NEO1 Antibody

What is NEO1 and what are its primary biological functions?

NEO1 (Neogenin-1) was originally identified as a homologue of the Deleted in Colorectal Cancer (DCC) gene and functions as a receptor for Netrins and Repulsive Guidance Molecule (RGM) proteins. Beyond its initial characterization in neuronal guidance, NEO1 plays crucial roles in inflammation resolution, tissue regeneration, apoptosis, differentiation, adhesion, and migration. Research has demonstrated that NEO1 regulates neutrophil migration into injury sites, neutrophil apoptosis, phagocytosis of apoptotic cells, and the biosynthesis of specialized proresolving mediators such as lipoxin A4, maresin-1, and protectin DX . NEO1 expression is particularly restricted to inflammatory Ly6Chi monocytes, indicating its cell-type specific functions in the inflammatory response .

How does NEO1 contribute to inflammation and what signaling pathways does it modulate?

NEO1 plays a significant role in modulating inflammatory responses through specific signaling networks. Studies have revealed that NEO1 deficiency affects inflammation by activating the PI3K/AKT pathway and suppressing the TGF-β pathway, both critical in restraining proinflammatory responses and promoting anti-inflammatory actions . This pathway modulation leads to monocyte polarization toward an anti-inflammatory and proresolving phenotype, characterized by reduced levels of proinflammatory cytokines including IL-6, KC, MIP2, and MCP-1 . During the resolution phase of inflammation, NEO1 influences neutrophil lifespan, with its inhibition inducing neutrophil apoptosis—a key feature initiating inflammation resolution mechanisms .

What is the expression pattern of NEO1 in normal tissues versus pathological conditions?

NEO1 shows varied expression patterns across different tissues and pathological states. In colorectal cancer (CRC), NEO1 is significantly downregulated compared to adjacent normal tissues, with expression decreasing as cancer progresses . This downregulation has been confirmed through multiple databases including Oncomine, The Cancer Genome Atlas (TCGA), and independent datasets (Gaedcke, Hong, Skrzypczak, and Zou), which consistently show lower NEO1 expression in various types of colorectal malignancies including colon adenocarcinoma (fold change = -2.665), rectal adenocarcinoma (fold change = -2.450), cecum adenocarcinoma (fold change = -2.037), and colon mucinous adenocarcinoma (fold change = -2.099) . In inflammatory conditions, NEO1 expression increases and correlates with disease severity, as demonstrated in critically ill ICU pediatric patients where plasma NEO1 levels strongly correlate with intraabdominal hypertension, abdominal compartment syndrome, severity of illness, ICU length of stay, and mortality .

What are the primary research applications for NEO1 antibodies?

NEO1 antibodies serve multiple crucial research applications: (1) Functional inhibition studies—anti-NEO1 antibodies can be used to block NEO1 activity, which has been shown to induce neutrophil apoptosis, enhance phagocytosis of apoptotic cells, and increase expression of decoy receptors like IL-1R2 that limit proinflammatory effects ; (2) Therapeutic potential evaluation—treatment with anti-NEO1 antibody significantly reduces experimental hepatic ischemia and reperfusion injury, with associated decreases in lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, and cytokine levels ; (3) Biomarker studies—NEO1 antibodies can be used to quantify NEO1 expression levels, which correlate with disease progression in colorectal cancer and severity in inflammatory conditions ; (4) Mechanistic investigations—NEO1 antibodies facilitate research into signaling pathways affected by NEO1, including PI3K/AKT and TGF-β pathways .

How can NEO1 antibodies be used to study inflammation resolution mechanisms?

NEO1 antibodies provide valuable tools for investigating inflammation resolution through several methodological approaches. Researchers can use anti-NEO1 antibodies to functionally inhibit NEO1, which studies have shown induces apoptosis of neutrophils—a critical step in inflammation resolution . This can be assessed using flow cytometry for apoptosis markers after 20-hour incubation with anti-NEO1 antibodies in the presence or absence of inflammatory stimuli such as LPS (100 ng/ml) . Additionally, NEO1 antibodies can be employed to examine expression of decoy receptors like IL-1R2, which limit proinflammatory effects of IL-1β . In phagocytosis assays, adding anti-NEO1 antibodies significantly increases phagocytosis rates of apoptotic cells in a dose-dependent manner, which can be confirmed through both functional assays and immunofluorescence analysis . Furthermore, researchers can use quantitative PCR to measure how anti-NEO1 antibody treatment affects expression of G protein-coupled receptors (GPCRs) such as ALX/FPR2 and DRV1/GPR32, which are known to mediate proresolving actions .

