UPK3A Human

What is UPK3A and where is it primarily expressed in humans?

UPK3A (Uroplakin 3A) is a gene that encodes a protein belonging to the Uroplakin-3 protein family. In humans, the canonical protein has a reported length of 287 amino acid residues and a molecular mass of 30.7 kDa. UPK3A is notably expressed in the ureter and forms a component of the asymmetric unit membrane (AUM), which is a highly specialized biomembrane elaborated by terminally differentiated urothelial cells. The protein is primarily localized in the endoplasmic reticulum (ER) and serves as a marker for characterizing Ureter Urothelium Superficial Cells and Bladder Urothelium Superficial Cells .

What molecular characteristics define the UPK3A protein?

The UPK3A gene encodes a protein with specific structural features that contribute to its function. The UPK3A transcript is approximately 1.7 kb in length and translates into a protein with a molecular weight of 28.9 kD. The protein undergoes post-translational modifications, with glycosylation being a notable modification that affects its functional properties. UPK3A is known to be a component of the asymmetric unit membrane, which is critical for maintaining the integrity and function of urothelial cells. Alternative splicing of the UPK3A gene results in two different isoforms, allowing for functional diversity .

What are the most effective methodologies for detecting UPK3A in human samples?

For detecting UPK3A in human samples, several methodological approaches have proven effective:

• Western Blot (WB): This is one of the most widely used applications for UPK3A antibodies. It allows for quantitative analysis of protein expression levels and can detect specific isoforms.

• Immunohistochemistry (IHC): Particularly useful for tissue samples to visualize the spatial distribution of UPK3A in different cell types and subcellular compartments.

• Immunofluorescence (IF): Enables high-resolution visualization of UPK3A localization within cells.

• ELISA: Useful for quantitative measurement of UPK3A levels in body fluids, particularly relevant for biomarker studies.

• Flow Cytometry (FCM): Allows for quantitative analysis of UPK3A expression at the single-cell level .

What are the key considerations when selecting antibodies for UPK3A research?

When selecting antibodies for UPK3A research, consider the following methodological aspects:

• Antibody Type: Both monoclonal and polyclonal antibodies are available. Monoclonal antibodies offer high specificity but might recognize only one epitope, while polyclonal antibodies can detect multiple epitopes but might have higher background.

• Species Reactivity: Ensure the antibody is reactive to your species of interest. Some antibodies are reactive to human (Hu), mouse (Ms), and rat (Rt) UPK3A, while others may be specific to only one species.

• Application Compatibility: Verify that the antibody has been validated for your specific application (WB, IHC, IF, etc.).

• Recognition of Specific Isoforms: Given that UPK3A has two isoforms due to alternative splicing, ensure the antibody can detect the isoform relevant to your research.

• Clone Selection: For monoclonal antibodies, different clones (e.g., BC17, TGJ-2, 5D9-7E3-2C10) may have different properties and applications .

How is UPK3A expression altered in gastric cancer and what are its clinical implications?

UPK3A exhibits significant alterations in expression in gastric cancer, with crucial clinical implications:

UPK3A is markedly upregulated in gastric cancer tissues compared to normal tissues, as demonstrated by analyses of The Cancer Genome Atlas (TCGA) database. This differential expression pattern suggests a potential role for UPK3A in gastric cancer pathogenesis. Clinically, patients with high UPK3A expression levels showed significantly poorer prognosis compared to those with lower expression. Kaplan-Meier plotter analysis of 1,222 gastric cancer patients (divided into high-expression [n=497] and low-expression [n=698] groups) revealed that UPK3A levels were significantly correlated with patient prognosis (P<0.001) .

These findings indicate that UPK3A may serve as a prognostic biomarker in gastric cancer and potentially represents a therapeutic target for intervention strategies.

What functional roles does UPK3A play in cancer cell behavior?

UPK3A influences multiple aspects of cancer cell behavior, as evidenced by functional studies:

Silencing of UPK3A in gastric cancer cell lines (SNU-216 and HGC-27) significantly inhibited cell proliferation, as measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and colony formation assays. Additionally, UPK3A knockdown substantially reduced cancer cell migration and invasion capabilities, as demonstrated by wound healing and Transwell assays. Mechanistically, UPK3A appears to promote gastric cancer progression by inactivating the p53 pathway, a critical tumor suppressor mechanism .

These functional roles suggest that UPK3A actively contributes to the aggressive behavior of cancer cells, making it a potential target for therapeutic intervention.

How does UPK3A interact with the p53 signaling pathway in cancer progression?

UPK3A exhibits a complex interaction with the p53 signaling pathway that contributes to cancer progression:

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that UPK3A is involved in the p53 signaling pathway. Specifically, UPK3A suppresses the activation of this critical tumor suppressor pathway. Quantitative RT-PCR and Western blot analyses showed that silencing UPK3A significantly upregulated the expression of p53 and other genes involved in p53 signaling (KLF4 and ZMAT3), while simultaneously decreasing the expression of negative p53 regulators (MDM2 and SP1) .

This antagonistic relationship between UPK3A and p53 signaling provides a mechanistic explanation for how UPK3A promotes cancer progression, as the p53 pathway is a key regulator of cell cycle arrest, DNA repair, and apoptosis.

What experimental approaches can be employed to study UPK3A's role in signal transduction?

