COX7A1 Antibody

What is COX7A1 and what is its biological significance?

COX7A1 (cytochrome c oxidase subunit 7A1) is an essential component of the mitochondrial respiratory chain, specifically functioning as a subunit of cytochrome c oxidase. It plays a crucial role in the super-assembly that integrates peripherally into multi-unit heteromeric complexes within the mitochondrial respiratory chain . The gene has several synonyms including COX7A, COX7AH, and COX7AM . As a key component of cellular energy metabolism, COX7A1 has gained significant attention in cancer research due to its implications in tumor cell metabolism and potential therapeutic applications . Understanding COX7A1's function is particularly important because alterations in mitochondrial function are increasingly recognized as critical factors in cancer development and progression.

What are the validated applications for COX7A1 antibodies in research?

COX7A1 antibodies have been validated for multiple research applications, with the most commonly used techniques being Western blotting (WB), immunohistochemistry (IHC), and enzyme-linked immunosorbent assay (ELISA) . In Western blotting, these antibodies enable detection and quantification of COX7A1 protein expression levels in cell and tissue lysates. For immunohistochemistry applications, they allow visualization of COX7A1 distribution in tissue sections, which has been particularly valuable in cancer tissue analysis where COX7A1 staining typically appears as brown granules in the cytoplasm, cell membrane, or nucleus . The staining intensity can be scored from 0 (negative) to 3 (brown staining), and combined with the percentage of positive cells to calculate an H-score ranging from 0 to 3 . ELISA applications provide quantitative measurement of COX7A1 in solution. Researchers should select antibodies based on the specific application requirements and validated reactivity with their species of interest, as many commercial antibodies are validated for human, mouse, and rat samples .

How should researchers evaluate and select the appropriate COX7A1 antibody for their experiments?

When selecting a COX7A1 antibody, researchers should implement a systematic evaluation approach. First, verify the antibody's species reactivity matches your experimental model - available antibodies have been validated for human, mouse, and rat samples . Second, confirm the antibody has been validated for your specific application (WB, IHC, or ELISA) . Third, evaluate published literature where the antibody has been successfully used, particularly noting any limitations reported.

For advanced validation, consider performing comparative analysis with multiple antibodies targeting different epitopes of COX7A1. Additionally, use positive and negative controls in your experimental design - positive controls might include tissues known to express high levels of COX7A1 (such as certain cancer cell lines), while negative controls could include tissues where COX7A1 is knocked down or tissues known to have minimal expression. If possible, verify specificity using immunoprecipitation followed by mass spectrometry. Finally, request detailed technical information from manufacturers regarding the antibody's production method, clonality, and epitope, as these factors significantly influence specificity and reproducibility .

What are the optimal conditions for detecting COX7A1 expression in cancer cells via Western blotting?

For optimal Western blot detection of COX7A1 in cancer cells, researchers should implement a carefully optimized protocol. Cell lysate preparation is critical - use a buffer that effectively extracts mitochondrial proteins (where COX7A1 is primarily located). Based on published methodologies, researchers have successfully detected COX7A1 in non-small cell lung cancer cell lines such as NCI-H838 and NCI-H1703 .

For protein separation, use 12-15% SDS-PAGE gels due to the relatively small size of COX7A1. Transfer conditions should be optimized for small proteins, typically using lower voltage for longer duration to prevent protein loss. For primary antibody incubation, a dilution of 1:50 has been successfully used in immunohistochemistry applications, though Western blot applications may require optimization of this ratio .

For validation and interpretation, always include appropriate loading controls and consider using positive controls from tissues known to express high levels of COX7A1. In experimental studies involving COX7A1 overexpression, verification of successful transfection is essential - published studies have shown approximately 8-fold increases in COX7A1 expression following vector transfection in cancer cell lines . This verification step ensures that subsequent effects on cell proliferation, apoptosis, or autophagy can be confidently attributed to the manipulated COX7A1 levels.

