CDK16 Human

What is CDK16 and how does it differ from conventional CDKs?

CDK16, also known as PCTAIRE1 or PCTK1, is an atypical member of the cyclin-dependent kinase family. Unlike conventional CDKs that contain the classic "PSTAIRE" motif in their αC helix, CDK16 features a distinctive "PCTAIRE" sequence motif that is conserved in its close relatives CDK17 and CDK18 . This structural difference contributes to its unique functions beyond typical cell cycle regulation. CDK16 plays key roles in neurite outgrowth, vesicle trafficking, and has emerged as a critical regulator in cancer cell proliferation . The human genome contains 21 genes encoding CDKs and an additional 5 genes encoding CDKL kinases, with CDK16 belonging to a functionally distinct subfamily .

How is CDK16 activated in cellular processes?

CDK16 activation occurs through a distinctive mechanism involving binding to membrane-associated protein cyclin Y (CCNY) or its homologue cyclin Y-like 1 (CCNYL1) . This interaction is facilitated by a phosphorylation-dependent 14-3-3 protein interaction, which differs from the activation mechanisms of classical CDKs . The kinase domain of CDK16 is flanked by N- and C-terminal extensions that play regulatory roles in its activation and cellular localization. This activation process enables CDK16 to phosphorylate its substrates using a unique consensus motif that differs from conventional CDKs, allowing it to regulate distinct cellular pathways .

What is the normal expression pattern of CDK16 in human tissues?

CDK16 shows a tissue-specific expression pattern in normal human tissues. Based on data from the Genotype-Tissue Expression (GTEx) project, CDK16 is expressed at varying levels across different tissue types . While the search results don't provide the complete tissue distribution pattern, studies have indicated that CDK16 is particularly significant in neuronal tissues, where it participates in neurite outgrowth and vesicle trafficking . Understanding the normal expression pattern provides a baseline for recognizing dysregulation in pathological conditions like cancer, where CDK16 is frequently overexpressed compared to matched normal tissues .

What methodologies are used to study CDK16 expression in cancer?

Researchers employ multiple complementary approaches to study CDK16 expression in cancer:

• Transcriptomic analysis: RNA-seq data from databases like TCGA and GTEx are commonly used to assess CDK16 mRNA expression across multiple cancer types, as demonstrated in pan-cancer studies .

• Quantitative RT-PCR: This technique provides validated measurement of CDK16 expression differences between tumor and adjacent normal tissues, as employed in endometrial cancer studies .

• Immunohistochemistry: Used to visualize and quantify CDK16 protein expression in patient tissue samples, allowing for correlation with clinicopathological features .

• In vitro functional studies: CDK16 knockdown experiments using shRNA or siRNA in cancer cell lines (such as H1299 lung cancer cells) help determine its functional role in cancer cell viability and proliferation .

• Correlation analyses: Statistical methods including Spearman's or Pearson's tests are applied to correlate CDK16 expression with clinical parameters, immune cell infiltration levels, and expression of other genes in the tumor microenvironment .

These methodologies collectively provide a comprehensive assessment of CDK16's role and potential as a biomarker in various cancer types.

How does CDK16 expression correlate with cancer prognosis?

In endometrial cancer specifically, CDK16 expression was found to be significantly higher in tumor tissues compared to adjacent normal tissues, and this elevated expression correlated with pathological stage and histological grade but not with age or weight . This indicates that CDK16 plays a key role in EC progression and could serve as a valuable prognostic indicator.

What molecular mechanisms underlie CDK16's role in cancer progression?

CDK16 promotes cancer progression through multiple interconnected mechanisms:

These mechanisms collectively contribute to CDK16's oncogenic functions across various cancer types, making it a promising target for cancer therapy.

How can researchers effectively knock down CDK16 expression in experimental models?

Effective CDK16 knockdown can be achieved through several approaches:

• Short hairpin RNA (shRNA): Studies have successfully used specific CDK16 shRNAs to downregulate its expression in cancer cell lines. For example, researchers used two specific CDK16 shRNAs to knock down CDK16 in H1299 lung cancer cells, which resulted in significant reduction in cell viability as measured by Cell Counting Kit-8 (CCK8) assays . This approach provides stable long-term knockdown suitable for extended studies.

