HSD17B6 Antibody

What is HSD17B6 and what are its primary biological functions?

HSD17B6 (Hydroxysteroid 17-Beta Dehydrogenase 6) is a NAD-dependent oxidoreductase enzyme with remarkably broad substrate specificity. It demonstrates both oxidative and reductive activity in vitro and plays significant roles in steroid metabolism. The enzyme exhibits 17-beta-hydroxysteroid dehydrogenase activity toward various steroids, converting 5-alpha-androstan-3-alpha,17-beta-diol to androsterone and estradiol to estrone. Additionally, it possesses 3-alpha-hydroxysteroid dehydrogenase activity towards androsterone and retinol dehydrogenase activity towards all-trans-retinol in vitro experimental settings. Functionally, HSD17B6 can convert androsterone to epi-androsterone through a two-step process: first oxidizing androsterone to 5-alpha-androstane-3,17-dione and then reducing it to epi-androsterone . This enzyme can act on both C-19 and C-21 3-alpha-hydroxysteroids, highlighting its versatility in steroid metabolism pathways.

What types of HSD17B6 antibodies are available for research applications?

Several types of HSD17B6 antibodies are available for research, primarily varying in host species, clonality, binding specificity, and conjugation status. Polyclonal rabbit antibodies targeting different epitopes of HSD17B6 are common, including those directed against the N-terminal region and specific amino acid sequences (AA 1-317, AA 61-160, AA 178-317). Other available options include mouse-host polyclonal antibodies. Most commercially available antibodies are unconjugated, though some biotin-conjugated variants exist for specialized applications . The diversity in available antibodies allows researchers to select the most appropriate option based on their specific experimental requirements, target species, and intended applications.

Which experimental applications are HSD17B6 antibodies suitable for?

HSD17B6 antibodies demonstrate utility across multiple experimental applications. Western Blotting (WB) is supported by most available antibodies, allowing for protein expression analysis and quantification. Immunohistochemistry (IHC) applications include both paraffin-embedded (IHC-P) and frozen section (IHC-fro) methodologies, enabling tissue localization studies . Some antibodies are additionally validated for ELISA (Enzyme-Linked Immunosorbent Assay), providing quantitative analysis options. More specialized applications include flow cytometry (FACS) and immunofluorescence for both cell cultures (IF-cc) and paraffin sections (IF-p) . When selecting an antibody for a specific application, researchers should verify the validation status for their particular experimental context and tissue/species of interest.

What species reactivity can be expected from HSD17B6 antibodies?

HSD17B6 antibodies exhibit varying degrees of cross-reactivity across species. Most commercially available antibodies demonstrate confirmed reactivity with human samples, making them suitable for clinical and translational research . Many antibodies also show cross-reactivity with mouse and rat samples, facilitating comparative studies and the use of rodent models. Some antibodies offer broader reactivity profiles that include dog, cow, horse, guinea pig, rabbit, and hamster samples . This cross-species functionality stems from conserved epitope regions across mammalian HSD17B6 proteins. When working with less common species or when cross-reactivity is critical to experimental design, researchers should carefully review the antibody's validated species reactivity profile or conduct preliminary validation studies.

How should researchers optimize HSD17B6 antibody dilutions for Western blotting and immunohistochemistry?

For optimal Western blotting results with HSD17B6 antibodies, researchers should conduct a systematic dilution series starting with manufacturer recommendations (typically 1:500 to 1:2000). The optimization process should evaluate signal-to-noise ratio, band specificity, and reproducibility across multiple experimental runs. For immunohistochemistry applications, start with a conservative dilution (e.g., 1:1000 as used successfully with ab272668 for human liver and testis tissues) and adjust based on staining intensity and background levels. Tissue-specific optimizations may be necessary, as HSD17B6 expression varies considerably across tissues.

A methodological approach includes:

• Perform initial dilution series (e.g., 1:500, 1:1000, 1:2000, 1:5000)

• Evaluate specificity using appropriate positive controls (liver or testis tissue recommended)

• Include negative controls (primary antibody omission and isotype controls)

• Assess background staining and signal-to-noise ratio

• Validate reproducibility with technical replicates

• Consider tissue-specific adjustments based on HSD17B6 expression levels

Remember that blocking reagents, incubation times, and detection systems will significantly impact optimal dilution determinations.