How can researchers effectively overexpress or knock down COX7A1 in cell culture models?

For effective COX7A1 overexpression in cell culture models, vector-based transfection has proven successful in multiple studies. The protocol that has yielded reproducible results involves:

• Amplification of the human COX7A1 coding sequence using PCR with high-fidelity DNA polymerase (such as Phusion® High-Fidelity DNA Polymerase from New England BioLabs)

• Cloning the amplified sequence into a suitable expression vector (pCI vector has been successfully used)

• Transfecting target cells with the constructed vector (2 μg/mL final concentration) using Lipofectamine 3000 according to manufacturer's protocol

• Including appropriate control groups with empty vector transfection

• Harvesting cells for experimentation after 24 hours of transfection

• Verifying overexpression efficiency through Western blot analysis

For COX7A1 knockdown experiments, siRNA or shRNA approaches can be employed, though specific optimization for COX7A1 silencing may be required. CRISPR-Cas9 gene editing provides another approach for generating COX7A1 knockout models for more comprehensive functional studies. When utilizing these models, researchers should carefully assess off-target effects and confirm specificity by rescue experiments where COX7A1 expression is restored to verify the phenotype is directly related to COX7A1 modulation rather than off-target effects .

What protocols yield optimal immunohistochemical detection of COX7A1 in tissue samples?

For optimal immunohistochemical detection of COX7A1 in tissue samples, a detailed protocol based on validated research methodologies includes:

• Sample preparation: For paraffin-embedded tissues, bake slides at 60°C overnight, followed by xylene dewaxing and gradient alcohol hydration

• Antigen retrieval: Use sodium citrate buffer to expose antigenic determinants

• Blocking: Apply hydrogen peroxide to block endogenous peroxidase activity, followed by goat serum blocking solution (approximately 50 μl)

• Primary antibody incubation: Dilute COX7A1 antibody at 1:50 and incubate for 1 hour at 37°C

• Secondary antibody application: After PBS washing, add HRP-labeled polymer (anti-rabbit) for incubation

• Signal development: Prepare DAB solution by mixing solution B and solution C in a 50:1 ratio (1 ml to 20 μl), apply 50-70 μl to each slide, and incubate for 1-3 minutes until tissues show brown staining

• Counterstaining: Soak slides in hematoxylin solution for 1-3 minutes until nuclei appear dark blue, then immediately rinse with tap water

• Mounting and visualization: Seal slides and examine under microscope

For scoring and quantification, evaluate both staining intensity (0-3 scale) and staining area (percentage of positive cells). Calculate the H-score as the product of staining area percentage and intensity score, producing values from 0 to 3. This standardized scoring approach enables objective comparison between samples and has been successfully implemented in studies examining COX7A1 expression in gastric cancer tissues .

How does COX7A1 expression influence cancer cell viability and what mechanisms are involved?

COX7A1 expression significantly impacts cancer cell viability through multiple interconnected pathways. Experimental evidence from lung cancer models indicates that COX7A1 overexpression markedly suppresses cell proliferation and colony formation capability . In NCI-H838 lung cancer cells, COX7A1 overexpression resulted in significantly decreased proliferation index after 48 hours compared to control groups .

Mechanistically, COX7A1 promotes apoptosis in cancer cells by increasing the expression of pro-apoptotic markers including Bax and cleaved Caspase 3. Flow cytometry analysis with Annexin V/PI staining has demonstrated that COX7A1 overexpression increases both early-stage (Annexin V-positive/PI-negative) and late-stage (Annexin V-positive/PI-positive) apoptotic cell populations. These findings have been further validated through TUNEL staining, confirming enhanced apoptotic activity .

Additionally, COX7A1 modulates autophagy, a critical process in cancer cell survival. Overexpression of COX7A1 blocks autophagic flux, resulting in autophagosome accumulation. This autophagy inhibition occurs through the downregulation of PGC-1α and upregulation of NOX2. Importantly, subsequent experiments have established that COX7A1's suppressive effect on cancer cell viability is partially dependent on this autophagy inhibition . This multifaceted impact on cell proliferation, apoptosis, and autophagy positions COX7A1 as a potential therapeutic target in cancer treatment strategies.

