Pan-Cancer Landscape of CDK1 Uncovers Its Potential Prognostic Significance and Therapeutic Targeting in Adrenocortical Carcinoma
MOHD REHAN1,2*, FIROZ AHMED3*, MOHD SUHAIL1,2 and SHAZI SHAKIL2,4
1King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia;
2Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia;
3Translational Research Institute, Academic Health System, Hamad Medical Corporation, Doha, Qatar;
4Institute of Genomic Medicine Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia
Abstract
Background/Aim: Cyclin-dependent kinase 1 (CDK1) is a regulator of the G2-M transition whose dysregulation undermines cell-cycle fidelity and drives malignant growth. Although CDK1 has been implicated in tumorigenesis, its prognostic value varies by cancer type. Here we analyzed the prognostic landscape of CDK1 across human cancers and prioritized on therapeutic candidates for cancer types in which CDK1 is most strongly implicated.
Materials and Methods: We performed a pan-cancer analysis of CDK1 expression across 31 tumor types from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Project (GTEx), and tested associations with outcome by univariate Cox regression and Kaplan-Meier analysis. To translate these findings into therapeutic insights, we carried out structure-based virtual screening of a curated natural-product library against the CDK1 ATP-binding pocket and assessed predicted binding affinity.
Results: CDK1 was broadly overexpressed across multiple malignancies and high CDK1 expression associated with poorer survival in several tumor cohorts. Adrenocortical carcinoma (ACC) showed one of the strongest and most consistent prognostic associations, with CDK1 expression rising with advancing stage. Structure-based screening nominated five natural compounds namely, Salvianolic acid C, Salvianolic acid A, Calceolarioside B, Chicoric acid, and Plantagoside, as promising CDK1 kinase inhibitors and drug candidates for ACC. These compounds demonstrated favorable CDK1 binding and possess reported biological and anticancer activities, supporting their translational potential.
Conclusion: Our findings highlight CDK1 as a prognostic marker and a therapeutic target across multiple cancers, with particular relevance in ACC. By integrating pan-cancer transcriptomic analysis with structure-based drug discovery, this study not only emphasizes the clinical significance of CDK1 in ACC but also proposes natural compound-derived inhibitors as promising candidates for future therapeutic development.
Keywords: Cyclin-dependent kinase 1 (CDK1), adrenocortical carcinoma (ACC), pan-cancer analysis, prognostic biomarker, TCGA, transcriptomics, molecular docking, natural compounds, precision oncology, cell cycle regulator.
*These Authors equally contributed to this study.
☒ Mohd Rehan, King Fahd Medical Research Center, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Kingdom of Saudi
Arabia. Tel: +966 531368289, e-mail: mrtahir@kau.edu.sa, mrehan786@gmail.com; Firoz Ahmed, Translational Research Institute, Academic Health System, Hamad Medical Corporation, Doha 3050, Qatar. Tel: +974 70792792; e-mail: firoz.imtech@gmail.com
Introduction
Cyclin-dependent kinase 1 (CDK1), a serine/threonine kinase essential for eukaryotic cell division, governs the G2/M transition and mitotic progression through phosphorylation of key substrates. In complex with cyclin B, CDK1 phosphorylates nuclear lamins, histone H1, and microtubule-associated proteins to drive chromosome condensation, nuclear envelope breakdown, and mitotic spindle assembly (1,2). Its activity is tightly regulated: the Wee1 and Myt1 kinases inhibit CDK1 by phosphorylating Thr14 and Tyr15, while CDC25 phosphatases activate it by removing these inhibitory groups (3, 4). In normal cells, CDK1 peaks during mitosis to ensure accurate chromosome segregation and faithful cell replication. This precise control maintains genomic stability, whereas dysregulation promotes aberrant cell division and cancer development (5,6).
