DHRS1 Antibody

What is DHRS1 and why is it important in research?

DHRS1 (Dehydrogenase/reductase SDR family member 1) is a member of the short-chain dehydrogenases/reductases (SDR) superfamily. This enzyme contains a conserved catalytic domain and functions primarily as an oxidoreductase . DHRS1 plays a crucial role in the regulation of retinoic acid and steroid hormone metabolism, which impacts fundamental cellular processes including differentiation, proliferation, and apoptosis . The protein is particularly significant in research because its dysregulation has been linked to various pathological conditions, including cancer and metabolic disorders, highlighting its potential as both a biomarker and therapeutic target . Recent research has particularly focused on its role in hepatocellular carcinoma (HCC), where decreased DHRS1 expression correlates with poorer prognosis, suggesting its value as a predictive biomarker .

What experimental applications are suitable for DHRS1 antibodies?

DHRS1 antibodies are versatile research tools applicable across multiple experimental techniques:

The selection of the appropriate application depends on the specific research question. For studies examining DHRS1 localization in tissues, IHC is recommended, whereas Western blotting is valuable for confirming protein expression levels and molecular weight (approximately 33,909 Da for human DHRS1) . The antibody's known reactivity across human, mouse, and rat species allows for comparative studies across these experimental models .

How should DHRS1 antibodies be stored and handled for optimal performance?

For optimal performance and longevity of DHRS1 antibodies, researchers should adhere to specific storage and handling protocols. Most commercial DHRS1 antibodies, such as the polyclonal PACO03402, are supplied in liquid form within a storage buffer containing PBS with 50% glycerol, 0.5% BSA, and 0.02% sodium azide . This formulation helps maintain antibody stability and prevents microbial contamination.

Long-term storage should be at -20°C, while working aliquots can be maintained at 4°C for several weeks. Repeated freeze-thaw cycles should be avoided as they can degrade antibody quality and affect experimental reproducibility. When preparing working solutions, researchers should use sterile techniques and appropriate diluents matching the intended application buffer systems. For immunohistochemistry applications specifically, the recommended dilution range is typically 1:100-1:300, but this should be optimized for each experimental protocol and tissue type .

How can researchers validate the specificity of DHRS1 antibodies?

Validating antibody specificity is critical for ensuring reliable research outcomes. For DHRS1 antibodies, a multi-step validation approach is recommended:

• Positive and negative control samples: Use tissues or cell lines with known DHRS1 expression levels. For instance, since DHRS1 is expressed in the endoplasmic reticulum, cell lines with high ER activity can serve as positive controls .

• Blocking peptide experiments: Pre-incubate the antibody with the immunizing peptide (for PACO03402, the synthesized peptide derived from the internal region of human DHRS1) before application to samples . Signal elimination confirms specificity.

• Knockout/knockdown verification: Compare staining in wild-type samples versus those with DHRS1 gene knockout or knockdown.

• Western blot analysis: Confirm detection of a single band at the expected molecular weight of 33,909 Da for human DHRS1 .

• Cross-reactivity assessment: Since the antibody may react with human, mouse, and rat samples , researchers should validate specificity across species relevant to their research.

• Immunoprecipitation followed by mass spectrometry: This can definitively identify the proteins being recognized by the antibody.

Researchers should document all validation steps and include appropriate controls in publications to enhance reproducibility and reliability of DHRS1-related findings.

What approaches are most effective for studying DHRS1's role in cancer biology?

To investigate DHRS1's functions in cancer biology, researchers should employ multiple complementary approaches:

• Expression analysis across cancer types: Use DHRS1 antibodies for immunohistochemistry on tissue microarrays containing various cancer types and corresponding normal tissues. In hepatocellular carcinoma specifically, DHRS1 expression has been shown to decrease, with lower expression correlating with poorer prognosis .

• Correlation with clinical outcomes: Analyze DHRS1 expression in patient samples in relation to survival data, tumor stage, and treatment response. This approach has revealed DHRS1 as a potential predictor of HCC prognosis .

• Immune infiltration studies: Investigate relationships between DHRS1 expression and immune cell infiltration, as DHRS1 has been linked to immune response in HCC . This can be accomplished through multiplex immunostaining or digital spatial profiling.

• Functional studies with gene manipulation: Employ CRISPR-Cas9 or siRNA technologies to modulate DHRS1 expression in cancer cell lines, followed by assays for proliferation, migration, invasion, and apoptosis.

• Pathway analysis: Combine DHRS1 antibody-based detection with analyses of related signaling molecules to understand the broader context of DHRS1 function in cancer cells.

