Inhibition of PTK6 Hinders the Growth and Migration of Ovarian Cancer and Its Potential Clinical Significance

Inhibition of PTK6 Hinders the Growth and Migration of Ovarian Cancer and Its Potential Clinical Significance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Inhibition of PTK6 Hinders the Growth and Migration of Ovarian Cancer and Its Potential Clinical Significance Lan-Ting Zhou, Zhenzhen Li, Fan Hu, Jiang Yang, Xuezhou Yang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8166231/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study investigates the oncogenic role of Protein Tyrosine Kinase 6 (PTK6) in ovarian cancer (OC), focusing on its clinical prognosis, and its function on OC. Methods Multi-omics analyses to identify differentially expressed genes (DEGs). PTK6 expression was validated across datasets and correlated with survival, tumor stage and signaling pathways. Functional assays included lentiviral PTK6 knockdown and pharmacological inhibition (tilfrinib) in OC cells, evaluated via CCK-8, EdU, wound healing assay, colony formation, and molecular docking. Results PTK6 was upregulated in OC, with high expression linked to poor overall, disease-specific, and progression-free survival. Single-cell analysis localized PTK6 predominantly to epithelial and malignant cells. PTK6 knockdown suppressed the proliferation and migration of Caov-4 and ID8 cells. Tilfrinib forms a stable complex with PTK6 and inhibits cell proliferation in a dose-dependent manner. Conclusions PTK6 drives OC progression via proliferation, immune evasion, and oncogenic pathway regulation. Inhibition of PTK6 by tilfrinib constitutes a promising targeted therapy for ovarian cancer. Ovarian cancer PTK6 cell proliferation tilfrinib Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction According to the Global Cancer Statistics (GLOBOCAN) released by the International Agency for Research on Cancer (IARC), ovarian cancer ranks 8th in terms of incidence among malignant tumors in women worldwide, with an age-standardized rate of 6.6 per 100,000 [ 1 ]. High-grade serous ovarian cancer (HGSOC), the predominant subtype, afflicts approximately 239,000 women annually and ranks as the deadliest among gynecological malignancies [ 2 ]. Alarmingly, the diagnostic and prognostic landscape for a substantial patient cohort is dire: over 70% of ovarian cancer cases are diagnosed at an advanced stage [ 3 ]. This delayed detection, attributable to the disease's insidious nature, precipitates a dismal prognosis [ 4 ]. Tyrosine-protein kinase 6, also known as BRK (breast tumor kinase), is a cytoplasmic non-receptor tyrosine kinase that acts as an intracellular signal transducer in epithelial tissues, and has emerged as a pivotal player in tumor biology [ 5 ]. In normal physiology, PTK6 is involved in epithelial cell differentiation and tissue homeostasis [ 6 ]. However, accumulating evidence indicates that PTK6 is frequently dysregulated in human malignancies, exhibiting context-dependent oncogenic roles across multiple tumor types. PTK6 overexpression has been documented in breast cancer (BC), where it correlates with advanced clinical stages and shorter overall survival (OS) [ 7 ]. Similarly, in colorectal cancer (CRC), elevated PTK6 expression enhances cancer stem cell (CSC) properties and chemoresistance to 5-fluorouracil and oxaliplatin, linked to poor prognosis in chemotherapy-treated patients [ 5 , 8 ]. Beyond solid tumors, PTK6 dysregulation is also observed in pancreatic ductal adenocarcinoma (PDAC), further highlighting its broad involvement in tumorigenesis [ 9 , 10 ]. In cervical cancer, PTK6 is upregulated in cell lines and clinical tissues, promoting proliferation, invasion, and migration through interactions with GRB2-associated binding 1 (GAB1) [ 11 ]. PTK6 also shapes the tumor microenvironment (TME) to support immune evasion [ 12 ]. In breast cancer, high PTK6 expression correlates with increased infiltration of NK cells and Th17 cells, while negatively associating with Th1 cells, macrophages, and cytotoxic T cells [ 13 ]. This immune-modulatory property further strengthens its contribution to tumor progression. Proteolysis - targeting chimeras (PROTACs) by inducing PTK6 degradation, such as MS105, inhibiting both catalytic and scaffold functions to suppress breast cancer cell growth and induce apoptosis across subtypes [ 14 ]. These findings support PTK6 as a viable therapeutic target. Herein, we establish PTK6 as a master oncogenic regulator in OC through integrated multi-omics analyses and functional validation. We first identified PTK6 overexpression significantly correlating with advanced tumor stage. Results of single-cell revealed predominant PTK6 expression in malignant epithelial cells. In vitro functional assays confirmed that PTK6 knockdown potently suppressed proliferation in Caov-4 cells. Molecular docking confirmed that tilfrinib forms stable complexes with PTK6 and exhibits dose-dependent anti-proliferative activity. Our findings establish PTK6 inhibition as a novel therapeutic paradigm for ovarian cancer, positioning it as a multifunctional target with diagnostic utility and precision oncology applications. Materials and methods Data Collection. Expression profile data and clinical information of TCGA-GTEX were downloaded from XENA ( https://xenabrowser.net/datapages/ ), with normal GTEX samples used as the control group. Differential analysis of the raw expression data of TCGA-OV was performed using the DESeq2 package in R. Genes with |LogFC| >2.5 and p.adj < 0.01 were selected as differential genes. Plots were generated using expression data normalized by log2(TPM + 1) transformation, a parameter selection strategy employed in our analysis. The analysis of PTK6 expression in tumor, normal, and metastatic tissues of ovarian cancer was performed using TNMplot database [ 15 ]. scRNA-seq data processing The single-cell RNA sequencing data and the associated cell type annotations were downloaded from the TISCH database. The data was processed and analyzed using the R packages MAESTRO and Seurat. Perform dimensionality reduction with t-SNE and subsequently cluster the cells [ 16 ]. Enrichment analysis Enrichment analysis was conducted using the clusterProfiler package. For GSEA, genes ranked by LogFC and genes ranked by correlation with the PTK6 gene were used to analyze KEGG, REACTOME, and Wikipathways gene sets. Survival analysis Based on the expression levels of the PTK6 gene in OV samples, the surv_cutpoint function of the survminer package was used for threshold grouping. The survfit function of the survival package was applied to fit the overall survival (OS) information and grouping information. Finally, the ggsurvplot function of the survminer package was used for analysis and visualization. Correlation analysis of immune cell infiltration Immune infiltration score files of TCGA were downloaded from the TIMER2 database ( http://timer.comp-genomics.org/ ) [ 17 ]. Data related to TCGA-OV samples were filtered out, and TIMER/CIBERSORT score data were used to evaluate the distribution and correlation of immune cells in different tumor samples. Correlation analysis of signaling pathway STAR-counts data and corresponding clinical information for OC tumors were downloaded from the TCGA database ( https://portal.gdc.cancer.gov ). TPM-formatted data were extracted and normalized via log2(TPM + 1) transformation. Genes within relevant pathways were collected and analyzed using the GSVA package in R, with the 'ssgsea' method specified for single-sample gene set enrichment analysis (ssGSEA) [ 18 ]. Spearman correlation analysis was applied to assess associations between gene expression and pathway scores. All statistical analyses were performed using R software (v4.0.3). Cell lines Human IOSE-80, SK-OV-3, OVCAR-3 cells and mouse ID8 cells were obtained from the Bowers Type Culture Collection (BTCC, Beijing, China). Human OVSAHO cells were obtained from Millipore (Sigma-Aldrich, Burlington, MA, USA). Human Caov-4 cells were obtained from WarnerBio (Wuhan, China). IOSE-80, Caov-4, SK-OV-3and OVCAR-3 cells were maintained in RPMI-1640 medium. OVSAHO human 293T cells and mouse ID8 cells were grown in Dulbecco’s modified Eagle’s medium (DMEM). All culture media were supplemented with 10% fetal bovine serum (FBS; Gibco, Grand Island, NY, USA) and 1% penicillin-streptomycin. Patients This study was performed with the approval of the research ethics board of Xiangyang Central Hospital affiliated hospital of Hubei University of Arts and Science (No. 2025-184-013). The patient provided informed consent for inclusion prior to participation in the study. And the information on ovarian cancer was shown in Table 1 . Table 1 General characteristics of ovarian cancer patients Patient number Sex Age Primary location Type of ovarian cancer pTNM stage case 1# female 54 yes HGSOC Ⅱ case 2# female 63 yes HGSOC Ⅱ case 3# female 50 yes HGSOC Ⅱ case 4# female 64 yes HGSOC Ⅱ case 5# female 52 yes HGSOC Ⅱ case 6# female 36 yes HGSOC Ⅱ case 7# female 54 yes HGSOC Ⅱ case 8# female 60 yes HGSOC Ⅱ case 9# female 53 yes HGSOC Ⅱ case 10# female 68 yes HGSOC Ⅲ case 11# female 64 yes HGSOC Ⅲ case 12# female 49 yes HGSOC Ⅲ case 13# female 54 yes HGSOC Ⅲ case 14# female 46 yes HGSOC Ⅲ Reagents, and antibodies Tilfrinib (HY-110244) was obtained from MedChemExpress (Shanghai, China). PTK6 (sc-166171) were purchased from Sant Cruz (Dallas, USA). β-actin (66009-1-Ig) were obtained from Proteintech (Wuhan, China). Plasmids, transfection, and infection The human PTK6-specific shRNA constructs and negative control shRNA (sh-Ctrl) were inserted into the pLKO.1 vector (Tsingke Biotech