What controls are essential when validating HSD17B6 antibody specificity for novel applications?

Rigorous validation of HSD17B6 antibody specificity requires a comprehensive control strategy:

• Positive tissue controls: Human liver and testis tissues demonstrate reliable HSD17B6 expression and should be included as positive controls .

• Negative controls:

  • Primary antibody omission controls to assess non-specific binding of secondary antibodies

  • Isotype controls to evaluate background from primary antibody host species

  • Tissues known to lack HSD17B6 expression

• Molecular specificity controls:

  • Pre-absorption with immunizing peptide to confirm epitope specificity

  • siRNA or CRISPR knockdown of HSD17B6 in relevant cell lines to confirm signal reduction

  • Overexpression systems to verify signal enhancement

• Cross-reactivity assessment:

  • Parallel testing with multiple HSD17B6 antibodies targeting different epitopes

  • Western blot verification of molecular weight specificity (expected ~35 kDa band)

  • Mass spectrometry validation of immunoprecipitated proteins

• Species validation:

  • When applying antibodies to new species, sequence comparison of epitope regions

  • Gradual dilution series to identify optimal conditions for cross-species applications

These controls collectively ensure that observed signals genuinely represent HSD17B6 rather than non-specific binding or cross-reactivity with related proteins.

How can researchers effectively use HSD17B6 antibodies to investigate its role in tumor suppression?

Given HSD17B6's emerging role as a potential tumor suppressor, particularly in lung adenocarcinoma (LUAD) , researchers can employ several antibody-based approaches to investigate this function:

• Expression analysis in clinical samples:

  • Implement tissue microarray (TMA) immunohistochemistry to correlate HSD17B6 expression with clinical parameters across large patient cohorts

  • Compare expression between tumor and matched adjacent normal tissues using carefully calibrated quantitative IHC methods

  • Correlate expression with tumor stage, differentiation status, and patient outcomes

• Mechanistic studies:

  • Use immunoprecipitation with HSD17B6 antibodies followed by mass spectrometry to identify novel protein interactions

  • Employ proximity ligation assays to confirm interactions with PTEN and AKT pathway components identified in previous studies

  • Investigate subcellular localization changes during malignant transformation using immunofluorescence

• Functional validation studies:

  • Analyze expression changes in HSD17B6-overexpressing or knockdown cell models using Western blotting

  • Monitor EMT marker alterations (E-cadherin, N-cadherin, vimentin) following HSD17B6 modulation

  • Evaluate changes in AKT phosphorylation and downstream effectors

• Pathway analysis integration:

  • Combine antibody-based detection with transcriptomic profiling to identify HSD17B6-regulated genes

  • Investigate correlations between HSD17B6 expression and key oncogenic pathways using multiplex IHC

These approaches, when properly controlled and executed with validated antibodies, can significantly advance understanding of HSD17B6's role in tumor suppression mechanisms.

How can researchers investigate the interplay between HSD17B6 and steroid hormone metabolism using antibody-based approaches?

Investigating HSD17B6's role in steroid metabolism requires sophisticated antibody-based methodologies:

• Enzyme activity correlation studies:

  • Combine enzymatic activity assays with quantitative Western blotting to correlate HSD17B6 protein levels with functional enzyme activity

  • Develop dual immunohistochemistry/activity staining protocols to simultaneously visualize protein expression and enzymatic function in tissue sections

• Substrate-specific expression patterns:

  • Implement multiplex immunofluorescence to co-localize HSD17B6 with steroid hormone receptors and metabolic intermediates

  • Correlate tissue-specific expression patterns with local steroid concentrations measured by mass spectrometry

• Regulatory feedback mechanisms:

  • Use phospho-specific and post-translational modification antibodies to characterize HSD17B6 regulation

  • Employ ChIP-seq with antibodies against potential transcriptional regulators of HSD17B6

• Metabolic complex assembly:

  • Apply proximity ligation assays to detect interactions between HSD17B6 and other steroid-metabolizing enzymes

  • Utilize immunoprecipitation followed by activity assays to isolate functional enzyme complexes

Methodological considerations include using appropriate fixation techniques that preserve both protein epitopes and enzymatic activity, implementing careful controls for antibody specificity, and correlating antibody-based findings with orthogonal techniques like mass spectrometry-based metabolomics.