• Prognostic model development: Use DHRS1-related immunomodulators to create risk prediction models, as demonstrated in HCC research where six DHRS1-associated immunomodulators (KDR, TNFRSF4, CD276, TNFSF4, SLAMF6, and SIGLEC9) were used to develop a prognostic signature .

These multi-faceted approaches can provide comprehensive insights into DHRS1's role in cancer biology and its potential as a therapeutic target.

How can researchers optimize immunohistochemistry protocols for DHRS1 detection?

Optimizing immunohistochemistry (IHC) protocols for DHRS1 detection requires attention to several critical parameters:

By systematically optimizing these parameters, researchers can achieve reliable and reproducible DHRS1 detection in tissue samples.

What is the relationship between DHRS1 expression and hepatocellular carcinoma?

Research has revealed significant associations between DHRS1 expression and hepatocellular carcinoma (HCC):

• Expression pattern: DHRS1 expression is decreased in HCC compared to normal liver tissue, and patients with reduced DHRS1 expression demonstrate poorer prognosis and survival outcomes .

• Biomarker potential: Evidence suggests that DHRS1 may constitute a unique and independent predictive biomarker for HCC, although this requires further experimental validation .

• Immune cell infiltration: DHRS1 expression levels and gene copy numbers are correlated with immune cell infiltration in HCC, particularly with macrophages and dendritic cells . This suggests DHRS1 may play a role in modulating the tumor immune microenvironment.

• Mechanistic insights: While the exact mechanisms remain to be fully elucidated, DHRS1's function as an oxidoreductase involved in metabolism of retinoids and steroids suggests potential pathways through which it might influence HCC development and progression.

• Therapeutic implications: The association of DHRS1 with HCC progression suggests it may represent a potential therapeutic target, though further research is needed to explore this possibility .

These findings collectively highlight the importance of DHRS1 in HCC pathogenesis and its potential clinical utility, making it a valuable target for ongoing research using specific antibodies.

How can researchers effectively study DHRS1-related immunomodulators in HCC?

To investigate DHRS1-related immunomodulators in hepatocellular carcinoma, researchers should employ a systematic approach:

• Correlation analysis: Begin with comprehensive correlation analyses between DHRS1 expression and known immunomodulators. Research has identified multiple immunomodulators associated with DHRS1 in HCC, including 25 immunostimulators (CD27, CD276, CD40, CD80, CD86, CXCR4, ENTPD1, ICOS, ICOSLG, IL2RA, IL6R, etc.) and 12 immunoinhibitors (ADORA2A, CSF1R, CTLA4, HAVCR2, KDR, etc.) .

• Prognostic value assessment: Apply univariate and multivariate Cox regression analyses to identify immunomodulators with significant prognostic value. A recent study identified six DHRS1-related immunomodulators (KDR, TNFRSF4, CD276, TNFSF4, SLAMF6, and SIGLEC9) that significantly correlated with HCC patient survival .

• Risk score development: Construct a prognostic model using the identified immunomodulators. The risk score can be calculated using the formula:
  Risk score = (β1 × gene1 expression) + (β2 × gene2 expression) + ... + (βi × genei expression)

  Where βi represents the Cox regression coefficient for each gene .

• Validation cohorts: Establish external validation cohorts to confirm the predictive accuracy of the risk score. This approach enhances the reliability and clinical applicability of findings .

• Protein-protein interaction network: Construct networks to understand the relationships between DHRS1 and immunomodulators, as well as interactions among the immunomodulators themselves .

• Functional validation: Perform in vitro and in vivo experiments to validate the functional significance of identified immunomodulators, using DHRS1 antibodies to monitor expression changes.

This methodical approach enables researchers to comprehensively understand the complex relationships between DHRS1 and the immune microenvironment in HCC, potentially leading to improved prognostic tools and therapeutic strategies.

What experimental designs are suitable for validating DHRS1 as a therapeutic target in HCC?

