SDR16C5 Human

What is SDR16C5 and what are its primary functions in human cells?

SDR16C5, formerly known as epidermal retinol dehydrogenase 2, encodes a member of the short-chain alcohol dehydrogenase/reductase superfamily of proteins. This protein localizes to the endoplasmic reticulum and functions bidirectionally in oxidation and reduction reactions . It participates in retinol metabolism, which is implicated in tumor formation. SDR16C5 plays essential roles in embryonic and adult tissue differentiation, development, and apoptosis, while also contributing to immune response and energy metabolism regulation .

What experimental methods are most reliable for detecting SDR16C5 expression?

Several validated methods exist for detecting SDR16C5 expression:

• RT-qPCR: Using specific primers (e.g., F-CAGCCTTTGGGTTTGCTGA, R-GGTTCCAGAATTGGCAACAGA) with SYBR Green PCR Mix .

• Western blotting: Using anti-SDR16C5 antibodies (e.g., 1:5,000, #PA5-31421; Invitrogen) .

• Immunohistochemistry: Employing standardized scoring systems (0-3 scale) for tissue sections .

• RNA sequencing: For comprehensive transcriptome analysis, with data validation through public databases like TCGA, GEPIA2, and GEO .

For reliable results, multiple detection methods should be employed with appropriate controls and standardized protocols.

How do researchers distinguish between normal physiological roles of SDR16C5 and its pathological functions?

Understanding the distinction between normal and pathological functions requires:

• Comparative expression analysis: Using matched tumor and adjacent normal tissues, as demonstrated in studies with pancreatic cancer samples .

• Functional assays: Employing knockdown experiments in both normal and cancer cell lines to compare phenotypic effects.

• Pathway analysis: KEGG pathway analysis and GO enrichment studies help identify context-specific pathways, such as the IL-17 signaling pathway in pancreatic cancer .

• Correlation with clinical outcomes: Analyzing survival data based on SDR16C5 expression levels using Kaplan-Meier curves and log-rank tests.

Research shows that while SDR16C5 is necessary for normal development, its overexpression in cancer tissues correlates with poorer survival outcomes, suggesting distinct pathological functions .

How does SDR16C5 expression vary across different human cancers?

SDR16C5 expression patterns show significant variation across cancer types. Research indicates:

• Pancreatic cancer (PAAD): Significantly upregulated compared to normal pancreatic tissue .

• Laryngeal carcinoma: Exhibits elevated expression .

• Colorectal cancer: Shows increased expression levels .

Comprehensive analysis using databases like UCSC Xena and TCGA reveals that SDR16C5 is highly expressed in multiple tumor types. For pancreatic cancer specifically, data from GSE15471, GSE16515, and GSE28735 datasets confirm significant upregulation in tumor tissues compared to matched normal tissues .

What transcriptional factors regulate SDR16C5 expression?

While the provided search results don't specifically address transcriptional regulation of SDR16C5, investigating regulatory mechanisms would involve:

• Promoter analysis: Identifying potential transcription factor binding sites.

• ChIP assays: Confirming which transcription factors bind to the SDR16C5 promoter.

• Reporter assays: Using luciferase constructs to quantify promoter activity under different conditions.

• Transcription factor knockdown/overexpression: Observing effects on SDR16C5 expression.

These approaches would help elucidate the regulatory network controlling SDR16C5 expression in both normal and pathological states.

How does SDR16C5 expression correlate with HPV status in cancer patients?

Evidence suggests that SDR16C5 protein expression levels may differ according to HPV (Human Papillomavirus) status in cancer patients . While complete details aren't provided in the search results, the research indicated a comparison between SDR16C5 expression in HPV-positive and HPV-negative tumors .

To investigate this correlation:

• Stratify patient samples by HPV status using PCR, in situ hybridization, or p16 immunohistochemistry

• Quantify SDR16C5 expression using consistent methodology

• Perform statistical analysis comparing expression between HPV+ and HPV- groups

• Control for confounding variables like cancer stage, grade, and patient demographics

This approach helps understand potential viral influences on SDR16C5 regulation and function in carcinogenesis.

What molecular mechanisms underlie SDR16C5's role in cancer cell proliferation?

SDR16C5 promotes cancer cell proliferation through several key mechanisms:

• Apoptosis inhibition: Knockdown studies demonstrate that silencing SDR16C5 promotes apoptosis by repressing Bcl-2 and affecting cleaved caspase 3 and cleaved caspase 9 protein expression . This suggests that SDR16C5 normally inhibits apoptotic pathways.