What is the relationship between COX7A1 expression and immune cell infiltration in tumors?

COX7A1 expression demonstrates significant correlations with immune cell infiltration patterns in tumors, suggesting an important role in shaping the tumor immune microenvironment. Analysis across multiple datasets including TCGA, GSE84437, GSE66229, and GSE26253 reveals consistent patterns of association between COX7A1 expression and specific immune cell populations .

COX7A1 expression shows a negative correlation with activated memory CD4+ T cells and a positive correlation with resting memory CD4+ T cells and resting mast cells . This shift in T cell activation status may contribute to reduced anti-tumor immunity in high COX7A1-expressing tumors. Additionally, COX7A1 expression negatively correlates with M1 macrophages (p = 0.006) while positively correlating with M2 macrophages . This macrophage polarization pattern is particularly significant as M1 macrophages typically exhibit anti-tumor properties while M2 macrophages are associated with immunosuppression and tumor promotion.

Further computational analysis using the ESTIMATE algorithm indicates that patients with high COX7A1 expression demonstrate higher Immune Score and Stromal Score, which paradoxically associates with poor prognosis . This suggests that while immune infiltration is increased, the composition of these immune cells likely creates an immunosuppressive rather than anti-tumor environment. Single-cell analysis has also revealed positive correlations between COX7A1 expression and fibroblasts and endothelial cells, further indicating its relationship with the broader tumor microenvironment beyond immune cells .

How can COX7A1 be utilized as a prognostic biomarker in cancer immunotherapy?

COX7A1 shows promising potential as a prognostic biomarker for cancer immunotherapy, particularly in gastric cancer patients. Research has identified COX7A1 as a key component in a gene model constructed to predict clinical efficacy of immunotherapy and patient prognosis . This model was developed through a sophisticated multi-step approach involving differential expression analysis in immunotherapy cohorts, Cox regression analysis to classify genes into protective and risky categories, and application of the Single Sample Gene Set Enrichment Analysis (ssGSEA) algorithm to score gene sets .

For clinical implementation, COX7A1 expression levels can be assessed in tumor samples using immunohistochemistry with appropriate antibodies diluted at 1:50 . The developed scoring system evaluates both staining intensity (0-3) and area (percentage of positive cells) to calculate an H-score. Higher COX7A1 expression correlates with specific immune cell infiltration patterns that predict poorer response to immunotherapy .

The relationship between COX7A1 expression and drug sensitivity has also been explored, providing additional data to refine patient selection for immunotherapy. To implement COX7A1 as a prognostic biomarker, researchers should consider integrating its expression analysis with other established biomarkers and clinical parameters. Multivariate analyses incorporating these factors can enhance predictive accuracy compared to using COX7A1 expression alone .

What technical challenges exist in studying the crosstalk between COX7A1, PGC-1α, and NOX2?

Investigating the molecular crosstalk between COX7A1, PGC-1α, and NOX2 presents several technical challenges that researchers must address. The primary difficulty lies in establishing causality and directionality in this regulatory network. While research has demonstrated that COX7A1 overexpression results in downregulation of PGC-1α and upregulation of NOX2 , the molecular mechanisms mediating these effects remain incompletely characterized.

To address these challenges, researchers should consider implementing time-course experiments following COX7A1 manipulation to determine the temporal sequence of changes in PGC-1α and NOX2 expression. Additionally, chromatin immunoprecipitation (ChIP) assays may help identify whether COX7A1 directly or indirectly regulates the transcription of these genes. Co-immunoprecipitation experiments could reveal potential protein-protein interactions within this network.