• Small interfering RNA (siRNA): As mentioned in the context of non-small cell lung cancer studies, siRNA targeting CDK16 can effectively reduce its expression for short-term experiments . This approach is particularly useful for initial screening and acute knockdown experiments.

• CRISPR-Cas9 genome editing: While not explicitly mentioned in the search results, CRISPR-Cas9 technology represents a cutting-edge approach for creating CDK16 knockout models that can provide complete elimination of CDK16 expression for comprehensive functional studies.

• Pharmacological inhibition: The study of CDK16 inhibitors like dabrafenib and rebastinib provides an alternative approach to functional knockdown through chemical means . This can complement genetic approaches by allowing dose-dependent and reversible inhibition.

When designing CDK16 knockdown experiments, researchers should consider including appropriate controls, validating knockdown efficiency at both mRNA and protein levels, and assessing phenotypic effects through relevant functional assays such as proliferation, cell cycle, and apoptosis assays.

What are the current approaches for targeting CDK16 in cancer therapy research?

Current approaches for targeting CDK16 in cancer therapy research include:

• Kinase inhibitors: The ATP-binding pocket of CDK16 can accommodate both type I and type II kinase inhibitors . Screening CDK16 against different inhibitor libraries has identified compounds with potential therapeutic value. The multitargeted cancer drugs dabrafenib and rebastinib have been identified as potent CDK16 inhibitors in both cell-free and cell-based assays .

• Structure-based drug design: Crystal structures of CDK16 in complex with inhibitors like indirubin E804 and rebastinib have revealed an inactive DFG-out binding conformation, providing valuable insights for structure-based drug design . The unique structural features of CDK16 can be exploited to develop more selective inhibitors.

• Combination therapy approaches: Evidence suggests that targeting CDKs in addition to conventional platinum medications may significantly improve treatment effectiveness for cancers like ovarian cancer . This combination approach could potentially overcome resistance mechanisms and enhance therapeutic efficacy.

• CDK16-immune pathway targeting: Given CDK16's role in shaping the immunosuppressive tumor microenvironment and influencing immunotherapy efficacy, combining CDK16 inhibition with immune checkpoint inhibitors represents a promising research direction .

• CDK16-p27 axis targeting: Research in non-small cell lung cancer suggests that targeting the CDK16-p27 axis may provide an effective therapeutic strategy , indicating that pathway-specific approaches could yield more selective anti-cancer effects.

These diverse approaches highlight the potential of CDK16 as a therapeutic target and provide a foundation for developing more effective cancer treatments.

How can the relationship between CDK16 and the tumor immune microenvironment be effectively studied?

To effectively study the relationship between CDK16 and the tumor immune microenvironment, researchers can employ a multi-faceted approach:

• Integrated bioinformatic analysis: Utilize databases like TIMER2 and ImmuCellAI to assess correlations between CDK16 expression and immune cell infiltration levels across various cancer types . This approach can identify broad patterns and generate hypotheses for further investigation.

• Gene Set Enrichment Analysis (GSEA): Apply GSEA using Pearson correlation coefficients to assess the link between CDK16 and immune-related genes and pathways . This can reveal functional associations and regulatory networks involving CDK16 in the immune context.

• Correlation studies with immune markers: Perform detailed correlation analyses between CDK16 and various immune-related genes, including:

  • Immunosuppressive genes

  • Immune activation genes

  • Chemokines and their receptors

  • Major Histocompatibility Complex (MHC) genes

• In vitro co-culture experiments: Design co-culture systems with cancer cells (with manipulated CDK16 expression) and various immune cell populations to directly observe how CDK16 levels affect immune cell behavior, activation, and function.

• In vivo models with immune profiling: Develop animal models with modulated CDK16 expression and perform comprehensive immune profiling of the tumor microenvironment using techniques like flow cytometry, single-cell RNA sequencing, and spatial transcriptomics.

• Immunotherapy response studies: Analyze the correlation between CDK16 expression and response to immunotherapy using clinical datasets, and validate findings in preclinical models with CDK16 modulation combined with immune checkpoint inhibitors .

This integrated approach can provide a comprehensive understanding of how CDK16 shapes the tumor immune microenvironment and influences immunotherapy outcomes, potentially leading to new therapeutic strategies.

What are the key structural features of CDK16 that distinguish it for drug development?