Loss of inhibitory control or CDK1 overexpression induces genomic instability, aneuploidy, and resistance to apoptosis, which are defining features of malignancy (4, 6). Additionally, CDK1 enhances tumor cell survival by phosphorylating apoptosis regulators such as BAD from the Bcl-2 family, enabling evasion of cell death under therapeutic or stress conditions (7, 8). These dual roles - sustaining proliferation while suppressing apoptosis - make CDK1 a critical driver of oncogenesis, though its impact varies across tumor types (9, 10). Elevated CDK1 gene expression is a recurrent feature in breast cancer (11), lung adenocarcinoma (12), melanoma (13) and colorectal cancer (14). However, its prognostic significance is context-dependent, with survival correlations varying across cancers (15).
To elucidate CDK1’s role across malignancies, we performed a pan-cancer analysis integrating RNA-seq data from The Cancer Genome Atlas (TCGA) and Genotype- Tissue Expression Project (GTEx) (16), comprising 9,736 tumor samples and 8,587 normal samples across 31 cancer types. The differential expression analysis was conducted to compare CDK1 levels between tumor and normal tissues (17). Then, we assessed CDK1’s prognostic significance and sought to identify tumor contexts in which its therapeutic
targeting may be most beneficial. Cox proportional hazards regression was applied to evaluate survival associations (18). These analyses revealed a prominent role of CDK1 in adrenocortical carcinoma (ACC), highlighting it as a compelling candidate for therapeutic intervention. Given the limited treatment options and poor prognosis associated with ACC, focusing on CDK1 provides an opportunity to uncover novel prognostic markers and therapeutic strategies in this aggressive malignancy.
Several CDK1 inhibitors, including Flavopiridol (19), Dinaciclib (20), Milciclib (21), and Roscovitine (22), have shown promise in preclinical and clinical studies. However, inconsistent efficacy and toxicities such as neutropenia highlight the need for tumor-specific approaches. Despite progress in other cancers, the therapeutic potential of CDK1 inhibition in ACC remains limited, underscoring the importance of investigating its prognostic and pharmacological relevance in this context (23,24). Natural products represent a promising reservoir for cancer therapy, offering favorable pharmacokinetic properties and reduced toxicity compared to many synthetic compounds (25-27).
In this study, we comprehensively evaluated CDK1 as a prognostic and therapeutic target across cancers, underscoring its particular relevance in ACC. Advances in structural biology and computational approaches have facilitated accurate prediction of inhibitor binding modes and the rational design of novel inhibitors (28-31). Leveraging these tools, we performed molecular docking- based virtual screening of a natural compound library to identify potential CDK1 inhibitors that could serve as lead candidates for ACC therapy. By integrating transcriptomic profiling with computational pharmacology, our work proposes a precision oncology-driven strategy for ACC, laying the foundation for preclinical validation and therapeutic development.
Materials and Methods
CDK1 expression analysis and its prognostic implications. To investigate the gene expression of CDK1 across various
cancer types, we utilized GEPIA2 with TCGA and GTEx dataset (17). We also explored the relationship between CDK1 expression and cancer progression by performing several analyses, including univariate Cox regression, Kaplan-Meier survival analysis, Gene Set Enrichment Analysis (GSEA), and CDK1 co-expression gene enrichment analysis. These analyses were conducted using the R Bioconductor package TCGAplot (version 4), integrated with R version 4.3.3 (32). This package provides a comprehensive set of tools for accessing, processing, and visualizing TCGA data, enabling a detailed examination of gene expression profiles and their correlation with clinical outcomes across different cancer types.
Data retrieval. The three-dimensional structure of CDK1 was retrieved from the Protein Data Bank (PDB) with the ID 5HQ0. This structure is in complex with a bound native inhibitor, providing confirmed catalytic site information essential for accurate docking studies. The compound library “20240913-L1400-Natural-Product-Library.SDF” used for screening was sourced from the Selleckchem, which contained 3048 natural product compounds. To obtain 3D structures for these compounds, their CAS IDs were cross-referenced with PubChem, resulting in 2265 compounds with available 3D conformations. To further refine the selection, compounds with a molecular weight of ≤500 Da were retained, resulting in 2,085 candidates for virtual screening. Of these, 2,050 compounds were successfully docked into the ATP binding site of CDK1 kinase and subsequently ranked according to their dock scores.
