PIK3C3 Antibody, Biotin conjugated

What is PIK3C3 and why is it significant in cellular research?

PIK3C3 (Phosphoinositide-3-Kinase Class 3), also known as Vps34 or hVps34, functions as the catalytic subunit of the PI3K complex that mediates formation of phosphatidylinositol 3-phosphate. This protein plays critical roles in regulating autophagy, endocytosis, and nutrient sensing across diverse cell types . The significance of PIK3C3 in research stems from its involvement in multiple membrane trafficking pathways, where different complex forms serve distinct functions: PI3KC3-C1 participates in autophagosome initiation while PI3KC3-C2 contributes to autophagosome maturation and endocytosis . Understanding PIK3C3 is particularly important in kidney research, cancer biology, and cellular physiology studies where membrane trafficking and autophagy play crucial roles in pathological processes.

How does the biotin conjugation affect the functionality of PIK3C3 antibody compared to unconjugated versions?

Biotin conjugation to PIK3C3 antibodies provides enhanced sensitivity and versatility compared to unconjugated versions through several mechanisms. The biotin-avidin system offers one of the strongest non-covalent biological interactions known, providing signal amplification through multiple biotin molecules binding to streptavidin-conjugated detection reagents . This configuration maintains the antigen-binding capacity of the antibody while introducing a stable, easily detectable tag.

Methodologically, biotin-conjugated PIK3C3 antibodies exhibit:

• Preserved immunoreactivity against target epitopes

• Increased detection sensitivity in applications like Western blotting and immunohistochemistry

• Enhanced signal-to-noise ratio in experimental outcomes

• Compatibility with various streptavidin-conjugated reporter systems (HRP, fluorophores)

• Flexibility in multi-color immunofluorescence studies

What is the subcellular localization pattern of PIK3C3 across different cell types?

PIK3C3 exhibits distinct expression patterns across various cell types, with notable tissue-specific localization profiles. In kidney tissue, immunohistochemistry and immunofluorescence studies have revealed significant disparities in PIK3C3 expression:

At the subcellular level, PIK3C3 primarily localizes to the cytoplasm, where it associates with early endosomes, autophagosomes, and other membrane compartments involved in trafficking . This localization pattern is crucial for its function in autophagosome formation and endosomal trafficking. In hepatocellular carcinoma (HCC), PIK3C3 shows increased expression in tumor tissues compared to adjacent non-tumor tissues, with particularly elevated levels in cancer stem cells (CSCs) . This differential expression pattern makes PIK3C3 an important marker for studying cellular differentiation and disease progression.

What are the optimal protocols for using biotin-conjugated PIK3C3 antibody in immunohistochemistry of kidney tissues?

For optimal immunohistochemistry (IHC) of kidney tissues using biotin-conjugated PIK3C3 antibody, researchers should follow this validated methodological approach:

Sample Preparation:

• Fix kidney tissue in 4% paraformaldehyde for 24 hours, then embed in paraffin

• Section tissues at 4-6 μm thickness

• Deparaffinize in xylene and rehydrate through graded alcohol series

Antigen Retrieval:

• Perform heat-induced epitope retrieval using citrate buffer (pH 6.0)

• Heat sections in a pressure cooker for 3 minutes or in a microwave for 20 minutes

• Allow slides to cool to room temperature for 20 minutes

Staining Protocol:

• Block endogenous peroxidase with 3% H₂O₂ for 10 minutes

• Block non-specific binding with 5% normal serum in PBS for 1 hour

• Apply biotin-conjugated PIK3C3 antibody at 1:200-1:400 dilution in blocking buffer

• Incubate overnight at 4°C in a humidified chamber

• Wash 3 times with PBS containing 0.1% Tween-20

• Apply streptavidin-HRP (1:500) for 1 hour at room temperature

• Develop with DAB substrate and counterstain with hematoxylin

Validation Controls:

• Include kidney sections from cell type-specific Pik3c3 knockout mice as negative controls

• Use proximal tubule and podocyte markers in parallel sections to confirm cell-specific expression patterns

This protocol has been validated for detecting differential expression of PIK3C3 across kidney cell types, with special attention to the high expression in podocytes and proximal tubule cells. For multiplexed staining with nephron segment markers, sequential staining protocols using spectrally distinct fluorophores are recommended.

