SLC7A1 Antibody, HRP conjugated

What is SLC7A1 and why is it significant in research?

SLC7A1 (Solute Carrier Family 7 Member 1) is a high-affinity, low capacity permease involved in the transport of cationic amino acids including arginine, lysine, and ornithine in non-hepatic tissues. It may also function as an ecotropic retroviral leukemia receptor . The significance of SLC7A1 in research stems from its overexpression in several cancers, particularly ovarian cancer, where it has been associated with poorer survival outcomes and plays a role in tumor progression through amino acid metabolism reprogramming . Recent studies have established SLC7A1 as a biomarker for predicting epithelial ovarian cancer (EOC) progression and cisplatin resistance, making it a promising therapeutic target .

What are the primary applications of SLC7A1 Antibody, HRP conjugated?

SLC7A1 Antibody, HRP conjugated is primarily utilized in research settings for the detection and quantification of SLC7A1 protein. The most common applications include:

• ELISA (Enzyme-Linked Immunosorbent Assay): The antibody can be used at dilutions of 1:500-1:1000 for ELISA applications, allowing for quantitative detection of SLC7A1 in various sample types .

• Western Blot: SLC7A1 antibody can be used for detection by western blot at 0.5 μg/mL concentration, with HRP conjugated secondary antibody diluted 1:50,000-100,000 when using non-conjugated primary antibodies .

• Immunohistochemistry (IHC): Used to visualize and score SLC7A1 expression in tissue samples, as demonstrated in studies examining SLC7A1 expression in ovarian cancer tissues .

How should SLC7A1 Antibody, HRP conjugated be stored and handled?

For optimal performance and longevity, SLC7A1 Antibody, HRP conjugated should be:

• Stored at -20°C or below after reconstitution.

• Aliquoted to avoid multiple freeze-thaw cycles, which can degrade antibody performance .

• Reconstituted properly - if lyophilized, add the recommended volume of distilled water to reach the final antibody concentration (typically 1 mg/mL) .

• Protected from prolonged exposure to light and heat, which can degrade the HRP conjugate.

• Handled according to the manufacturer's specific instructions, as storage conditions may vary slightly between different commercial preparations .

How does SLC7A1 expression correlate with immune cell infiltration in the tumor microenvironment?

Analysis of SLC7A1 expression in relation to the tumor immune microenvironment has revealed significant correlations that may impact cancer progression and treatment response. According to TIMER database analysis, SLC7A1 overexpression in ovarian cancer demonstrates:

• Significant positive correlation with:

  • CD4+ memory resting cells

  • CD8+ effector memory cells

  • M0 macrophages

  • Cancer-associated fibroblasts (CAFs) (p = 0.00015)

• Significant negative correlation with:

  • CD4+ memory-activated cells (p < 0.05)

Immunofluorescence studies suggest that SLC7A1 overexpression may affect the distribution of immune-infiltrating lymphocytes in tumors by inhibiting the expression of CCL4 . This relationship between SLC7A1 and immune cell populations provides insight into potential mechanisms by which SLC7A1 contributes to tumor progression and therapy resistance through modulation of the tumor immune microenvironment. Researchers investigating this relationship should consider multiplex immunohistochemistry or flow cytometry to simultaneously analyze SLC7A1 expression and immune cell markers in tumor samples .

What are the methodological considerations when assessing SLC7A1 expression in cancer-associated fibroblasts (CAFs) versus tumor cells?

When differentiating SLC7A1 expression in CAFs versus tumor cells, researchers should consider the following methodological approaches:

• Cell-specific markers: Use co-staining with established CAF markers (e.g., α-SMA, FAP, or PDGFRβ) alongside SLC7A1 to distinguish between cell types in tissue sections .

• Immunohistochemical scoring methodology: Follow standardized scoring systems as described in literature, where staining intensity scores (0-3) are multiplied by staining percentage scores (0-3):

  • 0 (negative)

  • 1 (low)

  • 2 (medium)

  • 3 (high)

  Final scores ranging from 0-9 can be categorized as low expression (scores <5) or medium-high expression (scores 5-9) .

• Spatial distribution analysis: Carefully document whether SLC7A1 expression is observed in tumor cells, stromal components, or both, as recent findings indicate significant expression in both compartments in HGSOC .

