DIRAS3 Antibody

What is DIRAS3 and why is it important in cancer research?

DIRAS3 (DIRAS family GTPase 3, also known as ARHI or NOEY2) is a maternally imprinted tumor suppressor gene that encodes a 26 kDa GTPase with approximately 60% amino acid homology to RAS proteins. Its distinctive feature is a 34-amino-acid N-terminal extension, which is essential for its tumor suppressive functions .

DIRAS3 is significant in cancer research for several reasons:

• It's the first endogenous non-RAS protein discovered that heterodimerizes with RAS, disrupts RAS clustering, blocks RAS signaling, and inhibits cancer cell growth

• It's frequently downregulated in multiple cancer types including ovary, breast, lung, prostate, colon, brain, and thyroid cancers

• It functions as a tumor suppressor by inhibiting signaling through PI3K/AKT, JAK/STAT, and RAS/MAPK pathways

• DIRAS3 plays critical roles in autophagy, cancer cell dormancy, and oxidative stress, making it a potential target for novel cancer therapies

Re-expression of DIRAS3 inhibits cancer cell growth, prevents angiogenesis, induces autophagy, and creates tumor dormancy in xenograft models, highlighting its potential as a therapeutic target .

What experimental applications are DIRAS3 antibodies suitable for?

DIRAS3 antibodies have been validated for multiple experimental applications in molecular and cellular biology research:

When selecting a DIRAS3 antibody, researchers should consider the specific experimental application, target species, and binding specificity (e.g., N-terminal vs. C-terminal epitopes) most relevant to their research question .

What positive controls should I use when working with DIRAS3 antibodies?

Implementing appropriate positive controls is crucial for ensuring the validity and reproducibility of experiments using DIRAS3 antibodies:

Cell lines with known DIRAS3 expression:

• NIH/3T3 cells

• Normal ovarian epithelial cells

• CAOv3 ovarian cancer cells (high endogenous DIRAS3 expression and basal autophagy)

Tissue samples:

• Mouse liver, mouse kidney, rat liver (as indicated in product information)

Expression systems:

• DIRAS3-inducible cell lines (typically Tet-on/DOX-inducible systems)

• Transiently transfected cells overexpressing DIRAS3

Recombinant proteins:

• Purified recombinant DIRAS3 protein is useful as a standard in quantitative assays and specificity testing

For inducible systems (such as DOX-inducible DIRAS3 expression), comparing induced versus non-induced samples provides an excellent internal control for antibody validation .

How can I optimize DIRAS3 antibody performance for detecting low-level expression in cancer samples?

Detecting low levels of DIRAS3 expression in cancer samples requires optimized sensitivity approaches:

Enhanced immunohistochemistry protocols:

• Implement heat-induced epitope retrieval (HIER) with optimized buffer conditions

• Utilize signal amplification systems such as tyramide signal amplification (TSA)

• Extend primary antibody incubation time (overnight at 4°C)

• Use high-sensitivity detection systems (polymer-based or biotin-free)

Enhanced Western blot detection:

• Increase protein loading (50-100 μg total protein)

• Use high-sensitivity chemiluminescent substrates

• Employ concentration steps like immunoprecipitation before Western blotting

• Consider using gradient gels for better resolution near 26 kDa

• Extend exposure time with cooled CCD camera systems

Alternative detection methods:

• Proximity ligation assay (PLA): Can detect protein-protein interactions with single-molecule sensitivity

• RNAscope in situ hybridization: To detect DIRAS3 mRNA as complementary approach

• Mass spectrometry: For targeted detection of DIRAS3 peptides

DIRAS3 expression is often downregulated in cancer tissues through epigenetic mechanisms, so combining protein detection with epigenetic analysis (e.g., promoter methylation status) can provide a more complete picture of DIRAS3 status .

How can I design experiments to study DIRAS3-RAS interactions using antibody-based approaches?

