STARD13 Antibody

What are the most reliable applications for STARD13 antibodies?

STARD13 antibodies have been validated for multiple applications with varying degrees of reliability. Based on the available commercial antibodies and research literature, the following applications have shown consistent results:

For optimal results, polyclonal rabbit antibodies targeting the central region (AA 516-679) or N-terminal regions have demonstrated superior specificity across multiple applications . For precise detection, Protein G purified antibodies with >95% purity are recommended, particularly for sensitive applications like immunofluorescence .

How do I optimize STARD13 antibody dilutions for Western blot assays?

When optimizing STARD13 antibody dilutions for Western blot, follow this methodological approach:

• Begin with manufacturer's recommended dilution (typically 1:1000 for most commercial STARD13 antibodies)

• Perform a dilution series (e.g., 1:500, 1:1000, 1:2000) on control samples with known STARD13 expression

• Include positive controls (cell lines with confirmed STARD13 expression) such as:

  • MCF-7 cells (higher STARD13 expression)

  • MDA-MB-231 cells (lower STARD13 expression)

• Include negative controls through STARD13 knockdown samples

• For loading controls, GAPDH or β-actin are suitable

Expect to observe STARD13 at approximately 125 kDa, though multiple isoforms have been reported. Blocking with 5% non-fat milk and using PVDF membranes generally produces cleaner results than nitrocellulose membranes when detecting STARD13 protein .

What species reactivity should I consider when selecting a STARD13 antibody?

When selecting STARD13 antibodies, species reactivity is a critical consideration:

Most commercially available STARD13 antibodies have been primarily validated in human samples, with variable cross-reactivity to mouse STARD13 . For studies involving multiple species, antibodies targeting the amino acid region 516-679 have demonstrated the most consistent cross-reactivity between human and mouse models . Always perform validation when using these antibodies in non-human models, as sequence homology does not guarantee equivalent epitope recognition.

How can I effectively use STARD13 antibodies to investigate its role in cancer stem cell biology?

To investigate STARD13's role in cancer stem cell (CSC) biology, implement this methodological framework:

• Spheroid Formation Assays:

  • Compare STARD13 expression between adherent cells and non-adherent spheres using validated antibodies at 1:500 dilution for immunofluorescence

  • Establish STARD13-overexpressing and knockdown cell models

  • Quantify sphere size and number in control versus modified cells

• CSC Marker Co-localization:

  • Perform dual immunofluorescence with STARD13 antibodies (1:200) and established CSC markers:

    • CD44+/CD24- (breast cancer)

    • ALDH1 activity (both breast and liver cancer)

    • OCT3/4, Nanog, and Sox2 expression

• Flow Cytometry Analysis:

  • Use STARD13 antibodies in conjunction with CSC surface markers

  • Quantify CD44+/CD24- population changes upon STARD13 manipulation

• Functional Assessment:

  • Examine chemoresistance profiles in cells with modified STARD13 expression

  • Analyze tumor-initiating capacity through limiting dilution assays

Research has demonstrated that STARD13 expression is significantly decreased in non-adherent spheres compared to adherent cells, and overexpression of STARD13 reduces stemness properties in both breast cancer and hepatocellular carcinoma models . This suggests STARD13 antibodies can be valuable tools in identifying cells with stem-like properties.

What approaches can I use to study STARD13's interaction with the Hippo/YAP pathway using STARD13 antibodies?

For studying STARD13's interaction with the Hippo/YAP pathway, employ these methodological approaches:

• Co-immunoprecipitation (Co-IP):

  • Use STARD13 antibodies (5μg per 500μg total protein) for pull-down experiments

  • Probe for YAP/TAZ and LATS1/2 interactions

  • Include RhoA in analysis to determine pathway interconnections

• Subcellular Fractionation:

  • Separate nuclear and cytoplasmic fractions

  • Use STARD13 antibodies (1:1000) in Western blot to detect changes in YAP/TAZ localization

  • Include phospho-YAP (Ser127) antibodies to assess YAP inactivation status

• Immunofluorescence Microscopy:

  • Perform dual staining with STARD13 (1:200) and YAP/TAZ antibodies (1:100)

  • Use phalloidin staining to visualize F-actin changes

  • Quantify nuclear versus cytoplasmic YAP localization

• Luciferase Reporter Assays:

  • Utilize 8xGTIIC-luciferase reporter system for YAP transcriptional activity

  • Correlate with STARD13 expression levels detected by immunoblotting

Research has shown that STARD13 overexpression increases YAP phosphorylation, promotes YAP cytoplasmic retention, and decreases YAP transcriptional activity as measured by 8xGTIIC-luciferase activity . These effects were mediated through STARD13's RhoGTPase activity, as RhoA overexpression rescued the inhibitory effects of STARD13 on YAP activity .

