AURKB Antibody

What is AURKB and what are its primary functions in cellular processes?

Aurora Kinase B (AURKB) is a chromosomal passenger serine/threonine protein kinase that belongs to the Aurora subfamily. It plays critical roles in:

• Regulating accurate chromosomal segregation

• Facilitating cytokinesis

• Controlling protein localization to the centromere and kinetochore

• Ensuring correct microtubule-kinetochore attachments

• Regulating the mitotic checkpoint

AURKB is also known by several alternate names including AIK2, AIM1, AIRK2, ARK2, STK1, STK12, and STK5. The protein has a calculated molecular weight of 39.2 kDa, though its observed molecular weight in experimental contexts typically ranges from 39-45 kDa .

For optimal preservation of AURKB antibodies:

• Store at -20°C for long-term storage (most formulations are stable for one year after shipment)

• Some formulations recommend storage at 2-8°C

• Avoid repeated freeze-thaw cycles

• For diluted antibodies, store in buffer solutions like PBS with preservatives (0.02-0.09% sodium azide and often 50% glycerol at pH 7.3)

• Some preparations advise against aliquoting for -20°C storage

• For diluted antibodies with low volume (e.g., 25 µL), dilute 1:10 with appropriate buffer to minimize loss

Products with BSA may have special storage considerations; for example, some 20μl sizes contain 0.1% BSA .

What controls should be included when validating a new AURKB antibody for Western blotting?

When validating a new AURKB antibody for Western blotting:

Positive Controls:

• HeLa cells (validated positive control)

• Mouse thymus tissue

• SK-N-SH cells

• HEK293 cell lysates

Validation Protocol:

• Run positive controls alongside experimental samples

• Expect to detect a band of approximately 39-48 kDa (specific antibodies may detect bands at different sizes; for example, Bio-Rad's rabbit anti-Aurora-B kinase detects a band of ~48 kDa)

• Include a loading control (e.g., GAPDH, β-actin)

• Consider running a phospho-specific control when using phospho-specific antibodies such as pT232

• Include negative controls such as samples where AURKB is known to be minimally expressed

Verification Strategy:

• Confirm specificity by comparing band patterns with published literature

• For conclusive validation, consider knockdown/knockout experiments to demonstrate specificity

How can researchers effectively design experiments to study AURKB in cancer models?

Designing effective experiments to study AURKB in cancer models requires a multi-faceted approach:

1. Expression Analysis:

• Quantify AURKB expression using Western blotting across multiple cancer cell lines (e.g., HCT116, HT29, SW480 for colorectal cancer)

• Validate findings using immunohistochemistry on tissue samples

• Consider temporal analysis (e.g., expression changes over 24-48h after treatment)

2. Functional Studies:

• Implement AURKB inhibition using selective inhibitors such as AZD1152 (dihydrogen phosphate prodrug)

• Design sequential treatment protocols (24h 5-FU followed by AURKB inhibitor shows enhanced efficacy in colorectal cancer models)

• Evaluate effects in both 2D and 3D in vitro models, as well as ex vivo cultures for greater translational relevance

3. Flow Cytometry Analysis:

• Assess cell cycle effects and polyploidy induction (>4N) following AURKB inhibition

• Implement propidium iodide staining to assess aneuploidy via flow cytometry

4. Mechanistic Studies:

• Analyze micronuclei formation using DAPI staining and immunofluorescent microscopy

• Investigate pathways affected by AURKB inhibition (cell cycle regulation, inflammatory response, immune pathways)

5. In Vivo Models:

• For syngeneic models, consider the 4T1 cell line injected bilaterally into Balb/c mice with combined treatment of AURKB inhibitors and radiation therapy

• Monitor tumor volume twice weekly throughout the study

What methodological approaches are recommended for studying AURKB phosphorylation?