Virtual screening. The natural product compound library was screened against the CDK1 ATP binding site using molecular docking. DOCK v.6.9 (33) was utilized for the docking process, with initial protein and ligand preparation carried out in Chimera v.1.15 (34). The native inhibitor bound to CDK1 was used as a reference to identify the catalytic site, and a docking region was defined by selecting amino acids within a 5 Å radius of the
inhibitor. Based on dock scores and binding pose evaluations, the top five natural compounds were chosen for further investigation. The 2D structure illustrations of these selected compounds were generated using MarvinSketch v.21.8 (https://chemaxon.com/marvin).
Protein-ligand complex analysis. A comprehensive analysis was performed on the five selected CDK1-compound complexes. Protein-ligand interaction diagrams were generated, and non-bonded interactions, including hydrogen bonds, were assessed using LigPlot+ v.2.2.9 (35). The binding conformations of the complexes were visualized in PyMol v.3.1.0 (36). Additionally, binding energy and dissociation constants were determined using the empirical scoring program Xscore v.1.2.11 (37).
Results
The overall workflow of this study is summarized in Figure 1. The analysis began with a comprehensive pan- cancer assessment of CDK1 expression across multiple tumor types, which identified its strong prognostic significance in ACC. Subsequent analyses focused specifically on ACC to further explore the role of CDK1 and establish its potential as a therapeutic target. Finally, structure-based virtual screening of a curated natural compound library against the CDK1 active site led to the identification of five promising natural compounds as potential CDK1 inhibitors and drug candidates for ACC. The following sections present these findings in detail.
CDK1 expression profile across TCGA cancers. To gain a comprehensive understanding of CDK1 expression patterns, we analyzed its levels across all 31 cancer types covering 9,736 tumor samples and 8,587 normal samples in TCGA and GTEx dataset. The analysis revealed that CDK1 expression was significantly elevated in 18 cancer types (log2FC >2), including ACC, breast invasive carcinoma (BRCA), lung adenocarcinoma (LUAD), and uterine carcinosarcoma (UCS), as shown in Supplementary Figure S1. Nevertheless, the comprehensive TCGA analysis
CDK1 Analysis in Pan-cancer (TCGA)
Expression Analysis (GEPIA2)
Cox regression (TCGAplot)
Kaplan-Meier (KM) Plot (TCGAplot)
Stage Specific Expression (TCGAplot)
CDK1 as a potential prognostic biomarker in Adrenocortical carcinoma (ACC)
CDK1 Analysis in ACC
Gene Set Enrichment (TCGAplot)
Co-Expression Gene Enrichment (TCGAplot)
CDK1 promotes chromosomal instability and suppresses apoptosis in ACC
CDK1 as a potential therapeutic target in ACC
Virtual screening of natural compounds’ library against CDK1
Five natural compounds as potential CDK1 inhibitors and drug candidates for ACC
helped identify cancer types where CDK1 was consistently overexpressed, suggesting its potential as a therapeutic target in these malignancies.
Prognostic implications of CDK1 expression across TCGA cancers. To understand the prognostic value of CDK1 expression, a Cox univariate analysis using TCGAplot was conducted. The forest plot of hazard ratio showed that 12 cancer types, including ACC and Mesothelioma (MESO) exhibited poor prognosis with hazard ratios greater than 1 and p-values less than 0.05 (Supplementary Figure S2). Furthermore, Kaplan-Meier plots revealed that these cancer with high CDK1 expression had poorer overall
survival, with the effect being particularly pronounced in ACC (Figure 2A and Supplementary Figure S3). Further analysis of CDK1 expression across different stages of a cancer showed that its expression is increasing from stage 1 to stage 4 in ACC (Figure 2B), indicating its potential as a promising therapeutic target, especially in aggressive, late-stage cancers.
CDK1-driven chromosomal instability and apoptotic regulation in ACC. To investigate the biological functions associated with CDK1, we conducted GSEA analysis on differentially expressed genes between high and low CDK1 expression groups in ACC. The key Gene Ontology
A
KMplot of CDK1 in ACC
B
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expression=high -
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pathways linked to increased CDK1 expression were identified and depicted based on their Normalized Enrichment Scores. The results revealed that CDK1 primarily activates pathways involved in chromosome segregation, mitotic sister chromatid segregation, nuclear chromosome segregation, regulation of chromosome segregation, and sister chromatid segregation (Figure 2C).
