TPX2 Antibody, HRP conjugated

What is TPX2 and what are its key cellular functions?

TPX2 (Targeting protein for Xklp2) is a microtubule-associated protein that plays crucial roles in mitotic spindle assembly. It functions as a spindle assembly factor required for normal mitotic spindle formation and microtubule assembly during apoptosis. TPX2 mediates Aurora Kinase A (AURKA) localization to spindle microtubules and activates AURKA by promoting its autophosphorylation at 'Thr-288' while protecting this residue from dephosphorylation. At the onset of mitosis, GOLGA2 interacts with importin-alpha, liberating TPX2 from its inactive state (bound to importin-alpha), allowing TPX2 to activate AURKA kinase and stimulate local microtubule nucleation .

What are the technical specifications of commercially available TPX2 Antibody, HRP conjugated?

The TPX2 Antibody, HRP conjugated (e.g., PACO56239) is typically supplied as follows:

• Reactivity: Human

• Source: Rabbit

• Isotype: IgG

• Size: 50μg

• Applications: ELISA

• Immunogen: Recombinant Human Targeting protein for Xklp2 protein (amino acids 160-320)

• Storage conditions: Preservative 0.03% Proclin 300 with 50% Glycerol in 0.01M PBS, pH 7.4

What alternative nomenclature and identifiers exist for TPX2 in scientific literature?

TPX2 is referenced in scientific literature under various synonyms including:

• Targeting protein for Xklp2

• Differentially expressed in cancerous and non-cancerous lung cells 2 (DIL-2)

• Hepatocellular carcinoma-associated antigen 519

• Hepatocellular carcinoma-associated antigen 90

• Protein fls353

• Restricted expression proliferation-associated protein 100 (p100)

• Gene identifiers: TPX2, C20orf1, C20orf2, DIL2, HCA519

• UniProt accession: Q9ULW0

How should TPX2 Antibody, HRP conjugated be optimized for immunohistochemistry experiments?

When optimizing TPX2 Antibody, HRP conjugated for immunohistochemistry:

• Antigen retrieval: Use citrate buffer (pH 6.0) with heat-induced epitope retrieval for 20 minutes.

• Blocking: Block with 3-5% normal serum from the same species as the secondary antibody for 1 hour.

• Antibody dilution: Begin with manufacturer's recommended dilution (typically 1:100 to 1:500) and titrate as needed.

• Controls: Include both positive controls (tissues known to express TPX2, such as pancreatic cancer tissues ) and negative controls (omitting primary antibody).

• Signal development: Since this antibody is HRP-conjugated, use DAB as a substrate and monitor development time carefully.

• Counterstaining: Use hematoxylin for nuclear counterstaining to assess TPX2 localization.

For quantification, evaluate both intensity and percentage of positive cells, as demonstrated in studies examining TPX2 expression in neuroblastoma where the median was used as the cut-off point for defining high and low TPX2 expression .

What approaches can be used to validate TPX2 antibody specificity in experimental settings?

Multiple approaches should be employed to validate TPX2 antibody specificity:

• Western blot validation: Confirm single band at the expected molecular weight (~100 kDa for human TPX2).

• siRNA knockdown controls: Compare staining in cells with TPX2 knockdown versus controls to verify reduced signal, as performed in pancreatic cancer cell lines .

• Peptide competition assay: Pre-incubate antibody with excess immunizing peptide to demonstrate specific blocking of signal.

• Orthogonal method validation: Compare protein expression results with mRNA expression data using RT-qPCR.

• Multiple antibody validation: Use alternative TPX2 antibodies targeting different epitopes to confirm staining patterns.

• Subcellular localization assessment: Verify correct localization pattern (primarily nuclear during interphase and spindle-associated during mitosis).

How can researchers effectively design co-immunoprecipitation experiments to study TPX2 protein interactions?

For effective co-immunoprecipitation (co-IP) of TPX2 and its interacting partners:

• Lysis buffer optimization: Use a mild lysis buffer (e.g., 20 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% NP-40, 5% glycerol) supplemented with phosphatase and protease inhibitors to preserve native protein interactions.

• Timing considerations: Since TPX2 interactions are often cell cycle-dependent (particularly with AURKA), synchronize cells or harvest at specific cell cycle phases.