How can I utilize STARD13 antibodies to investigate the STARD13-correlated ceRNA network in cancer?

To investigate the STARD13-correlated ceRNA network in cancer, implement these methodological approaches:

• RNA Immunoprecipitation (RIP):

  • Perform Ago2-RIP assays to assess STARD13 involvement in RISC complexes

  • Use STARD13 antibodies (1:50 dilution) for immunofluorescence to validate ceRNA network components

  • Correlate with expression of ceRNA partners (CDH5, HOXD1, HOXD10)

• Dual Luciferase Reporter Assays:

  • Construct luciferase reporters containing STARD13 3'UTR

  • Evaluate effects of miRNA mimics on reporter activity

  • Correlate findings with STARD13 protein levels using Western blot

• Combined RNA-Protein Analysis:

  • Perform immunoprecipitation with STARD13 antibodies

  • Isolate RNA from immunoprecipitates

  • Identify bound miRNAs through sequencing or PCR arrays

• Tissue Correlation Studies:

  • Use STARD13 antibodies (1:100) for IHC on cancer tissues

  • Correlate with expression of ceRNA partners and target miRNAs

  • Analyze association with clinical outcomes

Research has identified STARD13 as part of a ceRNA network involving CDH5, HOXD1, and HOXD10, collectively regulating LATS1/2 expression by competing for binding to common miRNAs (miR-424, miR-374a, miR-590-3p, miR-448, and miR-15a) . This network inhibits breast cancer stemness and is negatively correlated with YAP/TAZ activity .

How can I address non-specific bands when using STARD13 antibodies in Western blot?

When encountering non-specific bands with STARD13 antibodies, implement this systematic troubleshooting approach:

• Antibody Validation:

  • Confirm antibody specificity using STARD13 knockdown or knockout controls

  • Compare multiple antibodies targeting different epitopes of STARD13:

    • N-terminal region antibodies

    • Central region antibodies (AA 516-679)

    • C-terminal region antibodies

• Optimization Steps:

  • Increase blocking stringency (5% BSA instead of milk for phospho-detection)

  • Test gradient of antibody dilutions (1:500 to 1:2000)

  • Adjust exposure time to minimize background

  • Use fresh transfer buffers with appropriate methanol concentration

• Sample Preparation Refinements:

  • Include phosphatase inhibitors to preserve modification states

  • Use RIPA buffer with 0.1% SDS for more effective extraction

  • Optimize protein loading (20-50μg is typically sufficient)

• Expected Banding Pattern:

  • Primary STARD13 band at ~125 kDa

  • Potential isoforms at ~115 kDa and ~130 kDa

  • Phosphorylated forms may appear as slightly higher molecular weight bands

STARD13 contains multiple domains including RhoGAP and START domains, which may contribute to detection complexity. Additionally, STARD13 has been shown to interact with several proteins in the Hippo pathway, which may co-precipitate in some conditions .

What controls should I include when using STARD13 antibodies for immunohistochemistry?

For reliable STARD13 immunohistochemistry, include these essential controls:

• Positive Tissue Controls:

  • Normal liver tissue (moderate to high STARD13 expression)

  • Normal breast tissue (moderate STARD13 expression)

  • Pre-validated tissue microarrays containing known STARD13 expression

• Negative Controls:

  • Isotype-matched irrelevant antibody at the same concentration

  • Primary antibody omission control

  • Antigen pre-absorption using immunizing peptide

• Technical Controls:

  • Serial dilution of primary antibody (1:100, 1:200, 1:500)

  • Different antigen retrieval methods:

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

    • HIER using EDTA buffer (pH 9.0)

  • Fixation control: compare formalin-fixed versus frozen sections

• Biological Validation:

  • STARD13 expression shows distinctive patterns:

    • Decreased in hepatocellular carcinoma versus adjacent normal tissue

    • Reduced in higher-grade breast cancers

    • Predominantly cytoplasmic localization

Research has shown that STARD13 expression is significantly downregulated in HCC tissues compared to normal adjacent tissues, as confirmed by immunohistochemistry . This differential expression pattern provides a useful internal control when staining liver cancer sections.

What are the key considerations for multiplex immunofluorescence with STARD13 antibodies?

