entr1 Antibody

What types of antibodies are available for ENTR1 detection?

Drawing from general antibody classification principles, ENTR1 antibodies can be categorized into three main types: polyclonal, monoclonal, and recombinant. Each type offers distinct advantages in research applications. Polyclonal antibodies recognize multiple epitopes on the ENTR1 protein, providing strong signal amplification but potentially lower specificity. Monoclonal antibodies bind to a single epitope, offering high specificity but potentially more limited detection capabilities. Recombinant antibodies, produced through in vitro methods, generally demonstrate superior performance characteristics compared to traditional monoclonal or polyclonal antibodies . For optimal experimental design, researchers should consider selecting recombinant ENTR1 antibodies when available, as studies have demonstrated that recombinant antibodies generally outperform monoclonal or polyclonal antibodies in terms of specificity and reproducibility .

What validation standards should be applied to ENTR1 antibodies?

Proper validation of ENTR1 antibodies requires a comprehensive approach using knockout cell lines as negative controls. Following standardized characterization methodologies, researchers should validate ENTR1 antibodies for each specific application (Western blot, immunoprecipitation, immunofluorescence) separately . The validation process should include:

• Specificity testing using ENTR1 knockout cell lines

• Sensitivity assessment across a range of ENTR1 expression levels

• Reproducibility testing across multiple experimental conditions

• Cross-reactivity evaluation against similar proteins

Research indicates that more than 50% of commercially available antibodies fail in one or more applications, highlighting the critical importance of thorough validation . A successful validation approach would include parental cell lines expressing sufficient levels of ENTR1 protein alongside knockout controls, with detection thresholds appropriate for antibodies with binding affinities in the 1-50 nM range .

How should I design experiments to study ENTR1 expression in cancer tissues?

When designing experiments to study ENTR1 expression in cancer tissues, implement a multi-modal approach that combines complementary techniques:

• Immunohistochemistry (IHC): For tissue localization and expression level assessment

  • Use validated ENTR1-specific antibodies

  • Include appropriate positive and negative controls

  • Employ standardized scoring systems (e.g., H-score, Allred score)

  • Compare MAC tissues with adjacent normal tissues

• RNA sequencing: For gene expression profiling

  • Classify patients into high- and low-expression groups based on ENTR1 levels

  • Correlate expression with clinical outcomes using Kaplan-Meier survival curves

  • Conduct ROC analyses to assess diagnostic potential

• Functional validation:

  • Assess correlation between ENTR1 expression and cancer stemness markers

  • Analyze relationship with immune cell infiltration using computational methods like CIBERSORT

This approach allows for comprehensive characterization of ENTR1's role in cancer progression and its potential as a prognostic biomarker. The experimental design should incorporate appropriate statistical analyses, including Wilcoxon and Kruskal-Wallis tests to analyze associations between ENTR1 expression and clinical characteristics .

What are the optimal conditions for immunoprecipitation using ENTR1 antibodies?

For optimal immunoprecipitation (IP) of ENTR1, consider the following methodological approach:

• Antibody selection:

  • Choose antibodies validated specifically for IP applications

  • Recombinant antibodies generally show superior performance compared to monoclonal or polyclonal antibodies

• Lysis buffer optimization:

  • Use buffers containing 1% NP-40 or Triton X-100 for initial extraction

  • Include protease inhibitors to prevent protein degradation

  • Adjust salt concentration (150-300 mM NaCl) based on ENTR1's interaction strength with binding partners

• Protocol parameters:

  • Pre-clear lysates with protein A/G beads to reduce non-specific binding

  • Incubate antibodies with lysates at 4°C overnight with gentle rotation

  • Perform stringent washing steps (at least 4-5 washes) to reduce background

  • Elute under denaturing conditions for direct analysis or native conditions for functional studies

• Controls:

  • Include IgG control from the same species as the ENTR1 antibody

  • Validate specificity using ENTR1 knockout cell lines

  • Include input controls to assess IP efficiency

The success of ENTR1 immunoprecipitation should be verified through Western blotting using a separate validated anti-ENTR1 antibody that recognizes a different epitope to confirm specificity of the pulled-down protein.

How can I quantitatively assess ENTR1 protein levels using Western blotting?

