FAM83D Antibody, FITC conjugated

What is FAM83D and what are its primary cellular functions?

FAM83D (Family with sequence similarity 83, member D, also known as spindle protein CHICA or C20orf129) is a protein that localizes to the mitotic spindle and plays critical roles in proper spindle positioning and timely cell division. FAM83D functions by:

• Recruiting Casein Kinase 1α (CK1α) to the mitotic spindle, which is essential for proper spindle function

• Interacting with chromokinesin KIF22 to ensure proper chromosome congression and alignment during mitosis

• Participating in cell proliferation through activation of the ERK1/ERK2 signaling cascade

• Potentially regulating various signaling pathways including MAPK, TGF-β, and Hippo signaling

FAM83D demonstrates cell cycle-dependent interactions, with several proteins binding exclusively during mitosis, which explains its crucial role in cellular division processes .

Why is FAM83D significant in cancer research?

FAM83D has emerged as an important protein in cancer research due to its:

These characteristics make FAM83D a potential oncotarget gene and biomarker for various cancers .

What are the best methods for detecting FAM83D expression in experimental systems?

Detection of FAM83D expression can be accomplished through several complementary techniques:

For mRNA detection:

• Semi-quantitative RT-PCR offers initial screening capabilities

• Real-time RT-PCR provides quantitative assessment of gene expression relative to control genes (e.g., ACTB)

• RNA sequencing for genome-wide expression analysis and identification of potential associations with other genes

For protein detection:

• Western blotting using validated anti-FAM83D antibodies (typical band expected at ~45 kDa)

• Immunohistochemistry (IHC) on tissue sections or tissue microarrays

• Immunofluorescence (IF) to visualize subcellular localization, particularly during mitosis

• Flow cytometry for quantitative assessment in cell populations

When investigating FAM83D expression in cancer contexts, it's advisable to compare expression with both adjacent non-cancerous tissues and normal tissue controls from healthy individuals .

What are optimal methods for FAM83D functional analysis in cellular systems?

To investigate FAM83D functions in experimental systems, researchers employ:

Gene knockdown/knockout approaches:

• siRNA transfection for transient knockdown of FAM83D expression

• shRNA for stable knockdown through lentiviral delivery systems

• CRISPR/Cas9-mediated genome editing for complete knockout

• Rescue experiments by reintroducing wild-type or mutant FAM83D in knockout cells

Functional assays:

• Colony formation assays to assess effects on cell proliferation and survival

• Wound healing and Transwell assays to evaluate cell migration and invasion

• Sphere formation assays to evaluate cancer stem cell properties

• Caspase3/7 apoptosis assays to determine effects on programmed cell death

• Xenograft tumorigenesis models to assess in vivo growth and metastasis

Protein interaction studies:

• Co-immunoprecipitation (co-IP) to identify protein-protein interactions

• Mass spectrometry of immunoprecipitates to identify novel interacting partners

• Yeast two-hybrid screening to discover potential interactions

What are the advantages of using FITC-conjugated FAM83D antibodies over unconjugated antibodies?

FITC-conjugated FAM83D antibodies offer several distinct advantages:

• Direct detection: Eliminates the need for secondary antibodies, reducing background signal and potential cross-reactivity issues14

• Simplified protocols: Reduces the number of steps in immunofluorescence and flow cytometry procedures

• Multiplex compatibility: Allows for simultaneous detection of multiple proteins when combined with other fluorophores with different emission spectra

• Standardization: Provides consistent fluorophore-to-antibody ratios compared to secondary antibody detection methods

• Time efficiency: Shortens experimental protocols by eliminating secondary antibody incubation and washing steps

What are the optimal protocols for using FITC-conjugated FAM83D antibodies in different experimental applications?

For Immunofluorescence (IF) microscopy:

• Fix cells using 4% paraformaldehyde in PBS (15 minutes, room temperature)

• Permeabilize with 0.1% Triton X-100 in PBS (10 minutes)

• Block with 3% BSA in PBS (1 hour, room temperature)

• Incubate with FITC-conjugated FAM83D antibody at 1:50-1:200 dilution in blocking buffer (overnight at 4°C or 2 hours at room temperature)

• Wash 3x with PBS

• Counterstain nuclei with DAPI (1 μg/ml, 5 minutes)

• Mount with anti-fade mounting medium

• Image using appropriate filter sets for FITC (excitation ~495 nm, emission ~520 nm)

For Flow Cytometry:

• Harvest cells and wash with FACS buffer (PBS + 2% FBS)

• For intracellular staining: fix and permeabilize cells using commercial kits

• Block with 2% BSA in FACS buffer (30 minutes, 4°C)