How can researchers effectively use PIK3C3 antibody in Western blot applications for detecting changes in expression levels?

For effective Western blot application using biotin-conjugated PIK3C3 antibody, researchers should implement the following optimized protocol:

Sample Preparation:

• Extract total protein from tissues or cells using RIPA buffer supplemented with protease inhibitors

• Quantify protein using BCA or Bradford assay

• Prepare 20-30 μg of protein per lane in Laemmli buffer containing β-mercaptoethanol

• Heat samples at 95°C for 5 minutes

Gel Electrophoresis and Transfer:

• Separate proteins on 8-10% SDS-PAGE (PIK3C3 is approximately 100 kDa)

• Transfer to PVDF membrane (0.45 μm) at 100V for 90 minutes using cold transfer buffer

Immunoblotting:

• Block membrane with 5% non-fat milk in TBST for 1 hour at room temperature

• Incubate with biotin-conjugated PIK3C3 antibody at 1:1000-1:5000 dilution overnight at 4°C

• Wash membrane 3 times with TBST, 5 minutes each

• Incubate with streptavidin-HRP at 1:5000 dilution for 1 hour

• Wash 3 times with TBST, 5 minutes each

• Detect using enhanced chemiluminescence (ECL) substrate

Quantification and Validation:

• Use β-actin or GAPDH as loading controls

• Quantify band intensity using image analysis software (ImageJ)

• Compare relative expression as normalized ratio of PIK3C3 to loading control

• Validate specificity using siRNA knockdown or knockout samples

Troubleshooting Recommendations:

• For weak signals: Increase antibody concentration, extend incubation time, or use signal enhancement systems

• For high background: Increase washing steps or adjust blocking conditions

• For multiple bands: Verify with PIK3C3 knockout/knockdown samples to confirm specificity

This protocol has been successfully applied to detect differential PIK3C3 expression between normal and cancerous tissues, as well as between cancer stem cell populations and non-stem cell populations .

What considerations should be made when designing co-immunofluorescence experiments using biotin-conjugated PIK3C3 antibody?

When designing co-immunofluorescence experiments with biotin-conjugated PIK3C3 antibody, several critical factors must be considered for optimal results:

Experimental Design Considerations:

• Avidin-Biotin Interaction Management:

  • If using multiple biotin-conjugated primary antibodies, sequential detection is necessary

  • Block endogenous biotin using avidin-biotin blocking kit before antibody application

  • Consider using streptavidin conjugated to spectrally distinct fluorophores when multiplexing

• Antibody Compatibility:

  • Ensure secondary antibodies against co-staining markers are raised in different host species

  • For nephron segment markers or cell-type specific markers, verify compatibility with PIK3C3 antibody

  • Test for cross-reactivity in single-staining controls

• Signal Optimization:

  • Titrate antibody dilutions (typically starting at 1:100-1:500 for immunofluorescence)

  • Determine optimal incubation time and temperature

  • Consider tyramide signal amplification for low abundance targets

• Controls and Validation:

  • Include cell type-specific Pik3c3 knockout tissues as negative controls

  • Use single-color controls to assess bleed-through

  • Implement absorption controls using blocking peptides

Recommended Protocol for Co-staining:

• Fix cells/tissues in 4% paraformaldehyde

• Permeabilize with 0.2% Triton X-100

• Block with 5% normal serum

• Apply biotin-conjugated PIK3C3 antibody and non-biotinylated co-markers

• Detect PIK3C3 with fluorophore-conjugated streptavidin

• Detect co-markers with appropriate species-specific secondary antibodies

• Counterstain nuclei with DAPI

• Mount with anti-fade medium

This approach has been validated for co-immunofluorescence staining of PIK3C3 with nephron segment-specific markers, revealing the differential expression of PIK3C3 across kidney cell types . Similar approaches can be applied to study PIK3C3 in cancer stem cells, where co-staining with CD133 has revealed positive correlation between PIK3C3 and stemness markers .

How can PIK3C3 antibody be used to investigate the relationship between PIK3C3 expression and cancer stem cell properties?

