G beads for 2-4 hours at 4°C

  • Wash extensively with increasing stringency

• RNA extraction and analysis:

  • Reverse cross-links with proteinase K treatment

  • Extract RNA using TRIzol reagent

  • Analyze by RT-qPCR or RNA sequencing

Published research has used this approach to demonstrate that RBM47 specifically binds to IFNAR1 mRNA at the 3'UTR region, with three distinct binding sites identified through RIP followed by qRT-PCR analysis . These studies showed significant enrichment of IFNAR1 mRNA, but not IFNAR2 mRNA, in RBM47-Flag immunoprecipitates, confirming the specificity of RBM47-RNA interactions .

What are the key considerations when using RBM47 antibodies for immunohistochemistry (IHC) in different tissue types?

When performing IHC with RBM47 antibodies across various tissue types:

• Tissue-specific considerations:

  • Pancreatic tissue: Requires extended antigen retrieval (20 minutes in citrate buffer, pH 6.0) due to dense stroma

  • Breast tissue: May need lower antibody concentration (1:200) to avoid background staining

  • Lung tissue: Often requires shorter antigen retrieval time (10 minutes)

• Optimal protocol:

  • Fixation: 10% neutral buffered formalin, 24 hours

  • Antigen retrieval: Heat-induced epitope retrieval in citrate buffer (pH 6.0)

  • Blocking: 1% bovine serum albumin (BSA) solution

  • Primary antibody: RBM47 antibody (1:100 dilution) overnight at 4°C

  • Secondary detection: HRP-conjugated Goat Anti-rabbit IgG (1:100) for 45 minutes

  • Visualization: 3,3'-diaminobenzidine (DAB) staining for 10 minutes with hematoxylin counterstain

• Controls and validation:

  • Positive control: Include tissues with known RBM47 expression (e.g., interferon-stimulated tissues)

  • Negative control: Omit primary antibody or use tissues from RBM47 knockout/knockdown models

  • Expression pattern verification: RBM47 shows predominantly cytoplasmic localization

Research has successfully used this approach for evaluating RBM47 expression in pancreatic cancer tissues, revealing correlations between RBM47 expression and natural killer cell infiltration patterns .

How can interferon stimulation be used to optimize RBM47 detection in experimental systems?

Since RBM47 is an interferon-stimulated gene, interferon treatment can enhance detection:

• Interferon stimulation protocol:

  • Treat cells with recombinant IFN-α (1000 U/ml) for 12-24 hours

  • For optimal time course analysis: Collect samples at 0, 3, 6, 12, and 24 hours

  • Use JAK inhibitors (e.g., Ruxolitinib) as negative control to confirm specificity

• Cell-type specific considerations:

  Cell Type	Optimal IFN-α Concentration	Peak RBM47 Expression	Notes
  293T	1000 U/ml	12-16 hours	Strong induction
  HFF	500 U/ml	8-12 hours	Moderate induction
  HUVEC	1000 U/ml	12-24 hours	Sustained expression
  THP-1	500-1000 U/ml	6-12 hours	Rapid response

• Detection methods optimization:

  • Western blot: Increase sample loading to 40 μg for untreated samples

  • qRT-PCR: Design primers spanning exon junctions to avoid genomic DNA amplification

  • Immunofluorescence: Increase primary antibody incubation to overnight at 4°C

Research has demonstrated that IFN-α stimulation significantly upregulates both mRNA and protein levels of RBM47 in various cell types, with the promoter region of RBM47 containing three putative STAT1 binding motifs critical for IFN induction .

What are common issues when detecting RBM47 in samples and how can they be resolved?

Common detection issues and solutions include:

• Weak or no signal in Western blots:

  • Increase protein loading (40-60 μg)

  • Extend primary antibody incubation to overnight at 4°C

  • Use more sensitive detection systems (e.g., SuperSignal West Femto)

  • Consider pre-treating samples with IFN-α to upregulate RBM47 expression

  • Use RBM47-overexpressing cells as positive controls

• Non-specific bands:

  • Increase blocking time (2 hours with 5% milk)

  • Use more stringent washing conditions (6 × 10 minutes with 0.1% TBST)

  • Validate with RBM47 knockout controls to identify the specific band

  • Use monoclonal antibodies for higher specificity

• Inconsistent results between experiments:

  • Standardize cell culture conditions (density, passage number)

  • Control for interferon status of cells (endogenous interferon can vary)

  • Use internal loading controls (e.g., tubulin) for normalization

  • Prepare fresh lysates as RBM47 may degrade during storage

• Tissue-specific detection challenges:

  • For tissues with low expression, consider using amplification systems

  • For highly autofluorescent tissues, use Sudan Black B to reduce background

Research has shown that knockout validation is particularly important for RBM47 antibodies, as demonstrated in studies where RBM47 knockout cell lines were used to confirm antibody specificity in Western blot and immunofluorescence assays .