Another significant challenge is the difficulty in simultaneously visualizing these proteins in cellular compartments using immunofluorescence, as they may localize to different cellular structures. Advanced imaging techniques such as proximity ligation assay (PLA) can help detect protein interactions within 40 nm distance. For functional validation, researchers should design rescue experiments where PGC-1α is overexpressed or NOX2 is inhibited in COX7A1-overexpressing cells to determine if these interventions can reverse the phenotypic effects on autophagy and cell viability . This comprehensive approach would provide deeper insights into the mechanistic relationships between these proteins.

How can single-cell techniques enhance our understanding of COX7A1 function in heterogeneous tumor tissues?

Single-cell techniques offer powerful approaches to resolve the heterogeneous expression and function of COX7A1 within complex tumor tissues. Single-cell RNA sequencing (scRNA-seq) can reveal cell type-specific expression patterns of COX7A1 across different tumor compartments, allowing researchers to identify which specific cell populations express COX7A1 and how this expression correlates with cell states and functions.

Existing data already indicates that COX7A1 expression correlates with specific stromal cell populations, including fibroblasts and endothelial cells . Single-cell techniques can further refine this understanding by identifying distinct fibroblast subpopulations and their association with COX7A1 expression. Similarly, these techniques can reveal how COX7A1 expression varies across immune cell subsets within the tumor microenvironment.

For implementation, researchers should consider applying spatial transcriptomics approaches such as Visium or MERFISH to map COX7A1 expression within the physical context of the tumor microenvironment. This would allow visualization of how COX7A1-expressing cells spatially relate to different immune cell populations, potentially explaining the observed correlations with various immune cell types . Additionally, single-cell proteomics techniques like CyTOF (mass cytometry) or CODEX could be employed to simultaneously measure COX7A1 protein levels alongside markers of cell state, signaling pathway activation, and functional characteristics at single-cell resolution.

What emerging therapeutic strategies target COX7A1 or its related pathways in cancer treatment?

Emerging therapeutic strategies targeting COX7A1 or its related pathways represent a promising frontier in cancer treatment. Based on COX7A1's demonstrated ability to suppress cell proliferation and promote apoptosis in lung cancer models , several therapeutic approaches are being explored.

One strategy involves inducing COX7A1 overexpression in tumors through viral vector delivery systems or other gene therapy approaches. Vector-based systems similar to those used in experimental settings (pCI vectors with COX7A1) could potentially be adapted for therapeutic applications. The dual effect of COX7A1 on both promoting apoptosis through increased Bax and cleaved Caspase 3 expression and inhibiting protective autophagy makes it an attractive target for combination therapies.

Another approach focuses on targeting the downstream pathways affected by COX7A1. Since COX7A1 overexpression downregulates PGC-1α and upregulates NOX2 , drugs that mimic these effects could potentially replicate the anti-cancer properties of COX7A1. NOX2 inhibitors are being investigated for various applications and could be repurposed or modified for this context.

Additionally, since COX7A1 expression correlates with immune cell infiltration patterns , combining COX7A1-targeted therapies with immunotherapy approaches could potentially enhance treatment efficacy. Specifically, strategies to reverse the M2 macrophage polarization associated with high COX7A1 expression could complement COX7A1-targeting approaches. Further research is needed to determine optimal dosing, delivery methods, and potential combination therapies to maximize therapeutic efficacy while minimizing off-target effects.

What cell culture systems are most appropriate for studying COX7A1 function in cancer models?

For studying COX7A1 function in cancer models, selecting appropriate cell culture systems is critical for generating reliable and translatable results. Based on published research, human non-small cell lung cancer cell lines NCI-H838 and NCI-H1703 have been successfully used to investigate COX7A1 function . These cells should be maintained in RPMI-1640 medium supplemented with 10% Fetal Bovine Serum, 100 U/mL penicillin, and 0.1 g/mL streptomycin in a humidified 37°C incubator with 5% CO₂ .