• Antibody selection: Choose antibodies that don't target interaction domains - for studying TPX2-AURKA interactions, avoid antibodies targeting the N-terminus of TPX2 (amino acids 1-43) which is critical for AURKA binding.

• Controls: Include IgG control, input lysate, and where possible, lysates from cells with TPX2 knockdown.

• Reciprocal co-IP: Confirm interactions by performing co-IP in both directions (TPX2 pulldown followed by AURKA detection and vice versa).

• Detergent sensitivity testing: Test different detergent conditions as some interactions may be sensitive to specific detergents.

This approach can help identify and characterize important interactions such as the significant linear correlation observed between TPX2 expression and AURKA expression in neuroblastoma studies .

How can TPX2 expression analysis be integrated with tumor microenvironment studies?

Integration of TPX2 expression analysis with tumor microenvironment studies should follow a multi-layered approach:

• Multiplex immunofluorescence: Perform co-staining of TPX2 with immune cell markers (CD4, CD8, CD68) to assess spatial relationships between TPX2-expressing tumor cells and tumor-infiltrating immune cells.

• Correlation analyses with immune signatures: Analyze correlations between TPX2 expression and:

  • Chemokines and chemokine receptors

  • Immune activation genes

  • Immunosuppressive genes

  • MHC genes (notably negative correlations in most cancers)

  • DNA methyltransferases

  • Mismatch repair proteins

• Single-cell RNA sequencing: Characterize TPX2 expression at single-cell resolution together with immune cell profiling to identify cell-specific functions.

• Functional validation: Use co-culture systems with TPX2-manipulated tumor cells and immune cells to assess functional interactions.

Research indicates that TPX2 expression correlates significantly with chemokine and chemokine receptor expression across multiple cancer types, suggesting important interactions between TPX2-expressing tumor cells and the immune microenvironment .

What methodologies are recommended for studying the relationship between TPX2 and therapeutic response in cancer models?

To study TPX2's relationship with therapeutic responses:

• Drug sensitivity correlation analyses:

  • Correlate TPX2 expression with IC50 values of various drugs using databases like CellMiner, CTRP, and GDSC

  • Data indicates TPX2 expression correlates negatively with sensitivity to certain drugs but positively with others

• Knockdown/overexpression studies:

  • Manipulate TPX2 expression in cancer cell lines using siRNA or CRISPR-Cas9

  • Assess changes in sensitivity to chemotherapeutic agents, particularly taxanes

  • Previous research demonstrated knockdown of TPX2 sensitized pancreatic cancer cells to paclitaxel treatment

• Patient-derived xenograft (PDX) models:

  • Stratify PDX models based on TPX2 expression levels

  • Compare treatment responses across stratified groups

  • Analyze changes in TPX2 expression before and after treatment

• Immunotherapy response prediction:

  • Analyze TPX2 expression in responders versus non-responders to immunotherapy

  • Data from urothelial cancer patients showed significant differences in TPX2 expression between responders and non-responders to atezolizumab (anti-PD-L1)

• Mechanistic studies:

  • Investigate changes in TPX2-dependent pathways (Aurora A activation, mitotic spindle formation) after drug treatment

  • Evaluate combinations of TPX2 targeting with conventional therapies

How can researchers design experiments to differentiate between the direct and indirect effects of TPX2 on Aurora Kinase A activity?

To differentiate between direct and indirect effects of TPX2 on AURKA:

• In vitro kinase assays:

  • Compare AURKA activity with and without recombinant TPX2

  • Use truncated TPX2 proteins (particularly examining the N-terminal 1-43 amino acids which directly activate AURKA)

  • Quantify AURKA autophosphorylation at Thr-288 under various conditions

• Mutation studies:

  • Introduce point mutations in the TPX2-binding domain of AURKA

  • Create TPX2 mutants that cannot bind AURKA

  • Compare the effects on AURKA activity and localization

• Proximity ligation assays (PLA):

  • Visualize and quantify direct TPX2-AURKA interactions in situ

  • Compare interaction patterns throughout cell cycle phases

• Fluorescence resonance energy transfer (FRET):

  • Create TPX2 and AURKA fusion proteins with appropriate fluorophores

  • Measure direct interactions in live cells under various conditions

• Sequential ChIP experiments:

  • Determine if TPX2 and AURKA co-occupy specific genomic regions

  • Differentiate between co-localization and functional interaction

• Allosteric inhibitor testing:

  • Develop and test compounds that specifically disrupt TPX2-AURKA binding

  • Compare with direct AURKA inhibitors

  • Research indicates that TPX2 binding to Aurora A affects the inhibitory activity of Aurora inhibitors by altering kinase conformation

How should researchers standardize TPX2 expression scoring in tumor samples for prognostic studies?