What phenotypic changes can be observed when using NEO1 antibodies in experimental systems?

When employing NEO1 antibodies in experimental systems, researchers can observe several significant phenotypic changes: (1) Enhanced neutrophil apoptosis—functional inhibition of NEO1 shortens neutrophil lifespan and increases apoptotic markers ; (2) Increased phagocytosis—anti-NEO1 treatment significantly increases the rate of phagocytosis of apoptotic cells and bacteria in a dose-dependent manner ; (3) Altered monocyte polarization—in the absence of NEO1 function, there is a significant reduction in proinflammatory Ly6Chi monocytes and an increase in anti-inflammatory Ly6Clo monocytes ; (4) Reduced inflammatory cytokine production—NEO1 inhibition leads to decreased levels of IL-6, KC, MIP2, and MCP-1 in inflammatory exudates ; (5) Enhanced expression of proresolving receptors—stimulation with anti-NEO1 antibodies augments mRNA levels of ALX/FPR2 and DRV1/GPR32 receptors in macrophages ; (6) Improved tissue protection—in liver ischemia-reperfusion models, anti-NEO1 antibody treatment results in attenuated serum levels of damage markers like lactate dehydrogenase and improved tissue histology .

What controls should be included when performing NEO1 antibody-based experiments?

When designing NEO1 antibody-based experiments, several controls are essential for result validation: (1) Isotype-matched control antibodies—these should be included to determine non-specific antibody effects; (2) Vehicle controls—when testing the impact of anti-NEO1 antibodies on inflammation, include vehicle-only treatments alongside stimuli (e.g., LPS 100 ng/ml) and antibody treatments ; (3) Genetic controls—where possible, include NEO1-deficient (Neo1-/-) samples alongside antibody treatments to confirm specificity of observed effects ; (4) Dose-response experiments—establish optimal antibody concentrations by performing dose-response studies, particularly for phagocytosis assays where anti-NEO1 antibodies show dose-dependent effects ; (5) Time-course experiments—include multiple time points to capture dynamic processes such as neutrophil apoptosis (typically assessed after 20 hours) and inflammation resolution ; (6) Pathway inhibitors—when investigating NEO1-dependent signaling, include controls with specific inhibitors of implicated pathways (e.g., PI3K/AKT or TGF-β pathway inhibitors) .

What are the optimal conditions for using NEO1 antibodies in functional inhibition studies?

For optimal NEO1 functional inhibition studies, researchers should consider several methodological parameters: (1) Antibody concentration—titrate anti-NEO1 antibody concentrations to determine optimal inhibitory effects without non-specific actions; (2) Cell types—NEO1 expression is particularly restricted to inflammatory Ly6Chi monocytes, making these cells ideal targets for NEO1 inhibition studies ; (3) Timing—in neutrophil apoptosis studies, a 20-hour incubation period with anti-NEO1 antibodies has been shown to effectively induce apoptosis ; (4) Combinatorial stimulation—consider combining anti-NEO1 antibodies with inflammatory stimuli such as LPS (100 ng/ml) or IL-1β to study contextual effects ; (5) Readout selection—choose appropriate assays to measure desired endpoints, such as flow cytometry for apoptosis assessment, immunofluorescence for phagocytosis visualization, and qPCR for receptor expression analysis ; (6) Environmental conditions—maintain consistent temperature, CO2 levels, and media compositions across experimental and control groups to minimize variability. For in vivo studies, antibody delivery route, dosage, and timing relative to injury or inflammation induction are critical parameters that require optimization.

How can researchers effectively quantify NEO1 expression in experimental and clinical samples?