What approaches can resolve contradictory findings when studying HSD17B6 expression across different tissues or disease states?

Contradictory findings regarding HSD17B6 expression are not uncommon in research literature. Resolving these discrepancies requires a systematic methodological approach:

• Epitope mapping and antibody comparison:

  • Compare results from multiple antibodies targeting different HSD17B6 epitopes (N-terminus vs. central regions vs. C-terminus)

  • Conduct epitope masking experiments to identify potential context-dependent accessibility issues

• Isoform-specific analysis:

  • Design primers and antibodies specifically targeting known HSD17B6 isoforms

  • Correlate protein detection with transcript variant analysis to identify potential translation or splicing variations

• Methodological standardization:

  • Implement identical sample processing, antigen retrieval, and detection systems across comparative studies

  • Establish quantitative calibration curves using recombinant protein standards

  • Include internal expression controls across experimental batches

• Orthogonal validation:

  • Corroborate antibody-based findings with mRNA quantification methods

  • Implement mass spectrometry-based proteomic validation

  • Use CRISPR-engineered cell lines with epitope-tagged endogenous HSD17B6 as reference standards

• Contextual variables consideration:

  • Systematically evaluate the impact of tissue fixation conditions, processing times, and storage duration

  • Account for potential post-translational modifications affecting epitope recognition

  • Consider microenvironmental factors (pH, redox state) affecting protein conformation

This comprehensive approach can help distinguish genuine biological variations from technical artifacts, leading to more consistent and reliable HSD17B6 expression data.

How should researchers approach epitope mapping for HSD17B6 antibodies to ensure optimal detection of functionally relevant protein regions?

Strategic epitope mapping for HSD17B6 antibodies requires understanding both the protein's functional domains and potential conformational changes:

• Functional domain correlation:

  • Select antibodies targeting distinct functional regions (substrate-binding domain, catalytic site, protein interaction interfaces)

  • For comprehensive analysis, utilize antibodies recognizing the N-terminal region (such as those raised against amino acids MWLYLAAFVGLYYLLHWYRERQVVSHLQDKYVFITGCDSGFGNLLARQLD) , the mid-region (AA 61-160), and C-terminal domains (AA 178-317)

• Structural considerations:

  • Evaluate epitope accessibility in native protein conformations using non-denaturing detection methods

  • Compare linear versus conformational epitope recognition using native versus denatured protein preparations

• Systematic epitope mapping methodology:

  • Employ peptide array technology to precisely identify antibody binding sites

  • Generate truncated protein fragments for progressive epitope refinement

  • Use site-directed mutagenesis to identify critical binding residues

• Cross-reactivity prevention:

  • Conduct in silico analysis of epitope uniqueness across the SDR (short-chain dehydrogenase/reductase) family

  • Experimentally validate specificity against closely related proteins (other HSD17B family members)

• Application-specific epitope selection:

  • For detecting enzyme-substrate interactions, prioritize antibodies with epitopes distant from the active site

  • For monitoring protein-protein interactions, select antibodies recognizing regions outside interaction interfaces

This methodical approach ensures that selected antibodies will provide meaningful data relevant to the specific HSD17B6 functions under investigation.

How can HSD17B6 antibodies be employed to investigate its emerging role as a tumor suppressor in lung adenocarcinoma and other cancers?

Recent research has revealed HSD17B6's potential role as a tumor suppressor, particularly in lung adenocarcinoma (LUAD) . Researchers can employ several advanced antibody-based strategies to further investigate this function:

• Comprehensive tissue profiling:

  • Implement large-scale tissue microarray analysis across multiple cancer types to establish expression patterns

  • Correlate HSD17B6 expression with clinical outcomes using quantitative digital pathology

  • Compare expression patterns across tumor progression stages and metastatic sites

• Mechanism elucidation:

  • Utilize co-immunoprecipitation with HSD17B6 antibodies to identify novel interacting partners

  • Apply proximity ligation assays to confirm interactions with PTEN and components of the AKT/GSK3β/β-catenin pathway

  • Investigate subcellular redistribution during malignant transformation using super-resolution microscopy

• Signaling pathway integration:

  • Develop multiplex phospho-protein assays to simultaneously monitor HSD17B6 expression and AKT pathway activation

  • Employ reverse phase protein arrays for high-throughput analysis of signaling networks affected by HSD17B6 modulation

  • Correlate protein expression with transcriptional changes in EMT markers (CDH1, CDH2) and invasion-associated genes (MMP2, MMP9)

• Therapeutic response prediction:

  • Investigate HSD17B6 expression as a potential biomarker for radiotherapy response in LUAD patients

  • Develop quantitative IHC scoring systems calibrated against patient outcomes

  • Implement spatial analysis to evaluate tumor heterogeneity and its impact on treatment response

These approaches can significantly advance our understanding of HSD17B6's tumor-suppressive functions and potentially lead to new diagnostic or therapeutic strategies.