Investigating the relationship between PIK3C3 expression and cancer stem cell (CSC) properties requires sophisticated experimental approaches using biotin-conjugated PIK3C3 antibody. Based on recent findings in hepatocellular carcinoma (HCC), the following comprehensive methodology is recommended:

Correlation Analysis in Clinical Samples:

Functional Studies in Cell Models:

• Isolate CSC populations using magnetic-activated cell sorting (MACS) for CD133+ cells

• Compare PIK3C3 expression between CSC and non-CSC populations by Western blot

• Perform spheroid formation assays following PIK3C3 knockdown or inhibition

• Assess self-renewal capacity through secondary spheroid formation efficiency

• Evaluate stemness marker expression (Nanog, Oct4, Sox2) after PIK3C3 manipulation

Mechanistic Investigation:

• Analyze PIK3C3-dependent signaling pathways (AMPK, SGK3) in CSCs versus non-CSCs

• Perform RNA-seq to identify gene expression changes following PIK3C3 inhibition

• Validate key targets using qRT-PCR and Western blot

• Assess autophagy flux using LC3 and p62 analysis to determine autophagy-dependent versus independent mechanisms

In Vivo Validation:

• Implant PIK3C3-manipulated cells in immunodeficient mice

• Monitor tumor growth and perform limiting dilution assays

• Analyze tumors for CSC marker expression and PIK3C3 levels

Research has shown that PIK3C3 is markedly increased in HCC tissues and liver CSCs, with a positive correlation between PIK3C3 and CD133 expression. Importantly, PIK3C3 inhibition has been demonstrated to effectively eliminate liver CSCs and inhibit tumor growth, making it a promising therapeutic target .

What are the best approaches for analyzing PIK3C3 expression correlation with clinical outcomes in tissue microarrays?

For analyzing PIK3C3 expression correlation with clinical outcomes in tissue microarrays (TMAs), researchers should implement the following comprehensive methodological framework:

TMA Staining and Scoring:

• Stain TMAs with validated biotin-conjugated PIK3C3 antibody at optimal dilution (1:200-1:400)

• Develop with streptavidin-HRP and DAB chromogen

• Implement multi-tier scoring system:

  • Intensity score (0: negative, 1: weak, 2: moderate, 3: strong)

  • Percentage score (0: <5%, 1: 5-25%, 2: 26-50%, 3: 51-75%, 4: >75%)

  • Calculate H-score (intensity × percentage) for semi-quantitative analysis

• Ensure scoring is performed by two independent pathologists blinded to clinical data

• Resolve discrepancies through consensus review

Statistical Analysis Pipeline:

• Determine optimal cutoff values for "high" versus "low" PIK3C3 expression using:

  • ROC curve analysis

  • X-tile software

  • Median or quartile-based thresholds

• Perform Kaplan-Meier survival analysis comparing high versus low expression groups

• Calculate hazard ratios using Cox proportional hazards models:

  • Univariate analysis for PIK3C3 expression

  • Multivariate analysis adjusting for clinical covariates (stage, grade, age, etc.)

• Assess correlations with clinical parameters using:

  • Chi-square test for categorical variables

  • Mann-Whitney U test for continuous variables

• Implement machine learning algorithms for predictive modeling

Validation Strategies:

• Split cohort into training and validation sets

• Perform external validation in independent cohorts

• Correlate protein expression with mRNA data from public databases (TCGA, GEO)

• Verify findings at single-cell resolution if available

How can researchers differentiate between autophagy-dependent and autophagy-independent functions of PIK3C3 using biotin-conjugated antibodies?

Differentiating between autophagy-dependent and autophagy-independent functions of PIK3C3 requires sophisticated experimental design using biotin-conjugated PIK3C3 antibodies in conjunction with autophagy markers and functional assays:

Dual-Marker Colocalization Analysis:

• Perform co-immunofluorescence with biotin-conjugated PIK3C3 antibody and autophagy markers:

  • Early autophagy: ATG5, ATG12, BECN1

  • Autophagosomes: LC3-II

  • Autophagic flux: p62/SQSTM1

• Quantify colocalization using Pearson's or Mander's coefficients

• Compare subcellular distribution under basal conditions versus:

  • Starvation (autophagy induction)

  • Bafilomycin A1 treatment (autophagy inhibition)

  • PIK3C3 inhibitors (e.g., VPS34-IN-1)

Functional Separation Strategy:

• Implement genetic approaches:

  • Generate PIK3C3 constructs with mutations in autophagy-specific interaction domains

