TFPT Antibody

What is TFPT and why is it significant in research?

TFPT (TCF3 fusion partner) is a component of the chromatin-remodeling INO80 complex implicated in crucial cellular functions including DNA repair, checkpoint regulation, DNA replication, telomere maintenance, and chromosome segregation. It's also known as FB1 or Amida and appears to promote apoptosis in a TP53/p53-independent manner. TFPT gained significance in oncology research as one of three fusion partners of the E2A gene, with E2A-TFPT/FB1 fusion being a recurrent feature in pre-B Acute Lymphoblastic Leukemias (ALLs) . Though expressed at low levels in various human tissues, including hemopoietic cell lines from different lineages, its precise function remains largely uncharacterized as database sequence comparisons have failed to reveal strong homology with known proteins .

How should I select the appropriate TFPT antibody for my experimental design?

Selection should be based on several hierarchical considerations:

• Experimental application: Different antibodies are optimized for specific applications such as Western Blot (WB), Immunofluorescence (IF), Immunohistochemistry (IHC), or Flow Cytometry (FACS)

• Species reactivity: Confirm reactivity with your model organism (human, mouse, rat)

• Epitope specificity: Consider whether you need to target specific domains (N-terminal, C-terminal)

• Validation status: Prioritize antibodies with publications or validation data in your application

• Clonality: Polyclonal antibodies often provide broader epitope recognition, while monoclonals offer consistency between lots

For example, if investigating TFPT in human tissues via IHC, the ABIN6775870 antibody shows validated reactivity to human TFPT with specific optimization for IHC applications . For mouse-based studies, consider the 10097-2-AP antibody that demonstrates robust reactivity in both human and mouse samples .

What controls should I include when using TFPT antibodies for the first time?

A comprehensive validation requires several controls:

For newly developed or non-commercial antibodies, additional validation should include dilution range tests of primary antibody (1:500 to 1:10,000), secondary antibody (1:500, 1:1,000, and 1:2,500), and target protein (1, 5, and 25 μg) to demonstrate specificity . When possible, include at least one full blot as supplemental data to demonstrate antibody specificity .

What are the recommended protocols for TFPT antibody use in Western Blot analysis?

For optimal Western Blot results with TFPT antibodies:

• Sample preparation: Extract proteins using RIPA or NP-40 lysis buffers containing protease inhibitors

• Loading control: 20-30 μg total protein per lane for cell lysates

• Dilution ratio: Typically 1:500-1:2000 for primary antibody

• Incubation conditions: Overnight at 4°C for primary antibody, 1-2 hours at room temperature for secondary

• Detection method: ECL systems work well with HRP-conjugated secondaries

• Expected band: TFPT appears at approximately 29 kDa

Note that TFPT has a calculated molecular weight of 28-29 kDa, which aligns with the observed molecular weight in most experimental contexts . Always perform validation with positive controls such as K-562 or HL-60 cell lysates to confirm proper detection .

How should I design a flow cytometry panel including TFPT antibody?

When integrating TFPT antibody in flow cytometry panels:

• Panel hierarchy: Define marker tiers (primary phenotypic markers, secondary activation markers, tertiary analysis markers)

• Fluorochrome selection: Match TFPT expression level with appropriate brightness - as TFPT is typically expressed at low levels, use brighter fluorochromes (PE, APC, BV421)

• Compensation: Include single-stained controls for each fluorochrome

• Pre-staining preparation:

  • Block Fc receptors using Purified Human IgG-Fc Fragment or normal serum prior to antibody application

  • For intracellular TFPT detection, perform cell surface staining before fixation/permeabilization

• Antibody titration: Perform titration experiments (typically starting at 1:50-1:200) to determine optimal signal-to-noise ratio

Remember that panel design should avoid using similar fluorophores on co-expressed markers and match fluorophore brightness to antigen expression levels . When working with TFPT, consider its intracellular localization, which will require permeabilization steps.

