DTYMK Human

What is DTYMK and what is its primary function in human cells?

DTYMK (deoxythymidylate kinase), also known as thymidylate kinase (TMPK), is a nuclear-encoded enzyme that catalyzes the phosphorylation of deoxythymidine monophosphate (dTMP) to form deoxythymidine diphosphate (dTDP). This reaction represents a critical step in DNA synthesis, as it is the first merged step of both salvage and de novo pathways in the production of deoxythymidine triphosphate (dTTP), which is an essential material for DNA synthesis . The enzyme requires ATP and Mg²⁺ as cofactors for this catalytic activity . DTYMK comprises three important structural domains: the ligand-induced degradation (LID) domain, nucleoside monophosphate (NMP) binding site, and the CORE domain .

How is DTYMK expression regulated in normal human tissues?

DTYMK expression can be detected in all human tissues, though at varying levels, as it is essential for DNA synthesis and cellular proliferation . The enzyme serves as a key component in pyrimidine metabolism, functioning as a rate-limiting enzyme that controls dTTP production . In normal cells, DTYMK expression is tightly regulated during the cell cycle, with increased expression typically occurring during S-phase when DNA replication is active. The precise mechanisms regulating DTYMK expression in normal tissues involve complex transcriptional and post-transcriptional controls that respond to cellular proliferation cues and nucleotide pool balances .

What experimental methods are most reliable for measuring DTYMK expression in human tissue samples?

Researchers studying DTYMK expression in human tissues commonly employ several complementary techniques:

• Quantitative PCR (qPCR): For measuring DTYMK mRNA expression levels in tissues with high sensitivity and specificity .

• Western blot analysis: For detecting and quantifying DTYMK protein levels using specific antibodies .

• Immunohistochemistry (IHC): For visualizing DTYMK protein expression patterns within tissue contexts and assessing spatial distribution .

• RNA sequencing (RNA-seq): For comprehensive transcriptomic analysis of DTYMK expression in relation to other genes .

• Proteomics analysis: Using mass spectrometry-based approaches to quantify DTYMK protein levels across tissues .

For reliable results, researchers should consider using multiple methods in parallel and include appropriate controls for tissue-specific expression patterns and potential technical variabilities.

How does DTYMK expression differ between cancer and normal tissues?

DTYMK shows significant expression differences between cancer and normal tissues across multiple cancer types. Comprehensive pan-cancer analyses have revealed that DTYMK is abnormally expressed in most human cancers compared to their corresponding normal tissues . Specifically:

• DTYMK is significantly upregulated in 26 cancer types based on analyses integrating TCGA and GTEx databases .

• DTYMK is downregulated only in kidney chromophobe (KICH) and acute myeloid leukemia (LAML) .

• Paired tissue analysis confirmed DTYMK upregulation in 15 tumor types compared to adjacent normal tissues .

• DTYMK expression in cancer cell lines (from CCLE database) shows consistently higher levels than normal tissues .

These findings suggest that DTYMK overexpression is a common feature across most human malignancies, indicating its potential role in cancer development and progression.

What is the prognostic significance of DTYMK expression in human cancers?

DTYMK expression has emerged as a significant prognostic indicator across multiple cancer types:

These findings consistently indicate that abnormally high DTYMK expression is associated with worse clinical outcomes across numerous cancer types.

What molecular mechanisms explain DTYMK's role in cancer progression?

DTYMK contributes to cancer progression through multiple molecular mechanisms:

• Metabolic function in DNA synthesis: As a key enzyme in dTTP production, DTYMK supports the increased DNA synthesis requirements of rapidly proliferating cancer cells .

• Cell cycle regulation: DTYMK can regulate the cell cycle to promote cancer cell proliferation, particularly demonstrated in hepatocellular carcinoma .

• ceRNA mechanism: In HCC, DTYMK functions as a competing endogenous RNA (ceRNA) by competitively binding miR-378a-3p, which maintains the expression of MAPK activated protein kinase 2 (MAPKAPK2) .