CDK16 possesses several distinctive structural features that make it an interesting target for drug development:

• Unique PCTAIRE motif: CDK16 contains a characteristic "PCTAIRE" sequence in its αC helix, which differs from the classical "PSTAIRE" motif found in conventional CDKs like CDK2 . This unique motif contributes to its specific binding interactions and activation mechanisms.

• Conformational plasticity: Crystal structures of CDK16 reveal considerable conformational flexibility, suggesting that the isolated CDK16 kinase domain is relatively unstable in the absence of a cyclin partner . This plasticity may be exploited for the development of selective inhibitors.

• DFG-out binding conformation: CDK16 can adopt an inactive DFG-out binding conformation, as confirmed by crystal structures in complex with inhibitors like indirubin E804 and rebastinib . This conformation is particularly relevant for type II kinase inhibitor design.

• Dual inhibitor accommodation: The ATP-binding pocket of CDK16 can accommodate both type I and type II kinase inhibitors , providing versatility in drug development approaches and allowing for diverse chemical scaffolds to be explored.

• N- and C-terminal extensions: CDK16 contains N- and C-terminal extensions flanking its central kinase domain , which may offer additional sites for allosteric modulation or selective targeting beyond the catalytic domain.

These structural characteristics, particularly the ability to adopt a DFG-out conformation and accommodate different inhibitor types, present unique opportunities for developing selective CDK16 inhibitors with potential applications in cancer therapy.

What are the current known inhibitors of CDK16 and their mechanisms of action?

Several inhibitors of CDK16 have been identified through screening and structural studies:

• Dabrafenib: This multitargeted cancer drug has been identified as one of the most potent CDK16 inhibitors in both cell-free and cell-based assays . While primarily known as a BRAF inhibitor, its activity against CDK16 represents an important off-target effect that may contribute to its clinical efficacy.

• Rebastinib: Another multitargeted cancer drug shown to potently inhibit CDK16 . The crystal structure of CDK16 in complex with rebastinib revealed that it binds to an inactive DFG-out conformation of the kinase , classifying it as a type II inhibitor.

• Indirubin E804: This compound forms a complex with CDK16, also stabilizing the DFG-out conformation . Indirubin derivatives have been studied extensively as CDK inhibitors and may provide a scaffold for developing more selective CDK16-targeted compounds.

• Type I and Type II kinase inhibitors: The ATP-binding pocket of CDK16 can accommodate both types of inhibitors , expanding the chemical space for potential CDK16-targeting compounds. Type I inhibitors typically bind to the active conformation, while type II inhibitors, like rebastinib, stabilize the inactive conformation.

The mechanisms of action primarily involve competitive binding to the ATP-binding site, with some inhibitors specifically stabilizing the inactive DFG-out conformation of the kinase. The structural insights gained from these inhibitor complexes provide valuable information for the development of more selective CDK16 inhibitors with improved pharmacological properties.

How should researchers interpret conflicting data on CDK16 expression across different cancer types?

When faced with conflicting data on CDK16 expression across different cancer types, researchers should consider several factors and employ specific analytical approaches:

By considering these factors and employing a multi-faceted analytical approach, researchers can better interpret seemingly conflicting data and develop a more nuanced understanding of CDK16's role across different cancer types.

How can CDK16 be validated as a prognostic biomarker in clinical settings?

Validating CDK16 as a prognostic biomarker in clinical settings requires a systematic approach:

• Multi-cohort validation: Confirm the prognostic value of CDK16 in independent patient cohorts across different geographic regions and healthcare settings. Current studies have already established CDK16 as a risk factor for poor prognosis in multiple cancer types through univariate Cox regression analyses and Kaplan-Meier survival analyses .

• Multivariate analysis: Conduct multivariate analyses to determine if CDK16 provides independent prognostic information beyond established clinical factors. This should include:

  • Adjustment for clinicopathological features (age, stage, grade)

  • Consideration of treatment regimens

  • Inclusion of other molecular markers

• Standardized detection methods: Develop and validate standardized assays for CDK16 detection in clinical samples. This could include:

  • Immunohistochemistry protocols with validated antibodies

  • Quantitative RT-PCR assays

  • RNA-seq-based expression signatures

• Establishment of cutoff values: Define optimal cutoff values for categorizing patients into high and low CDK16 expression groups. Current studies have used median expression as the cutoff , but more sophisticated approaches like receiver operating characteristic (ROC) curve analysis may provide more clinically relevant thresholds.

