BICC1 Antibody

What is BICC1 and what are its basic molecular characteristics?

BICC1 (BicC family RNA binding protein 1) is a 104.8 kilodalton RNA-binding protein in humans. It may also be known under alternative nomenclature including BICC, CYSRD, protein bicaudal C homolog 1, and FGFR2-BICC1 fusion kinase protein. The protein functions primarily as an RNA-binding protein that can post-transcriptionally regulate gene expression by binding to the 3'UTR of target mRNAs, influencing their stability and translation . BICC1 contains specific RNA-binding domains that facilitate its regulatory functions across multiple cellular pathways.

In which experimental models can BICC1 expression be reliably detected?

BICC1 expression can be detected in various experimental models including human cell lines (particularly pancreatic adenocarcinoma cell lines such as AsPC-1, BxPC-3, and CFPAC-1), mouse models (including Pan02 and KPC cells), and primary tissue samples. Based on current research, BICC1 detection is particularly relevant in pancreatic cancer models, where it shows significant overexpression compared to normal pancreatic tissues . When designing experiments, researchers should consider species-specific antibody reactivity as orthologs exist in canine, porcine, monkey, mouse and rat models .

How should researchers select the appropriate BICC1 antibody for mechanistic studies in cancer research?

When selecting BICC1 antibodies for mechanistic cancer research, researchers should consider:

• Epitope specificity: Choose antibodies targeting relevant domains (N-terminal vs. internal regions) based on your research focus. N-terminal antibodies are particularly useful when studying full-length BICC1 function in RNA binding.

• Validated applications: Select antibodies specifically validated for your intended application:

  • For protein interaction studies: Use antibodies validated for immunoprecipitation (IP)

  • For localization studies: Use antibodies validated for immunofluorescence (IF)

  • For expression analysis: Use antibodies validated for Western blot (WB)

• Species cross-reactivity: If conducting comparative studies across species, select antibodies with demonstrated cross-reactivity to relevant species (human, mouse, rat) .

• Published validation: Prioritize antibodies previously utilized in peer-reviewed research on BICC1's role in cancer pathways, particularly those with demonstrated specificity in pancreatic cancer models .

What are the critical validation steps for BICC1 antibodies before use in pivotal experiments?

Before using BICC1 antibodies in pivotal experiments, researchers should perform these critical validation steps:

• Specificity verification:

  • Positive control using cell lines known to express BICC1 (e.g., CFPAC-1 cells)

  • Negative control using BICC1-knockdown cells generated with validated shRNA constructs

  • Western blot confirmation of correct molecular weight (104.8 kDa)

• Cross-reactivity assessment:

  • If using in multiple species, validate detection in each species independently

  • Test for non-specific binding in knockout/knockdown models

• Application-specific validation:

  • For IHC: Validate with positive and negative control tissues

  • For IF: Confirm subcellular localization pattern matches known BICC1 distribution

  • For IP: Verify enrichment compared to IgG control followed by mass spectrometry

• Lot-to-lot consistency: When obtaining new antibody lots, perform parallel experiments with previous lots to ensure consistent performance .

How can researchers effectively design experiments to study BICC1's role in VEGF-independent angiogenesis?

To effectively study BICC1's role in VEGF-independent angiogenesis, researchers should implement a multi-faceted experimental approach:

• In vitro angiogenesis models:

  • Tube formation assays using human endothelial cells (HUVECs) treated with conditioned media from BICC1-overexpressing or BICC1-depleted cancer cells

  • Endothelial cell migration assays to assess directional cell movement in response to BICC1-mediated secreted factors

  • Compare results with and without VEGF inhibitors (e.g., Bevacizumab) to confirm VEGF-independence

• In vivo angiogenesis assessment:

  • Orthotopic pancreatic cancer models with modulated BICC1 expression (overexpression/knockdown)

  • Quantification of microvessel density using endothelial markers (CD34)

  • Comparative analysis between BICC1 expression levels and tumor growth/vascularization

• Molecular pathway analysis:

  • RNA sequencing to identify BICC1-regulated transcripts related to angiogenesis

  • RNA immunoprecipitation (RIP) to identify direct RNA targets of BICC1

  • Focus on LCN2 pathway components and JAK2/STAT3 signaling molecules

What are the optimal conditions for using BICC1 antibodies in RNA immunoprecipitation (RIP) experiments?

