RPS11 Antibody

What is RPS11 and what is its biological function?

RPS11 (ribosomal protein S11) is a critical component of the small ribosomal subunit involved in ribosome biogenesis. It functions as part of the large ribonucleoprotein complex responsible for protein synthesis in cells . This protein plays an essential role in the translation machinery and has been implicated in various cellular processes beyond protein synthesis. Recent studies have also identified RPS11's potential role in cancer progression, particularly in hepatocellular carcinoma where elevated levels correlate with poor prognosis .

What are the key applications for RPS11 antibody in research?

RPS11 antibody is validated for multiple research applications including Western Blot (WB), Immunohistochemistry (IHC), and ELISA . These applications allow researchers to detect and quantify RPS11 expression in various experimental systems. Western blotting enables protein quantification in cell and tissue lysates, while IHC permits visualization of RPS11 expression patterns in tissue sections, which is particularly useful for cancer research studies. For comprehensive investigations, researchers often employ multiple detection methods to validate findings across different experimental platforms .

What species reactivity can I expect with commercial RPS11 antibodies?

The RPS11 antibody (15942-1-AP) has confirmed reactivity with human, mouse, and rat samples . This cross-species reactivity makes it versatile for comparative studies across different model organisms. The antibody recognizes the RPS11 protein based on an immunogen derived from RPS11 fusion protein (Ag8346). When planning experiments using non-validated species, preliminary testing is recommended to confirm cross-reactivity before proceeding with full-scale experiments.

What are the optimal dilutions for different applications of RPS11 antibody?

The recommended dilution ranges vary by application technique:

In published hepatocellular carcinoma research, scientists have successfully employed RPS11 antibody at 1:1,000 dilution for Western blot and 1:100 for IHC . It is advisable to optimize dilutions for your specific experimental system, as sensitivity may vary depending on sample type, detection method, and expression level of the target protein. Begin with a mid-range dilution and adjust based on signal-to-noise ratio results.

What protocol should I follow for Western blot detection of RPS11?

For Western blot detection of RPS11:

• Harvest cells and lyse using RIPA buffer supplemented with protease inhibitors

• Quantify protein concentration and load 20μg of total protein per well on 10% SDS-PAGE gels

• Transfer proteins to 0.45μm PVDF membranes

• Block membranes with 5% nonfat dry milk

• Incubate with RPS11 primary antibody (1:2000-1:12000 dilution) overnight at 4°C

• Wash and incubate with appropriate HRP-conjugated secondary antibody

• Visualize using enhanced chemiluminescence detection system

The expected molecular weight for RPS11 is 18 kDa, which corresponds to both the calculated (158 aa, 18 kDa) and observed (18 kDa) molecular weights . Include appropriate positive controls (e.g., HEK-293, MDA-MB-453, or ROS1728 cells) where RPS11 expression has been validated .

What is the recommended protocol for IHC staining with RPS11 antibody?

For optimal IHC results with RPS11 antibody:

• Prepare tissue sections and perform antigen retrieval using TE buffer pH 9.0 (alternatively, citrate buffer pH 6.0 may be used)

• Block endogenous peroxidase activity with 3% H₂O₂ solution (15 minutes at room temperature)

• Incubate sections with RPS11 antibody (1:300-1:1200 dilution) overnight at 4°C

• Apply HRP-conjugated secondary antibody for 45 minutes at 37°C

• Develop with DAB solution

• Counterstain nuclei with Harris' Hematoxylin

• Mount and visualize

For assessment, the H-score method has been successfully employed in research studies, which multiplies staining intensity (negative: 0, weak: 1, moderate: 2, strong: 3) by staining extent (0-100%) . This scoring system allows for quantitative comparison across different samples and experimental conditions.

How can I validate RPS11 antibody specificity for my experimental system?

Validating antibody specificity is critical for generating reliable research data. Implement these strategies:

• Positive and negative controls: Include known RPS11-expressing cell lines (HEK-293, MDA-MB-453) as positive controls

• Molecular weight verification: Confirm band appears at the expected 18 kDa position

• Knockdown/knockout validation: Use RPS11 siRNA or CRISPR-edited cells lacking RPS11 expression

• Peptide competition assay: Pre-incubate antibody with immunizing peptide to block specific binding

• Multiple antibody approach: Verify results using antibodies targeting different epitopes

• Multiple detection methods: Cross-validate findings using both WB and IHC techniques

These complementary approaches ensure antibody specificity and increase confidence in experimental results, particularly important when studying proteins with potential isoforms or high homology with related proteins.