• Integration into prognostic models: Develop integrated prognostic models that incorporate CDK16 expression with other relevant biomarkers and clinical factors. The established nomogram for endometrial cancer that accurately predicts recurrence represents a successful example of this approach .

• Prospective clinical validation: Conduct prospective studies to validate the prognostic value of CDK16 in real-time clinical decision-making, assessing whether CDK16-based stratification leads to improved patient outcomes.

• Analytical and clinical validation: Follow the guidelines for biomarker development, including analytical validation (assay reproducibility, precision, and accuracy) and clinical validation (demonstration of clinical utility in the intended use population).

By following this comprehensive validation approach, CDK16 could be established as a reliable prognostic biomarker with potential applications in clinical decision-making for cancer patients.

What is the relationship between CDK16 and immunotherapy response?

The relationship between CDK16 expression and immunotherapy response represents an important emerging area of research:

This relationship highlights the potential of CDK16 not only as a prognostic biomarker but also as a predictive biomarker for immunotherapy response and a potential target for improving immunotherapy outcomes in cancer patients.

How does CDK16 interact with the cell cycle machinery in normal versus cancer cells?

The interaction between CDK16 and cell cycle machinery differs significantly between normal and cancer cells:

• Normal cell function: In normal cells, CDK16 plays regulated roles in:

  • Ensuring accurate DNA duplication and homogeneous distribution to daughter cells

  • Mediating precise gene expression regulation necessary for healthy growth

  • Contributing to vesicle trafficking and neurite outgrowth in specialized cell types

• Cancer cell dysregulation: In cancer cells, CDK16 is frequently overexpressed and contributes to dysregulated proliferation through:

  • Altered p27-dependent mechanisms, as demonstrated in non-small cell lung cancer and cutaneous squamous cell carcinoma

  • Enhanced cell cycle progression, evidenced by reduced cancer cell viability following CDK16 knockdown

  • Promotion of transcriptional dysregulation that facilitates cancer emergence and spread

• Activation mechanisms: CDK16 is activated through binding to cyclin Y via a phosphorylation-dependent 14-3-3 interaction . This activation mechanism may be amplified or dysregulated in cancer cells, contributing to their increased proliferative capacity.

• Substrate specificity: CDK16 has a unique consensus substrate phosphorylation motif compared with conventional CDKs , which may result in phosphorylation of distinct targets in the cell cycle machinery, potentially bypassing normal regulatory checkpoints in cancer cells.

• Interaction with tumor suppressors: The relationship between CDK16 and p27, a key cell cycle inhibitor, appears particularly important in cancer contexts . Disruption of this relationship may contribute to the ability of cancer cells to evade cell cycle checkpoints.

Understanding these differential interactions between normal and cancer contexts is crucial for developing therapeutic strategies that selectively target cancer cells while minimizing effects on normal cellular functions. Further mechanistic studies comparing normal and cancer cell models would help elucidate the full spectrum of CDK16's role in cell cycle dysregulation during carcinogenesis.

What are the potential roles of CDK16 in autophagy regulation?

While the search results provide limited direct information on CDK16's role in autophagy, one reference specifically mentions "New tricks of an old autophagy regulator: AMPK-dependent regulation of autophagy through CCNY (cyclin Y)-CDK16" . This suggests an emerging research area connecting CDK16 to autophagy regulation through several potential mechanisms:

• AMPK-CDK16-CCNY axis: The mentioned publication suggests a relationship between AMP-activated protein kinase (AMPK), a master regulator of cellular energy homeostasis and autophagy, and the CCNY-CDK16 complex. This connection indicates that CDK16 may participate in energy-sensing pathways that regulate autophagy.

• Cell cycle-autophagy crosstalk: Given CDK16's established role in cell cycle regulation, it may function at the intersection of cell cycle and autophagy pathways, potentially coordinating these processes during cellular stress or nutrient deprivation.

• Vesicle trafficking connection: CDK16's known role in vesicle trafficking could extend to autophagosome formation or maturation, as both processes involve complex membrane dynamics and trafficking machinery.

• Cancer context relevance: Dysregulation of autophagy is a hallmark of many cancers, and CDK16's overexpression in multiple cancer types suggests that its role in autophagy regulation may contribute to cancer cell survival and therapeutic resistance.