Studying DIRAS3-RAS interactions requires carefully designed antibody-based approaches to detect these protein-protein interactions:

Co-immunoprecipitation (Co-IP) strategies:

• Forward and reverse Co-IP: Immunoprecipitate with anti-DIRAS3 and probe for RAS, then reverse the approach

• Use mild detergents (e.g., 1% NP-40 or 0.5% Triton X-100) to preserve membrane associations

• Include appropriate controls: IgG control, lysates from cells not expressing one protein

Proximity-based detection methods:

• Proximity Ligation Assay (PLA): Detect DIRAS3-RAS interactions in situ with single-molecule resolution

• Immunofluorescence co-localization using specific antibodies for DIRAS3 and RAS

Advanced electron microscopy:

• Immunogold electron microscopy with differentially sized gold particles (e.g., DIRAS3: 2nm, K-RAS: 4.5nm)

• Bi-variate K-function analysis to quantify co-localization at ultrastructural level

Functional validation approaches:

• Assess effects of DIRAS3 and mutant constructs (ΔNT DIRAS3, C226S) on RAS clustering

• Use membrane sheet preparations to focus on plasma membrane interactions

• Study interactions under different cellular conditions (starvation, growth factor stimulation)

Research has demonstrated that DIRAS3 directly binds to RAS, forming heteromers that disrupt RAS clustering and inhibit downstream signaling. The N-terminal extension of DIRAS3 and its membrane association through the CAAX-box domain are both critical for this interaction .

What strategies can I use to study DIRAS3-mediated autophagy using antibody-based approaches?

DIRAS3-mediated autophagy can be comprehensively studied using various antibody-based strategies:

Monitoring autophagic flux:

• Track LC3-I to LC3-II conversion by Western blot using anti-LC3B antibodies

• Measure SQSTM1/p62 degradation as marker of autophagic flux

• Use chloroquine to block autophagosome-lysosome fusion and assess accumulation

• Use tandem mCherry-GFP-LC3 reporter systems to differentiate autophagosomes (yellow) from autolysosomes (red)

Detecting DIRAS3-autophagy protein interactions:

• Co-immunoprecipitation of DIRAS3 with key autophagy proteins (BECN1, ATG12, LC3)

• Immunofluorescence co-localization studies of DIRAS3 with autophagy markers

• Immunogold electron microscopy to visualize DIRAS3 localization to autophagosomal membranes

Monitoring autophagy pathway activation:

• Assess phosphorylation status of key autophagy regulators:

  • Decreased p-MTOR (Ser2448)

  • Decreased p-STK11/LKB1 (Ser428)

  • Increased p-AMPK (Thr172)

• Track nuclear translocation of autophagy-related transcription factors:

  • TFEB

  • FOXO3

Visualizing autophagosome formation:

• Immunofluorescence staining for ATG proteins (ULK1, ATG13, ATG14, BECN1)

• Quantify puncta formation as measure of autophagosome initiation

Research has shown that DIRAS3 is essential for autophagy and triggers this process through multiple mechanisms, including downregulation of the PtdIns3K-AKT-MTOR pathway, interaction with BECN1, and disruption of the BECN1-BCL2 complex .

How can I use DIRAS3 antibodies to investigate tumor dormancy mechanisms?

DIRAS3 antibodies can be valuable tools for investigating tumor dormancy mechanisms, particularly given DIRAS3's role in inducing and maintaining dormancy:

Monitoring DIRAS3 expression in dormant models:

• Use immunohistochemistry to detect DIRAS3 in dormant tumor regions

• Compare DIRAS3 expression in proliferating vs. dormant regions using dual staining with proliferation markers

• Quantify DIRAS3 levels during dormancy induction, maintenance, and exit phases

In vivo dormancy models:

• Create inducible DIRAS3 expression systems (e.g., DOX-inducible) in xenograft models

• Monitor tumor growth and angiogenesis before/during/after DIRAS3 induction

• Sample tumors at various timepoints to track molecular changes via IHC and Western blotting

• Assess effects of autophagy inhibitors (chloroquine, DC661) on dormant tumor recurrence

Pathway analysis in dormant cells:

• Analyze key signaling pathways modulated by DIRAS3 during dormancy:

  • PI3K/AKT/MTOR pathway inhibition

  • RAS/MAPK signaling suppression

  • Autophagy pathway activation

  • Angiogenesis inhibition

• Use phospho-specific antibodies to track signaling dynamics

Studies have shown that re-expression of DIRAS3 induces dormancy in xenograft models, inhibiting cancer cell growth and angiogenesis. DIRAS3-mediated induction of autophagy facilitates the survival of dormant cancer cells in a nutrient-poor environment, suggesting that targeting DIRAS3-positive dormant cells could eliminate residual disease after conventional therapy .

What are the optimal conditions for using DIRAS3 antibodies in co-immunoprecipitation experiments?

