LRRC41 Antibody

What is LRRC41 and where is it commonly expressed?

LRRC41 (also known as MUF1, PP7759, and Protein Muf1) is a leucine-rich repeat containing protein encoded on chromosome 1, which is the largest human chromosome spanning approximately 260 million base pairs and constituting 8% of the human genome. LRRC41 is expressed across multiple species including humans, mice, and rats. Research has identified its expression in various tissues, with notable implications in hepatocellular carcinoma pathology. The protein's structure contains characteristic leucine-rich repeat domains that facilitate protein-protein interactions and potentially contribute to its functional role in cellular processes .

What are the available types of LRRC41 antibodies for research?

The primary LRRC41 antibodies available for research include rabbit polyclonal antibodies that recognize LRRC41 across multiple species (human, mouse, and rat). These antibodies are typically unconjugated and purified using antigen affinity chromatography. They are validated for applications including Western Blot (WB) and Immunohistochemistry on paraffin-embedded tissues (IHC-P). The antibodies target specific epitopes of the LRRC41 protein and are typically provided in liquid form with storage buffers containing PBS with glycerol and sodium azide . Unlike some other targets, monoclonal antibodies for LRRC41 are less commonly referenced in the current literature.

How is LRRC41 associated with disease pathology?

LRRC41 has been implicated in hepatocellular carcinoma (HCC) progression through recent research. Overexpression of LRRC41 is associated with HCC progression and correlates with poor prognosis. Analysis using EPIC immune scoring has revealed a negative correlation between LRRC41 and several immune cell types including macrophages, endothelial cells, and CD8T cells, suggesting potential immune evasion mechanisms. Furthermore, there is evidence of a positive correlation between LRRC41 and microsatellite instability (MSI) in HCC. These associations indicate that LRRC41 may contribute to tumor progression by influencing both cellular proliferation pathways and the tumor immune microenvironment .

How should researchers validate LRRC41 antibodies before experimental use?

Researchers should implement multiple validation strategies to ensure LRRC41 antibody specificity and performance. A comprehensive approach includes:

• Orthogonal Validation: Cross-reference antibody-based results with data from non-antibody methods, such as RNA expression profiles from resources like the Human Protein Atlas. This allows verification of antibody specificity by comparing protein expression patterns with corresponding RNA expression levels .

• Binary Validation: Test the antibody in systems with known positive and negative expression of LRRC41, such as:

  • Cell lines with established high and low expression

  • Genetic knockouts if available

  • Induced/inhibited expression models

• Application-Specific Validation: Validate the antibody separately for each intended application (Western blot, IHC, IF) as preparation methods affect epitope presentation differently .

• Multiple Antibody Approach: When possible, confirm results using different antibodies against distinct LRRC41 epitopes to reduce epitope-specific artifacts.

A successful validation approach would show concordance between antibody-based detection and RNA-seq or proteomics data patterns across multiple cell lines or tissues .

What are the optimal conditions for Western blot detection of LRRC41?

For optimal Western blot detection of LRRC41, researchers should consider the following protocol:

• Sample Preparation:

  • Use RIPA buffer with protease inhibitors for protein extraction

  • Heat samples at 95°C for 5 minutes in reducing Laemmli buffer

• Electrophoresis and Transfer:

  • Resolve proteins on 10% SDS-PAGE gels (LRRC41 has a molecular weight of approximately 68 kDa)

  • Use semi-dry or wet transfer systems with PVDF membrane (0.45 μm pore size)

• Antibody Incubation:

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

  • Incubate with anti-LRRC41 antibody (typically at 1:1000 dilution) overnight at 4°C

  • Wash 3-5 times with TBST

  • Incubate with HRP-conjugated secondary antibody (typically 1:5000) for 1 hour at room temperature

• Optimization Considerations:

  • Validate using cell lines with known high and low LRRC41 expression

  • Include positive and negative controls for band verification

  • Consider fresh versus frozen samples for optimal protein preservation

Expected results should show a specific band at approximately 68 kDa, with intensity varying by cell type according to expression levels predicted by RNA data.

How can researchers effectively use LRRC41 antibodies in immunohistochemistry?

