NRIP3 Antibody

What is NRIP3 and what are its known cellular functions?

NRIP3, also known as C11orf14 or NY-SAR-105, is a 241 amino acid protein encoded by a gene located on human chromosome 11 . Recent studies have demonstrated that NRIP3 plays a critical role in protecting cells from DNA damage during replication stress . The protein has gained significant attention due to its upregulation in esophageal squamous cell carcinoma (ESCC) tumor tissues compared to non-tumor tissues, as confirmed by gene expression profiling from TCGA database .

NRIP3 functions in a molecular pathway that involves its interaction with DDI1 (DNA-damage inducible 1 homolog 1) and RTF2 (replication termination factor 2) . Through these interactions, NRIP3 contributes to replication stress management, specifically by promoting the removal of RTF2, which is a key determinant for cellular ability to manage replication stress . Additionally, NRIP3 has been shown to increase DDI1 expression via the PPARα pathway, establishing what researchers refer to as the NRIP3-PPARα-DDI1-RTF2 axis .

What are the common applications for NRIP3 antibodies in research?

NRIP3 antibodies are versatile tools in research with applications across multiple experimental techniques. Primary applications include:

• Western Blotting (WB): Used to detect and quantify NRIP3 protein levels in cell or tissue lysates. Polyclonal antibodies against the C-terminal region of NRIP3 are commonly used for this purpose .

• Immunohistochemistry (IHC): Enables visualization of NRIP3 expression and localization in tissue sections. This technique has been valuable in analyzing NRIP3 expression in tumor tissues such as ESCC and liver cancer .

• Co-immunoprecipitation (Co-IP): Essential for studying protein-protein interactions involving NRIP3. This method has been crucial in confirming interactions between NRIP3 and other proteins like DDI1 and RTF2 .

• ELISA: Allows for quantitative detection of NRIP3 in biological samples .

• Immunofluorescence (IF): Provides subcellular localization information for NRIP3 protein .

The selection of the appropriate application depends on the specific research question, with considerations for tissue type, experimental design, and the level of protein detection sensitivity required.

How should researchers validate NRIP3 antibody specificity?

Validating antibody specificity is crucial for ensuring reliable experimental results. For NRIP3 antibodies, the following validation approaches are recommended:

• Positive and negative controls: Include tissues or cell lines known to express high levels of NRIP3 (e.g., ESCC tissues) as positive controls, and those with low or no expression as negative controls .

• Knockdown/knockout validation: Compare antibody reactivity in wild-type cells versus NRIP3-knockdown cells (as demonstrated in the 109-sh4 NRIP3-KD cell line) .

• Overexpression validation: Test antibody reactivity in cells overexpressing NRIP3 (such as 30-NRIP3 overexpressing cells) .

• Western blot analysis: Confirm that the antibody detects a band of the expected molecular weight (~27 kDa for human NRIP3).

• Cross-reactivity testing: If working with multiple species, validate that the antibody reacts specifically with NRIP3 from the species of interest .

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide to confirm specificity through signal ablation.

Thorough validation ensures that experimental observations truly reflect NRIP3 biology rather than non-specific interactions or artifacts.

What methodological considerations are important when using NRIP3 antibodies for co-immunoprecipitation studies?

Co-immunoprecipitation (Co-IP) has been instrumental in elucidating NRIP3's interactions with proteins like DDI1 and RTF2. When conducting Co-IP experiments with NRIP3 antibodies, consider these methodological aspects:

• Reciprocal IP verification: Confirm interactions by performing reciprocal IP experiments. For instance, the interaction between NRIP3 and DDI1 was confirmed by co-IP experiments for DDI1 protein using NRIP3 antibody and then by reciprocal IP of the NRIP3 protein with DDI1 antibody .

• Cell lysis conditions: Optimize lysis buffers to maintain protein-protein interactions while efficiently extracting NRIP3. Consider that some interactions may be transient or weak, requiring mild detergents and physiological salt concentrations.

