STRING: 9615.ENSCAFP00000023945
CSF3 antibodies vary in their optimal applications based on host species, clonality, and production methods. Based on current research protocols, the following application guidelines should be considered:
| Antibody Type | Optimal Applications | Recommended Dilutions | Validated Species Reactivity |
|---|---|---|---|
| Polyclonal (Rabbit) | WB, ELISA, IHC-P | WB: 1:500-1:1000, IHC-P: 1:50-1:200 | Human, Mouse, Rat |
| Monoclonal [CSF3/900] | Flow Cytometry, IF, IHC-P | Flow: 1-2 μg/million cells, IF: 1-2 μg/ml, IHC-P: 1-2 μg/ml | Human, Macaque Monkey |
For CSF3 neutralization experiments, antibody concentrations of 100 μg/ml have been validated to completely neutralize high concentrations of CSF3 without cytotoxicity, as measured by lactate dehydrogenase analysis (showing <1% cytotoxicity compared to Triton X-treated positive controls) . When designing experiments, it's critical to confirm antibody specificity through appropriate controls, including isotype controls (mouse IgG for monoclonal and rabbit IgG for polyclonal antibodies).
Validation should employ multiple complementary approaches:
Molecular weight verification: Human CSF3 is a 207 amino acid precursor containing a 29 amino acid signal peptide that is proteolytically cleaved to form a 178 amino acid mature protein . Confirm the molecular weight matches expected size by Western blot.
Positive and negative control samples: Include known positive samples (HL-60 cell line, 293T cells, and mouse liver tissue have been validated) and negative controls.
Knockdown/overexpression validation: Compare antibody signals in wild-type versus CSF3-silenced cells. Research has validated this approach using shCSF3 lentiviral constructs in HCT 116 and RKO cell lines, where both qRT-PCR and western blot confirmed decreases in CSF3 mRNA and protein levels .
Cross-reactivity testing: Examine antibody performance across multiple species when conducting comparative studies. The rabbit polyclonal antibody CAB6178 has demonstrated reactivity with human, mouse, and rat samples, while also showing predicted reactivity in cow, sheep, and pig systems .
CSF3 neutralizing antibodies serve as powerful tools for dissecting the specific contribution of CSF3 in complex inflammatory processes. Methodological approach:
Dose optimization: Start with a titration series (10-100 μg/ml) to identify the minimum concentration needed for effective neutralization. Research has shown that 10 μg/ml of CSF3 neutralizing antibody neutralizes 50% of the bioactivity of 0.125 ng/ml of recombinant human CSF3 .
Efficacy verification: Measure downstream neutrophil activation markers or proliferation assays to confirm functional neutralization.
Control implementation: Include matched isotype controls (mouse IgG for CSF3 neutralizing antibody) at equivalent concentrations.
Cytotoxicity assessment: Always perform parallel cytotoxicity assays (LDH release, Trypan blue exclusion) to ensure observed effects are not due to cell death. Research has confirmed that at 100 μg/ml, CSF3 neutralizing antibody shows no signs of cell death or toxicity .
Combination studies: In models of neutrophilic airway inflammation, researchers have demonstrated that anti-CSF3 neutralizing antibody decreases airway neutrophilia and neutrophil-promoting gene expression, rendering dexamethasone sensitivity in treated mice . This approach can be adapted to investigate other inflammatory conditions.
CSF3 overexpression has been associated with poor prognosis in colorectal cancer. Researchers should consider these methodological approaches:
Tissue microarray (TMA) analysis: Utilize CSF3 antibodies for IHC on patient-derived TMAs to correlate expression with clinical outcomes. A CRC tissue microarray including 91 CRC samples and 104 para-carcinoma tissues revealed that 57.1% of tumor tissues had high CSF3 expression compared to only 10.6% of para-carcinoma tissues (p<0.001) .
Prognostic correlation: Link CSF3 expression levels with clinical parameters through comprehensive statistical analysis. Research has shown significant correlations between high CSF3 expression and advanced tumor stage (p=0.003), lymph node invasion (p=0.014), and patient age above 60 years (p=0.014) .
Functional validation in cancer models: Implement CSF3 knockdown studies through shRNA approaches:
Transfect cancer cells (e.g., HCT 116, RKO) with validated shCSF3 constructs
Confirm knockdown efficacy via qRT-PCR and Western blot
Assess functional consequences through proliferation assays (CCK-8), colony formation assays, apoptosis measurement (flow cytometry), and migration analysis (wound-healing assay)
In vivo validation: Establish xenograft models using CSF3-silenced cancer cells to evaluate tumor growth dynamics, followed by IHC analysis of harvested tumors for CSF3 and proliferation markers like Ki67 .
CSF3 has been implicated in activating the NF-κB pathway in colorectal cancer. A comprehensive methodological approach includes:
Pathway component analysis: Assess phosphorylation status of key NF-κB pathway components (particularly p65) in CSF3-manipulated cells using phospho-specific antibodies.