How can researchers distinguish between the functions of different RBM47 isoforms in experimental designs?

To distinguish between RBM47 isoforms functionally:

• Isoform-specific expression strategies:

  • Generate expression constructs for full-length RBM47, 3RRM variant (containing only the RNA recognition motifs), and ΔRRM variant (lacking RNA recognition motifs)

  • Use lentiviral systems for stable expression with tetracycline-inducible promoters

  • Validate expression by Western blot with antibodies recognizing different epitopes

• Functional assays to differentiate isoforms:

  • Reporter assays: Test each isoform's ability to enhance ISRE (IFN-stimulated response element) promoter activity

  • Antiviral assays: Compare virus inhibition (e.g., VSV-GFP replication) between isoforms

  • mRNA stability assays: Measure IFNAR1 mRNA half-life in cells expressing different isoforms

• RNA binding specificity assessment:

  • Perform RNA immunoprecipitation with each isoform

  • Use EMSA (electrophoretic mobility shift assay) to compare binding to IFNAR1 mRNA fragments

  • Conduct luciferase reporter assays with target 3'UTR sequences

Research has demonstrated that the RNA recognition domain of RBM47 is essential for its antiviral function, as the full-length RBM47 and 3RRM variant enhanced ISRE promoter activity and inhibited VSV-GFP replication, while the ΔRRM mutant did not .

How can researchers combine RBM47 antibodies with other methodologies to study RNA-protein complexes in situ?

To study RBM47-RNA complexes in situ:

• Proximity ligation assay (PLA) for RNA-protein interaction:

  • Fix cells with 4% paraformaldehyde

  • Perform reverse transcription with BrdU-labeled nucleotides

  • Incubate with anti-RBM47 antibody and anti-BrdU antibody

  • Use PLA probes against the primary antibodies

  • Amplify signal according to PLA protocol

  • Visualize interactions as fluorescent dots

• Fluorescence-based RNA-protein co-localization:

  • Perform RNA FISH for target mRNAs (e.g., IFNAR1) using fluorescent probes

  • Follow with immunofluorescence for RBM47 using specific antibodies

  • Analyze co-localization using confocal microscopy

  • Quantify using Pearson's or Mander's correlation coefficients

• CLIP-seq (cross-linking immunoprecipitation-sequencing) optimization:

  • Cross-link cells with UV irradiation (254 nm, 400 mJ/cm²)

  • Immunoprecipitate with RBM47 antibodies

  • Perform RNA library preparation and high-throughput sequencing

  • Analyze binding motifs and RNA targets using bioinformatics tools

• Biochemical fractionation with immunoblotting:

  • Separate cytoplasmic, nuclear, and polysome fractions

  • Perform Western blotting for RBM47 in each fraction

  • Compare distribution with target mRNAs detected by RT-qPCR

Research using these approaches has identified that RBM47 predominantly interacts with mRNAs in cytoplasmic compartments, consistent with its role in stabilizing IFNAR1 mRNA through binding to specific regions in the 3'UTR .

What are the methodological considerations for studying RBM47's role in mRNA stability using pulse-chase experiments?

For optimal pulse-chase experiments to study RBM47's effect on mRNA stability:

• Experimental design:

  • Cell models: Use matched pairs of RBM47-overexpressing, knockdown, and control cells

  • For primary cells: Consider using cells from RBM47 heterozygous mice compared to wild-type

• Transcription inhibition approach:

  • Treat cells with actinomycin D (5 μg/ml)

  • Collect RNA at 0, 2, 4, 6, and 8 hours post-treatment

  • Extract total RNA using TRIzol reagent

  • Quantify target mRNAs (e.g., IFNAR1) by RT-qPCR

  • Calculate half-life using exponential decay model

• Metabolic labeling approach:

  • Pulse cells with 4-thiouridine (4sU) for 1 hour

  • Chase with uridine for various time periods

  • Isolate labeled RNA using biotinylation and streptavidin pull-down

  • Analyze by RT-qPCR or RNA-seq

• Controls and validation:

  • Include known stable (e.g., GAPDH) and unstable (e.g., c-Myc) mRNAs as controls

  • Verify RBM47 expression/knockdown by Western blot at each timepoint

  • Confirm binding to target mRNA by RIP-qPCR in parallel samples

Research has shown that RBM47 specifically stabilizes IFNAR1 mRNA but not IFNAR2 or STAT1 mRNAs in IFN-α-stimulated cells, with RT-PCR assays demonstrating reduced IFNAR1 mRNA content in RBM47 knockout cells compared to wild-type cells .

