pdcd10b Antibody

What is PDCD10 and why is it important in research?

PDCD10 (Programmed Cell Death 10) is a highly conserved protein encoded by the PDCD10 gene that plays a crucial role in regulating cell apoptosis. It interacts with the serine/threonine protein kinase MST4 to modulate the extracellular signal-regulated kinase (ERK) pathway . PDCD10 has gained significant research interest due to its involvement in:

• Tumor progression mechanisms in various cancers including osteosarcoma and pancreatic cancer

• Vascular development and cerebral cavernous malformations

• Cell survival and apoptosis regulatory pathways

• Cellular transformation and anchorage-independent growth

Research has shown that PDCD10 inhibits tumor cell apoptosis and promotes tumor progression by activating the EMT (epithelial-mesenchymal transition) pathway . The protein is highly expressed in patients with osteosarcoma and is closely related to patient prognosis, making it a potential therapeutic target .

What is the difference between PDCD10, PDCD10a, and PDCD10b?

PDCD10a and PDCD10b appear to be variants or isoforms of the PDCD10 protein. While the core literature focuses primarily on PDCD10 as a whole, these specific isoforms may have tissue-specific or organism-specific expression patterns . The distinction is particularly important when:

• Conducting cross-species studies (human vs. murine models)

• Investigating specific tissue expression patterns

• Designing targeted genetic knockdown experiments

• Selecting antibodies for specific experimental applications

When designing experiments, researchers should carefully consider which isoform is most relevant to their specific research question and ensure their antibodies have appropriate specificity.

What are the recommended applications for PDCD10 antibodies?

Based on validated research applications, PDCD10 antibodies are suitable for:

Each application requires specific optimization for your experimental system. Most commercial antibodies provide recommended starting dilutions that should be further optimized for specific cell lines or tissues .

How should I validate a new PDCD10 antibody for my research?

Proper antibody validation is crucial for reliable research outcomes. A comprehensive validation protocol for PDCD10 antibodies should include:

• Western blot analysis with positive controls: Use cell lines known to express PDCD10 such as PC-3 (prostate cancer) which shows high expression, compared to cell lines with lower expression like HeLa or HepG2 .

• Knockout/knockdown validation: The gold standard approach involves:

  • Using siRNA knockdown of PDCD10 (siPDCD10-1 or siPDCD10-2) to reduce expression

  • Comparing antibody reactivity in wild-type vs. knockdown samples

  • Looking for significant reduction in signal intensity in the knockdown samples

• Recombinant protein controls: Test antibody reactivity against:

  • Purified recombinant PDCD10 protein

  • Overexpressed GFP-PDCD10 fusion protein in transfected cells

• Cross-reactivity assessment: Ensure specificity by testing against:

  • Related protein family members

  • E. coli lysates and other potential contaminants like GST

• Multiple detection methods: Confirm specificity across methods like IHC, IF, and WB .

A properly validated antibody should detect endogenous PDCD10 at the expected molecular weight (~25 kDa) and show reduced signal in knockdown experiments .

What are the best positive control tissues/cell lines for PDCD10 antibody testing?

Based on expression data, the following samples serve as effective positive controls:

Cell Lines:

• PC-3 (prostate cancer): High PDCD10 expression

• A-431, K-562, U-251MG, SKOV3: Validated positive samples

• MG63 and U2OS (osteosarcoma lines): Used in PDCD10 functional studies

Tissue Samples:

• Osteosarcoma tissue: Shows high PDCD10 expression (86.84% positive by IHC)

• Mouse brain tissue: Consistent PDCD10 expression

• Human renal cancer tissue: Validated for IHC applications

• Rat spleen tissue: Validated for IHC applications

When establishing a new antibody or methodology, it's recommended to use multiple positive controls spanning different tissue types and expression levels to ensure reliability across various experimental conditions .

What methodological considerations are important when using PDCD10 antibodies for immunohistochemistry?

When performing IHC with PDCD10 antibodies, consider these critical methodological aspects:

• Tissue preparation and fixation:

  • Paraffin-embedded sections should be properly fixed and processed

  • For PDCD10, standard formalin fixation has been validated in multiple studies

• Antigen retrieval methods:

  • Heat-induced epitope retrieval is typically required

  • Buffer selection (citrate vs. EDTA) may affect antibody performance

• Blocking optimization:

  • Sufficient blocking is crucial to reduce background

  • BSA or serum-based blocking solutions are commonly used

• Antibody concentration:

  • Starting dilution of 1:200 is recommended for most commercial antibodies

  • Titration experiments should be performed to optimize signal-to-noise ratio

• Detection systems:

  • Both chromogenic (DAB) and fluorescent detection systems work with PDCD10 antibodies

  • Signal amplification may be necessary for low-expressing samples

• Counterstaining:

  • Hematoxylin counterstaining helps visualize tissue architecture

  • When performing co-localization studies, select compatible fluorophores

• Controls:

  • Include positive control tissues (osteosarcoma, renal cancer tissue)

  • Include negative controls (antibody diluent only, isotype control)

  • If possible, include PDCD10-knockdown tissue as specificity control

PDCD10 primarily shows nuclear localization in most cell types, with some cytoplasmic staining also reported . This subcellular distribution should be considered when evaluating staining patterns.