• TGF-β1 stimulation experiments: Consider incorporating TGF-β1 treatments when studying CAF-specific SLC7A1 expression, as evidence suggests TGF-β1 upregulates SLC7A1 expression specifically in CAFs .

• Functional validation: Complement expression studies with functional assays (Transwell, scratch, CCK8, and cell adhesion assays) to determine the biological significance of SLC7A1 expression in different cellular compartments .

How can researchers accurately investigate the role of SLC7A1 in amino acid metabolism in cancer cells?

To rigorously investigate SLC7A1's role in amino acid metabolism in cancer cells, researchers should employ a multi-faceted approach:

• Amino acid transport assays: Utilize radiolabeled amino acids or amino acid autoanalyzers to directly measure the effect of SLC7A1 expression or knockdown on the transport of specific amino acids (particularly phenylalanine and arginine) in cancer cells .

• Gene knockdown/overexpression validation: Establish stable SLC7A1 knockdown or overexpression cell lines using appropriate genetic tools (siRNA, shRNA, or CRISPR-Cas9) with proper validation of expression changes via western blot and qRT-PCR .

• Metabolomic profiling: Perform comprehensive metabolomic analysis to identify alterations in amino acid concentrations and related metabolic pathways following SLC7A1 modulation .

• Functional assays: Connect amino acid transport to downstream biological effects using:

  • Proliferation assays (e.g., CCK8, EdU incorporation)

  • Migration assays (e.g., wound healing, Transwell)

  • Drug resistance assays (e.g., cisplatin sensitivity testing)

• Pathway analysis: Investigate downstream signaling pathways affected by SLC7A1-mediated amino acid transport using phosphorylation-specific antibodies or pathway inhibitors to establish mechanistic connections .

What optimization steps should be taken when using SLC7A1 Antibody, HRP conjugated for ELISA assays?

To achieve optimal results with SLC7A1 Antibody, HRP conjugated in ELISA assays, researchers should implement the following optimization steps:

• Antibody titration: Test different dilutions around the recommended range (1:500-1:1000) to determine the optimal concentration that maximizes signal-to-noise ratio .

• Blocking optimization: Evaluate different blocking reagents (BSA, casein, non-fat milk) to minimize background and improve specificity.

• Antigen concentration standardization: Create a standard curve using recombinant SLC7A1 protein (such as the recombinant Human High affinity cationic amino acid transporter 1 protein, specifically regions 430-492AA that served as immunogen) .

• Incubation parameters: Optimize both time and temperature for antibody incubation, as HRP conjugated antibodies may have different kinetics than unconjugated antibodies.

• Detection system evaluation: Select an appropriate substrate for HRP (TMB, ABTS, etc.) based on desired sensitivity and detection range.

• Reproducibility assessment: Perform intra- and inter-assay validation to ensure consistent and reliable results across experiments.

• Cross-reactivity testing: Validate antibody specificity against related transporters in the SLC7 family to confirm selective detection of SLC7A1.

How can researchers quantitatively assess SLC7A1 expression in tissue samples to establish clinically relevant thresholds?

For establishing clinically relevant thresholds of SLC7A1 expression in tissue samples, researchers should employ systematic quantitative approaches:

• Standardized immunohistochemical scoring:

  • Implement the validated scoring system described in literature, which combines staining intensity (0-3) and percentage of positive cells (0-3)

  • Calculate final scores (0-9) through multiplication of these parameters

  • Define expression levels as negative/low (scores <5) or medium/high (scores 5-9)

• Digital pathology approaches:

  • Utilize whole slide imaging and automated analysis software for objective quantification

  • Apply machine learning algorithms to distinguish between tumor cells and stromal components

  • Implement color deconvolution to specifically measure DAB signal intensity

• Correlation with clinical outcomes:

  • Perform Kaplan-Meier survival analysis with different SLC7A1 expression thresholds

  • Determine optimal cut-off values using statistical methods like ROC curve analysis

  • Validate thresholds across independent patient cohorts

• Multi-marker integration:

  • Combine SLC7A1 expression with other established biomarkers

  • Utilize multivariate analysis to determine independent prognostic value

  • Consider tumor mutation burden (TMB) in relation to SLC7A1 expression levels

• Tissue microarray validation:

  • Confirm expression patterns across large patient cohorts using tissue microarrays

  • Assess heterogeneity in expression by evaluating multiple cores per patient

What are the best experimental approaches to investigate the relationship between SLC7A1 expression and cisplatin resistance in ovarian cancer?

