LRRC19 Antibody

What is LRRC19 and what cellular functions does it regulate?

LRRC19, also known as leucine-rich repeat-containing protein 19, is implicated in several critical cellular processes including signal transduction, protein-protein interactions, and intracellular trafficking. The protein contains distinctive leucine-rich repeat domains that enable specific molecular interactions. Research indicates LRRC19 plays significant roles in immune response regulation, epithelial barrier function, and potentially tumor suppression mechanisms. Understanding these functions provides crucial context for researchers employing LRRC19 antibodies in their experimental designs .

What types of LRRC19 antibodies are available for research?

The primary research tool available is the LRRC19 Polyclonal Antibody (e.g., PACO41094), which is raised in rabbits using recombinant Human Leucine-rich repeat-containing protein 19 protein (amino acids 25-270) as the immunogen. This antibody demonstrates high specificity for human LRRC19 protein. The antibody is typically supplied in liquid form in a storage buffer containing preservatives, glycerol, and PBS (pH 7.4). Protein G purification ensures >95% purity of the antibody preparation, making it suitable for precise detection applications .

What is the expression pattern of LRRC19 across normal and cancer tissues?

LRRC19 shows differential expression across tissue types, with notably lower mRNA expression in colorectal cancer tissues compared to adjacent normal tissues. Database analyses through platforms like TIMER and Oncomine have demonstrated significant downregulation of LRRC19 in multiple cancer types beyond colorectal cancer, including kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and rectum adenocarcinoma (READ). Interestingly, LRRC19 shows elevated expression in some cancers like esophageal carcinoma, suggesting tissue-specific regulatory mechanisms .

What molecular pathways does LRRC19 interact with in cancer progression?

Bioinformatic analyses have revealed that LRRC19 potentially influences several key cancer-related pathways. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) enrichment analyses suggest LRRC19 involvement in retinol metabolism and the zymogen granule membrane. Protein interaction network studies using STRING database and GEPIA validation identify strong associations between LRRC19 and several other proteins including ZCCHC10, MOB3B, IMMP2L, and TRMT11. The connection to retinol metabolism is particularly interesting given that vitamin A derivatives play established roles in regulating cell growth and differentiation, while dysregulation can contribute to carcinogenesis .

What is the role of LRRC19 in immune response regulation?

LRRC19 has been identified as an activator of NF-κB signaling and inducer of proinflammatory cytokine expression. Research indicates LRRC19 functions as a bridge between selenium adjuvant therapy and renal clear cell carcinoma. In gut epithelial tissues, LRRC19 promotes immune cell recruitment and inflammation. This immune modulatory function suggests potential mechanisms through which LRRC19 downregulation might influence the tumor microenvironment and potentially affect immune surveillance of cancer cells. Understanding these immunological aspects may open avenues for combining LRRC19-targeted therapies with immunotherapeutic approaches .

What are the optimal protocols for using LRRC19 antibody in different experimental applications?

LRRC19 antibody applications vary by experimental technique, each with optimized protocols:

For ELISA: Recommended dilution ranges from 1:2000 to 1:10000. The antibody functions effectively in both direct and sandwich ELISA formats, with sensitivity depending on the specific sample type being analyzed.

For Immunohistochemistry (IHC): Optimal dilutions range from 1:20 to 1:200. For formalin-fixed, paraffin-embedded tissue sections, antigen retrieval using citrate buffer (pH 6.0) is recommended prior to antibody incubation. Visualization can be achieved using appropriate detection systems based on horseradish peroxidase or alkaline phosphatase.

For Immunofluorescence (IF): Dilutions between 1:200 and 1:500 typically yield optimal results. Cell fixation with 4% paraformaldehyde followed by permeabilization with 0.1% Triton X-100 generally provides good accessibility to the antigen while preserving cellular structures .

What are the best methods for validating LRRC19 expression in clinical samples?

Validation of LRRC19 expression in clinical samples requires a multi-faceted approach:

Quantitative Real-Time PCR (qRT-PCR): RNA extraction from tissue samples using TRIzol reagent, followed by cDNA synthesis and qPCR analysis has been demonstrated as effective. The following primers have been validated for human LRRC19: forward: 5′-ATGAAAGTCACAGGCATCACAATCC-3′ and reverse: 5′-ATTTTCTTCACATAATTCATGGATA-3′, with GAPDH serving as an internal control (forward: 5′-TCGACAGTCAGCCGCATCTTCTTT-3′ and reverse: 5′-ACCAAATCCGTTGACTCCGACCTT-3′). Expression is typically calculated using the 2^-ΔΔCT method.

Immunohistochemistry: Formalin-fixed, paraffin-embedded tissues sectioned at 4-5 μm thickness, followed by antigen retrieval and incubation with anti-LRRC19 antibody. Visualization at 200x magnification with quantification across multiple fields provides reliable assessment of protein expression patterns and intensity .

How can I optimize Western blot protocols for LRRC19 detection?

For optimal Western blot detection of LRRC19:

• Sample preparation: Lyse cells or tissue samples in RIPA buffer supplemented with protease inhibitors

• Protein loading: 20-50 μg of total protein per lane is typically sufficient

• Gel percentage: 10-12% SDS-PAGE gels provide optimal resolution

• Transfer conditions: Semi-dry transfer at 15V for 30 minutes or wet transfer at 100V for 60 minutes

• Blocking: Use 5% non-fat milk in TBST for 1 hour at room temperature

• Primary antibody: Incubate with LRRC19 antibody at 1:500 to 1:1000 dilution overnight at 4°C

• Secondary antibody: Anti-rabbit HRP-conjugated antibody at 1:5000 dilution for 1 hour at room temperature

• Detection: ECL substrate with appropriate exposure time

The expected molecular weight of LRRC19 is approximately 37-40 kDa, and validation with positive and negative control samples is recommended to confirm specificity .