• Antibody selection: Choose antibodies raised against epitopes that won't interfere with protein interactions. For NRIP3, C-terminal antibodies have been successfully used in co-IP studies .

• Controls: Include isotype controls and input samples (pre-IP lysate) to assess non-specific binding and IP efficiency.

• Detection method: Consider using sensitive detection methods for Western blotting after IP, especially when studying low-abundance interactions.

• Crosslinking consideration: For transient interactions, consider using chemical crosslinking before cell lysis to stabilize protein complexes.

This methodological approach enabled researchers to discover and validate the interactions between NRIP3, DDI1, and RTF2, which provided insights into the molecular mechanism underlying NRIP3's role in replication stress management .

How does the NRIP3-PPARα-DDI1-RTF2 axis contribute to chemoradiotherapy resistance in cancer?

The NRIP3-PPARα-DDI1-RTF2 axis represents a protective molecular pathway in ESCC cells that mediates resistance to replication stress signals induced by chemoradiotherapy . Understanding this mechanism requires analysis of several interconnected processes:

• NRIP3 upregulation in tumors: NRIP3 is upregulated in 64.47% (176/273) of ESCC tumor tissues compared to paired non-tumor tissues, as demonstrated by immunohistochemistry staining of tissue microarrays .

• Protection from replication stress: NRIP3 overexpression confers resistance to aphidicolin treatment (a replication stress inducer), as measured by reduced DNA damage in comet assays and decreased apoptosis rates .

• Molecular interactions: NRIP3 interacts with DDI1, a proteasomal shuttle protein required for RTF2 removal during replication stress response. Additionally, NRIP3 directly interacts with RTF2, accelerating its removal .

• PPARα pathway activation: NRIP3 increases DDI1 expression via PPARα activation. This was confirmed by:

  • Elevated expression of PPARα target genes in NRIP3-overexpressing cells

  • Attenuation of DDI1 upregulation when treated with PPARα antagonist MK-886

  • Reversal of DDI1 downregulation in NRIP3-knockdown cells when treated with PPARα agonist WY-14643

• Clinical correlation: Elevated NRIP3 expression is associated with poor clinical outcomes in ESCC patients receiving radiotherapy and/or cisplatin-based chemotherapy .

This axis provides cancer cells with enhanced ability to recover from replication fork stalling induced by chemotherapy and radiotherapy, thereby promoting treatment resistance.

What experimental approaches can be used to study the role of NRIP3 in replication stress response?

Investigating NRIP3's role in replication stress response requires multiple experimental approaches:

• Comet assay for DNA damage assessment: This technique has been effectively used to demonstrate that NRIP3-overexpressing cells exhibit resistance to aphidicolin-induced replication stress, while NRIP3-knockdown cells show increased sensitivity .

• Apoptosis analysis: Flow cytometry with appropriate staining (e.g., Annexin V/PI) can quantify apoptosis rates following replication stress induction in cells with modified NRIP3 expression .

• Genetic manipulation models:

  • Create stable NRIP3-overexpressing cell lines (e.g., 30-NRIP3 cells)

  • Generate NRIP3-knockdown cells using shRNA (e.g., 109-sh4 cells)

• Protein interaction studies:

  • Co-immunoprecipitation to investigate interactions between NRIP3, DDI1, and RTF2

  • Proximity ligation assays to visualize protein interactions in situ

• Replication stress inducers:

  • Aphidicolin (inhibitor of replicative polymerase)

  • Cisplatin (DNA crosslinking agent used in chemotherapy)

  • Ionizing radiation

• Pathway modulation:

  • PPARα antagonists (e.g., MK-886) to block the pathway

  • PPARα agonists (e.g., WY-14643) to activate the pathway

• Gene expression analysis:

  • qRT-PCR to measure expression of NRIP3, DDI1, and PPARα target genes

  • Western blotting to assess protein levels and modifications

These approaches collectively provide a comprehensive understanding of NRIP3's functional role in protecting cells from replication stress.

What are the technical challenges in detecting endogenous NRIP3 in different tissue types?