• Incubate with FITC-conjugated FAM83D antibody at 1:50-1:200 dilution (30-60 minutes, 4°C, protected from light)

• Wash 2x with FACS buffer

• Analyze using flow cytometer with 488 nm laser and appropriate emission filters

• Include appropriate isotype control at the same concentration as the primary antibody

For Immunohistochemistry (IHC):

• Deparaffinize and rehydrate FFPE tissue sections

• Perform antigen retrieval (citrate buffer pH 6.0, 95°C, 20 minutes)

• Block endogenous peroxidase and non-specific binding

• Incubate with FITC-conjugated FAM83D antibody at optimized dilution (overnight at 4°C)

• Wash with PBS

• Visualize under fluorescence microscope or convert FITC signal to chromogenic signal using anti-FITC HRP and DAB substrate

How can FAM83D antibodies be used to investigate cell cycle-dependent protein interactions?

To study FAM83D's cell cycle-dependent interactions:

• Synchronize cells at different cell cycle stages:

  • G1/S arrest using double thymidine block

  • S phase using single thymidine block

  • G2/M arrest using CDK1 inhibitor RO-3306

  • Mitotic arrest using nocodazole or STLC (S-trityl L-cysteine)

• Validate cell cycle synchronization:

  • Flow cytometry analysis with propidium iodide staining

  • Western blot for cell cycle markers (cyclin B1, phospho-histone H3)

• Analyze FAM83D interactions:

  • Co-immunoprecipitation using FAM83D antibodies at different cell cycle stages

  • Mass spectrometry analysis of immunoprecipitates to identify differential interactors

  • Validate interactions using reciprocal co-IP

• Visualize localization changes:

  • Use FITC-conjugated FAM83D antibodies for immunofluorescence microscopy

  • Co-stain with markers for mitotic structures (α-tubulin for spindles)

  • Perform live-cell imaging with FAM83D-GFP and potential interactors

Research has shown that FAM83D interacts with CK1α specifically during mitosis but not in asynchronous cells, highlighting the importance of cell cycle context in studying this protein's functions .

What are the considerations for using FAM83D antibodies in cancer stem cell (CSC) research?

When using FAM83D antibodies in CSC research, consider:

Experimental design considerations:

• Combine FAM83D detection with established CSC markers (e.g., CD44, CD133)

• Use flow cytometry with multi-parameter analysis to correlate FAM83D with CSC marker expression

• Employ functional assays like sphere formation to validate CSC properties

Analytical approaches:

• Analyze correlation between FAM83D expression and CSC marker levels in clinical samples

• Investigate effects of FAM83D knockdown on CSC marker expression and CSC functionality

• Examine signaling pathway changes that link FAM83D to CSC properties

Pathway analysis:

• Focus on MAPK, TGF-β, and Hippo signaling pathways that have been linked to FAM83D's role in promoting CD44 expression and CSC properties

• Assess changes in key pathway components:

  • TGF-β pathway: phosphorylated Smad2

  • MAPK pathway: phosphorylated ERK1/2

  • Hippo pathway: YAP expression and phosphorylation status

Research has shown that FAM83D knockdown can reduce CD44 expression and inhibit sphere formation and self-renewal capabilities, suggesting a mechanistic link between FAM83D and cancer stemness .

What are the optimal approaches for self-conjugating FAM83D antibodies with FITC?

For researchers preparing their own FITC-conjugated FAM83D antibodies:

Preparation of antibody:

• Ensure antibody purity (preferably >90% pure)

• Determine starting antibody concentration (optimal range: 1-4 mg/ml)

• Remove interfering buffer components:

  • Amines (Tris, glycine)

  • Sodium azide (>0.1%)

  • BSA (>0.5%)

  • Glycerol (>10%)

Conjugation options:

• Commercial kits (recommended for most users):

  • Mix-n-Stain™ FITC Antibody Labeling Kit allows labeling of 5-100 μg antibody in 15 minutes

  • Follow manufacturer's protocol precisely for optimal results

• Manual conjugation protocol:

  • Buffer exchange antibody into carbonate buffer (pH 9.0)

  • Calculate molar ratio (typically 10-20 FITC molecules per antibody)

  • Dissolve FITC in DMSO and add dropwise to antibody solution while stirring

  • Incubate 1-2 hours at room temperature protected from light

  • Purify conjugate using gel filtration columns to remove unconjugated FITC

Quality control assessments:

• Determine final protein concentration

• Calculate fluorophore-to-protein ratio (optimal F/P ratio: 3-7)

• Perform functional validation:

  • Comparison with unconjugated antibody in Western blot

  • Immunofluorescence with positive control samples

  • Flow cytometry analysis of cells with known FAM83D expression

The commercially available kits offer convenience and reliability for most research applications, while manual conjugation provides flexibility for specialized requirements 14.