Effective quantification of NEO1 expression requires multi-modal approaches depending on the sample type: (1) Quantitative real-time PCR—for mRNA quantification, design primers specific to NEO1 (avoiding cross-reactivity with related genes like DCC) and normalize to appropriate housekeeping genes ; (2) Western blotting—for protein quantification, use validated anti-NEO1 antibodies and appropriate loading controls (e.g., Arf1 has been used in yeast studies) ; (3) Immunohistochemistry/immunofluorescence—for tissue localization studies, optimize antibody concentration, antigen retrieval methods, and blocking conditions to minimize background; (4) Flow cytometry—for cell-specific expression analysis, particularly useful for identifying NEO1-expressing Ly6Chi monocytes in inflammatory contexts ; (5) ELISA—for quantifying soluble NEO1 in blood plasma or other biological fluids from clinical samples ; (6) Bioinformatics approaches—leverage public databases like TCGA and Oncomine to analyze NEO1 expression across tissue types and pathological conditions . When analyzing clinical samples, researchers should stratify data according to relevant clinical parameters (e.g., disease stage, severity scores like PRISM-III, or survival outcomes) to identify correlations with NEO1 expression .

How does NEO1 contribute to colorectal cancer progression and what are its potential applications as a prognostic biomarker?

NEO1's role in colorectal cancer (CRC) progression involves complex mechanisms that warrant detailed investigation. Studies have shown that NEO1 is significantly downregulated in CRC compared to adjacent normal tissues, with expression decreasing as cancer progresses . This downregulation pattern has been validated across multiple datasets with substantial fold changes ranging from -1.756 to -2.949 . Functionally, NEO1 appears to act as a tumor suppressor in CRC, as NEO1 overexpression restrains proliferation, migration, and invasion of CRC cells, while its knockdown produces opposite effects . Gene Set Enrichment Analysis (GSEA) reveals that low NEO1 expression samples are enriched in inflammation-related signaling pathways, epithelial-mesenchymal transition (EMT), and angiogenesis—all critical processes in cancer advancement .

For prognostic applications, survival analyses demonstrate that low NEO1 expression correlates with poor prognosis in CRC patients . This suggests that NEO1 quantification could serve as a valuable prognostic biomarker to stratify patients and inform treatment decisions. Future research should focus on developing standardized NEO1 detection methods for clinical samples, establishing threshold values for prognostic significance, and investigating whether NEO1 status can predict response to specific cancer therapies.

What are the contradictions in NEO1 function across different disease models and how can these be reconciled?

NEO1 exhibits apparently contradictory functions across different disease models that require careful analysis to reconcile. In inflammatory conditions, NEO1 appears to promote inflammation, as its inhibition or deficiency leads to enhanced resolution of inflammation, increased neutrophil apoptosis, and greater phagocytosis of apoptotic cells . Conversely, in colorectal cancer, NEO1 seems to function as a tumor suppressor, with its decreased expression correlating with cancer progression and poorer outcomes .

Future research should employ tissue-specific and inducible knockout models, along with time-course analyses, to dissect these seemingly contradictory functions of NEO1 across disease contexts.

How do post-translational modifications affect NEO1 function and antibody recognition?

Post-translational modifications (PTMs) of NEO1 likely play crucial roles in modulating its function and antibody recognition, though this area remains underexplored. Potential PTMs affecting NEO1 include: (1) Phosphorylation—NEO1's interaction with signaling pathways like PI3K/AKT suggests possible regulation through phosphorylation events ; (2) Glycosylation—as a transmembrane receptor, NEO1 likely undergoes N-linked and O-linked glycosylation, potentially affecting ligand binding and stability; (3) Proteolytic processing—many guidance receptors undergo proteolytic cleavage to generate active fragments; (4) Ubiquitination—which could regulate NEO1 turnover and availability.

These PTMs may significantly impact antibody recognition by altering epitope accessibility or conformation. Researchers should consider using antibodies targeting different epitopes when studying NEO1 in diverse contexts. For mechanistic studies, comparing results obtained with antibodies recognizing different domains of NEO1 can provide insights into domain-specific functions. Additionally, treatments affecting PTMs (e.g., phosphatase inhibitors, glycosylation inhibitors) may alter NEO1 detection patterns and should be controlled for in experimental designs.

Future studies should employ mass spectrometry-based approaches to comprehensively map NEO1 PTMs across different tissues and disease states, correlating these modifications with functional outcomes and antibody recognition patterns.

What are common pitfalls in NEO1 antibody selection and how can these be avoided?