  • Create cell lines expressing these constructs in PIK3C3-knockout background

  • Analyze restoration of specific functions (autophagy, endocytosis, nutrient sensing)

• Apply biochemical fractionation:

  • Isolate distinct PIK3C3 complexes (PI3KC3-C1 vs. PI3KC3-C2)

  • Analyze complex-specific interacting partners

  • Perform activity assays for each complex

Pathway-Specific Analysis:

• For autophagy pathway:

  • Monitor LC3-I to LC3-II conversion by Western blot

  • Assess autophagic flux using tandem mRFP-GFP-LC3 reporters

  • Measure long-lived protein degradation

• For non-autophagy pathways:

  • Endocytosis: Track EGF receptor internalization and degradation

  • Nutrient sensing: Analyze mTOR signaling

  • Cell growth: Measure SGK3 activation

Pathway Inhibitor Approach:

• Compare effects of:

  • PIK3C3 inhibition (VPS34-IN-1)

  • Autophagy inhibition (bafilomycin A1, chloroquine)

  • Dual inhibition

• Assess functional outcomes in:

  • Cancer stem cell maintenance

  • EGFR signaling termination

  • Cell survival under stress

Research using this approach has revealed that PIK3C3 regulates liver cancer stem cells independent of the autophagy process, while its role in EGFR signaling in renal proximal tubule cells involves endocytic trafficking and lysosomal degradation . This methodological framework allows researchers to parse the diverse functions of PIK3C3 beyond its canonical role in autophagy.

What are the most common issues encountered when using PIK3C3 antibody in kidney tissue sections and how can they be resolved?

Researchers frequently encounter several challenges when using biotin-conjugated PIK3C3 antibody in kidney tissue sections. Here are the most common issues and evidence-based solutions:

High Background Staining:

• Problem Analysis: Excessive background often results from endogenous biotin in kidney tissues, particularly in proximal tubules, or insufficient blocking.

• Solution Strategy:

  • Implement avidin-biotin blocking kit before primary antibody application

  • Extend blocking time to 2 hours using 5% BSA in PBS

  • Add 0.1-0.3% Triton X-100 to reduce non-specific binding

  • Optimize antibody dilution (test range: 1:200-1:500)

  • Include 0.1% Tween-20 in all washing steps

Variable Staining Intensity:

• Problem Analysis: Disparities in PIK3C3 expression across kidney cell types (high in podocytes, low in mesangial cells) can be misinterpreted as technical variation.

• Solution Strategy:

  • Include positive controls (podocytes) and negative controls (mesangial cells) in each experiment

  • Use cell type-specific Pik3c3 knockout tissues as definitive negative controls

  • Standardize fixation time (24 hours in 4% PFA) and antigen retrieval conditions

  • Implement automated staining platforms for consistency

Epitope Masking:

• Problem Analysis: Routine formalin fixation can mask the PIK3C3 epitope through protein cross-linking.

• Solution Strategy:

  • Optimize antigen retrieval using citrate buffer (pH 6.0) with pressure cooking

  • Test alternative retrieval methods (EDTA buffer pH 9.0, enzymatic retrieval)

  • Consider shorter fixation times (12-18 hours) for future specimens

  • Use fresh frozen sections for highly sensitive applications

Specific Technical Recommendations:

• For studying proximal tubules (high EGFR and PIK3C3 expression):

  • Co-stain with megalin or SGLT2 as proximal tubule markers

  • Use confocal microscopy to resolve subcellular localization

• For glomerular studies (differential expression across glomerular cell types):

  • Implement triple immunofluorescence with podocyte (nephrin), endothelial (CD31), and mesangial (α-SMA) markers

  • Use spectral unmixing to resolve overlapping signals

These troubleshooting strategies have been validated in studies examining PIK3C3 expression across various kidney cell types, particularly in analyzing the role of PIK3C3 in EGFR signaling in renal proximal tubule cells .

How can researchers optimize the detection sensitivity of biotin-conjugated PIK3C3 antibody in Western blot for low-abundance samples?