Co. Ltd, Beijing, China). The target sequences of sh-PTK6 are listed in supplementary Table S4 . Lentiviruses were produced using HEK-293T cells. For transfection, Neofect DNA transfection reagent (Beijing, China) and specific plasmids were added to 6-well plates. After 6 hours of incubation, the medium was replaced, and cells were harvested at 48 hours post-transfection. Two days after infection, cells were thoroughly washed and subjected to selection with puromycin-containing medium to obtain stably infected cells. Cell viability assay Cells were seeded into 96-well plates and cultured overnight. Following respective treatments, cell viability was assessed using the Cell Counting Kit-8 (CCK-8; C0005, TargetMol, Shanghai, China) assay in accordance with the manufacturer's protocol. EdU assay DNA synthesis was assessed using the BeyoClick™ EdU-555 Cell Proliferation Kit (C0075, Beyotime, Shanghai, China). The EdU assay was conducted in accordance with the experimental instruction manual. For drug-treated cells, an appropriate number of cells were seeded in 24-well plates, and then drugs were added for a 48-hour treatment. Subsequently, 10 µM EdU was added to the cell culture medium, followed by incubation at 37 ℃ for 2 hours. After removing medium, cells were fixed with 4% paraformaldehyde at room temperature for 15 minutes. Then, 1 ml of permeabilization solution containing 0.3% Triton X-100 was added, and cells were incubated at room temperature for 10–15 minutes. The Click reaction solution was added, followed by incubation at room temperature in the dark for 30 minutes. Nuclei were stained with Hoechst 33342 for 10 minutes. The cell proliferation parameter was calculated using the following formula: (EdU⁺ cells / Total nuclei) × 100%. Propidium staining Propidium staining was conducted using the Propidium Iodide Staining Solution (40710ES03, Yeasen Biotechnology, Shanghai, China) in accordance with the experimental instruction manual. Cells were collected using an appropriate method and wash them in PBS. The cells were fixed in pre-cooled 70% ethanol at 4°C for 30 minutes. After washing the cells with PBS, the cells were treated with ribonuclease. PI (propidium iodide) were added with a concentration of 50 µg/mL. Then, the images was obtained by using fluorescence microscope. Colony formation assay Cells were seeded in 6-well plates at optimized densities. Following 24-hour adherence in complete medium, respective treatments were administered and maintained for 48 hours. The plates were then incubated for an additional 10 days under standard culture conditions (37 ℃, 5% CO₂). Resultant colonies were fixed with ice-cold methanol for 15 minutes, stained with crystal violet (Beyotime, Shanghai, China), and subsequently rinsed with PBS. After air-drying, the plates were digitally scanned, and the absorbance (OD value) of the plates was measured. Wound healing assay Cells (1 × 10⁵ cells/well) were seeded in 6-well plates and incubated at 37 ℃ until reaching 100% confluence as a uniform monolayer. A straight, vertical scratch was created across each well using a sterile 20-µl pipette tip. The culture plates were then returned to the 37 ℃ incubator for continuous incubation of 24 h. Wound healing progression in each well was observed and imaged under a light microscope [ 19 ]. Quantitative polymerase chain reaction (QPCR) Total RNA was isolated from cells utilizing TRIzol reagent (Invitrogen, Carlsbad, CA, USA). For subsequent mRNA analyses, total RNA was subjected to reverse transcription to generate first-strand cDNA using a cDNA synthesis kit (Vazyme, Nanjing, China). Quantitative real-time PCR (qPCR) was carried out on an ABI 7500 Real-Time PCR System with SYBR Green Premix Ex Taq (Vazyme, Nanjing, China) following the manufacturer's protocols. The primer sequences are provided in supplementary Table S4 . Relative mRNA expression levels were calculated using the 2^(-ΔΔC T ) method. All experiments were performed with both biological replicates and technical triplicates. Western blot After the cells were collected by centrifugation, they were resuspended in radioimmunoprecipitation assay lysis buffer (Boster, Wuhan, China). Following boiling for 10 minutes, the samples were subjected to ultrasonic disruption on ice, and protein concentrations were determined. Proteins were separated and transferred onto nitrocellulose membranes (GE HealthCare Life Sciences, Loughborough, UK). After blocking with 5% non-fat milk, the membranes were incubated with primary antibodies overnight at 4°C, followed by washing with phosphate-buffered saline containing Tween 20. Subsequently, the membranes were incubated with IRdye 800-conjugated anti-rabbit or anti-mouse immunoglobulin G secondary antibodies for 1 hour at room temperature. Protein bands were visualized using the Odyssey Imaging System (LI-COR, Lincoln, NE, USA). Molecular docking analysis Molecular docking analysis was performed according to the method described previously [ 20 ]. The chemical structure of tilfrinib was obtained from the PubChem database. The structure of PTK6 protein was retrieved from PDB database ( https://www.rcsb.org/structure/5D7V ). The structure was saved in PDB format after removing water molecules and ligands using PyMOL. Subsequent structural refinement and format conversion were performed using Open Babel 2.4.1. Molecular docking simulations were executed using AutoDock Vina 1.1.2. Following docking, the analysis focused on key virtual binding parameters to assess the binding affinity and mode between the ligand and target protein. Molecular dynamics simulation Molecular dynamics simulations of the PTK6-tilfrinib complex were performed using the Desmond/Maestro noncommercial version 2022.1 [ 21 ]. The system was solvated with TIP3P water molecules and neutralized with 0.15 M NaCl. Following energy minimization and system relaxation, production simulations were conducted for 100 ns under an isothermal-isobaric (NPT) ensemble at 300 K and 1 bar. Trajectory coordinates were recorded at 100 ps intervals. All other parameters were set according to the default protocols. Statistical Analysis To compare two groups, a two-tailed unpaired Student’s t -test or was conducted. For multiple comparisons between more than two groups, a one- or two-way ANOVA followed by Tukey’s post hoc test was performed. Kaplan-Meier estimates were utilized to calculate survival curves, and the log-rank test was applied to test differences between groups. Data are presented as the mean ± SEM. The value of P < 0.05 was considered statistically significant. Results 1. Identification of differential expressed genes in ovarian cancer. To explore the differential expressed genes in OC, the data of RNA sequencing was obtained from the TCGA and GTEX databases. A total of 6561 DEGs were identified, including 4284 significantly up-regulated genes and 2277 significantly down-regulated ones (Supplementary Fig. S1 A-C, supplementary Table S1 ). To further validate this result, we analyzed the sequencing data of ovarian cancer from GSE203130. We identified 1796 differentially expressed genes, including 1639 up-regulated genes and 157 down-regulated genes (Fig. 1 A-C, supplementary Table S2 ). GO and KEGG pathway were analyzed. The top 20 results were selected for plotting. In up-regulated genes, biological processes mainly involved for regulation of cell-cell adhesion, cell activation and inflammatory response (Fig. 1 D). And the mainly enriched KEGG pathway included pathways in cancer, cell cycle, transcriptional misregulation in cancer, and p53 signaling pathway (Supplementary Fig. S2 A). In down-regulated genes, positive regulation of apoptotic process was interestingly enriched (Fig. 1 F). A total of 4 pathways were obtained by KEGG pathway analysis (Supplementary Fig. S2 B). Collectively, the results of pathway enrichment analysis showed that cell proliferation is crucial in the development of ovarian cancer. We directed our attention to PTK6 among the DEGs, as its function in OC is rarely mentioned. Firstly, PTK6 was found to be elevated in OC tumor tissues according to TCGA and GTEx datasets (Supplementary Fig. S2 C). Importantly, the expression PTK6 was higher in metastatic ovarian cancer than other ovarian cancer (Supplementary Fig. S2 D). Other GSE databases also showed an up-regulation of PTK6 expression (Supplementary Fig. S2 E-F). In human ovarian cancer tissues, the expression of PTK6 was significantly upregulated in pTNM stage III tumors compared with stage II tumors, suggesting an association between PTK6 expression and tumor malignancy (Fig. 1 F-G). 2. The prognostic value of PTK6 expression in ovarian cancer. To assess the clinical prognosis relevance of PTK6, we carried out the log-rank test. It was found that high levels of PTK6 were correlated with a poor prognosis (Fig. 2 A-C). In addition, nomograms for predicting one-year, three-year, and five-year outcomes were developed for overall survival (Fig. 2 A), disease-specific survival (Fig. 2 B), and progression-free interval (Fig. 2 C). 3. Single-cell analysis of PTK6 expression in ovarian cancer. To identify which cell types express PTK6, we analyzed single-cell expression of PTK6 in OC. The results revealed that PTK6 was mainly expressed in epithelial cells and malignant cells though a low level of PTK6 at the single-cell level (Supplementary Fig. S3 A-C). Our finding suggested PTK6 might be directly associated with the function of tumor epithelium. 