How can PDCD10 antibodies be used to investigate protein-protein interactions in cancer research?

PDCD10 antibodies are valuable tools for studying protein-protein interactions through several methodologies:

• Co-immunoprecipitation (Co-IP):

  • PDCD10 antibodies can pull down interaction partners like MST4

  • This approach validated the PDCD10-MST4 interaction in 293T cells

  • Protocol: Lyse cells in appropriate buffer, pre-clear with protein G, incubate with PDCD10 antibody, precipitate complexes, and analyze by Western blot for interaction partners

• Proximity ligation assay (PLA):

  • Allows visualization of protein interactions in situ

  • Requires antibodies from different species for PDCD10 and putative partners

• Immunofluorescence co-localization:

  • Can show spatial overlap between PDCD10 and interaction partners

  • Particularly useful for studying PDCD10's association with cellular structures

• Fluorescence resonance energy transfer (FRET):

  • When combined with fluorescently-tagged proteins

  • Provides high-resolution detection of direct protein interactions

The interaction between PDCD10 and MST4 has been confirmed through yeast two-hybrid screening and validated by co-immunoprecipitation analysis . This interaction appears to influence cellular transformation and anchorage-independent growth, which are important hallmarks of cancer progression.

What approaches are recommended for studying PDCD10 function in tumor progression?

Based on published research methodologies, several approaches have proven effective:

• Genetic manipulation strategies:

  • siRNA knockdown: siPDCD10-1 and siPDCD10-2 have been validated for transient knockdown

  • Stable knockdown: Lentiviral shRNA vectors (like LV-PDCD10 71721) for long-term studies

  • Overexpression: Transfection with PDCD10 cDNA in pcDNA-3.1 plasmids

  • CRISPR/Cas9 knockout: For complete elimination of PDCD10 expression

• Functional assays in vitro:

  • Proliferation: CCK-8 assay and plate cloning assays

  • Migration: Wound healing assay

  • Invasion: Transwell assay

  • Apoptosis: Flow cytometry with Annexin V/PI staining

  • Anoikis assay: Using poly-HEME coated plates to prevent cell attachment

• In vivo models:

  • Subcutaneous xenograft models in immunodeficient mice

  • MG63-bearing mice have proven effective for studying PDCD10's role in tumor growth

  • Measurement of tumor volume, weight, and immunohistochemical analysis

• Molecular pathway analysis:

  • Western blot analysis for EMT markers

  • Apoptosis pathway components

  • ERK signaling pathway components

Research has shown that PDCD10 knockdown inhibits osteosarcoma growth, proliferation, migration, and invasion, while PDCD10 overexpression promotes these processes . These findings suggest PDCD10 inhibits tumor cell apoptosis and promotes tumor progression by activating the EMT pathway.

How do I address contradictory findings when studying PDCD10 in different cancer types?

Contradictory findings regarding PDCD10 function across different cancer types are a documented challenge . A systematic approach to addressing this includes:

• Tissue and context specificity analysis:

  • Compare expression patterns across tissue types using tissue microarrays

  • Analyze PDCD10 expression in different stages of the same cancer type

  • Use public datasets (like TCGA and GTEx) to compare PDCD10 expression patterns across cancer types

• Molecular context investigation:

  • Examine PDCD10 binding partners in different cellular contexts

  • Analyze pathway differences between responsive and non-responsive tissues

  • Consider genetic background and mutations in related genes

• Methodological validation:

  • Ensure antibody specificity in each tissue type being studied

  • Validate knockdown/overexpression efficiency in each model system

  • Use multiple methodological approaches to confirm findings

• Comprehensive reporting:

  • Document all experimental variables that might influence outcomes

  • Report negative results alongside positive findings

  • Compare methodological differences between your study and contradictory publications

For example, while PDCD10 promotes tumor progression in osteosarcoma and pancreatic cancer , its function may differ in other tumor types. Analysis of PDCD10 expression using TCGA and GTEx databases can help identify cancer types where PDCD10 might play different roles , guiding more targeted experimental approaches.