What are the critical parameters for successful immunohistochemistry with TFPT antibodies?

For reproducible IHC results with TFPT antibodies:

• Fixation: 10% neutral buffered formalin, 24 hours maximum

• Antigen retrieval: TE buffer pH 9.0 gives optimal results, though citrate buffer pH 6.0 can be used as an alternative

• Blocking: 5-10% normal serum (matched to secondary antibody species) with 1% BSA

• Antibody dilution: 1:50-1:500 range, with exact dilution requiring optimization for each tissue type

• Detection system: Polymer-based detection systems offer higher sensitivity for low-abundance targets

• Counterstain: Hematoxylin provides good nuclear contrast

The recommended tissue for positive control is mouse liver, which has been documented to show specific TFPT staining . When performing IHC on human samples, remember that TFPT expression levels vary across tissues and may be elevated in certain cancer types.

How can I validate antibody specificity when contradictory results emerge between different TFPT antibodies?

When faced with discrepancies between antibodies:

• Epitope mapping: Compare the immunogens used to generate each antibody - differences may indicate recognition of distinct protein domains or isoforms

• Cross-validation techniques: Employ orthogonal methods:

  • Mass spectrometry to confirm protein identity

  • RNA interference to correlate protein reduction with signal decrease

  • Recombinant expression of tagged TFPT to confirm antibody recognition

• Structural considerations: Use computational modeling tools like tFold-Ag to predict antibody-antigen complex structures and potential binding interfaces

• Literature reconciliation: Systematically review published data for each antibody clone

• Multiple antibody approach: Use at least two antibodies targeting different epitopes in parallel experiments

For TFPT specifically, consider that post-translational modifications might affect epitope accessibility in different experimental contexts. Antibodies raised against different regions (N-terminal vs. C-terminal) may yield different results depending on protein interactions or complex formation within the INO80 complex .

What strategies can address non-specific binding in TFPT immunodetection assays?

Persistent non-specific binding can be addressed through:

• Optimization of blocking conditions:

  • Test different blocking agents (BSA, casein, non-fat milk)

  • Extend blocking time (2-3 hours at room temperature)

  • Include 0.1-0.3% Triton X-100 or 0.05% Tween-20 in blocking buffer

• Stringent washing:

  • Increase wash buffer volume and duration

  • Add detergents or salt to increase stringency

• Antibody optimization:

  • Further dilute primary antibody

  • Reduce incubation temperature (4°C overnight instead of room temperature)

  • Use affinity-purified antibodies

• Fc receptor blocking:

  • When working with immune cells, pre-incubate with dedicated FcR blocking agent before adding TFPT-specific antibody

• Secondary antibody selection:

  • Use highly cross-adsorbed secondary antibodies

  • Consider fragment antibodies (F(ab')2) to reduce Fc-mediated binding

For TFPT detection in cell lines with high endogenous Fc receptor expression, such as macrophages or B cells, implementing an Fc receptor blocking step is essential to prevent false positive results .

How can computational approaches enhance TFPT antibody design and epitope prediction?

Recent computational advances offer new possibilities for antibody research:

• Structural prediction: Tools like tFold-Ag can predict the structure of antibody-antigen complexes with high accuracy (TM-score of 0.708)

• Epitope mapping: Computational epitope prediction can identify optimal antigenic regions for antibody development

• Antibody optimization:

  • In silico affinity maturation through targeted mutations

  • Prediction of cross-reactivity with homologous proteins

• High-throughput screening: Virtual screening of candidate antibodies against TFPT can prioritize candidates for experimental validation

• Ensemble strategies: Combining predictions from multiple models (like tFold-Ag and AlphaFold-Multimer) can enhance accuracy from 0.217 to 0.288 DockQ score

These computational approaches are particularly valuable for TFPT antibody development given the protein's role in chromatin remodeling complexes, where structural biology approaches like crystallography may be challenging due to complex formation .