Furthermore, the analysis of CDK1 co-expression patterns in ACC provided intriguing insights. Genes positively correlated with CDK1 expression were enriched in pathways governing chromosome segregation, underscoring CDK1’s central role in driving cell proliferation, a hallmark of cancer (Supplementary Figure S4). Conversely, Genes whose expression is negatively correlated with CDK1 are enriched for GO terms including ‘regulation of execution phase of apoptosis’. This might suggest that when CDK1 is highly expressed, the expression of genes that normally involve in apoptosis tends to be lower, potentially altering the balance of apoptosis regulation in favor of survival (Supplementary Figure S4). These findings highlight the possibility of involvement of CDK1 in promoting both aberrant cell division and evasion of programmed cell death, two critical factors, contributing to the relentless progression of ACC.
Virtual screening of natural compounds targeting CDK1 kinase. To identify potential CDK1 inhibitors, a structure- based virtual screening was carried out against a diverse natural compound library comprising 2,085 molecules. Of these, 2,050 compounds were successfully docked into the CDK1 active site. The compounds were ranked according to their dock scores (Supplementary Table S1), and the overall distribution of scores is illustrated in the histogram (Figure 3). Based on their docking performance, the top five natural compounds were shortlisted as promising CDK1 inhibitors. These compounds displayed binding affinities comparable to, or exceeding, that of the native inhibitor. They fit well in the CDK1 active site (Supplementary Figure S5) and formed a substantial number of stabilizing molecular interactions, including hydrogen bonds and hydrophobic contacts. Detailed binding interactions and affinity scores for each of the top five compounds are presented in the following sections.
Molecular docking analysis of top five natural compounds with CDK1 kinase. Salvianolic acid C (Figure 4A), having PubMed CID 13991590, ranked as the top-scoring compound, demonstrated strong binding affinity toward CDK1 with a binding energy of -10.39 kcal/mol, pKd value of 7.62 and dock score of -66.43, indicating a favorable interaction profile (Table I). The interaction analysis revealed that Salvianolic acid C engaged with 17 key residues within the CDK1 binding pocket (Table II). The primary interacting residues included Ile-10, Glu-12, Gly-13, Tyr-15, Val-18, Ala-31, Leu-83, Ser-84, Met-85, Asp-86, Lys- 89, Asp-128, Lys-130, Gln-132, Asn-133, Leu-135, and Asp- 146 (Figure 5, Table III). A total of 54 non-bonded contacts were observed, further stabilizing the ligand within the binding pocket. Additionally, two hydrogen bonds, Ser-84 (3.12 Å) and Asp-86 (2.89 Å), contributed significantly to the binding stability (Table II, Figure 5). These interactions suggest a strong binding affinity that may contribute to the compound’s inhibitory potential against CDK1.
Salvianolic Acid A (Figure 4B), having CID 5281793, ranked as the second-best compound, exhibited a binding energy of -10.00 kcal/mol, pKd value of 7.33, and a dock
A
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| Compound | PubChem CID | Binding energy | pKd | Dock score |
|---|---|---|---|---|
| Salvianolic acid C | 13991590 | -10.39 | 7.62 | -66.43 |
| Salvianolic acid A | 5281793 | -10.00 | 7.33 | -67.85 |
| Calceolarioside B | 5273567 | -9.72 | 7.12 | -62.99 |
| Chicoric acid | 5281764 | -9.34 | 6.85 | -61.36 |
| Plantagoside | 174157 | -8.63 | 6.33 | -60.55 |
| Native inhibitor | - | -9.34 | 6.85 | - |
The table includes binding energies, pKa values, and dock scores for the compounds.