How can researchers establish in vivo models to study RBM47 function and validate antibody specificity?

For developing and validating in vivo models to study RBM47:

• Generation of genetic models:

  • Complete knockout models: Note that RBM47⁻/⁻ homozygous mice may not be viable

  • Heterozygous models: RBM47⁺/⁻ mice show significantly lower RBM47 protein levels in multiple tissues

  • Conditional knockout models: Use tissue-specific Cre recombinase expression

  • Knock-in models: Consider epitope-tagged RBM47 for antibody validation

• Validation of antibody specificity in tissue samples:

  • Compare staining patterns between wild-type and RBM47⁺/⁻ tissues

  • Perform peptide competition assays to confirm specificity

  • Use multiple antibodies targeting different epitopes

  • Correlate protein detection with mRNA expression by in situ hybridization

• Functional assessment in viral challenge models:

  • Challenge mice with various viruses (e.g., VSV, HSV-1)

  • Measure viral loads in blood, lung, spleen, and brain

  • Assess tissue injury through histological analysis

  • Quantify ISG expression in various tissues

• Experimental considerations for tissue analysis:

  Tissue Type	Protein Extraction Method	Special Considerations
  Blood	RBC lysis buffer, followed by RIPA	Monitor inflammatory status
  Lung	Mechanical homogenization in RIPA	Higher protease inhibitor concentration
  Spleen	Gentle homogenization in NP-40 buffer	Preserve immune cell populations
  Brain	Regional dissection, specialized extraction buffer	Lipid interference with extraction

Research has shown that in RBM47 heterozygous mice, both RBM47 and IFNAR1 protein levels were significantly reduced across multiple tissues compared to wild-type mice. These mice exhibited increased viral loads and more severe tissue injury upon viral challenge, with decreased expression of ISGs like IFIT1 and Cig5, despite normal IFN-β production .

How should researchers interpret contradictory findings regarding RBM47's role in cancer versus antiviral immunity?

When interpreting contradictory roles of RBM47:

• Context-dependent function analysis:

  • Cell type specificity: Compare RBM47 function in epithelial cells versus immune cells

  • Pathway interaction: Assess how RBM47 interacts with IFN signaling versus cancer pathways

  • Target mRNA repertoire: Determine if RBM47 binds different mRNAs in different contexts

• Integrated experimental approach:

  • Examine RBM47 expression across cancer and normal tissues with paired antibody and mRNA detection

  • Perform RNA-seq and RIP-seq in both cancer and immune contexts

  • Use gene ontology analysis to categorize RBM47-regulated genes by function

• Mechanistic resolution of paradoxical findings:

  • RBM47 as tumor suppressor: Stabilizes mRNAs of tumor suppressors in breast cancer

  • RBM47 in pancreatic cancer: Promotes cell proliferation and immune evasion

  • RBM47 in immunity: Enhances interferon signaling by stabilizing IFNAR1 mRNA

• Reconciliation framework:

  • Timing: Early versus late roles in disease progression

  • Dosage: Expression level dependent effects

  • Interaction partners: Different protein complexes in different contexts

What statistical approaches are recommended for quantifying RBM47 expression in immunohistochemistry or Western blot studies?

For quantitative analysis of RBM47 expression:

• Western blot quantification:

  • Normalization method: Express RBM47 relative to loading controls (e.g., tubulin, GAPDH)

  • Technical replicates: Perform at least three independent experiments

  • Statistical analysis: Apply paired t-tests for comparing treatments in the same cell line

  • Presentation: Include both representative blots and quantification graphs with error bars

• Immunohistochemistry scoring systems:

  • H-score method: Intensity (0-3) × percentage of positive cells (0-100%), resulting in score of 0-300

  • Allred score: Sum of proportion score (0-5) and intensity score (0-3), resulting in score of 0-8

  • Digital analysis: Use image analysis software with validated algorithms for objective quantification

• Correlation with clinical parameters:

  • Kaplan-Meier survival analysis based on RBM47 expression levels

  • Cox regression for multivariate analysis with other prognostic factors

  • Correlation with immune cell infiltration using Spearman's rank correlation

• Multi-parameter analysis:

  • Combine RBM47 expression with target mRNA levels (e.g., IFNAR1)

  • Correlate with ISG expression or viral load in infection models

  • In cancer studies, correlate with known markers of progression

Research approaches have employed statistical methods such as Student's t-test for comparing RBM47 expression between groups, with error bars representing 95% confidence intervals obtained from multiple PCR reactions . When examining RBM47's relationship to other factors like NK cell infiltration in pancreatic cancer, correlation analysis has been valuable for establishing potential mechanistic relationships .