• Signaling pathway activation: Through its ceRNA activity, DTYMK activates the phospho-heat shock protein 27 (phospho-HSP27)/nuclear factor NF-kappaB (NF-κB) axis, which:

  • Mediates drug resistance

  • Promotes tumor cell proliferation

  • Facilitates infiltration of tumor-associated macrophages by inducing CCL5 expression

• Immune microenvironment modulation: DTYMK expression correlates with infiltration of six immune cell types (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells), suggesting it influences tumor immune microenvironment .

• Functional cellular states: Single-cell analysis reveals that DTYMK expression correlates with malignant cellular functional states, including cell cycle progression, DNA damage responses, DNA repair, invasion, epithelial-mesenchymal transition (EMT), and proliferation .

These multifaceted mechanisms highlight DTYMK's importance beyond its canonical enzymatic function, revealing its roles in broader regulatory networks affecting cancer biology.

How effective is DTYMK as a diagnostic biomarker for cancer detection?

Research indicates that DTYMK has considerable potential as a diagnostic biomarker across multiple cancer types:

• Diagnostic accuracy: Analysis using receiver operating characteristic (ROC) curves has shown that DTYMK expression can effectively differentiate between tumor and normal tissues in most cancer types . Time-dependent ROC analysis has specifically demonstrated DTYMK's predictive accuracy in liver hepatocellular carcinoma (LIHC) and lung adenocarcinoma (LUAD) .

• Pan-cancer applicability: DTYMK's consistent overexpression pattern across 26 cancer types suggests broad applicability as a diagnostic marker . Its diagnostic potential appears particularly strong in hepatocellular carcinoma, where significant expression differences between tumor and normal tissues have been repeatedly observed .

• Correlation with diagnostic parameters: DTYMK expression correlates with established diagnostic parameters such as tumor stages and grades, particularly in HCC, reinforcing its potential clinical utility .

While DTYMK shows promise as a diagnostic biomarker, clinical implementation would require standardization of detection methods, establishment of appropriate cutoff values, and validation in large prospective cohorts with diverse patient demographics.

What are the most robust methodological approaches for validating DTYMK as a prognostic marker?

To rigorously validate DTYMK as a prognostic marker, researchers should employ these methodological approaches:

• Multi-cohort validation:

  • Analysis across independent patient cohorts from different geographical regions and ethnic backgrounds

  • Inclusion of both retrospective and prospective study designs

  • Utilization of multiple data sources (TCGA, GTEx, clinical trial cohorts, institutional biobanks)

• Statistical validation:

  • Univariate and multivariate Cox regression analyses to establish independent prognostic value

  • Kaplan-Meier survival analysis with appropriate stratification methods

  • Concordance index (C-index) calculation to assess discriminative ability

  • Competing risk models to account for other causes of mortality

• Combinatorial marker assessment:

  • Integration with established clinical prognostic factors

  • Development of composite prognostic scores incorporating DTYMK

  • Comparison with existing prognostic models to demonstrate added value

• Mechanistic validation:

  • Correlation of DTYMK expression with functional cellular states (cell cycle, DNA damage, etc.)

  • Association with treatment responses in clinical settings

  • Evaluation in relevant preclinical models to confirm causative relationships

• Technical considerations:

  • Standardization of detection methods (qPCR, IHC, etc.)

  • Establishment of appropriate cutoff values for high vs. low expression

  • Assessment of intratumoral heterogeneity through spatial analysis

Following these methodological approaches would provide robust evidence for DTYMK's prognostic utility and facilitate its translation into clinical applications.

How does DTYMK's prognostic value compare across different cancer types?

DTYMK's prognostic significance varies across cancer types, with some consistent patterns emerging from pan-cancer analyses:

The prognostic significance of DTYMK appears most robust in hepatocellular carcinoma and lung adenocarcinoma, where multiple independent studies have confirmed its association with poor survival outcomes and advanced clinical features . The mechanistic basis for these cancer-specific differences may relate to varying dependencies on nucleotide metabolism pathways, different roles of DTYMK in tumor-specific molecular networks, or cancer-specific microenvironmental factors that interact with DTYMK-related pathways.

