Abcam ab172975: A rabbit recombinant monoclonal antibody targeting phosphorylated S608 of human RB1 .
Assay Genie CABP0570: A rabbit polyclonal antibody validated for Western blot (WB) and ELISA .
Cross-reactivity: Primarily human, with some commercial variants (e.g., Biocompare products) reacting with murine and rat samples .
Western blot (WB): Used to detect phosphorylated RB1 in lysates (e.g., Jurkat cells treated with FBS) .
Immunohistochemistry (IHC): Suitable for paraffin-embedded tissues (e.g., melanoma and retina) .
Dysregulation of RB1 phosphorylation is a hallmark of cancers, including retinoblastoma and melanoma .
The antibody aids in studying RB1's role in tumor suppression and resistance to targeted therapies (e.g., in ovarian cancer) .
S608 phosphorylation occurs early in G1 phase, preceding S780 phosphorylation .
Knockdown of Pin1 reduces S780 phosphorylation, underscoring the dependency of RB1 activation on S608/S612 modifications .
Cancer Biology
The antibody is instrumental in:
Diagnostic Potential
While not approved for clinical use, the antibody enables quantitative assessment of RB1 phosphorylation in research settings, aiding biomarker discovery .
Phosphorylation of RB1 at serine 608 is a key regulatory event in the cell cycle. The Retinoblastoma protein functions as a tumor suppressor and negative regulator of the cell cycle. When in its hypophosphorylated state, RB1 binds to E2F family transcription factors, preventing the transcription of E2F-responsive genes necessary for cell cycle progression. Phosphorylation at S608, which depends on CDK4, contributes to the inactivation of RB1's growth-suppressive function, allowing E2F release and subsequent entry into S phase . This phosphorylation event is particularly important in understanding the mechanisms of cancer development and progression, as dysregulation of this process can lead to uncontrolled cell proliferation .
While RB1 contains multiple phosphorylation sites, S608 phosphorylation has distinct functional implications. Unlike phosphorylation at S807/811 which has been more strongly associated with RB1's role in apoptosis and interaction with Bax , S608 phosphorylation appears more specifically involved in cell cycle regulation through E2F binding. Research indicates that various phosphorylation sites work in concert, with S608 being part of a coordinated phosphorylation program. Experimental approaches comparing the effects of phosphorylation-site mutants have revealed that S608 phosphorylation contributes to conformational changes that affect pocket domain interactions with E2F transcription factors .
For optimal Western blotting results with Phospho-RB1 (S608) antibodies:
Sample preparation: Use fresh cell or tissue lysates extracted with phosphatase inhibitors to preserve phosphorylation status.
Dilution ratios: Most Phospho-RB1 (S608) antibodies work optimally at dilutions between 1:500-1:2000 .
Observed molecular weight: Expect to detect bands at approximately 110 kDa .
Positive controls: Jurkat cell lysates are recommended as positive controls .
Blocking: Use 5% BSA in TBST rather than milk (which contains phosphatases).
Detection system: An enhanced chemiluminescence system provides sensitive detection of phosphorylated epitopes.
For recombinant monoclonal antibodies like EPR10849, a dilution of 1:1000 is typically recommended , while polyclonal antibodies may require optimization within the 1:500-1:2000 range .
When performing IHC with Phospho-RB1 (S608) antibodies:
Fixation: Formalin-fixed, paraffin-embedded (FFPE) tissues are commonly used.
Antigen retrieval: Most protocols require heat-induced epitope retrieval (HIER) with citrate buffer (pH 6.0) or EDTA buffer (pH 9.0).
Recommended dilutions: For IHC applications, dilutions typically range from 1:100-1:300 .
Detection systems: Both manual and automated immunostaining systems can be used, as demonstrated in studies utilizing Leica Bond Refine polymer detection systems .
Controls: Include phosphatase-treated sections as negative controls to verify phospho-specificity.
Subcellular localization: Expect predominantly nuclear staining, consistent with RB1's cellular localization .
To validate antibody specificity:
Phosphatase treatment: Treat half of your sample with lambda phosphatase to remove phosphorylation, which should eliminate signal from a truly phospho-specific antibody.
Knockout/knockdown controls: Use RB1-null cell lines or RB1-knockdown samples as negative controls.
Peptide competition assays: Pre-incubate the antibody with phosphorylated and non-phosphorylated peptides; only the phosphorylated peptide should block specific binding.
Immunoprecipitation validation: Perform IP followed by Western blot with another RB1 antibody.
Compare multiple phospho-specific antibodies: Use antibodies from different vendors that recognize the same phosphorylation site.
Induction experiments: Compare samples treated with agents known to induce or reduce S608 phosphorylation (e.g., CDK4/6 inhibitors should reduce signal).
Selection should be based on the specific experimental requirements, with monoclonals like EPR10849 offering high reproducibility for mechanistic studies , while polyclonals might provide advantages in detection sensitivity .