What methodological approaches can researchers use to investigate RBM47's role in regulating alternative splicing?

To investigate RBM47's splicing regulatory function:

• High-throughput splicing analysis:

  • RNA-seq in RBM47 knockdown/knockout versus control cells

  • Analysis using specialized tools (e.g., rMATS, MISO, VAST-TOOLS)

  • Validation of alternative exon usage by RT-PCR

  • Minigene splicing reporter assays for candidate events

• Direct binding assessment:

  • CLIP-seq to map RBM47 binding sites near alternative exons

  • Motif analysis to identify binding preferences

  • In vitro binding assays with synthetic RNA containing splicing regulatory elements

  • Mutagenesis of predicted binding sites in minigene constructs

• Functional splicing complex analysis:

  • Co-immunoprecipitation with splicing factors

  • Mass spectrometry to identify RBM47 interactors

  • Immunofluorescence co-localization with splicing speckle markers

  • In vitro splicing assays with recombinant RBM47

• Isoform-specific functional analysis:

  • Generate isoform-specific antibodies or tagged constructs

  • Compare full-length versus RRM-only constructs in splicing assays

  • Assess domain requirements for interaction with splicing machinery

Previous research has identified RBM47 as an alternative splicing factor, with studies demonstrating its role in regulating splicing events in various contexts . The three RNA recognition motifs (RRMs) in RBM47 are likely critical for this function, as suggested by functional studies with the 3RRM variant form versus the ΔRRM variant .

How can emerging technologies be integrated with RBM47 antibodies to advance understanding of RNA-protein interaction dynamics?

Integration of emerging technologies with RBM47 antibodies:

• Single-molecule imaging approaches:

  • Single-molecule FISH combined with immunofluorescence

  • Live-cell imaging with fluorescently tagged RBM47

  • Single-molecule tracking to monitor RBM47-mRNA complex formation and dynamics

  • Super-resolution microscopy (STORM, PALM) for nanoscale localization

• Mass spectrometry-based interaction mapping:

  • BioID or APEX2 proximity labeling with RBM47 fusion proteins

  • Quantitative proteomics of RBM47 interactome under different conditions

  • Crosslinking mass spectrometry to identify protein-protein interfaces

  • Targeted proteomics for monitoring RBM47 complex formation

• Spatial transcriptomics integration:

  • Visium spatial gene expression with RBM47 immunofluorescence

  • Multiplex imaging of RBM47 with target mRNAs and cell type markers

  • 3D reconstruction of RBM47-RNA interactions in tissue context

  • Correlation of spatial RBM47 patterns with local ISG expression

• CRISPR-based technologies:

  • CRISPRi for targeted RBM47 silencing in specific cell populations

  • CRISPR activation to enhance RBM47 expression

  • CRISPR RNA tracking combined with RBM47 imaging

  • Domain-specific CRISPR editing to generate functional variants

These approaches can provide insights into how RBM47 dynamically interacts with target mRNAs like IFNAR1 in different cellular compartments, potentially revealing mechanisms underlying its context-dependent roles in cancer and antiviral immunity .

What experimental approaches can researchers use to investigate RBM47's role as a cofactor in APOBEC1-mediated C-to-U RNA editing?

For investigating RBM47's RNA editing cofactor function:

Research has identified RBM47 as an essential cofactor of APOBEC1-mediated C-to-U RNA editing , suggesting it plays a critical role in determining target specificity or enhancing catalytic efficiency of the editing complex.

How should researchers design experiments to distinguish between RBM47's roles in mRNA stability versus other RNA processing functions?

