CRLF1 Antibody

What applications are CRLF1 antibodies suitable for in research settings?

CRLF1 antibodies are validated for several research applications with varying specificity and sensitivity profiles. The primary applications include:

• Western Blotting (WB): Most commercially available CRLF1 antibodies are optimized for Western blot applications at dilutions ranging from 1:1000 to 1:3000. These antibodies typically detect a band around 46 kDa, corresponding to the predicted molecular weight of CRLF1 protein. For optimal results, samples should be prepared in reducing conditions with SDS-PAGE (typically 10% gels) followed by transfer to PVDF or nitrocellulose membranes .

• Immunohistochemistry on Paraffin-embedded tissues (IHC-P): Selected antibodies like ab211438 have been validated for detecting CRLF1 in formalin-fixed paraffin-embedded tissue sections. This application requires appropriate antigen retrieval methods and optimized antibody concentrations .

• ELISA: Some CRLF1 antibodies have been specifically tested for ELISA applications, allowing for quantitative measurement of CRLF1 levels in biological samples .

When selecting an antibody for a specific application, researchers should review validation data provided by manufacturers and consider previously published studies that have successfully employed these antibodies.

Which sample types can be reliably tested with CRLF1 antibodies?

CRLF1 antibodies have been validated against several sample types, with human samples showing the highest reactivity:

• Human samples: All reviewed antibodies demonstrate confirmed reactivity with human CRLF1. Cell lysates from human cell lines such as HepG2 have been successfully used in Western blot applications .

• Tissue expression profiles: CRLF1 expression has been detected in multiple human tissues including muscle, chondrocytes, fibroblasts, and brain tissue. This information is important when selecting positive controls for experiments .

• Cancer cell lines: CRLF1 antibodies have been successfully used with ovarian cancer cell lines (A2780, CaoV3, SKOV3) and papillary thyroid carcinoma cells in research settings .

When planning experiments with new sample types, preliminary validation with appropriate positive and negative controls is recommended to confirm antibody specificity.

How should experiments be designed to investigate CRLF1's role in the JAK-STAT pathway?

When investigating CRLF1's role in JAK-STAT signaling, consider the following experimental design approach:

• Baseline assessment: Establish baseline expression levels of CRLF1 and key JAK-STAT components (JAK1/2, STAT1/3/5) using Western blot analysis with validated antibodies for each protein.

• Functional manipulation: Design experiments that include:

  • siRNA or shRNA-mediated CRLF1 knockdown

  • CRISPR-Cas9 genetic knockout of CRLF1

  • Overexpression of wild-type CRLF1 using appropriate expression vectors

• Downstream signaling analysis: Following CRLF1 manipulation, assess:

  • Phosphorylation status of STAT proteins (particularly pSTAT3)

  • Nuclear translocation of STAT proteins (using cellular fractionation or immunofluorescence)

  • Transcriptional activation of known STAT target genes (using qRT-PCR)

• Receptor complex analysis: Since CRLF1 forms a heterodimer with CLCF1 that interacts with the CNTFR complex, co-immunoprecipitation experiments should be conducted to analyze:

  • CRLF1-CLCF1 heterodimer formation

  • Interaction with receptor components (CNTFR, IL-6ST/gp130, LIFR)

• Functional readouts: Measure biological responses associated with JAK-STAT activation, such as:

  • Cell proliferation assays

  • Apoptosis assessment

  • Cell differentiation markers

This comprehensive approach allows for detailed characterization of CRLF1's specific contributions to JAK-STAT signaling .

What controls are essential when validating CRLF1 antibody specificity?

Rigorous validation of CRLF1 antibody specificity requires a systematic approach with multiple controls:

• Positive expression controls:

  • Cell lines with confirmed high CRLF1 expression (e.g., HepG2)

  • Recombinant CRLF1 protein for Western blot positive control

  • Tissues with known CRLF1 expression (based on RNA-seq or proteomics data)

• Negative expression controls:

  • Cell lines with minimal CRLF1 expression

  • CRLF1 knockout cell lines (CRISPR-Cas9 generated)

  • siRNA/shRNA knockdown samples showing decreased signal compared to non-targeting controls

• Antibody controls:

  • Isotype controls matching the CRLF1 antibody class (e.g., rabbit IgG)

  • Secondary antibody-only controls to identify non-specific binding

  • Pre-absorption with immunizing peptide to confirm epitope specificity

• Cross-reactivity assessment:

  • Testing against related cytokine receptor family members

  • Expression vectors containing CRLF1 with epitope tags to confirm co-localization of signals

• Multiple antibody validation:

  • Compare results using antibodies targeting different CRLF1 epitopes

  • Correlation of protein detection with mRNA expression levels using qPCR

For research involving patient samples or critical phenotype assessments, antibody validation should be documented with quantitative metrics of specificity and sensitivity .