What are common challenges when using PDCD10 antibodies for Western blotting?

Researchers often encounter these technical challenges when using PDCD10 antibodies for Western blotting:

• Detection specificity issues:

  • PDCD10 has a molecular weight of approximately 25 kDa

  • Non-specific bands may appear around similar molecular weights

  • Solution: Use positive controls and PDCD10 knockdown samples to confirm specificity

• Weak signal strength:

  • PDCD10 expression varies considerably across cell lines

  • Solution: Load more protein for low-expressing samples, use signal enhancement systems, or select cell lines with higher expression like PC-3

• Background noise:

  • Can obscure specific PDCD10 signal

  • Solution: Optimize blocking (5% non-fat milk or BSA), increase washing steps, and titrate primary antibody concentration

• Inconsistent results between experiments:

  • May reflect protein degradation

  • Solution: Use fresh samples, add protease inhibitors to lysis buffer, and standardize protein extraction method

• Discrepancies between antibody sources:

  • Different epitopes can yield different results

  • Solution: Validate multiple antibodies against the same samples and report epitope information

A recommended Western blot protocol includes:

• Sample preparation with RIPA buffer containing protease inhibitors

• 20-40 μg protein loading

• Separation on 12-15% SDS-PAGE

• Transfer to PVDF membrane

• Blocking with 5% non-fat milk

• Primary antibody incubation (1:500-1:1000) overnight at 4°C

• Detection with appropriate secondary antibody and ECL system

How can I optimize immunofluorescence experiments with PDCD10 antibodies?

For successful immunofluorescence experiments with PDCD10 antibodies, consider these optimization strategies:

• Fixation method selection:

  • 4% paraformaldehyde (10-15 minutes) generally works well

  • Methanol fixation may be better for certain epitopes

  • Test both methods to determine optimal signal

• Permeabilization optimization:

  • PDCD10 shows nuclear localization in many cell types

  • Sufficient permeabilization is essential (0.1-0.5% Triton X-100)

  • Adjust permeabilization time based on cell type

• Antibody titration:

  • Start with manufacturer's recommended dilution

  • Perform systematic dilution series (1:100 to 1:1000)

  • Monitor signal-to-noise ratio at each concentration

• Signal amplification techniques:

  • Tyramide signal amplification for weak signals

  • Biotin-streptavidin systems for enhanced detection

  • Longer primary antibody incubation (overnight at 4°C)

• Controls and validation:

  • Include PDCD10 knockdown cells as negative controls

  • Use cells with confirmed PDCD10 expression as positive controls

  • Include secondary-only controls to assess background

• Mounting media selection:

  • Use anti-fade mounting media to prevent photobleaching

  • DAPI or Hoechst counterstain helps localize nuclear PDCD10

• Multi-labeling considerations:

  • When co-staining, select antibodies from different host species

  • Test for cross-reactivity between antibodies

  • Sequence staining steps appropriately to minimize interference

PDCD10 has been reported to localize primarily to the nucleus in many cell types, though some cytoplasmic staining has also been observed . This subcellular distribution should be considered when evaluating staining patterns.

What strategies can help resolve conflicting data between PDCD10 antibody immunostaining and gene expression analysis?

When faced with discrepancies between protein detection (immunostaining) and gene expression data for PDCD10, consider these investigative approaches:

• Post-transcriptional regulation analysis:

  • Examine miRNA regulation of PDCD10

  • Investigate protein degradation pathways

  • Assess translational efficiency through polysome profiling

• Technical validation:

  • Confirm antibody specificity through knockout/knockdown controls

  • Validate RNA expression using multiple primer sets

  • Use multiple antibodies targeting different PDCD10 epitopes

• Methodological cross-validation:

  • Compare Western blot results with immunostaining

  • Use in situ hybridization to visualize mRNA localization

  • Correlate with proteomics data when available

• Tissue/cell heterogeneity assessment:

  • Consider cell type-specific expression within heterogeneous tissues

  • Use single-cell technologies when appropriate

  • Microdissect specific regions for targeted analysis

• Experimental conditions examination:

  • Consider treatment conditions that might affect protein vs. mRNA

  • Assess time-course of expression changes

  • Evaluate the impact of cell confluency or cell cycle phase

• Alternative gene products investigation:

  • Examine alternative splicing of PDCD10

  • Assess expression of PDCD10a vs. PDCD10b variants

  • Consider protein modifications that might affect antibody recognition

A systematic analysis using multiple detection methods can help determine whether discrepancies arise from biological phenomena (such as post-transcriptional regulation) or technical artifacts (such as antibody specificity issues).