What methodological considerations are important when using HSD17B6 antibodies to investigate cellular responses to radiotherapy?

Research suggests HSD17B6 may influence radioresistance in lung adenocarcinoma , making it a potential biomarker for treatment response. When investigating this relationship with antibody-based methods, several specialized considerations apply:

• Temporal expression analysis:

  • Implement time-course studies following radiation exposure with standardized fixation protocols

  • Consider both acute (0-24h) and delayed (24-96h) expression changes

  • Compare expression patterns between single and fractionated radiation schedules

• Spatial heterogeneity assessment:

  • Utilize multiplexed immunofluorescence to analyze HSD17B6 expression relative to hypoxia markers and proliferation indices

  • Implement digital spatial profiling to identify microenvironmental factors affecting expression

  • Consider intra-tumoral variation in expression and its impact on localized radiation response

• Functional correlation methodology:

  • Correlate HSD17B6 expression with DNA damage repair markers (γH2AX, 53BP1) following radiation

  • Analyze co-expression with apoptosis markers to evaluate cell fate decisions

  • Implement clonogenic survival assays in parallel with expression analysis

• Technical adjustments for irradiated samples:

  • Optimize antigen retrieval protocols for irradiated tissues, which may exhibit altered protein-protein crosslinking

  • Include appropriate positive controls from standardized cell lines with known radiation responses

  • Consider potential radiation-induced post-translational modifications affecting epitope recognition

• Quantitative approach standardization:

  • Develop rigorous scoring systems calibrated against radiation dose and survival outcomes

  • Implement digital image analysis algorithms to ensure objective quantification

  • Establish standard reference materials for inter-laboratory calibration

These methodological considerations will help researchers establish reliable correlations between HSD17B6 expression and radiotherapy response, potentially improving treatment stratification.

How can emerging antibody technologies enhance HSD17B6 research beyond traditional Western blotting and immunohistochemistry?

Several cutting-edge antibody technologies can significantly enhance HSD17B6 research:

• Single-cell protein analysis:

  • Implement mass cytometry (CyTOF) with HSD17B6 antibodies to analyze expression at single-cell resolution

  • Apply cyclic immunofluorescence to evaluate co-expression with multiple pathway components

  • Utilize imaging mass cytometry to preserve spatial context while achieving single-cell resolution

• Live-cell dynamics:

  • Develop cell-permeable antibody fragments or nanobodies for monitoring HSD17B6 in living cells

  • Apply FRET-based biosensors incorporating anti-HSD17B6 antibody fragments to monitor protein-protein interactions

  • Implement optogenetically controlled intrabodies to modulate HSD17B6 function with spatiotemporal precision

• Spatial transcriptomics integration:

  • Combine in situ sequencing with immunofluorescence to correlate HSD17B6 protein expression with local transcriptional profiles

  • Implement Digital Spatial Profiling with HSD17B6 antibodies to analyze protein expression in defined tissue regions

  • Utilize multiplexed ion beam imaging (MIBI) for high-parameter analysis of HSD17B6 in complex tissue microenvironments

• Antibody-based enzymatic modulation:

  • Develop activity-modulating antibodies that can enhance or inhibit HSD17B6 catalytic function

  • Create bifunctional antibodies linking HSD17B6 to specific subcellular compartments

  • Engineer antibody-enzyme fusions for targeted modification of HSD17B6 or its substrates

• Antibody-guided proteomics:

  • Implement proximity-dependent biotinylation with HSD17B6 antibodies to identify novel interaction partners

  • Apply antibody-guided chromatin profiling to identify genomic binding sites and transcriptional regulatory functions

  • Utilize antibody-based selective isolation for targeted metabolomics of HSD17B6-associated steroid compounds

These innovative approaches expand research possibilities beyond traditional methods, enabling deeper insights into HSD17B6 biology and function.

