FAM83G Antibody

What is FAM83G and why is it significant for research?

FAM83G (Family with sequence similarity 83 member G), also known as PAWS1 (Protein Associated with SMAD1) or FLJ41564, is a protein that plays critical roles in multiple cellular signaling pathways. It functions as a substrate for type I bone morphogenetic protein receptors and modulates bone morphogenetic protein signaling . Recent research has identified FAM83G as a novel inducer of apoptosis, with the phosphorylation of its S356 residue being crucial for this function . Additionally, mutations in FAM83G have been associated with palmoplantar keratoderma (PPK), a skin disorder characterized by thickening of the epidermis on the palms and soles . FAM83G is significant for research due to its involvement in these diverse biological processes and potential implications in disease pathogenesis.

How do I select an appropriate FAM83G antibody for my experiments?

When selecting a FAM83G antibody, consider the following methodological approach:

• Determine your experimental application: Different antibodies perform optimally in specific applications such as Western blotting, immunohistochemistry, or immunofluorescence. Commercial antibodies like HPA023369 are validated for immunoblotting (0.04-0.4 μg/mL), immunofluorescence (0.25-2 μg/mL), and immunohistochemistry (1:50-1:200) .

• Verify species reactivity: Ensure the antibody recognizes FAM83G in your species of interest. For example, HPA023369 is specifically reactive to human FAM83G .

• Confirm clonality type: Polyclonal antibodies like HPA023369 offer high sensitivity but may have batch-to-batch variation, while monoclonal antibodies provide consistency but potentially lower sensitivity .

• Check validation data: Look for antibodies with enhanced validation, such as orthogonal RNA sequencing validation, to ensure specificity and reliability .

• Review literature: Examine published studies that have successfully used specific FAM83G antibodies for applications similar to yours.

What are the known functions of FAM83G in cellular signaling?

FAM83G functions in multiple signaling pathways:

• BMP signaling: FAM83G acts as a substrate for type I bone morphogenetic protein receptors and modulates BMP signaling through interaction with SMAD proteins .

• Apoptosis regulation: FAM83G induces apoptosis when overexpressed in cells, with this function dependent on phosphorylation at serine 356 (S356). FAM83G appears to interact with heat shock protein 27 (HSP27) and modulates its phosphorylation at S15 and S82 residues, impacting apoptosis regulation .

• WNT signaling: FAM83G interacts with casein kinase 1α (CK1α), and this interaction is essential for proper WNT signaling. Mutations in FAM83G that disrupt CK1α binding lead to attenuated WNT signaling, which appears to underlie the development of palmoplantar keratoderma .

• Kinase interactions: FAM83G associates with PKD1/PKCμ, which likely phosphorylates FAM83G at S356. This phosphorylation is critical for FAM83G's role in reducing cell survival .

What experimental controls should I include when using FAM83G antibodies?

For rigorous FAM83G antibody experiments, include these controls:

• Positive controls: Use cell lines or tissues known to express FAM83G, such as HCT116 and HepG2 cells, which show high endogenous expression .

• Negative controls: Include samples where FAM83G expression is absent or knocked down. Alternatively, use the antibody without primary incubation for non-specific binding assessment.

• Peptide competition: Pre-incubate the antibody with immunogen peptides like the sequence "RLLPDPGSPRLAQNARPMTDGRATEEHPSPFGIPYSKLSQSKHLKARTGGSQWASSDSKRRAQ" to verify specificity .

• Genetic validation: Compare wildtype cells with FAM83G knockout or knockdown cells to confirm antibody specificity.

• Multiple antibody validation: When possible, use multiple antibodies targeting different epitopes of FAM83G to cross-validate findings.

• Loading controls: For western blotting, include housekeeping proteins (β-actin, GAPDH) to ensure equal loading across samples.

How does FAM83G phosphorylation affect its function in apoptosis regulation?

FAM83G phosphorylation, particularly at serine 356 (S356), plays a critical role in its pro-apoptotic function:

This phosphorylation-dependent mechanism represents a potential therapeutic target, as modulating FAM83G phosphorylation could potentially induce apoptosis in cancer cells.

What are the implications of FAM83G mutations in disease pathogenesis?