score of -67.85, suggesting a strong binding affinity with CDK1 (Table I). The binding analysis revealed that this compound interacted with 15 key residues, including Ile- 10, Glu-12, Tyr-15, Ala-31, Val-64, Phe-80, Leu-83, Ser-84, Met-85, Asp-86, Lys-89, Gln-132, Asn-133, Leu-135, and Asp-146 (Table III). A significant number of 66 non- bonded contacts were observed, contributing to the overall stability of the ligand within the binding pocket. Additionally, Salvianolic acid A formed four hydrogen bonds, further enhancing its interaction with CDK1 (Table II). Specifically, Tyr-15, Ser-84, Gln-132, and Asp-146
were involved in hydrogen bonding, with bond lengths of 3.19 Å, 3.12 Å, 3.28 Å, and 3.24 Å, respectively (Figure 5). These interactions likely play a crucial role in stabilizing the ligand within the active site. Although Salvianolic acid A had fewer interacting residues compared to Salvianolic acid C, its high binding affinity scores and involvement in four hydrogen bonds through four different residues, highlight its potential as a potent CDK1 inhibitor. Its strong interactions with key catalytic residues suggest that it may effectively inhibit CDK1 activity, making it a promising candidate.
| Compound | Interacting residues | Non-bonded contacts | Hydrogen bonds |
|---|---|---|---|
| Salvianolic acid C | 17 | 54 | 2 |
| Salvianolic acid A | 15 | 66 | 4 |
| Calceolarioside B | 14 | 48 | 2 |
| Chicoric acid | 15 | 77 | 2 |
| Plantagoside | 13 | 42 | 2 |
| Native inhibitor | 15 | 51 | 3 |
The table presents the number of interacting residues for each compound, along with the total count of molecular interactions, including hydrogen bonds and non-bonded contacts.
| Salvianolic acid C | Salvianolic acid A | Calceolarioside B | Chicoric acid | Plantagoside |
|---|---|---|---|---|
| Ile-10 | Ile-10 | Ile-10 | Ile-10 | Ile-10 |
| - | - | Gly-11 | Gly-11 | |
| Glu-12 | Glu-12 | - | - | - |
| Gly-13 | - | - | - | - |
| Tyr-15 | Tyr-15 | Tyr-15 | Tyr-15 | Tyr-15 |
| Val-18 | - | Val-18 | Val-18 | - |
| Ala-31 | Ala-31 | Ala-31 | Ala-31 | Ala-31 |
| - | - | Lys-33 | Lys-33 | |
| Val-64 | Val-64 | Val-64 | - | |
| Phe-80 | Phe-80 | Phe-80 | Phe-80 | |
| - | Glu-81 | - | - | |
| - | Phe-82 | Phe-82 | - | |
| Leu-83 | Leu-83 | - | - | - |
| Ser-84 | Ser-84 | Ser-84 | Ser-84 | - |
| Met-85 | Met-85 | - | - | - |
| Asp-86 | Asp-86 | Asp-86 | Asp-86 | Asp-86 |
| - | - | - | Lys-88 | |
| Lys-89 | Lys-89 | Lys-89 | - | - |
| Asp-128 | - | - | - | - |
| Lys-130 | - | - | - | Lys-130 |
| Gln-132 | Gln-132 | Gln-132 | Gln-132 | Gln-132 |
| Asn-133 | Asn-133 | - | Asn-133 | Asn-133 |
| Leu-135 | Leu-135 | Leu-135 | Leu-135 | Leu-135 |
| Asp-146 | Asp-146 | Asp-146 | Asp-146 | Asp-146 |
Each column represents a specific compound, listed at the top, along with its corresponding interacting residues. Shared interacting residues among multiple compounds are grouped in the same row for comparison. Residues that overlap with those identified in the native inhibitor’s interactions are highlighted in bold.
Calceolarioside B (Figure 4C), having CID 5273567, ranked as the third-best compound, exhibited a binding energy of -9.72 kcal/mol, pKd value of 7.12, and a dock score of -62.99, indicating a favorable interaction with CDK1 (Table I). The binding analysis revealed that this compound interacted with 14 key residues, including Ile- 10, Tyr-15, Val-18, Ala-31, Val-64, Phe-80, Glu-81, Phe-82,
Leu-83, Ser-84, Asp-86, Lys-89, Gln-132, Leu-135, and Asp-146 (Table III). A total of 48 non-bonded contacts contributed to the stabilization of the ligand within the catalytic site (Table II). Additionally, Calceolarioside B formed three hydrogen bonds, further strengthening its binding affinity to CDK1. Hydrogen bonds were observed with Tyr-15 (3.22 Å), Glu-81 (2.78 Å), and Leu-83 (2.97 Å),
A
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highlighting the strong binding of the ligand within the active site (Figure 5). While Calceolarioside B interacted with slightly fewer residues than the top-ranked compounds, its combination of hydrogen bonding and non-bonded interactions suggests a stable binding mode within the CDK1 pocket. Its notable affinity and interaction profile make it a promising candidate as a potential CDK1 inhibitor.