How can CRLF1 antibodies be used to investigate CRLF1's role in cancer chemoresistance?

Recent research has identified CRLF1 as a mediator of chemoresistance, particularly in ovarian cancer. To investigate this phenomenon, researchers can implement the following methodological approach:

• Expression correlation analysis:

  • Use CRLF1 antibodies for immunohistochemistry on patient-derived tumor samples

  • Compare CRLF1 expression levels between chemosensitive and chemoresistant tumors

  • Correlate expression with patient survival and treatment response metrics

• Mechanistic studies in cell models:

  • Establish cisplatin-resistant and sensitive cancer cell lines

  • Analyze CRLF1 protein levels by Western blot using validated antibodies

  • Perform gain/loss-of-function experiments by modulating CRLF1 expression

  • Assess changes in chemosensitivity using cell viability assays (MTT, Annexin V)

• Pathway analysis:

  • Investigate the AKT/mTORC2 pathway components following CRLF1 manipulation

  • Use co-immunoprecipitation with CRLF1 antibodies to detect protein interactions with:

    • AKT isoforms

    • SIN1 (an essential mTORC2 component)

    • Other signaling mediators

  • Assess phosphorylation status of key proteins in the pathway

• Pyroptosis assessment:

  • Measure pyroptosis markers (GSDME cleavage, LDH release, IL-1β secretion)

  • Use immunofluorescence with CRLF1 antibodies to examine cellular localization

  • Assess CRLF1's impact on the ASK1/JNK/Caspase3/GSDME cascade

• In vivo validation:

  • Develop xenograft models with CRLF1-modulated cancer cells

  • Administer chemotherapy agents and monitor tumor response

  • Use CRLF1 antibodies for post-mortem tissue analysis to confirm mechanism

This methodological framework can reveal how CRLF1 confers chemoresistance through its newly discovered role as an AKT/mTORC2 binding protein that inhibits pyroptosis .

What techniques can be used to investigate both secreted and intracellular functions of CRLF1?

CRLF1 has unique dual functionality as both a secreted cytokine when complexed with CLCF1 and as an intracellular signaling molecule. To comprehensively study both roles, researchers should employ these methodological approaches:

• Secreted CRLF1 analysis:

  • ELISA: Use sandwich ELISA with capture and detection antibodies against different CRLF1 epitopes to quantify secreted protein in culture supernatants or biological fluids

  • Immunoprecipitation: Concentrate CRLF1 from conditioned media using specific antibodies for downstream analysis

  • Western blot: Analyze TCA-precipitated culture media for secreted CRLF1

  • Functional assays: Add recombinant CRLF1 or CRLF1-containing conditioned media to responder cells and measure CNTFR-associated signaling outputs

• Intracellular CRLF1 investigation:

  • Subcellular fractionation: Separate cellular compartments and use Western blotting to detect CRLF1 localization

  • Immunofluorescence microscopy: Use CRLF1 antibodies optimized for immunofluorescence to visualize protein distribution

  • Proximity ligation assay (PLA): Detect interaction between CRLF1 and intracellular binding partners

  • FRET/BRET analysis: For studying dynamic interactions in living cells

• Differential functional assessment:

  • Signal sequence mutants: Create CRLF1 variants lacking the signal peptide to prevent secretion while maintaining intracellular expression

  • Pathway-specific inhibitors: Use secretion inhibitors (e.g., Brefeldin A) to differentiate between intracellular and extracellular functions

  • Cell-impermeable CRLF1 neutralizing antibodies: Block extracellular activities without affecting intracellular functions

• Domain-specific function analysis:

  • Create domain deletion mutants targeting Ig-like or FNIII domains

  • Assess both secretion efficiency and binding capabilities to interacting partners

  • Perform rescue experiments with mutant constructs in CRLF1-depleted cells

Evidence suggests that CRLF1's intracellular functions may be particularly important in processes like chemoresistance, where adding extracellular CRLF1 protein does not recapitulate the effects of endogenous expression .

What are common issues when using CRLF1 antibodies, and how can they be resolved?

Researchers often encounter several challenges when working with CRLF1 antibodies. Here are methodological solutions to common problems:

• Low or no signal in Western blots:

  • Problem: CRLF1 has moderate expression in many tissues.

  • Solution: Increase protein loading (50-80 μg total protein); use highly sensitive ECL substrates; optimize antibody concentration through titration (try 1:1000 to 1:5000); ensure sample is not degraded by adding protease inhibitors during lysis.

  • Technical note: HepG2 lysates have been validated as positive controls for CRLF1 detection at concentrations of 30 μg per lane .

• Multiple bands or non-specific binding:

  • Problem: Some antibodies may detect non-specific proteins.

  • Solution: Increase blocking time (2-3 hours with 5% BSA or milk); perform more stringent washing steps; reduce primary antibody concentration; use monoclonal antibodies for higher specificity; verify with CRLF1 knockdown controls.