Different phospho-specific RB1 antibodies reveal distinct aspects of RB1 function:
S608 phosphorylation:
S807/811 phosphorylation:
S795 phosphorylation:
Experimental evidence shows that while all these phosphorylation events can be detected in immunoprecipitation studies with Bax, the S807/811 phosphorylation shows the strongest signal, followed by S608 and S795, which require longer exposure times for detection .
Phospho-RB1 (S608) antibodies provide valuable tools for investigating cancer-specific RB pathway alterations:
Alternative mechanism detection: Studies have used phospho-S608 antibodies to identify tumors that inactivate the RB pathway through hyperphosphorylation rather than genetic mutation of RB1 .
Multi-parameter analysis: Combine phospho-S608 detection with other markers:
CDK4/6 expression levels
Cyclin D1 overexpression
p16INK4a status
E2F target gene expression
Tissue microarray analysis: Screen multiple tumor types to identify patterns of RB1 phosphorylation across cancer subtypes. This has been particularly informative in studies of breast, colon, prostate, kidney, and nasopharyngeal cancers .
Treatment response monitoring: Monitor changes in S608 phosphorylation following treatment with CDK inhibitors or other targeted therapies.
Correlation with clinical outcomes: Assess whether S608 phosphorylation status correlates with patient prognosis or treatment response.
Research has shown that phosphorylation of pRb at S608 can be detected in tumors without coding alterations in RB1, suggesting this as an alternative mechanism of RB pathway inactivation in cancer development .
To study the relationship between CDK4 activity and RB1 S608 phosphorylation:
CDK4 inhibition studies:
Treat cells with selective CDK4/6 inhibitors (palbociclib, ribociclib, abemaciclib)
Monitor S608 phosphorylation over time using Western blot
Compare with other phosphorylation sites to determine specificity
Genetic manipulation:
Express wild-type, dominant-negative, or constitutively active CDK4 constructs
Generate CDK4 knockout or knockdown cell lines using CRISPR-Cas9 or RNAi
Assess changes in S608 phosphorylation status
Cell synchronization experiments:
Synchronize cells at different cell cycle phases
Analyze correlation between CDK4 activity and S608 phosphorylation throughout the cell cycle
Use double-labeling with cell cycle markers
In vitro kinase assays:
Purify CDK4/cyclin D complexes
Perform in vitro kinase reactions with recombinant RB1 protein or peptides
Use phospho-specific antibodies to detect site-specific phosphorylation
Phosphoproteomic analysis:
Perform mass spectrometry to quantitatively assess changes in multiple RB1 phosphorylation sites
Compare phosphorylation patterns after CDK4 manipulation
Research has established that phosphorylation of RB1 at S608 specifically depends on CDK4 activity, distinguishing it from other phosphorylation events mediated by different CDKs .
RB1 function is regulated by a complex interplay of post-translational modifications (PTMs):
Phosphorylation crosstalk:
S608 phosphorylation occurs in coordination with other phosphorylation events
The sequential phosphorylation model suggests certain sites must be phosphorylated before others
Evidence indicates CDK3/cyclin-C-mediated phosphorylation at S807/S811 is required for G0-G1 transition, while S608 phosphorylation by CDK4 regulates G1/S transition
Methylation-phosphorylation interaction:
Acetylation effects:
Experimental approaches:
Use site-specific mutants (phosphomimetic or phospho-deficient)
Apply specific kinase or acetyltransferase inhibitors
Employ phosphatase treatments alongside other PTM-specific enzymes
Perform sequential ChIP experiments to determine occupancy of differently modified RB1
Research has shown that these diverse modifications create a complex "RB1 code" that determines its binding partners and functional outcomes in different cellular contexts .
For optimal specificity in detecting endogenous phosphorylation, consider using rabbit-derived antibodies which demonstrate excellent reactivity with human, rat, and monkey samples when used at recommended dilutions .
Comprehensive validation controls include:
Phosphatase controls:
Treat duplicate samples with lambda phosphatase
Compare phosphatase-treated vs. untreated samples by Western blot
Signal should disappear in phosphatase-treated samples
Genetic controls:
Use RB1-null cell lines (e.g., certain SCLC lines)
Compare with RB1-expressing cell lines
No signal should be detected in RB1-null cells
Stimulation/inhibition controls:
Serum-starve cells (reduces phosphorylation)
Treat with CDK4/6 inhibitors (reduces S608 phosphorylation)
Stimulate with growth factors (increases phosphorylation)
Peptide competition:
Pre-incubate antibody with phosphorylated peptide
Pre-incubate with non-phosphorylated peptide
Only phospho-peptide should block specific signal
Multiple antibody validation:
Compare results between different antibody clones/vendors
Use both monoclonal and polyclonal antibodies if possible
Positive control samples:
These controls ensure that observed signals truly represent S608 phosphorylation rather than artifacts or non-specific binding.
Emerging research applications include:
These applications are revealing how dynamic phosphorylation of RB1 at S608 contributes to epigenetic regulation across different cellular contexts.