FAM83G mutations have significant implications for disease pathogenesis:

• Palmoplantar keratoderma (PPK): A novel homozygous variant (c.794G>C) causing an Arg265 to Pro substitution (p.Arg265Pro) in FAM83G was identified in a 60-year-old female patient with PPK. This mutation, similar to previously reported A34E variant in humans and R52P variant in dogs, abolishes the interaction between FAM83G and casein kinase 1α (CK1α) .

• WNT signaling disruption: The loss of CK1α binding due to these mutations leads to attenuated WNT signaling, which appears to be the underlying mechanism for PPK development. This reinforces the importance of properly regulated WNT signaling in skin homeostasis .

• Cancer implications: FAM83G expression varies across cancer types. While non-small cell lung cancer cells show FAM83G levels similar to non-cancerous cells, small cell lung cancer cell lines display variable expression. Interestingly, cancer cells with high FAM83G expression also show elevated HSP27 expression, suggesting a compensatory mechanism against FAM83G's pro-apoptotic effects .

• Potential therapeutic targeting: Understanding how FAM83G mutations affect protein-protein interactions and downstream signaling provides potential therapeutic targets. For instance, restoring proper WNT signaling might be beneficial for PPK patients, while enhancing FAM83G phosphorylation could potentially induce apoptosis in certain cancer types .

How does FAM83G interact with CK1α and what is the functional significance of this interaction?

The interaction between FAM83G and casein kinase 1α (CK1α) is crucial for proper cell signaling:

• Binding mechanism: FAM83G interacts with CK1α through its N-terminal DUF1669 domain. Specific residues within this domain, including Arg265, are critical for this interaction .

• WNT signaling regulation: The FAM83G-CK1α complex plays an essential role in WNT signaling. When this interaction is disrupted by mutations such as R265P, WNT signaling is attenuated .

• Disease relevance: Mutations that abolish the FAM83G-CK1α interaction, including A34E in humans, R52P in dogs, and R265P in the recently identified PPK patient, all lead to palmoplantar keratoderma. This consistent phenotype across different mutations affecting the same interaction highlights its physiological importance .

• Experimental evidence: Functional characterization of the FAM83G R265P variant in DLD1 colorectal cancer cells and patient-derived skin fibroblasts confirmed that the mutation prevents CK1α binding and inhibits WNT signaling .

• Structural considerations: The F296A mutation in FAM83G also disrupts CK1α binding, suggesting that multiple residues contribute to forming a proper interaction surface .

This interaction represents a critical node in cell signaling networks, with implications for both development and disease pathogenesis.

What is the differential expression pattern of FAM83G across cancer types and what are its implications?

FAM83G shows variable expression across different cancer types with important implications:

• Expression in colon and liver cancer: Cancerous cells like HCT116 (colon cancer) and HepG2 (liver cancer) demonstrate higher FAM83G protein levels compared to non-cancerous cells .

• Expression in lung cancer:

  • Non-small cell lung cancer (NSCLC) cells show FAM83G mRNA levels similar to or lower than non-cancerous cells (1.22 ± 1.01 in NSCLC with EGFR mutation, 0.69 ± 0.17 in NSCLC with BRAF mutation, 1.09 ± 1.09 in NSCLC with wild-type EGFR/BRAF/KRAS, and 0.72 ± 0.27 in NSCLC with KRAS mutation) .

  • Small cell lung cancer (SCLC) cells display variable FAM83G expression (19.42 ± 44.16), with some showing significantly higher levels than non-cancerous cells .

• Correlation with HSP27 expression: SCLC cells with high FAM83G mRNA levels also exhibit significantly higher HSP27 mRNA levels compared to SCLC cells with low FAM83G expression. This suggests a compensatory mechanism where increased HSP27 expression counteracts the pro-apoptotic effects of high FAM83G levels .

• Implications for cancer biology: The variable expression patterns of FAM83G across cancer types suggest different roles in cancer progression. In some contexts, FAM83G may act as a tumor suppressor through its pro-apoptotic function, while in others, cancer cells may develop mechanisms to counteract this function .

• Therapeutic potential: These expression patterns suggest that targeting FAM83G or its interacting partners (like HSP27) could be a potential therapeutic strategy, particularly in cancers with high FAM83G expression .