  • Technical note: The predicted band size for CRLF1 is 46 kDa, but post-translational modifications may affect migration .

• Inconsistent IHC staining:

  • Problem: Variable results with tissue samples.

  • Solution: Optimize antigen retrieval methods (test both citrate and EDTA-based buffers at different pH values); test multiple antibody dilutions; increase incubation time (overnight at 4°C); use polymer detection systems for signal amplification.

  • Technical note: Comparison with mRNA expression (by ISH or qPCR) can help validate staining patterns.

• Antibody performance differs across species:

  • Problem: Most CRLF1 antibodies are optimized for human samples.

  • Solution: When working with other species, perform alignment analysis of the immunogen sequence; calculate homology percentage; verify with species-specific positive controls; consider custom antibody development for highly divergent regions.

  • Technical note: Antibodies raised against human CRLF1 amino acids 100-400 have shown the most consistent cross-species reactivity .

• Detecting CRLF1-CLCF1 heterodimers:

  • Problem: Standard conditions may dissociate the heterodimer.

  • Solution: Use non-reducing and mild lysis conditions; perform native PAGE; consider chemical crosslinking before analysis; use co-immunoprecipitation with antibodies against both proteins.

These methodological approaches can significantly improve experimental outcomes when working with CRLF1 antibodies.

How can researchers distinguish between specific CRLF1 signal and background in complex tissue samples?

When analyzing CRLF1 expression in complex tissue samples such as tumors or brain tissue, distinguishing specific signal from background is critical. Implement these methodological approaches:

• Comprehensive control strategy:

  • Adjacent normal tissue controls: Compare expression patterns with matched normal tissue

  • Antibody validation controls: Include sections stained with isotype control antibodies

  • Absorption controls: Pre-incubate antibody with immunizing peptide to demonstrate specificity

  • Genetic controls: When possible, include tissues from CRLF1 knockout models or CRLF1-depleted xenografts

• Multi-method confirmation:

  • Complementary detection methods: Validate IHC findings with in situ hybridization for CRLF1 mRNA

  • Quantitative correlation: Compare protein detection by IHC with mRNA levels from matched samples by qPCR

  • Western blot validation: When possible, prepare protein extracts from the same tissues for Western blot analysis

• Advanced imaging and quantification approaches:

  • Spectral unmixing: For tissues with high autofluorescence, use spectral imaging to separate specific signal

  • Digital pathology: Apply computational image analysis to quantify staining intensity and patterns

  • Multiplexed immunofluorescence: Co-stain for CRLF1 along with cell type-specific markers to assess expression patterns

• Tissue-specific optimization:

  • Fixation optimization: Test multiple fixation protocols to minimize background while preserving antigenicity

  • Blocking enhancements: For tissues with high background, use additional blocking steps (avidin/biotin block for endogenous biotin; hydrogen peroxide for endogenous peroxidases)

  • Detection system selection: Choose detection systems optimized for sensitivity/specificity balance

• Quantitative assessment framework:

  • Develop a scoring system incorporating intensity and distribution metrics

  • Use positive control tissues with known CRLF1 expression as calibration standards

  • Implement blind scoring by multiple observers to ensure reproducibility

These approaches collectively enhance the reliability of CRLF1 detection in complex tissue samples and minimize misinterpretation due to background or non-specific staining .

How can researchers effectively study CRLF1's interaction with the AKT/mTORC2 pathway?

Recent research has revealed CRLF1's novel role in enhancing the interaction between AKT and SIN1 (an essential mTORC2 component). To effectively study this interaction and its downstream effects, researchers should implement this methodological framework:

• Protein-protein interaction analysis:

  • Co-immunoprecipitation: Use CRLF1 antibodies to pull down protein complexes, followed by Western blot detection of AKT and SIN1

  • Reciprocal co-IP: Perform immunoprecipitation with AKT or SIN1 antibodies and detect CRLF1

  • Proximity ligation assay (PLA): Visualize and quantify CRLF1-AKT and CRLF1-SIN1 interactions in situ

  • FRET/BRET analysis: For studying dynamic interactions in living cells

• Domain mapping and mutational analysis:

  • Generate truncated CRLF1 constructs to identify domains required for AKT/SIN1 binding

  • Create point mutations in candidate interaction regions

  • Develop binding-defective CRLF1 variants as experimental tools

  • Test mutant constructs using pull-down assays and functional readouts

• Signaling pathway assessment:

  • Monitor AKT phosphorylation at Ser473 (mTORC2-dependent site) and Thr308

  • Assess activation of downstream targets (e.g., FOXO proteins, GSK3β)

  • Examine mTORC2-specific functions versus mTORC1 activities

  • Use specific inhibitors (MK-2206 for AKT, mTOR kinase inhibitors) as controls

• Functional consequence analysis:

  • Pyroptosis assays: Measure cell death markers (LDH release, propidium iodide uptake)

  • ASK1/JNK/Caspase3/GSDME cascade: Monitor activation state of each component

  • Chemosensitivity testing: Assess how modulating the CRLF1-AKT-mTORC2 axis affects response to chemotherapeutics

• Experimental validation table:

This comprehensive approach enables detailed characterization of the CRLF1-AKT-mTORC2 signaling axis and its role in processes such as chemoresistance and pyroptosis inhibition .