What are the most effective methods for manipulating DTYMK expression in experimental models?

Researchers have employed several effective techniques to modulate DTYMK expression in experimental cancer models:

• RNA interference (RNAi) approaches:

  • Short hairpin RNA (shRNA) has been successfully used to achieve stable DTYMK knockdown in hepatocellular carcinoma cells, resulting in significant inhibition of tumor growth in vitro and in vivo .

  • Small interfering RNA (siRNA) for transient DTYMK knockdown to study acute effects on cellular phenotypes and molecular pathways.

• CRISPR-Cas9 gene editing:

  • Complete DTYMK knockout models to study loss-of-function effects.

  • CRISPR interference (CRISPRi) for tunable repression of DTYMK expression.

  • CRISPR activation (CRISPRa) systems for upregulation studies.

• Viral vector systems:

  • Lentiviral or adenoviral vectors for efficient delivery of expression-modulating constructs.

  • Inducible expression systems (e.g., Tet-On/Tet-Off) for temporal control of DTYMK expression.

• Overexpression models:

  • Plasmid-based overexpression of wild-type DTYMK.

  • Expression of tagged DTYMK variants (e.g., FLAG, HA, GFP) for localization and interaction studies.

• Pharmacological inhibition:

  • Small molecule inhibitors targeting DTYMK enzymatic activity.

  • Nucleoside analogs that interfere with DTYMK substrate recognition.

Each approach has specific advantages depending on the research question. For studying DTYMK's role in cancer progression, combining in vitro manipulation with in vivo models (e.g., xenografts or genetically engineered mouse models) provides the most comprehensive insights into its biological functions and therapeutic potential .

How can researchers effectively study the role of DTYMK in immune infiltration and tumor microenvironment?

To investigate DTYMK's relationship with immune infiltration and the tumor microenvironment, researchers should consider these methodological approaches:

• Bioinformatic analysis of public datasets:

  • TIMER algorithm application to analyze correlations between DTYMK expression and six types of immune infiltrates (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells) .

  • CIBERSORT analysis for detailed immune cell composition assessment.

  • TISIDB database interrogation to explore associations with lymphocytes, immunomodulators, and chemokines .

• Multi-parameter flow cytometry and mass cytometry (CyTOF):

  • Quantification and phenotyping of tumor-infiltrating immune cells in DTYMK-high versus DTYMK-low tumors.

  • Analysis of immune activation markers and checkpoint molecule expression.

• Spatial transcriptomics and multiplex immunohistochemistry:

  • Co-localization analysis of DTYMK expression with immune cell infiltrates.

  • Spatial mapping of cytokine/chemokine expression patterns in relation to DTYMK expression.

• In vitro co-culture systems:

  • Co-culture of DTYMK-modulated tumor cells with immune cells (T cells, macrophages, etc.).

  • Conditioned media experiments to assess paracrine effects on immune cell recruitment and function.

• In vivo immune-competent models:

  • Syngeneic mouse models with DTYMK manipulation to study native immune responses.

  • Humanized mouse models to better recapitulate human immune-tumor interactions.

• Functional immune assays:

  • Cytotoxicity assays to measure immune cell killing of DTYMK-modulated tumor cells.

  • Cytokine/chemokine profiling to characterize immune signaling networks.

• Mechanistic validation:

  • Analysis of CCL5 expression and other chemokines induced by DTYMK-mediated NF-κB activation .

  • Assessment of tumor-associated macrophage recruitment and polarization in relation to DTYMK expression.

These approaches can systematically dissect DTYMK's immunomodulatory functions and identify potential intervention points for combined targeting of DTYMK and immune pathways.

What experimental designs best capture the competing endogenous RNA (ceRNA) function of DTYMK?

To effectively investigate DTYMK's ceRNA functions, researchers should implement the following experimental designs:

• Molecular interaction validation:

  • RNA immunoprecipitation (RIP) assays to confirm direct binding between DTYMK mRNA and miR-378a-3p .

  • Luciferase reporter assays with wild-type and mutated DTYMK 3'UTR to validate microRNA binding sites.