To differentiate between RBM47's diverse RNA processing functions:

• Comprehensive target identification approach:

  • Perform parallel RIP-seq and CLIP-seq experiments

  • Compare binding patterns at 3'UTRs (stability) versus exon-intron boundaries (splicing)

  • Analyze binding at known editing sites versus stability regulatory elements

  • Develop computational pipelines to categorize binding patterns

• Function-specific rescue experiments:

  • Generate domain-specific RBM47 mutants:

    Domain	Expected Function	Mutation Strategy
    RRM1	RNA binding	Point mutations in RNA-contact residues
    RRM2-3	Protein interaction	Surface mutations on non-RNA-binding face
    C-terminal	Recruitment of effectors	Truncation or deletion

  • Test each mutant for rescue of specific functions in RBM47-deficient cells

• Temporal analysis of RNA processing:

  • Nascent RNA sequencing to capture co-transcriptional events

  • Pulse-chase RNA labeling to track newly synthesized transcripts

  • Subcellular fractionation to separate nuclear versus cytoplasmic functions

  • Time-course analysis following RBM47 induction or depletion

• Mechanistic dissection:

  • For stability: Measure half-life of target mRNAs like IFNAR1

  • For splicing: Quantify inclusion/exclusion ratios of alternative exons

  • For editing: Measure C-to-U conversion efficiency at known sites

  • For translation: Analyze polysome association of target mRNAs

Research has demonstrated that RBM47 has multiple functions, including mRNA stabilization (e.g., IFNAR1, IL-10), alternative splicing regulation, and acting as a cofactor for C-to-U RNA editing . The RNA recognition motifs of RBM47 are essential for these functions, as demonstrated by experimental comparisons between full-length RBM47, the 3RRM variant, and the ΔRRM variant .

What methodological considerations are important when investigating RBM47 as a potential therapeutic target?

For translational research targeting RBM47:

• Target validation methodology:

  • Genetic approach: Compare phenotypes of RBM47 knockout/knockdown versus overexpression

  • Pharmacological approach: Develop and test small molecule modulators of RBM47 function

  • Patient-derived models: Analyze RBM47 expression and function in primary cells

  • Correlation with clinical outcomes: Associate RBM47 levels with disease progression

• Context-dependent function assessment:

  • For cancer applications: Evaluate effects in both primary tumors and metastatic settings

  • For antiviral applications: Test across multiple virus families and in different tissue types

  • For inflammatory conditions: Assess impact on both protective and pathological inflammation

  • For combined settings: Study RBM47 modulation in virus-associated cancers

• Delivery and targeting strategies:

  • For enhancement strategies: mRNA delivery, CRISPR activation, or small molecule stabilizers

  • For inhibition strategies: siRNA/ASO approaches, protein degraders, or inhibitory peptides

  • Tissue-specific targeting: Employ tissue-tropic delivery vehicles

  • Temporal control: Use inducible systems for precise timing of modulation

• Safety assessment:

  • Monitor interferon signaling and inflammatory responses

  • Evaluate impact on RNA processing globally

  • Assess compensatory mechanisms in long-term studies

  • Check for unexpected off-target effects on other RNA-binding proteins

Research has revealed potentially contradictory roles for RBM47 in different contexts, with tumor suppressor activity in several cancers but potential promotion of cell proliferation and immune evasion in pancreatic cancer . Additionally, since RBM47 stabilizes IFNAR1, it may contribute to both antiviral protection and inflammation, depending on context . These complex roles suggest that therapeutic targeting would require careful consideration of disease context and potential side effects.

How can researcher-developed RBM47 antibodies be validated for potential diagnostic applications?

For validating RBM47 antibodies in diagnostic applications:

• Analytical validation protocol:

  • Specificity testing against recombinant RBM47 and closely related proteins

  • Sensitivity determination using serial dilutions of recombinant protein

  • Reproducibility assessment across multiple lots and operators

  • Stability testing under various storage and handling conditions

• Clinical sample validation:

  • Test across diverse sample types (tissue sections, blood, liquid biopsies)

  • Compare with gold standard methods (e.g., mass spectrometry, RNA-seq)

  • Establish reference ranges in healthy versus disease populations

  • Perform blinded testing on well-characterized clinical cohorts

• Diagnostic performance metrics:

  • Determine sensitivity, specificity, PPV, and NPV for specific clinical applications

  • Generate ROC curves and calculate area under curve (AUC)

  • Compare performance against existing diagnostic markers

  • Assess correlation with disease severity or prognosis

• Implementation considerations:

  • Standardize protocols for sample collection and processing

  • Establish quantitative cutoff values for positive/negative results

  • Develop quality control materials and procedures

  • Design appropriate confirmation testing strategies

Research has shown variable RBM47 expression across different tissues and disease states, with reduced expression in certain cancers acting as a tumor suppressor , while showing increased expression in others like pancreatic cancer . Additionally, RBM47 expression is upregulated by interferon stimulation , suggesting potential utility as a biomarker for viral infections or interferon treatment response.