FAM13A Antibody, HRP conjugated

What is FAM13A and why is it important in research?

FAM13A (Family with sequence similarity 13, member A) is a protein that has been associated with non-small cell lung cancer (NSCLC) through genome-wide association studies. It exists in multiple isoforms, with one containing a RhoGAP domain that plays a significant role in cellular functions. FAM13A is involved in tumor cell proliferation and migration, making it an important target for cancer research. Studies have shown increased numbers of FAM13A protein-expressing cells in the tumoral region of lung tissues from patients with NSCLC, indicating its relevance in cancer development . Additionally, FAM13A has been found to correlate inversely with CTLA4 and directly with HIF1α levels in control regions of NSCLC patients, suggesting its involvement in immune regulation within the tumor microenvironment .

What are the common applications for FAM13A antibodies in research?

FAM13A antibodies are versatile research tools with multiple validated applications:

FAM13A antibodies can be used to study protein expression patterns in various tissues, localize the protein within cells, and quantify expression levels . These applications are particularly valuable for investigating FAM13A's role in disease states such as NSCLC. When using HRP-conjugated versions, researchers benefit from direct enzyme-linked detection capabilities that eliminate the need for secondary antibodies in certain applications.

What is the expected molecular weight of FAM13A in Western blot analysis?

While the calculated molecular weight of FAM13A is 117 kDa based on amino acid sequence, researchers should note that the observed molecular weight in Western blot analysis is typically around 65 kDa . This discrepancy between calculated and observed molecular weights is important to understand when interpreting Western blot results. The difference may be attributed to several factors including post-translational modifications, proteolytic processing, alternative splicing of the protein, or the specific isoform being detected. FAM13A has multiple isoforms, including the full-length protein and shorter variants that contain the RhoGAP domain . Researchers should be aware of this difference when designing experiments and analyzing results to avoid misinterpretation of bands on Western blots.

How does FAM13A expression correlate with T cell function in the tumor microenvironment?

FAM13A demonstrates complex relationships with T cell populations that vary between effector and regulatory phenotypes. Research has shown that FAM13A RhoGAP is consistently downregulated in CD4+CD25+Foxp3+ T regulatory cells while being upregulated in CD4+CD25- T effector cells that express Tbet . This pattern suggests FAM13A may play a role in T cell differentiation or function.

In the context of the tumor microenvironment:

• FAM13A inversely correlates with CTLA4 expression in the control lung region of NSCLC patients, but this correlation is lost in tumoral regions

• FAM13A positively correlates with HIF1α expression in control lung regions of NSCLC patients

• HIF1α is known to inhibit regulatory T cell development by degrading Foxp3

These findings suggest FAM13A may be associated with antitumor effector T cell function, particularly in oxygen-depleted regions surrounding growing tumors. The relationship between FAM13A and immune checkpoint molecules like CTLA4 makes this protein particularly relevant for immunotherapy research. When investigating these relationships, HRP-conjugated FAM13A antibodies can provide sensitive detection in tissue sections to visualize spatial relationships between FAM13A-expressing cells and T cell populations.

What is the role of FAM13A RhoGAP domain in cellular migration and metastasis?

The RhoGAP domain of FAM13A plays a critical role in regulating cellular migration and potential metastatic behavior in cancer cells. Experimental evidence reveals:

• In scratch assays with A549 lung adenocarcinoma cells, siRNA targeting FAM13A resulted in decreased cell density and numbers while affecting migration patterns

• Silencing FAM13A through siRNA downregulated both FAM13A isoforms, including the RhoGAP-containing isoform

• FAM13A inhibition reduced expression of growth receptors like EGFR and TGFβRII as well as AKT signaling

These findings indicate that FAM13A, particularly through its RhoGAP domain, functions in regulating Rho-dependent pathways involved in cellular migration. The RhoGAP domain likely modulates the activity of Rho GTPases, which are key regulators of cytoskeletal dynamics and cell movement. Interestingly, variants in the FAM13A gene, especially those affecting the RhoGAP domain in exons 2-5, may confer tumor suppressive functions and have been associated with reduced risk of both COPD and lung cancer .

When studying these migration effects, researchers can utilize HRP-conjugated FAM13A antibodies for sensitive detection of protein localization during migration assays.

How does FAM13A interact with TGFβ signaling in cancer progression?