To robustly investigate the relationship between SLC7A1 expression and cisplatin resistance in ovarian cancer, researchers should consider these experimental approaches:

• Genetic modulation studies:

  • Generate stable SLC7A1 knockdown and overexpression in ovarian cancer cell lines

  • Validate expression changes at protein and mRNA levels

  • Assess cisplatin sensitivity using cell viability assays (MTT, CCK8) and IC50 determination

• Drug resistance models:

  • Develop cisplatin-resistant cell lines through incremental drug exposure

  • Compare SLC7A1 expression between parental and resistant lines

  • Investigate whether SLC7A1 knockdown can resensitize resistant cells to cisplatin

• Mechanistic investigations:

  • Explore connections between amino acid metabolism and cisplatin resistance

  • Assess whether specific amino acids (particularly arginine and phenylalanine) mediate the resistance phenotype

  • Investigate downstream pathways affected by SLC7A1-mediated amino acid transport

• Co-culture experiments:

  • Establish co-culture systems with cancer cells and CAFs with varying SLC7A1 expression

  • Assess how stromal SLC7A1 expression affects cancer cell drug resistance

  • Investigate paracrine factors that might mediate this interaction

• Clinical correlation studies:

  • Analyze SLC7A1 expression in paired pre- and post-treatment samples from patients

  • Correlate expression levels with treatment response and progression-free survival

  • Validate findings in independent patient cohorts

How might SLC7A1 targeting be incorporated into immunotherapy approaches for ovarian cancer?

Based on the established relationship between SLC7A1 expression and immune cell infiltration, emerging research could explore several immunotherapy-related approaches:

• Combination therapy strategies:

  • Investigate synergistic effects between SLC7A1 inhibitors and immune checkpoint inhibitors

  • Determine if SLC7A1 blockade enhances T cell infiltration and activation within tumors

  • Assess whether modulating SLC7A1 can overcome immunotherapy resistance mechanisms

• CAF-targeted approaches:

  • Develop strategies to specifically target SLC7A1 in CAFs to modify the tumor microenvironment

  • Evaluate whether CAF-specific SLC7A1 inhibition alters immune cell recruitment and function

  • Investigate the impact on CCL4 expression and subsequent effects on chemokine gradients

• Metabolism-based immunomodulation:

  • Explore how SLC7A1-mediated amino acid transport affects T cell functionality

  • Determine if competitive inhibition of SLC7A1 can redirect amino acid availability to enhance immune cell activity

  • Assess potential metabolic competition between cancer cells and T cells for key amino acids

• Predictive biomarker development:

  • Validate SLC7A1 expression as a predictive biomarker for immunotherapy response

  • Integrate SLC7A1 expression with immune cell profiling to create composite biomarkers

  • Develop clinically applicable assays for patient stratification

What are the technical challenges in developing specific inhibitors targeting SLC7A1 for cancer therapy?

Developing specific inhibitors targeting SLC7A1 presents several technical challenges that researchers must address:

• Structural considerations:

  • SLC7A1 is a transmembrane protein with 14 transmembrane domains, making structural characterization difficult

  • Limited availability of high-resolution crystal structures hampers structure-based drug design

  • Need for appropriate expression and purification systems to produce functional protein for screening assays

• Selectivity challenges:

  • SLC7A1 belongs to a family of related transporters with similar substrate preferences

  • Achieving selectivity over other cationic amino acid transporters (SLC7A2, SLC7A3) requires sophisticated medicinal chemistry

  • Need to avoid disruption of physiological amino acid transport in normal tissues

• Functional validation:

  • Establishing appropriate assays to measure specific inhibition of SLC7A1-mediated transport

  • Differentiating between direct transporter inhibition and indirect effects on expression or localization

  • Developing cell-based and in vitro transport assays with adequate throughput for screening campaigns

• Efficacy demonstration:

  • Confirming that SLC7A1 inhibition directly impacts cancer cell viability and proliferation

  • Establishing appropriate in vivo models that recapitulate the metabolic dependencies observed in human tumors

  • Determining optimal dosing schedules to achieve sustained pathway inhibition

• Delivery to tumor microenvironment:

  • Ensuring adequate drug exposure in both tumor cells and CAFs

  • Addressing potential compensatory mechanisms that might emerge upon SLC7A1 inhibition

  • Developing strategies to monitor target engagement in vivo