Co-immunoprecipitation (Co-IP) experiments with DIRAS3 antibodies require careful optimization to detect authentic protein interactions while minimizing artifacts:

Buffer optimization:

• Use buffers containing 0.5-1% non-ionic detergents (NP-40, Triton X-100, Digitonin) to preserve membrane protein interactions

• Include protease and phosphatase inhibitors to prevent degradation and preserve post-translational modifications

• Consider adding GTP/GDP for small GTPase interactions

Antibody selection and validation:

• Validate antibody specificity before Co-IP experiments

• Consider epitope location: Ensure the epitope is not involved in protein-protein interactions

• Test multiple antibodies targeting different regions of DIRAS3

Cell lysis considerations:

• For inducible systems, optimize induction time for maximal expression

• Consider membrane fractionation to enrich for DIRAS3-RAS interactions occurring at the plasma membrane

Controls and validation:

• Input control: Check expression levels of target proteins in lysate before IP

• IgG control: Parallel IP with isotype-matched control IgG

• Reverse Co-IP: Confirm interaction by immunoprecipitating binding partner

For studying DIRAS3-BECN1 interactions, research has demonstrated direct protein-protein binding that can be detected by co-immunoprecipitation. This interaction is enhanced during nutrient deprivation and plays a crucial role in autophagy induction .

How do I design experiments to differentiate between DIRAS3 and other RAS family proteins?

Differentiating DIRAS3 from other RAS family proteins requires careful experimental design that leverages their structural and functional differences:

Antibody-based differentiation:

• Use antibodies targeting the unique 34-amino-acid N-terminal extension of DIRAS3

• Validate antibody specificity against recombinant DIRAS3 and RAS proteins

Size-based differentiation:

• DIRAS3 (26 kDa) vs. standard RAS proteins (~21 kDa) can be resolved on higher-percentage SDS-PAGE gels

• Use gradient gels (10-20%) for optimal resolution in the 20-30 kDa range

Expression pattern analysis:

• Exploit tissue-specific expression differences (DIRAS3 is highly expressed in normal ovarian and breast epithelial cells but downregulated in corresponding cancers)

• Analyze imprinting status (DIRAS3 is maternally imprinted, unlike RAS genes)

Functional differentiation:

• Subcellular localization studies: Both localize to membranes, but distribution patterns may differ

• Downstream signaling effects: DIRAS3 inhibits pathways that RAS activates

• Autophagy induction: DIRAS3 strongly induces autophagy, unlike classical RAS proteins

Genetic approaches:

• Use siRNA sequences targeting unique regions of DIRAS3 mRNA

• Design PCR primers that distinguish DIRAS3 from RAS family members

The distinctive N-terminal extension of DIRAS3 is critical for its tumor suppressive functions and provides a key distinguishing feature from other RAS family proteins .

What are the challenges in detecting DIRAS3 in cancer tissues with imprinting abnormalities?

Detecting DIRAS3 in cancer tissues with imprinting abnormalities presents several challenges that require specialized approaches:

Challenges related to imprinting status:

• DIRAS3 is normally expressed only from the paternal allele due to maternal imprinting

• Cancer cells may exhibit loss of imprinting (LOI) or allele-specific silencing

• Heterogeneous expression patterns within the same tumor sample

• Loss of expression can occur in a single "hit" through multiple mechanisms

Methodological challenges:

• Standard antibody-based methods cannot distinguish allele-specific expression

• Expression levels may be below detection threshold of conventional techniques

• Presence of multiple mechanisms of downregulation (genetic, epigenetic, post-transcriptional)

• Distinguishing DIRAS3 protein from closely related RAS family members

Advanced approaches to address these challenges:

• Combined genetic-protein analysis:

  • Allele-specific PCR followed by protein analysis from the same sample

  • Laser capture microdissection to isolate specific cell populations

• Epigenetic assessment:

  • Methylation-specific PCR to analyze DIRAS3 promoter status

  • Correlate epigenetic status with protein expression levels

• Enhanced detection methods:

  • Signal amplification systems for immunohistochemistry

  • Mass spectrometry-based proteomics for DIRAS3 detection

DIRAS3's unique status as a maternally imprinted tumor suppressor gene makes it particularly vulnerable to expression loss in cancer, and comprehensive analysis requires integration of genetic, epigenetic, and protein-level approaches .