For optimal RNA immunoprecipitation (RIP) experiments using BICC1 antibodies:

• Cell preparation:

  • Use fresh cells with high BICC1 expression (e.g., PAAD cell lines)

  • Crosslink with formaldehyde (1% for 10 minutes) to preserve RNA-protein interactions

  • Prepare cell lysates in non-denaturing conditions with RNase inhibitors

• Antibody selection and validation:

  • Choose antibodies specifically validated for immunoprecipitation applications

  • Perform preliminary Western blot to confirm BICC1 detection in your sample

  • Use 5-10 μg of antibody per reaction, with matched IgG controls

• Immunoprecipitation conditions:

  • Pre-clear lysates with protein A/G beads

  • Incubate with BICC1 antibody overnight at 4°C

  • Wash stringently (at least 4-5 washes) to reduce background

• RNA recovery and analysis:

  • Extract RNA from immunoprecipitated complexes

  • Verify enrichment of known BICC1 targets (e.g., LCN2 mRNA)

  • Perform RT-qPCR or RNA sequencing for comprehensive analysis

• Controls and validation:

  • Include input controls (pre-immunoprecipitation)

  • Use IgG negative controls

  • Confirm depletion of BICC1 in flow-through fractions by Western blot

What are the optimized protocols for BICC1 immunohistochemistry in pancreatic tumor tissues?

For optimized BICC1 immunohistochemistry in pancreatic tumor tissues:

• Tissue preparation:

  • Fix tissues in 10% neutral buffered formalin for 24-48 hours

  • Process and embed in paraffin using standard protocols

  • Cut sections at 4-5 μm thickness onto charged slides

• Antigen retrieval optimization:

  • Heat-induced epitope retrieval in citrate buffer (pH 6.0) for 20 minutes

  • Alternative: EDTA buffer (pH 9.0) if citrate buffer yields insufficient signal

• Blocking and antibody conditions:

  • Block with 5% normal serum (matched to secondary antibody species)

  • Use BICC1 primary antibody at 1:100-1:200 dilution (optimize for each antibody)

  • Incubate overnight at 4°C in humid chamber

• Detection system:

  • Use high-sensitivity polymer-based detection systems

  • Develop with DAB and counterstain with hematoxylin

  • Mount with permanent mounting medium

• Controls and validation:

  • Include positive control (known BICC1-expressing pancreatic cancer tissue)

  • Include negative control (normal pancreatic tissue)

  • Use antibody diluent without primary antibody as technical negative control

How should researchers quantify BICC1 expression in relation to microvessel density in tumor samples?

For accurate quantification of BICC1 expression in relation to microvessel density:

• Sequential or dual staining approach:

  • Perform BICC1 IHC on one section

  • Stain adjacent sections for endothelial markers (CD34 or CD31)

  • Alternatively, perform multiplex immunofluorescence for simultaneous detection

• Standardized quantification methods:

  • For BICC1: Use H-score method (intensity × percentage of positive cells)

  • For microvessel density: Count CD34/CD31-positive vessels in 5-10 high-power fields (HPF)

  • Calculate mean vessel counts per HPF in areas with highest vessel density ("hot spots")

• Digital image analysis:

  • Capture standardized digital images at 200-400× magnification

  • Use image analysis software (ImageJ with appropriate plugins)

  • Apply consistent thresholds for positivity across all samples

• Correlation analysis:

  • Plot BICC1 H-scores against mean microvessel density

  • Calculate Pearson's or Spearman's correlation coefficients

  • Perform regression analysis to determine relationship strength

• Data presentation:

  • Present data as scatter plots with regression lines

  • Include representative images showing matched BICC1 and microvessel staining

What experimental approaches can identify novel mRNA targets of BICC1 beyond LCN2?

To identify novel mRNA targets of BICC1 beyond the known LCN2 interaction:

• High-throughput approaches:

  • RNA immunoprecipitation followed by sequencing (RIP-seq)

  • Crosslinking immunoprecipitation followed by sequencing (CLIP-seq)

  • Photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP)

• Bioinformatic analysis:

  • Motif discovery in identified RNA sequences to determine BICC1 binding motifs

  • Secondary structure analysis of binding regions

  • Pathway enrichment analysis of potential target mRNAs

• Validation experiments:

  • Direct RIP-qPCR for candidate targets

  • Reporter assays with wild-type and mutated 3'UTR sequences

  • In vitro binding assays with recombinant BICC1 and synthetic RNA

• Functional validation:

  • Assess target mRNA stability and translation efficiency in BICC1-depleted cells

  • Rescue experiments with BICC1 re-expression

  • Mutational analysis of BICC1 RNA-binding domains

How can researchers effectively investigate the mechanisms by which BICC1 stabilizes target mRNAs?