When performing multiplex immunofluorescence with STARD13 antibodies, address these critical technical considerations:

• Antibody Compatibility:

  • Ensure primary antibodies are from different host species to avoid cross-reactivity:

    • Rabbit anti-STARD13 pairs well with mouse anti-YAP or mouse anti-F-actin

    • Goat anti-STARD13 (if available) enables use with rabbit anti-phospho-YAP

• Signal Optimization:

  • Use Tyramide Signal Amplification (TSA) for enhanced STARD13 detection

  • Optimize antibody concentration and incubation time for each antibody:

    • STARD13 antibody: 1:200 dilution, overnight at 4°C

    • YAP/TAZ antibodies: 1:100-1:200, overnight at 4°C

  • Test sequential versus simultaneous staining protocols

• Fluorophore Selection:

  • Choose spectrally distinct fluorophores with minimal overlap:

    • FITC (green) or Alexa Fluor 488 for STARD13

    • Alexa Fluor 594 (red) for YAP/TAZ

    • DAPI (blue) for nuclear counterstain

• Control Panel:

  • Single-stain controls for each antibody

  • Fluorescence-minus-one (FMO) controls

  • STARD13 knockdown/overexpression controls to validate specificity

• Image Acquisition Settings:

  • Use identical exposure settings across all comparable samples

  • Perform sequential scanning to minimize bleed-through

  • Include z-stack imaging for 3D localization analysis

Research has employed dual immunofluorescence to demonstrate that STARD13 overexpression promotes cytoplasmic retention of YAP . When using STARD13 antibodies in multiplex applications, cytoplasmic STARD13 staining pattern should be distinct from the nuclear/cytoplasmic distribution of YAP/TAZ, providing an internal control for staining quality .

How can STARD13 antibodies be used to evaluate chemotherapy sensitivity in cancer cells?

To evaluate chemotherapy sensitivity using STARD13 antibodies, implement this research methodology:

• Expression Correlation Studies:

  • Use STARD13 antibodies (1:1000) for Western blot or IHC (1:200) to quantify STARD13 levels

  • Compare STARD13 expression with:

    • IC50 values for chemotherapeutic agents

    • Expression of MDR proteins (Pgp)

    • Patient response to treatment regimens

• Functional Validation:

  • Create STARD13-overexpressing and knockdown models

  • Assess drug sensitivity through:

    • MTT/CCK-8 viability assays with dose-response curves

    • Flow cytometry for apoptosis markers (Annexin V/PI)

    • Colony formation assays post-treatment

  • Validate STARD13 levels by immunoblotting

• Mechanism Investigation:

  • Examine STARD13's relationship with:

    • Drug efflux (using doxorubicin fluorescence retention)

    • YAP/TAZ nuclear localization by immunofluorescence

    • Side population (SP) analysis for cancer stem cell properties

Research has demonstrated that STARD13 overexpression enhances 5-FU sensitivity in hepatocellular carcinoma by suppressing cancer stemness via attenuating YAP transcriptional activity . Additionally, STARD13 overexpression increased doxorubicin sensitivity in breast cancer models by decreasing the activity of multidrug resistance proteins and enhancing drug intake .

What methodologies can reveal STARD13's role in regulating RhoGTPase signaling using antibody-based approaches?

To investigate STARD13's regulation of RhoGTPase signaling using antibody-based approaches, implement these methodologies:

• RhoGTPase Activity Assays:

  • Use G-LISA RhoA activation assay in conjunction with STARD13 immunoblotting

  • Correlate STARD13 expression levels with RhoA activity in:

    • STARD13-overexpressing cells

    • STARD13-knockdown cells

    • Control cells

• Downstream Effector Analysis:

  • Use Western blotting with STARD13 antibodies (1:1000) alongside:

    • Phospho-MLC-S19 antibodies (RhoA effector)

    • F-actin visualization using phalloidin staining

    • ROCK activity assays

• Co-localization Studies:

  • Perform dual immunofluorescence with:

    • STARD13 antibodies (1:200)

    • RhoA antibodies (1:100)

    • F-actin staining (phalloidin)

  • Analyze membrane localization patterns

• Rescue Experiments:

  • Overexpress constitutively active RhoA in STARD13-overexpressing cells

  • Assess reversal of STARD13-mediated phenotypes

  • Validate through immunoblotting and functional assays

Research has demonstrated that STARD13 overexpression significantly decreased RhoA activity in hepatocellular carcinoma cells, as measured by G-LISA RhoA activation assay . Additionally, STARD13 overexpression inhibited stress fiber formation as visualized by F-actin staining, and decreased phosphorylation of myosin light chain (MLC-S19), a downstream effector of RhoA signaling .

How can I use STARD13 antibodies to evaluate patient prognosis in clinical cancer samples?

