TMEM45A Antibody

What is TMEM45A and why is it significant in research?

TMEM45A is a transmembrane protein belonging to the TMEM family, with a canonical length of 275 amino acids and molecular weight of approximately 31.7 kDa in humans. It has several synonyms including DNAPTP4, DNA polymerase-transactivated protein 4, dermal papilla derived protein 7, and DERP7 . TMEM45A is significant in research due to its high expression in keratinocytes and correlation with keratinization, suggesting a crucial role in normal epidermal physiology . Additionally, it has been implicated in cancer progression, particularly in promoting cell proliferation, migration, invasion, and therapy resistance in various cancers including breast, ovarian, and glioblastoma .

What is the subcellular localization of TMEM45A and how does this impact antibody selection?

TMEM45A is primarily localized in cellular membranes, as expected for a transmembrane protein . This subcellular localization has important implications for antibody selection and experimental design. When selecting antibodies for detecting TMEM45A, researchers should consider antibodies raised against epitopes accessible in their experimental conditions. For intact cell applications like immunofluorescence, antibodies targeting extracellular domains may be preferred, while for Western blotting where proteins are denatured, antibodies targeting any domain can be effective .

What is the observed molecular weight of TMEM45A in Western blot and how should discrepancies be addressed?

While the theoretical molecular weight of TMEM45A is 31.7 kDa, Western blot detection often reveals bands at 70-75 kDa . This discrepancy is likely due to post-translational modifications such as glycosylation, which is common for membrane proteins. When validating TMEM45A antibodies, researchers should be aware of this difference and not automatically reject antibodies that detect bands at higher molecular weights. To address discrepancies, consider:

• Running positive and negative controls (overexpression and knockdown samples)

• Checking for tissue-specific isoforms or modifications

• Confirming specificity through additional techniques like immunoprecipitation or mass spectrometry

• Consulting literature for reported molecular weight patterns in specific tissue/cell types

What sample preparation methods are most effective for TMEM45A detection in different applications?

Effective sample preparation is crucial for accurate TMEM45A detection. For membrane proteins like TMEM45A, ensure complete solubilization while preserving epitope integrity .

How does TMEM45A expression correlate with cancer progression and therapy resistance?

TMEM45A has been strongly implicated in cancer progression and therapy resistance across multiple cancer types. Research demonstrates that TMEM45A is upregulated under hypoxic conditions and is closely associated with chemotherapy resistance in liver, breast, head and neck, and kidney cancer cells . High expression of TMEM45A correlates with poor prognosis in patients with breast, bladder, and ovarian cancer .

In breast cancer specifically, TMEM45A has been identified as a potential driver of palbociclib resistance (a CDK4/6 inhibitor used in HR+ breast cancer treatment) . Silencing TMEM45A enhances sensitivity to palbociclib, promotes cell cycle arrest and apoptosis, and inhibits breast cancer cell proliferation, suggesting its potential as a therapeutic target for overcoming drug resistance .

What molecular mechanisms underlie TMEM45A's role in cancer progression?

TMEM45A promotes cancer progression through several molecular mechanisms:

• Cell Cycle Regulation: TMEM45A promotes cell proliferation by favoring the G1/S cell cycle transition in ovarian cancer cells .

• Epithelial-Mesenchymal Transition (EMT): TMEM45A favors EMT in colorectal cancer, enhancing invasive potential .

• Cellular Glycolysis: Research indicates TMEM45A enhances cellular glycolysis, contributing to the metabolic reprogramming characteristic of cancer cells .

• Signaling Pathway Activation: Gene set enrichment analysis (GSEA) confirms that TMEM45A activates the AKT/mTOR signaling pathway, which is integral to cell cycle progression and glycolysis .

• Therapy Resistance: TMEM45A expression correlates with resistance to targeted therapies like palbociclib in breast cancer .

Understanding these mechanisms provides potential points of intervention and biomarker development in cancer research.

What experimental approaches are most effective for studying TMEM45A's role in cancer metabolism?

Based on recent research focusing on TMEM45A's role in cellular glycolysis and cancer metabolism, several experimental approaches are particularly effective:

• Gene Expression Modulation: Using siRNA or shRNA to silence TMEM45A expression, followed by assessment of metabolic parameters and drug sensitivity .

• Metabolic Flux Analysis: Measuring glycolytic rates and mitochondrial respiration in TMEM45A-manipulated cells using techniques like Seahorse XF analysis.

• Expression Correlation Studies: Analyzing the correlation between TMEM45A expression and glycolysis-related proteins through Western blotting and immunohistochemistry .

• Pathway Analysis: Employing Gene Set Enrichment Analysis (GSEA) to identify pathways affected by TMEM45A expression, with particular focus on metabolic pathways like AKT/mTOR .

• In Vivo Models: Testing TMEM45A manipulation in cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models to assess effects on tumor growth and metabolism in physiologically relevant conditions .

How can researchers effectively validate TMEM45A antibody specificity?

Validating antibody specificity is crucial for obtaining reliable research results. For TMEM45A antibodies, a comprehensive validation approach should include:

• Positive and Negative Controls: Testing antibodies on cell lines with known TMEM45A expression levels (e.g., A431, MDA-MB-231, SKOV-3 cells) versus TMEM45A-knockdown samples .

• Multiple Detection Methods: Confirming results across different applications (e.g., WB, IHC, IF) to ensure consistent detection patterns.

• Peptide Competition Assay: Pre-incubating the antibody with immunizing peptide should eliminate specific signals.