To validate DHRS1 as a therapeutic target in hepatocellular carcinoma, researchers should implement a multi-phase experimental design:

• In vitro functional studies:

  • Use CRISPR-Cas9 or siRNA to modulate DHRS1 expression in HCC cell lines

  • Assess the impact on proliferation, migration, invasion, apoptosis, and cell cycle

  • Investigate changes in relevant signaling pathways using DHRS1 antibodies for detection

  • Study effects on metabolism of retinoids and steroids, given DHRS1's known function

• Mechanistic investigations:

  • Perform RNA-seq and proteomics analyses following DHRS1 modulation to identify altered pathways

  • Conduct chromatin immunoprecipitation (ChIP) to identify transcription factors regulating DHRS1

  • Investigate DHRS1's interaction with the immune microenvironment, given its established relationship with immune cell infiltration

  • Study DHRS1's enzymatic activity and identify potential inhibitors or activators

• In vivo validation:

  • Generate xenograft models using DHRS1-modulated HCC cell lines

  • Create genetic mouse models with liver-specific DHRS1 knockout or overexpression

  • Monitor tumor growth, metastasis, and survival outcomes

  • Analyze immune cell infiltration in tumor tissues using immunohistochemistry with DHRS1 antibodies

• Translational research:

  • Correlate DHRS1 expression in patient samples with treatment response

  • Develop DHRS1-targeting compounds and test their efficacy in preclinical models

  • Design combination therapy approaches, particularly with immunotherapies given DHRS1's connection to immune modulators

  • Create patient-derived xenografts to test DHRS1-targeting strategies in models that better represent human disease

• Clinical correlation:

  • Develop a nomogram incorporating DHRS1 expression and related immunomodulators for patient stratification

  • Design early-phase clinical trials based on preclinical findings

This comprehensive approach would establish whether DHRS1 represents a viable therapeutic target in HCC and provide the foundation for translating these findings into clinical applications.

What are common challenges in DHRS1 antibody experiments and how can they be resolved?

Researchers working with DHRS1 antibodies may encounter several technical challenges. The following table outlines common issues and their solutions:

When troubleshooting, researchers should always remember that DHRS1 is primarily localized to the endoplasmic reticulum and mitochondria , which might require specific sample preparation techniques for optimal detection. Additionally, incorporating appropriate positive controls (tissues known to express DHRS1) and negative controls (tissues where DHRS1 is absent or depleted) is essential for validating experimental results.

How should researchers interpret contradictory DHRS1 expression data across different studies?

When encountering contradictory DHRS1 expression data across different studies, researchers should consider several factors to resolve discrepancies:

To reconcile contradictory findings, researchers should conduct comprehensive meta-analyses, perform validation studies using multiple antibodies and techniques, and clearly report all methodological details to enhance reproducibility.

What considerations are important when selecting DHRS1 antibodies for specific research applications?

When selecting DHRS1 antibodies for specific research applications, researchers should carefully evaluate several key parameters:

• Antibody type and source:

  • Polyclonal antibodies (like PACO03402) offer high sensitivity but potentially lower specificity

  • Monoclonal antibodies provide high specificity but might miss certain epitopes

  • Consider the host species (rabbit for PACO03402) for compatibility with experimental systems

• Validated applications:

  • Ensure the antibody has been validated for your specific application (ELISA, IHC, etc.)

  • Review published literature using the antibody for similar applications

  • Request validation data from manufacturers for your intended use

• Epitope characteristics:

  • Consider the immunogen used (for PACO03402, a synthesized peptide from the internal region of human DHRS1)

  • Evaluate whether the epitope is conserved across species if conducting comparative studies

  • Assess epitope accessibility in your experimental conditions (native vs. denatured)

• Species reactivity:

  • Confirm reactivity with your species of interest (PACO03402 reacts with human, mouse, and rat samples)

  • Request sequence alignment data for cross-species applications

• Technical specifications:

  • Review recommended dilutions for your application (1:100-1:300 for IHC with PACO03402)

  • Consider antibody format (liquid in PBS with 50% glycerol for PACO03402)

  • Evaluate storage requirements and shelf-life

• Research objectives:

  • For localization studies, prioritize antibodies validated for immunofluorescence or IHC

  • For protein-protein interaction studies, select antibodies that don't interfere with binding domains

  • For quantitative analyses, choose antibodies with linear detection ranges

• Batch consistency:

  • Consider purchasing sufficient quantities of a single lot for long-term projects

  • Request lot-specific validation data when available

Making informed decisions based on these considerations will significantly enhance experimental outcomes and reliability when working with DHRS1 antibodies in research settings.

How might DHRS1 antibodies contribute to understanding the role of DHRS1 in other diseases beyond HCC?

While DHRS1's role in hepatocellular carcinoma has been investigated , DHRS1 antibodies can facilitate exploration of its functions in other disease contexts:

• Other cancer types: Given that dysregulation of DHRS1 has been linked to various cancers , researchers can employ DHRS1 antibodies to perform comprehensive tissue microarray analyses across different malignancies. This approach could reveal cancer-specific expression patterns and potentially identify additional cancer types where DHRS1 might serve as a biomarker or therapeutic target.