To use STARD13 antibodies for prognostic evaluation in clinical cancer samples, implement this methodological framework:

• Tissue Microarray Analysis:

  • Optimize STARD13 antibody dilution for IHC (typically 1:200-1:500)

  • Score STARD13 expression using standardized methods:

    • H-score (intensity × percentage of positive cells)

    • 0-3 intensity scale (negative, weak, moderate, strong)

  • Correlate with clinicopathological parameters and survival data

• Automated Quantification:

  • Use digital pathology software to quantify STARD13 staining

  • Employ machine learning algorithms for consistent scoring

  • Validate with pathologist review

• Multiplex Biomarker Panels:

  • Combine STARD13 IHC with:

    • YAP/TAZ expression (1:100 dilution)

    • Stemness markers (ALDH1, CD44, Nanog)

    • EMT markers (E-cadherin, vimentin)

  • Develop integrated prognostic models

• Validation Cohorts:

  • Test prognostic value in independent patient cohorts

  • Perform multivariate analysis adjusting for:

    • Tumor stage

    • Grade

    • Patient demographics

    • Treatment regimens

What novel approaches can be used to study STARD13 post-translational modifications using antibody-based methods?

To study STARD13 post-translational modifications using antibody-based methods, consider these innovative approaches:

• Phospho-specific Antibody Development:

  • Generate antibodies against predicted phosphorylation sites:

    • Identify candidate sites through phospho-proteomic databases

    • Synthesize phospho-peptides for immunization

    • Validate specificity with phosphatase treatments

• Proximity Ligation Assay (PLA):

  • Combine STARD13 antibodies with:

    • Ubiquitin antibodies to detect ubiquitination

    • SUMO antibodies to detect SUMOylation

    • Phospho-specific antibodies

  • Visualize potential modifications as discrete fluorescent spots

• Immunoprecipitation-Mass Spectrometry (IP-MS):

  • Use STARD13 antibodies for pull-down (5μg antibody per 1mg protein)

  • Perform MS analysis to identify:

    • Phosphorylation sites

    • Ubiquitination sites

    • Other modifications

  • Compare modification profiles in different cellular contexts

• STARD13 Domain-specific Antibodies:

  • Develop antibodies targeting specific STARD13 domains:

    • RhoGAP domain (essential for RhoGTPase activity)

    • START domain (lipid transfer function)

  • Assess domain-specific modifications and their functional impacts

How can I apply high-throughput screening methods using STARD13 antibodies to identify novel therapeutic strategies?

To apply high-throughput screening with STARD13 antibodies for therapeutic discovery, implement these methodological approaches:

• Cell-based Phenotypic Screens:

  • Create STARD13 reporter cell lines:

    • STARD13 promoter-driven luciferase/GFP

    • STARD13-GFP fusion proteins

  • Screen compound libraries for:

    • STARD13 expression modulators

    • STARD13 localization changes

  • Validate hits using STARD13 antibodies in Western blot or IF

• Reverse Phase Protein Array (RPPA):

  • Use validated STARD13 antibodies on RPPA platforms

  • Screen for:

    • Compounds that modulate STARD13 expression/phosphorylation

    • Synthetic lethal interactions with STARD13 status

  • Develop signature profiles including STARD13 and related pathway components

• Drug Combination Screens:

  • Combine standard chemotherapeutics with:

    • RhoA inhibitors

    • YAP/TAZ inhibitors

  • Assess STARD13 expression/modification changes

  • Correlate with chemosensitivity profiles

• Patient-derived Organoid Screening:

  • Establish organoid libraries from patient samples

  • Characterize STARD13 expression by IHC/IF

  • Screen therapeutic agents

  • Correlate response with STARD13 status

Research has already demonstrated that STARD13 expression levels correlate with chemosensitivity. Specifically, STARD13 overexpression enhanced 5-FU sensitivity in hepatocellular carcinoma and doxorubicin sensitivity in breast cancer models . These findings suggest that STARD13 status could serve as a biomarker for treatment response and that strategies to modulate STARD13 expression or its downstream pathways might enhance chemotherapeutic efficacy.

What are the critical factors for successful chromatin immunoprecipitation (ChIP) using STARD13-related antibodies?

Although STARD13 itself is not a transcription factor, its regulation of YAP/TAZ nuclear localization makes ChIP approaches relevant for studying its downstream effects. For successful ChIP using YAP/TAZ antibodies in STARD13-modulated contexts:

• Crosslinking Optimization:

  • Test different crosslinking conditions:

    • 1% formaldehyde for 10 minutes (standard)

    • Dual crosslinking with DSG followed by formaldehyde (for improved capture)

  • Optimize based on target genes (CTGF, CYR61, etc.)