Selecting appropriate NEO1 antibodies requires careful consideration to avoid several common pitfalls: (1) Cross-reactivity—as NEO1 shares homology with DCC, antibodies may cross-react with related proteins, necessitating validation using NEO1-deficient samples or knockdown controls ; (2) Epitope accessibility—NEO1's structure and interaction with binding partners may mask certain epitopes, requiring antibodies targeting different regions for comprehensive analysis; (3) Sensitivity to fixation—some epitopes may be sensitive to fixation methods, requiring optimization of fixation protocols for immunohistochemistry or immunofluorescence; (4) Lot-to-lot variability—particularly with polyclonal antibodies, which may show variability between production batches; (5) Application-specific performance—antibodies performing well in one application (e.g., Western blotting) may not work effectively in others (e.g., immunoprecipitation).

To avoid these pitfalls, researchers should: validate antibodies using positive and negative controls (including NEO1-deficient samples where available); test multiple antibodies targeting different epitopes; perform appropriate blocking experiments; and thoroughly document antibody details (including catalog number, lot number, and dilution) in publications to ensure reproducibility.

How can researchers optimize NEO1 knockdown or overexpression systems for functional studies?

Optimizing NEO1 knockdown or overexpression systems requires careful methodological considerations:

For knockdown approaches: (1) siRNA design—use validated siRNA sequences such as those reported in the literature (e.g., siNEO1 #1: GACCAAAGGTCGAAGATCA, siNEO1 #2: GAGCTGTCTATGACCGATA) ; (2) Transfection optimization—determine optimal transfection reagent concentrations and incubation times for target cell types; (3) Knockdown verification—confirm NEO1 reduction at both mRNA (qPCR) and protein (Western blot) levels; (4) Controls—include scrambled siRNA controls to account for non-specific effects ; (5) Timing—establish appropriate time points post-transfection for functional assays based on NEO1 protein half-life.

For overexpression approaches: (1) Vector selection—commercial plasmids like pCMV3-NEO1 have been successfully used ; (2) Transfection efficiency—optimize transfection protocols for target cell lines and consider stable transfection for long-term studies; (3) Expression verification—confirm NEO1 overexpression through Western blotting and/or immunofluorescence; (4) Controls—include empty vector controls (e.g., pCMV3) to account for transfection effects ; (5) Physiological relevance—consider whether expression levels achieved are within physiologically relevant ranges.

For both approaches, researchers should perform dose-response and time-course experiments to determine optimal conditions for functional studies, and consider cell type-specific factors that might influence NEO1 expression and function.

What techniques are available for studying NEO1 interactions with binding partners and downstream signaling pathways?

Researchers can employ multiple techniques to investigate NEO1 interactions and signaling pathways:

• Co-immunoprecipitation (Co-IP) - Use anti-NEO1 antibodies to pull down protein complexes, followed by Western blotting to identify interacting partners. This approach can identify direct binding partners like Netrin-1 and RGM proteins.

• Proximity Ligation Assay (PLA) - Detect protein-protein interactions in situ with high sensitivity, visualizing NEO1 interactions within cellular compartments.

• Phospho-specific antibodies - Monitor activation of downstream pathways implicated in NEO1 signaling, such as PI3K/AKT and TGF-β pathways .

• Reporter assays - Employ pathway-specific reporters (e.g., AKT or TGF-β responsive elements driving luciferase expression) to quantify pathway activation following NEO1 manipulation.

• Phosphoproteomics - Use mass spectrometry-based approaches to identify phosphorylation changes in response to NEO1 activation or inhibition, revealing novel signaling components.

• RNA-Seq and GSEA/GSVA - Analyze transcriptional changes following NEO1 modulation to identify affected pathways, as demonstrated in colorectal cancer studies where NEO1 status correlated with inflammation-related signaling, EMT, and angiogenesis pathways .

• CRISPR screens - Identify genes that modify NEO1-dependent phenotypes, potentially revealing new pathway components or regulatory mechanisms.

When interpreting results from these approaches, researchers should consider the cell type specificity of NEO1 signaling, as pathway activation patterns may differ between inflammatory cells (e.g., Ly6Chi monocytes) and cancer cells .

What is the potential for using NEO1 as a biomarker in inflammatory conditions?

NEO1 shows significant promise as a biomarker in inflammatory conditions based on clinical evidence. In a cohort study of 59 critically ill pediatric ICU patients, plasma NEO1 levels demonstrated strong correlations with several clinical parameters: intraabdominal hypertension (IAH), abdominal compartment syndrome (ACS), disease severity measured by Pediatric Risk of Mortality III (PRISM-III) score, ICU length of stay, and mortality . This suggests that NEO1 quantification in blood plasma could serve as a valuable prognostic indicator in critical illness characterized by inflammation.

