znf750 Antibody

What are the primary applications for ZNF750 antibodies in research?

ZNF750 antibodies are primarily used in Western Blotting (WB), Immunocytochemistry (ICC), Immunofluorescence (IF), and ELISA applications. These antibodies enable the detection of endogenous levels of total ZNF750 protein in experimental samples . For optimal results in Western Blotting, researchers should use SDS-PAGE under reducing conditions with sample denaturation prior to loading. The antibody typically detects ZNF750 at approximately 77 kDa. For immunofluorescence, a dilution range of 1:100-1:500 is recommended when using formaldehyde-fixed cells, followed by permeabilization with 0.1% Triton X-100 .

What is the reactivity profile of available ZNF750 antibodies?

Most commercially available ZNF750 antibodies show confirmed reactivity with human and mouse samples . Predicted reactivity (based on sequence homology but requiring experimental validation) extends to other species including pig, zebrafish, bovine, horse, sheep, rabbit, dog, chicken, and Xenopus . When studying ZNF750 in non-human models, it is advisable to perform preliminary validation tests, as cross-reactivity may vary based on epitope conservation across species.

How should researchers validate the specificity of ZNF750 antibodies?

Validation should include multiple complementary approaches:

• Positive controls using tissue/cells known to express ZNF750 (e.g., skin, prostate, lung, placenta, thymus, and primary keratinocytes)

• Negative controls using tissues/cells with minimal ZNF750 expression (e.g., fibroblasts, peripheral blood leukocytes, pancreas, and brain)

• Knockdown/knockout validation using siRNA or CRISPR to confirm signal reduction

• Peptide competition assays using the immunizing peptide to confirm specificity

• Comparison of staining/detection patterns with published literature

For immunohistochemistry applications, normal epithelial tissues serve as excellent positive controls due to ZNF750's established role in epithelial differentiation .

What is the functional significance of ZNF750 in normal tissue?

ZNF750 functions as a critical transcriptional regulator of epidermal cell differentiation by inducing differentiation genes while inhibiting progenitor factors . It plays an essential role in epithelial tissue homeostasis, where it acts downstream of p63 to regulate terminal differentiation programs . ZNF750 shows tissue-specific expression patterns, being predominantly expressed in skin, prostate, lung, placenta, and thymus, with particularly strong expression in primary keratinocytes . Understanding this normal expression pattern is crucial for interpreting experimental results, especially when studying ZNF750's role in disease contexts.

How can researchers effectively study ZNF750's tumor suppressor function using antibody-based approaches?

To investigate ZNF750's tumor suppressor role, researchers should implement a multi-faceted approach:

• Tissue microarray analysis: Compare ZNF750 protein expression between tumor and matched normal tissues using immunohistochemistry. Research has established that ZNF750 is significantly downregulated in tumor tissues compared to normal tissues (P<0.00005) .

• Cell line studies: Perform restoration experiments by introducing wild-type ZNF750 in cell lines with low endogenous expression, followed by functional assays (proliferation, migration, colony formation). Include mutant ZNF750 constructs as controls, as research has shown that wild-type, but not mutant ZNF750, inhibits malignant phenotypes .

• Mechanism exploration: Use chromatin immunoprecipitation (ChIP) to identify direct transcriptional targets of ZNF750. Published research indicates ZNF750 binds and recruits KDM1A and HDAC1 to specific gene promoters, including LAMB3 and CTNNAL1, to repress their transcription .

• Clinical correlation studies: Correlate ZNF750 expression levels with patient survival data. Studies have demonstrated that low ZNF750 expression correlates with poorer prognosis in ESCC and other squamous cell carcinomas .

What methodological approaches should be used to study the ZNF750-RAC1 regulatory axis in cancer research?

To effectively investigate the ZNF750-RAC1 regulatory relationship in cancer:

• Expression correlation analysis: Perform qRT-PCR and Western blot analyses to establish inverse correlation between ZNF750 and RAC1 expression levels in cell lines and patient samples.