4. Immune features analysis of PTK6 expression in Ovarian Cancer As shown in enrichment analysis of DEG, the inflammatory and immune response were also enriched, suggesting a relation of PTK6 with immune response. Consequently, we undertook a correlation analysis by utilizing databases focused on immune cell infiltration. The results revealed that PTK6 was positively related to myeloid dendritic cell, neutrophils and CD4 + T cells, and that PTK6 expression was negatively correlated with that of B cells (Fig. 3 A-B). The relationship between the degree of PTK6 and immune cell abundance was visualized with a lollipop chart (Fig. 3 B). In OC, PTK6 shows a positive correlation with several immune checkpoints, including C10orf54, VTCN1, CD44, CTLA4, TGFB1, TNFRSF14, ITGB2, TNFRSF18 (Fig. 3 C). 5. Correlation between PTK6 expression and signaling pathway in ovarian cancer. To clarify which signaling pathways in ovarian cancer are closely associated with PTK6, we analyzed the correlation between PTK6 expression and these signaling pathways. The findings demonstrated a significant positive correlation between PTK6 expression and signaling pathways such as angiogenesis, P53 pathway, and inflammatory response (Supplementary Fig. S4 ). And PTK6 expression was negatively correlated with DNA repair, DNA replication, and G2M checkpoint (Supplementary Fig. S4 ). The PTK6-related genes analysis demonstrated that the top 10 positively or negatively related genes were obtained in OC (Supplementary Fig. S5 A-B, supplementary Table S3 ). Furthermore, the co-expression pattern between these genes and PTK6 was identified (Supplementary Fig. S5 C-D). 6. PTK6 knockdown significantly inhibited the proliferation and migration of ovarian cancer. To investigate the effect of PTK6 on the proliferation and migration of ovarian cancer cells, we first detected the expression of PTK6 in various types of ovarian cancer. It was found that the expression of PTK6 mRNA was significantly up-regulated in OC cells (Fig. 4 A). The protein level of PTK6 was significantly elevated in Caov-4 cells (Fig. 4 B). We used lentivirus shRNA to interfere with PTK6 expression in Caov-4 cells, resulting in a significant down-regulation of PTK6 (Fig. 4 C-D). After PTK6 knockdown, microscopic observation showed a marked alteration in the cytomorphology of Caov-4 cells and a notable reduction in the number of cells (Fig. 4 E). The CCK8 assay demonstrated that the Caov-4 cell growth was significantly decreased after PTK6 knockdown (Fig. 4 F). Wound healing assays were performed to evaluate the migratory capacity of ovarian cancer cells. The results showed that Caov-4 cells with PTK6 knockdown exhibited a decreased migratory ability (Fig. 4 G-H). The EdU assay indicated a significant decrease in the DNA synthesis rate of Caov-4 cells after PTK6 knockdown compared to the negative control group (Fig. 4 I-J). Colony formation assay confirmed that the cell proliferation was inhibited by PTK6 knockdown (Fig. 4 K-L). These results suggested that PTK6 interference inhibited the proliferation of ovarian cancer cells. 7. Tilfrinib significantly inhibited the proliferation and migration of ovarian cancer cells. To verify the binding between tilfrinib and PTK6, we performed analysis of molecular docking and molecular dynamics simulation. And the molecular docking results demonstrated that tilfrinib bind to PTK6 with a binding free energy of -8.5 kcal/mol (Supplementary Fig. S6 A-B). Meanwhile, after initial fluctuations, the RMSD of the ligand (Supplementary Fig. S6 C). This indicates that both molecules exhibited minimal fluctuations relative to their initial conformations, highlighting the extremely high stability of their initial conformations. The RMSF values of amino acid residues involved in forming interactions with tilfrinib, suggesting that the binding of tilfrinib to PTK6 are relatively stable (Supplementary Fig. S6 D). During the simulation, multiple sets of interactions were formed between the protein and the small molecule (Supplementary Fig. S6 E-F). In summary, the molecular dynamics simulation confirms that tilfrinib and PTK6 exhibit extremely high affinity. Next, cell proliferation capacity was investigated in Caov-4 cell with a different dose of tilfrinib treatment. The cell viability of Caov-4 cells was inhibited by tilfrinib in a manner dependent on concentration by CCK8 assay. (Fig. 5 A-C). The EdU assay demonstrated that tilfrinib suppressed DNA replication (Fig. 5 D-E). Wound healing assays were performed to evaluate the migratory capacity, and the results exhibited a decreased migratory ability of Caov-4 cells after PTK6 knockdown (Fig. 5 F-G). The Colony formation assay indicated that tilfrinib inhibited the growth ability of Caov-4 cells (Fig. 5 H-I). In summary, tilfrinib inhibits cell proliferation of OC. Then, we tested the effects of tilfrinib on the proliferation capacity of mouse ID8 cells. The proliferation of ID8 cells was also inhibited by tilfrinib treatment as shown by CCK8 and EdU assay (Fig. 6 A-C). The apoptosis of ID8 cells was increased after tilfrinib treatment (Fig. 6 D-E). Meanwhile, tilfrinib inhibited the growth ability of ID8 cells by colony formation assay (Fig. 6 F-G). Collectively, these results indicated that pharmacological inhibitor of PTK6 significantly suppressed ovarian cancer cell proliferation. Discussion Ovarian cancer exhibits a high mortality rate among gynecological malignancies, with epithelial ovarian cancer being the most prevalent subtype. For patients with advanced-stage disease, systemic pharmacotherapy constitutes the cornerstone of treatment [ 22 ]. While significant advances have been made in ovarian cancer research over recent decades, the five-year survival rate for these patients remains disappointingly low. PTK6 has emerged as a critical regulator in tumorigenesis and progression. Accumulating evidence highlights its dysregulated expression across multiple malignancies [ 23 ]. Our findings demonstrate that PTK6 is significantly upregulated in ovarian cancer (OC) with high expression correlating robustly with poor clinical outcomes. This aligns with its predominant localization in epithelial and malignant cells, suggesting a direct role in tumor cell biology. The observed associations between PTK6 and immune cell infiltration highlight its potential to modulate the tumor immune microenvironment. Concurrently, PTK6’s linkage to pro-tumor signaling pathway activation further supports its multifaceted contribution to OC progression. Functional validation through PTK6 knockdown and pharmacological inhibition with tilfrinib confirms its role in promoting cell proliferation and cell migration, while molecular docking studies establish tilfrinib as a promising PTK6-targeted agent with dose-dependent anti-proliferative effects. Collectively, these results position PTK6 as a novel prognostic biomarker and therapeutic target, offering a rationale for further preclinical and clinical exploration of PTK6 inhibition in OC management. PTK6 expression is aberrantly elevated in most solid tumors, with distinct patterns across cancer types [ 24 ]. Pan-cancer analyses utilizing TCGA and GTEx datasets reveal that PTK6 is upregulated in over 70% of tumor types, including breast cancer (BC), colorectal cancer (CRC), cervical cancer, prostate cancer, ovarian cancer, bladder cancer, clear cell renal carcinoma (KIRC), and pancreatic ductal adenocarcinoma (PDAC) [ 25 – 30 ]. In cervical cancer, PTK6 levels are markedly increased in cell lines and clinical tissues [ 11 ]. Similarly, in CRC, PTK6 is overexpressed in tumor tissues and cell lines, with higher levels linked to advanced stages and poor survival in patients receiving chemotherapy [ 26 ]. In prostate cancer, elevated PTK6 expression is associated with poor patient prognosis. PTK6 demonstrates cytoplasmic relocalization in tumor cells, in contrast to its nuclear localization in normal prostate epithelium [ 28 ]. And it was reported that PTEN loss-driven tumorigenesis critically depends on consequent PTK6 activation via Y342 phosphorylation, supporting that PTK6 activation promotes invasive prostate cancer [ 31 ]. PTK6 shapes the tumor immune microenvironment to facilitate immune evasion [ 32 ]. In breast cancer, high PTK6 expression correlates with increased infiltration of NK cells and Th17 cells, while negatively associating with Th1 cells, macrophages, and cytotoxic T cells [ 33 ]. This suggests PTK6 may promote an immunosuppressive TME, potentially impairing anti-tumor immunity. PTK6 inhibitors, have shown promise in preclinical studies by suppressing PTK6 activity. In breast cancer, XMU-MP-2 disrupt FAK phosphorylation, inhibiting AKT activation and reducing cancer cell survival [ 34 ]. In colorectal cancer, they target the PTK6-JAK2/STAT3 axis, diminishing cancer stem cell traits and reversing chemoresistance to drugs like 5-fluorouracil and oxaliplatin [ 26 ]. Tilfrinib is a selective inhibitor of PTK6 [ 35 ]. In breast cancer cell lines, tilfrinib has shown good anti-proliferative activity. PTK6 has been found to drive the phase separation of HNRNPH1, which in turn activates autophagy and suppresses apoptosis in CRC cells [ 36 ]. In patient-derived organoids (PDO) and mouse xenograft models of CRC, tilfrinib treatment significantly inhibits tumor growth. By inhibiting PTK6, tilfrinib disrupts this autophagy pathway, tipping the balance towards apoptosis and ultimately suppressing tumor growth. Abbreviations OC, ovarian cancer; HGSOC, high-grade serous ovarian cancer; BRK, breast tumor kinase; OS, overall survival; TME, tumor microenvironment; PROTACs, proteolysis - targeting chimeras; TPM, transcripts per million; ssGSEA, single-sample gene set enrichment analysis; VTCN1, RMSD, root mean square deviation; RMSF, root mean square fluctuation; IRS-4, insulin receptor substrate 