• EMT promotion: Silencing SDR16C5 inhibits cancer cell migration by interrupting epithelial-mesenchymal transition , indicating its role in promoting this process critical for cancer invasion.

• Signaling pathway modulation: Evidence suggests SDR16C5 participates in cancer development through the IL-17 signaling pathway .

These mechanisms collectively enable cancer cells to proliferate excessively while evading apoptosis, contributing to aggressive tumor growth.

What experimental protocols are most effective for SDR16C5 gene silencing?

Based on published research, effective approaches for SDR16C5 knockdown include:

• siRNA transfection: Using validated siRNA sequences targeting SDR16C5:

  • si-RNA1-SDR16C5: sense, 5-GCUAAUGACCAUGGACAUUTT-3, antisense, 5-AAUGUCCAUGGUCAUUAGCTT-3

  • si-RNA2-SDR16C5: sense, 5-GCCUUUGGGUUUGCUGAAUTT-3, antisense, 5-AUUCAGCAAACCCAAAGGCTT-3

  • si-RNA3-SDR16C5: sense, 5-GCACAGGAUGGGUCAGAAUTT-3, antisense, 5-AUUCUGACCCAUCCUGUGCTT-3

For optimal knockdown:

• Test multiple siRNA sequences to identify those with highest efficiency

• Validate knockdown at both mRNA (RT-qPCR) and protein levels (western blot)

• Include appropriate negative controls (non-targeting siRNA)

• Optimize transfection conditions for specific cell lines

How does SDR16C5 affect cancer cell migration and invasion?

Research indicates that SDR16C5 plays a significant role in promoting cancer cell migration and invasion:

• EMT regulation: Silencing SDR16C5 inhibits the migration of pancreatic cancer cell lines (PANC-1 and SW1990) by interrupting epithelial-mesenchymal transition .

• EMT marker modulation: After SDR16C5 knockdown, researchers observed changes in key EMT markers, including E-cadherin and vimentin, as measured by western blot analysis .

To investigate these effects, researchers typically employ:

• Wound healing assays to measure migration

• Transwell migration and invasion assays

• Analysis of EMT markers via western blotting or immunofluorescence

• Real-time cell migration tracking

These methodologies help quantify SDR16C5's impact on cancer cell motility and invasive potential.

How does SDR16C5 interact with the IL-17 signaling pathway?

KEGG pathway analysis and immunofluorescence staining indicate that SDR16C5 is associated with immunity and may participate in pancreatic cancer development through the IL-17 signaling pathway . While detailed molecular interactions aren't fully described in the available data, this connection represents an important area for further investigation.

To explore this interaction, researchers should:

• Analyze expression changes in IL-17 pathway components after SDR16C5 manipulation

• Perform co-immunoprecipitation to identify direct binding partners

• Use pathway inhibitors to determine if blocking IL-17 signaling affects SDR16C5-mediated phenotypes

• Investigate transcriptional regulation between SDR16C5 and IL-17 pathway genes

Understanding this relationship could reveal how SDR16C5 influences inflammatory processes in cancer progression.

What is known about SDR16C5's relationship with immune cell infiltration?

The relationship between SDR16C5 expression and immune cell infiltration represents an emerging research area. According to the available data, analysis of the correlation between SDR16C5 expression and immune cell subset abundance has been performed in pancreatic cancer .

To investigate this relationship:

• Apply computational deconvolution methods to RNA-seq data using tools like the immunedeconv R package

• Compare immune cell profiles between high and low SDR16C5 expression groups

• Validate findings using immunohistochemistry or flow cytometry

• Determine how SDR16C5 modulation affects immune cell recruitment or activation

This research direction may reveal immunomodulatory functions of SDR16C5 and suggest potential combination therapy approaches targeting both SDR16C5 and immune pathways.

How does SDR16C5 affect retinol metabolism in cancer cells?

SDR16C5 participates in the retinol metabolism pathway, which is related to tumor formation . As a member of the short-chain dehydrogenase/reductase superfamily, it likely catalyzes oxidation-reduction reactions involving retinoids, though specific substrates and products in cancer cells require further characterization.

To investigate this function:

• Measure SDR16C5's enzymatic activity on retinoid substrates in cancer vs. normal cells

• Analyze how SDR16C5 modulation affects retinoic acid signaling and target gene expression

• Profile retinoid metabolites in cells with varying SDR16C5 expression using mass spectrometry

• Investigate connections between altered retinoid metabolism and cancer hallmarks

This research could reveal how SDR16C5-mediated changes in retinoid metabolism contribute to cancer development and progression.