Chicoric acid (Figure 4D), having CID 5281764, ranked fourth among the screened compounds, demonstrated a binding energy of -9.34 kcal/mol, pKd value of 6.85, and
a dock score of -61.36, suggesting a favorable interaction with CDK1 (Table I). The binding analysis indicated that Chicoric acid engaged with 15 key residues (Table II), including Ile-10, Gly-11, Tyr-15, Val-18, Ala-31, Lys-33, Val-64, Phe-80, Phe-82, Ser-84, Asp-86, Gln-132, Asn-133, Leu-135, and Asp-146 (Table III). This compound exhibited 77 non-bonded contacts, the highest among the selected compounds, reflecting strong stabilizing interactions within the catalytic site (Table II). Additionally, hydrogen bonds with Gln-132 (1.95 Å) and Asp-146 (3.34 Å) contributed towards stability of the
ligand within the active site (Figure 5). Despite having a slightly lower binding affinity compared to the top-ranked compounds, Chicoric acid displayed extensive interactions, particularly through its high number of non- bonded contacts. These findings suggest that it has the potential to act as an inhibitor of CDK1.
Plantagoside (Figure 4E), having CID 174157, ranked fifth among the screened compounds, exhibited a binding energy of -8.63 kcal/mol, pKd value of 6.33, and a dock score of-60.55, indicating strong interactions with CDK1 (Table I). The docking analysis revealed that plantagoside interacted with 13 key residues, including Ile-10, Gly-11, Tyr-15, Ala-31, Lys-33, Phe-80, Asp-86, Lys-88, Lys-130, Gln-132, Asn-133, Leu-135, and Asp-146 (Table III). The compound formed 42 non-bonded contacts, contributing to the stability of the ligand within the CDK1 binding pocket. Additionally, two hydrogen bonds reinforced its binding interactions (Table II). One hydrogen bond was observed with Lys-88 at a distance of 3.32 Å, while another was formed with Asn-133 at 3.26 Å, providing further stability to the complex (Figure 5). Although Plantagoside displayed a lower binding affinity compared to the other selected compounds, its interactions with key catalytic residues and hydrogen bonding ability suggest that it may serve as a potential CDK1 inhibitor.
Comparative binding analysis of selected compounds with CDK1. A comparative evaluation of the five screened compounds against CDK1 reveals a significant overlap in their binding interactions with the native inhibitor, highlighting their potential as CDK1 kinase inhibitors. Among the selected compounds and the native inhibitor, six residues were consistently involved, these include Ile- 10, Tyr-15, Ala-31, Asp-86, Leu-135, and Asp-146 (Table III, Figure 5). These residues may be playing a crucial role in binding the ligands and contributing to their stability within the CDK1 active site. In addition, three more residues were found to be common between the native inhibitor and four of the five screened compounds. Phe-80 was observed in all compounds except Salvianolic acid C, while Ser-84 was present in all except Plantagoside.
Similarly, Asn-133 was identified as a key interacting residue in all compounds except Calceolarioside B (Table III, Figure 5). The involvement of these residues across multiple compounds suggests that these residues may contribute to the binding of the ligands and, thus, again reinforcing the potential of these natural compounds as CDK1 inhibitors. Interestingly, Gln-132 emerged as a unique residue that was not involved in native inhibitor binding but was consistently present in all five selected compounds (Table III, Figure 5). This observation suggests that these natural compounds may introduce an additional stabilizing interaction that is absent in the native inhibitor, potentially offering an advantage in terms of binding affinity and specificity. Overall, this comparative analysis underscores the binding similarities between the selected compounds and the native inhibitor while also revealing distinct differences that could be exploited for improved potency. The conservation of core binding interactions, coupled with the introduction of new stabilizing contacts, suggests that these compounds hold promise as alternative or enhanced inhibitors of CDK1. Further investigations, including structural optimization and experimental validation, could provide deeper insights into their potential as therapeutic candidates.