What methods should be used to study CRLF1's role in neurological development and diseases?

CRLF1 has been implicated in neurological development and diseases, particularly through mutations associated with Crisponi syndrome and cold-induced sweating syndrome. To effectively study these functions, researchers should employ these methodological approaches:

• Expression analysis in neural tissues:

  • Developmental profiling: Use CRLF1 antibodies for Western blot and IHC to track expression across developmental stages in neural tissues

  • Cell-type specificity: Employ double-labeling techniques with neural cell markers (neurons, astrocytes, oligodendrocytes) to identify CRLF1-expressing populations

  • Single-cell analysis: Correlate protein detection with scRNA-seq data to identify specific neural subtypes expressing CRLF1

• Receptor complex analysis:

  • CRLF1-CLCF1 heterodimer formation: Use co-immunoprecipitation and Western blotting to detect complex formation

  • Receptor binding studies: Analyze interaction with CNTFR complex components (CNTFR, IL-6ST/gp130, LIFR)

  • Competition assays: Assess competition between CRLF1-CLCF1 and CNTF for receptor binding

• Functional analysis in neural models:

  • Primary neuron cultures: Test effects of CRLF1 manipulation on neurite outgrowth, synaptogenesis, and survival

  • Neural progenitor differentiation: Examine impact on fate specification and maturation

  • 3D organoid models: Assess neurodevelopmental processes in more complex systems

• Disease-associated mutation analysis:

  • Patient-derived cells: Use fibroblasts from individuals with CRLF1 mutations to analyze expression levels and signaling

  • CRISPR-engineered mutations: Introduce disease-associated mutations into cellular models

  • Rescue experiments: Test if wild-type CRLF1 can rescue phenotypes in mutant cells

• JAK/STAT pathway assessment in neural context:

  • Monitor STAT3 phosphorylation and nuclear translocation in neural cells

  • Assess expression of STAT-responsive genes following CRLF1-CLCF1 treatment

  • Use JAK inhibitors to confirm pathway specificity

• Autonomic nervous system function:

  • Develop assays to measure sympathetic nervous system responses

  • Investigate thermoregulation mechanisms potentially impacted by CRLF1 dysfunction

  • Study sweating responses in model systems with CRLF1 manipulation

These approaches provide a comprehensive framework for investigating CRLF1's neurological functions and the pathogenic mechanisms underlying CRLF1-associated neurological disorders .

How can CRLF1 antibodies be used to study its role in cancer progression and metastasis?

CRLF1 has been implicated in promoting malignant phenotypes in several cancers, including papillary thyroid carcinoma and ovarian cancer. Researchers interested in studying CRLF1's oncogenic properties should implement these methodological approaches:

• Expression profiling in cancer progression:

  • Tissue microarray analysis: Use validated CRLF1 antibodies for IHC on cancer progression tissue arrays

  • Correlation with clinical parameters: Analyze relationship between CRLF1 expression and:

    • Tumor stage/grade

    • Metastatic status

    • Patient survival

    • Treatment response

  • Cancer subtype analysis: Compare expression across molecular subtypes

• Functional characterization in cancer models:

  • Migration and invasion assays: After CRLF1 modulation (knockdown/overexpression), assess:

    • Wound healing/scratch assays

    • Transwell migration

    • Matrigel invasion

    • 3D spheroid invasion models

  • Proliferation assessment: Measure cell growth, colony formation, and cell cycle distribution

  • EMT marker analysis: Examine epithelial and mesenchymal markers by Western blot and immunofluorescence

• Signaling pathway investigation:

  • ERK1/2 and AKT activation: Monitor phosphorylation status following CRLF1 manipulation

  • Pathway inhibitor studies: Use MEK inhibitors (U0126) or AKT inhibitors (MK-2206) to determine pathway dependency

  • Transcriptional profiling: Identify downstream gene expression changes by RNA-seq

• In vivo metastasis models:

  • Xenograft studies: Compare tumor growth and metastatic spread with CRLF1-modulated cancer cells

  • Experimental metastasis assays: Assess colonization potential after tail vein injection

  • Patient-derived xenografts: Correlate CRLF1 expression with metastatic potential

• Quantitative experimental data table:

These methodological approaches enable comprehensive characterization of CRLF1's oncogenic functions and potential as a therapeutic target in cancer .

What techniques should be employed to study CRLF1 mutations in genetic disorders?