For clinical implementation, researchers must: (1) Establish standardized assay methods with defined reference ranges; (2) Determine optimal sampling timing and frequency; (3) Validate findings in larger, diverse patient cohorts; (4) Compare NEO1's performance against established biomarkers; (5) Investigate whether NEO1 levels could guide therapeutic decisions or monitor treatment response.

The association between Neo1 and clinical outcomes indicates potential applications in patient stratification, helping to identify those at highest risk who might benefit from more aggressive or targeted anti-inflammatory interventions.

How can NEO1 antibody-based therapeutic approaches be developed for inflammatory and ischemic conditions?

Development of NEO1 antibody-based therapeutic approaches requires a systematic research progression:

• Target validation: Building on evidence that functional inhibition of NEO1 reduces experimental hepatic ischemia-reperfusion injury and promotes inflammation resolution , further validate NEO1 as a therapeutic target across multiple disease models.

• Antibody optimization: Develop and characterize antibodies with optimal properties for therapeutic use, including high specificity, appropriate affinity, favorable pharmacokinetics, and minimal immunogenicity.

• Mechanism elucidation: Fully characterize mechanisms by which anti-NEO1 antibodies exert beneficial effects, including neutrophil apoptosis induction, enhanced phagocytosis, and modulation of PI3K/AKT and TGF-β pathways .

• Delivery optimization: Determine optimal administration routes, dosing schedules, and potential delivery systems for various conditions.

• Preclinical efficacy studies: Test anti-NEO1 antibodies in relevant animal models of inflammation and ischemia-reperfusion injury, with comprehensive assessment of efficacy parameters including biochemical markers (LDH, AST, ALT), cytokine profiles, histopathology, and functional outcomes .

• Safety evaluation: Conduct thorough toxicology studies to identify potential adverse effects, considering NEO1's roles in diverse physiological processes.

• Translational considerations: Develop companion diagnostics to identify patients most likely to benefit from anti-NEO1 therapy, potentially based on plasma NEO1 levels or genetic/transcriptomic profiles.

This structured approach could lead to novel therapeutic strategies for conditions like hepatic ischemia-reperfusion injury, where current treatment options remain limited.

What research models best recapitulate human NEO1 biology for translational studies?

Selecting appropriate research models to recapitulate human NEO1 biology requires consideration of several factors:

• Genetic models: Neo1-deficient (Neo1-/-) mice have proven valuable for studying NEO1's role in inflammation resolution and tissue regeneration . Conditional and inducible knockout models would allow tissue-specific and temporal control of NEO1 deletion, helping to dissect context-dependent functions.

• Chimeric models: Bone marrow transplant chimeric mice have demonstrated that hematopoietic NEO1 expression is crucial for regulating monocyte polarization and clearance functions , suggesting similar approaches could illuminate cell-type specific NEO1 functions in humans.

• Humanized models: For more translational relevance, consider humanized mouse models engrafted with human immune cells to better recapitulate human-specific aspects of NEO1 biology in inflammation.

• Ex vivo human systems: Fresh human neutrophils and monocytes treated with anti-NEO1 antibodies have successfully demonstrated effects on apoptosis and phagocytosis , providing directly translatable insights.

• Disease-specific models: For studying NEO1 in colorectal cancer, patient-derived xenografts or organoids maintain the genetic and phenotypic characteristics of human tumors, including NEO1 expression patterns .

• Cell-based assays: For mechanistic studies, cell lines with validated NEO1 expression can be used with genetic manipulation tools. In colorectal cancer research, DLD1, HCT116, and SW480 cell lines have been successfully employed for NEO1 overexpression and knockdown studies .

When selecting models, researchers should validate that the NEO1 expression patterns, regulatory mechanisms, and downstream pathways reflect those observed in human tissues and pathologies.

Table 1: NEO1 Expression in Colorectal Cancer Subtypes Compared to Normal Tissue

Table summarizing NEO1 downregulation across multiple datasets and colorectal cancer subtypes .

Table 2: Effect of NEO1 Inhibition on Inflammatory Parameters

Table summarizing effects of NEO1 inhibition or deficiency on key inflammatory parameters based on experimental findings .

Table 3: NEO1 Toxin Sensitivity in Different Genetic Models

Table summarizing toxin sensitivity of different yeast strains with NEO1 mutations, demonstrating NEO1's role in plasma membrane asymmetry .