How should I analyze differential LRRC19 expression between tumor and normal tissues?

Analysis of differential LRRC19 expression requires both bioinformatic and experimental approaches:

Bioinformatic analysis: Utilize publicly available databases such as GEO, Oncomine, and TIMER for preliminary assessment. The GEO2R online analysis tool is effective for screening differentially expressed genes (DEGs) between cancer and adjacent normal tissues. Apply appropriate statistical cutoffs (e.g., |logFC| > 1 and adjusted P < 0.01) to identify significant changes. For comprehensive analysis, examine multiple independent datasets to ensure reproducibility.

Experimental validation: Perform qRT-PCR on paired tumor and normal samples, normalizing to appropriate housekeeping genes. Calculate fold changes using the 2^-ΔΔCT method. Statistical analysis should include paired t-tests or Wilcoxon signed-rank tests depending on data distribution. Immunohistochemistry can provide spatial context to expression differences, especially important for heterogeneous tumors .

What are the recommended approaches for correlating LRRC19 expression with patient survival data?

To establish robust correlations between LRRC19 expression and patient outcomes:

• Database analysis: Utilize specialized survival analysis tools such as GEPIA, PrognoScan, and Kaplan-Meier plotter to examine correlations between LRRC19 expression and patient prognosis across various cancer types.

• Patient stratification: Categorize patients into high and low LRRC19 expression groups based on median expression or more sophisticated cutoff determination methods such as X-tile or receiver operating characteristic curve analysis.

• Statistical methods: Employ Kaplan-Meier survival analysis with log-rank tests to compare survival differences. Cox proportional hazards regression models should be used for multivariate analysis to identify independent prognostic factors.

• Clinical correlation: Analyze associations between LRRC19 expression and clinicopathological features including tumor stage, grade, metastasis status, and response to therapy to provide contextual understanding of expression data .

How can I interpret LRRC19 protein interaction networks in the context of cancer biology?

Protein interaction network analysis for LRRC19 provides crucial insights into its functional role in cancer:

• Network construction: Use databases like STRING to predict functional protein associations, focusing on both direct (physical) and indirect (functional) interactions.

• Validation: Confirm key interactions through experimental methods such as co-immunoprecipitation, proximity ligation assays, or yeast two-hybrid screens.

• Functional enrichment: Perform GO and KEGG pathway analysis on the network to identify biological processes and signaling pathways potentially regulated by LRRC19 and its interactors.

• Hub protein identification: Determine whether LRRC19 functions as a hub protein or peripheral component within specific networks. Current evidence suggests strong associations with ZCCHC10, MOB3B, IMMP2L, and TRMT11.

• Cross-cancer analysis: Compare interaction networks across different cancer types to identify common and tissue-specific mechanisms through which LRRC19 may influence cancer development and progression .

What experimental models are most appropriate for studying LRRC19 function in cancer?

Selection of appropriate experimental models depends on specific research questions:

In vitro models: Human colorectal cancer cell lines with varying endogenous LRRC19 expression levels (e.g., HCT116, HT29, SW480) provide accessible systems for mechanistic studies. CRISPR/Cas9-mediated knockout or overexpression models allow precise manipulation of LRRC19 levels. Three-dimensional organoid cultures derived from patient tumors offer more physiologically relevant systems that maintain tissue architecture and cellular heterogeneity.

In vivo models: Xenograft models using established cell lines or patient-derived tumors with modulated LRRC19 expression in immunocompromised mice enable assessment of tumor growth, metastasis, and response to therapies. Genetically engineered mouse models with tissue-specific LRRC19 alterations would provide valuable insights into its role in tumor initiation and progression in an immunocompetent context .

How might LRRC19 targeting be developed as a therapeutic strategy?

Development of LRRC19-targeted therapies could follow several strategies:

• Expression restoration: For cancers with LRRC19 downregulation, approaches to restore expression might include epigenetic modifiers if the downregulation is due to promoter methylation or histone modifications.

• Pathway modulation: Targeting downstream effectors in LRRC19-regulated pathways, particularly those involved in retinol metabolism or NF-κB signaling, could circumvent the need for direct LRRC19 modulation.

• Biomarker utilization: Even without direct targeting, LRRC19 expression levels could serve as biomarkers for patient stratification, particularly for treatments targeting pathways influenced by LRRC19.

• Immunotherapy combinations: Given LRRC19's role in immune response regulation, exploring combinations of LRRC19-targeted approaches with immunotherapies may yield synergistic effects.

• Diagnostic applications: Development of specific and sensitive detection methods for LRRC19 expression in liquid biopsies could enable non-invasive monitoring of disease progression and treatment response .

What are common issues with LRRC19 antibody applications and how can they be resolved?

Several common challenges and their solutions include:

How can I validate the specificity of LRRC19 antibody for my research?

Comprehensive validation requires multiple approaches:

• Positive and negative controls: Include tissues or cell lines known to express or lack LRRC19 expression.

• Knockout/knockdown validation: Compare staining between wild-type samples and those with LRRC19 genetically knocked out or knocked down.

• Peptide competition assay: Pre-incubation of the antibody with the immunizing peptide should abolish specific staining.

• Multiple antibody comparison: Use different antibodies targeting distinct epitopes of LRRC19 to confirm staining patterns.

• Correlation with mRNA expression: Verify that protein detection correlates with mRNA levels across multiple samples.

• Western blot confirmation: Ensure that the antibody detects a band of the expected molecular weight (approximately 37-40 kDa for LRRC19) .