4; PDO, patient-derived organoids. Declarations Ethics approval and consent to participate This study was performed with the approval of the research ethics board of Xiangyang Central Hospital affiliated hospital of Hubei University of Arts and Science (Approval No. 2025-041-014). This study was conducted in compliance with the Declaration of Helsinki and all applicable ethical guidelines. Patients provided written informed consent. Consent for publication All authors agree with the publication of this article. Availability of data and materials All data generated or analyzed during this study are included in this published article and its supplementary information files. Competing interests The authors have no conflict of interest. Funding This study was supported by the project of the National Natural Science Foundation of China [grant no. 82472634 and 82301374]; the Key Research & Development Program of Hubei Province [grant no. 2023BCB128 and 2024BCB055]; the Hubei Provincial Natural Science Foundation of China [grant no. 2024AFD428 and 2025AFD068]; the project of Xiangyang Central Hospital [grant no. 2024BS03]. Author contributions L.T.Z. and Z.L. wrote the main manuscript text. L.T.Z. and Z.L. conducted the experiments and analyzed the data. L.T.Z., F.H. and J.Y. prepared figures and data. X.Y. performed the supervision work. X.Q., H.X. and L.F. revised the manuscript. All authors reviewed the manuscript. Acknowledgements Not applicable. References Wei YF, Ning L, Xu YL, Ma J, Li DR, Feng ZF, Liu FH, Li YZ, Xu HL, Li P et al. Worldwide patterns and trends in ovarian cancer incidence by histological subtype: a population-based analysis from 1988 to 2017. EClinicalMedicine 2025, 79:102983. 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Discovery of 4-anilino alpha-carbolines as novel Brk inhibitors. Bioorg Med Chem Lett. 2014;24(8):1948–51. Chen B, Liu B, Chen J, Li W, Ma N, Liu J, Fan R, Hu Q, Song H, Xu Y, et al. PTK6 drives HNRNPH1 phase separation to activate autophagy and suppress apoptosis in colorectal cancer. Autophagy. 2025;21(8):1680–99. Additional Declarations No competing interests reported. Supplementary Files FigureS1S6.doc TableS1.TheDEGofOCfromTCGA.xlsx TableS2.TheDEGofOCfromGSE203130.xlsx TableS3.ThePTK6correlatedDEG.xlsx TableS4.ThesequenceofprimerandshRNA.doc SupplementaryfileUncroppedGelsandBlotsimages.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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16:41:00","extension":"html","order_by":41,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":130497,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/2e41c7ca0be2eccff9987aeb.html"},{"id":98427682,"identity":"eef88d7a-74e3-415c-9198-c729eb9f9579","added_by":"auto","created_at":"2025-12-17 16:40:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3798803,"visible":true,"origin":"","legend":"\u003cp\u003eThe differentially expressed genes between ovarian cancer tissues and normal tissues.\u003c/p\u003e\n\u003cp\u003e(A) The volcano plot. (B) The heatmap. (C) The top 20 differentially expressed genes. (D) GO analysis of up-regulated genes. (E) GO analysis of down-regulated genes. (F) and (G) The expression of PTK6 was examined in tumor tissues by IHC and quantitative analysis was shown. Data are shown as mean ± SEM. Statistical significance was determined using the Mann–Whitney U test (****P \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/a72b30b57a61bbb2b7b9945c.jpg"},{"id":98429409,"identity":"564fa54c-2e4c-4789-9fc4-d12f9eaca55b","added_by":"auto","created_at":"2025-12-17 16:43:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2993554,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between PTK6 gene expression and survival prognosis in OC was analyzed.\u003c/p\u003e\n\u003cp\u003e(A) Overall survival and nomograms predicting one-year, three-year, and five-year survival of OC, (B) Disease specific survival and nomograms predicting, (C) Progress free interval and nomograms predicting.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/0ecce5eb0b1486dd58d6a089.jpg"},{"id":98427673,"identity":"76ddb114-b57b-41f8-91b5-5642ab093e8b","added_by":"auto","created_at":"2025-12-17 16:40:59","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2286032,"visible":true,"origin":"","legend":"\u003cp\u003eThe relation between the PTK6 expression and immune signature in OC.\u003c/p\u003e\n\u003cp\u003e(A) and (B) The relation between PTK6 and immune cells. (C) The relation between PTK6 and immune checkpoints.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/aed48d8497415e4427e9895a.jpg"},{"id":98430287,"identity":"83f76db6-67c0-4d89-939d-ef4e8b806ba7","added_by":"auto","created_at":"2025-12-17 16:45:06","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3256353,"visible":true,"origin":"","legend":"\u003cp\u003ePTK6 knockdown inhibited the proliferation of ovarian cancer cells.\u003c/p\u003e\n\u003cp\u003e(A) and (B) mRNA and protein levels of PTK6 in ovarian cancer cells. (C) and (D) PTK6 levels in Caov-4 cells after PTK6 knockdown. (E) and (F) The morphology and viability of Caov-4 cells (Scale bar, 50 μm). Two-way ANOVA with Sidak's multiple comparisons test. (G) and (H) Scratches were made in culture plates of Caov-4 cells and wound healing was calculated (Scale bar, 10 μm). (I) and (J) EdU+ positive Caov-4 cells (Scale bar, 50 μm). (K) Clonal formation of Caov-4 cells after PTK6 knockdown. (L) The OD value of Caov-4 cells after PTK6 knockdown.Data are shown as mean ± SEM. Statistical significance was determined using the Mann–Whitney U test (ns: not significant; **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/be4e2ee54162b17f854bec3b.jpg"},{"id":98427688,"identity":"9b7eee8e-afd1-42c6-8cd7-080c0b52414f","added_by":"auto","created_at":"2025-12-17 16:40:59","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5324828,"visible":true,"origin":"","legend":"\u003cp\u003eTilfrinib significantly inhibited the proliferation of Caov-4 cells.\u003c/p\u003e\n\u003cp\u003e(A) The proliferation activity of Caov-4 cells with tilfrinib treatment. (B) The morphology of Caov-4 cells (Scale bar, 100 μm). (C) The viability of Caov-4 cells. Two-way ANOVA with Sidak's multiple comparisons test. (D) and (E) Images and quantification of EdU+ positive Caov-4 cells (Scale bar, 50 μm). (F) and (G) Scratches were made in culture plates of Caov-4 cells and wound healing was calculated (Scale bar, 10 μm). (H) The OD value of Caov-4 cells. (I) Clonal formation of Caov-4 cells. Data are shown as mean ± SEM. Statistical significance was determined using the Mann–Whitney U test (****P \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/a4a42e960f9ea4c0caf89ef6.jpg"},{"id":98092677,"identity":"78d9669e-2bab-4a5b-90ff-4cdc709a1ef5","added_by":"auto","created_at":"2025-12-12 17:32:22","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3529884,"visible":true,"origin":"","legend":"\u003cp\u003eTilfrinib significantly inhibited the proliferation of ID8 cells.\u003c/p\u003e\n\u003cp\u003e(A) The proliferation activity of ID8 cells with tilfrinib treatment. (B) and (C) Images and quantification of EdU+ positive ID8 cells (Scale bar, 20 μm). (D) and (E) Images and quantification of PI positive cells (Scale bar, 50 μm). (F) The OD value of ID8 cells. (G) Clonal formation of ID8 cells.Data are shown as mean ± SEM. Statistical significance was determined using the Mann–Whitney U test (ns: not significant; **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/fbff3600da974b4d279c9cb6.jpg"},{"id":102296931,"identity":"1c37795c-6b0c-4d1e-a25a-2b2de008ea05","added_by":"auto","created_at":"2026-02-10 10:22:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":22003387,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/b285cc55-3509-425e-a800-3386ebbfafcb.pdf"},{"id":98092660,"identity":"8b1deecf-f495-4f51-97df-32e723c1b693","added_by":"auto","created_at":"2025-12-12 17:32:22","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2172416,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1S6.doc","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/c69eaa3c9b024f5b7bc3f8f8.doc"},{"id":98622815,"identity":"adb32300-b9a6-4820-a547-8cbbc4594d13","added_by":"auto","created_at":"2025-12-19 17:02:39","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":717983,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.TheDEGofOCfromTCGA.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/b696bffcd9956ac28aea45d3.xlsx"},{"id":98428203,"identity":"5fbb89cf-f786-4188-870e-c1a4cc82bee0","added_by":"auto","created_at":"2025-12-17 16:41:46","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2858954,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.TheDEGofOCfromGSE203130.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/fd04fc402476dded34e1cf61.xlsx"},{"id":98430454,"identity":"af015814-3e00-40b7-8b8d-cce1b66ed5d7","added_by":"auto","created_at":"2025-12-17 16:45:29","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":269693,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.ThePTK6correlatedDEG.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/27adb93cbb7c4f538081d37b.xlsx"},{"id":98092666,"identity":"cf136b30-94a6-4403-9edb-bb01ed26c9e6","added_by":"auto","created_at":"2025-12-12 17:32:22","extension":"doc","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":31744,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4.ThesequenceofprimerandshRNA.doc","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/ea618b503a611ae9fd4878c7.doc"},{"id":98430364,"identity":"ad61f37e-ffd5-4280-a827-19c19b589cc3","added_by":"auto","created_at":"2025-12-17 16:45:13","extension":"doc","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3147231,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryfileUncroppedGelsandBlotsimages.doc","url":"https://assets-eu.researchsquare.com/files/rs-8166231/v1/217b9dc190b7a08d85a828be.