  • Cross-linking immunoprecipitation and sequencing (CLIP-seq) to identify all potential miRNA binding sites on DTYMK transcripts.

• Functional relationship studies:

  • Co-expression analysis of DTYMK and its putative ceRNA targets (e.g., MAPKAPK2) .

  • Rescue experiments in which miR-378a-3p inhibitors are used to reverse the effects of DTYMK knockdown.

  • Overexpression of DTYMK wild-type vs. microRNA binding site mutants to distinguish between protein-coding and ceRNA functions.

• Pathway analysis:

  • Assessment of downstream signaling (e.g., phospho-HSP27/NF-κB axis) in response to DTYMK ceRNA modulation .

  • Proteomics and phospho-proteomics to capture global changes resulting from DTYMK ceRNA functions.

  • ChIP-seq to identify transcriptional targets of effector pathways (e.g., NF-κB binding sites).

• Comprehensive ceRNA network mapping:

  • RNA-seq following DTYMK modulation to identify all potential ceRNA partners.

  • Competitive endogenous RNA database (ceRDB) analysis to predict DTYMK's broader ceRNA functions.

  • Construction of ceRNA networks specific to different cancer types.

• In vivo validation:

  • Creation of mouse models expressing DTYMK variants specifically lacking miRNA binding sites.

  • Therapeutic targeting of the DTYMK-miR-378a-3p-MAPKAPK2 axis in xenograft models.

These experimental designs collectively provide a robust framework for dissecting DTYMK's ceRNA functions separate from its enzymatic roles, offering a more complete understanding of its contributions to cancer pathophysiology .

What is the current evidence supporting DTYMK as a therapeutic target in cancer?

Current evidence strongly supports DTYMK as a promising therapeutic target in cancer:

• Knockdown effects on tumor growth:

  • DTYMK knockdown significantly inhibits the growth of hepatocellular carcinoma both in vitro and in vivo .

  • Growth inhibition and metabolic disorder have been observed in LKB1 mutant-related lung cancer following DTYMK depletion .

• Chemosensitization effects:

  • DTYMK knockdown increases sensitivity to oxaliplatin in HCC, suggesting potential for combination therapy approaches .

  • DTYMK modulation affects drug resistance pathways through the phospho-HSP27/NF-κB axis .

• Essential role in cancer cell viability:

  • As a critical enzyme in DNA synthesis, targeting DTYMK disrupts a fundamental process required for cancer cell proliferation .

  • DTYMK appears particularly important in rapidly proliferating cancers with high DNA synthesis demands.

• Selective overexpression in tumors:

  • DTYMK's significant upregulation in 26 cancer types compared to normal tissues provides a potential therapeutic window for selective targeting .

• Multiple cancer applications:

  • Evidence from pan-cancer analyses suggests that DTYMK targeting could be applicable across numerous cancer types, with particularly strong evidence in hepatocellular carcinoma and lung cancer .

• Multiple targetable mechanisms:

  • Beyond its enzymatic function, DTYMK's ceRNA activity and immune modulatory effects offer additional intervention points .

This collective evidence establishes DTYMK as a multifaceted cancer dependency with therapeutic potential across different targeting strategies and cancer types.

What approaches can be used to develop selective inhibitors of DTYMK?

Developing selective DTYMK inhibitors requires systematic approaches across multiple drug discovery paradigms:

• Structure-based drug design:

  • Leveraging the three known domains of DTYMK (LID domain, NMP binding site, and CORE domain) for rational inhibitor design .

  • Using crystallographic data to identify unique structural features that differentiate DTYMK from related kinases.

  • Molecular docking studies to predict binding modes of potential inhibitors.

• Active site targeting:

  • Development of ATP-competitive inhibitors that exploit the ATP-binding pocket of DTYMK.

  • Design of substrate (dTMP) analogs that compete for the active site.

  • Allosteric inhibitors that disrupt the conformational changes required for DTYMK catalysis.

• High-throughput screening approaches:

  • Biochemical assays measuring DTYMK enzymatic activity for compound library screening.

