ASPHD1 Human

What is ASPHD1 and what are its key characteristics?

ASPHD1 is a protein encoded by the ASPHD1 gene (Locus ID 253982) that contains an aspartate beta-hydroxylase domain. It is a paralog of ASPH (aspartate beta-hydroxylase), which has been more extensively studied as a potential candidate for molecular targeted therapy and immunotherapy . ASPHD1 is primarily expressed in brain and pituitary gland tissues, suggesting its importance in neurological and endocrine functions . The protein is identified by UniProt ID Q5U4P2 and has at least two transcript variants referenced in NCBI (RefSeq: NM_181718, NM_198907) .

How does ASPHD1 relate to other aspartate beta-hydroxylase domain proteins?

ASPHD1 functions as a critical paralog of ASPH (aspartate beta-hydroxylase). While ASPH has been extensively investigated for its role in cancer progression and as a potential therapeutic target, ASPHD1's relationship to cancer and other conditions remains less studied . The shared domain suggests similar enzymatic functions, likely involving protein hydroxylation, but the specific substrates and biological pathways may differ. Research indicates that ASPHD1 might have distinct tissue-specific roles, particularly in brain and pituitary tissues, compared to other family members .

What cellular compartments typically contain ASPHD1?

Based on the available research, ASPHD1 appears to be expressed in multiple cellular compartments. Studies investigating ASPHD1 in melanoma cells demonstrated its expression using Western blot and immunohistochemistry techniques, suggesting both cytoplasmic and potentially membrane-associated localization . The protein's hydroxylase domain suggests it may function within the endoplasmic reticulum, similar to other proteins with this domain, though specific cellular localization studies would be needed to confirm this hypothesis.

How does ASPHD1 expression differ between normal and cancer tissues?

Research has demonstrated significant differences in ASPHD1 expression between cancer and normal tissues. In skin cutaneous melanoma (SKCM), ASPHD1 expression is significantly upregulated compared to non-tumor tissues, with particularly elevated levels observed in metastatic SKCM . This finding has been validated through multiple approaches:

• Analysis of RNA-seq data from TCGA (471 SKCM samples) and GTEx (557 non-tumor samples) databases

• Verification through independent GEO datasets

• Quantitative RT-PCR comparing human melanoma cell lines with normal epidermal melanocytes

• Western blot protein analysis

• Immunohistochemistry comparing melanoma and non-tumor skin tissues

All these methods consistently showed higher ASPHD1 expression in melanoma compared to normal tissues, suggesting its potential role in cancer biology.

What are the recommended methods for measuring ASPHD1 expression?

Based on published research methodologies, several techniques are effective for measuring ASPHD1 expression:

For reliable results, researchers should consider validating findings using multiple techniques, as demonstrated in studies that combined RNA-seq data from public databases with experimental qRT-PCR and Western blot validation .

What statistical approaches should be used when analyzing ASPHD1 expression data?

When analyzing ASPHD1 expression data, several statistical approaches have proven effective:

• For comparing expression between groups: Mann-Whitney U test has been used to compare ASPHD1 expression between tumor and non-tumor samples

• For survival analysis: Kaplan-Meier curves and Cox proportional hazard regression models (both univariate and multivariate) to evaluate the relationship between ASPHD1 expression and patient survival

• For identifying associated genes: Differential expression analysis using limma R package, with correlation analysis to identify co-expressed genes

• For clinical parameter associations: Chi-square tests to evaluate relationships between ASPHD1 expression and clinicopathological parameters

Significance thresholds typically include p < 0.05 for statistical significance across analyses. For more complex analyses like Gene Set Enrichment Analysis (GSEA), parameters such as |standardized enrichment score| > 1, nominal p-value < 0.05, and FDR q-value < 0.25 have been used as significance cutoffs .

What is the prognostic value of ASPHD1 in cancer?

These analyses suggest that ASPHD1 may serve as a potential prognostic biomarker in SKCM, though the mechanisms underlying this association require further investigation .

How does ASPHD1 expression correlate with immune cell infiltration in tumors?

ASPHD1 expression shows significant associations with various immune components within the tumor microenvironment. Research using databases such as TISIDB and TIMER 2.0 has revealed correlations between ASPHD1 expression and:

• Immunostimulators

• Immunoinhibitors

• Chemokines

• Tumor-infiltrating lymphocytes (TILs)

Specifically, ASPHD1 expression correlates with infiltration of CD4+ T cells, CD8+ T cells, mast cells, Th2 cells, and dendritic cells . Notably, ASPHD1 expression is tightly associated with immune checkpoint markers CTLA4 and CD276, suggesting potential implications for immunotherapy responses . These findings indicate that ASPHD1 may play a role in shaping the tumor immune microenvironment, which could contribute to its prognostic significance.