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inhibition of PTK6 Hinders the Growth and Migration of Ovarian Cancer and Its Potential Clinical Significance","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the Global Cancer Statistics (GLOBOCAN) released by the International Agency for Research on Cancer (IARC), ovarian cancer ranks 8th in terms of incidence among malignant tumors in women worldwide, with an age-standardized rate of 6.6 per 100,000 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. High-grade serous ovarian cancer (HGSOC), the predominant subtype, afflicts approximately 239,000 women annually and ranks as the deadliest among gynecological malignancies [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Alarmingly, the diagnostic and prognostic landscape for a substantial patient cohort is dire: over 70% of ovarian cancer cases are diagnosed at an advanced stage [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This delayed detection, attributable to the disease's insidious nature, precipitates a dismal prognosis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTyrosine-protein kinase 6, also known as BRK (breast tumor kinase), is a cytoplasmic non-receptor tyrosine kinase that acts as an intracellular signal transducer in epithelial tissues, and has emerged as a pivotal player in tumor biology [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In normal physiology, PTK6 is involved in epithelial cell differentiation and tissue homeostasis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, accumulating evidence indicates that PTK6 is frequently dysregulated in human malignancies, exhibiting context-dependent oncogenic roles across multiple tumor types.\u003c/p\u003e\u003cp\u003ePTK6 overexpression has been documented in breast cancer (BC), where it correlates with advanced clinical stages and shorter overall survival (OS) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Similarly, in colorectal cancer (CRC), elevated PTK6 expression enhances cancer stem cell (CSC) properties and chemoresistance to 5-fluorouracil and oxaliplatin, linked to poor prognosis in chemotherapy-treated patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Beyond solid tumors, PTK6 dysregulation is also observed in pancreatic ductal adenocarcinoma (PDAC), further highlighting its broad involvement in tumorigenesis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In cervical cancer, PTK6 is upregulated in cell lines and clinical tissues, promoting proliferation, invasion, and migration through interactions with GRB2-associated binding 1 (GAB1) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. PTK6 also shapes the tumor microenvironment (TME) to support immune evasion [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In breast cancer, high PTK6 expression correlates with increased infiltration of NK cells and Th17 cells, while negatively associating with Th1 cells, macrophages, and cytotoxic T cells [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This immune-modulatory property further strengthens its contribution to tumor progression. Proteolysis - targeting chimeras (PROTACs) by inducing PTK6 degradation, such as MS105, inhibiting both catalytic and scaffold functions to suppress breast cancer cell growth and induce apoptosis across subtypes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These findings support PTK6 as a viable therapeutic target.\u003c/p\u003e\u003cp\u003eHerein, we establish PTK6 as a master oncogenic regulator in OC through integrated multi-omics analyses and functional validation. We first identified PTK6 overexpression significantly correlating with advanced tumor stage. Results of single-cell revealed predominant PTK6 expression in malignant epithelial cells. \u003cem\u003eIn vitro\u003c/em\u003e functional assays confirmed that PTK6 knockdown potently suppressed proliferation in Caov-4 cells. Molecular docking confirmed that tilfrinib forms stable complexes with PTK6 and exhibits dose-dependent anti-proliferative activity. Our findings establish PTK6 inhibition as a novel therapeutic paradigm for ovarian cancer, positioning it as a multifunctional target with diagnostic utility and precision oncology applications.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eData Collection.\u003c/p\u003e\u003cp\u003eExpression profile data and clinical information of TCGA-GTEX were downloaded from XENA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xenabrowser.net/datapages/\u003c/span\u003e\u003cspan address=\"https://xenabrowser.net/datapages/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), with normal GTEX samples used as the control group. Differential analysis of the raw expression data of TCGA-OV was performed using the DESeq2 package in R. Genes with |LogFC| \u0026gt;2.5 and p.adj\u0026thinsp;\u0026lt;\u0026thinsp;0.01 were selected as differential genes. Plots were generated using expression data normalized by log2(TPM\u0026thinsp;+\u0026thinsp;1) transformation, a parameter selection strategy employed in our analysis. The analysis of PTK6 expression in tumor, normal, and metastatic tissues of ovarian cancer was performed using TNMplot database [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003escRNA-seq data processing\u003c/p\u003e\u003cp\u003eThe single-cell RNA sequencing data and the associated cell type annotations were downloaded from the TISCH database. The data was processed and analyzed using the R packages MAESTRO and Seurat. Perform dimensionality reduction with t-SNE and subsequently cluster the cells [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEnrichment analysis\u003c/p\u003e\u003cp\u003eEnrichment analysis was conducted using the clusterProfiler package. For GSEA, genes ranked by LogFC and genes ranked by correlation with the PTK6 gene were used to analyze KEGG, REACTOME, and Wikipathways gene sets.\u003c/p\u003e\u003cp\u003eSurvival analysis\u003c/p\u003e\u003cp\u003eBased on the expression levels of the PTK6 gene in OV samples, the surv_cutpoint function of the survminer package was used for threshold grouping. The survfit function of the survival package was applied to fit the overall survival (OS) information and grouping information. Finally, the ggsurvplot function of the survminer package was used for analysis and visualization.\u003c/p\u003e\u003cp\u003eCorrelation analysis of immune cell infiltration\u003c/p\u003e\u003cp\u003eImmune infiltration score files of TCGA were downloaded from the TIMER2 database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://timer.comp-genomics.org/\u003c/span\u003e\u003cspan address=\"http://timer.comp-genomics.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Data related to TCGA-OV samples were filtered out, and TIMER/CIBERSORT score data were used to evaluate the distribution and correlation of immune cells in different tumor samples.\u003c/p\u003e\u003cp\u003eCorrelation analysis of signaling pathway\u003c/p\u003e\u003cp\u003eSTAR-counts data and corresponding clinical information for OC tumors were downloaded from the TCGA database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). TPM-formatted data were extracted and normalized via log2(TPM\u0026thinsp;+\u0026thinsp;1) transformation. Genes within relevant pathways were collected and analyzed using the GSVA package in R, with the 'ssgsea' method specified for single-sample gene set enrichment analysis (ssGSEA) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Spearman correlation analysis was applied to assess associations between gene expression and pathway scores. All statistical analyses were performed using R software (v4.0.3).\u003c/p\u003e\u003cp\u003eCell lines\u003c/p\u003e\u003cp\u003eHuman IOSE-80, SK-OV-3, OVCAR-3 cells and mouse ID8 cells were obtained from the Bowers Type Culture Collection (BTCC, Beijing, China). Human OVSAHO cells were obtained from Millipore (Sigma-Aldrich, Burlington, MA, USA). Human Caov-4 cells were obtained from WarnerBio (Wuhan, China). IOSE-80, Caov-4, SK-OV-3and OVCAR-3 cells were maintained in RPMI-1640 medium. OVSAHO human 293T cells and mouse ID8 cells were grown in Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium (DMEM). All culture media were supplemented with 10% fetal bovine serum (FBS; Gibco, Grand Island, NY, USA) and 1% penicillin-streptomycin.