  • Cell-based phenotypic screens using DTYMK-dependent cancer models.

  • Fragment-based screening to identify chemical scaffolds with high ligand efficiency.

• Targeted degradation strategies:

  • Development of proteolysis-targeting chimeras (PROTACs) for DTYMK.

  • Molecular glue degraders that induce DTYMK protein degradation.

  • Ligand-induced degradation exploiting DTYMK's LID domain.

• RNA-based therapeutics:

  • siRNA or antisense oligonucleotides targeting DTYMK mRNA.

  • RNA-targeting small molecules that disrupt DTYMK's ceRNA functions.

• Selectivity optimization:

  • Profiling against related nucleotide kinases to ensure specificity.

  • Cellular target engagement studies to confirm on-target activity.

  • Toxicity assessment in normal cells to establish therapeutic window.

These approaches can be pursued in parallel and iteratively refined to develop potent and selective DTYMK inhibitors for cancer therapy.

What potential resistance mechanisms might emerge from DTYMK-targeted therapies?

Anticipating resistance mechanisms to DTYMK-targeted therapies can guide development of more effective treatment strategies:

• Pathway redundancy and bypass mechanisms:

  • Upregulation of alternative deoxynucleotide synthesis pathways.

  • Compensatory increases in thymidine kinase (TK) to enhance dTMP production via the salvage pathway.

  • Activation of nucleoside diphosphate kinase (NDK) to bypass DTYMK's role in dTDP phosphorylation.

• Target alterations:

  • Mutations in the DTYMK gene affecting inhibitor binding while preserving catalytic function.

  • Alternative splicing generating inhibitor-resistant DTYMK isoforms.

  • Genomic amplification of DTYMK leading to overexpression that overwhelms inhibitor concentrations.

• Molecular adaptation:

  • Rewiring of the ceRNA network to compensate for lost DTYMK ceRNA functions .

  • Activation of alternative signaling pathways that bypass the phospho-HSP27/NF-κB axis .

  • Upregulation of downstream effectors like MAPKAPK2 to maintain pathway activity despite DTYMK inhibition .

• Microenvironmental adaptations:

  • Changes in tumor-associated macrophage recruitment patterns independent of DTYMK-mediated mechanisms .

  • Alterations in immune infiltration patterns that become less dependent on DTYMK-regulated factors.

  • Stromal cell signaling that compensates for lost DTYMK functions in tumor cells.

• Cellular metabolic reprogramming:

  • Shifts in nucleotide metabolism that reduce dependence on the canonical dTMP-dTDP-dTTP pathway.

  • Alterations in cell cycle checkpoints that accommodate lower dTTP levels.

Understanding these potential resistance mechanisms can inform combination therapy strategies and sequential treatment approaches to maximize the clinical benefit of DTYMK-targeted interventions.

What are the most promising areas for future DTYMK research in cancer biology?

Several high-priority research areas could significantly advance our understanding of DTYMK in cancer:

• Comprehensive mechanistic dissection:

  • Further elucidation of DTYMK's dual roles as both an enzyme and a ceRNA regulator.

  • Investigation of cancer-specific DTYMK-dependent molecular networks.

  • Identification of additional microRNA interactions beyond miR-378a-3p .

• Immunomodulatory functions:

  • Detailed characterization of how DTYMK affects different immune cell populations.

  • Exploration of DTYMK's role in immunotherapy response prediction.

  • Development of combined DTYMK/immune checkpoint inhibition strategies.

• Therapeutic targeting innovations:

  • Development of first-in-class DTYMK inhibitors with optimized pharmacological properties.

  • Exploration of DTYMK degradation approaches.

  • Investigation of synthetic lethality interactions with DTYMK inhibition.

• Biomarker development:

  • Creation and validation of DTYMK-based diagnostic assays.

  • Development of companion diagnostics for future DTYMK-targeted therapies.

  • Integration of DTYMK into multi-parameter prognostic models.

• Metabolic interconnections:

  • Exploration of how DTYMK interfaces with broader cellular metabolic networks.