Studying AURKB phosphorylation requires specialized approaches:

Antibody Selection:

• Use phospho-specific antibodies targeting key phosphorylation sites, such as pT232, which is critical for AURKB activation

• Ensure antibodies are validated for phospho-specificity through cross-adsorption against non-phosphorylated forms of the immunizing peptide

Sample Preparation:

• Harvest cells during M phase when AURKB phosphorylation is highest

• Use phosphatase inhibitors in lysis buffers to preserve phosphorylation status

• Consider synchronizing cells to enrich for mitotic populations

Analytical Methods:

• Western blotting: Use appropriate dilutions (1:250-1:2,000 for phospho-specific antibodies)

• Immunofluorescence: Optimize fixation methods (often paraformaldehyde works well)

• ELISA: Consider dilutions of 1:10,000-1:50,000 for phospho-specific antibodies

Validation Approaches:

• Use Aurora kinase inhibitors as negative controls

• Include lambda phosphatase-treated samples as dephosphorylation controls

• Consider using cells treated with microtubule-targeting agents (e.g., nocodazole) to enrich for mitotic cells with high AURKB phosphorylation

How does AURKB expression correlate with cancer prognosis and what are the implications for therapeutic targeting?

AURKB expression has significant correlations with cancer prognosis and therapeutic potential:

Prognostic Associations:

Therapeutic Implications:

• AURKB inhibition significantly enhances the effectiveness of standard chemotherapies like 5-fluorouracil (5-FU) in colorectal cancer models

• Sequential treatment approaches (chemotherapy followed by AURKB inhibition) show greater efficacy than simultaneous administration

• In triple-negative breast cancer (TNBC), AURKB inhibition induces radiosensitization with radiation enhancement ratios of 1.24-1.72

Mechanistic Understanding:

• AURKB promotes cancer progression through cell cycle dysregulation and inflammatory/immune pathway modulation

• AURKB inhibition increases micronuclei formation and aneuploidy when combined with radiation therapy, suggesting a mechanism for enhanced treatment efficacy

• AURKB expression positively correlates with CD4+ Th2 cells in almost all cancers, potentially contributing to immune suppression and tumor growth

These findings suggest AURKB inhibition is a promising strategy for enhancing standard cancer treatments, with potential applications in precision oncology.

What is the relationship between AURKB expression and immune cell infiltration in cancer?

AURKB expression demonstrates complex relationships with immune cell infiltration in cancer microenvironments:

Immune Cell Correlations:

• AURKB expression positively correlates with CD4+ Th2 cells across nearly all cancer types except TGCT

• CD4+ Th2 cells typically inhibit immune responses and promote tumor growth and spread

• Different immune cell populations show variable correlations with AURKB expression depending on cancer type and analysis algorithm used

Immunomodulatory Associations:

• AURKB expression positively correlates with immune checkpoint genes in multiple cancers including OV, HNSC, LUAD, STAD, KIRP, PRAD, BLCA, BRCA, THCA, LGG, LIHC, PAAD, and KIRC

• Negative correlation with immune checkpoint genes is observed in THYM, TGCT, CECS, and LUSC

• AURKB expression positively correlates with immunomodulatory genes (immune factors, receptors, MHC, immunosuppressive and immunostimulatory genes) in THCA, LGG, OV, PAAD, KICH, LIHC, and KIRC

Therapeutic Relevance:

• AURKB expression shows positive correlation with Tumor Mutational Burden (TMB) in 18 cancer types and Microsatellite Instability (MSI) in 7 cancer types

• These correlations suggest AURKB could be a predictor of response to immunotherapy, as both TMB and MSI are established biomarkers for immunotherapy response

• The imbalance in Th cell subsets (with predominance of Th2 at tumor sites) may be influenced by AURKB through promotion of IL-4 secretion from CD4+ T cells

These findings highlight AURKB's potential role in modulating the tumor immune microenvironment and suggest targeting AURKB could enhance immunotherapy efficacy in specific cancer contexts.