\u003c/p\u003e\u003cp\u003ePatients\u003c/p\u003e\u003cp\u003eThis study was performed with the approval of the research ethics board of Xiangyang Central Hospital affiliated hospital of Hubei University of Arts and Science (No. 2025-184-013). The patient provided informed consent for inclusion prior to participation in the study. And the information on ovarian cancer was shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneral characteristics of ovarian cancer patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePatient number\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePrimary location\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eType of ovarian cancer\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003epTNM stage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 1#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 2#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 3#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 4#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 5#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 6#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 7#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 8#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 9#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅡ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 10#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅢ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 11#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅢ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 12#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅢ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 13#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅢ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecase 14#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003efemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHGSOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eⅢ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eReagents, and antibodies\u003c/p\u003e\u003cp\u003eTilfrinib (HY-110244) was obtained from MedChemExpress (Shanghai, China). PTK6 (sc-166171) were purchased from Sant Cruz (Dallas, USA). β-actin (66009-1-Ig) were obtained from Proteintech (Wuhan, China).\u003c/p\u003e\u003cp\u003ePlasmids, transfection, and infection\u003c/p\u003e\u003cp\u003eThe human PTK6-specific shRNA constructs and negative control shRNA (sh-Ctrl) were inserted into the pLKO.1 vector (Tsingke Biotech Co. Ltd, Beijing, China). The target sequences of sh-PTK6 are listed in supplementary Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e. Lentiviruses were produced using HEK-293T cells. For transfection, Neofect DNA transfection reagent (Beijing, China) and specific plasmids were added to 6-well plates. After 6 hours of incubation, the medium was replaced, and cells were harvested at 48 hours post-transfection. Two days after infection, cells were thoroughly washed and subjected to selection with puromycin-containing medium to obtain stably infected cells.\u003c/p\u003e\u003cp\u003eCell viability assay\u003c/p\u003e\u003cp\u003eCells were seeded into 96-well plates and cultured overnight. Following respective treatments, cell viability was assessed using the Cell Counting Kit-8 (CCK-8; C0005, TargetMol, Shanghai, China) assay in accordance with the manufacturer's protocol.\u003c/p\u003e\u003cp\u003eEdU assay\u003c/p\u003e\u003cp\u003eDNA synthesis was assessed using the BeyoClick\u0026trade; EdU-555 Cell Proliferation Kit (C0075, Beyotime, Shanghai, China). The EdU assay was conducted in accordance with the experimental instruction manual. For drug-treated cells, an appropriate number of cells were seeded in 24-well plates, and then drugs were added for a 48-hour treatment. Subsequently, 10 \u0026micro;M EdU was added to the cell culture medium, followed by incubation at 37 ℃ for 2 hours. After removing medium, cells were fixed with 4% paraformaldehyde at room temperature for 15 minutes. Then, 1 ml of permeabilization solution containing 0.3% Triton X-100 was added, and cells were incubated at room temperature for 10\u0026ndash;15 minutes. The Click reaction solution was added, followed by incubation at room temperature in the dark for 30 minutes. Nuclei were stained with Hoechst 33342 for 10 minutes. The cell proliferation parameter was calculated using the following formula: (EdU⁺ cells / Total nuclei) \u0026times; 100%.\u003c/p\u003e\u003cp\u003ePropidium staining\u003c/p\u003e\u003cp\u003ePropidium staining was conducted using the Propidium Iodide Staining Solution (40710ES03, Yeasen Biotechnology, Shanghai, China) in accordance with the experimental instruction manual. Cells were collected using an appropriate method and wash them in PBS. The cells were fixed in pre-cooled 70% ethanol at 4\u0026deg;C for 30 minutes. After washing the cells with PBS, the cells were treated with ribonuclease. PI (propidium iodide) were added with a concentration of 50 \u0026micro;g/mL. Then, the images was obtained by using fluorescence microscope.\u003c/p\u003e\u003cp\u003eColony formation assay\u003c/p\u003e\u003cp\u003eCells were seeded in 6-well plates at optimized densities. Following 24-hour adherence in complete medium, respective treatments were administered and maintained for 48 hours. The plates were then incubated for an additional 10 days under standard culture conditions (37 ℃, 5% CO₂). Resultant colonies were fixed with ice-cold methanol for 15 minutes, stained with crystal violet (Beyotime, Shanghai, China), and subsequently rinsed with PBS. After air-drying, the plates were digitally scanned, and the absorbance (OD value) of the plates was measured.\u003c/p\u003e\u003cp\u003eWound healing assay\u003c/p\u003e\u003cp\u003eCells (1 \u0026times; 10⁵ cells/well) were seeded in 6-well plates and incubated at 37 ℃ until reaching 100% confluence as a uniform monolayer. A straight, vertical scratch was created across each well using a sterile 20-\u0026micro;l pipette tip. The culture plates were then returned to the 37 ℃ incubator for continuous incubation of 24 h. Wound healing progression in each well was observed and imaged under a light microscope [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eQuantitative polymerase chain reaction (QPCR)\u003c/p\u003e\u003cp\u003eTotal RNA was isolated from cells utilizing TRIzol reagent (Invitrogen, Carlsbad, CA, USA). For subsequent mRNA analyses, total RNA was subjected to reverse transcription to generate first-strand cDNA using a cDNA synthesis kit (Vazyme, Nanjing, China). Quantitative real-time PCR (qPCR) was carried out on an ABI 7500 Real-Time PCR System with SYBR Green Premix Ex Taq (Vazyme, Nanjing, China) following the manufacturer's protocols. The primer sequences are provided in supplementary Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e. Relative mRNA expression levels were calculated using the 2^(-ΔΔC\u003csub\u003eT\u003c/sub\u003e) method. All experiments were performed with both biological replicates and technical triplicates.\u003c/p\u003e\u003cp\u003eWestern blot\u003c/p\u003e\u003cp\u003eAfter the cells were collected by centrifugation, they were resuspended in radioimmunoprecipitation assay lysis buffer (Boster, Wuhan, China). Following boiling for 10 minutes, the samples were subjected to ultrasonic disruption on ice, and protein concentrations were determined. Proteins were separated and transferred onto nitrocellulose membranes (GE HealthCare Life Sciences, Loughborough, UK). After blocking with 5% non-fat milk, the membranes were incubated with primary antibodies overnight at 4\u0026deg;C, followed by washing with phosphate-buffered saline containing Tween 20. Subsequently, the membranes were incubated with IRdye 800-conjugated anti-rabbit or anti-mouse immunoglobulin G secondary antibodies for 1 hour at room temperature. Protein bands were visualized using the Odyssey Imaging System (LI-COR, Lincoln, NE, USA).\u003c/p\u003e\u003cp\u003eMolecular docking analysis\u003c/p\u003e\u003cp\u003eMolecular docking analysis was performed according to the method described previously [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The chemical structure of tilfrinib was obtained from the PubChem database. The structure of PTK6 protein was retrieved from PDB database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org/structure/5D7V\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org/structure/5D7V\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The structure was saved in PDB format after removing water molecules and ligands using PyMOL. Subsequent structural refinement and format conversion were performed using Open Babel 2.4.1. Molecular docking simulations were executed using AutoDock Vina 1.1.2. Following docking, the analysis focused on key virtual binding parameters to assess the binding affinity and mode between the ligand and target protein.\u003c/p\u003e\u003cp\u003eMolecular dynamics simulation\u003c/p\u003e\u003cp\u003eMolecular dynamics simulations of the PTK6-tilfrinib complex were performed using the Desmond/Maestro noncommercial version 2022.1 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The system was solvated with TIP3P water molecules and neutralized with 0.15 M NaCl. Following energy minimization and system relaxation, production simulations were conducted for 100 ns under an isothermal-isobaric (NPT) ensemble at 300 K and 1 bar. Trajectory coordinates were recorded at 100 ps intervals. All other parameters were set according to the default protocols.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eTo compare two groups, a two-tailed unpaired Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test or was conducted. For multiple comparisons between more than two groups, a one- or two-way ANOVA followed by Tukey\u0026rsquo;s post hoc test was performed. Kaplan-Meier estimates were utilized to calculate survival curves, and the log-rank test was applied to test differences between groups. Data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. The value of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\n\u003ch3\u003e1. Identification of differential expressed genes in ovarian cancer.