  • Investigation of metabolic vulnerabilities created by DTYMK inhibition.

  • Analysis of DTYMK's role in nucleotide pool balance and genomic stability.

• Clinical translation:

  • Initiation of early-phase clinical trials for DTYMK-targeted approaches.

  • Development of patient selection strategies based on DTYMK expression and pathway activation.

  • Investigation of potential biomarkers of response to DTYMK inhibition.

These research directions collectively represent promising avenues to translate the growing body of DTYMK knowledge into clinical applications.

How might single-cell analysis technologies advance our understanding of DTYMK function?

Single-cell technologies offer unique insights into DTYMK biology that complement traditional bulk approaches:

• Cellular heterogeneity characterization:

  • Revealing variable DTYMK expression across different cell populations within tumors.

  • Identifying rare cell subpopulations that are particularly dependent on DTYMK function.

  • Correlating DTYMK expression with stemness markers and differentiation states.

• Functional state associations:

  • Extending current findings on DTYMK's correlation with functional states (cell cycle, DNA damage, DNA repair, invasion, EMT, proliferation) .

  • Mapping DTYMK expression to detailed cell cycle phases at single-cell resolution.

  • Identifying transition states where DTYMK may play critical regulatory roles.

• Microenvironmental interactions:

  • Characterizing cell-type specific DTYMK expression patterns within the tumor microenvironment.

  • Spatial mapping of DTYMK-expressing cells relative to immune infiltrates.

  • Analyzing intercellular communication networks involving DTYMK-high cells.

• Treatment response dynamics:

  • Monitoring single-cell expression changes following DTYMK inhibition.

  • Identifying resistance-associated cell states that emerge during treatment.

  • Characterizing differential sensitivity to DTYMK targeting across heterogeneous tumor cell populations.

• Multi-omics integration:

  • Combining single-cell transcriptomics, proteomics, and metabolomics to create integrated views of DTYMK function.

  • Correlating DTYMK expression with chromosomal instability at single-cell resolution.

  • Mapping DTYMK-associated epigenetic states across tumor cell subpopulations.

Single-cell technologies can transform our understanding of DTYMK from a binary (high/low expression) view to a nuanced appreciation of its role within complex cellular ecosystems, potentially revealing new therapeutic opportunities.

What translational research is needed to move DTYMK-targeted therapies into clinical trials?

To advance DTYMK-targeted therapies toward clinical trials, several translational research priorities should be addressed:

• Lead compound development and optimization:

  • Identification and refinement of potent, selective DTYMK inhibitors with favorable pharmacokinetic properties.

  • Medicinal chemistry optimization for improved drug-like characteristics.

  • Development of biomarkers for pharmacodynamic assessment.

• Preclinical efficacy studies:

  • Comprehensive testing in diverse cancer models representing different cancer types with DTYMK overexpression.

  • Evaluation of monotherapy vs. combination approaches, particularly with standard-of-care chemotherapies like oxaliplatin .

  • Testing in models that recapitulate resistance to current therapies.

• Patient selection strategies:

  • Development of validated assays to quantify DTYMK expression/activity in patient samples.

  • Identification of molecular signatures beyond DTYMK expression that predict response.

  • Creation of companion diagnostic approaches for clinical trial enrichment.

• Toxicology and safety assessment:

  • Comprehensive evaluation of on-target toxicity in normal tissues with DTYMK expression.

  • Assessment of off-target effects and potential for drug-drug interactions.

  • Development of strategies to mitigate potential adverse effects.

• Biomarker development:

  • Validation of pharmacodynamic markers of DTYMK inhibition.

  • Identification of early response biomarkers predictive of clinical benefit.

  • Development of resistance markers to guide treatment adjustment.

• Clinical trial design optimization:

  • Creation of innovative trial designs appropriate for DTYMK-targeted therapies.

  • Development of endpoint strategies sensitive to DTYMK inhibition effects.

  • Planning for combination trials based on preclinical synergy data.

Addressing these translational research priorities will create a solid foundation for moving DTYMK-targeted therapeutic approaches into first-in-human clinical trials with optimized chances of success.