• Promoter analysis: Conduct ChIP assays to confirm direct binding of ZNF750 to the RAC1 promoter region. This technique has been used to successfully demonstrate ZNF750's direct binding to RAC1 promoter in breast cancer cell lines .

• Functional rescue experiments: Perform RAC1 overexpression in cells with restored ZNF750 expression to determine if RAC1 can rescue the phenotypic effects of ZNF750.

• Signaling pathway analysis: Investigate downstream effectors of RAC1 that are altered by ZNF750 expression using phospho-protein arrays or targeted Western blotting.

• In vivo models: Develop xenograft models with manipulated ZNF750/RAC1 expression to validate the clinical relevance of this axis.

The ZNF750-RAC1 axis has significant implications for breast cancer prognosis, as upregulation of RAC1 directly correlates with decreased survival rates in breast cancer patients .

How can researchers address potential inconsistencies in ZNF750 antibody staining patterns between different cancer types?

When encountering inconsistent staining patterns across different cancer types:

• Epitope mapping: Different antibodies target distinct epitopes of ZNF750. Researchers should select antibodies targeting conserved regions (such as the N-terminal C2H2 zinc finger motif) for consistent detection across sample types .

• Mutation status assessment: ZNF750 harbors different mutations across cancer types. Prior to immunostaining, perform genetic analysis to identify mutations that might affect antibody binding. Research has identified missense, truncation, and genomic deletion mutations in squamous cell carcinomas .

• Isoform-specific detection: Verify which ZNF750 isoforms are expressed in your tissue of interest and select antibodies that can detect these specific variants.

• Quantitative comparison methods: Implement digital pathology techniques for standardized quantification of staining intensity across different samples.

• Multi-antibody approach: Use multiple antibodies targeting different ZNF750 epitopes to create a comprehensive detection strategy and validate findings across reagents.

What methodological considerations are critical when studying the relationship between ZNF750 mutations and protein expression?

When investigating the relationship between ZNF750 genetic alterations and protein expression:

• Mutation classification system: Categorize mutations as nonsense, frameshift, or missense. Research has shown that nonsense and frameshift mutations (87.5% of mutations in ESCC) cause significantly reduced ZNF750 expression compared to samples without mutations (P<0.05) .

• Protein degradation analysis: Determine if mutations lead to protein degradation through proteasome pathways by treating cells with proteasome inhibitors and measuring protein levels.

• Domain-specific functional assays: Since ZNF750 contains a critical C2H2 zinc finger motif in the N-terminal domain and PLNLS motifs in the C-terminal domain for protein-protein interactions, use domain-specific antibodies to assess how mutations affect specific functional regions .

• Transcript-protein correlation: Perform parallel mRNA (RT-qPCR) and protein (Western blot) analyses to determine if discrepancies exist between transcript and protein levels, which might indicate post-transcriptional or post-translational regulatory mechanisms.

• Subcellular localization studies: Use immunofluorescence to determine if mutations alter the predominantly nuclear localization of ZNF750, as proper localization is essential for its transcriptional regulatory functions .

What controls should be included when using ZNF750 antibodies for cancer research?

A comprehensive control strategy should include:

• Tissue expression controls:

  • Positive tissue controls: Skin, prostate, lung, placenta, or thymus tissues known to express ZNF750

  • Negative tissue controls: Peripheral blood leukocytes, pancreas, or brain tissues with minimal ZNF750 expression

• Cell line controls:

  • Positive cell controls: Primary keratinocytes with high ZNF750 expression

  • Negative cell controls: Fibroblasts with minimal ZNF750 expression

• Technical controls:

  • Isotype control antibody (matching the host species of the ZNF750 antibody)

  • Secondary antibody-only control

  • Blocking peptide competition to confirm specificity

• Expression manipulation controls:

  • siRNA/shRNA knockdown of ZNF750 to confirm signal reduction

  • Overexpression of wild-type and mutant ZNF750 to validate detection specificity

• Disease-relevant controls:

  • Matched normal-tumor tissue pairs to assess differential expression in cancer contexts

How can researchers optimize ZNF750 immunohistochemistry protocols for differentiation status assessment in cancer samples?