• Metabolic disorders: As a member of the short-chain dehydrogenases/reductases family, DHRS1 is involved in metabolism of retinoids and steroids . Researchers can use DHRS1 antibodies to investigate its expression and localization in tissues relevant to metabolic diseases, such as adipose tissue, pancreas, and liver, potentially uncovering novel pathophysiological mechanisms.

• Inflammatory conditions: The established relationship between DHRS1 and immune cell infiltration in HCC suggests potential roles in inflammatory processes. DHRS1 antibodies can be employed in multiplex immunohistochemistry to study co-localization with inflammatory markers across various inflammatory diseases.

• Neurodegenerative disorders: Oxidative stress plays a crucial role in neurodegenerative diseases, and as an oxidoreductase , DHRS1 might influence redox balance in neural tissues. DHRS1 antibodies could facilitate investigation of its expression and function in brain tissues from patients with conditions like Alzheimer's or Parkinson's disease.

• Development and differentiation: DHRS1's involvement in retinoic acid metabolism suggests potential roles in developmental processes. Researchers can use DHRS1 antibodies to track its expression during embryonic development and cellular differentiation in various organ systems.

By expanding DHRS1 research beyond HCC using specific antibodies, researchers may uncover novel disease associations and therapeutic opportunities across multiple medical fields.

What novel methodologies are emerging for studying DHRS1 protein interactions and functions?

Emerging methodologies for investigating DHRS1 protein interactions and functions include:

• Proximity labeling techniques: BioID or APEX2 fusion proteins with DHRS1 can identify proteins in close proximity within cellular compartments, particularly valuable given DHRS1's localization in the endoplasmic reticulum and mitochondria . These techniques can map the DHRS1 interactome in its native cellular environment.

• CRISPR-based screening: CRISPR activation or interference libraries targeting genes potentially associated with DHRS1 can systematically identify functional relationships. Phenotypic readouts combined with DHRS1 antibody-based detection can reveal genetic interactions and regulatory networks.

• Single-cell analysis: Coupling DHRS1 antibodies with single-cell technologies can reveal cell-type-specific expression patterns and functions, particularly relevant when studying heterogeneous tissues like tumors where DHRS1 expression may vary between cell populations.

• Spatial transcriptomics and proteomics: These technologies can map DHRS1 expression in tissue contexts while preserving spatial information, providing insights into how DHRS1 distribution relates to tissue architecture and microenvironmental factors.

• Organoid models: Patient-derived organoids combined with DHRS1 antibody-based analyses can provide physiologically relevant models for studying DHRS1 function in three-dimensional tissue contexts.

• Computational approaches: Machine learning algorithms integrating DHRS1 expression data with other molecular features can predict functional relationships and potential therapeutic vulnerabilities, as demonstrated in the development of prognostic models using DHRS1-related immunomodulators in HCC .

• PROTAC (Proteolysis Targeting Chimera) technology: This approach can be used to develop targeted DHRS1 degraders for precise temporal control over DHRS1 levels, enabling detailed studies of its cellular functions.

These innovative methodologies, when combined with traditional approaches using DHRS1 antibodies, provide powerful tools for comprehensive investigation of DHRS1 biology across various research contexts.

How can researchers integrate DHRS1 expression data with other omics datasets for comprehensive disease modeling?

Integrating DHRS1 expression data with other omics datasets enables sophisticated disease modeling approaches:

• Multi-omics data integration: Researchers can correlate DHRS1 antibody-derived protein expression data with:

  • Transcriptomic data to identify regulatory mechanisms governing DHRS1 expression

  • Genomic data to detect mutations or copy number variations affecting DHRS1 gene

  • Epigenomic data to uncover methylation patterns or histone modifications regulating DHRS1

  • Metabolomic data to connect DHRS1 activity with metabolic pathways, particularly those involving retinoids and steroids

• Network-based approaches: Construct protein-protein interaction networks centered on DHRS1, similar to the approach used to analyze DHRS1-related immunomodulators in HCC . These networks can reveal functional modules and potential therapeutic targets.

• Machine learning models: Develop predictive algorithms incorporating DHRS1 expression and related biomarkers to forecast disease progression and treatment responses. This approach has been demonstrated in HCC where DHRS1-related immunomodulators were used to create prognostic signatures .

• Pathway enrichment analysis: Identify biological pathways significantly associated with DHRS1 expression changes across different disease contexts, providing insights into mechanism-based disease classification.