How can researchers effectively use AURKB antibodies to study its interaction with other chromosomal passenger complex proteins?

Studying AURKB interactions with other chromosomal passenger complex (CPC) proteins requires specialized experimental approaches:

Co-Immunoprecipitation (Co-IP) Strategy:

• Select antibodies with validated IP capabilities (e.g., Cell Signaling Technology's Aurora B/AIM1 antibodies #3094 and #28711)

• Use recommended dilutions (typically 1:100 for IP)

• Include appropriate controls:

  • IgG control of the same species as the antibody

  • Input sample (pre-IP lysate)

  • Negative control (samples where AURKB expression is knocked down)

• Western blot for interacting partners (INCENP, Survivin, Borealin)

Proximity Ligation Assay (PLA) Approach:

• Select antibodies validated for immunofluorescence applications (1:800-1:1600 dilution)

• Use antibodies from different species for AURKB and interaction partners

• Follow standard PLA protocols to visualize protein-protein interactions in situ

• Include appropriate controls (single antibody controls, negative controls)

Immunofluorescence Co-localization:

• Use antibodies validated for immunofluorescence at optimal dilutions

• Employ cell synchronization to enrich for mitotic cells

• Focus on specific cell cycle phases where CPC localization changes

• Use high-resolution microscopy (confocal or super-resolution) for precise co-localization analysis

Advanced Techniques:

• FRET (Fluorescence Resonance Energy Transfer) to study direct interactions

• BiFC (Bimolecular Fluorescence Complementation) for visualization of protein complexes

• ChIP-seq to study AURKB associations with chromatin and other CPC components at specific genomic loci

What are common challenges when using AURKB antibodies and how can they be addressed?

Researchers working with AURKB antibodies may encounter several challenges:

Issue: Weak or No Signal in Western Blotting
Solutions:

• Verify sample source matches antibody reactivity (human, mouse, etc.)

• Use validated positive controls (HeLa cells, mouse thymus tissue, SK-N-SH cells)

• Optimize antibody dilution within recommended ranges (1:500-1:2000)

• Enrich for mitotic cells as AURKB expression is highest during M phase

• Consider sample preparation: ensure phosphatase inhibitors are included if studying phosphorylated forms

Issue: High Background in Immunohistochemistry
Solutions:

• Follow specific antigen retrieval recommendations (TE buffer pH 9.0 or citrate buffer pH 6.0)

• Optimize antibody concentration (1:20-1:200 for IHC)

• Increase blocking time or concentration

• Use appropriate controls to distinguish specific from non-specific staining

• Consider more stringent washing steps

Issue: Non-specific Bands in Western Blotting
Solutions:

• Verify expected molecular weight (typically 39-45 kDa)

• Increase antibody specificity through more stringent washing

• Use gradient gels to better resolve proteins of similar molecular weights

• Consider using knockout/knockdown samples as negative controls

• For phospho-specific antibodies, treat samples with phosphatase as negative controls

Issue: Cell Cycle-Dependent Variability
Solutions:

• Synchronize cells to specific cell cycle stages for consistent results

• Document cell confluence and passage number

• Consider that AURKB is expressed primarily during S and G2/M phases

• For phosphorylation studies, harvest cells during mitosis when activity is highest

How can researchers troubleshoot inconsistent results when studying AURKB inhibition in cancer models?

