NME1 Antibody

What is NME1 and why is it significant in cancer research?

NME1 (Non-Metastatic Cells 1, Protein NM23A Expressed in) is a metastasis suppressor protein first identified through differential hybridization between murine melanoma sub-lines with varying metastatic capacities. Highly metastatic sub-lines exhibit significantly lower levels of nm23 than less metastatic cells . NME1 possesses nucleoside diphosphate kinase (NDPK) activity, catalyzing the phosphorylation of nucleoside diphosphates to corresponding triphosphates . Its significance stems from its role in regulating metastatic potential across multiple cancer types, with decreased expression notably connected to aggressive behavior in melanoma, breast, colon, and gastric carcinomas, while elevated levels are observed in advanced thyroid carcinomas and neuroblastoma .

What applications are NME1 antibodies commonly used for?

NME1 antibodies are utilized across multiple experimental applications including:

• Western Blotting (WB)

• Immunohistochemistry (IHC) on paraffin-embedded sections

• Enzyme-linked immunosorbent assay (ELISA)

• Flow Cytometry (FACS)

• Immunocytochemistry (ICC)

• Immunoprecipitation (IP)

• RNA interference (RNAi) validation

Selection of the appropriate antibody should be based on the specific application and species reactivity requirements, with monoclonal antibodies offering greater specificity and polyclonal antibodies providing stronger signals in certain applications.

How do I properly validate an NME1 antibody for my research?

Proper validation of NME1 antibodies requires multiple approaches:

• Specificity testing: Verify using positive and negative controls, including:

  • Cell lines with known NME1 expression levels

  • NME1 knockout or knockdown models

  • Tissue samples with documented NME1 expression

• Cross-reactivity assessment: Test for potential cross-reactivity with related proteins, particularly NME2 which shares 90% sequence identity with NME1 .

• Application-specific validation:

  • For WB: Confirm a single band at the expected molecular weight (18-23 kDa)

  • For IHC: Compare staining patterns with literature reports and include appropriate controls

  • For IP: Verify pulled-down protein by mass spectrometry or western blot

• Literature verification: Cross-reference your findings with published studies using the same or similar antibodies .

What are the key differences between monoclonal and polyclonal NME1 antibodies in research applications?

Selection depends on experimental goals: use monoclonals when absolute specificity is required and polyclonals when detection sensitivity is paramount. For quantitative analyses comparing NME1 levels across different samples, monoclonal antibodies generally provide more consistent results .

How should I optimize immunohistochemistry protocols for NME1 detection in different cancer tissues?

Optimizing IHC for NME1 requires tissue-specific considerations:

• Fixation and antigen retrieval:

  • Most NME1 antibodies work with formalin-fixed paraffin-embedded (FFPE) tissues

  • Heat-induced epitope retrieval (HIER) using citrate buffer (pH 6.0) is typically effective

  • For challenging tissues, try EDTA buffer (pH 9.0) as an alternative

• Dilution optimization:

  • Start with manufacturer's recommendation (typically 1:100 for IHC as specified for some antibodies)

  • Perform a dilution series (1:50 to 1:500) to determine optimal signal-to-noise ratio

  • Include positive control tissues (e.g., normal breast tissue, lymph nodes)

• Detection systems:

  • For low expression tissues: use high-sensitivity detection systems

  • For quantitative analysis: consider automated platforms for consistency

• Cancer-specific considerations:

  • Breast cancer: Compare DCIS regions with invasive components (NME1 levels drop in invasive components)

  • Melanoma: Higher background melanin can interfere with DAB detection; consider alternative chromogens

  • Neuroblastoma: Include normal adrenal tissue as reference

• Validation strategy:

  • Use multiple antibodies targeting different epitopes

  • Correlate with RNA expression data when available

What controls should be included when performing western blot analysis for NME1?