To optimize ZNF750 immunohistochemistry for differentiation assessment:

• Fixation protocol standardization: Establish consistent fixation times (recommended 24 hours in 10% neutral buffered formalin) to preserve epitope integrity.

• Antigen retrieval optimization: Test multiple retrieval methods (heat-induced in citrate buffer pH 6.0, EDTA buffer pH 9.0, or enzymatic retrieval) to determine optimal epitope exposure conditions.

• Signal amplification techniques: For low ZNF750 expression cases, implement tyramide signal amplification or polymer-based detection systems to enhance sensitivity.

• Counterstaining strategy: Use differential counterstaining to simultaneously assess ZNF750 expression and differentiation markers (e.g., cytokeratins, involucrin).

• Scoring system development: Establish a quantitative scoring system that accounts for:

  • Nuclear staining intensity (as ZNF750 is primarily nuclear)

  • Percentage of positive cells

  • Distribution pattern relative to differentiation zones within the tissue

Research has demonstrated that low ZNF750 expression significantly correlates with undifferentiated histology in ESCC (P<0.05) , making standardized assessment protocols essential for accurate histopathological correlation.

What approaches should be used to investigate ZNF750-mediated regulation of long non-coding RNAs like TINCR?

To study ZNF750's regulation of TINCR and other lncRNAs:

• Expression correlation analysis: Perform qRT-PCR to quantify ZNF750 and TINCR expression levels across cell lines and patient samples to establish correlation patterns.

• Promoter binding studies: Conduct ChIP assays using ZNF750 antibodies followed by qPCR targeting the TINCR promoter region to confirm direct regulation.

• Reporter assays: Generate luciferase reporter constructs containing the TINCR promoter to quantitatively assess ZNF750's effect on TINCR transcriptional activation.

• Gain/loss-of-function experiments:

  • Overexpress wild-type and mutant ZNF750 to measure effects on TINCR expression

  • Perform rescue experiments by modulating TINCR levels in ZNF750-deficient backgrounds

• Functional outcome assessment: Evaluate phenotypic changes (differentiation markers, proliferation, migration) associated with the ZNF750-TINCR regulatory axis.

Research has established that ZNF750 promotes the expression of TINCR, which mediates both cancer-inhibition and differentiation-induction effects of ZNF750 , making this regulatory relationship a critical target for mechanistic investigation.

How should researchers interpret discrepancies between ZNF750 mRNA expression and protein levels in experimental samples?

When encountering discrepancies between ZNF750 transcript and protein levels:

• Post-transcriptional regulation assessment:

  • Analyze microRNA binding sites in ZNF750 mRNA

  • Evaluate mRNA stability through actinomycin D chase experiments

  • Assess alternative splicing patterns using RT-PCR with isoform-specific primers

• Post-translational modification analysis:

  • Investigate ubiquitination status to determine if protein degradation is enhanced

  • Assess phosphorylation states that might affect protein stability

  • Evaluate other modifications that could impact antibody epitope recognition

• Protein half-life determination:

  • Perform cycloheximide chase assays to measure ZNF750 protein turnover rates

  • Compare wild-type vs. mutant ZNF750 stability

• Technical validation:

  • Use multiple antibodies targeting different ZNF750 epitopes

  • Implement multiple protein detection methods (Western blot, immunofluorescence, immunohistochemistry)

• Correlation with functional outcomes:

  • Determine which measurement (mRNA or protein) better correlates with biological functions or clinical outcomes

Research has demonstrated that nonsense and frameshift mutations in ZNF750 cause reduced expression levels , which may manifest differently at mRNA versus protein levels, necessitating comprehensive analysis.

What bioinformatic approaches are recommended for analyzing ZNF750 expression in relation to patient survival and clinical outcomes?

For robust bioinformatic analysis of ZNF750's clinical significance:

Research has established that low ZNF750 expression significantly correlates with poorer prognosis in both Kyushu and TCGA datasets (P<0.0005 and P<0.05, respectively) .

How can ChIP-seq be optimized to identify genome-wide binding sites of ZNF750 in normal versus cancer cells?