What are the key considerations when using RPS11 antibody in cancer research studies?

When investigating RPS11 in cancer contexts, consider these critical factors:

• Expression patterns: RPS11 shows differential expression across cancer types, with elevated levels observed in hepatocellular carcinoma and glioblastoma

• Prognostic significance: High RPS11 expression correlates with poor prognosis in hepatocellular carcinoma patients, associated with elevated AFP, CA19-9, and ALP levels

• Experimental design: Include appropriate cohort stratification based on RPS11 expression levels (e.g., RPS11-high vs. RPS11-low groups)

• Scoring methodology: Utilize quantitative assessment methods (H-score) for consistent evaluation across samples

• Clinical correlation: Analyze relationships between RPS11 expression and clinicopathological features, including tumor differentiation and biomarker levels

• Pathway analysis: Consider integrating single-sample gene-set enrichment analysis (ssGSEA) to investigate biological pathways associated with RPS11 expression

Research has demonstrated significant associations between RPS11 expression and specific clinical parameters in HCC:

These findings suggest potential utility of RPS11 as a biomarker in certain cancer types .

How should I troubleshoot weak or non-specific signal when using RPS11 antibody?

When encountering suboptimal results with RPS11 antibody, systematically address these potential issues:

• Antibody dilution: Adjust concentration based on expression level (try more concentrated antibody for weak signals)

• Antigen retrieval: Compare TE buffer (pH 9.0) versus citrate buffer (pH 6.0) for IHC applications

• Blocking conditions: Optimize blocking reagent (5% BSA vs. 5% milk) and duration

• Incubation parameters: Extend primary antibody incubation time or adjust temperature

• Detection system: Ensure appropriate secondary antibody matching and consider signal amplification methods

• Sample preparation: Verify protein extraction efficiency and integrity through total protein staining

• Background reduction: Increase washing stringency and duration between antibody incubations

Document all optimization steps systematically to establish a reproducible protocol for your specific experimental system.

How should I quantify and interpret RPS11 expression levels in tissue samples?

For rigorous quantification of RPS11 expression:

• IHC scoring: Apply the H-score method, multiplying staining intensity (0-3) by percentage of positive cells (0-100%), yielding scores from 0-300

• Expression categories: Classify samples into negative (0), weak (1-100), moderate (101-150), and strong (151-300) expression groups

• Dichotomization: For statistical analysis, consider grouping samples into RPS11-high (moderate and strong) versus RPS11-low (negative and weak) categories

• Controls: Include appropriate positive and negative controls in each batch

• Blinded assessment: Have multiple pathologists score independently, blinded to clinical data

• Inter-observer validation: Calculate inter-observer agreement metrics to ensure scoring consistency

This standardized approach enables reliable comparison across different studies and experimental conditions, facilitating meta-analysis and data integration .

What is the significance of RPS11 expression in different disease contexts?

Emerging research indicates differential roles of RPS11 across disease contexts:

• Hepatocellular carcinoma: High RPS11 expression associates with elevated AFP levels, poor tumor differentiation, and unfavorable prognosis

• Glioblastoma: Elevated RPS11 levels correlate with poor patient outcomes

• Normal tissue function: As a component of the small ribosomal subunit, RPS11 plays essential roles in protein synthesis

When investigating new disease models, consider both the canonical role of RPS11 in ribosome function and potential non-canonical functions that might contribute to pathogenesis. Correlation with other ribosomal proteins and translation factors can provide insights into whether observed effects relate to global translation changes or specific RPS11 functions.

How can I integrate RPS11 expression data with other molecular markers?

For comprehensive molecular profiling:

• Multi-marker analysis: Examine correlations between RPS11 and established markers (e.g., AFP, CA19-9, ALP in liver cancer)

• Prognostic modeling: Develop nomograms integrating RPS11 with other significant prognostic variables

• Pathway analysis: Perform ssGSEA to identify biological pathways associated with RPS11 expression

• Transcriptome integration: Correlate RPS11 protein levels with mRNA expression profiles

• Decision curve analysis (DCA): Assess the performance of RPS11 in predicting clinical outcomes

• Calibration curves: Evaluate the accuracy of prognostic models incorporating RPS11 expression

This integrated approach can reveal whether RPS11 provides independent prognostic information or functions as part of broader biological processes, enhancing its utility in research and potentially in clinical applications .