• Therapeutic implications: Understanding CDK16's role in autophagy could reveal new therapeutic opportunities, particularly in combining CDK16 inhibitors with autophagy modulators for enhanced anti-cancer effects.

This represents an emerging research direction that warrants further investigation through focused studies on the mechanistic connections between CDK16, its binding partners, and the core autophagy machinery in both normal and pathological contexts.

How does CDK16 sensitize cancer cells to TNF family cytokines?

The search results mention "PCTAIRE1-Knockdown Sensitizes Cancer Cells to TNF Family Cytokines" , suggesting an important relationship between CDK16 and TNF-mediated cell death pathways. Although detailed mechanisms aren't fully described in the provided materials, we can infer several potential mechanisms:

• Apoptotic pathway regulation: CDK16 may normally suppress apoptotic pathways triggered by TNF family cytokines. When CDK16 is knocked down, this suppression is relieved, making cancer cells more susceptible to TNF-induced cell death.

• NF-κB signaling modulation: TNF family cytokines activate NF-κB signaling, which typically promotes cell survival. CDK16 might enhance this pro-survival pathway, and its knockdown could shift the balance toward cell death pathways.

• Cell cycle checkpoint interaction: CDK16's role in cell cycle regulation might influence how cells respond to death signals. In certain cell cycle phases, cells may be more vulnerable to TNF-induced apoptosis, and CDK16 knockdown could increase the proportion of cells in these vulnerable phases.

• Death receptor expression or function: CDK16 might regulate the expression or functionality of TNF family receptors, and its knockdown could enhance receptor availability or downstream signaling.

• Therapeutic potential: This sensitization effect suggests that combining CDK16 inhibitors with TNF family cytokines or agonists could represent a promising therapeutic strategy, particularly for cancers resistant to conventional treatments.

This area represents an important direction for further research, as understanding the precise mechanisms could lead to novel therapeutic combinations leveraging both CDK16 inhibition and TNF pathway activation for enhanced cancer cell killing.

What computational approaches are most effective for predicting potential CDK16 inhibitors?

While the search results don't explicitly detail computational approaches for predicting CDK16 inhibitors, we can infer effective strategies based on the structural and inhibitor information provided:

• Structure-based virtual screening: The available crystal structures of CDK16 in complex with inhibitors like indirubin E804 and rebastinib provide valuable templates for structure-based virtual screening campaigns. Molecular docking against these structures, particularly focusing on the ATP-binding pocket, can identify potential inhibitors from large compound libraries.

• Pharmacophore modeling: The known inhibitors of CDK16, including dabrafenib and rebastinib , can be used to develop pharmacophore models that capture the essential features required for CDK16 inhibition. These models can then guide the design or identification of novel inhibitors with similar binding properties.

• Machine learning approaches: The development of machine learning models trained on known CDK16 inhibitors and non-inhibitors could enable more accurate prediction of potential new inhibitors. These models could incorporate molecular descriptors, fingerprints, or structural features derived from the crystal structures.

• Molecular dynamics simulations: Given the conformational plasticity of CDK16 noted in the crystal structures , molecular dynamics simulations could help understand the dynamic binding properties and identify transient binding pockets that might not be evident in static crystal structures.

• Fragment-based approaches: The ability of CDK16 to accommodate both type I and type II inhibitors suggests that fragment-based drug design approaches could be particularly effective, allowing the exploration of diverse chemical scaffolds targeting different binding modes.

• Selectivity modeling: Computational approaches that specifically address selectivity against other CDKs would be valuable, leveraging the unique "PCTAIRE" motif and structural features of CDK16 to design inhibitors with reduced off-target effects.

These computational approaches, especially when combined with experimental validation, can accelerate the discovery and development of selective CDK16 inhibitors for research and potential therapeutic applications.

What are the most promising directions for future CDK16 research in cancer?

Based on the current understanding of CDK16 in cancer, several promising research directions emerge:

• Therapeutic targeting: Development of selective CDK16 inhibitors represents a key research priority, leveraging the unique structural features and inhibitor binding properties of CDK16 . These could serve as both research tools and potential therapeutic agents.

• Biomarker validation: Further validation of CDK16 as a prognostic and predictive biomarker across different cancer types, with standardized assessment methods and defined cutoff values, would enhance its clinical utility .