For effective immunohistochemistry (IHC) detection of LRRC41, researchers should follow these methodological guidelines:

• Tissue Preparation:

  • Fix tissues in 10% neutral buffered formalin for 24-48 hours

  • Process and embed in paraffin following standard protocols

  • Section at 4-5 μm thickness on charged slides

• Antigen Retrieval:

  • Heat-induced epitope retrieval using citrate buffer (pH 6.0) for 20 minutes

  • Allow slides to cool to room temperature gradually

• Staining Protocol:

  • Block endogenous peroxidase with 3% H₂O₂ in methanol

  • Block non-specific binding with 5% normal serum

  • Incubate with anti-LRRC41 primary antibody (typically 1:100-1:200 dilution) overnight at 4°C

  • Apply HRP-conjugated secondary antibody followed by DAB chromogen

• Validation Controls:

  • Include positive control tissues with known LRRC41 expression

  • Include negative controls by omitting primary antibody

  • Consider parallel RNA in situ hybridization for orthogonal validation

• Interpretation Guidelines:

  • Assess subcellular localization (expected to be primarily cytoplasmic and/or nuclear)

  • Evaluate staining intensity across different cell types within the tissue

  • Compare expression patterns with RNA-seq data from similar tissues

This approach ensures reliable detection of LRRC41 in tissue sections while controlling for potential artifacts.

How can LRRC41 expression be correlated with immune infiltration in tumor microenvironment?

To correlate LRRC41 expression with immune infiltration in tumor microenvironments:

• Integrated Analytical Approach:

  • Perform multiplex immunohistochemistry or immunofluorescence with antibodies targeting LRRC41 and immune markers (CD8, CD68, etc.)

  • Conduct RNA-seq analysis on tumor samples and apply computational deconvolution algorithms like EPIC

  • Analyze flow cytometry data of dissociated tumor tissues for immune populations

• Computational Methods:

  • Use the "ssGSEA" method through R software GSVA package to analyze enrichment of immune-related gene sets

  • Calculate Spearman's correlation between LRRC41 expression and immune cell signature scores

  • Generate heatmaps showing relationships between LRRC41 expression and immune cell populations

• Validation Strategy:

  • Cross-reference findings with public datasets like TCGA

  • Confirm correlations through in vitro co-culture experiments

  • Validate with spatial transcriptomics or imaging mass cytometry for spatial relationships

Research has demonstrated a negative correlation between LRRC41 expression and several immune cell types including macrophages, endothelial cells, and CD8T cells in HCC, suggesting potential immune evasion mechanisms associated with LRRC41 upregulation .

What approaches can be used to investigate the role of LRRC41 in cancer progression?

To investigate LRRC41's role in cancer progression, researchers should employ these integrated approaches:

• Functional Studies:

  • CRISPR/Cas9-mediated knockout or knockdown of LRRC41 in cancer cell lines

  • Overexpression studies using lentiviral or plasmid-based systems

  • Assessment of proliferation, migration, invasion, and colony formation

  • In vivo xenograft models with modulated LRRC41 expression

• Molecular Mechanism Exploration:

  • Immunoprecipitation followed by mass spectrometry to identify LRRC41 binding partners

  • ChIP-seq to identify potential transcriptional regulatory functions

  • RNA-seq to determine transcriptome changes upon LRRC41 modulation

  • Pathway analysis using GSVA to identify affected signaling networks

• Clinical Correlation:

  • Analysis of LRRC41 expression in patient samples using tissue microarrays

  • Kaplan-Meier survival analysis stratified by LRRC41 expression levels

  • Multivariate Cox regression analysis to determine independent prognostic value

  • Correlation with established cancer biomarkers and staging

How can researchers explore LRRC41 as a potential therapeutic target?

To explore LRRC41 as a therapeutic target, researchers should utilize these methodical approaches:

• Target Validation Strategies:

  • Confirm overexpression in disease state compared to normal tissues

  • Demonstrate phenotypic reversal upon target inhibition

  • Establish mechanism of action through pathway analysis

  • Validate in multiple model systems and patient-derived samples

• Drug Discovery Approaches:

  • Molecular docking studies with existing drug libraries

  • High-throughput screening assays for small molecule inhibitors

  • PROTAC (Proteolysis Targeting Chimera) design for targeted degradation

  • Develop antibody-drug conjugates targeting LRRC41

• Therapeutic Assessment Methods:

  • Evaluate drug sensitivity correlations with LRRC41 expression

  • Conduct molecular docking simulations with potential therapeutic compounds

  • Test combinations with established therapeutic agents

  • Assess off-target effects through proteomics approaches

Current research has identified promising therapeutic compounds targeting LRRC41, including AZD-5363 (an Akt inhibitor) and temsirolimus (an mTOR inhibitor), which demonstrated favorable binding through molecular docking simulations. Additionally, FDA-approved drugs such as oxiglutathione, thymopentin, deferoxamine mesylate, dermorphin, and ritonavir have shown potential as LRRC41 inhibitors based on molecular docking studies .

How should researchers address non-specific binding when using LRRC41 antibodies?