What are the optimal conditions for detecting FAM83G using Western blotting?

For optimal FAM83G detection by Western blotting, follow these methodological guidelines:

• Antibody selection and concentration: Use a validated antibody such as HPA023369 at the recommended concentration of 0.04-0.4 μg/mL . This range provides flexibility to optimize signal-to-noise ratio for your specific samples.

• Sample preparation:

  • Lyse cells in a buffer containing protease inhibitors to prevent degradation

  • If studying phosphorylated FAM83G, include phosphatase inhibitors

  • Denature samples at 95°C for 5 minutes in Laemmli buffer containing SDS and β-mercaptoethanol

• Gel electrophoresis parameters:

  • Use 8-10% polyacrylamide gels as FAM83G has a molecular weight of approximately 80-90 kDa

  • Run at 100-120V to ensure proper protein separation

• Transfer conditions:

  • Transfer to PVDF or nitrocellulose membranes

  • Use wet transfer at 100V for 60-90 minutes or overnight at 30V at 4°C for larger proteins like FAM83G

• Blocking and antibody incubation:

  • Block with 5% non-fat dry milk or 5% BSA in TBST

  • For phospho-specific detection (such as S356 phosphorylation), use 5% BSA instead of milk

  • Incubate with primary antibody overnight at 4°C

  • Wash thoroughly (3-5 times) with TBST

  • Incubate with appropriate HRP-conjugated secondary antibody for 1 hour at room temperature

• Detection and controls:

  • Use enhanced chemiluminescence detection

  • Include positive controls like HCT116 or HepG2 cell lysates, which show high endogenous FAM83G expression

  • Include negative controls such as FAM83G knockout cell lysates when available

What approaches can be used to study FAM83G phosphorylation?

To study FAM83G phosphorylation, employ these methodological approaches:

• Phospho-specific antibodies:

  • Generate or obtain antibodies that specifically recognize phosphorylated S356

  • Validate specificity using phosphatase treatments and phosphorylation-deficient mutants (S356A)

• Phosphatase treatments:

  • Treat cell lysates with lambda phosphatase to remove phosphate groups

  • Compare migration patterns before and after treatment on Phos-tag or standard SDS-PAGE gels

• Phosphomimetic and phosphodeficient mutants:

  • Generate S356A (phosphodeficient) and S356D/E (phosphomimetic) FAM83G constructs

  • Compare functional outcomes in cellular assays as demonstrated in studies showing S356A mutation abolishes FAM83G's effect on cell survival

• Mass spectrometry:

  • Immunoprecipitate FAM83G from cells and analyze by MS to identify phosphorylation sites

  • Compare phosphorylation profiles under different conditions (e.g., treatment with kinase activators/inhibitors)

• In vitro kinase assays:

  • Express and purify recombinant FAM83G

  • Incubate with purified PKD1/PKCμ or other candidate kinases in the presence of ATP

  • Detect phosphorylation using 32P-ATP incorporation or phospho-specific antibodies

• Cell-based assays with phosphorylation-modulating peptides:

  • Use cell-permeable peptides containing the S356 consensus site (like AF-956 for colon cancer cells)

  • Assess functional outcomes such as changes in apoptosis markers

• Kinase inhibition studies:

  • Treat cells with specific inhibitors of PKD1/PKCμ

  • Assess the impact on FAM83G phosphorylation and downstream functions

How can I assess FAM83G-mediated effects on WNT signaling?

To evaluate FAM83G's impact on WNT signaling, implement these methodological approaches:

• TOPFlash reporter assays:

  • Transfect cells with a TOPFlash luciferase reporter containing TCF/LEF binding sites

  • Co-transfect wild-type FAM83G or mutants (like R265P) that disrupt CK1α binding

  • Stimulate WNT signaling with WNT ligands or GSK3 inhibitors like CHIR99021 (5 μM)

  • Measure luciferase activity to quantify WNT pathway activation

• β-catenin stabilization and localization:

  • Assess β-catenin levels by Western blotting in cytoplasmic and nuclear fractions