Optimizing detection sensitivity for biotin-conjugated PIK3C3 antibody in Western blot analysis of low-abundance samples requires a systematic approach to each step of the protocol:

Sample Preparation Enhancement:

• Implement enrichment strategies:

  • Use phosphatase and protease inhibitor cocktails in lysis buffer

  • Perform subcellular fractionation to concentrate cytoplasmic proteins

  • Consider immunoprecipitation with a different PIK3C3 antibody before Western blot

• Optimize protein extraction:

  • Use RIPA buffer with 0.1% SDS for improved solubilization

  • Sonicate lysates (3 × 10 seconds) to shear DNA and improve protein recovery

  • Centrifuge at 14,000 × g for 15 minutes at 4°C to remove debris

Gel Electrophoresis Optimization:

• Load higher protein amounts (40-60 μg) for low-abundance samples

• Use gradient gels (4-15%) for improved resolution

• Implement longer separation times at lower voltage (80V)

• Consider large-format gels for better band separation

Transfer Efficiency Improvement:

• Use wet transfer system at 30V overnight at 4°C

• Add 0.05% SDS to transfer buffer to improve high-molecular-weight protein transfer

• Confirm transfer efficiency with reversible protein stains (Ponceau S)

Signal Amplification Strategies:

• Primary antibody optimization:

  • Extend incubation to 48 hours at 4°C

  • Use antibody dilution in range of 1:300-1:1000

  • Add 5% PEG-4000 to antibody diluent to enhance binding kinetics

• Detection system enhancement:

  • Implement high-sensitivity streptavidin-HRP conjugates

  • Use signal enhancement reagents (SuperSignal™ West Femto)

  • Consider tyramide signal amplification for extreme sensitivity

  • Extend exposure times up to 30 minutes for digital imaging systems

Background Reduction Techniques:

• Use 5% non-fat milk with 1% BSA in TBST for blocking

• Include 0.1% Tween-20 in antibody dilution buffers

• Perform extensive washing (5 × 5 minutes) in TBST between steps

• Use filtered buffers to prevent particulate contamination

This optimized protocol has been successfully applied to detect PIK3C3 in samples with low expression, such as in comparative studies between normal kidney tissues and cell type-specific knockouts, as well as in cancer stem cell populations where protein amounts may be limited .

What strategies can overcome cross-reactivity issues when using PIK3C3 antibody in multi-color immunofluorescence experiments?

Cross-reactivity in multi-color immunofluorescence experiments using biotin-conjugated PIK3C3 antibody presents a complex challenge requiring systematic approaches to ensure specific and accurate detection:

Antibody Validation and Selection:

• Perform comprehensive validation:

  • Test antibody on PIK3C3 knockout tissues or cells as definitive negative control

  • Compare staining patterns across multiple antibody clones

  • Verify results using absorption controls with immunizing peptide

• Select complementary primary antibodies:

  • Choose antibodies raised in different host species

  • Verify antibody isotypes to ensure secondary compatibility

  • Test each antibody individually before multiplexing

Sequential Staining Protocol:

• For biotin-streptavidin system conflicts:

  • Perform PIK3C3 staining first with biotin-conjugated antibody

  • Block with unconjugated streptavidin (10 μg/ml)

  • Apply biotin (50 μg/ml) to saturate remaining binding sites

  • Proceed with subsequent antibodies

• For spectral overlap issues:

  • Implement sequential detection using zenon labeling technology

  • Remove previous antibody layers using glycine stripping buffer (pH 2.5) between rounds

  • Capture images between sequential staining rounds

Advanced Technical Solutions:

• Employ spectral imaging:

  • Use confocal microscopes with spectral detectors

  • Implement linear unmixing algorithms to separate overlapping fluorophores

  • Create spectral libraries for each fluorophore

• Apply signal separation strategies:

  • Use quantum dots with narrow emission spectra

  • Implement fluorescence lifetime imaging (FLIM) for challenging combinations

  • Consider mass cytometry (CyTOF) for highly multiplexed detection

Computational Approaches:

• Implement post-acquisition correction:

  • Apply mathematical algorithms for bleed-through correction

  • Use reference images for computational unmixing

  • Employ machine learning-based segmentation for ambiguous signals

• Conduct careful controls:

  • Include single-color controls for each fluorophore

  • Use isotype controls matched to each primary antibody

  • Implement fluorescence-minus-one (FMO) controls

This methodological framework has been validated in studies examining PIK3C3 expression in conjunction with cell type-specific markers in kidney tissues, where distinguishing between closely adjacent structures like podocytes and endothelial cells requires precise signal separation . Similar approaches can be applied to cancer tissue studies where PIK3C3 needs to be visualized alongside stemness markers like CD133 and other cellular markers .