How should researchers interpret discrepancies between HSD17B6 antibody-based protein detection and mRNA expression data?

Discrepancies between protein and mRNA levels are common in HSD17B6 research and require systematic analysis:

• Methodological validation:

  • Confirm antibody specificity using multiple detection methods and controls

  • Verify mRNA detection specificity with appropriate primers targeting different transcript regions

  • Implement absolute quantification standards for both protein and mRNA measurements

• Post-transcriptional regulation analysis:

  • Investigate microRNA-mediated regulation, particularly miR-31-5p which has been shown to negatively regulate HSD17B6 expression

  • Assess transcript stability through actinomycin D chase experiments

  • Analyze alternative splicing patterns using isoform-specific detection methods

• Post-translational considerations:

  • Evaluate protein stability using cycloheximide chase experiments

  • Investigate potential proteolytic processing affecting antibody epitope recognition

  • Assess subcellular localization differences that might affect extraction efficiency

• Systematic interpretation framework:

  • Consider time-course studies to identify temporal delays between transcription and translation

  • Implement mathematical modeling to account for known regulatory mechanisms

  • Develop integrated analysis pipelines that normalize protein and mRNA data to appropriate reference standards

• Biological context integration:

  • Evaluate tissue-specific regulatory mechanisms affecting translation efficiency

  • Consider disease-specific alterations in protein metabolism

  • Analyze microenvironmental factors affecting protein stability

This comprehensive approach can help researchers distinguish genuine biological regulatory mechanisms from technical artifacts when interpreting discrepancies between protein and mRNA data.

What statistical approaches are recommended for quantifying HSD17B6 expression differences across experimental conditions?

Proper statistical analysis of HSD17B6 expression requires careful consideration of data characteristics and experimental design:

• Appropriate test selection:

  • For normally distributed data with equal variances, use parametric tests (t-test for two groups, ANOVA for multiple groups)

  • For non-normally distributed data, apply non-parametric alternatives (Mann-Whitney U, Kruskal-Wallis)

  • For paired samples (e.g., tumor vs. adjacent normal), use paired tests

  • For complex designs with multiple factors, implement mixed-effects models

• Sample size considerations:

  • Conduct a priori power analysis based on expected effect sizes from preliminary data

  • For clinical samples, consider retrospective power analysis to interpret negative findings

  • Implement sequential analysis approaches for resource-intensive experiments

• Data normalization strategies:

  • For Western blot quantification, normalize to appropriate loading controls (avoid using single housekeeping genes)

  • For IHC scoring, implement standardized scoring systems (H-score, Allred score) calibrated against control tissues

  • For multiplexed assays, use internal reference standards and batch correction algorithms

• Advanced analytical approaches:

  • Apply principal component analysis to identify patterns across multiple parameters

  • Implement clustering algorithms to identify sample subgroups based on expression patterns

  • Develop multivariate models incorporating clinical and experimental variables

• Reporting standards:

  • Present complete statistical details including test selection justification

  • Report effect sizes and confidence intervals in addition to p-values

  • Implement standardized visualization approaches (box plots with individual data points, violin plots)

  • Address multiple testing correction when analyzing HSD17B6 alongside other markers

Proper statistical analysis ensures that reported differences in HSD17B6 expression are robust and biologically meaningful.

How can HSD17B6 antibodies be incorporated into clinical diagnostic workflows for cancer prognostication?

The potential prognostic significance of HSD17B6 in cancers like lung adenocarcinoma suggests value in developing standardized diagnostic applications:

• Clinical assay development:

  • Select antibody clones demonstrating robust performance across diverse sample types and processing conditions

  • Establish standardized immunohistochemistry protocols optimized for automated staining platforms

  • Develop digital image analysis algorithms for objective quantification

  • Create calibration standards for inter-laboratory harmonization

• Scoring system standardization:

  • Define clinically relevant cut-points through correlation with patient outcomes

  • Implement multi-parameter scoring incorporating intensity, percentage positivity, and subcellular localization

  • Validate scoring systems across independent patient cohorts

  • Establish quality control measures for routine diagnostic implementation

• Integration with existing biomarkers:

  • Develop multiplex IHC panels combining HSD17B6 with established prognostic markers