  • Use immunofluorescence to visualize β-catenin nuclear translocation

  • Compare results between cells expressing wild-type versus mutant FAM83G

• Co-immunoprecipitation of FAM83G with CK1α:

  • Transfect cells with tagged versions of FAM83G (wild-type or mutants) and CK1α

  • Immunoprecipitate FAM83G using appropriate antibodies or tag-specific antibodies

  • Analyze co-precipitated CK1α by Western blotting

• WNT target gene expression:

  • Measure mRNA levels of WNT target genes (e.g., AXIN2, LGR5, MYC) by qRT-PCR

  • Compare expression in cells with wild-type FAM83G versus CK1α-binding deficient mutants

• Proximity ligation assays (PLA):

  • Visualize and quantify endogenous FAM83G-CK1α interactions in situ

  • Compare PLA signals between wild-type cells and cells expressing FAM83G mutants

• CRISPR-Cas9 genome editing:

  • Generate FAM83G knockout cell lines or knock-in cell lines expressing mutant FAM83G

  • Assess basal and stimulated WNT signaling in these engineered cell lines

What cell models are most appropriate for studying FAM83G function?

Select optimal cell models for FAM83G research based on your specific research questions:

• Cancer cell lines with varying FAM83G expression:

  • HCT116 (colon cancer) and HepG2 (liver cancer): High endogenous FAM83G expression, suitable for knockdown studies

  • DLD1 (colorectal cancer): Used successfully for FAM83G-CK1α interaction studies

  • Small cell lung cancer lines with variable FAM83G expression: Useful for comparing effects in high vs. low FAM83G contexts

• Non-cancer cell lines:

  • CHO cells: Low endogenous FAM83G, ideal for overexpression studies

  • HEK293 cells: Commonly used for signaling studies and protein-protein interaction analyses

• Patient-derived models:

  • Primary fibroblasts from patients with FAM83G mutations (e.g., FIB15, FIB03, FIB04): Valuable for studying disease-relevant phenotypes

  • Induced pluripotent stem cells (iPSCs) derived from patients with FAM83G mutations, which can be differentiated into relevant cell types

• Knockout and knockin models:

  • CRISPR-Cas9 generated FAM83G knockout cell lines

  • Cell lines with endogenous FAM83G mutations (e.g., S356A or R265P)

• Three-dimensional models:

  • Skin organoids for studying PPK-related phenotypes

  • Intestinal organoids for WNT signaling studies

• In vivo models:

  • Transgenic mouse models expressing wild-type or mutant FAM83G

  • Naturally occurring dog models with FAM83G R52P mutation that develop PPK-like phenotypes

How can I troubleshoot non-specific binding when using FAM83G antibodies?

When encountering non-specific binding with FAM83G antibodies, implement these solutions:

• Optimize antibody concentration:

  • Titrate the antibody concentration to find the optimal balance between specific signal and background

  • For HPA023369, start with the middle of the recommended range (0.2 μg/mL for Western blot) and adjust as needed

• Modify blocking conditions:

  • Increase blocking time (from 1 hour to overnight)

  • Try different blocking agents (5% milk, 5% BSA, commercial blocking buffers)

  • Add 0.1-0.3% Triton X-100 or Tween-20 to reduce hydrophobic interactions

• Increase washing stringency:

  • Extend washing times and increase the number of washes

  • Add 0.1% SDS to TBST washing buffer to reduce non-specific interactions

  • Use higher salt concentration (up to 500 mM NaCl) in washing buffer

• Validate with controls:

  • Use peptide competition assays with the immunogen sequence to identify specific bands

  • Include FAM83G knockout or knockdown samples as negative controls

  • Test multiple FAM83G antibodies targeting different epitopes

• Sample preparation considerations:

  • Ensure complete denaturation of proteins

  • Use fresh samples and avoid freeze-thaw cycles

  • Pre-clear lysates with Protein A/G beads before immunoprecipitation

• Cross-adsorption:

  • Pre-incubate antibody with proteins from species not being studied

  • Use cross-adsorbed secondary antibodies to reduce cross-reactivity

How should I interpret differences in FAM83G expression between normal and cancer cells?