CRLF1 mutations have been identified in rare genetic disorders including Crisponi syndrome and cold-induced sweating syndrome (CISS). To effectively study these mutations and their functional consequences, researchers should employ these methodological approaches:

• Mutation identification and characterization:

  • Genomic sequencing: Use targeted or whole-exome sequencing to identify CRLF1 mutations

  • Structural prediction: Employ computational tools to predict effects on protein structure

  • Domain mapping: Analyze mutation distribution across functional domains (Ig-like, FNIII domains)

  • Mutation database development: Catalog mutations with associated phenotypes

• Expression and stability analysis:

  • mRNA quantification: Use real-time qPCR to assess transcript levels in patient-derived cells

  • Nonsense-mediated decay assessment: Compare mutant transcripts with and without NMD inhibitors

  • Protein expression: Use Western blot with validated antibodies to detect mutant protein levels

  • Protein half-life studies: Perform cycloheximide chase assays to assess stability

• Functional impact assessment:

  • Secretion assays: Measure secretion efficiency of wild-type versus mutant CRLF1

  • CLCF1 heterodimer formation: Assess ability to form functional complexes with CLCF1

  • Receptor binding studies: Test binding affinity to CNTFR complex components

  • Signaling activation: Measure JAK/STAT pathway activation in response to mutant CRLF1

• Disease-relevant functional assays:

  • Sympathetic neuron development: Assess impact on neural development and survival

  • Thermoregulation models: Develop assays to measure temperature-sensitive responses

  • Rescue experiments: Test if wild-type CRLF1 can restore function in patient-derived cells

• Genotype-phenotype correlation table:

These methodological approaches provide a comprehensive framework for investigating CRLF1 mutations and understanding their pathogenic mechanisms in genetic disorders .

What are the optimal conditions for using CRLF1 antibodies in co-immunoprecipitation experiments?

Co-immunoprecipitation (co-IP) is crucial for studying CRLF1's interactions with binding partners such as CLCF1, AKT, and SIN1. To optimize co-IP experiments with CRLF1 antibodies, follow these methodological guidelines:

• Lysis buffer optimization:

  • Recommended composition: 50 mM Tris-HCl pH 7.4, 150 mM NaCl, 1% NP-40 or 0.5% Triton X-100, 1 mM EDTA

  • Critical additives:

    • Protease inhibitor cocktail (complete, EDTA-free)

    • Phosphatase inhibitors (for studying phosphorylation-dependent interactions)

    • 5-10% glycerol to stabilize protein complexes

  • Avoid harsh detergents (SDS, deoxycholate) that may disrupt protein-protein interactions

• Antibody selection and application:

  • Validated antibodies: Use antibodies specifically validated for immunoprecipitation

  • Optimal concentration: Typically 2-5 μg antibody per 500 μg total protein

  • Pre-clearing step: Incubate lysates with protein A/G beads before adding antibody to reduce non-specific binding

  • Controls: Include isotype control antibody and input sample (5-10% of lysate used for IP)

• CRLF1-specific considerations:

  • Heterodimer preservation: When studying CRLF1-CLCF1 complexes, use gentle lysis conditions and minimize freeze-thaw cycles

  • Crosslinking option: Consider mild crosslinking (0.5-1% formaldehyde for 10 minutes) to stabilize transient interactions

  • Sequential IP: For complex multi-protein assemblies, consider sequential IP with antibodies against different components

• Technical protocol optimization:

  • Incubation time: 4-16 hours at 4°C with gentle rotation

  • Washing stringency: Balance between removing non-specific binding while preserving specific interactions (typically 4-5 washes)

  • Elution method: Either low pH (glycine buffer pH 2.5) followed by neutralization, or direct elution in SDS sample buffer

• Downstream detection optimization:

  • Western blot detection: Use highly sensitive ECL substrates for detecting low-abundance interacting proteins

  • Mass spectrometry analysis: For unbiased identification of novel binding partners

  • Validation approach: Confirm interactions with reciprocal co-IP and orthogonal methods (PLA, FRET)

These optimized conditions will significantly enhance the specificity and sensitivity of co-IP experiments for studying CRLF1 protein complexes and interactions .

How can researchers effectively use CRLF1 antibodies in multiplexed immunofluorescence studies?