• Antibody Selection:

  • Use ChIP-validated YAP/TAZ antibodies (5μg per ChIP reaction)

  • Include TEAD family transcription factors as partners

  • Validate with IgG negative controls

  • Compare results in STARD13-overexpressing versus control cells

• Target Selection:

  • Focus on established YAP/TAZ target genes:

    • CTGF (primary YAP/TAZ target)

    • CYR61

    • ANKRD1

  • Design primers for TEAD binding motifs in promoter regions

• Technical Considerations:

  • Include sonication optimization for 200-500bp fragments

  • Perform ChIP-qPCR validation before proceeding to ChIP-seq

  • Include input normalization and percent-input calculations

Research has established that STARD13 overexpression decreases YAP/TAZ transcriptional activity, as measured by reduced expression of target genes like CTGF . ChIP experiments focusing on YAP/TAZ binding to target promoters in cells with modified STARD13 expression could reveal mechanistic insights into how STARD13 regulates gene expression programs through this pathway.

How can I optimize immunoelectron microscopy protocols for STARD13 detection?

For successful immunoelectron microscopy detection of STARD13, implement these specialized protocol optimizations:

• Sample Preparation:

  • Test both pre-embedding and post-embedding labeling:

    • Pre-embedding: Better antibody accessibility but potential antigen loss

    • Post-embedding: Better preservation but reduced antibody penetration

  • For STARD13, mild fixation (2% PFA + 0.2% glutaraldehyde) often provides best results

• Antibody Selection and Dilution:

  • Choose antibodies with validated specificity in IF/IHC

  • Test antibody dilutions (typically 5-10× more concentrated than for IF)

  • For STARD13, polyclonal antibodies against central regions (AA 516-679) often provide superior ultrastructural detection

• Detection Systems:

  • Use gold particles of appropriate size:

    • 5-10nm for superior resolution

    • 15-20nm for easier visualization

  • For double-labeling:

    • STARD13 (10nm gold) with YAP/TAZ (5nm gold)

    • STARD13 (15nm gold) with cytoskeletal markers (5nm gold)

• Controls:

  • Omission of primary antibody

  • STARD13 knockdown/knockout samples

  • Competing peptide controls

  • Isotype-matched irrelevant antibody controls

• Expected Localization Patterns:

  • Cytoplasmic localization, potentially associated with membrane structures

  • Possible association with actin cytoskeleton based on RhoGTPase activity

  • Proximity to focal adhesion complexes

While no published studies have specifically used immunoelectron microscopy for STARD13 localization, its functional role in regulating RhoGTPase signaling and actin cytoskeleton suggests potential association with specific subcellular structures that could be revealed through this high-resolution approach.

What are the key considerations for quantitative image analysis of STARD13 immunofluorescence data?

For robust quantitative analysis of STARD13 immunofluorescence data, implement these methodological considerations:

• Acquisition Parameters:

  • Standardize all imaging conditions:

    • Exposure times

    • Gain settings

    • Offset values

    • Laser power (for confocal)

  • Include fluorescence calibration standards

  • Capture multiple random fields (minimum 5-10 per condition)

• Segmentation Strategies:

  • Develop appropriate cell segmentation algorithms:

    • Nuclear segmentation using DAPI

    • Cytoplasmic segmentation using general cytoplasmic markers

  • Implement threshold determination methods:

    • Otsu's method

    • Background subtraction with rolling ball algorithm

    • Manual thresholding with blinded observers

• Quantification Metrics:

  • For STARD13 expression:

    • Mean fluorescence intensity

    • Integrated density

    • Area of positive staining

  • For co-localization with other proteins:

    • Pearson's correlation coefficient

    • Mander's overlap coefficient

    • Object-based co-localization

• Analysis Workflow:

  • Use open-source platforms (ImageJ/FIJI, CellProfiler) or commercial software

  • Develop reproducible analysis pipelines

  • Include batch processing capabilities for large datasets

  • Implement statistical validation approaches

• Validation Approaches:

  • Compare image analysis results with parallel Western blot quantification

  • Include positive and negative controls in every experiment

  • Perform inter-observer reliability testing

Research has used immunofluorescence to demonstrate that STARD13 overexpression increases cytoplasmic retention of YAP . Quantitative analysis of nuclear-to-cytoplasmic ratios of YAP in cells with different levels of STARD13 expression provides important mechanistic insights into how STARD13 regulates this pathway.