  • Create integrated risk assessment models incorporating multiple biomarkers

  • Validate predictive performance through prospective clinical studies

  • Establish synergistic and redundant relationships with existing biomarkers

• Specialized clinical applications:

  • Investigate utility for predicting radiotherapy response in lung cancer patients

  • Evaluate applications in treatment selection for steroid hormone-dependent cancers

  • Assess value in monitoring treatment response and disease recurrence

• Implementation considerations:

  • Develop standard operating procedures for pre-analytical variables (fixation time, processing methods)

  • Establish external quality assessment programs for laboratory performance

  • Create reporting templates incorporating evidence-based interpretation guidelines

  • Design clinician education resources explaining the biological significance of HSD17B6 expression

These developments could help translate HSD17B6's biological significance into clinically actionable information for patient stratification and treatment planning.

What are the critical quality control parameters for developing HSD17B6 antibody-based diagnostic assays?

Developing robust diagnostic assays based on HSD17B6 antibodies requires rigorous quality control across multiple parameters:

• Analytical validation metrics:

  • Determine limit of detection through serial dilution studies

  • Establish reproducibility through intra- and inter-laboratory testing

  • Quantify precision using coefficient of variation across multiple runs

  • Assess accuracy through correlation with orthogonal methods

  • Evaluate analytical specificity through cross-reactivity testing

• Pre-analytical variable control:

  • Standardize tissue fixation duration (24-48 hours in 10% neutral buffered formalin)

  • Establish maximum acceptable tissue age for reliable detection

  • Define requirements for pre-treatment steps (antigen retrieval methods and conditions)

  • Develop protocols addressing specimen heterogeneity

• Reference standard development:

  • Create cell line microarrays with known HSD17B6 expression levels

  • Develop synthetic peptide standards for antibody calibration

  • Establish consensus positive and negative control tissues

  • Implement digital reference images for scoring calibration

• Technical performance monitoring:

  • Design run controls detecting assay drift

  • Implement Levey-Jennings charts for longitudinal performance tracking

  • Establish acceptability criteria for control performance

  • Develop troubleshooting protocols for common failure modes

• Clinical validation parameters:

  • Define ranges for healthy, benign, and malignant tissues

  • Establish clinical sensitivity and specificity for intended use

  • Determine positive and negative predictive values in target populations

  • Evaluate robustness across diverse patient demographics

These quality control measures ensure that HSD17B6 antibody-based assays generate reliable and clinically meaningful results when implemented in diagnostic settings.

How might future research leverage HSD17B6 antibodies to explore its potential role in treatment resistance mechanisms?

Emerging evidence suggests HSD17B6 may influence treatment responses, particularly radioresistance in lung cancer . Future research can leverage antibody-based approaches to explore this potential:

• Therapy response prediction:

  • Develop quantitative IHC protocols correlating pre-treatment HSD17B6 expression with therapeutic outcomes

  • Implement serial sampling strategies to monitor expression changes during treatment

  • Create multiplex panels combining HSD17B6 with DNA damage response and apoptosis markers

  • Apply spatial analysis methods to evaluate expression in treatment-resistant tumor regions

• Resistance mechanism elucidation:

  • Use co-immunoprecipitation to identify therapy-induced changes in HSD17B6 protein interactions

  • Implement ChIP-seq with antibodies against potential transcriptional regulators of HSD17B6

  • Apply CRISPR screens combined with antibody-based detection to identify synthetic lethal interactions

  • Utilize phospho-specific antibodies to monitor therapy-induced signaling changes

• Novel therapeutic targeting strategies:

  • Develop activity-modulating antibodies or antibody-drug conjugates targeting HSD17B6

  • Explore nanobody-based approaches for intracellular targeting

  • Investigate combination therapies specifically addressing HSD17B6-mediated resistance mechanisms

  • Create bifunctional antibodies linking HSD17B6 to pro-apoptotic signaling components

• Translational research methodology:

  • Establish patient-derived organoid models with preserved HSD17B6 expression patterns

  • Develop humanized mouse models with native HSD17B6 regulation

  • Implement high-content screening platforms incorporating HSD17B6 antibody-based readouts

  • Create computational models integrating antibody-based expression data with transcriptomic and metabolomic profiles

These research directions could significantly advance our understanding of HSD17B6's role in treatment resistance and potentially lead to novel therapeutic strategies targeting these mechanisms.