A comprehensive control strategy for NME1 western blotting includes:

• Positive controls:

  • Cell lines with known NME1 expression (e.g., non-metastatic melanoma lines)

  • Recombinant NME1 protein (purified or overexpressed)

• Negative controls:

  • NME1 knockdown or knockout cell lines

  • Highly metastatic cell lines with low NME1 expression

• Specificity controls:

  • Pre-adsorption of antibody with immunizing peptide

  • Secondary antibody-only control

  • Isotype control for monoclonal antibodies

• Loading controls:

  • Standard housekeeping proteins (β-actin, GAPDH)

  • Total protein staining methods (Ponceau S, REVERT)

• Size verification:

  • Molecular weight markers to confirm NME1 band (approximately 18-23 kDa)

  • Note any post-translational modifications that may alter migration

• Sample preparation considerations:

  • Fresh vs. frozen samples

  • Protein extraction method consistency

  • Protease and phosphatase inhibitors inclusion

How can I distinguish between different NME family members in my experiments?

Distinguishing between NME family members requires careful experimental design:

• Antibody selection strategy:

  • Use antibodies targeting non-conserved regions (particularly C-terminal domains)

  • Verify specificity against recombinant NME proteins (particularly NME1 vs. NME2)

  • For western blot, utilize slight molecular weight differences (NME1: 18 kDa, NME2: 17 kDa)

• Experimental approaches:

  • Immunoprecipitation followed by mass spectrometry for definitive identification

  • siRNA/shRNA knockdown of specific NME members as validation controls

  • Expression of tagged constructs for specific detection

• Functional assays to distinguish NME1:

  • NDPK activity assays in the presence of specific inhibitors

  • CaMKII activity modulation (unique to NME1 at nanomolar concentrations)

  • Metastasis suppression assays in appropriate cell models

• Technical considerations:

  • Run extended SDS-PAGE gels for better separation of closely related proteins

  • Consider 2D gel electrophoresis to separate based on both size and charge

  • Use reciprocal verification with multiple antibodies

What are the mechanisms behind contradictory roles of NME1 in different cancer types, and how can antibody-based studies address this?

The paradoxical roles of NME1 across cancer types can be investigated through:

• Tissue-specific expression pattern analysis:

  • Use immunohistochemistry to map NME1 localization differences between cancer types

  • Compare nuclear vs. cytoplasmic distribution using subcellular fractionation and immunoblotting

  • Correlate expression patterns with clinical outcomes across cancer types

• Post-translational modification analysis:

  • Employ phospho-specific antibodies to detect serine phosphorylation sites (Ser122, Ser144)

  • Investigate CoAlation of NME1 at Cys109 under oxidative stress conditions

  • Examine how these modifications affect function in different cellular contexts

• Protein-protein interaction studies:

  • Use co-immunoprecipitation with NME1 antibodies to identify tissue-specific binding partners

  • Compare interaction profiles between cancers where NME1 has opposite effects

  • Investigate concentration-dependent effects on partners like CaMKII

• Functional heterogeneity investigations:

  • Examine NME1 expression in cancer stem cell populations vs. bulk tumor cells

  • Correlate with stem cell markers (Sox2, Sox10, Oct-4, KLF4)

  • Investigate cell-to-cell variability using single-cell techniques

• Experimental design considerations:

  • Include multiple cancer types in comparative studies

  • Use identical experimental conditions and antibody concentrations

  • Account for tumor microenvironment factors

How can NME1 antibodies be employed to study its concentration-dependent dual role in modulating CaMKII activity?

Investigating NME1's biphasic regulation of CaMKII requires sophisticated antibody applications:

• Quantitative immunofluorescence approach:

  • Use calibrated immunofluorescence with NME1 antibodies to measure endogenous protein concentrations

  • Correlate with CaMKII activity measurements in the same cells

  • Employ ratiometric imaging to determine local concentrations at subcellular levels

• Proximity-based detection methods:

  • Implement proximity ligation assays (PLA) to detect NME1-CaMKII interactions

  • Compare interaction frequencies under conditions with different NME1 concentrations

  • Correlate with functional outcomes using phospho-specific antibodies for CaMKII substrates

• In vitro reconstitution experiments:

  • Utilize purified components with titrated NME1 concentrations

  • Include antibodies to:

    • Block specific domains of NME1

    • Immunoprecipitate complexes at different concentration points

    • Detect autophosphorylation of CaMKII at Thr286

• Advanced microscopy techniques:

  • Super-resolution microscopy to visualize nanoscale interactions

  • FRET-based approaches to monitor real-time interactions

  • Single-molecule tracking to examine dynamic associations

• Experimental validation strategy:

  • Include NME1 mutants (H118F, S120G) that retain specific functions

  • Use concentration ranges spanning nanomolar (enhancement) to micromolar (inhibition)

  • Distinguish between effects on S-type vs. T-type CaMKII substrates

What methodological approaches can address the contradictory findings regarding NME1's role in melanoma progression?

Resolving contradictory findings on NME1 in melanoma requires integrated approaches:

• Patient sample stratification:

  • Use NME1 antibodies for immunohistochemical analysis of large cohorts

  • Stratify by disease stage, genetic background, and treatment history

  • Correlate NME1 expression with melanoma stem cell markers

• Functional heterogeneity assessment:

  • Compare NME1 levels in melanoma spheres vs. monolayer cultures

  • Sort cells based on NME1 expression levels for functional assays

  • Investigate cell cycle status of NME1-high vs. NME1-low populations

• Experimental model considerations:

  • Compare in vitro findings with in vivo xenograft models

  • Utilize genetic manipulation approaches:

    • CRISPR/Cas9 knockout followed by rescue with mutant variants

    • Inducible expression systems to control NME1 levels temporally

  • Account for microenvironmental factors (hypoxia, immune components)

• Multi-omics integration:

  • Correlate protein expression (antibody-based) with:

    • Transcriptomic data

    • Epigenetic modifications at the NME1 promoter

    • Post-translational modifications

• Technical validation strategy:

  • Use multiple antibody clones targeting different epitopes

  • Validate antibody specificity in CRISPR-edited cell lines

  • Include appropriate controls for each experimental system

What are common technical challenges when using NME1 antibodies, and how can they be addressed?

How can I quantitatively assess NME1 protein levels in patient samples for prognostic studies?

Quantitative assessment of NME1 in patient samples requires standardized approaches:

• IHC scoring systems:

  • Implement H-score (0-300) combining intensity and percentage of positive cells

  • Use automated digital pathology platforms for unbiased quantification

  • Include tissue microarrays with control samples for normalization

• Quantitative protein analysis:

  • Consider reverse phase protein arrays (RPPA) for high-throughput analysis

  • Use ELISA with recombinant protein standard curves

  • Implement digital western blot technologies with internal standards

• Quality control measures:

  • Include calibration standards on each slide/blot

  • Process all samples with identical protocols

  • Implement blinded scoring by multiple observers

• Clinical correlation approaches:

  • Match NME1 expression with clinical parameters using multivariate analysis

  • Establish thresholds based on outcome correlations

  • Consider combining with other biomarkers for improved prognostic value

• Sample consideration:

  • Account for tumor heterogeneity through multiple sampling

  • Compare primary tumors with metastatic lesions when available

  • Document preservation methods and processing times

What approaches can help investigate the relationship between NME1's enzymatic activities and its metastasis suppressor function?

Investigating the connection between NME1's enzymatic functions and metastasis suppression requires:

• Structure-function analysis:

  • Use NME1 antibodies to detect mutant proteins with specific enzymatic deficiencies:

    • H118F (lacks all enzymatic activities)

    • S120G (deficient in protein phosphotransfer)

    • P96S (reduced NDPK activity)

  • Correlate expression with metastatic potential in cellular models

• Activity-specific assays:

  • NDPK activity measurements using coupled enzymatic assays

  • Histidine kinase activity using phosphohistidine-specific antibodies

  • 3'-5' exonuclease activity through nuclease assays

  • CoAlation status under oxidative stress conditions

• Domain-specific blocking strategies:

  • Use antibodies targeting specific functional domains

  • Complement with domain-specific inhibitors

  • Engineer domain-specific dominant negatives

• Pathway analysis approaches:

  • Identify downstream targets of each enzymatic activity

  • Use phospho-specific antibodies to monitor relevant signaling pathways

  • Correlate pathway activation with metastatic phenotypes

• In vivo validation strategies:

  • Generate xenograft models with enzymatic mutants

  • Use inducible systems to modulate activity temporally

  • Perform rescue experiments with domain-specific mutants

How can single-cell analysis techniques be combined with NME1 antibodies to understand its heterogeneous expression in tumor microenvironments?