How are PDCD10 antibodies being used in translational cancer research?

PDCD10 antibodies are becoming increasingly important in translational cancer research through several applications:

• Prognostic biomarker development:

  • PDCD10 expression correlates with prognosis in osteosarcoma patients

  • High expression is associated with poorer five-year survival rates

  • Immunohistochemical analysis using validated antibodies can help stratify patients

• Therapeutic target validation:

  • Antibodies help validate PDCD10 as a potential therapeutic target

  • They facilitate screening of compounds that modulate PDCD10 function

  • They enable target engagement studies for developing therapeutics

• Mechanism-of-action studies:

  • Investigation of how PDCD10 promotes tumor progression through EMT pathway activation

  • Studies on apoptosis inhibition mechanisms in cancer cells

  • Analysis of PDCD10's interaction with other cancer-related proteins

• Companion diagnostics development:

  • PDCD10 antibodies could potentially serve in companion diagnostics

  • Expression levels might predict response to therapies targeting related pathways

  • Combined with other markers for improved predictive power

• Patient-derived xenograft (PDX) characterization:

  • Assessing PDCD10 expression in PDX models

  • Correlating expression with tumor behavior and drug responses

  • Allowing personalized treatment approaches

Research has demonstrated that PDCD10 is highly expressed in 86.84% of osteosarcoma patients, and the five-year mortality rate of PDCD10-positive patients is significantly higher than that of negative patients . This suggests that PDCD10 immunostaining could be a valuable prognostic tool in clinical oncology.

What novel methodologies are being developed for PDCD10 protein analysis?

Several cutting-edge methodologies are advancing our ability to study PDCD10:

• Proximity-based protein interaction mapping:

  • BioID or APEX2 proximity labeling to identify PDCD10 interaction partners

  • Mass spectrometry-based interactome analysis

  • Spatial proteomics for subcellular localization studies

• Advanced imaging techniques:

  • Super-resolution microscopy for detailed localization studies

  • Live-cell imaging with fluorescently tagged PDCD10

  • Correlative light and electron microscopy for ultrastructural studies

• Single-cell protein analysis:

  • Mass cytometry (CyTOF) for single-cell protein expression profiling

  • Imaging mass cytometry for spatial context

  • Single-cell Western blotting technologies

• In situ protein analysis:

  • Multiplex immunofluorescence for co-expression studies

  • Digital spatial profiling for quantitative analysis

  • CODEX (CO-Detection by indEXing) for highly multiplexed imaging

• Functional proteomics approaches:

  • Protein arrays for systematic interaction studies

  • Activity-based protein profiling

  • Thermal proteome profiling to study drug effects on PDCD10

• Structural biology techniques:

  • Cryo-EM studies of PDCD10 complexes

  • Hydrogen-deuterium exchange mass spectrometry for dynamics

  • Cross-linking mass spectrometry for interaction interfaces

These advanced methodologies can complement traditional antibody-based approaches and provide deeper insights into PDCD10 function, particularly in the context of complex diseases like cancer.

What is the potential of PDCD10 as a therapeutic target based on current antibody-based research?

Based on antibody-facilitated research, PDCD10 shows promising potential as a therapeutic target:

• Validated oncogenic functions:

  • PDCD10 promotes proliferation, migration, and invasion in osteosarcoma

  • It activates the EMT pathway and inhibits apoptosis in tumor cells

  • It's associated with poorer prognosis in pancreatic cancer and osteosarcoma

• Therapeutic approaches being investigated:

  • Gene therapy: siRNA or shRNA to knockdown PDCD10 expression

  • Small molecule inhibitors: Targeting PDCD10 protein-protein interactions

  • Biomarker-guided therapy: PDCD10 expression as a predictive marker

• Pathway intervention opportunities:

  • Targeting PDCD10-MST4 interaction

  • Inhibiting PDCD10-mediated ERK pathway activation

  • Preventing PDCD10-induced EMT activation

• Potential clinical applications:

  • PDCD10 inhibition may sensitize cancer cells to conventional therapies

  • PDCD10 knockdown lines are more sensitive to 5-FU and Gemcitabine treatment

  • Combined therapies targeting PDCD10 and related pathways

• Challenges and considerations:

  • Tissue-specific functions may require targeted approaches

  • Safety concerns due to PDCD10's role in normal cellular processes

  • Delivery methods for PDCD10-targeting therapeutics

• Biomarker development:

  • Antibody-based assays to identify patients most likely to benefit

  • Monitoring treatment response through PDCD10 expression changes

  • Combination with other biomarkers for enhanced prediction