Multiplexed immunofluorescence allows simultaneous detection of CRLF1 alongside other proteins, providing insights into co-expression patterns, cellular localization, and pathway activation. For optimal results with CRLF1 antibodies in multiplexed studies, implement these methodological strategies:

• Panel design considerations:

  • Antibody species selection: Choose primary antibodies from different host species (e.g., rabbit anti-CRLF1 paired with mouse, rat, or goat antibodies against other targets)

  • Fluorophore selection: Design panel with spectrally distinct fluorophores to minimize bleed-through

  • CRLF1 pathway markers: Include antibodies against interacting partners (CLCF1, CNTFR) or downstream effectors (phospho-STAT3, phospho-AKT)

  • Cellular context markers: Add cell type-specific markers to identify CRLF1-expressing populations

• Technical protocol optimization:

  • Sequential staining approach: For same-species antibodies, use sequential staining with blocking steps between rounds

  • Tyramide signal amplification: Consider TSA for low-abundance targets, including CRLF1 in some tissue contexts

  • Antibody validation: Test each antibody individually before multiplexing to confirm specific staining

  • Fixation optimization: Test multiple fixation methods to preserve antigenicity of all targets

• Controls and validation:

  • Single-color controls: Run single-color stains for spectral unmixing and bleed-through assessment

  • Biological validation: Compare staining patterns with mRNA expression (ISH or single-cell RNA-seq)

  • Blocking peptide controls: Use blocking peptides for CRLF1 to verify specificity

  • Quantitative validation: Compare IF quantification with Western blot or ELISA measurements

• Advanced multiplexing approaches:

  • Cyclic immunofluorescence: For higher-parameter analysis (>5 markers), consider cyclic methods with antibody stripping

  • Mass cytometry imaging: For very high-parameter analysis, consider metal-tagged antibodies and imaging mass cytometry

  • Automated image analysis: Implement machine learning algorithms for cellular segmentation and phenotyping

• Application-specific considerations table:

These methodological approaches enable sophisticated analysis of CRLF1 in complex tissue contexts and in relation to its signaling partners and downstream effectors .

How should researchers interpret discrepancies between CRLF1 mRNA and protein expression levels?

Researchers frequently encounter discrepancies between CRLF1 mRNA and protein levels, which can complicate data interpretation. To address these challenges, implement these methodological approaches:

• Systematic validation strategy:

  • Parallel measurements: Simultaneously assess mRNA (by qPCR) and protein (by Western blot) from the same samples

  • Multiple detection methods: Validate protein expression using different antibodies targeting distinct epitopes

  • Quantitative correlation analysis: Calculate correlation coefficients between mRNA and protein levels across sample sets

• Mechanistic investigation of discrepancies:

  • Post-transcriptional regulation:

    • Assess mRNA stability using actinomycin D chase experiments

    • Examine miRNA targeting of CRLF1 through luciferase reporter assays

    • Analyze polysome profiles to assess translation efficiency

  • Post-translational regulation:

    • Measure protein stability with cycloheximide chase assays

    • Investigate ubiquitination status through immunoprecipitation

    • Assess secretion efficiency by comparing intracellular and extracellular levels

• Context-dependent factors:

  • Disease state influence: Compare normal vs. pathological samples (e.g., cancer tissues often show altered protein stability)

  • Tissue-specific differences: Systematic comparison across tissue types to identify patterns

  • Cell stress response: Examine effects of cellular stress (hypoxia, nutrient deprivation) on mRNA-protein correlation

• Technical considerations:

  • Extraction method bias: Optimize protein extraction to ensure complete recovery of membrane-associated and secreted CRLF1

  • Antibody specificity: Validate antibodies against recombinant CRLF1 and CRLF1-depleted samples

  • RNA quality assessment: Ensure RNA integrity for accurate mRNA quantification

• Analytical framework:

  • Time-course analysis: Examine temporal relationships between mRNA and protein expression changes

  • Mathematical modeling: Develop models incorporating synthesis and degradation rates

  • Multi-omics integration: Incorporate proteomic, transcriptomic, and epigenomic data for comprehensive analysis

For example, in Crisponi syndrome patients with CRLF1 mutations, significantly decreased mRNA levels were observed in fibroblasts, suggesting mutation-mediated decay of abnormal transcripts. This mechanistic insight helps explain the discrepancy between expected and observed protein levels .

What are the key considerations when analyzing CRLF1's dual roles in different cellular contexts?

CRLF1 exhibits context-dependent functions, acting as both a secreted cytokine in complex with CLCF1 and as an intracellular signaling molecule. When analyzing these dual roles, researchers should consider these methodological approaches:

• Experimental design for context discrimination:

  • Cell type-specific analysis: Compare CRLF1 functions across:

    • Neural cells (where neurotrophic functions predominate)

    • Immune cells (where immunomodulatory roles may be primary)

    • Cancer cells (where both functions may contribute to malignancy)

  • Genetic manipulation strategies:

    • Generate signal sequence mutants that prevent secretion

    • Create domain-specific mutants that selectively disrupt particular functions

    • Use inducible systems to control timing of expression

• Pathway analysis framework:

  • Secreted function assessment:

    • Focus on CNTFR complex activation and downstream JAK/STAT signaling

    • Measure classic neurotrophic readouts (neurite outgrowth, survival)

    • Use receptor blocking antibodies to confirm pathway specificity

  • Intracellular function assessment:

    • Examine AKT/mTORC2 interaction and activation

    • Monitor pyroptosis inhibition pathways (ASK1/JNK/Caspase3/GSDME)

    • Compare with extracellular administration of recombinant CRLF1

• Data integration approach:

  • RNA-seq context analysis: Compare transcriptional responses to CRLF1 under different conditions

  • Protein interaction network mapping: Identify context-specific binding partners

  • Phenotypic profiling: Develop comprehensive readouts of cellular responses

• Context-dependent function comparison table:

• Analytical considerations:

  • Temporal dynamics: Different functions may predominate at different time points

  • Concentration dependence: Dose-response relationships may differ between pathways

  • Feedback mechanisms: Consider how one function may regulate the other

This comprehensive analytical framework enables proper interpretation of CRLF1's complex and context-dependent functions, which is essential for understanding its role in both normal development and disease states .