Ubiquitination assays: Implement immunoprecipitation techniques to examine CSF3's effect on IκBα ubiquitination:
Functional rescue experiments: Combine CSF3 silencing with constitutively active NF-κB components to assess pathway dependencies.
Co-expression analysis: Utilize bioinformatics tools like Coexpedia to identify co-expressed genes and perform KEGG enrichment analyses to map related pathways .
Recent studies have identified CSF3 as a potential drug target for COVID-19 treatment. Researchers can implement these approaches:
Differential expression analysis: Compare CSF3 expression in infected versus uninfected respiratory cells. Analysis of datasets GSE150819 and GSE147507 identified CSF3 as a consistently upregulated gene across human bronchial organoids, A549, Calu3, and NHBE cell lines infected with SARS-CoV-2 .
Gene set enrichment analysis (GSEA): Identify pathways associated with CSF3 expression in infection models. GSEA analysis revealed that the top four positive regulatory pathways of CSF3 were proteasome, Parkinson's disease, oxidative phosphorylation, and Graft vs. host disease; while the top four negative regulatory pathways were mismatch repair, DNA replication, homologous recombination, and inositol phosphate metabolism .
Drug screening methodologies:
Antibody-based target validation: Use CSF3 antibodies to confirm drug-target engagement through competitive binding assays.
Research has demonstrated synergistic induction of CSF3 expression by IL-17A and glucocorticoids in neutrophilic airway diseases. Key methodological considerations include:
Experimental design for synergy studies:
In vivo validation models:
Analysis of steroid sensitivity:
Successful IHC staining for CSF3 requires careful optimization:
Antigen retrieval optimization: Test both heat-induced epitope retrieval (HIER) methods with citrate buffer (pH 6.0) and EDTA buffer (pH 9.0) to determine optimal conditions for your specific tissue type.
Antibody concentration titration: For polyclonal antibodies, test a range from 1:50 to 1:200; for monoclonal antibodies, optimize between 1-2 μg/ml .
Signal amplification considerations: For tissues with low CSF3 expression, implement tyramide signal amplification systems to enhance detection sensitivity.
Background reduction strategies:
Implement proper blocking with 1-5% BSA or 5-10% normal serum from the same species as the secondary antibody
Include 0.1-0.3% Triton X-100 for adequate permeabilization
For highly vascularized tissues, pre-treat sections with hydrogen peroxide to block endogenous peroxidases
Validation through multiple detection methods: Confirm IHC findings with complementary techniques such as RNAscope or in situ hybridization, particularly when studying tissues with expected low expression levels.
Western blot detection of CSF3 presents several technical challenges that require specific optimization:
Sample preparation considerations:
For secreted CSF3, concentrate cell culture supernatants using centrifugal filter units (10 kDa cut-off)
For cellular CSF3, use RIPA buffer with protease inhibitor cocktails
Optimize protein loading (typically 20-50 μg of total protein)
Antibody selection and dilution:
Membrane blocking optimization:
Test both 5% non-fat dry milk and 5% BSA in TBST to determine which provides optimal signal-to-noise ratio
Incubate primary antibody at 4°C overnight for maximum sensitivity
Detection system selection:
For low abundance CSF3, implement high-sensitivity ECL substrates or fluorescent secondary antibodies
Consider using HRP-polymer detection systems for enhanced signal
Controls implementation:
By addressing these technical considerations, researchers can optimize Western blot protocols for consistent and specific detection of CSF3 protein.
Current research suggests several promising directions:
Therapeutic antibody development:
Engineer CSF3-targeting antibodies with optimized affinity and specificity
Develop antibody-drug conjugates targeting CSF3-expressing tumor cells
Investigate combination therapies with existing immune checkpoint inhibitors
Biomarker implementation:
Establish standardized IHC protocols for CSF3 detection in tumor biopsies
Develop companion diagnostics to identify patients likely to respond to CSF3-targeted therapies
Create multiplex assays combining CSF3 with other cancer-associated markers
Patient stratification strategies:
Correlate CSF3 expression with treatment response in clinical trials
Implement CSF3 detection in liquid biopsies for monitoring treatment efficacy
Develop predictive algorithms incorporating CSF3 expression for personalized medicine approaches
The development of these applications requires rigorous validation of antibody specificity, reproducibility of detection methods, and correlation with clinical outcomes.
As single-cell technologies advance, new applications for CSF3 antibodies are emerging:
Single-cell protein analysis:
Implement CSF3 antibodies in mass cytometry (CyTOF) panels
Develop optimized protocols for single-cell Western blotting
Incorporate CSF3 detection in spatial transcriptomics workflows
Multi-omics integration:
Correlate single-cell CSF3 protein expression with transcriptomic profiles
Implement computational approaches to integrate proteomic and genomic data
Develop new analytical pipelines specific for cytokine-producing cells
Spatial analysis methodologies:
Optimize CSF3 antibodies for multiplexed immunofluorescence imaging
Implement clearing techniques for whole-tissue CSF3 visualization
Develop quantitative spatial analysis algorithms for CSF3-expressing cells