What evidence supports SDR16C5 as a prognostic biomarker?

Several lines of evidence support SDR16C5's potential as a prognostic biomarker:

• Survival correlation: Higher expression of SDR16C5 is significantly associated with poorer survival in pancreatic cancer patients .

• Expression patterns: SDR16C5 is overexpressed in multiple tumor types including pancreatic cancer, laryngeal carcinoma, and colorectal cancer .

• Functional relevance: Its roles in promoting proliferation, inhibiting apoptosis, and enhancing migration provide biological plausibility for its prognostic significance .

Survival analysis using Kaplan-Meier methods and time ROC analysis has been employed to measure the predictive power of SDR16C5 expression for pancreatic cancer . Similar approaches could be applied to other cancer types where SDR16C5 is implicated.

What methods are most appropriate for measuring SDR16C5 in clinical specimens?

For clinical biomarker applications, several methods are suitable for measuring SDR16C5:

• Immunohistochemistry (IHC): Using validated antibodies with standardized scoring systems (0-3 scale) as indicated in clinical studies . This method preserves tissue architecture and allows for assessment of protein localization.

• RT-qPCR: For quantitative mRNA expression analysis using validated primers and reference genes .

• Digital PCR: For absolute quantification with improved sensitivity in challenging samples.

• Protein-based assays: Western blotting for research applications, though ELISA might be more suitable for clinical testing if antibodies are available.

For clinical implementation, standardization is crucial:

• Establish consistent sample collection and processing protocols

• Define clinically relevant cutoff values

• Include appropriate controls

• Validate analytical performance characteristics

How might SDR16C5 be therapeutically targeted in cancer?

Based on functional studies, targeting SDR16C5 represents a promising therapeutic strategy:

• RNAi-based approaches: siRNA or shRNA targeting could be developed into therapeutic modalities, building on the successful knockdown approaches used in research .

• Small molecule inhibitors: Computational approaches could identify compounds that inhibit SDR16C5's enzymatic activity or protein-protein interactions.

• Combination strategies: Given SDR16C5's connection to the IL-17 signaling pathway and immune infiltration, combining SDR16C5 inhibition with immunotherapy might be effective .

• Targeted protein degradation: PROTAC (Proteolysis Targeting Chimera) technology could be employed to selectively degrade SDR16C5 protein.

Development process should include:

• Target validation in multiple cancer models

• Specificity assessment to minimize off-target effects

• Pharmacokinetic and pharmacodynamic evaluation

• Biomarker development for patient selection

What transgenic mouse models would be valuable for studying SDR16C5 function?

While not addressed in the provided search results, developing appropriate mouse models would advance SDR16C5 research:

• Conditional knockout models: Using floxed SDR16C5 alleles with tissue-specific Cre recombinase expression to study tissue-specific functions.

• Inducible overexpression models: Implementing tetracycline-responsive systems to control SDR16C5 expression temporally.

• Cancer-specific models: Crossing SDR16C5 transgenic mice with established cancer models (e.g., pancreatic cancer models) to study its role in tumor initiation and progression.

• Humanized models: Replacing mouse SDR16C5 with the human version for more translational insights.

These models would facilitate:

• In vivo validation of in vitro findings

• Study of systemic effects of SDR16C5 modulation

• Testing of therapeutic approaches

• Investigation of developmental roles

How can single-cell approaches advance SDR16C5 research?

Single-cell technologies offer powerful ways to elucidate SDR16C5's role in cancer heterogeneity:

• Single-cell RNA sequencing (scRNA-seq): To identify specific cancer cell subpopulations with differential SDR16C5 expression and correlate with functional states.

• Spatial transcriptomics: To map SDR16C5 expression within the tumor microenvironment while preserving spatial context.

• CyTOF/mass cytometry: For simultaneous protein-level analysis of SDR16C5 and other markers across thousands of individual cells.

• Single-cell ATAC-seq: To investigate chromatin accessibility at the SDR16C5 locus in different cell populations.

These approaches would:

• Reveal heterogeneity in SDR16C5 expression within tumors

• Identify associations with cellular states (stemness, EMT, drug resistance)

• Map interactions between SDR16C5-expressing cells and immune populations

• Track expression changes during disease progression

What are the most promising approaches for developing SDR16C5 inhibitors?

Development of specific SDR16C5 inhibitors would require:

• Structure-based drug design: Modeling the protein structure (if crystal structure unavailable) and performing virtual screening of compound libraries.

• High-throughput screening: Testing chemical libraries for inhibitors of SDR16C5 enzymatic activity.