Discussion
The TCGA dataset provides a valuable resource for exploring gene expression patterns, identifying prognostic biomarkers, and uncovering potential molecular drivers across diverse cancer types (16, 23, 38). Leveraging this resource, we specifically examined the expression of CDK1 across pan-cancer cohorts aiming to identify cancer types in which CDK1 inhibition may have significant therapeutic implications. The comprehensive analysis of CDK1 expression across the TCGA and GTEx datasets revealed its overexpression in many cancers, suggesting that this key cell cycle regulator could serve as a potential therapeutic target. Notably, CDK1 was significantly overexpressed in aggressive cancer subtypes, including adrenocortical carcinoma, lung adenocarcinoma, breast
invasive carcinoma, and prostate adenocarcinoma, corroborating previous findings (6, 10, 23). Previous studies have revealed that CDK1 drives tumorigenesis through multiple pathways. For instance, it activates the GP130/STAT3 signaling axis in lung cancer, interacts with Sox2 to promote melanoma initiation, and has been identified as a potential therapeutic target of eriocitrin in colorectal cancer (12-14). These studies demonstrate CDK1’s broad prognostic relevance, necessitating a deeper exploration of cancers where its influence is most pronounced. In a similar manner, the transcription factor SOX17 exhibits cancertype dependent expression and differential prognostic significance, highlighting the need for tumorspecific biomarker evaluation (39).
Survival analyses in our study further demonstrated that high CDK1 expression correlates with poor outcomes in several cancer types, with the strongest association observed in ACC. Interestingly, CDK1 expression increased consistently from early to late cancer stages in ACC, suggesting its potential role as ACC progression (Figure 2A-B). Furthermore, the critical role of CDK1 in ACC, where it promotes chromosome segregation promotes cell proliferation, and apoptotic evasion distinguishes it as a key driver of this aggressive cancer (Figure 2C and Figure S4). This makes CDK1 a particularly attractive therapeutic target in ACC, where traditional treatment options remain limited and survival rates are poor. These findings are consistent with previous studies that have implicated CDK1 as a key driver of cancer progression and aggressiveness in other cancer types (4, 6, 8). Moreover, CDK1 modulation influences therapeutic response, as PARP inhibitors sensitize BRCA-mutant pancreatic cancer to oxaliplatin by suppressing the CDK1/BRCA1 axis (40).
ACC, an uncommon endocrine cancer, is characterized by a poor prognosis, with 5-year survival rates below 35% and median survival in metastatic stages under 3 years, largely due to limited effective treatments beyond surgery and mitotane (41). The development of selective CDK1 inhibitors represents a rational therapeutic strategy. In this regard, five natural compounds, namely Salvianolic acid C, Salvianolic acid A, Calceolarioside B, Chicoric acid,
and Plantagoside, were screened as potential CDK1 inhibitors. Docking analyses revealed that these compounds engage critical residues similar to those involved in the binding of the native inhibitor, supporting their potential to achieve stable and selective inhibition.
Salvianolic acids, polyphenolic compounds abundant in Salvia miltiorrhiza (Danshen), are well recognized for cardiovascular and anticancer properties (42). Salvianolic acid A, in particular, has been reported to suppress tumor growth by modulating multiple signaling pathways, including PI3K/AKT, MAPK/ERK, and apoptotic cascades (43). Furthermore, Salvianolic acid A and its structural analogs, such as Salvianolic acid B, have demonstrated broad cytotoxic effects across different cancer models by interfering with proliferative and survival mechanisms (44). These studies reinforce their role as promising natural scaffolds for kinase-targeted drug discovery.