When encountering non-specific binding with LRRC41 antibodies, researchers should systematically address the issue:

• Identifying Non-Specific Binding Problems:

  • Multiple unexpected bands in Western blot

  • Diffuse staining in unexpected cellular compartments in IHC/IF

  • Positive staining in known negative control samples

  • Inconsistency between antibody results and orthogonal data

• Optimization Strategies:

  • Blocking Optimization: Test different blocking agents (BSA, casein, normal serum) and increase blocking time

  • Antibody Dilution Series: Perform titration experiments to determine optimal concentration

  • Buffer Modifications: Adjust salt concentration and detergent levels in wash and antibody diluent buffers

  • Incubation Conditions: Test different temperatures and durations for primary antibody incubation

• Validation Approaches:

  • Peptide Competition: Pre-incubate antibody with immunizing peptide to confirm specificity

  • Binary Models: Test in systems with confirmed positive and negative LRRC41 expression

  • Multiple Antibody Verification: Compare results with alternative antibodies targeting different epitopes

  • Orthogonal Validation: Cross-reference with RNA expression or mass spectrometry data

Implementation of these strategies ensures reliable detection of LRRC41 while minimizing artifacts that could lead to misinterpretation of experimental results.

How can researchers reconcile discrepancies between antibody-based detection and RNA expression data for LRRC41?

When facing discrepancies between protein detection via antibodies and RNA expression data for LRRC41, researchers should:

• Systematic Evaluation of Potential Causes:

  • Post-transcriptional Regulation: Assess microRNA targeting LRRC41 mRNA

  • Protein Stability: Investigate proteasomal degradation using inhibitors like MG132

  • Protein Modifications: Examine phosphorylation or ubiquitination affecting epitope recognition

  • Technical Limitations: Consider sensitivity differences between methods

• Experimental Verification Approaches:

  • Time-course Studies: Analyze both RNA and protein over time to detect temporal discrepancies

  • Subcellular Fractionation: Determine if protein localization affects detection

  • Alternative Detection Methods: Employ mass spectrometry for antibody-independent protein quantification

  • Transcript Isoform Analysis: Investigate alternative splicing affecting antibody epitopes

• Interpretation Framework:

  • Establish whether discrepancies follow a pattern across different samples

  • Consider biological context (cell type, disease state) that might explain differences

  • Evaluate whether differences are quantitative (levels) or qualitative (presence/absence)

  • Document conditions where concordance is observed versus discordant

What quality control measures should be implemented when analyzing LRRC41 expression in patient samples?

For reliable analysis of LRRC41 expression in patient samples, implement these quality control measures:

• Pre-analytical Quality Control:

  • Standardize sample collection protocols (time, preservation method)

  • Document ischemic time for surgical specimens

  • Employ consistent fixation duration and reagents

  • Maintain detailed records of storage conditions and duration

• Analytical Quality Controls:

  • Internal Controls: Include known positive and negative tissues on each slide/run

  • Batch Controls: Run standard samples across different batches to assess inter-batch variability

  • Technical Replicates: Perform duplicate or triplicate analyses when feasible

  • Orthogonal Validation: Confirm key findings with alternative methods (e.g., RNA-seq, proteomics)

• Interpretive Quality Controls:

  • Blinded Assessment: Have multiple observers score samples independently

  • Automated Analysis: Implement digital pathology algorithms to reduce subjectivity

  • Calibration Samples: Use samples with established LRRC41 levels as reference points

  • Statistical Validation: Apply appropriate statistical methods to assess reliability

• Documentation Standards:

  • Record detailed antibody information (clone, lot, dilution)

  • Document all protocol deviations

  • Maintain comprehensive metadata for each sample

  • Establish clear criteria for interpretable versus non-interpretable results

These measures ensure that variations in LRRC41 expression reflect true biological differences rather than technical artifacts, enhancing the reliability of clinical correlations.

How does LRRC41 interact with signaling pathways in cancer progression?

Recent research suggests complex interactions between LRRC41 and key signaling pathways in cancer:

Understanding these pathway interactions will be crucial for developing effective targeted therapies against LRRC41 in cancer treatment.

What are the emerging therapeutic strategies targeting LRRC41 in cancer?

Emerging therapeutic strategies targeting LRRC41 in cancer include:

These emerging therapeutic strategies represent promising directions for targeting LRRC41 in cancer treatment, particularly for hepatocellular carcinoma.

How can LRRC41 serve as a prognostic biomarker in cancer?

LRRC41 shows significant potential as a prognostic biomarker in cancer, particularly hepatocellular carcinoma:

The evidence suggests that LRRC41 overexpression promotes clinicopathological progression in HCC patients, leading to poorer prognosis, making it a valuable biomarker for risk stratification and treatment planning.