For quantitative assessment of ENTR1 protein levels using Western blotting, follow these methodological guidelines:

• Sample preparation:

  • Use standardized protein extraction protocols with phosphatase and protease inhibitors

  • Determine protein concentration using BCA or Bradford assays

  • Load equal amounts of protein (20-50 μg) per lane

• Antibody selection and optimization:

  • Use antibodies specifically validated for Western blot applications

  • Determine optimal antibody dilution through titration experiments

  • Select secondary antibodies with minimal cross-reactivity

• Quantification methodology:

  • Use housekeeping proteins (β-actin, GAPDH) or total protein stains as loading controls

  • Employ digital image analysis software for densitometry

  • Calculate relative expression as ratio of ENTR1 signal to loading control

  • Create standard curves using recombinant ENTR1 protein for absolute quantification

• Quality control measures:

  • Include positive and negative controls in each experiment

  • Validate antibody specificity using ENTR1 knockout cell lines

  • Assess linear dynamic range of detection

For comparing ENTR1 expression between different samples (e.g., tumor vs. normal tissue), include both sample types on the same blot to minimize technical variation, and normalize to appropriate loading controls to account for differences in total protein content.

How can I study the relationship between ENTR1 expression and immune cell infiltration?

To investigate the relationship between ENTR1 expression and immune cell infiltration, implement this comprehensive approach:

• Computational analysis of RNA-seq data:

  • Utilize algorithms like CIBERSORT to quantify 22 distinct immune cell populations

  • Apply ESTIMATE method to calculate immune, stromal, and ESTIMATE scores

  • Perform correlation analysis using Pearson's correlation coefficient between ENTR1 expression and immune parameters

  • Stratify samples into high and low ENTR1 expression groups based on median expression

• Multiplex immunofluorescence:

  • Use validated antibodies against ENTR1 and immune cell markers (CD8, CD4, etc.)

  • Employ spectral unmixing to distinguish multiple fluorophores

  • Quantify co-localization patterns using digital image analysis

• Flow cytometry of disaggregated tumor samples:

  • Create single-cell suspensions from fresh tumor samples

  • Stain for ENTR1 and immune cell markers

  • Analyze correlations between ENTR1 expression and immune cell percentages

• Validation experiments:

  • Use in vitro co-culture systems to assess direct effects of ENTR1 expression on immune cell function

  • Perform knockdown/overexpression studies to establish causality

Research has demonstrated that ENTR1 expression positively correlates with CD8+ T cell infiltration (p = 0.01) while showing negative correlation with stromal scores (correlation coefficient = -0.24, p = 0.03) . These findings suggest a potential role for ENTR1 in modulating the tumor immune microenvironment, particularly in relation to cytotoxic T cell recruitment.

What approaches can I use to investigate the association between ENTR1 and cancer cell stemness?

To investigate the association between ENTR1 and cancer cell stemness, employ these methodological approaches:

• Bioinformatic analysis:

  • Calculate RNA-based stemness scores (RNAss) using established algorithms

  • Perform correlation analysis between ENTR1 expression and stemness scores

  • Conduct Gene Set Enrichment Analysis (GSEA) to identify stemness-related pathways

  • Compare ENTR1 expression with known stemness markers (NANOG, OCT4, SOX2)

• Functional stemness assays:

  • Sphere formation assays with ENTR1 knockdown/overexpression cells

  • Serial dilution xenograft experiments to assess tumor-initiating capacity

  • Side population analysis to identify cells with stem-like properties

  • Limiting dilution assays to quantify stem cell frequency

• Molecular analysis:

  • ChIP-seq to identify ENTR1-associated regulatory elements in stemness genes

  • RNA-seq to profile transcriptional changes following ENTR1 modulation

  • Single-cell RNA-seq to identify ENTR1-high subpopulations with stemness properties

Current research has established a significant positive correlation between ENTR1 expression and cell stemness in mucinous adenocarcinoma (correlation coefficient = 0.44, p < 0.0001) . This suggests that ENTR1 may play a role in maintaining or promoting cancer stem cell properties, potentially contributing to tumor progression and therapeutic resistance.

How can I develop antibodies with custom specificity profiles for ENTR1 epitopes?

Developing antibodies with custom specificity profiles for ENTR1 epitopes requires a systematic approach combining experimental selection and computational modeling:

• Phage display selection strategy:

  • Design selection schemes against multiple ENTR1 epitopes

  • Perform positive selections against target epitopes

  • Implement negative selections against undesired epitopes

  • Sequence selected antibody clones using high-throughput sequencing

• Computational modeling and optimization:

  • Build energy-based models to predict binding specificities

  • Identify binding modes associated with each epitope

  • Optimize antibody sequences by minimizing energy functions for desired epitopes while maximizing them for undesired epitopes

  • Use the model to design novel sequences with predefined binding profiles

• Experimental validation:

  • Synthesize and express designed antibody sequences

  • Test binding specificity against multiple ENTR1 epitopes

  • Validate performance in relevant applications (WB, IP, IF)

This approach allows for the development of highly specific antibodies that can discriminate between closely related epitopes, which is particularly valuable for studying specific domains or post-translational modifications of ENTR1. Research has demonstrated that such computational approaches can successfully disentangle different binding modes even when they are associated with chemically very similar ligands .

How can I address non-specific binding issues with ENTR1 antibodies?