• Single-cell multi-omics: Integrate DHRS1 protein expression at the single-cell level with transcriptomic and epigenomic data to identify cell-type-specific roles in heterogeneous tissues.

• Temporal dynamics modeling: Track DHRS1 expression changes over disease progression using longitudinal sampling and correlate with other molecular changes to understand disease evolution.

• Drug response prediction: Correlate DHRS1 expression patterns with drug sensitivity data to identify potential therapeutic vulnerabilities and resistance mechanisms.

• Clinical data integration: Develop comprehensive nomograms incorporating DHRS1 expression, clinical parameters, and other molecular markers for improved patient stratification and personalized treatment planning, as demonstrated in HCC research .

These integrative approaches transform isolated DHRS1 expression data into contextually rich insights that can advance precision medicine initiatives across multiple disease areas.

What are promising directions for developing new DHRS1 antibodies with enhanced specificity or functionality?

The development of next-generation DHRS1 antibodies with improved characteristics represents an important frontier for advancing research capabilities:

• Epitope-specific monoclonal antibodies: Developing monoclonal antibodies targeting different functional domains of DHRS1 would enable more precise studies of protein interactions and activities. Current antibodies like PACO03402 target the internal region of human DHRS1 , but antibodies specific to catalytic domains or protein-interaction regions could provide more functional insights.

• Phospho-specific antibodies: Creating antibodies that specifically recognize phosphorylated forms of DHRS1 would enable studies of regulatory mechanisms controlling DHRS1 activity and signaling pathway integration.

• Conformation-specific antibodies: Developing antibodies that distinguish between different conformational states of DHRS1 would allow researchers to investigate the relationship between structure and function, particularly relevant given DHRS1's enzymatic activities as an oxidoreductase .

• Recombinant antibody fragments: Engineering smaller antibody formats like single-chain variable fragments (scFvs) or nanobodies against DHRS1 could improve tissue penetration for imaging applications and enable intracellular expression for live-cell studies.

• Bifunctional antibodies: Creating bispecific antibodies that simultaneously target DHRS1 and related proteins could facilitate studies of protein complexes and signaling pathways, particularly relevant given DHRS1's associations with immunomodulators in HCC .

• Species-specific antibodies: Developing antibodies with enhanced specificity for DHRS1 from specific model organisms would improve comparative studies across species while maintaining high specificity.

• Application-optimized antibodies: Engineering antibodies specifically optimized for challenging applications like super-resolution microscopy, chromatin immunoprecipitation, or proximity ligation assays would expand research capabilities.

These advances in antibody technology would significantly enhance our ability to study DHRS1 biology across multiple experimental contexts and disease models.

How might DHRS1 research contribute to precision medicine approaches in oncology?

DHRS1 research has significant potential to advance precision medicine in oncology through several mechanisms:

• Prognostic stratification: DHRS1 expression patterns, particularly in combination with related immunomodulators, can be used to develop sophisticated prognostic models for patient stratification. This approach has already shown promise in hepatocellular carcinoma, where a six-gene signature of DHRS1-related immunomodulators (KDR, TNFRSF4, CD276, TNFSF4, SLAMF6, and SIGLEC9) was used to create a risk score with significant prognostic value .

• Predictive biomarkers: By correlating DHRS1 expression with treatment outcomes across different therapies, researchers can identify patient populations likely to benefit from specific interventions. This is particularly relevant given DHRS1's association with immune cell infiltration in HCC , which might predict immunotherapy responsiveness.

• Therapeutic target identification: As an enzyme involved in metabolic processes , DHRS1 represents a potential druggable target. Structure-based drug design focused on its catalytic domain could lead to the development of specific inhibitors or activators with therapeutic potential.

• Combination therapy rationales: Understanding DHRS1's relationship with other pathways can inform rational combination therapies. For instance, if DHRS1 dysregulation affects specific metabolic pathways, combining DHRS1-targeted therapy with metabolism-modulating drugs might yield synergistic effects.

• Monitoring treatment response: DHRS1 antibodies could be used to monitor changes in protein expression during treatment, potentially serving as pharmacodynamic biomarkers to assess therapeutic efficacy in real-time.

• Resistance mechanism identification: Studying how DHRS1 expression changes in treatment-resistant populations might reveal adaptation mechanisms and inform second-line treatment strategies.

• Liquid biopsy development: If DHRS1 or its metabolic products can be detected in circulation, this could enable non-invasive monitoring of disease progression and treatment response.

By integrating DHRS1 research into comprehensive precision oncology frameworks, researchers can contribute to more personalized and effective cancer treatment approaches.