FAM13A demonstrates a complex, bidirectional regulatory relationship with TGFβ that impacts cancer cell proliferation and migration:

This creates an autoregulatory loop where:

• TGFβ suppresses FAM13A expression, inhibiting proliferation

• siRNA knockdown of FAM13A induces TGFβ levels

• FAM13A inhibits TGFβ function via suppression of TGFβRII

• During cellular migration, TGFβ accelerates this process by inducing the FAM13A RhoGAP isoform

This complex interaction has significant implications for understanding cancer progression, as it suggests FAM13A may serve as a switch between proliferative and migratory phenotypes in cancer cells. Researchers investigating these pathways can use HRP-conjugated FAM13A antibodies in Western blots to quantify protein expression changes under various TGFβ treatment conditions.

What are the optimal conditions for using HRP-conjugated FAM13A antibodies in Western blot analysis?

When using HRP-conjugated FAM13A antibodies for Western blot analysis, researchers should consider the following technical parameters for optimal results:

• Sample Preparation: Based on validated applications, mouse kidney, lung, ovary, and pancreas tissues have shown positive results in Western blot using FAM13A antibodies . Human samples should be similarly effective.

• Loading Control Selection: When studying FAM13A (observed at ~65 kDa despite a calculated 117 kDa) , choose loading controls that don't migrate at similar molecular weights to avoid band overlap.

• Blocking and Antibody Dilution:

  • Use 5% non-fat dry milk or BSA in TBST for blocking

  • For primary antibody (when not using direct HRP-conjugated versions): 1:500-1:1000 dilution is recommended

  • For HRP-conjugated FAM13A antibodies: Start with manufacturer's recommended dilution, typically 1:1000-1:5000

• Detection Considerations:

  • HRP-conjugated antibodies eliminate the need for secondary antibody incubation

  • Use enhanced chemiluminescence (ECL) substrates appropriate for the expected expression level

  • For low abundance detection, consider using high-sensitivity ECL substrates

• Expected Results: Look for a predominant band at approximately 65 kDa , though additional bands may represent other FAM13A isoforms.

Titration experiments are recommended to determine optimal antibody concentration for specific experimental conditions, as signal-to-noise ratio can vary based on tissue type and expression levels.

How should researchers optimize immunohistochemistry protocols for FAM13A detection in tissue samples?

Optimizing immunohistochemistry protocols for FAM13A detection requires attention to several critical parameters:

• Tissue Preparation and Antigen Retrieval:

  • For formalin-fixed, paraffin-embedded tissues, heat-induced epitope retrieval is recommended

  • TE buffer pH 9.0 is suggested as the primary antigen retrieval method

  • Alternatively, citrate buffer pH 6.0 may be used

• Blocking and Antibody Parameters:

  • Block with normal serum matching the host species of the secondary antibody (not needed with direct HRP-conjugation)

  • Recommended dilution range: 1:20-1:200 for standard IHC applications

  • For HRP-conjugated antibodies, start with a 1:100 dilution and optimize as needed

• Visualization System:

  • With HRP-conjugated antibodies, proceed directly to chromogenic detection

  • DAB (3,3'-diaminobenzidine) provides a brown precipitate with excellent stability

  • AEC (3-amino-9-ethylcarbazole) offers a red precipitate that may provide better contrast in certain tissues

• Positive Control Selection:

  • Human skeletal muscle and tonsil tissues have been validated for positive FAM13A expression

  • Lung tissue from NSCLC patients shows increased FAM13A expression in tumoral regions

• Counterstaining and Mounting:

  • Light hematoxylin counterstaining helps visualize tissue architecture

  • Use aqueous mounting medium with AEC or permanent mounting with DAB

The protocol should be optimized for each specific tissue type, as FAM13A expression varies across tissues and may be influenced by pathological conditions such as cancer.

What controls should be included when using FAM13A antibodies in immunofluorescence studies?

When conducting immunofluorescence studies with FAM13A antibodies, proper controls are essential for result validation and interpretation:

• Primary Antibody Controls:

  • Positive Control: Include HeLa cells, which have been validated for FAM13A detection

  • Negative Control: Omit primary antibody while maintaining all other steps

  • Isotype Control: Use non-specific IgG from the same host species and at the same concentration

• Specificity Controls:

  • siRNA Knockdown Control: Cells treated with FAM13A siRNA should show reduced staining compared to non-targeting siRNA

  • Blocking Peptide Control: Pre-incubation of antibody with immunizing peptide should abolish specific staining

• Technical Controls:

  • Autofluorescence Control: Examine unstained samples to identify any intrinsic fluorescence

  • Cross-reactivity Control: In multi-color experiments, include single-stained samples to confirm absence of bleed-through

• Biological Validation Controls:

  • Known Expression Pattern: Compare staining pattern to published subcellular localization data

  • Physiological Context Control: Include samples where FAM13A expression is expected to change (e.g., hypoxic conditions that induce HIF1α )

• Quantification Controls:

  • Dynamic Range Control: Include samples with known high and low expression levels

  • Technical Replicate: Perform staining in triplicate to ensure reproducibility

For the specific case of HRP-conjugated FAM13A antibodies in immunofluorescence, a tyramide signal amplification approach can be used, where the HRP catalyzes deposition of fluorescent tyramide. In this case, additional enzyme activity controls should be included.