What are the emerging research directions for CRLF1 antibodies in therapeutic target validation?

As CRLF1 emerges as a potential therapeutic target in multiple disease contexts, antibodies are becoming critical tools for target validation. Researchers should consider these future directions and methodological approaches:

• Cancer therapy applications:

  • Target validation methodology:

    • Use CRLF1 antibodies to assess expression in patient-derived xenografts

    • Correlate expression with response to standard chemotherapies

    • Develop antibody-drug conjugates targeting CRLF1-expressing cells

  • Combination therapy assessment:

    • Test CRLF1 antibodies in combination with AKT/mTOR inhibitors

    • Evaluate potential synergy with pyroptosis-inducing agents

    • Monitor pathway activation markers to confirm mechanism of action

• Neurological disorder applications:

  • Function-blocking antibodies:

    • Develop antibodies that disrupt CRLF1-CLCF1 heterodimer formation

    • Test effects on CNTFR signaling in neural models

    • Assess potential for restoring proper neuronal development

  • Diagnostic applications:

    • Use CRLF1 antibodies to develop biomarker assays for related disorders

    • Correlate CRLF1 levels with disease progression and severity

• Binding-defective CRLF1 variants as therapeutic tools:

  • Validation methodology:

    • Use antibodies to confirm expression and localization of engineered variants

    • Develop specific antibodies that distinguish wild-type from binding-defective variants

    • Monitor pathway competition and dominant-negative effects

• Technical innovation for therapeutic development:

  • Advanced antibody platforms:

    • Develop bispecific antibodies targeting CRLF1 and key pathway components

    • Engineer antibody fragments for improved tissue penetration

    • Create intracellular antibodies (intrabodies) targeting non-secreted CRLF1 functions

  • High-throughput screening approaches:

    • Use CRLF1 antibodies in automated immunoassays to screen compound libraries

    • Develop cell-based reporter systems for pathway activation

• Future research priority matrix:

These emerging directions highlight the critical role of CRLF1 antibodies in translating basic research findings into therapeutic applications, particularly in oncology and neurology .

What methodological innovations are needed to advance CRLF1 research?

Future progress in understanding CRLF1 biology and its therapeutic applications will require several methodological innovations. Researchers should consider developing and implementing these advanced approaches:

• Structural biology and interaction tools:

  • High-resolution structural determination: Develop antibodies that facilitate crystallization of CRLF1 alone and in complexes

  • Single-molecule interaction analysis: Apply techniques like single-molecule FRET using labeled antibodies to study dynamic interactions

  • Cryo-EM applications: Use antibodies as fiducial markers for complex orientation in structural studies

• Advanced cellular and tissue analysis:

  • Spatial transcriptomics integration: Combine CRLF1 protein detection with spatial transcriptomic data

  • Super-resolution microscopy: Develop fluorophore-conjugated antibodies optimized for techniques like STORM or PALM

  • Live-cell imaging: Engineer non-perturbing antibody fragments for real-time tracking of CRLF1 dynamics

• In vivo research tools:

  • PET imaging probes: Develop radiolabeled antibodies for non-invasive CRLF1 detection in animal models

  • Conditional expression systems: Create more sophisticated genetic tools with tissue-specific and temporal control

  • Humanized mouse models: Engineer models expressing human CRLF1 variants for better translational research

• Systems biology approaches:

  • Multi-omics integration frameworks: Develop computational methods to integrate CRLF1 protein data with transcriptomics, metabolomics, and epigenomics

  • Network perturbation analysis: Use targeted CRLF1 modulation to understand system-wide effects

  • Mathematical modeling: Create predictive models of CRLF1 pathway dynamics under various conditions

• Therapeutic development methodologies:

  • Domain-specific neutralizing antibodies: Generate tools that selectively block specific CRLF1 functions

  • Intracellular antibody delivery: Develop methods to target non-secreted pools of CRLF1

  • Antibody engineering: Create bispecific antibodies linking CRLF1 to specific cellular compartments or binding partners

• Technical gaps and proposed solutions table:

These methodological innovations will collectively advance our understanding of CRLF1 biology and accelerate translation of these insights into clinical applications for cancer, neurological disorders, and other CRLF1-related conditions .