• Immunotherapy combinations: Exploring the combination of CDK16 inhibition with immunotherapy, based on the observed relationship between CDK16 expression and immunotherapy response, could lead to improved treatment strategies for cancer patients .

• Mechanism elucidation: Deeper investigation into the precise mechanisms through which CDK16 regulates cancer cell proliferation, apoptosis, and the tumor immune microenvironment would provide valuable insights for targeted intervention .

• Synthetic lethality approaches: Identifying synthetic lethal interactions with CDK16 inhibition could reveal novel combination strategies that selectively target cancer cells while sparing normal tissues.

• Resistance mechanisms: Understanding how cancers might develop resistance to CDK16-targeted therapies would be crucial for designing effective treatment strategies and identifying appropriate biomarkers for patient selection.

• Pan-cancer analyses: Expanding comprehensive pan-cancer analyses to identify cancer types most likely to benefit from CDK16-targeted approaches and to understand context-specific functions of CDK16 across different malignancies .

These research directions, pursued in parallel, would significantly advance our understanding of CDK16's role in cancer and potentially lead to new therapeutic strategies for improving patient outcomes.

How might CDK16 research inform our understanding of other atypical CDKs?

CDK16 research provides valuable insights into the broader family of atypical CDKs and their roles in cellular processes and disease:

• Structural insights: The unique structural features of CDK16, including the "PCTAIRE" motif shared with CDK17 and CDK18 , can inform our understanding of activation mechanisms and inhibitor binding properties across this subfamily of atypical CDKs.

• Functional diversity: CDK16's roles beyond classical cell cycle regulation, including vesicle trafficking, neurite outgrowth, and immune modulation , highlight the functional diversity of atypical CDKs and suggest similar expanded roles for related family members.

• Cancer relevance: The significant role of CDK16 in multiple cancer types suggests that other atypical CDKs may similarly contribute to cancer pathogenesis, potentially through distinct but complementary mechanisms.

• Activation mechanisms: The cyclin Y-dependent activation of CDK16 through phosphorylation-dependent 14-3-3 interactions represents a non-canonical activation mechanism that may be shared or paralleled in other atypical CDKs.

• Therapeutic approaches: Successful strategies for targeting CDK16, including the development of selective inhibitors that exploit its unique structural features , could serve as templates for targeting other atypical CDKs with therapeutic potential.

• Biomarker applications: The utility of CDK16 as a prognostic biomarker across multiple cancer types suggests that other atypical CDKs might similarly serve as valuable biomarkers in specific disease contexts.

By advancing our understanding of CDK16, researchers can develop conceptual frameworks and experimental approaches that facilitate the study of other atypical CDKs, potentially uncovering new biological insights and therapeutic opportunities across this important kinase family.

What methodological advances would accelerate CDK16 research?

Several methodological advances would significantly accelerate CDK16 research:

• Improved structural biology techniques: Advanced cryo-electron microscopy approaches could help resolve the full-length structure of CDK16 including its regulatory domains and in complex with its activators like cyclin Y, providing deeper insights into activation mechanisms and inhibitor design.

• Development of selective chemical probes: Highly selective CDK16 inhibitors with well-characterized cellular activities would serve as valuable chemical probes for dissecting CDK16 functions across different cellular contexts and disease models.

• Single-cell analysis methods: Application of single-cell transcriptomics and proteomics to study CDK16 expression and activity at the single-cell level would reveal cell type-specific functions and heterogeneity in cancer contexts.

• Spatially resolved techniques: Methodologies that provide spatial information about CDK16 expression, activation, and interactions within tissues would enhance our understanding of its context-dependent functions in the tumor microenvironment.

• Improved animal models: Development of conditional knockout models and knockin models with fluorescent or affinity tags would facilitate the study of CDK16 in specific tissues and developmental contexts.

• Phosphoproteomics advances: Enhanced phosphoproteomic approaches would help identify the complete set of CDK16 substrates and their context-dependent regulation, providing a more comprehensive view of CDK16's signaling network.

• AI-driven data integration: Artificial intelligence approaches for integrating multi-omics data related to CDK16 could reveal non-obvious connections and generate novel hypotheses about its functions and therapeutic targeting.

• High-throughput functional genomics: Application of CRISPR screens and other functional genomics approaches could identify synthetic lethal interactions and genetic dependencies related to CDK16, informing combination therapy strategies.