How should researchers interpret FAM83D expression data in cancer studies?

When analyzing FAM83D expression data in cancer research:

Quantitative considerations:

• Define clear thresholds for "high" versus "low" expression (e.g., 2-fold increase relative to normal tissue using 2^-ΔΔCT method)

• Consider both the percentage of positive cells and the intensity of staining in IHC analyses

Clinical correlations:

• Analyze relationships between FAM83D expression and clinicopathological variables as shown in this example from hepatocellular carcinoma research:

Survival analysis:

• Use Kaplan-Meier curves to assess the relationship between FAM83D expression and patient outcomes

• Consider multivariate analysis to determine if FAM83D is an independent prognostic factor

Integration with other markers:

• Evaluate the complementary value of FAM83D with established markers (e.g., AFP for HCC)

• Consider the subset of cases where FAM83D is overexpressed but conventional markers are normal (25.23% of HCC cases showed high FAM83D but normal AFP)

What are the common pitfalls in FAM83D research and how can they be avoided?

Antibody validation concerns:

• Verify antibody specificity using positive and negative controls

• Use genetic approaches (knockdown/knockout) to confirm specificity

• Include isotype controls for flow cytometry and immunofluorescence applications

Experimental design issues:

• Account for cell cycle-dependent expression and localization of FAM83D

• Synchronize cells when studying mitotic functions of FAM83D

• Consider the impact of cell confluency on FAM83D expression and localization

Data interpretation challenges:

• Distinguish between correlation and causation in cancer studies

• Verify functional significance through mechanistic studies

• Consider the impact of FAM83D on multiple signaling pathways simultaneously

Technical considerations for FITC conjugates:

• Be aware of FITC's pH sensitivity (optimal at pH >7.0)

• Protect FITC-conjugated antibodies from photobleaching

• Consider photobleaching controls in quantitative imaging experiments

• Store FITC conjugates protected from light at 2-8°C and avoid repeated freeze-thaw cycles

Context-dependent protein interactions:

• Remember that FAM83D interactions may be cell-type specific or context-dependent

• For example, FAM83D interacts with CK1α specifically during mitosis

• Other FAM83 family members (particularly FAM83G) may affect the behavior of FAM83D or its interactors

How might advanced FAM83D antibody applications contribute to targeted cancer therapies?

FAM83D antibodies could advance targeted cancer therapies through:

Diagnostic applications:

• Development of FAM83D-based companion diagnostics to identify patients most likely to benefit from specific therapeutic approaches

• Use as a biomarker for early detection or monitoring of disease progression

Therapeutic target validation:

• Identification of the precise mechanisms by which FAM83D contributes to cancer progression

• Determination of downstream effectors of FAM83D that might be more amenable to pharmacological intervention

Potential drug development approaches:

• Disruption of specific protein-protein interactions (e.g., FAM83D-CK1α, FAM83D-FBXW7)

• Modulation of FAM83D degradation pathways

• Identification of synthetic lethal interactions with FAM83D overexpression

Combination therapy strategies:

• Investigation of synergistic effects between FAM83D-targeted approaches and existing therapies

• Enhancement of radiotherapy efficacy, as FAM83D knockdown has been shown to increase radiosensitivity in esophageal cancer cells

What are promising research avenues for understanding FAM83D's role in signaling pathway integration?

Future research directions for FAM83D should focus on:

Pathway crosstalk investigation:

• Detailed mapping of how FAM83D simultaneously affects multiple signaling cascades (MAPK, TGF-β, Hippo)

• Time-resolved analysis of pathway activation following FAM83D manipulation

• Single-cell analyses to understand cell-to-cell variability in FAM83D function

Structural biology approaches:

• Elucidation of the three-dimensional structure of FAM83D alone and in complex with key interactors

• Identification of critical binding interfaces for targeted disruption

• Understanding how the DUF1669 domain, which has weak homology to phospholipase D, contributes to FAM83D function

Systems biology integration:

• Multi-omics approaches (transcriptomics, proteomics, phosphoproteomics) to comprehensively map FAM83D-dependent networks

• Mathematical modeling of FAM83D's impact on cellular signaling networks

• Analysis of how FAM83D interacts with other FAM83 family members in signaling regulation

Translational relevance:

• Investigation of FAM83D's role in therapy resistance mechanisms

• Exploration of epigenetic mechanisms controlling FAM83D expression, as DNA methylation status of the FAM83D promoter has been associated with its expression levels

• Development of small molecule inhibitors targeting the FAM83D-CK1α interaction or other critical FAM83D functions