• Molecular Weight Verification: While TMEM45A has a theoretical molecular weight of 31.7 kDa, it often appears at 70-75 kDa in Western blots due to post-translational modifications . Researchers should be aware of this expected discrepancy.

• Comparison of Multiple Antibodies: Using antibodies targeting different epitopes of TMEM45A to confirm detection patterns.

What are the potential pitfalls in TMEM45A detection and how can they be mitigated?

Several challenges can arise when detecting TMEM45A:

• Membrane Protein Solubilization: As a transmembrane protein, TMEM45A may be difficult to extract completely. Use detergent-based buffers specifically designed for membrane proteins and avoid excessive heating which can cause aggregation.

• Post-Translational Modifications: Since TMEM45A undergoes post-translational modifications resulting in higher-than-expected molecular weight, use appropriate positive controls to confirm band identity.

• Cross-Reactivity: Some antibodies may cross-react with related TMEM family proteins. Perform specificity tests as described in FAQ 4.1.

• Sample Processing for IHC/IF: Improper fixation or permeabilization can affect epitope accessibility. Optimize these parameters for each antibody and tissue type.

• Expression Level Variations: TMEM45A expression can vary significantly between tissues and under different conditions (e.g., hypoxia increases expression) . Include appropriate controls representative of the experimental conditions.

How can TMEM45A be targeted therapeutically based on recent research findings?

Recent research suggests several promising approaches for targeting TMEM45A therapeutically:

• RNA Interference: siRNA or shRNA targeting TMEM45A has been shown to enhance sensitivity to palbociclib and suppress tumor growth in both in vitro and in vivo models .

• Exosomal Delivery Systems: Engineered exosomes loaded with siRNA targeting TMEM45A present a promising strategy for enhancing CDK4/6 inhibitor sensitivity without observable toxic side effects, as demonstrated in patient-derived xenograft (PDX) models .

• Combination Therapy Approaches: Targeting TMEM45A in combination with existing therapies (such as CDK4/6 inhibitors in breast cancer) may overcome resistance mechanisms .

• Metabolic Targeting: Given TMEM45A's role in cellular glycolysis, combining TMEM45A inhibition with glycolysis inhibitors might provide synergistic effects in cancer treatment.

• Biomarker Development: TMEM45A expression levels could serve as biomarkers for predicting response to certain therapies, particularly CDK4/6 inhibitors in breast cancer .

How should researchers interpret variations in TMEM45A expression across different cell lines and tissues?

TMEM45A expression varies significantly across different cell lines and tissues, which has important implications for research interpretation:

• Tissue-Specific Expression: TMEM45A is highly expressed in keratinocytes and correlates with keratinization, suggesting tissue-specific functions . When comparing expression across different tissues, consider the baseline expression in normal counterparts.

• Cancer-Associated Variations: In cancer research, TMEM45A overexpression has been observed in various cancer types including breast, bladder, and ovarian cancers . Expression levels should be interpreted in the context of cancer type and stage.

• Response to Microenvironmental Conditions: TMEM45A is upregulated under hypoxic conditions . Therefore, experimental conditions including oxygen levels should be standardized and reported.

• Cell Line Variations: Some cell lines consistently express higher levels of TMEM45A, including A431, MDA-MB-231, and SKOV-3 . These can serve as positive controls for antibody validation.

• Quantification Methods: When quantifying TMEM45A expression, use appropriate normalization controls and consider both protein and mRNA levels for comprehensive analysis.

What are the best practices for analyzing TMEM45A in the context of cancer metabolism studies?

When investigating TMEM45A in cancer metabolism research, consider these best practices:

• Integrated Multi-Omics Approach: Combine proteomics, transcriptomics, and metabolomics data to comprehensively understand how TMEM45A affects metabolic pathways.

• Pathway Analysis: Use Gene Set Enrichment Analysis (GSEA) to identify metabolic pathways affected by TMEM45A expression or manipulation .

• Real-Time Metabolic Measurements: Implement real-time measurements of glycolytic rates and mitochondrial respiration using platforms like Seahorse XF Analyzer.

• In Vivo Validation: Confirm in vitro findings using appropriate animal models (CDX or PDX) to account for the complexity of tumor microenvironment .

• Co-Expression Analysis: Analyze the correlation between TMEM45A and glycolysis-related proteins to identify potential functional relationships .

• Therapeutic Response Monitoring: When testing TMEM45A-targeting approaches, monitor both metabolic parameters and therapeutic responses to establish causative relationships.

How can researchers effectively correlate TMEM45A expression with clinical outcomes and therapeutic responses?

To effectively correlate TMEM45A expression with clinical outcomes and therapeutic responses:

• Tissue Microarray Analysis: Use tissue microarrays with clinical follow-up data to analyze TMEM45A expression across large cohorts of patient samples.

• Survival Analysis: Perform Kaplan-Meier survival analysis stratifying patients based on TMEM45A expression levels to determine prognostic significance.

• Multivariate Analysis: Include TMEM45A expression in multivariate models along with established clinical parameters to assess its independent prognostic value.

• Therapy Response Correlation: In treatment studies, correlate baseline TMEM45A expression with response rates to specific therapies, particularly CDK4/6 inhibitors in breast cancer .

• Serial Sampling: When possible, analyze TMEM45A expression in pre-treatment and post-progression samples to assess changes associated with acquired resistance.

• Patient-Derived Models: Establish PDX models from patients with varying TMEM45A expression levels to test therapeutic hypotheses in clinically relevant systems .