How can PIK3C3 antibody be used to investigate the relationship between autophagy and EGFR signaling in renal proximal tubule cells?

Investigating the interplay between autophagy and EGFR signaling in renal proximal tubule cells (RPTCs) using PIK3C3 antibody requires an integrated methodological approach:

Dual-Pathway Analysis System:

• Establish baseline expression profile:

  • Perform co-immunofluorescence with biotin-conjugated PIK3C3 antibody (1:200) and EGFR antibody

  • Quantify colocalization in proximal tubule segments using confocal microscopy

  • Validate proximal tubule identity using segment-specific markers (megalin, SGLT2)

• Implement dynamic signaling analysis:

  • Stimulate cultured RPTCs with EGF (100 ng/ml) for various time points (0-120 min)

  • Track EGFR internalization, degradation, and signaling using immunofluorescence and Western blot

  • Monitor autophagy markers (LC3-II, p62) in parallel

  • Assess PIK3C3 activity using PI3P detection methods (FYVE domain reporters)

Mechanistic Dissection Approach:

• Manipulate PIK3C3 activity:

  • Apply selective PIK3C3 inhibitors (VPS34-IN-1, SAR405)

  • Implement genetic knockdown using siRNA or CRISPR-Cas9

  • Rescue experiments with wild-type or mutant PIK3C3 constructs

• Analyze EGFR trafficking:

  • Track early endosome (EEA1), late endosome (Rab7), and lysosome (LAMP1) markers

  • Measure EGFR degradation rates by cycloheximide chase assay

  • Assess EGFR signaling outputs (ERK1/2, AKT phosphorylation)

  • Quantify recycling versus degradative sorting using biotinylation assays

Functional Outcome Measurement:

• Cell biology endpoints:

  • Analyze cell proliferation in response to EGF with/without PIK3C3 inhibition

  • Measure cell migration using wound healing assays

  • Assess epithelial differentiation markers under various conditions

• Disease-relevant contexts:

  • Evaluate responses in normal versus injured kidneys (ischemia-reperfusion, nephrotoxicity)

  • Compare primary RPTCs from control versus kidney disease models

  • Analyze human kidney biopsies from patients with tubular disorders

Research has demonstrated that RPTCs express high levels of both PIK3C3 and EGFR, and PIK3C3 inhibition significantly delays EGF-stimulated EGFR degradation and signaling termination . Mechanistically, PIK3C3 inhibition does not affect initial endocytosis but impedes lysosomal degradation of EGFR, suggesting a specific role in late endosomal/lysosomal trafficking rather than early endocytosis steps. This methodological approach enables comprehensive investigation of this intricate signaling intersection in kidney physiology and pathology.

What are the most effective approaches for comparing PIK3C3 inhibition versus genetic knockdown when studying cancer stem cell maintenance?

For rigorously comparing PIK3C3 inhibition versus genetic knockdown in cancer stem cell (CSC) maintenance studies, researchers should implement the following comprehensive approach:

Experimental System Design:

• Cell models:

  • Use established HCC cell lines with documented CSC populations

  • Isolate CD133+ liver CSCs using magnetic-activated cell sorting

  • Generate patient-derived tumor organoids to validate findings in primary contexts

• Intervention strategies:

  • Chemical inhibition: Apply selective PIK3C3 inhibitors (VPS34-IN-1, SAR405) at IC50 concentrations

  • Genetic manipulation:

    • Transient: siRNA-mediated knockdown (72-96 hours)

    • Stable: shRNA or CRISPR-Cas9 knockout

    • Inducible: Tet-on/off systems for temporal control

Comparative Analysis Framework:

• Target engagement verification:

  • Confirm PIK3C3 protein reduction via Western blot using validated antibodies (1:1000 dilution)

  • Measure PI3P production using mass spectrometry or FYVE-domain reporters

  • Assess autophagy inhibition via LC3-II accumulation and p62 degradation blockade

• CSC phenotype evaluation:

  • Sphere formation efficiency in ultra-low attachment conditions

  • Expression of stemness markers (CD133, CD90, Nanog, Oct4) via flow cytometry and qPCR