For comprehensive investigation of UPK3A's role in signal transduction, researchers should consider these methodological approaches:

• Gene Silencing/Knockout Studies: Using siRNA (as demonstrated in gastric cancer studies) or CRISPR-Cas9 technology to silence or knockout UPK3A expression, followed by functional assays to assess effects on downstream signaling.

• Overexpression Systems: Introducing wild-type or mutant UPK3A to examine gain-of-function effects on signaling pathways.

• Co-immunoprecipitation (Co-IP): To identify protein-protein interactions between UPK3A and components of the p53 pathway or other signaling molecules.

• Chromatin Immunoprecipitation (ChIP): To investigate whether UPK3A influences transcription factor binding to regulatory regions of target genes.

• Phosphoproteomics: To identify changes in phosphorylation patterns of signaling proteins upon UPK3A manipulation.

• Reporter Assays: Using luciferase or other reporter systems to quantitatively measure the activity of p53 and other relevant signaling pathways in the presence or absence of UPK3A .

How can researchers effectively design experiments to investigate UPK3A's contribution to cancer cell metabolic reprogramming?

To investigate UPK3A's potential role in cancer cell metabolic reprogramming, researchers should consider these methodological approaches:

• Metabolic Flux Analysis: Use isotope-labeled nutrients (e.g., 13C-glucose, 13C-glutamine) to track metabolic pathways in UPK3A-manipulated cells.

• Seahorse XF Analysis: Measure oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) to assess mitochondrial respiration and glycolysis in cells with altered UPK3A expression.

• Metabolomics Profiling: Conduct untargeted or targeted metabolomics to identify metabolic signatures associated with UPK3A expression levels.

• Expression Analysis of Metabolic Enzymes: Investigate whether UPK3A affects the expression of key metabolic enzymes through qRT-PCR, Western blotting, or proteomics.

• Glucose Uptake and Lactate Production Assays: Measure these parameters as indicators of glycolytic activity in UPK3A-modulated cells.

• Mitochondrial Function Assays: Assess mitochondrial membrane potential, mass, and ROS production in relation to UPK3A expression.

• Integration with Signaling Pathway Analysis: Investigate how UPK3A-mediated changes in the p53 pathway might influence metabolic enzyme expression or activity, given p53's known roles in metabolic regulation .

What strategies can be employed to develop UPK3A as a potential therapeutic target in cancer?

For developing UPK3A as a potential therapeutic target in cancer, researchers should consider these strategic approaches:

• Structure-Based Drug Design: Determine the three-dimensional structure of UPK3A protein to identify potential binding pockets for small molecule inhibitors.

• High-Throughput Screening: Screen chemical libraries to identify compounds that can inhibit UPK3A expression or function.

• Peptide-Based Inhibitors: Design peptides that can disrupt interactions between UPK3A and its binding partners.

• Antibody-Drug Conjugates: Develop antibodies that specifically target UPK3A and are conjugated with cytotoxic agents.

• RNA Interference Therapeutics: Design siRNA or antisense oligonucleotides that can specifically downregulate UPK3A expression.

• PROTAC Technology: Develop proteolysis-targeting chimeras that can selectively degrade UPK3A protein.

• Combinatorial Approaches: Investigate synergistic effects of UPK3A inhibition with standard chemotherapeutics or other targeted therapies.

• Biomarker Development: Establish UPK3A expression as a biomarker for patient stratification and treatment response prediction .

How can researchers address the issue of antibody specificity when studying UPK3A?

Addressing antibody specificity challenges in UPK3A research requires a methodical approach:

• Multi-antibody Validation: Use multiple antibodies targeting different epitopes of UPK3A to confirm results.

• Knockout/Knockdown Controls: Include UPK3A-knockout or knockdown samples as negative controls to verify antibody specificity.

• Peptide Blocking: Preincubate the antibody with the immunizing peptide to confirm that the observed signal is specifically competed away.

• Cross-reactivity Testing: Test the antibody against closely related proteins (e.g., other uroplakin family members) to ensure specificity.

• Isotype Controls: Include appropriate isotype controls in immunohistochemistry and flow cytometry experiments.

• Recombinant Protein Standards: Use purified recombinant UPK3A protein as a positive control and to establish standard curves for quantitative analyses.

• Alternative Detection Methods: Complement antibody-based detection with nucleic acid-based methods (e.g., RT-PCR, RNA-seq) to confirm expression patterns .

What are the key considerations for developing accurate biomarker assays for UPK3A in clinical samples?

Developing accurate UPK3A biomarker assays for clinical applications requires attention to these methodological aspects:

• Sample Collection and Processing: Standardize protocols for sample collection, processing, and storage to minimize pre-analytical variability.

• Assay Platform Selection: Choose appropriate platforms (ELISA, mass spectrometry, immunohistochemistry) based on the sample type, required sensitivity, and throughput.

• Reference Range Establishment: Determine normal reference ranges for UPK3A in relevant populations, accounting for factors like age, sex, and potential confounders.

• Analytical Validation: Assess assay performance parameters including sensitivity, specificity, precision, accuracy, and linearity.

• Clinical Validation: Evaluate the assay's performance in distinguishing disease states, predicting outcomes, or monitoring response to therapy.

• Quality Control: Implement rigorous quality control measures, including positive and negative controls and inter-laboratory comparison.

• Isoform Specificity: Ensure the assay can distinguish between different UPK3A isoforms if they have different clinical implications.

• Interference Testing: Assess potential interferents in clinical samples that might affect assay performance .