For gastric cancer studies, cell lines used in the GSE84437, GSE66229, and GSE26253 datasets provide validated models for COX7A1 research . When designing experiments, researchers should consider establishing paired cell lines with stable COX7A1 overexpression or knockdown to enable robust comparative studies. The pCI vector system has been validated for COX7A1 overexpression studies with a final concentration of 2 μg/mL and Lipofectamine 3000 as the transfection reagent .

To enhance translational relevance, three-dimensional organoid cultures derived from patient samples can provide more physiologically relevant models than traditional two-dimensional cultures. These organoids better recapitulate the cellular heterogeneity and tissue architecture of primary tumors. Additionally, co-culture systems incorporating cancer cells with stromal and immune components allow investigation of COX7A1's role in cellular interactions within the tumor microenvironment, particularly relevant given COX7A1's correlation with various immune cell populations .

How should researchers design experiments to investigate COX7A1's impact on autophagy in cancer cells?

When investigating COX7A1's impact on autophagy in cancer cells, researchers should implement a comprehensive experimental design that addresses both autophagy flux and mechanisms. Based on published methodologies, the following approach is recommended:

• Establish appropriate cell models with COX7A1 overexpression using validated vector transfection methods (pCI-COX7A1, 2 μg/mL)

• Verify COX7A1 expression levels via Western blot analysis before proceeding with autophagy studies

• Assess autophagy markers through multiple complementary techniques:

  • Western blot analysis of key autophagy proteins including p62 (which accumulates when autophagy is inhibited) and LC3-II (which increases during autophagosome formation)

  • Implement the tandem mRFP-GFP-LC3 reporter assay to differentiate between autophagosome formation and autolysosomal degradation (GFP signal quenches in acidic autolysosomes while mRFP remains stable)

• Include appropriate controls for autophagy studies:

  • Starvation conditions (EBSS medium) as a positive control for autophagy induction

  • Chloroquine or bafilomycin A1 treatment as autophagy flux inhibitor controls

• Investigate molecular mechanisms by analyzing:

  • Expression levels of PGC-1α and NOX2, which have been implicated in COX7A1's regulation of autophagy

  • Consider implementing siRNA knockdown of PGC-1α or NOX2 to determine if they are necessary for COX7A1's effects on autophagy

For validation, perform rescue experiments where autophagy is pharmacologically induced (e.g., with rapamycin) in COX7A1-overexpressing cells to determine if restoration of autophagy reverses the phenotypic effects on cell viability and apoptosis . Time-course experiments are also valuable to determine the temporal relationship between COX7A1 expression changes and autophagy modulation.

What quantitative techniques provide the most reliable assessment of COX7A1's effects on apoptosis?

• Western blot analysis of apoptotic markers: Quantify expression levels of pro-apoptotic proteins including Bax and cleaved Caspase 3, which have demonstrated increased expression following COX7A1 overexpression . Include anti-apoptotic markers such as Bcl-2 for a more comprehensive assessment of apoptotic balance.

• Flow cytometry with Annexin V/PI staining: This technique allows quantification of both early-stage apoptotic cells (Annexin V-positive/PI-negative) and late-stage apoptotic cells (Annexin V-positive/PI-positive) . For robust analysis, collect at least 10,000 events per sample and include appropriate controls including unstained, single-stained, and positive control (staurosporine-treated) samples.

• TUNEL staining: This method detects DNA fragmentation characteristic of apoptotic cells and provides visualization of apoptotic cells in situ . For quantification, analyze multiple fields per sample and determine the percentage of TUNEL-positive cells.

• Caspase activity assays: Measure the enzymatic activity of executioner caspases (caspase-3/7) using luminescent or fluorescent substrates, which provides a quantitative measure of apoptotic pathway activation.

For all techniques, time-course experiments should be conducted (24, 48, and 72 hours post-COX7A1 manipulation) to capture the dynamics of apoptotic response. Statistical analysis should include appropriate tests (typically ANOVA with post-hoc comparisons) with biological replicates (minimum n=3) to ensure reliability. When reporting results, provide both representative images and quantitative data with statistical significance indicators .