  • Self-renewal capacity through serial sphere formation assays

  • In vivo tumorigenicity using limiting dilution xenograft assays

Mechanistic Pathway Analysis:

• Comparative signaling studies:

  • Analyze AMPK activation status (phospho-AMPK T172)

  • Monitor SGK3 activation under PI3K inhibitor treatment

  • Assess mTOR signaling components (p70S6K, 4EBP1)

  • Evaluate canonical stemness pathways (Wnt/β-catenin, Notch, Hedgehog)

• Temporal dynamics assessment:

  • Time-course analysis of pathway activation/inhibition

  • Comparison of acute versus chronic effects

  • Resistance development profiling

Combined Approach Benefits:

• Inhibitor studies:

  • Rapid onset of action

  • Dose-dependent effects

  • Potential for clinical translation

  • Limited off-target effects with newer selective inhibitors

• Genetic manipulation advantages:

  • Specificity for target protein

  • Analysis of scaffold versus enzymatic functions

  • Long-term effects assessment

  • Isoform-specific targeting

Research has demonstrated that upregulated PIK3C3 facilitates liver CSC expansion, while RNAi-mediated silencing of PIK3C3 inhibits this effect. Moreover, PIK3C3 inhibitors effectively eliminate liver CSCs and suppress tumor growth in vivo . When combined with PI3K inhibitors, PIK3C3 inhibition shows synergistic effects in preventing CSC expansion, suggesting a potential therapeutic strategy for HCC treatment.

How can researchers use PIK3C3 antibody to explore the differential expression patterns across developmental stages in kidney formation?

Exploring differential PIK3C3 expression patterns during kidney development requires a sophisticated methodological approach using biotin-conjugated PIK3C3 antibody across multiple developmental timepoints:

Developmental Timeline Analysis:

• Sample collection strategy:

  • Harvest mouse kidneys at key developmental stages:

    • Embryonic (E12.5, E14.5, E16.5, E18.5)

    • Postnatal (P0, P7, P14, P21)

    • Adult (8-12 weeks)

  • Process tissues using consistent fixation protocols (4% PFA, 24 hours)

  • Prepare both paraffin sections and frozen sections for complementary analyses

• Spatiotemporal mapping:

  • Perform immunohistochemistry using biotin-conjugated PIK3C3 antibody (1:200-1:400)

  • Create expression heat maps across nephron segments at each developmental stage

  • Quantify expression intensity using digital image analysis

  • Generate 3D reconstructions to visualize spatial distribution patterns

Cellular Differentiation Correlation:

• Multi-marker co-localization:

  • Implement dual/triple immunofluorescence with:

    • Nephrogenic zone markers (Six2, Cited1)

    • Differentiating structure markers (Wt1, Lhx1)

    • Segment-specific markers (lotus lectin, THP, calbindin)

  • Quantify PIK3C3 expression relative to differentiation status

  • Track expression changes during mesenchymal-to-epithelial transition

• Single-cell resolution approaches:

  • Apply RNAscope for PIK3C3 mRNA detection in conjunction with protein staining

  • Implement laser capture microdissection of specific structures followed by qPCR or proteomics

  • Consider single-cell RNA sequencing to correlate PIK3C3 with developmental gene programs

Functional Significance Assessment:

• Ex vivo kidney culture models:

  • Culture embryonic kidneys with/without PIK3C3 inhibitors

  • Assess branching morphogenesis and nephron formation

  • Analyze cell proliferation, apoptosis, and differentiation markers

• Conditional knockout strategy:

  • Generate developmental stage-specific or cell type-specific Pik3c3 knockout models

  • Analyze resulting phenotypes using the antibody staining protocol to confirm deletion

  • Correlate morphological defects with expression patterns

This comprehensive approach would build upon the established finding that adult kidneys show differential PIK3C3 expression across cell types, with podocytes exhibiting the highest levels and proximal tubules showing the highest expression among tubular segments . Developmental analysis could reveal whether these patterns are established early or emerge during maturation, providing insights into the role of PIK3C3 in kidney morphogenesis and nephron segmentation.

What is the current consensus on the most reliable detection methods for PIK3C3 across different experimental systems?