Detecting endogenous NRIP3 across various tissue types presents several technical challenges that researchers must address:

• Variable expression levels: NRIP3 expression varies significantly between tissue types and disease states. In ESCC, 64.47% of tumor tissues show upregulation compared to paired non-tumor tissues , requiring different detection sensitivity approaches depending on the tissue.

• Antibody selection considerations:

  • Specificity: Choose antibodies validated for the specific application and tissue type

  • Epitope accessibility: Consider that epitope accessibility may vary across fixation methods and tissue types

  • Cross-reactivity: Evaluate potential cross-reactivity with other proteins, especially in tissues with complex protein expression profiles

• Fixation and antigen retrieval optimization:

  • For IHC applications, different tissues may require specific fixation protocols

  • Antigen retrieval conditions (pH, temperature, duration) often need optimization for specific tissues

  • Commercial NRIP3 antibodies have been verified for IHC in human liver cancer samples

• Signal amplification requirements:

  • In tissues with low endogenous expression, signal amplification techniques may be necessary

  • Consider using high-sensitivity detection systems (e.g., tyramide signal amplification)

• Validation strategies:

  • Include appropriate positive controls (e.g., ESCC tumor tissues known to express NRIP3)

  • Use negative controls (tissues known to have low/no expression)

  • Consider using multiple antibodies targeting different epitopes for confirmation

• Background reduction techniques:

  • Optimize blocking conditions to minimize non-specific binding

  • Use appropriate dilutions (e.g., 1:50-1:200 for IHC as recommended for some NRIP3 antibodies)

Addressing these challenges through methodical optimization is essential for reliable detection of endogenous NRIP3 across different experimental contexts.

What are the optimal storage and handling conditions for NRIP3 antibodies?

Proper storage and handling of NRIP3 antibodies is crucial for maintaining their activity and specificity over time. Based on manufacturer recommendations and standard practices:

• Storage temperature: Store NRIP3 antibodies at -20°C for long-term storage. Commercial antibodies are typically valid for 12 months when stored properly .

• Freeze-thaw cycles: Minimize freeze-thaw cycles as they can lead to antibody denaturation and loss of activity. Aliquot antibodies upon receipt to avoid repeated freezing and thawing .

• Buffer composition: Most NRIP3 antibodies are supplied in phosphate buffered solution (pH 7.4) containing stabilizers (typically 0.05%) and glycerol (often 50%) to maintain stability during freeze-thaw cycles .

• Working dilution preparation: When preparing working dilutions, use fresh, cold buffer and handle the antibody on ice to prevent degradation.

• Shipping considerations: NRIP3 antibodies are typically shipped with ice packs. Upon receipt, store immediately at the recommended temperature (-20°C) .

• Contamination prevention: Use sterile techniques when handling antibodies to prevent microbial contamination.

• Documentation: Maintain records of antibody lot numbers, receipt dates, and aliquot preparation to track antibody age and potential deterioration.

Following these guidelines will help ensure consistent results and maximize the useful lifespan of NRIP3 antibodies in research applications.

What controls should be included when studying NRIP3-DDI1-RTF2 interactions?

When investigating the interactions between NRIP3, DDI1, and RTF2, proper controls are essential to ensure reliable and interpretable results:

• Input controls: Include analysis of pre-immunoprecipitation lysates to confirm the presence of all proteins of interest before co-IP .

• Negative IP controls:

  • IgG control: Perform parallel immunoprecipitation with isotype-matched non-specific IgG

  • Irrelevant antibody control: Use antibodies against proteins not expected to interact with the complex

• Reciprocal IP verification: As demonstrated in published research, confirm interactions by performing reciprocal immunoprecipitations (e.g., IP with NRIP3 antibody followed by DDI1 detection, and vice versa) .