What are the recommended protocols for CRLF1 antibody validation?

Comprehensive validation of CRLF1 antibodies is essential for ensuring reliable experimental results. Below is a structured protocol for systematic antibody validation:

• Expression system validation:

  • Protocol overview: Generate positive and negative control samples

  • Methodology:

    1. Transfect HEK293T cells with CRLF1 expression vector or empty vector control

    2. Harvest cells 48 hours post-transfection

    3. Prepare lysates using RIPA buffer with protease inhibitors

    4. Run Western blot with serial dilutions of lysate (5-50 μg)

    5. Compare signal between CRLF1-expressing and control samples

  • Expected outcome: Single specific band at 46 kDa in CRLF1-expressing cells, absent in controls

• Knockdown/knockout validation:

  • Protocol overview: Generate CRLF1-depleted samples

  • Methodology:

    1. Transfect cells with CRLF1-targeting siRNA or non-targeting control

    2. Alternatively, generate CRISPR-Cas9 knockout cell lines

    3. Confirm knockdown/knockout by qPCR

    4. Prepare lysates and perform Western blot

    5. Compare signal between CRLF1-depleted and control samples

  • Expected outcome: Significant reduction in band intensity in CRLF1-depleted samples

• Epitope blocking validation:

  • Protocol overview: Confirm epitope specificity

  • Methodology:

    1. Pre-incubate primary antibody with 5-10× excess of immunizing peptide for 2 hours at RT

    2. Run parallel Western blots with blocked and unblocked antibody

    3. For IHC/IF, perform parallel staining with blocked and unblocked antibody

  • Expected outcome: Signal should be abolished or significantly reduced with blocked antibody

• Cross-reactivity assessment:

  • Protocol overview: Test reactivity against related proteins

  • Methodology:

    1. Express recombinant CRLF1 alongside related cytokine receptor proteins

    2. Perform Western blot against all proteins with the same antibody

    3. Analyze cross-reactivity with computational epitope mapping

  • Expected outcome: Antibody should be specific for CRLF1 with minimal cross-reactivity

• Multi-application validation table:

These comprehensive validation protocols ensure antibody specificity and reliability across multiple applications, which is critical for generating reproducible and trustworthy data in CRLF1 research .

What are the recommended methods for quantifying CRLF1 expression in different experimental systems?

Accurate quantification of CRLF1 expression is essential for understanding its role in various biological contexts. Below are recommended methods for reliable CRLF1 quantification across different experimental systems:

• Protein expression quantification:

  • Western blot densitometry:

    1. Use appropriate loading controls (GAPDH, β-actin, or total protein staining)

    2. Include standard curve of recombinant CRLF1 (10-100 ng)

    3. Ensure signal is in linear range by testing multiple exposure times

    4. Normalize to loading control and calculate relative expression

    5. Use ImageJ or similar software for quantification

  • ELISA-based quantification:

    1. Use sandwich ELISA with capture and detection antibodies targeting different epitopes

    2. Generate standard curve with recombinant CRLF1 (range: 0.1-100 ng/mL)

    3. Analyze samples in triplicate to ensure reproducibility

    4. Calculate concentration based on 4-parameter logistic regression

• Cellular expression analysis:

  • Flow cytometry:

    1. Fix cells with 4% paraformaldehyde and permeabilize with 0.1% saponin

    2. Stain with fluorophore-conjugated CRLF1 antibody or primary/secondary combination

    3. Include isotype control and blocking peptide control

    4. Analyze using geometric mean fluorescence intensity

    5. Present data as mean fluorescence intensity ratio over isotype control

  • Quantitative immunofluorescence:

    1. Use consistent acquisition settings across all samples

    2. Include calibration standards in each experiment

    3. Perform automated image analysis for unbiased quantification

    4. Report integrated density or mean pixel intensity within defined regions

• Tissue expression analysis:

  • Immunohistochemistry scoring:

    1. Develop standardized scoring system (e.g., H-score = % positive cells × intensity)

    2. Have multiple independent observers score specimens

    3. Use digital pathology software for automated analysis

    4. Report both intensity and proportion of positive cells

  • Multiplexed tissue analysis:

    1. Use multiplexed IF to identify cell type-specific expression

    2. Perform colocalization analysis with cell type markers

    3. Quantify using cell-by-cell analysis rather than whole tissue averages

• Secreted CRLF1 measurement:

  • Media concentration determination:

    1. Collect conditioned media at defined time points

    2. Concentrate proteins using TCA precipitation or centrifugal filters

    3. Normalize to cell number or total cellular protein

    4. Quantify using Western blot or ELISA as described above

• Data standardization approaches:

  • Absolute quantification: Using purified CRLF1 standards to determine concentrations

  • Relative quantification: Normalizing to reference samples included in each experiment

  • Multi-site standardization: Including common reference standards across laboratories