When analyzing FAM83G expression differences between normal and cancer cells, consider:

• Quantification methods:

  • Use multiple techniques (Western blot, qRT-PCR, immunohistochemistry) to confirm expression differences

  • Normalize protein levels to appropriate housekeeping genes/proteins

  • Consider absolute quantification methods like digital PCR for more precise measurements

• Interpretation framework:

  • Compare data with published values: HCT116 and HepG2 cells show higher FAM83G levels than non-cancerous cells

  • NSCLC cells show similar or lower FAM83G mRNA levels compared to non-cancerous cells (approximately 0.69-1.22 fold)

  • SCLC cells show variable expression (mean 19.42 ± 44.16 fold), with some significantly higher than normal cells

• Functional context:

  • High FAM83G expression may indicate potential pro-apoptotic pressure

  • Check corresponding HSP27 levels, as high FAM83G-expressing cancer cells often upregulate HSP27 as a compensatory mechanism

  • Assess phosphorylation status of FAM83G at S356, as this determines its pro-apoptotic function

• Clinical relevance:

  • Correlate expression with patient data when available

  • Consider expression in the context of cancer type, stage, and treatment response

  • Evaluate potential as a biomarker based on expression patterns

• Heterogeneity considerations:

  • Account for intra-tumoral heterogeneity by analyzing multiple regions

  • Consider cell type-specific expression within heterogeneous samples

  • Use single-cell techniques when appropriate to resolve cellular heterogeneity

What are the key considerations when interpreting FAM83G phosphorylation data?

For accurate interpretation of FAM83G phosphorylation data, address these key factors:

• Phosphorylation site specificity:

  • Confirm which specific residue is phosphorylated (e.g., S356)

  • Verify that phospho-specific antibodies or detection methods are site-specific

  • Consider that multiple phosphorylation sites may exist on FAM83G besides S356

• Physiological context:

  • Determine if the observed phosphorylation occurs under physiological conditions

  • Compare basal versus stimulated phosphorylation levels

  • Consider the dynamics of phosphorylation (rapid/transient vs. sustained)

• Kinase-phosphatase balance:

  • Identify the responsible kinase (likely PKD1/PKCμ for S356)

  • Consider potential phosphatases that may regulate FAM83G

  • Evaluate the impact of kinase inhibitors or activators on phosphorylation status

• Functional correlation:

  • Correlate phosphorylation status with functional outcomes (e.g., cell survival, apoptosis)

  • Compare wild-type FAM83G with phosphomimetic (S356D/E) and phosphodeficient (S356A) mutants

  • Assess downstream effects on interacting partners (e.g., HSP27 phosphorylation)

• Technical considerations:

  • Be aware that phosphorylation detection can be affected by sample preparation

  • Include phosphatase inhibitors during cell lysis

  • Consider that antibody affinity may be affected by neighboring modifications

• Quantitative assessment:

  • Determine the stoichiometry of phosphorylation (percentage of FAM83G molecules phosphorylated)

  • Use appropriate normalization to total FAM83G protein

  • Apply quantitative techniques like selected reaction monitoring (SRM) mass spectrometry

How can I reconcile conflicting data regarding FAM83G function across different experimental systems?

When faced with conflicting FAM83G functional data across experimental systems, employ these analytical approaches:

• Cell type-specific effects:

  • Compare results across different cell types systematically

  • Note that FAM83G overexpression reduces cell survival in both CHO and HCT116 cells , but effects may vary in other systems

  • Consider differences in endogenous expression levels and compensatory mechanisms (e.g., HSP27 upregulation in cancer cells)

• Expression level considerations:

  • Evaluate whether observed effects depend on expression level

  • Note that studies typically use ~10-fold overexpression compared to endogenous levels

  • Consider physiological versus non-physiological expression levels

• Technical variability sources:

  • Compare antibody specificity and detection methods

  • Standardize experimental conditions across systems

  • Ensure appropriate controls are included in all systems

• Protein interaction networks:

  • Map FAM83G interaction partners in each experimental system

  • Consider that FAM83G interacts with multiple proteins (CK1α, PKD1/PKCμ, HSP27)

  • Differences in these interactions may explain varying functions

• Post-translational modifications:

  • Assess phosphorylation status of FAM83G at S356 and potentially other sites

  • Consider other modifications that might affect function

• Genetic background:

  • Account for mutations or variations in interacting proteins

  • Consider compensatory pathways that might differ between systems

• Reconciliation strategies:

  • Perform rescue experiments in multiple systems

  • Use domain mapping to identify context-dependent functional regions

  • Develop unified models that incorporate context-specific functions

What are promising approaches for targeting FAM83G in cancer therapy?