• Expression modulation controls:

  • NRIP3-overexpressing cells (e.g., 30-NRIP3) to evaluate interaction enhancement

  • NRIP3-knockdown cells (e.g., 109-sh4) to confirm interaction specificity

• Pathway modulation controls:

  • PPARα antagonist (MK-886) treatment to assess the impact on DDI1 levels and subsequent interactions

  • PPARα agonist (WY-14643) to evaluate pathway stimulation effects

• Specificity controls:

  • Competition with excess immunizing peptide to confirm antibody specificity

  • Secondary antibody-only controls to assess non-specific binding

• Replicate experiments: Perform multiple independent experiments to confirm reproducibility of observed interactions.

These controls collectively help to validate the specificity and biological relevance of the observed NRIP3-DDI1-RTF2 interactions, as demonstrated in published research on this molecular axis .

How can NRIP3 antibodies be used to evaluate patient prognosis in cancer?

NRIP3 antibodies have demonstrated significant utility in prognostic evaluation of cancer patients, particularly in esophageal squamous cell carcinoma (ESCC). Implementation of NRIP3 as a prognostic marker involves several methodological considerations:

• Tissue microarray (TMA) analysis: NRIP3 antibodies have been successfully used for immunohistochemical staining of ESCC tissue microarrays (300 ESCC cases from Linzhou Cancer Hospital and 73 cases from SYSUCC, Guangzhou) .

• Scoring system development:

  • Establish a standardized scoring system for NRIP3 expression levels

  • Define clear criteria for positive versus negative staining

  • Consider both staining intensity and percentage of positive cells

• Clinical correlation analysis:

  • Compare NRIP3 expression with treatment response data

  • Correlate expression levels with survival outcomes

  • Analyze association with other clinicopathological parameters

• Multivariate analysis:

  • Include NRIP3 expression in multivariate models alongside established prognostic factors

  • Determine independent prognostic value

• Validation in independent cohorts:

  • Confirm findings across different patient populations

  • Consider multicenter validation studies

Research has demonstrated that elevated NRIP3 expression is associated with poor clinical outcomes in ESCC patients receiving radiotherapy and/or cisplatin-based chemotherapy . This suggests that NRIP3 immunohistochemistry could be a valuable tool for stratifying patients who might benefit from alternative treatment approaches.

What methodological approaches can determine if NRIP3 is a therapeutic target in chemoradiotherapy-resistant cancers?

Evaluating NRIP3 as a potential therapeutic target in chemoradiotherapy-resistant cancers requires systematic investigation using the following methodological approaches:

• Target validation experiments:

  • Genetic manipulation: Compare chemoradiotherapy sensitivity in NRIP3-overexpressing versus knockdown models

  • Phenotypic rescue experiments: Determine if restoring NRIP3 expression in knockdown cells reverses sensitivity

• Mechanism exploration:

  • Investigate the complete NRIP3-PPARα-DDI1-RTF2 axis through pathway modulation

  • Use PPARα antagonists (e.g., MK-886) to pharmacologically disrupt the pathway

  • Evaluate downstream effects on replication stress response

• Combination treatment strategies:

  • Test NRIP3 inhibition in combination with standard chemoradiotherapy

  • Analyze synergistic effects through combination index calculations

• Therapeutic window assessment:

  • Compare effects of NRIP3 inhibition on cancer versus normal cells

  • Evaluate potential toxicities in preclinical models

• Biomarker development:

  • Identify which patient subgroups might benefit most from NRIP3-targeted therapy

  • Develop companion diagnostic approaches using validated NRIP3 antibodies

• Preclinical efficacy studies:

  • In vitro: Cell viability, colony formation, apoptosis assays

  • In vivo: Tumor growth inhibition in xenograft models

• Target engagement measurement:

  • Develop assays to confirm that therapeutic interventions successfully modulate NRIP3 activity

  • Monitor changes in the NRIP3-PPARα-DDI1-RTF2 axis in treated samples

Current research shows that NRIP3 protects ESCC tumor cells from DNA damage induced by chemoradiotherapy through the NRIP3-PPARα-DDI1-RTF2 axis , suggesting that disrupting this pathway could potentially restore treatment sensitivity in resistant tumors.