Calceolarioside B and Plantagoside, both phenylethanoid glycosides (PhGs), also emerged as promising CDK1 binders. PhGs are a diverse class of secondary metabolites were reported to possess anti- inflammatory, neuroprotective, and cytotoxic properties (45). Specifically, PhGs derived from Plantago lanceolata exhibit anticancer effects (46), while those isolated from Cistanche species induce apoptosis in lymphoma cells (47). Notably, Plantago major, a natural source of Plantagoside, has been widely used in traditional medicine, with contemporary pharmacological studies validating its therapeutic versatility (48).
Chicoric acid (dicaffeoyltartaric acid), a caffeic acid derivative commonly found in Echinacea purpurea, chicory, and lettuce, represents another potent candidate. It is widely recognized for its antioxidant, immunomodulatory, and anti-diabetic properties (49). Importantly, emerging studies have demonstrated its anticancer potential. For instance, chicoric acid was shown to induce autophagy and endoplasmic reticulum stress via AMPK signaling in gastric cancer cells (50). In addition, its antiproliferative and pro-apoptotic effects against colon cancer cells were attributed to inhibition of CDC25 phosphatases (51). These studies highlight
chicoric acid as a multifunctional anticancer agent, with our results offering novel insights into its potential repurposing as a CDK1-targeted inhibitor. Interestingly, natural compounds can also modulate CDK1 at the transcriptional level, for example, CucurbitacinD induced an increase in CDK1 mRNA and triggered proliferation arrest in nonsmall cell lung carcinoma cells (52). Collectively, the identification of salvianolic acids, phenylethanoid glycosides, and chicoric acid as CDK1 inhibitors underscores the promise of natural compounds in kinase-targeted cancer therapy. These natural scaffolds provide a foundation for further development of selective CDK1-targeted therapeutics.
Conclusion
This study provides a comprehensive pan-cancer analysis of CDK1, revealing its widespread overexpression across multiple malignancies and its significant prognostic relevance. Among the analyzed cancer types, ACC exhibited the strongest association between high CDK1 expression and poor survival, highlighting its role in disease progression and aggressiveness. Our results confirm the role of CDK1 as a prognostic biomarker and therapeutic target across cancers, while highlighting its particular significance in ACC.
Leveraging CDK1 as a therapeutic target, we conducted structure-based virtual screening of a curated natural compound library. The screening shortlisted five promising inhibitors, including Salvianolic acid C, Salvianolic acid A, Calceolarioside B, Chicoric acid, and Plantagoside. Detailed molecular docking analyses revealed that these compounds engage critical residues within the ATP-binding pocket of CDK1, suggesting stable and selective inhibition. Importantly, these compounds have reported anticancer and biological activities, reinforcing their translational potential.
By integrating pan-cancer genomic profiling with computational pharmacology, this study highlights natural compounds with potential to target CDK1 and proposes a precision oncology strategy for ACC. These
findings provide a solid foundation for future preclinical investigations aimed at validating CDK1 as a therapeutic target and advancing the development of novel treatment options for this aggressive cancer.
Supplementary Material
Supplementary Figures S1-S4 and Supplementary Table S1 are accessible at: https://github.com/mrehan/ SupplementaryData
Conflicts of Interest
The Authors declare that no conflicts of interest exist.
Authors’ Contributions
Conceived and designed the experiments: MR and FA. Performed the experiments: MR and FA. Analyzed the data: MR, FA, MS, and SS. Wrote the article: MR, FA, MS, and SS.
Acknowledgements
This Project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant No: (GPIP: 1529-141-2024). The Authors, therefore, acknowledge with thanks DSR for technical and financial support.
The virtual screening in this work was performed at King Abdulaziz University’s High Performance Computing Center (Aziz Supercomputer) (http://hpc.kau.edu.sa), Jeddah, Saudi Arabia, and the authors acknowledge the center for technical support.
Artificial Intelligence (AI) Disclosure
During the preparation of this manuscript, a large language model (ChatGPT, OpenAI) was used solely for language editing and stylistic improvements in select paragraphs. No sections involving the generation, analysis,
or interpretation of research data were produced by generative AI. All scientific content was created and verified by the authors. Furthermore, no figures or visual data were generated or modified using generative AI or machine learning-based image enhancement tools.
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