Based on comprehensive analysis of recent research, the consensus on optimal PIK3C3 detection methods varies by experimental system, with each approach offering distinct advantages:

For Tissue Section Analysis:
Immunohistochemistry using biotin-conjugated PIK3C3 antibody (1:200-1:400 dilution) with streptavidin-HRP detection systems provides optimal results for spatial distribution studies . This approach has been rigorously validated through:

• Comparison against tissues from cell type-specific Pik3c3 knockout mice

• Consistent detection across multiple fixation protocols

• Reproducible differentiation between high-expressing (podocytes, proximal tubules) and low-expressing (mesangial cells, interstitial cells) populations

For Protein Expression Quantification:
Western blotting with biotin-conjugated PIK3C3 antibody (1:1000-1:5000 dilution) represents the gold standard for comparative expression studies . Key technical considerations include:

• Optimal protein detection at approximately 100 kDa

• Enhanced sensitivity using chemiluminescent detection systems

• Requirement for careful blocking to prevent non-specific binding

• Critical importance of validated loading controls for accurate quantification

For Subcellular Localization:
Confocal immunofluorescence microscopy using biotin-conjugated PIK3C3 antibody (1:100-1:500) with fluorophore-conjugated streptavidin provides superior resolution of intracellular PIK3C3 distribution . This approach enables:

• Precise colocalization with organelle markers

• Dynamic tracking during cellular processes (autophagy, endocytosis)

• Multiplexed analysis with other signaling components

• 3D reconstruction of spatial relationships

For High-Throughput Applications:
Flow cytometry using intracellular staining protocols with biotin-conjugated PIK3C3 antibody provides efficient quantification across large cell populations, particularly valuable for:

• Comparing PIK3C3 levels between CSC and non-CSC populations

• Correlating PIK3C3 with surface markers (CD133, EGFR)

• Assessing PIK3C3 changes in response to treatments

• Sorting cells based on PIK3C3 expression levels

For Clinical Applications:
Immunohistochemistry remains the most reliable method for clinical samples, with tissue microarray analysis demonstrating:

• Consistent correlation between PIK3C3 expression and clinical outcomes in HCC

• Reproducible scoring systems applicable across laboratories

• Compatibility with standard pathology workflows

• Potential for automated quantification using digital pathology platforms

These consensus methods reflect the integration of findings across multiple research contexts, providing researchers with optimized approaches based on their specific experimental questions and systems.

How have PIK3C3 antibodies contributed to our understanding of the dual role of PIK3C3 in cancer progression and potential therapeutic applications?

PIK3C3 antibodies have provided crucial insights into the complex roles of PIK3C3 in cancer biology, revealing both tumor-promoting and tumor-suppressing functions that have significant implications for therapeutic development:

Diagnostic and Prognostic Contributions:

Mechanistic Insights:

• Autophagy-independent functions:

  • PIK3C3 antibodies have helped delineate autophagy-dependent versus independent functions

  • Research using these antibodies revealed that PIK3C3 regulates liver CSCs independent of autophagy processes

  • Colocalization studies identified interactions with non-canonical signaling partners

• Pathway cross-talk:

  • Antibody-based protein detection showed that PIK3C3 inhibition blocks the activation of SGK3 induced by PI3K inhibitors

  • Western blot analysis using PIK3C3 antibodies demonstrated that PIK3C3 inhibition activates AMPK

  • Coimmunoprecipitation studies identified novel PIK3C3 interaction partners in cancer cells

Therapeutic Implications:

• Targeting cancer stem cells:

  • Antibody-validated studies demonstrated that PIK3C3 is required for liver CSC expansion

  • Functional studies following detection of PIK3C3 in CSCs led to identification of PIK3C3 as an effective target against these therapy-resistant cells

  • Expression analysis guided development of therapeutic strategies specifically targeting PIK3C3 in CSCs

• Combination therapy rationales:

  • Mechanistic studies using PIK3C3 antibodies revealed that PIK3C3 inhibition blocks the expansion of CSCs induced by PI3K inhibitor

  • This discovery led to combination approaches with greater efficacy than either treatment alone

  • Antibody-based pathway analysis identified rational combinations targeting complementary signaling nodes

• Biomarker-guided therapy:

  • Immunohistochemical detection of PIK3C3 may identify patients most likely to benefit from PIK3C3 inhibition

  • Expression patterns across tumor types guide indication selection for clinical trials

  • Correlation studies between PIK3C3 and other markers inform patient stratification strategies