Integrating single-cell techniques with NME1 antibodies enables:

• Single-cell protein analysis approaches:

  • Mass cytometry (CyTOF) with metal-conjugated NME1 antibodies

  • Multiplexed ion beam imaging (MIBI) for spatial context

  • Imaging mass cytometry for tissue section analysis with cellular resolution

• Combined protein-RNA analysis:

  • CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing)

  • REAP-seq (RNA Expression and Protein Sequencing)

  • These approaches allow correlation of NME1 protein levels with transcriptome-wide expression

• Spatial proteomics applications:

  • Multiplexed immunofluorescence with NME1 and microenvironment markers

  • Digital spatial profiling for quantitative assessment

  • Correlation with geographic features (hypoxic regions, invasion fronts)

• Live-cell NME1 dynamics:

  • Antibody fragments for live cell imaging

  • Nanobody-based detection systems

  • Correlation with cell behavior using time-lapse microscopy

• Data integration strategies:

  • Computational approaches to integrate protein, RNA, and spatial data

  • Machine learning algorithms to identify patterns in heterogeneous expression

  • Trajectory analysis to map NME1 changes during cancer progression

What are the best methodological approaches to study NME1's role in activating transcription of target genes like ALDOC?

Investigating NME1's transcriptional regulatory functions requires:

• Chromatin association studies:

  • Chromatin immunoprecipitation (ChIP) with NME1 antibodies followed by sequencing

  • CUT&RUN or CUT&Tag for higher resolution and lower background

  • Sequential ChIP to identify co-factors at target promoters

• Transcriptional activity assessment:

  • Measure pre-mRNA levels of target genes like ALDOC

  • Use reporter assays with promoter-luciferase constructs

  • Analyze epigenetic activation markers (H3K4me3, H3K27ac) at target promoters

• Protein-DNA interaction characterization:

  • Electrophoretic mobility shift assays (EMSA) with recombinant NME1

  • DNA pulldown assays followed by western blotting with NME1 antibodies

  • Microscale thermophoresis to measure binding affinities

• Mechanistic studies:

  • RNA polymerase II recruitment analysis using ChIP

  • Investigation of chromatin remodeling complex interactions

  • Analysis of NME1 domains required for transcriptional activation

• Functional validation approaches:

  • CRISPR-mediated deletion of NME1 binding sites in target promoters

  • Rescue experiments with NME1 mutants lacking DNA binding capacity

  • Correlation of binding with transcriptional output using RT-qPCR

How can multi-parametric analysis combining NME1 expression with other markers improve cancer prognosis assessment?

Advanced prognostic approaches combining NME1 with other markers include:

• Multiplexed protein detection systems:

  • Multiplexed immunofluorescence with NME1 and other biomarkers

  • Mass spectrometry-based imaging for simultaneous detection of multiple proteins

  • Digital spatial profiling for quantitative assessment in tissue context

• Integrated biomarker panels:

  • Combine NME1 with:

    • MT1-MMP (inversely correlated in invasive breast cancer)

    • Stem cell markers (Sox2, Sox10, Oct-4) in melanoma

    • Dynamin-2 for endocytic pathway analysis

  • Develop weighted algorithms for prognostic scoring

• Multi-omics integration approaches:

  • Correlate protein expression with:

    • Mutation profiles

    • Methylation patterns

    • microRNA expression

  • Implement machine learning for pattern recognition

• Dynamic assessment strategies:

  • Monitor NME1 levels in circulating tumor cells

  • Analyze in liquid biopsies during treatment

  • Correlate changes with treatment response

• Validation and implementation:

  • Retrospective analysis on tissue microarrays with long-term follow-up

  • Prospective collection in clinical trials

  • Development of standardized reporting guidelines