How can researchers address specificity concerns when using FAM13A antibodies?

Addressing specificity concerns with FAM13A antibodies requires a multi-faceted approach:

• Genetic Validation:

  • Perform siRNA knockdown experiments targeting FAM13A, which should reduce or eliminate specific signal

  • If possible, use CRISPR/Cas9 knockout cells or tissues as definitive negative controls

• Molecular Weight Verification:

  • Be aware that while the calculated molecular weight of FAM13A is 117 kDa, the observed molecular weight is typically 65 kDa

  • Multiple bands may represent different isoforms, including the RhoGAP-containing variant

• Cross-Reactivity Assessment:

  • Test the antibody in samples known to lack FAM13A expression

  • Verify species reactivity (known to react with human and mouse samples)

• Comparison of Multiple Antibodies:

  • Use antibodies targeting different epitopes of FAM13A to confirm results

  • Compare polyclonal and monoclonal antibodies when available

• Peptide Competition Assay:

  • Pre-incubate the antibody with excess immunizing peptide, which should block specific binding

• Technical Controls:

  • Include recombinant FAM13A protein as a positive control when possible

  • For HRP-conjugated antibodies, include enzyme activity controls

By implementing these validation approaches, researchers can confidently interpret their results and address reviewer concerns regarding antibody specificity.

What approaches should be used to accurately quantify FAM13A expression in different experimental conditions?

Accurate quantification of FAM13A expression requires selecting appropriate methods based on experimental goals:

• Western Blot Quantification:

  • Use technical replicates (minimum n=3) for statistical analysis

  • Include gradient standards of recombinant FAM13A protein if absolute quantification is needed

  • Normalize to appropriate loading controls (β-actin, GAPDH, or tubulin)

  • Use software like ImageJ for densitometric analysis

  • Account for both FAM13A isoforms in quantification (full-length and RhoGAP-containing)

• Immunohistochemistry Quantification:

  • Develop a clear scoring system (e.g., H-score, Allred score)

  • Count positive cells as a percentage of total cells in multiple high-power fields

  • Use digital pathology software for automated quantification when possible

  • Consider both staining intensity and percentage of positive cells

• Immunofluorescence Quantification:

  • Measure mean fluorescence intensity across multiple cells

  • Analyze subcellular distribution patterns

  • Use Z-stack imaging to capture complete cellular volume

  • Apply consistent thresholding methods across all samples

• RT-qPCR for mRNA Quantification:

  • Design primers specific to different FAM13A isoforms, particularly distinguishing between isoforms with and without the RhoGAP domain

  • Use validated reference genes for normalization

  • Apply the 2^-ΔΔCt method for relative quantification

• Experimental Condition Considerations:

  • Include time course experiments when studying dynamic processes like TGFβ-induced changes

  • Account for hypoxia effects, as FAM13A correlates with HIF1α

  • Consider cell density effects on FAM13A expression

For optimal results, researchers should combine multiple quantification approaches to corroborate findings across different methodological platforms.

How can researchers interpret contradictory results between FAM13A protein and mRNA expression?

Discrepancies between FAM13A protein and mRNA expression levels are not uncommon and can provide valuable insights into regulatory mechanisms. Researchers should consider several factors when encountering such contradictions:

• Post-transcriptional Regulation:

  • MicroRNAs might target FAM13A mRNA, reducing protein without affecting mRNA levels

  • RNA-binding proteins could alter mRNA stability or translation efficiency

  • Alternative splicing may produce multiple protein isoforms from the same transcript

• Post-translational Modifications:

  • Protein stability may be affected by ubiquitination or other degradation signals

  • Functional activity might be regulated through phosphorylation without changing expression levels

  • The RhoGAP domain's activity may be regulated separately from protein abundance

• Technical Considerations:

  • Antibody specificity might detect only certain isoforms or modified forms of FAM13A

  • The observed 65 kDa band versus calculated 117 kDa might represent specific detection limitations

  • Primer design in qPCR might amplify specific transcript variants but not others

• Biological Context:

  • TGFβ signaling has been shown to suppress both FAM13A isoforms while affecting cell function

  • Hypoxic conditions influencing HIF1α levels may affect protein translation efficiency

  • Cell-type specific regulatory mechanisms may exist (e.g., different in T cells versus tumor cells)

• Interpretative Framework:

  • Time-course experiments may reveal delays between mRNA changes and protein expression

  • Consider feedback loops, such as the autoregulatory relationship between FAM13A and TGFβ

  • Cellular localization changes might occur without total protein level changes

When reporting such discrepancies, researchers should present both protein and mRNA data with appropriate controls and discuss potential biological mechanisms explaining the differences rather than dismissing them as technical artifacts.