\u003c/h3\u003e\n\u003cp\u003eTo explore the differential expressed genes in OC, the data of RNA sequencing was obtained from the TCGA and GTEX databases. A total of 6561 DEGs were identified, including 4284 significantly up-regulated genes and 2277 significantly down-regulated ones (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-C, supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). To further validate this result, we analyzed the sequencing data of ovarian cancer from GSE203130. We identified 1796 differentially expressed genes, including 1639 up-regulated genes and 157 down-regulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-C, supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGO and KEGG pathway were analyzed. The top 20 results were selected for plotting. In up-regulated genes, biological processes mainly involved for regulation of cell-cell adhesion, cell activation and inflammatory response (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). And the mainly enriched KEGG pathway included pathways in cancer, cell cycle, transcriptional misregulation in cancer, and p53 signaling pathway (Supplementary Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA). In down-regulated genes, positive regulation of apoptotic process was interestingly enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). A total of 4 pathways were obtained by KEGG pathway analysis (Supplementary Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB). Collectively, the results of pathway enrichment analysis showed that cell proliferation is crucial in the development of ovarian cancer. We directed our attention to PTK6 among the DEGs, as its function in OC is rarely mentioned. Firstly, PTK6 was found to be elevated in OC tumor tissues according to TCGA and GTEx datasets (Supplementary Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC). Importantly, the expression PTK6 was higher in metastatic ovarian cancer than other ovarian cancer (Supplementary Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eD). Other GSE databases also showed an up-regulation of PTK6 expression (Supplementary Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eE-F). In human ovarian cancer tissues, the expression of PTK6 was significantly upregulated in pTNM stage III tumors compared with stage II tumors, suggesting an association between PTK6 expression and tumor malignancy (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF-G).\u003c/p\u003e\n\u003ch3\u003e2. The prognostic value of PTK6 expression in ovarian cancer.\u003c/h3\u003e\n\u003cp\u003eTo assess the clinical prognosis relevance of PTK6, we carried out the log-rank test. It was found that high levels of PTK6 were correlated with a poor prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). In addition, nomograms for predicting one-year, three-year, and five-year outcomes were developed for overall survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), disease-specific survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), and progression-free interval (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003e3. Single-cell analysis of PTK6 expression in ovarian cancer.\u003c/h3\u003e\n\u003cp\u003eTo identify which cell types express PTK6, we analyzed single-cell expression of PTK6 in OC. The results revealed that PTK6 was mainly expressed in epithelial cells and malignant cells though a low level of PTK6 at the single-cell level (Supplementary Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA-C). Our finding suggested PTK6 might be directly associated with the function of tumor epithelium.\u003c/p\u003e\n\u003ch3\u003e4. Immune features analysis of PTK6 expression in Ovarian Cancer\u003c/h3\u003e\n\u003cp\u003eAs shown in enrichment analysis of DEG, the inflammatory and immune response were also enriched, suggesting a relation of PTK6 with immune response. Consequently, we undertook a correlation analysis by utilizing databases focused on immune cell infiltration. The results revealed that PTK6 was positively related to myeloid dendritic cell, neutrophils and CD4\u003csup\u003e+\u003c/sup\u003e T cells, and that PTK6 expression was negatively correlated with that of B cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B). The relationship between the degree of PTK6 and immune cell abundance was visualized with a lollipop chart (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In OC, PTK6 shows a positive correlation with several immune checkpoints, including C10orf54, VTCN1, CD44, CTLA4, TGFB1, TNFRSF14, ITGB2, TNFRSF18 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003e5. Correlation between PTK6 expression and signaling pathway in ovarian cancer.\u003c/h3\u003e\n\u003cp\u003eTo clarify which signaling pathways in ovarian cancer are closely associated with PTK6, we analyzed the correlation between PTK6 expression and these signaling pathways. The findings demonstrated a significant positive correlation between PTK6 expression and signaling pathways such as angiogenesis, P53 pathway, and inflammatory response (Supplementary Fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). And PTK6 expression was negatively correlated with DNA repair, DNA replication, and G2M checkpoint (Supplementary Fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). The PTK6-related genes analysis demonstrated that the top 10 positively or negatively related genes were obtained in OC (Supplementary Fig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eA-B, supplementary Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Furthermore, the co-expression pattern between these genes and PTK6 was identified (Supplementary Fig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eC-D).\u003c/p\u003e\n\u003ch3\u003e6. PTK6 knockdown significantly inhibited the proliferation and migration of ovarian cancer.\u003c/h3\u003e\n\u003cp\u003eTo investigate the effect of PTK6 on the proliferation and migration of ovarian cancer cells, we first detected the expression of PTK6 in various types of ovarian cancer. It was found that the expression of \u003cem\u003ePTK6\u003c/em\u003e mRNA was significantly up-regulated in OC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The protein level of PTK6 was significantly elevated in Caov-4 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). We used lentivirus shRNA to interfere with \u003cem\u003ePTK6\u003c/em\u003e expression in Caov-4 cells, resulting in a significant down-regulation of PTK6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D). After \u003cem\u003ePTK6\u003c/em\u003e knockdown, microscopic observation showed a marked alteration in the cytomorphology of Caov-4 cells and a notable reduction in the number of cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). The CCK8 assay demonstrated that the Caov-4 cell growth was significantly decreased after \u003cem\u003ePTK6\u003c/em\u003e knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Wound healing assays were performed to evaluate the migratory capacity of ovarian cancer cells. The results showed that Caov-4 cells with \u003cem\u003ePTK6\u003c/em\u003e knockdown exhibited a decreased migratory ability (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG-H). The EdU assay indicated a significant decrease in the DNA synthesis rate of Caov-4 cells after \u003cem\u003ePTK6\u003c/em\u003e knockdown compared to the negative control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI-J). Colony formation assay confirmed that the cell proliferation was inhibited by \u003cem\u003ePTK6\u003c/em\u003e knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK-L). These results suggested that \u003cem\u003ePTK6\u003c/em\u003e interference inhibited the proliferation of ovarian cancer cells.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003e7. Tilfrinib significantly inhibited the proliferation and migration of ovarian cancer cells.\u003c/h3\u003e\n\u003cp\u003eTo verify the binding between tilfrinib and PTK6, we performed analysis of molecular docking and molecular dynamics simulation. And the molecular docking results demonstrated that tilfrinib bind to PTK6 with a binding free energy of -8.5 kcal/mol (Supplementary Fig. \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003eA-B). Meanwhile, after initial fluctuations, the RMSD of the ligand (Supplementary Fig. \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003eC). This indicates that both molecules exhibited minimal fluctuations relative to their initial conformations, highlighting the extremely high stability of their initial conformations. The RMSF values of amino acid residues involved in forming interactions with tilfrinib, suggesting that the binding of tilfrinib to PTK6 are relatively stable (Supplementary Fig. \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003eD). During the simulation, multiple sets of interactions were formed between the protein and the small molecule (Supplementary Fig. \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003eE-F). In summary, the molecular dynamics simulation confirms that tilfrinib and PTK6 exhibit extremely high affinity.\u003c/p\u003e\u003cp\u003eNext, cell proliferation capacity was investigated in Caov-4 cell with a different dose of tilfrinib treatment. The cell viability of Caov-4 cells was inhibited by tilfrinib in a manner dependent on concentration by CCK8 assay. (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-C). The EdU assay demonstrated that tilfrinib suppressed DNA replication (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD-E). Wound healing assays were performed to evaluate the migratory capacity, and the results exhibited a decreased migratory ability of Caov-4 cells after \u003cem\u003ePTK6\u003c/em\u003e knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF-G). The Colony formation assay indicated that tilfrinib inhibited the growth ability of Caov-4 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH-I). In summary, tilfrinib inhibits cell proliferation of OC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThen, we tested the effects of tilfrinib on the proliferation capacity of mouse ID8 cells. The proliferation of ID8 cells was also inhibited by tilfrinib treatment as shown by CCK8 and EdU assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-C). The apoptosis of ID8 cells was increased after tilfrinib treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD-E). Meanwhile, tilfrinib inhibited the growth ability of ID8 cells by colony formation assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF-G). Collectively, these results indicated that pharmacological inhibitor of PTK6 significantly suppressed ovarian cancer cell proliferation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOvarian cancer exhibits a high mortality rate among gynecological malignancies, with epithelial ovarian cancer being the most prevalent subtype. For patients with advanced-stage disease, systemic pharmacotherapy constitutes the cornerstone of treatment [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. While significant advances have been made in ovarian cancer research over recent decades, the five-year survival rate for these patients remains disappointingly low.