• Fragment-based approaches: Identifying small chemical fragments that bind to SDR16C5 and optimizing them into lead compounds.

• Rational design based on substrate analogs: Developing competitive inhibitors based on knowledge of natural substrates.

• Antibody-based approaches: Developing function-blocking antibodies for potential therapeutic use.

The most effective development pipeline would include:

• Target validation in multiple models

• Structure-activity relationship studies

• ADMET (absorption, distribution, metabolism, excretion, toxicity) optimization

• In vivo proof-of-concept studies

What bioinformatic pipelines are recommended for analyzing SDR16C5 across multi-omics datasets?

For comprehensive analysis of SDR16C5 across multi-omics datasets, researchers should implement:

• Integrated data analysis: Combining transcriptomics (TCGA, GEO), proteomics (CPTAC), and clinical data as demonstrated in SDR16C5 research in pancreatic cancer .

• Correlation analysis: Identifying genes that correlate with SDR16C5 expression (positively or negatively) across different cancers using the CCLE database .

• Pathway enrichment: Performing GO and KEGG analyses for differentially expressed SDR16C5-associated genes to identify functional pathways .

• Survival analysis: Using Kaplan-Meier methods and time ROC analysis to evaluate prognostic significance .

• Immune infiltration analysis: Employing the immunedeconv R package to correlate SDR16C5 expression with immune cell populations .

For robust results:

• Apply appropriate normalization methods for cross-platform comparisons

• Implement rigorous statistical testing with multiple comparison corrections

• Validate key findings across independent datasets

• Visualize results effectively using tools like R's ggplot2 and pheatmap packages

How can researchers validate contradictory findings about SDR16C5 function?

When encountering contradictory findings about SDR16C5 function, researchers should:

• Carefully assess methodological differences: Compare cell lines, knockdown efficiency, experimental conditions, and analytical approaches.

• Consider tissue-specific effects: SDR16C5 may function differently across cancer types or even within cancer subtypes.

• Validate with multiple approaches: Combine in vitro, in vivo, and patient data analysis to build a comprehensive picture.

• Perform reproducibility studies: Repeat key experiments using standardized protocols across different laboratories.

• Integrate contextual factors: Consider microenvironmental influences, genetic background, and signaling context.

A systematic validation approach would include:

• Independent replication of key findings

• Use of multiple cell lines and model systems

• Application of complementary methodologies

• Careful attention to technical details like antibody specificity and knockdown efficiency

What criteria should be used to select patient populations for SDR16C5-targeted clinical trials?

For clinical trials targeting SDR16C5, patient selection criteria should include:

• SDR16C5 expression level: Prioritize patients with high SDR16C5 expression, as higher expression correlates with poorer survival .

• Cancer type: Initially focus on cancers with established SDR16C5 overexpression, such as pancreatic cancer, laryngeal carcinoma, and colorectal cancer .

• Biomarker validation: Develop and validate assays to accurately measure SDR16C5 expression in patient samples.

• Pathway activation: Consider status of related pathways, such as IL-17 signaling, which may interact with SDR16C5 function .

• Prior treatment history: Define appropriate line of therapy based on preclinical evidence.

Stratification factors might include:

• HPV status, given evidence of differential SDR16C5 expression

• Tumor stage and grade

• Immune infiltration patterns

• Specific genetic alterations (e.g., KRAS mutations in pancreatic cancer)

What combination therapy approaches might synergize with SDR16C5 inhibition?

Based on SDR16C5's functional roles, several combination approaches warrant investigation:

• Immunotherapy combinations: Given SDR16C5's association with immune response and the IL-17 signaling pathway , combining SDR16C5 inhibition with immune checkpoint inhibitors might enhance efficacy.

• Apoptosis inducers: Since SDR16C5 knockdown promotes apoptosis by affecting Bcl-2, cleaved caspase 3, and cleaved caspase 9 , combination with BH3 mimetics or other apoptosis-inducing agents could be synergistic.

• Anti-EMT agents: SDR16C5 silencing interrupts epithelial-mesenchymal transition , suggesting combinations with other EMT inhibitors might effectively prevent metastasis.

• Conventional chemotherapy: Evaluating whether SDR16C5 inhibition sensitizes cancer cells to standard chemotherapy agents.

• Retinoid-based therapies: Given SDR16C5's role in retinol metabolism , combining with retinoid pathway modulators might yield synergistic effects.

Rational design of combinations should be based on:

• Mechanistic understanding of pathway interactions

• Preclinical evidence of synergy

• Non-overlapping toxicity profiles

• Biomarker strategies for patient selection