For optimal ChIP-seq analysis of ZNF750 binding patterns:

• Antibody selection criteria:

  • Choose antibodies validated specifically for ChIP applications

  • Test multiple antibodies in preliminary ChIP-qPCR assays against known targets like LAMB3, CTNNAL1, or RAC1 promoters

  • Verify antibody specificity using ZNF750 knockout/knockdown controls

• Experimental design considerations:

  • Include paired normal and cancer samples from the same tissue origin

  • Use cell line models with manipulated ZNF750 expression (overexpression in deficient lines, knockdown in high-expressing lines)

  • Implement spike-in normalization for accurate cross-sample comparisons

• Computational analysis pipeline:

  • Use specialized peak callers optimized for transcription factors with C2H2 zinc finger domains

  • Perform motif enrichment analysis to identify ZNF750 binding motifs

  • Integrate with RNA-seq data to correlate binding with transcriptional outcomes

• Validation strategy:

  • Confirm selected binding sites with ChIP-qPCR

  • Use reporter assays to validate functional significance of binding

  • Perform site-directed mutagenesis of predicted binding motifs

• Context-specific analysis:

  • Compare binding patterns in differentiated versus undifferentiated states

  • Assess co-binding with known ZNF750 partners like KDM1A and HDAC1

What are the recommended approaches for studying ZNF750 protein-protein interactions that mediate its tumor suppressor function?

To investigate ZNF750 protein interaction networks:

• Affinity purification mass spectrometry (AP-MS):

  • Generate tagged ZNF750 constructs (FLAG, HA, or BioID) for efficient pulldown

  • Compare interactomes between wild-type and cancer-associated mutant ZNF750 proteins

  • Implement quantitative proteomics approaches (SILAC, TMT) for differential interaction analysis

• Co-immunoprecipitation validation:

  • Verify key interactions (particularly with KDM1A and HDAC1, known co-factors)

  • Perform reciprocal Co-IPs to confirm specificity

  • Map interaction domains using truncated constructs focusing on the C-terminal PLNLS motifs essential for protein-protein interactions

• Proximity ligation assay (PLA):

  • Visualize endogenous interactions in situ

  • Compare interaction patterns between normal and cancer tissues

• Functional validation:

  • Perform siRNA knockdown of interaction partners followed by ZNF750 target gene expression analysis

  • Develop and test interaction-deficient ZNF750 mutants in rescue experiments

• Chromatin context analysis:

  • Implement sequential ChIP (re-ChIP) to confirm co-occupancy at target promoters

  • Assess histone modification changes associated with ZNF750-containing complexes

Research has established that ZNF750 binds and recruits KDM1A and HDAC1 to promoters of LAMB3 and CTNNAL1 , making these interactions critical targets for mechanistic investigation.

How can researchers effectively study the dual role of ZNF750 in differentiation regulation and tumor suppression?

To investigate this dual functionality:

• Temporal expression analysis:

  • Track ZNF750 expression during differentiation time courses

  • Compare expression patterns in normal differentiation versus malignant transformation

• Target gene categorization:

  • Classify ZNF750 target genes into differentiation-related versus tumor suppression-related groups

  • Identify common regulatory mechanisms between these functionally distinct target sets

• Domain-specific function mapping:

  • Generate domain mutants targeting the C2H2 zinc finger motif versus PLNLS motifs

  • Assess differential effects on differentiation markers versus oncogenic phenotypes

• Context-dependent interactome analysis:

  • Compare ZNF750 protein interaction networks in differentiation versus transformation contexts

  • Identify context-specific co-factors that direct ZNF750 activity toward differentiation or tumor suppression

• Integrative genomics approach:

  • Correlate ZNF750 binding patterns with chromatin accessibility and histone modifications

  • Develop comprehensive models of how ZNF750 functions change during malignant transformation

Research has demonstrated that ZNF750 acts as a transcriptional regulator of epidermal differentiation by inducing differentiation genes while inhibiting progenitor factors , and this function appears central to its tumor suppressor activity in squamous cell carcinomas.