\u003c/p\u003e\u003cp\u003ePTK6 has emerged as a critical regulator in tumorigenesis and progression. Accumulating evidence highlights its dysregulated expression across multiple malignancies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Our findings demonstrate that PTK6 is significantly upregulated in ovarian cancer (OC) with high expression correlating robustly with poor clinical outcomes. This aligns with its predominant localization in epithelial and malignant cells, suggesting a direct role in tumor cell biology. The observed associations between PTK6 and immune cell infiltration highlight its potential to modulate the tumor immune microenvironment. Concurrently, PTK6\u0026rsquo;s linkage to pro-tumor signaling pathway activation further supports its multifaceted contribution to OC progression. Functional validation through PTK6 knockdown and pharmacological inhibition with tilfrinib confirms its role in promoting cell proliferation and cell migration, while molecular docking studies establish tilfrinib as a promising PTK6-targeted agent with dose-dependent anti-proliferative effects. Collectively, these results position PTK6 as a novel prognostic biomarker and therapeutic target, offering a rationale for further preclinical and clinical exploration of PTK6 inhibition in OC management.\u003c/p\u003e\u003cp\u003ePTK6 expression is aberrantly elevated in most solid tumors, with distinct patterns across cancer types [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Pan-cancer analyses utilizing TCGA and GTEx datasets reveal that PTK6 is upregulated in over 70% of tumor types, including breast cancer (BC), colorectal cancer (CRC), cervical cancer, prostate cancer, ovarian cancer, bladder cancer, clear cell renal carcinoma (KIRC), and pancreatic ductal adenocarcinoma (PDAC) [\u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In cervical cancer, PTK6 levels are markedly increased in cell lines and clinical tissues [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Similarly, in CRC, PTK6 is overexpressed in tumor tissues and cell lines, with higher levels linked to advanced stages and poor survival in patients receiving chemotherapy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In prostate cancer, elevated PTK6 expression is associated with poor patient prognosis. PTK6 demonstrates cytoplasmic relocalization in tumor cells, in contrast to its nuclear localization in normal prostate epithelium [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. And it was reported that PTEN loss-driven tumorigenesis critically depends on consequent PTK6 activation via Y342 phosphorylation, supporting that PTK6 activation promotes invasive prostate cancer [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. PTK6 shapes the tumor immune microenvironment to facilitate immune evasion [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In breast cancer, high PTK6 expression correlates with increased infiltration of NK cells and Th17 cells, while negatively associating with Th1 cells, macrophages, and cytotoxic T cells [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This suggests PTK6 may promote an immunosuppressive TME, potentially impairing anti-tumor immunity.\u003c/p\u003e\u003cp\u003ePTK6 inhibitors, have shown promise in preclinical studies by suppressing PTK6 activity. In breast cancer, XMU-MP-2 disrupt FAK phosphorylation, inhibiting AKT activation and reducing cancer cell survival [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In colorectal cancer, they target the PTK6-JAK2/STAT3 axis, diminishing cancer stem cell traits and reversing chemoresistance to drugs like 5-fluorouracil and oxaliplatin [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTilfrinib is a selective inhibitor of PTK6 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In breast cancer cell lines, tilfrinib has shown good anti-proliferative activity. PTK6 has been found to drive the phase separation of HNRNPH1, which in turn activates autophagy and suppresses apoptosis in CRC cells [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In patient-derived organoids (PDO) and mouse xenograft models of CRC, tilfrinib treatment significantly inhibits tumor growth. By inhibiting PTK6, tilfrinib disrupts this autophagy pathway, tipping the balance towards apoptosis and ultimately suppressing tumor growth.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eOC, ovarian cancer; HGSOC, high-grade serous ovarian cancer; BRK, breast tumor kinase; OS, overall survival; TME, tumor microenvironment; PROTACs, proteolysis - targeting chimeras; TPM, transcripts per million; ssGSEA, single-sample gene set enrichment analysis; VTCN1, RMSD, root mean square deviation; RMSF, root mean square fluctuation; IRS-4, insulin receptor substrate 4; PDO, patient-derived organoids.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed with the approval of the research ethics board of Xiangyang Central Hospital affiliated hospital of Hubei University of Arts and Science (Approval No. 2025-041-014). This study was conducted in compliance with the Declaration of Helsinki and all applicable ethical guidelines. Patients provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors agree with the publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the project of the National Natural Science Foundation of China [grant no. 82472634 and 82301374]; the Key Research \u0026amp; Development Program of Hubei Province [grant no. 2023BCB128 and 2024BCB055]; the Hubei Provincial Natural Science Foundation of China [grant no. 2024AFD428 and 2025AFD068]; the project of Xiangyang Central Hospital [grant no. 2024BS03].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL.T.Z. and Z.L. wrote the main manuscript text. L.T.Z. and Z.L. conducted the experiments and analyzed the data. L.T.Z., F.H. and J.Y. prepared figures and data. X.Y. performed the supervision work. X.Q., H.X. and L.F. revised the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWei YF, Ning L, Xu YL, Ma J, Li DR, Feng ZF, Liu FH, Li YZ, Xu HL, Li P et al. Worldwide patterns and trends in ovarian cancer incidence by histological subtype: a population-based analysis from 1988 to 2017. \u003cem\u003eEClinicalMedicine\u003c/em\u003e 2025, 79:102983.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Duval AJ, Adli M, Matei D. Biology-driven therapy advances in high-grade serous ovarian cancer. 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Autophagy. 2025;21(8):1680\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ovarian cancer, PTK6, cell proliferation, tilfrinib","lastPublishedDoi":"10.21203/rs.3.rs-8166231/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8166231/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThis study investigates the oncogenic role of Protein Tyrosine Kinase 6 (PTK6) in ovarian cancer (OC), focusing on its clinical prognosis, and its function on OC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eMulti-omics analyses to identify differentially expressed genes (DEGs). PTK6 expression was validated across datasets and correlated with survival, tumor stage and signaling pathways. Functional assays included lentiviral PTK6 knockdown and pharmacological inhibition (tilfrinib) in OC cells, evaluated via CCK-8, EdU, wound healing assay, colony formation, and molecular docking.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePTK6 was upregulated in OC, with high expression linked to poor overall, disease-specific, and progression-free survival. Single-cell analysis localized PTK6 predominantly to epithelial and malignant cells. PTK6 knockdown suppressed the proliferation and migration of Caov-4 and ID8 cells. Tilfrinib forms a stable complex with PTK6 and inhibits cell proliferation in a dose-dependent manner.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003ePTK6 drives OC progression via proliferation, immune evasion, and oncogenic pathway regulation. Inhibition of PTK6 by tilfrinib constitutes a promising targeted therapy for ovarian cancer.\u003c/p\u003e","manuscriptTitle":"Inhibition of PTK6 Hinders the Growth and Migration of Ovarian Cancer and Its Potential Clinical Significance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 17:32:17","doi":"10.21203/rs.3.rs-8166231/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0122d4c1-965d-42ce-98f3-7d77214badc8","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T10:26:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 17:32:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8166231","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8166231","identity":"rs-8166231","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}