znf704 Antibody

What are the recommended methods for detecting ZNF704 expression in tissue samples?

For comprehensive ZNF704 detection in tissue samples, a multi-method approach is recommended. RNA sequencing and qRT-PCR are effective for quantifying ZNF704 mRNA levels, with validated primers (forward: 5'-GATCAAGCTCAACACAGACTCA-3', reverse: 5'-TCTGGGATGGGGAAAGTAGGA-3') . For protein detection, immunohistochemistry (IHC) using anti-ZNF704 antibody (1:200 dilution, Thermo Fisher Scientific) provides visualization in paraffin-embedded sections. Western blotting offers quantitative protein analysis, with β-actin serving as an effective loading control . For accurate quantification of IHC results, Image-Pro Plus 6.0 software can be used to measure average color values from stained sections.

What cell lines are suitable for ZNF704 functional studies?

Based on published research, several cancer cell lines have been validated for ZNF704 functional studies. For uveal melanoma research, OCM1A and C918 cell lines from American Type Culture Collection have been successfully used in ZNF704 knockdown and overexpression experiments . These cells should be maintained in RPMI 1640 medium supplemented with 10% heat-inactivated FBS, HEPES buffer, L-glutamine, MEM essential vitamin mixture, MEM non-essential amino acids, and 1% antibiotics at 37°C with 5% CO2 . Chondrosarcoma cell lines have also shown detectable ZNF704 expression and are suitable for functional studies . When selecting cell lines, consider those that naturally express ZNF704 at levels that allow for observable changes upon experimental manipulation.

What are the validated protocols for ZNF704 knockdown in experimental models?

For effective ZNF704 knockdown, RNA interference using specific shRNAs has been validated in multiple studies. Two effective shRNA sequences include: shZNF704-1: 5'-GCAATCTCCTCCGGTCACTTT-3' and shZNF704-2: 5'-GGATGGAGAACCGAGACATGT-3' . These can be delivered using lentiviral vectors from commercial sources. Following transfection, a 48-hour incubation period is recommended before validating knockdown efficiency by qRT-PCR and immunoblotting. For transient knockdown, siRNAs can be used with similar target sequences. In vivo knockdown for xenograft models requires stable transfection of cell lines prior to inoculation in immune-deficient mice (such as 4-week-old BALB/c-nu mice) . Knockdown efficiency should be verified in harvested tumors at the experimental endpoint.

How can ZNF704 overexpression be achieved in cellular models?

ZNF704 overexpression can be achieved through lentiviral vector systems containing the full ZNF704 coding sequence. The protocol involves synthesizing the ZNF704 coding sequence and inserting it into a lentiviral overexpression vector . Lentiviruses are then packaged in 293FT cells and concentrated through ultracentrifugation before infecting target cells. Efficiency should be verified 48 hours post-infection using qRT-PCR and immunoblotting to confirm increased ZNF704 expression . For stable overexpression, selection with appropriate antibiotics is recommended, followed by maintenance of overexpressing cell lines. This approach has been successfully used to demonstrate that ZNF704 overexpression promotes cell proliferation and reduces apoptosis in cancer cell lines.

What are the optimal conditions for immunoblotting detection of ZNF704 protein?

For optimal immunoblotting detection of ZNF704 protein, cell lysates should be prepared using RIPA buffer with protease inhibitors. Protein concentration should be determined using a BCA assay, with 50 μg of total protein loaded per lane on SDS-polyacrylamide gels . After electrophoresis, proteins should be transferred to PVDF membranes and blocked with 5% non-fat milk. Primary antibody incubation with anti-ZNF704 (from validated vendors such as Invitrogen) should be performed at 4°C overnight, followed by appropriate secondary antibody incubation. β-actin serves as an effective loading control . Signal detection via chemiluminescence systems should be optimized based on expected expression levels, with exposure times adjusted accordingly. For weak signals, enhanced chemiluminescence substrates or longer exposure times may be necessary.

How does ZNF704 regulate cell signaling pathways in cancer progression?

ZNF704 has been demonstrated to activate the PI3K/AKT/mTOR signaling pathway in cancer cells. RNA sequencing analysis of ZNF704 knockdown cells revealed 1983 upregulated and 1618 downregulated genes, indicating its broad regulatory role . Gene Set Enrichment Analysis (GSEA) showed that ZNF704 knockdown activated apoptosis and P53 pathways, while ZNF704 overexpression enriched AKT, mTOR, and glycolysis pathways . Mechanistically, ZNF704 increases phosphorylation of mTOR, 4EBP1, and S6, while upregulating HKII and cyclin D1 expression. This activation promotes cell proliferation and inhibits apoptosis. Additionally, ZNF704 has been shown to downregulate SORBS3, identified as a tumor suppressor in uveal melanoma . For studying these interactions, researchers should employ phospho-specific antibodies against AKT/mTOR pathway components in conjunction with ZNF704 antibody to visualize pathway activation states.

What methodologies are recommended for investigating ZNF704's role in tumor microenvironment interactions?

To investigate ZNF704's role in tumor microenvironment interactions, a multi-omics approach is recommended. Begin with co-culture systems where cancer cells with modulated ZNF704 expression (knockdown or overexpression) are cultured with stromal cells, immune cells, or endothelial cells. Analyze secretome profiles using cytokine arrays or mass spectrometry to identify altered secretory factors. For in vivo studies, xenograft models with ZNF704-modulated cells can be analyzed for tumor infiltrating immune cells using flow cytometry and immunohistochemistry with ZNF704 antibody co-staining . Single-cell RNA sequencing of tumor and microenvironment components can provide insights into cell-specific effects. Additionally, investigate the impact of ZNF704 expression on extracellular matrix composition and organization through proteomic analysis and second harmonic generation imaging. These approaches can reveal how ZNF704 influences the reciprocal signaling between tumor cells and their microenvironment.