To investigate mechanisms by which BICC1 stabilizes target mRNAs:

• mRNA stability assessments:

  • Actinomycin D chase experiments comparing mRNA half-lives in BICC1-expressing versus BICC1-depleted cells

  • Pulse-chase labeling with 5-ethynyluridine (EU) to track newly synthesized mRNAs

  • qRT-PCR analysis at multiple time points to generate decay curves

• Molecular interaction studies:

  • Identify protein partners of BICC1 using co-immunoprecipitation followed by mass spectrometry

  • Investigate interactions with known mRNA decay machinery components

  • Examine competitive binding with destabilizing RNA-binding proteins

• 3'UTR analysis:

  • Create reporter constructs with target 3'UTRs fused to luciferase

  • Perform deletion/mutation analysis to identify critical binding regions

  • Test chimeric 3'UTRs to determine transferability of stabilization effect

• Subcellular localization studies:

  • Fluorescence microscopy to co-localize BICC1 with mRNA targets

  • Assess co-localization with P-bodies, stress granules, or other RNA processing bodies

  • Subcellular fractionation to quantify target mRNAs in different compartments

How does BICC1 interface with the JAK2/STAT3 signaling pathway in cancer progression?

BICC1's interface with the JAK2/STAT3 signaling pathway involves several mechanistic steps:

• Indirect activation mechanism:

  • BICC1 binds to the 3'UTR of LCN2 mRNA, enhancing its stability and translation

  • Increased LCN2 protein is secreted and binds to its receptor 24p3R

  • This interaction leads to direct phosphorylation of JAK2

  • Activated JAK2 subsequently phosphorylates STAT3

• Downstream effects:

  • Phosphorylated STAT3 translocates to the nucleus

  • STAT3 activation promotes transcription of pro-angiogenic factors, particularly CXCL1

  • CXCL1 induction drives VEGF-independent angiogenesis

  • This pathway contributes to Bevacizumab resistance in pancreatic cancer

• Experimental evidence:

  • JAK2/STAT3 phosphorylation levels correlate with BICC1 expression

  • JAK2 inhibitors block BICC1-mediated angiogenic effects

  • STAT3 knockdown abrogates BICC1-induced CXCL1 expression

  • LCN2 neutralization prevents BICC1-mediated JAK2 activation

What are the recommended methods for investigating BICC1-dependent drug resistance mechanisms in cancer?

For investigating BICC1-dependent drug resistance mechanisms:

• In vitro resistance models:

  • Develop Bevacizumab-resistant cell lines through chronic exposure

  • Compare BICC1 expression between parental and resistant lines

  • Create isogenic cell lines with modulated BICC1 expression (overexpression/knockdown)

  • Assess drug sensitivity using proliferation, apoptosis, and tube formation assays

• In vivo resistance models:

  • Establish xenograft or orthotopic models with BICC1-modulated cancer cells

  • Treat with anti-angiogenic therapies (e.g., Bevacizumab)

  • Monitor tumor growth, vascularization, and metastasis

  • Collect tumor tissues for molecular and histological analyses

• Mechanistic investigations:

  • RNA-seq to identify alternative angiogenic pathways activated by BICC1

  • Phospho-protein arrays to map activated signaling nodes

  • Secretome analysis to identify BICC1-dependent secreted factors

  • Small molecule inhibitor screens to identify vulnerabilities

• Clinical correlations:

  • Analyze BICC1 expression in pre- and post-treatment patient samples

  • Correlate BICC1 levels with response to anti-angiogenic therapy

  • Investigate biomarker potential through survival analyses

  • Develop combination treatment strategies targeting BICC1-dependent pathways

How can researchers address non-specific binding issues when using BICC1 antibodies in Western blot applications?