When encountering non-specific binding with ENTR1 antibodies, implement this systematic troubleshooting approach:

• Antibody validation assessment:

  • Verify antibody specificity using ENTR1 knockout cell lines

  • Test multiple antibodies targeting different ENTR1 epitopes

  • Consider switching to recombinant antibodies, which generally show better specificity

• Protocol optimization:

  • Increase blocking stringency (5% BSA or 5% milk in TBS-T)

  • Optimize antibody concentration through titration experiments

  • Increase washing duration and number of wash steps

  • Include competing peptides to block non-specific interactions

• Sample preparation improvements:

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

  • Use freshly prepared samples to minimize protein degradation

  • Optimize protein extraction conditions for ENTR1 detection

• Application-specific adjustments:

  Application	Troubleshooting Approach
  Western blot	Use gradient gels to better resolve ENTR1; optimize transfer conditions
  Immunofluorescence	Implement antigen retrieval; use detergents to improve penetration
  Flow cytometry	Optimize fixation/permeabilization; include viability dye to exclude dead cells
  Immunoprecipitation	Pre-clear lysates extensively; use more stringent wash buffers

Research indicates that more than 50% of commercial antibodies fail in one or more applications , emphasizing the importance of thorough validation and optimization for each specific application.

What metrics should I use to evaluate the quality of ENTR1 antibodies?

To comprehensively evaluate ENTR1 antibody quality, assess these key metrics:

• Specificity parameters:

  • Signal-to-noise ratio in Western blots comparing wild-type to ENTR1 knockout cells

  • Cross-reactivity profile against closely related proteins

  • Background levels in immunofluorescence using knockout controls

  • Off-target binding in immunoprecipitation-mass spectrometry experiments

• Sensitivity metrics:

  • Limit of detection (LOD) using recombinant ENTR1 protein dilution series

  • Dynamic range of quantification

  • Ability to detect endogenous ENTR1 in different cell types with varying expression levels

• Reproducibility assessment:

  • Intra-assay coefficient of variation (CV) across technical replicates

  • Inter-assay CV across independent experiments

  • Lot-to-lot consistency for the same antibody catalog number

• Application-specific performance:

  Application	Quality Metrics
  Western blot	Band specificity; linearity of signal; consistency of molecular weight
  Immunofluorescence	Signal localization; background levels; staining pattern consistency
  Immunohistochemistry	Staining intensity; background; correlation with RNA expression
  Flow cytometry	Population separation; staining index; correlation with other methods

Research suggests that recombinant antibodies generally demonstrate superior performance compared to monoclonal or polyclonal antibodies , making them the preferred choice for detecting ENTR1 in critical research applications.

How should I interpret contradictory results when using different ENTR1 antibodies?

When faced with contradictory results from different ENTR1 antibodies, follow this methodological framework for resolution:

• Systematic antibody validation:

  • Test all antibodies against ENTR1 knockout controls

  • Compare antibody performance across multiple applications

  • Verify epitope locations and potential overlap between antibodies

  • Assess if antibodies recognize different ENTR1 isoforms or post-translational modifications

• Orthogonal method validation:

  • Confirm ENTR1 expression using RNA-based methods (qPCR, RNA-seq)

  • Use genetic approaches (siRNA, CRISPR) to manipulate ENTR1 levels

  • Apply mass spectrometry to definitively identify ENTR1 protein

  • Correlate findings with functional assays related to ENTR1 activity

• Technical consideration analysis:

  • Evaluate whether discrepancies are application-specific

  • Assess if sample preparation methods affect epitope accessibility

  • Consider fixation and antigen retrieval effects on epitope detection

  • Examine buffer conditions that might affect antibody performance

• Research literature assessment:

  • Review publications that have used the same antibodies

  • Contact manufacturers for additional validation data

  • Consider consulting public antibody validation repositories

How can ENTR1 antibodies be used to develop prognostic assays for colorectal cancer?

Developing prognostic assays using ENTR1 antibodies requires a systematic approach:

• Standardized immunohistochemistry protocol:

  • Select highly validated ENTR1 antibodies with proven specificity

  • Establish standardized staining protocols and scoring systems

  • Develop automated image analysis algorithms for quantification

  • Validate on tissue microarrays with known clinical outcomes

• Prognostic model development:

  • Determine optimal cutoff values for ENTR1 expression

  • Integrate ENTR1 with other prognostic markers

  • Perform multivariate analysis adjusting for clinicopathological variables

  • Validate in independent patient cohorts

• Clinical implementation considerations:

  • Develop standard operating procedures for clinical laboratories

  • Establish quality control measures for reproducibility

  • Create reference standards for inter-laboratory comparisons

  • Design reporting formats with clear clinical interpretation guidelines

What methodologies can I use to investigate the functional mechanisms of ENTR1 in cancer progression?