For standardized TPX2 expression scoring in tumor samples:

• Staining protocol standardization:

  • Fixed antibody dilution and incubation time

  • Standardized antigen retrieval method

  • Consistent detection system (HRP/DAB)

• Scoring system:

  • H-score method: Calculate as the product of staining intensity (0-3) and percentage of positive cells (0-100%), yielding a score of 0-300

  • Allred score: Combine proportion score (0-5) and intensity score (0-3) for a total score of 0-8

  • Cut-off determination: Use median value as demonstrated in neuroblastoma studies , or determine cut-offs using ROC curve analysis against survival outcomes

• Cellular localization assessment:

  • Nuclear vs. cytoplasmic staining

  • Spindle association during mitosis

  • Quantify abnormal localization patterns

• Digital pathology integration:

  • Use automated image analysis software for unbiased quantification

  • Train algorithms on pathologist-annotated samples

  • Validate algorithm against multiple independent cohorts

• Correlation with clinical parameters:

  • Age (higher expression in young patients in 9 tumor types)

  • Gender (variable by cancer type)

  • Tumor stage (significant associations in 10 tumor types)

How does TPX2 expression correlate with genetic alterations in different cancer types?

TPX2 expression demonstrates significant correlations with genetic alterations across multiple cancer types:

• MYCN amplification:

  • TPX2 mRNA expression significantly higher in neuroblastoma with MYCN gene amplification compared to single-copy MYCN tumors (P<0.0001 in TARGET-NB set; P=0.002 in validation set)

• Tumor mutational burden (TMB):

  • Positive correlation with TMB in 20 cancer types

  • Negative correlation in COAD (colon adenocarcinoma) and THYM (thymoma)

• Microsatellite instability (MSI):

  • Positive association with MSI in 9 cancer types

  • Negative association in COAD

• Neoantigen load:

  • Positive correlation with neoantigen burden in 10 cancer types

  • Negative correlation in COAD

• DNA repair mechanisms:

  • Positive correlation with mismatch repair (MMR) genes in most cancer types

  • Positive correlation with DNA methyltransferases across cancer types

These correlations suggest distinct mechanisms by which TPX2 may influence or be influenced by genomic instability in different tumor contexts, with important implications for targeted therapy approaches.

What is the evidence supporting TPX2 as a therapeutic target in specific cancer types?

Evidence supporting TPX2 as a therapeutic target includes:

• Pancreatic cancer:

  • TPX2 is expressed at high levels in pancreatic cancer cell lines with amplification of the TPX2 locus in some cases

  • TPX2 expression is upregulated in pancreatic tumors compared to normal tissue

  • Treatment with TPX2-targeting siRNAs reduced pancreatic cancer cell growth in tissue culture, induced apoptosis, and inhibited growth in soft agar and in nude mice

  • Knockdown of TPX2 sensitized pancreatic cancer cells to paclitaxel treatment

• Multiple solid tumors:

  • TPX2 overexpression correlates with poor prognosis across multiple cancer types

  • TPX2 acts as an oncogene in gastric cancer, colorectal carcinoma, and hepatocellular carcinoma

  • Its role in mitotic spindle assembly makes it a rational target for disrupting cancer cell division

• Immunotherapy connection:

  • In urothelial cancer, TPX2 expression differs significantly between responders and non-responders to atezolizumab (anti-PD-L1)

  • TPX2 correlates with immune cell infiltration markers in multiple tumor types

• Synergistic potential:

  • TPX2 targeting could synergistically combine with anti-mitotic agents like taxanes

  • TPX2 amplification is associated with resistance to Eg5/KSP inhibitors, suggesting targeting TPX2 may overcome this resistance

• Aurora kinase pathway:

  • TPX2 serves as a critical activator of Aurora A kinase

  • Blocking TPX2 binding to Aurora A may provide higher specificity than conventional kinase inhibitors

What are the most common technical challenges when using TPX2 Antibody, HRP conjugated, and how can they be addressed?