When studying AURKB inhibition in cancer models, inconsistent results may stem from several factors:

Issue: Variable Efficacy of AURKB Inhibitors
Solutions:

• Confirm inhibitor activity using polyploidy induction assay (>4N DNA content) via flow cytometry

• Verify inhibition of phosphorylation targets using phospho-specific antibodies

• Consider timing of inhibitor administration (sequential vs. simultaneous treatment shows different outcomes)

• Test multiple concentrations to establish dose-response relationships

• Validate the inhibitor's specificity for AURKB versus other Aurora kinases

Issue: Cell Line-Dependent Responses
Solutions:

• Test inhibitors across multiple cell lines representative of the cancer type

• Characterize baseline AURKB expression levels in each cell line

• Consider genetic background (p53 status, etc.) that may influence response

• Include both 2D and 3D culture models for more robust findings

• When possible, include patient-derived ex vivo cultures to confirm clinical relevance

Issue: Temporal Considerations
Solutions:

• Monitor response kinetics over multiple time points (24h, 48h, 72h)

• For combination treatments, test different sequences (e.g., 5-FU treatment for 24h followed by AURKB inhibition showed enhanced efficacy compared to simultaneous treatment)

• Consider cell cycle synchronization to normalize starting populations

Issue: In Vivo Model Variability
Solutions:

• Standardize tumor size before initiating treatment

• Ensure consistent dosing and administration routes

• Monitor tumor volume frequently (e.g., twice weekly)

• Consider using orthotopic models rather than subcutaneous for greater physiological relevance

• Document immune status of model organisms, particularly in syngeneic models

What considerations are important when comparing data from different phospho-specific AURKB antibodies?

When comparing data from different phospho-specific AURKB antibodies, researchers should consider several critical factors:

Epitope Specificity:

• Verify the exact phosphorylation site recognized (e.g., pT232 is critical for AURKB activation)

• Review immunogen information to understand how the antibody was generated

• Check if antibodies were cross-adsorbed against non-phosphorylated peptides to ensure phospho-specificity

Validation Methods:

• Review how each antibody was validated for phospho-specificity

• Check if phosphatase treatment controls were used

• Determine if specificity was verified using AURKB inhibitors or genetic approaches

Technical Variations:

• Note differences in dilution recommendations between antibodies (e.g., 1:250-1:2,000 for WB)

• Compare buffer compositions that might affect antibody performance

• Consider differences in antibody formats (monoclonal vs. polyclonal)

• Identify host species differences that might affect secondary antibody selection

Data Interpretation:

• Be aware that different phospho-antibodies may reflect different aspects of AURKB activity

• Consider that some antibodies might detect overlapping phosphorylation sites on related Aurora kinases

• Document differences in detection sensitivity between antibodies

• When reporting results, clearly specify which phospho-specific antibody was used

Standardization Approach:

• When possible, validate key findings with multiple phospho-specific antibodies

• Include appropriate positive controls (e.g., nocodazole-treated cells with high AURKB activity)

• Use recombinant phosphorylated AURKB as a standardization control

• Consider quantitative approaches (e.g., mass spectrometry) as complementary methods for important findings

What are the emerging applications of AURKB antibodies in cancer immunotherapy research?

Emerging applications of AURKB antibodies in cancer immunotherapy research show significant promise:

Biomarker Development:

• AURKB expression correlates with TMB and MSI, established predictors of immunotherapy response in multiple cancers

• AURKB antibodies can help stratify patients likely to respond to immune checkpoint inhibitors

• Monitoring AURKB expression may provide insights into acquired resistance mechanisms

Immune Microenvironment Characterization:

• AURKB antibodies enable investigation of associations between AURKB expression and immune cell infiltration

• Multiplex IHC/IF using AURKB antibodies alongside immune cell markers helps map spatial relationships

• Understanding AURKB's role in promoting CD4+ Th2 cells across cancer types may lead to novel immunomodulatory approaches

Combination Therapy Assessment:

• AURKB inhibition combined with radiation therapy shows enhanced efficacy in TNBC models

• AURKB antibodies are essential tools for monitoring inhibition efficacy

• Potential synergistic effects between AURKB inhibitors and immunotherapies need further investigation

Resistance Mechanism Studies:

• AURKB upregulation occurs in response to 5-FU treatment in colorectal cancer

• AURKB antibodies help track expression changes following standard treatments

• Understanding AURKB-mediated resistance pathways may inform rational combination strategies

Novel Target Identification:

• AURKB antibodies facilitate investigation of downstream pathways and co-expressed genes

• Exploration of the miRNA-AURKB regulatory network (involving 12 key miRNAs including hsa-let-7 family) may reveal additional therapeutic targets

• New AURKB-interacting proteins identified through immunoprecipitation with AURKB antibodies could become novel therapeutic targets

How might single-cell analysis techniques using AURKB antibodies provide new insights into tumor heterogeneity?