Based on current knowledge of FAM83G biology, several promising therapeutic approaches emerge:

• Enhancing FAM83G phosphorylation:

  • Develop small molecules that promote FAM83G S356 phosphorylation

  • Target PKD1/PKCμ activators to increase FAM83G phosphorylation and induce apoptosis

  • Design cell-permeable peptides similar to AF-956 that mimic phosphorylated FAM83G and induce apoptosis in cancer cells

• Inhibiting compensatory mechanisms:

  • Target HSP27, which is upregulated in cancer cells with high FAM83G expression

  • Develop combination therapies that simultaneously enhance FAM83G activity and block protective mechanisms

• Modulating protein-protein interactions:

  • Design molecules that enhance or disrupt FAM83G interactions with key partners (CK1α, HSP27) depending on the therapeutic goal

  • Use structural information about the FAM83G-CK1α interaction to guide drug design

• Cancer-specific targeting:

  • Exploit differential expression patterns of FAM83G across cancer types

  • Develop targeted approaches for SCLC with high FAM83G expression

  • Use cancer-specific cell entry mechanisms, as demonstrated with the colon cancer-specific peptide AF-956

• Biomarker development:

  • Use FAM83G expression and phosphorylation status as predictive biomarkers for response to therapies

  • Develop diagnostic tools to identify cancers with high FAM83G/HSP27 expression

• Gene therapy approaches:

  • Deliver wild-type FAM83G to enhance apoptosis in appropriate contexts

  • Use CRISPR-based approaches to modulate FAM83G expression or introduce specific mutations

What techniques are emerging for studying FAM83G protein interactions in live cells?

Cutting-edge techniques for studying FAM83G interactions in live cells include:

• FRET/BRET-based approaches:

  • Generate FAM83G and interaction partners (CK1α, PKD1/PKCμ, HSP27) tagged with appropriate fluorophores or luciferase/fluorophore pairs

  • Monitor real-time interactions in living cells

  • Assess how mutations (R265P) or treatments affect these interactions

• Proximity labeling techniques:

  • Express FAM83G fused to enzymes like BioID2, TurboID, or APEX2

  • Identify proteins in proximity to FAM83G through biotinylation

  • Compare interactome differences between wild-type and mutant FAM83G

• Fluorescence correlation spectroscopy (FCS):

  • Measure diffusion rates of fluorescently tagged FAM83G

  • Detect changes in mobility that indicate complex formation

  • Quantify binding affinities in living cells

• Optogenetic approaches:

  • Create light-inducible FAM83G variants to control activity temporally

  • Study downstream signaling events following controlled activation

  • Assess spatial regulation of FAM83G function

• Live-cell phosphorylation sensors:

  • Design FRET-based sensors that detect FAM83G S356 phosphorylation

  • Monitor phosphorylation dynamics in real-time

  • Correlate with cellular outcomes like apoptosis initiation

• Super-resolution microscopy:

  • Visualize FAM83G complexes at nanoscale resolution

  • Track dynamic changes in complex formation

  • Study spatial organization of signaling hubs

• Single-molecule tracking:

  • Follow individual FAM83G molecules in living cells

  • Determine residence times in different cellular compartments

  • Assess how mutations affect molecular dynamics

How might understanding FAM83G biology contribute to developing treatments for palmoplantar keratoderma?