Common technical challenges and their solutions include:

• High background signal:

  • Increase blocking time (2 hours at room temperature)

  • Use 5% BSA instead of normal serum for blocking

  • Increase washing steps (5 washes of 5 minutes each)

  • Dilute antibody further (1:500 to 1:1000)

  • Use additional blocking agents for endogenous peroxidase (3% H₂O₂ for 10 minutes)

• Weak or absent signal:

  • Optimize antigen retrieval (try both citrate buffer pH 6.0 and EDTA buffer pH 9.0)

  • Decrease antibody dilution (1:50 to 1:100)

  • Increase incubation time (overnight at 4°C)

  • Ensure target protein is not degraded (fresh or properly stored samples)

  • Check for proper sample fixation (10% neutral buffered formalin for 24 hours)

• Non-specific binding:

  • Include 0.1-0.3% Triton X-100 in washing buffer

  • Use avidin/biotin blocking kit if using biotin-based detection

  • Pre-absorb antibody with non-specific proteins

  • Filter secondary antibody solutions before use

• Inconsistent staining patterns:

  • Standardize fixation times and conditions

  • Use positive control tissues in every experiment

  • Ensure consistent time from sectioning to staining

  • Use an automated staining platform if available

• Cell cycle-dependent detection issues:

  • Synchronize cells when studying TPX2 in cell culture

  • Note that TPX2 localization and levels change dramatically during cell cycle progression

How can discrepancies between TPX2 protein levels and mRNA expression be effectively investigated and explained?

To address discrepancies between TPX2 protein and mRNA levels:

• Time-course experiments:

  • Measure both protein and mRNA at multiple time points

  • Assess for temporal delays between transcription and translation

• Post-transcriptional regulation assessment:

  • Analyze microRNA targeting TPX2 mRNA

  • Examine RNA-binding proteins that may stabilize or destabilize TPX2 mRNA

  • Investigate alternative splicing using PCR with isoform-specific primers

• Post-translational modification analysis:

  • Assess ubiquitination status of TPX2 protein

  • Measure protein half-life in different conditions

  • Examine phosphorylation states using phospho-specific antibodies

• Technical validation:

  • Use multiple methodologies for protein detection (western blot, immunofluorescence, ELISA)

  • Employ different primer sets for mRNA detection

  • Ensure antibodies detect all relevant isoforms of TPX2

• Cellular compartmentalization:

  • Perform subcellular fractionation to assess protein localization

  • Compare total protein versus nuclear/cytoplasmic distribution

• Cell cycle synchronization:

  • Analyze expression in synchronized cell populations

  • TPX2 demonstrates significant cell cycle-dependent regulation

What controls and validation steps are essential when studying TPX2 function using genetic knockdown or knockout approaches?

Essential controls and validation steps for TPX2 genetic manipulation studies:

• Knockdown validation:

  • Confirm reduction at both mRNA level (qRT-PCR) and protein level (western blot)

  • Use multiple siRNA sequences to reduce off-target effects

  • Include non-targeting siRNA control

  • Quantify knockdown efficiency (typically aim for >70% reduction)

• Rescue experiments:

  • Re-express siRNA-resistant TPX2 to confirm phenotype specificity

  • Use both wild-type and mutant versions (e.g., Aurora A binding-deficient mutant)

  • Ensure expression levels similar to endogenous protein

• Phenotypic validation:

  • Assess proliferation rates (as demonstrated in pancreatic cancer studies )

  • Evaluate mitotic spindle formation via immunofluorescence

  • Quantify cell cycle distribution using flow cytometry

  • Measure apoptosis induction (as observed in pancreatic cancer cells )

• Specificity controls:

  • Monitor expression of related proteins (e.g., Aurora A)

  • Assess potential compensatory mechanisms

  • Evaluate expression of downstream targets

• Time-dependent analysis:

  • Observe acute versus chronic effects of TPX2 depletion

  • Consider inducible knockdown/knockout systems for temporal control

• Functional readouts:

  • Mitotic index assessment

  • Spindle morphology evaluation

  • Centrosome number quantification

  • Chromosomal segregation error rate

  • Drug sensitivity testing (particularly to anti-mitotic agents like paclitaxel )

Through careful experimental design incorporating these controls and validation steps, researchers can gain reliable insights into TPX2 function in normal and pathological contexts.