The phosphorylation status of RB1 at S608 has significant implications for CDK4/6 inhibitor therapy:
Predictive biomarker potential:
S608 phosphorylation levels may predict sensitivity to CDK4/6 inhibitors
Antibody-based detection can be used to stratify patients for clinical trials
Monitoring changes in phosphorylation during treatment may provide early indicators of response
Resistance mechanism identification:
Persistent S608 phosphorylation despite CDK4/6 inhibition suggests alternative kinases are active
This pattern may identify tumors developing resistance to CDK4/6 inhibitors
Combination therapy rationale:
Understanding the relationship between S608 phosphorylation and other signaling pathways can guide rational combination therapies
Targeting multiple pathways affecting RB1 phosphorylation may overcome resistance
Experimental approaches:
Time-course analysis of S608 phosphorylation after CDK4/6 inhibitor treatment
Correlation of phosphorylation status with clinical response
Comparison with other phosphorylation sites to determine site-specific effects
Translation to clinical practice:
Development of IHC-based assays for clinical samples
Standardization of S608 phosphorylation assessment for patient selection
Research on S608 phosphorylation provides mechanistic insights into how CDK4/6 inhibitors exert their effects and may help identify patients most likely to benefit from these targeted therapies.
When selecting Phospho-RB1 (S608) antibodies, consider:
Application-specific validation:
Host species and format:
Clonality considerations:
Epitope specificity:
Review immunogen information
Check sequence alignment with other RB1 phosphorylation sites
Consider antibodies raised against longer vs. shorter peptide sequences
Reactivity with species of interest:
Technical support and validation data:
Evaluate the quality and comprehensiveness of technical documentation
Look for actual experimental images rather than just statements of reactivity
Consider the manufacturer's reputation for antibody validation
Selecting the appropriate antibody based on these criteria ensures more reliable and reproducible experimental results.
Optimizing phospho-flow for RB1 S608 analysis:
Cell fixation and permeabilization:
Test multiple fixation protocols (paraformaldehyde, methanol)
Compare permeabilization agents (saponin, Triton X-100)
Optimize timing to preserve phospho-epitopes while allowing antibody access
Antibody selection and validation:
Test both monoclonal and polyclonal antibodies for flow performance
Verify specificity with phosphatase-treated controls
Titrate antibody concentration for optimal signal-to-noise ratio
Multi-parameter analysis:
Include cell cycle markers (DNA content, Ki-67)
Add surface markers to identify specific cell subpopulations
Consider multiplexing with other phospho-proteins (pCDK4, other pRB sites)
Controls and standardization:
Use phosphatase-treated cells as negative controls
Include cells with known high S608 phosphorylation as positive controls
Implement fluorescence minus one (FMO) controls for accurate gating
Data analysis considerations:
Analyze phosphorylation relative to cell cycle phase
Use appropriate statistical methods for heterogeneous populations
Consider phosphorylation index relative to total RB1 expression
This approach enables quantitative assessment of S608 phosphorylation across different cell subpopulations, providing insights into heterogeneity of RB pathway activation within complex samples.
Emerging applications include:
Liquid biopsy development:
Detection of phosphorylated RB1 in circulating tumor cells
Correlation with disease progression and treatment response
Non-invasive monitoring of RB pathway activation
Single-cell analysis:
Integration with single-cell proteomics
Mapping heterogeneity of RB1 phosphorylation in tumors
Identifying rare cell populations with altered phosphorylation
Therapeutic response prediction:
Development of companion diagnostics for CDK4/6 inhibitors
Standardized IHC assays for clinical decision-making
Integration into multi-biomarker predictive panels
Targeted protein degradation:
Monitoring phosphorylation-dependent degradation of RB1
Assessing effects of novel targeted protein degradation therapeutics
Studying phosphorylation-dependent protein-protein interactions
Spatial biology:
Implementation in multiplexed tissue imaging platforms
Analysis of spatial relationships between phosphorylated RB1 and other markers
Tumor microenvironment effects on RB1 phosphorylation
These forward-looking applications could transform how we understand and target the RB pathway in cancer, moving beyond traditional research applications toward clinically actionable insights.
Future advances may include:
Recombinant antibody engineering:
Development of single-chain variable fragments (scFvs) for improved tissue penetration
Bispecific antibodies targeting both phospho-S608 and total RB1
Engineered antibodies with reduced background and increased specificity
Next-generation detection systems:
Proximity ligation assays for studying S608 phosphorylation in situ
FRET-based biosensors for live-cell imaging of phosphorylation dynamics
Nanobody development for super-resolution microscopy applications
Intracellular antibodies ("intrabodies"):
Development of cell-permeable antibodies for live-cell applications
Real-time monitoring of S608 phosphorylation dynamics
Targeted modulation of phosphorylated RB1 function
Multiparametric analysis tools:
Mass cytometry-compatible antibodies for high-dimensional analysis
Oligonucleotide-conjugated antibodies for spatial transcriptomics integration
Multiplexed imaging antibodies for contextual analysis of RB1 phosphorylation
Computational approaches:
Machine learning algorithms to improve phosphorylation pattern recognition
Integrative analysis of multiple phosphorylation sites
Predictive modeling of phosphorylation dynamics