Understanding FAM83G biology offers pathways to novel PPK treatments:

• WNT signaling modulation:

  • Develop topical or systemic WNT pathway activators to compensate for attenuated signaling caused by FAM83G mutations

  • Target downstream WNT components to bypass the need for functional FAM83G-CK1α interaction

• Protein-protein interaction restoration:

  • Design small molecules that stabilize the interaction between mutant FAM83G and CK1α

  • Develop peptide mimetics that bridge mutant FAM83G and CK1α

• Gene therapy approaches:

  • Deliver wild-type FAM83G to affected skin areas using viral vectors or nanoparticles

  • Use CRISPR-based approaches to correct specific mutations (R265P, A34E)

• RNA therapeutics:

  • Employ antisense oligonucleotides to promote exon skipping in cases where this might restore function

  • Use siRNA to reduce expression of mutant FAM83G if it has dominant-negative effects

• Targeting compensatory pathways:

  • Identify and modulate pathways that become dysregulated in the absence of proper FAM83G-CK1α interaction

  • Develop combination therapies that address multiple aspects of the disease mechanism

• Patient-derived models for drug screening:

  • Use fibroblasts derived from patients with FAM83G mutations (like FIB15 from the R265P patient)

  • Develop skin organoids from patient cells for more physiologically relevant drug screening

• Symptom management:

  • Design treatments that address hyperkeratosis regardless of the underlying molecular mechanism

  • Develop formulations that penetrate thickened epidermis to deliver therapeutics effectively

What are the most significant advances in our understanding of FAM83G function?

Recent research has significantly advanced our understanding of FAM83G in several key areas:

• Dual role in signaling: FAM83G has been established as a critical component in both BMP and WNT signaling pathways, functioning as a substrate for type I BMP receptors and as an anchor for CK1α in WNT signaling .

• Pro-apoptotic function: The identification of FAM83G as a novel inducer of apoptosis represents a significant advance, with its S356 phosphorylation demonstrated to be essential for this function. This phosphorylation is likely mediated by PKD1/PKCμ and affects downstream HSP27 phosphorylation and apoptotic signaling .

• Disease connections: The discovery of multiple FAM83G mutations (A34E, R52P in dogs, and R265P) all causing similar palmoplantar keratoderma phenotypes through disruption of CK1α binding has established a clear genotype-phenotype relationship. This consistently links disrupted WNT signaling to the development of PPK .

• Cancer relevance: The differential expression patterns of FAM83G across cancer types, along with the compensatory upregulation of HSP27 in high FAM83G-expressing cancers, has revealed potential roles in cancer biology and identified possible therapeutic targets .

• Structural insights: Understanding the importance of specific residues like R265 and F296 in mediating protein-protein interactions has provided structural insights into FAM83G function .

These advances collectively position FAM83G as a multifunctional signaling protein with significant implications for both development and disease, offering multiple avenues for further research and therapeutic development.

What consensus guidelines should researchers follow when studying FAM83G antibodies?

Researchers studying FAM83G using antibodies should adhere to these consensus guidelines:

• Validation requirements:

  • Confirm antibody specificity using multiple methods: Western blot, immunoprecipitation, and immunofluorescence

  • Validate using genetic controls (FAM83G knockout/knockdown cells)

  • Perform peptide competition assays with immunogen sequences such as "RLLPDPGSPRLAQNARPMTDGRATEEHPSPFGIPYSKLSQSKHLKARTGGSQWASSDSKRRAQ"

  • Include positive controls (HCT116, HepG2) with known FAM83G expression

• Application-specific optimization:

  • For Western blotting: Use recommended concentrations (0.04-0.4 μg/mL for HPA023369)

  • For immunofluorescence: Follow validated protocols (0.25-2 μg/mL for HPA023369)

  • For immunohistochemistry: Use established dilutions (1:50-1:200 for HPA023369)

• Reporting standards:

  • Document complete antibody information: source, catalog number, lot number, clonality, and species

  • Report all validation experiments performed

  • Provide detailed methods including blocking conditions, incubation times, and detection methods

• Functional studies:

  • Correlate antibody detection with functional readouts

  • Consider both expression levels and post-translational modifications

  • Use multiple antibodies targeting different epitopes when possible

• Reproducibility measures:

  • Perform experiments with biological replicates

  • Include appropriate statistical analyses

  • Share detailed protocols to enable reproduction by other laboratories

• Special considerations:

  • For phosphorylation studies: Use phospho-specific antibodies alongside total FAM83G antibodies

  • For interaction studies: Validate antibody compatibility with immunoprecipitation conditions

  • For tissue analyses: Optimize fixation and antigen retrieval methods for each tissue type