How can ZNF704 expression data be integrated with other molecular markers for improved cancer prognosis?

For integrating ZNF704 expression data with other molecular markers, multivariate analysis methods are essential. Start by quantifying ZNF704 expression in patient cohorts using IHC scoring or RNA-seq data, then correlate with established molecular markers for the specific cancer type . For uveal melanoma, integrate ZNF704 with BAP1, SF3B1, and EIF1AX mutation status, as well as chromosome 3 monosomy data. In chondrosarcoma, combine with IDH1/2 mutation status and CDKN2A deletion data . Employing machine learning algorithms such as random forest or support vector machines can help identify the optimal combination of markers for prognostic accuracy. Kaplan-Meier survival analysis with ZNF704 stratification should be performed to validate prognostic value, followed by Cox proportional hazards regression to confirm independent prognostic significance . This integrated approach can potentially enhance the accuracy of patient stratification for personalized treatment strategies.

What are common challenges in ZNF704 antibody-based experiments and how can they be addressed?

Common challenges in ZNF704 antibody experiments include non-specific binding, inconsistent staining patterns, and variable sensitivity across different applications. To address these issues:

• Antibody validation: Verify antibody specificity using positive and negative controls. Cells with ZNF704 knockdown or overexpression serve as excellent controls .

• Optimization for IHC: Test multiple antigen retrieval methods (heat-induced epitope retrieval using citrate buffer pH 6.0 or EDTA buffer pH 9.0) and antibody dilutions (1:100 to 1:500) to determine optimal conditions .

• Western blot optimization: Use freshly prepared lysates, test different blocking agents (5% BSA or 5% non-fat milk), and optimize primary antibody incubation times (overnight at 4°C is often optimal) .

• Signal enhancement: For weak signals, consider signal amplification systems such as tyramide signal amplification or higher sensitivity detection reagents.

• Background reduction: Increase washing steps, adjust blocking time, or include 0.1-0.3% Triton X-100 in blocking solutions to reduce non-specific binding.

How can researchers validate that ZNF704 antibody is detecting the correct target in their experimental system?

Rigorous validation of ZNF704 antibody specificity is critical for experimental reliability. A comprehensive validation approach includes:

• Genetic validation: Utilize cells with ZNF704 knockdown (using validated shRNAs) or knockout (CRISPR-Cas9) as negative controls, and ZNF704-overexpressing cells as positive controls .

• Size validation: Confirm that detected bands match the expected molecular weight of ZNF704 protein (approximately 84 kDa) on Western blots.

• Multiple antibody validation: When possible, use antibodies from different vendors or targeting different epitopes of ZNF704 to confirm consistent results.

• Immunoprecipitation followed by mass spectrometry: This can provide definitive identification of the protein being detected by the antibody.

• Peptide competition assay: Pre-incubating the antibody with excess target peptide should abolish specific staining in IHC or Western blot applications.

• Cross-species reactivity testing: If studying ZNF704 in multiple species, verify antibody reactivity across relevant species.

What are the implications of ZNF704 as a potential therapeutic target in cancer treatment?

ZNF704's emerging role as an oncogene in multiple cancers positions it as a promising therapeutic target. Research indicates that ZNF704 knockdown significantly inhibits tumor growth both in vitro and in vivo models of uveal melanoma and chondrosarcoma . Several therapeutic strategies warrant investigation:

• Small molecule inhibitors: Developing compounds that can disrupt ZNF704's transcriptional activity or protein-protein interactions.

• Targeted protein degradation: Employing proteolysis-targeting chimeras (PROTACs) or molecular glues to facilitate ZNF704 degradation.

• Gene therapy approaches: Using siRNA or CRISPR-Cas9 to suppress ZNF704 expression in tumors.

• Combination therapies: Since ZNF704 activates the PI3K/AKT/mTOR pathway, combining ZNF704 inhibition with existing PI3K/AKT/mTOR inhibitors may yield synergistic effects .

• Biomarker-guided therapy: Stratifying patients based on ZNF704 expression levels to identify those most likely to benefit from targeted therapies.

Preclinical studies should assess efficacy, toxicity profiles, and resistance mechanisms to these approaches before clinical translation.

How can single-cell analysis techniques be applied to study ZNF704 expression heterogeneity in tumor samples?

Single-cell analysis offers powerful insights into ZNF704 expression heterogeneity within tumors. Researchers should consider these methodological approaches:

• Single-cell RNA sequencing (scRNA-seq): Dissociate tumor samples into single-cell suspensions and process through platforms like 10x Genomics, Drop-seq, or Smart-seq2 to quantify ZNF704 mRNA expression at single-cell resolution.

• Single-cell proteomics: Apply mass cytometry (CyTOF) with ZNF704 antibody to simultaneously detect ZNF704 protein along with other signaling molecules at single-cell level.

• Multiplex immunofluorescence: Combine ZNF704 antibody with markers for cell lineage, proliferation, and signaling pathways to visualize expression patterns within the spatial context of the tumor.

• Spatial transcriptomics: Technologies like Visium, MERFISH, or GeoMx DSP can map ZNF704 expression within the tissue architecture, revealing relationships with microenvironmental features.

• Computational integration: Apply algorithms to integrate single-cell data with bulk sequencing, clinical outcomes, and spatial information to comprehensively characterize ZNF704's role in tumor heterogeneity.

These approaches can reveal whether ZNF704 expression is uniform or restricted to specific tumor cell subpopulations, potentially identifying cellular states associated with aggressive behavior or treatment resistance.