Single-cell analysis techniques employing AURKB antibodies offer powerful approaches to understanding tumor heterogeneity:

Single-Cell Protein Analysis:

• Mass cytometry (CyTOF) with AURKB antibodies can reveal distinct cell populations based on AURKB expression levels

• Single-cell Western blotting can quantify AURKB protein in rare subpopulations

• Imaging mass cytometry combines spatial information with single-cell AURKB quantification

Spatial Transcriptomics Integration:

• Combining AURKB immunofluorescence with spatial transcriptomics reveals relationships between AURKB protein levels and transcriptional states

• This approach can identify spatial niches where AURKB-high cells interact with specific immune populations

• The correlation between AURKB expression and immune checkpoint genes can be mapped spatially within tumors

Clonal Evolution Tracking:

• Sequential tumor sampling with AURKB antibody staining can track changes in subpopulations during treatment

• This approach may identify emerging resistant clones with altered AURKB expression

• Understanding whether AURKB expression precedes or follows other resistance markers

Functional Heterogeneity Assessment:

• Live-cell imaging with fluorescently-tagged AURKB antibody fragments can track dynamics in single cells

• Correlation of AURKB activity with other functional readouts (e.g., DNA damage, proliferation) at single-cell level

• In vitro microdissection of AURKB-high versus AURKB-low regions followed by drug sensitivity testing

Clinical Applications:

• Single-cell analysis of AURKB in circulating tumor cells may provide non-invasive monitoring of tumor evolution

• Patient-derived organoids analyzed at single-cell level for AURKB expression could guide personalized therapy

• Integration of single-cell AURKB data with clinical outcomes to develop more precise prognostic models

What methodological approaches should be considered when designing experiments to study AURKB's role in resistance to targeted therapies?

When designing experiments to study AURKB's role in resistance to targeted therapies, researchers should consider these methodological approaches:

Resistance Model Development:

• Generate resistant cell lines through long-term exposure to targeted therapies

• Compare AURKB expression and phosphorylation between parental and resistant lines using validated antibodies

• Develop isogenic cell lines with AURKB overexpression or knockdown to establish causality

• Consider patient-derived models that recapitulate clinical resistance patterns

Temporal Analysis:

• Monitor AURKB expression changes during resistance development using time-course experiments

• Use AURKB antibodies for Western blotting at defined intervals (24h, 48h, etc.)

• Implement live-cell reporters for real-time monitoring of AURKB activity

• Correlate AURKB changes with emergence of resistant phenotypes

Mechanistic Studies:

• Use phospho-specific AURKB antibodies to track activation status

• Employ immunoprecipitation to identify novel interaction partners in resistant cells

• Implement ChIP-seq to determine if AURKB alters chromatin accessibility or transcription factor binding

• Analyze downstream signaling changes through phospho-proteomics

Combinatorial Approaches:

• Test AURKB inhibitors in combination with primary targeted therapies

• Determine optimal sequencing (sequential vs. simultaneous administration)

• Evaluate potential synergy using appropriate statistical methods

• Monitor both immediate response and long-term resistance development

Translational Validation:

• Analyze AURKB expression in paired patient samples (pre-treatment and post-resistance)

• Correlate AURKB levels with clinical outcomes using IHC with optimized protocols

• Develop predictive biomarkers based on AURKB expression or activity patterns

• Test combinations identified in preclinical models in patient-derived xenografts or organoids