To investigate ENTR1's functional mechanisms in cancer progression, implement these methodological approaches:

• Genetic manipulation strategies:

  • CRISPR/Cas9 knockout of ENTR1 in cancer cell lines

  • Inducible shRNA systems for temporal control of ENTR1 knockdown

  • Overexpression of wild-type and mutant ENTR1 variants

  • Domain-specific mutations to identify functional regions

• Molecular interaction studies:

  • Co-immunoprecipitation with validated ENTR1 antibodies

  • Proximity labeling (BioID, APEX) to identify ENTR1 interaction partners

  • Yeast two-hybrid or mammalian two-hybrid screening

  • Pull-down assays with recombinant ENTR1 protein domains

• Functional assays:

  • Cell proliferation, migration, and invasion assays

  • 3D organoid culture systems

  • In vivo xenograft models with ENTR1-modified cells

  • Pathway activity assessment using reporter assays

• Mechanistic investigations:

  • Transcriptome analysis following ENTR1 modulation

  • ChIP-seq to identify ENTR1-associated genomic regions

  • Protein localization studies using fractionation and imaging

  • Phospho-proteomic analysis to identify signaling pathways

GSEA analysis has revealed that ENTR1 expression is associated with pyrimidine metabolism (FDR = 0.026) , providing initial insights into potential molecular mechanisms. Additionally, the significant correlation between ENTR1 expression and cancer cell stemness suggests involvement in maintaining stem-like properties in cancer cells , which could be further investigated using the methodologies outlined above.

How can I apply antibody engineering principles to develop ENTR1-targeting therapeutic antibodies?

Developing ENTR1-targeting therapeutic antibodies requires combining antibody engineering principles with thorough understanding of ENTR1 biology:

• Target epitope identification:

  • Identify accessible epitopes on ENTR1 in disease states

  • Map functional domains critical for ENTR1's pathological role

  • Assess epitope conservation across species for preclinical testing

  • Evaluate potential cross-reactivity with related proteins

• Antibody format optimization:

  • Compare conventional IgG formats with alternative scaffolds

  • Evaluate fragment formats (Fab, scFv) for improved tissue penetration

  • Consider bispecific formats to engage immune effector cells

  • Assess antibody-drug conjugate potential if ENTR1 is internalized

• Affinity maturation and specificity engineering:

  • Apply computational models to design custom specificity profiles

  • Use phage display with positive/negative selection strategies

  • Implement deep mutational scanning to identify beneficial mutations

  • Optimize binding kinetics for therapeutic applications

• Functional screening:

  • Develop cell-based assays to assess functional antagonism

  • Evaluate effects on ENTR1-dependent signaling pathways

  • Assess impacts on cancer cell stemness given ENTR1's correlation with stemness markers

  • Test effects on immune cell recruitment given ENTR1's correlation with CD8+ T cell infiltration

The computational approach described in the research literature enables the design of antibodies with customized specificity profiles, either with specific high affinity for particular target epitopes or with cross-specificity for multiple targets . This methodology could be applied to develop ENTR1 antibodies with precisely engineered binding properties for therapeutic applications.

What are the best approaches to investigate ENTR1 expression in patient-derived xenograft models?

To effectively investigate ENTR1 expression in patient-derived xenograft (PDX) models, implement these methodological approaches:

• Species-specific antibody selection:

  • Choose antibodies that specifically recognize human ENTR1 without cross-reactivity to mouse ENTR1

  • Validate specificity using tissues from both species

  • Consider using antibodies recognizing different epitopes to confirm findings

  • Select recombinant antibodies when available for improved specificity

• Multi-modal analysis:

  • Combine immunohistochemistry with RNA-seq for comprehensive profiling

  • Use RNAscope for in situ visualization of ENTR1 mRNA

  • Implement laser capture microdissection to separate tumor from stromal components

  • Apply single-cell analysis techniques to assess heterogeneity

• Longitudinal monitoring:

  • Establish sampling protocols at different stages of PDX establishment

  • Compare ENTR1 expression between primary tumor and derived PDX models

  • Track expression changes across PDX passages

  • Correlate with treatment responses and tumor evolution

• Analytical framework:

  • Develop quantitative scoring systems for ENTR1 protein expression

  • Implement image analysis algorithms for automated quantification

  • Apply statistical methods to assess correlations with clinical parameters

  • Integrate with broader multi-omics datasets from the same models

This approach allows for comprehensive characterization of ENTR1 expression patterns in PDX models, providing insights into its role in tumor maintenance, progression, and response to therapies. Given ENTR1's established association with cell stemness and immune infiltration , PDX models offer valuable opportunities to investigate these relationships in a more physiologically relevant context than conventional cell line models.