How can TFPT antibodies be utilized in leukemia research models?

Given TFPT's association with childhood leukemia through E2A-TFPT fusion:

• Fusion protein detection: Specialized antibodies targeting the fusion junction can specifically identify leukemic cells harboring the translocation

• Differential diagnosis: Immunophenotyping panels incorporating TFPT antibodies may help classify leukemia subtypes

• Minimal residual disease: Highly sensitive detection methods using TFPT antibodies could monitor treatment response

• Mechanistic studies:

  • Co-immunoprecipitation with TFPT antibodies can identify novel interaction partners

  • ChIP-seq using TFPT antibodies can map chromatin association patterns

• Therapeutic applications: Development of antibody-drug conjugates (ADCs) similar to the approach used for tissue factor (TF) could target TFPT-expressing leukemic cells

Research suggests that E2A-TFPT/FB1 fusion appears to be a recurrent feature of pre-B ALLs, indicating its potential value as a diagnostic or therapeutic target . When designing experiments, consider using cell lines known to express TFPT such as K-562 or HL-60 .

What methodological considerations apply when using TFPT antibodies in patient-derived xenograft (PDX) models?

When incorporating TFPT antibodies in PDX research:

• Species cross-reactivity: Confirm whether your TFPT antibody recognizes both human and mouse TFPT to differentiate tumor cells from stromal components

• Heterogeneous expression: Account for variable TFPT expression levels within tumors - some PDX models may show TFPT expression in only 25-50% of tumor cells

• Antibody penetration: Optimize tissue processing for improved antibody access in solid tumor masses

• Multiplexed analysis:

  • Combine TFPT staining with lineage markers for comprehensive tumor characterization

  • Consider sequential immunofluorescence for co-localization studies

• Quantification methods: Establish consistent scoring systems for TFPT positivity (H-score, Allred score, or digital image analysis)

The success of antibody-based therapies in PDX models with heterogeneous target expression suggests that TFPT-targeted approaches may be effective even when the protein is not uniformly expressed throughout the tumor .

What quality control measures ensure reproducibility when working with TFPT antibodies across different research groups?

To enhance reproducibility:

• Detailed antibody reporting:

  • Record complete antibody information (catalog number, lot, concentration, host)

  • Document dilution factors and incubation conditions

  • Archive original uncropped blots with molecular weight markers

• Validation across lot numbers:

  • Test new antibody lots against previous lots

  • Maintain frozen aliquots of working antibody dilutions

• Standardized protocols:

  • Establish SOPs for sample preparation, staining, and analysis

  • Include timing details for critical steps

• Reference standards:

  • Use consistent positive controls across experiments

  • Consider developing stabilized reference samples

• Documentation of imaging parameters:

  • For IF/IHC, record exposure times, gain settings, and post-processing

  • For flow cytometry, document voltage settings and compensation matrices

As recommended by journals, provide at least one representative full blot as supplemental data for reviewers when publishing, detailing the validation of each TFPT antibody used to demonstrate protein specificity .

How should I approach conflicting data from different lots of the same TFPT antibody?

When facing lot-to-lot variability:

• Systematic comparison:

  • Run side-by-side experiments with both lots

  • Quantify signal intensity across a dilution series

  • Assess background levels on negative controls

• Epitope verification:

  • Confirm that both lots recognize the same epitope

  • Check for potential changes in antibody production methods

• Application-specific validation:

  • Re-validate new lots specifically for your application

  • Adjust dilutions to match signal strength of previous lots

• Extended controls:

  • Include additional positive and negative controls

  • Perform peptide competition assays with both lots

• Manufacturer communication:

  • Report discrepancies to the manufacturer

  • Request technical support and validation data

For research continuity, consider purchasing multiple vials of the same TFPT antibody lot for long-term studies, and store according to manufacturer recommendations (typically at -20°C with 50% glycerol) .