How does ASPHD1 expression affect drug sensitivity in cancer treatment?

Research has identified significant relationships between ASPHD1 expression and drug sensitivity in cancer treatment. Studies demonstrate that upregulated expression of ASPHD1 is associated with higher IC50 values (the concentration needed to inhibit growth by 50%) for 24 chemotherapy drugs, including doxorubicin and masitinib . This suggests that tumors with higher ASPHD1 expression may be more resistant to certain chemotherapeutic agents.

This finding has important implications for personalized medicine approaches, as ASPHD1 expression levels could potentially serve as a predictive biomarker for treatment response. Researchers investigating cancer therapies should consider evaluating ASPHD1 expression when designing studies on drug efficacy or resistance mechanisms.

What are effective approaches for ASPHD1 knockdown studies?

For researchers conducting ASPHD1 functional studies, RNA interference using siRNA represents an effective approach for gene knockdown. Commercial siRNA oligo duplexes targeting human ASPHD1 are available, typically providing multiple unique 27mer siRNA duplexes to ensure effective knockdown .

When conducting ASPHD1 knockdown experiments, researchers should consider:

• Using multiple siRNA sequences (typically 3 unique sequences) to control for off-target effects

• Including appropriate controls such as scrambled siRNA negative controls

• Optimizing transfection conditions (10nM final concentration is commonly used)

• Validating knockdown efficiency using qRT-PCR and/or Western blot

• Assessing phenotypic consequences relevant to your research question

Quality siRNA products often come with performance guarantees, expecting at least 70% knockdown of target mRNA when used at 10nM concentration, as measured by quantitative RT-PCR .

What functional enrichment analyses are useful for understanding ASPHD1's biological role?

To understand ASPHD1's biological functions and associated pathways, researchers have employed several functional enrichment analyses:

• Gene Ontology (GO) and KEGG pathway analysis:

  • Using R packages such as "clusterProfiler" and "ggplot2" to analyze differentially expressed genes related to ASPHD1

  • Identifying biological processes, molecular functions, and cellular components associated with ASPHD1

• Gene Set Enrichment Analysis (GSEA):

  • Using annotated gene sets (e.g., C5.all.v7.1.symbols.gmt)

  • Performing 1000 gene set permutations

  • Setting significance thresholds of |standardized enrichment score| > 1, nominal p-value < 0.05, and FDR q-value < 0.25

• Protein-Protein Interaction (PPI) network analysis:

  • Using STRING database (http://string-db.org)

  • Setting medium confidence (0.400) as minimum interaction fraction

  • Identifying key protein interactions and potential functional modules

• Co-expression network analysis:

  • Using Coexpedia database (http://www.coexpedia.org/)

  • Sorting co-expressed genes by neighbor's local linear selection scores (p-value < 0.05)

  • Identifying genes frequently co-expressed with ASPHD1 across conditions

These analyses provide complementary insights into ASPHD1's potential biological functions and can guide hypothesis generation for experimental validation.

What cell and tissue models are appropriate for studying ASPHD1 function?

Based on the available research, several model systems appear appropriate for investigating ASPHD1 function:

• Cell line models:

  • Human melanoma cell lines have shown high ASPHD1 expression and have been successfully used in expression studies

  • Human normal epidermal melanocytes provide appropriate controls for melanoma studies

  • Cell lines derived from brain and pituitary tissues may be particularly relevant given ASPHD1's predominant expression in these tissues

• Tissue samples:

  • SKCM tissue samples have demonstrated differential ASPHD1 expression and clinical correlations

  • Brain and pituitary tissue samples are relevant given ASPHD1's expression pattern

  • Paired tumor and adjacent normal tissue samples provide valuable controls for expression studies

• Animal models:

  • Zebrafish gnrh3:egfp models have been used to study ASPHD1's role in reproductive traits and development

  • Mouse models may be appropriate for studying tissue-specific expression and functional consequences of ASPHD1 modulation

When selecting an appropriate model system, researchers should consider the specific biological question being addressed and the relevance of ASPHD1 expression to the tissue or process under investigation.