How might FAM13A serve as a biomarker or therapeutic target in NSCLC and other diseases?

FAM13A shows significant potential as both a biomarker and therapeutic target based on current research findings:

• Biomarker Applications:

  • Diagnostic Potential: Increased FAM13A expression has been observed in tumoral regions of NSCLC patient samples

  • Prognostic Indicator: The relationship between FAM13A and tumor cell proliferation suggests possible value in predicting disease progression

  • Therapeutic Response Prediction: The inverse correlation with CTLA4 in control regions might predict immunotherapy response

• Therapeutic Target Considerations:

  • RhoGAP Domain Modulation: Targeting the RhoGAP domain could potentially inhibit tumor cell migration

  • TGFβ-FAM13A Axis: Disrupting the autoregulatory loop between FAM13A and TGFβ might suppress tumor growth

  • Immunotherapeutic Context: The relationship with effector T cells suggests potential synergies with immune checkpoint inhibitors

• Dual-Disease Relevance:

  • COPD-Lung Cancer Connection: FAM13A variants have been associated with reduced risk of both COPD and lung cancer, suggesting common mechanistic pathways

  • Potential for Preventive Interventions: Understanding protective variants might lead to preventive approaches

• Technical Approaches for Biomarker Development:

  • Develop standardized IHC scoring systems for FAM13A in clinical samples

  • Investigate circulating FAM13A protein or mRNA as non-invasive biomarkers

  • Combine with other markers for improved sensitivity/specificity

• Therapeutic Development Strategies:

  • siRNA approaches have shown promise in inhibiting tumor cell proliferation

  • Small molecule inhibitors targeting the RhoGAP domain could be developed

  • Combination approaches with TGFβ pathway modulators might provide synergistic effects

The complex roles of FAM13A in both immune function and tumor cell biology suggest multiple avenues for translational development, though additional validation studies would be needed before clinical implementation.

What are the most promising techniques for studying FAM13A protein-protein interactions in living cells?

Understanding FAM13A's protein interaction network is crucial for deciphering its functions in health and disease. Several advanced techniques offer promising approaches:

• Proximity-Based Labeling Techniques:

  • BioID/TurboID: Fusion of biotin ligase to FAM13A enables biotinylation of proximal proteins

  • APEX2: Peroxidase-based labeling allows temporally controlled identification of interaction partners

  • Applications: These methods are particularly useful for identifying RhoGAP domain interactions with GTPases and potential novel binding partners

• Fluorescence-Based Interaction Studies:

  • Förster Resonance Energy Transfer (FRET): Enables real-time visualization of FAM13A interactions with suspected partners like Rho GTPases

  • Bimolecular Fluorescence Complementation (BiFC): Allows visualization of interaction-dependent fluorophore reconstitution

  • Fluorescence Correlation Spectroscopy (FCS): Provides quantitative binding parameters in living cells

• Optogenetic Approaches:

  • Light-inducible dimerization: Controls FAM13A interactions with temporal precision

  • Optogenetic activation of RhoGAP domain: Enables study of downstream signaling events

  • Applications: Particularly valuable for understanding the kinetics of FAM13A-mediated regulation

• Live-Cell Protein Complementation Assays:

  • NanoBiT/NanoLuc: Split luciferase complementation provides sensitive detection of protein interactions

  • Split-GFP: Allows visualization of interactions with minimal disruption to protein function

  • Applications: Useful for monitoring dynamic changes in FAM13A interactions during processes like TGFβ stimulation

• Advanced Microscopy Techniques:

  • Single-molecule tracking: Monitors FAM13A dynamics and interactions at the single-molecule level

  • Lattice light-sheet microscopy: Enables 3D visualization of interactions with minimal phototoxicity

  • Applications: Particularly valuable for understanding spatial regulation of FAM13A in migration studies

These techniques can be applied to investigate the interactions suggested by current research, including FAM13A relationships with TGFβ signaling components, HIF1α, and cytoskeletal regulators involved in migration.