What positive and negative controls should I include when working with RPS11 antibody?

Include these controls for rigorous experimental design:

Positive controls:

• Cell lines: HEK-293, MDA-MB-453, and ROS1728 cells have confirmed RPS11 expression

• Tissue samples: Human stomach cancer tissue shows positive IHC staining

• Loading control: Tubulin (1:5,000 dilution) for Western blot normalization

Negative controls:

• Primary antibody omission: Complete staining protocol without primary antibody

• Isotype control: Rabbit IgG at equivalent concentration to test for non-specific binding

• Knockdown/knockout: RPS11-depleted samples to confirm signal specificity

These controls help distinguish specific signal from technical artifacts and enable accurate quantification across experiments.

How do I optimize antigen retrieval for RPS11 IHC staining?

For optimal antigen retrieval in IHC:

• Primary recommendation: Use TE buffer pH 9.0 for RPS11 antibody as suggested by validation data

• Alternative approach: Citrate buffer pH 6.0 can be used if TE buffer yields suboptimal results

• Temperature and time: Heat-induced epitope retrieval at 95-100°C for 15-20 minutes

• Cooling period: Allow slow cooling to room temperature before proceeding

• Comparative analysis: If optimizing, prepare duplicate slides processed with different retrieval methods

• Tissue-specific considerations: Different fixation protocols may require adjusted retrieval parameters

Document all retrieval parameters when reporting methods to ensure reproducibility across different laboratories and experimental setups.

What are the critical parameters for quantitative Western blot analysis of RPS11?

For quantitative Western blot analysis:

• Protein loading: Standardize to 20μg total protein per lane

• Loading controls: Include housekeeping proteins (e.g., Tubulin at 1:5,000 dilution)

• Antibody dilution: Use consistent dilution (starting with 1:2000 for RPS11 antibody)

• Exposure conditions: Capture images within linear detection range

• Multiple biological replicates: Perform at least three independent experiments

• Densitometry: Normalize RPS11 band intensity to loading control

• Statistical analysis: Apply appropriate statistical tests to determine significance of observed differences

This standardized approach ensures reproducible quantification and meaningful comparison of RPS11 expression across different experimental conditions and sample types.

How can RPS11 antibody be used in investigating ribosome biogenesis defects?

For studying ribosome biogenesis:

• Co-immunoprecipitation: Use RPS11 antibody to isolate and identify associated ribosomal and non-ribosomal proteins

• Sucrose gradient fractionation: Analyze RPS11 distribution across ribosomal subunits, monosomes, and polysomes

• Proximity labeling: Combine with BioID or APEX techniques to map the RPS11 interaction network

• Cell stress response: Monitor RPS11 expression and localization under various cellular stresses

• Ribosome assembly kinetics: Track RPS11 incorporation during small subunit biogenesis

• Comparative analysis: Examine potential differences in RPS11 function across normal versus malignant cells

These approaches can provide insights into both canonical ribosomal functions and potential extraribosomal roles of RPS11 in normal physiology and disease contexts.

What are emerging applications of RPS11 as a biomarker in cancer research?

RPS11 shows promise as a cancer biomarker:

• Prognostic stratification: High RPS11 expression is associated with poor prognosis in hepatocellular carcinoma and glioblastoma

• Multiparameter modeling: Integration of RPS11 with other markers improves predictive accuracy

• Therapeutic response prediction: Potential correlation between RPS11 levels and sensitivity to specific treatments

• Early detection: Evaluation of RPS11 as part of multi-marker panels for early cancer detection

• Recurrence monitoring: Assessment of RPS11 expression in surveillance protocols

Results from HCC studies demonstrate:

• Association between high RPS11 expression and elevated AFP, CA19-9, and ALP levels

• Correlation with poor tumor differentiation

• Potential incorporation into nomograms for predicting survival and recurrence

• Integration with decision curve analysis to assess predictive performance

These findings suggest RPS11 may have value beyond its known role in ribosome function, potentially serving as an informative biomarker in certain cancer types.