To address non-specific binding with BICC1 antibodies in Western blotting:

• Antibody optimization:

  • Titrate antibody concentration (typically start at 1:500-1:2000 dilution)

  • Test multiple incubation conditions (1 hour at room temperature vs. overnight at 4°C)

  • Use optimized blocking agents (5% BSA often performs better than milk for phospho-proteins)

• Sample preparation refinements:

  • Ensure complete protein denaturation (boil samples thoroughly in loading buffer)

  • Add reducing agents (DTT or β-mercaptoethanol) to disrupt disulfide bonds

  • Use freshly prepared lysates with complete protease inhibitor cocktails

• Technical adjustments:

  • Increase washing duration and frequency (minimum 4-5 washes of 5-10 minutes each)

  • Use PVDF membranes instead of nitrocellulose for better protein retention

  • Implement gradient gels to improve separation around the 104.8 kDa region

• Validation controls:

  • Include positive control lysates from cells with confirmed BICC1 expression

  • Run parallel blots with BICC1 knockdown/knockout samples

  • Consider peptide competition assays to confirm specificity

What approaches can resolve discrepancies between BICC1 antibody detection methods in the same experimental system?

To resolve discrepancies between different BICC1 detection methods:

• Systematic comparison analysis:

  • Use multiple antibodies targeting different epitopes of BICC1

  • Compare results across applications (WB, IHC, IF, IP) with standardized samples

  • Document differences in detection sensitivity and specificity

• Technical reconciliation:

  • For WB vs. IHC discrepancies: Consider epitope accessibility in fixed tissues

  • For WB vs. IP differences: Evaluate native vs. denatured protein recognition

  • For IF vs. IHC variations: Assess fixation and permeabilization effects

• Validation with orthogonal methods:

  • Confirm BICC1 expression at mRNA level using qRT-PCR

  • Use mass spectrometry to validate protein identity in immunoprecipitates

  • Implement CRISPR/Cas9 knockout controls for definitive specificity testing

• Standardization of protocols:

  • Normalize protein loading across experiments

  • Establish consistent scoring systems for semi-quantitative methods

  • Use recombinant BICC1 protein as calibration standard when available

How can single-cell technologies advance our understanding of BICC1 function in heterogeneous tumor microenvironments?

Single-cell technologies can advance BICC1 research in heterogeneous tumor microenvironments through:

• Single-cell RNA sequencing applications:

  • Profile BICC1 expression across different cell populations within tumors

  • Identify cell-specific BICC1 regulatory networks

  • Discover correlations between BICC1 and angiogenesis-related genes at single-cell resolution

  • Map BICC1 expression to specific cancer cell subpopulations (e.g., stem-like cells, invasive fronts)

• Spatial transcriptomics approaches:

  • Preserve spatial context while quantifying BICC1 expression

  • Correlate BICC1 levels with proximity to vascular structures

  • Map BICC1-expressing cells relative to immune infiltrates

  • Identify spatial niches where BICC1 expression drives specific phenotypes

• Single-cell protein analysis:

  • Use cyclic immunofluorescence to simultaneously detect BICC1 and multiple pathway components

  • Implement mass cytometry (CyTOF) with metal-conjugated BICC1 antibodies

  • Apply proximity ligation assays to detect BICC1-protein interactions in situ

  • Correlate BICC1 protein levels with cell state markers

• Functional single-cell assays:

  • Combine CRISPR screens with single-cell sequencing to identify BICC1 genetic interactions

  • Track dynamics of BICC1-dependent signaling in live cells

  • Analyze BICC1-dependent cell-cell communication networks

What are the cutting-edge approaches for targeting BICC1-mediated pathways for therapeutic development?

Cutting-edge approaches for targeting BICC1-mediated pathways include:

• RNA-based therapeutics:

  • siRNA/shRNA delivery systems specifically targeting BICC1

  • Antisense oligonucleotides disrupting BICC1 mRNA function

  • mRNA modifications to prevent BICC1 binding to target transcripts

  • CRISPR-Cas13 systems for specific BICC1 mRNA degradation

• Small molecule development:

  • High-throughput screening for compounds disrupting BICC1-RNA interactions

  • Structure-based design targeting BICC1 RNA-binding domains

  • Allosteric modulators affecting BICC1 protein conformation

  • Degraders (PROTACs) targeting BICC1 for proteasomal degradation

• Combination therapy strategies:

  • Dual targeting of BICC1 and VEGF pathways

  • Sequential treatment protocols to prevent resistance development

  • Targeting downstream BICC1 effectors (LCN2, JAK2/STAT3, CXCL1)

  • Tumor microenvironment modifications to enhance anti-BICC1 treatments

• Biomarker-guided approaches:

  • Development of companion diagnostics for BICC1 expression

  • Patient stratification based on BICC1 pathway activation

  • Real-time monitoring of BICC1 target engagement

  • Liquid biopsy methods to track BICC1-dependent circulating factors