How does ASPHD1 interact with other proteins in cellular networks?

Protein-protein interaction (PPI) network analysis has revealed potential functional relationships between ASPHD1 and other proteins. Studies utilizing the STRING database with medium confidence (0.400) interaction thresholds have identified several interaction partners . Additionally, gene co-expression network analysis using the Coexpedia database has highlighted genes frequently co-expressed with ASPHD1, providing insights into its functional networks .

Of particular interest is the interaction between ASPHD1 and KCTD13 (potassium channel tetramerization domain containing 13). Research has demonstrated that KCTD13 can modulate ASPHD1 to exacerbate GnRH neuron phenotypes, suggesting a functional relationship relevant to reproductive traits . This interaction represents an important area for further investigation, particularly in understanding how ASPHD1 functions within larger protein complexes and signaling networks.

What contradictory findings exist in ASPHD1 research and how can they be reconciled?

The current literature on ASPHD1 presents some apparently contradictory findings that merit careful consideration:

To reconcile these contradictions, researchers should consider:

• Conducting tissue-specific and context-dependent functional studies

• Investigating the impact of ASPHD1 on different treatment modalities

• Exploring the relationship between ASPHD1 and the tumor immune microenvironment

• Examining potential dual roles of ASPHD1 in different stages of cancer progression

What emerging techniques might advance ASPHD1 research?

Several cutting-edge techniques could significantly advance our understanding of ASPHD1 function:

• Single-cell RNA sequencing (scRNA-seq):

  • Would allow researchers to examine ASPHD1 expression at the single-cell level

  • Could reveal cell type-specific expression patterns and heterogeneity within tissues

  • May uncover relationships between ASPHD1 expression and specific cell states or differentiation trajectories

• CRISPR-Cas9 genome editing:

  • Enables precise modification of ASPHD1 gene sequences

  • Allows for creation of knockout models and introduction of specific mutations

  • Facilitates high-throughput screening of ASPHD1 function in various biological contexts

• Spatial transcriptomics:

  • Combines RNA sequencing with spatial information

  • Could reveal ASPHD1 expression patterns within specific tissue microenvironments

  • May uncover relationships between ASPHD1 expression and tissue architecture

• Proteomics approaches:

  • Mass spectrometry-based identification of ASPHD1 interacting partners

  • Analysis of post-translational modifications affecting ASPHD1 function

  • Examination of ASPHD1 in multi-protein complexes

• Integrative multi-omics approaches:

  • Combining genomics, transcriptomics, proteomics, and metabolomics data

  • Could provide comprehensive understanding of ASPHD1's role in cellular networks

  • May identify novel biomarkers and therapeutic targets associated with ASPHD1 function

Implementation of these techniques could address current knowledge gaps and provide more comprehensive insights into ASPHD1's biological functions and disease associations.

What are the most promising avenues for future ASPHD1 research?

Based on current findings, several research directions appear particularly promising:

• Detailed mechanistic studies of how ASPHD1 influences the tumor immune microenvironment, particularly its associations with immune checkpoint markers like CTLA4 and CD276

• Investigation of ASPHD1's role in reproductive traits, building on findings of its expression in brain and pituitary tissues and its modulation by KCTD13

• Development of therapeutic strategies targeting ASPHD1 or its interaction partners, particularly in contexts where its expression correlates with drug resistance

• Exploration of ASPHD1 as a biomarker for patient stratification in clinical trials, given its prognostic significance in SKCM

• Comparative studies of ASPHD1 across different cancer types to determine if its prognostic value extends beyond SKCM

Researchers pursuing these directions will contribute to a more comprehensive understanding of ASPHD1's biological functions and potential clinical applications.

How might ASPHD1 research impact clinical practice?

The translational potential of ASPHD1 research appears substantial, with several possible impacts on clinical practice:

• Prognostic biomarker development: ASPHD1 expression levels could be incorporated into prognostic models for SKCM patients, potentially influencing treatment decisions and follow-up protocols

• Predictive biomarkers for drug response: Given ASPHD1's association with drug sensitivity, its expression might help predict responses to specific chemotherapeutic agents

• Immunotherapy patient selection: The association between ASPHD1 and immune checkpoint markers suggests it might help identify patients likely to respond to immunotherapies

• Novel therapeutic target identification: Understanding ASPHD1's functional role could reveal new therapeutic approaches, potentially involving its enzymatic activity or protein-protein interactions