TYMS and CENPF emerge as key oncogenes and prognostic markers in glioma

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The high mortality rate among glioma patients is largely attributed to tumor metastasis and unfavorable prognosis. Diverse analysis of genomic and transcriptomic alterations is found in glioma, posing an urgent need for identifying novel therapeutic and prognostic targets with underlying molecular mechanisms. Methods The functional status relevant to TYMS and CENPF in pan-cancer was analyzed using CancerSEA database. We assessed the expression levels and clinical characteristics of TYMS and CENPF in TCGA-glioma data. The prognostic potential of TYMS and CENPF was assessed through Kaplan-Meier survival curve analysis and Cox proportional hazards modeling. To identify co-expressed genes, we applied a correlation analysis with a high R-value threshold, followed by PPI network construction and GSEA. Additionally, a gene-chemical interaction network was built using data from the Comparative Toxicogenomics Database (CTD), providing a framework for exploring potential therapeutic relationships. Furthermore, we collected clinical glioma tissue samples and detected mRNA and protein expression levels using qPCR and HPA analysis. Results We showed that TYMS and CENPF overexpression were notably higher in glioma patients, and related to histological types and glioma WHO grades. TYMS and CENPF were clinically correlated with worse prognosis in glioma and could be potential independent prognostic factors. GSEA analysis indicated that TYMS/CENPF and ten co-expressed genes regulated glioma cell motility and other cell behaviors via PI3K/AKT and MET signaling pathways. Conclusions Our findings suggested that aberrant TYMS/CENPF expression was significantly linked to glioma WHO grades and poor survival rates, contributing to a more comprehensive understanding of glioma therapeutic targets. Glioma WHO grade therapeutic target prognosis drug interaction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Glioma is a common brain malignancy originating from the central nervous system, with glioblastoma (GBM) being one of the most aggressive WHO glioma grades [ 1 ]. Due to the aggressive biological characteristics of glioma, the 5-years overall survival rate for patients with GBM is 15–18 months [ 2 ]. Furthermore, the prognosis for glioma recurrence is particularly grim, with a median survival duration of only 6–9 months, underscoring the need for more effective treatment strategies [ 3 ]. Malignant cancer recurrence and metastasis after surgery resection followed by chemotherapy and/or radiation are the primary cause of mortality in glioma patients [ 4 ]. The current clinical evaluation of gene-directed therapies underscores the importance of continued research into new molecular targets, which could ultimately lead to the creation of more potent and targeted treatments. Thymidylate synthetase (TYMS) is a cofactor which catalyzes the methylation of deoxyuridylate to deoxythymidylate in the regulation of DNA replication and repair [ 5 ]. Functionally, the polymorphism of TYMS gene is a kind of etiopathogenesis in tumorigenesis, including hepatocellular carcinoma [ 6 ] and colorectal cancer [ 7 ]. Increasing evidence suggests that TYMS improves cancer cell responsiveness to chemotherapy, such as functioning as a key target of 5-FU treatment and inhibiting tumor cell proliferation [ 8 ]. Centromere protein F (CENPF) encodes a protein that related to the centromere-kinetochore complex and maintains cell cycle in the G2 phase [ 9 ]. In cancer, it has been reported that CENPF positively regulates cell growth, inhibits cell apoptosis and tumor metastasis in papillary thyroid cancer [ 10 ]. Nevertheless, the specific function of TYMS and CENPF gene in glioma remains unknown and needs to be explored. In this research, we aimed to investigate the function of TYMS and CENPF accompanied by the underlying regulatory mechanism in glioma. To achieve this, we performed RNA-seq analysis using TCGA-GBMLGG cohorts, allowing for a comprehensive investigation of TYMS/CENPF-regulated proteins and signaling pathways. Collectively, these results highlighted that TYMS and CENPF were related to decreased overall survival in patients with glioma, suggesting their clinical values as prognostic and therapeutic target in glioma. Mechanistically, we also investigated the co-expressed genes regulated by TYMS and CENPF and the specific regulatory signaling pathways in glioma. Methods and materials Cancer cell function analysis We employed the CancerSEA platform ( http://biocc.hrbmu.edu.cn/CancerSEA/home.jsp ) to conduct a comprehensive analysis of cancer cell function at the single-cell level. Subsequent correlation analysis revealed the relationships between TYMS/CENPF expression and various functional states, including angiogenic potential, metastatic capacity, cell cycle progression, and invasive behavior. Expression levels of TYMS/CENPF and clinical significance in glioma We analyzed individual TYMS/CENPF expression levels in normal and glioma tissue samples using TCGA clinical data and the R package. Our analysis included data from the TCGA-GBMLGG dataset for glioma samples, while normal tissue data were obtained from the Genotype-Tissue Expression (GTEx) project. The Wilcoxon test was used to compare data between normal and HCC tissue samples, and the Kruskal-Wallis test was employed to analyze the relationships between multiple clinical parameters, including age, histological types, and WHO grade, with statistical significance defined as p < 0.05. Survival analysis of TYMS and CENPF in glioma To assess the relationship between TYMS/CENPF expression and glioma patient survival, we created Kaplan-Meier survival curves for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). Patients were divided into two groups based on the median value of TYMS/CENPF mRNA transcripts. To further understand the relationship between clinical risk factors and overall survival, we conducted univariate and multivariate analysis to assess the individual and combined effects of these factors on patient survival." PPI network analysis and gene set enrichment analysis (GSEA) TCGA-GBMLGG cohorts were divided into two groups based on the high/low expression levels of TYMS or CENPF. The genes that coded with proteins were screened with both of Pearson and Spearman correlation R > 0.75. Then, TYMS, CENPF and other ten proteins were subjected to PPI network analysis using GeneMAINA ( http://genemania.org/ ). In addition, gene sets or signaling pathways were considered to be significantly enriched if normalized enrichment score (NES) > 1, p.adjust < 0.05 and qvalue < 0.25. Gene-chemicals interaction network analysis We employed the Comparative Toxicogenomics Database (CTD, http://ctdbase.org/ ) to explore the interactions between TYMS/CENPF and anti-glioma chemicals. By utilizing Cytoscape software, we created a gene-chemical interaction network to visualize the relationships between TYMS/CENPF and various compounds. Our analysis aimed to identify chemicals that influence the expression of TYMS/CENPF, either by increasing or decreasing their mRNA or protein levels. qRT-PCR analysis of TYMS/CENPF expression levels in glioma tissues A total of 20 glioma patients who underwent surgery between 2021 and 2023 was included in this study. None of these patients had undergone preoperative radiotherapy, chemotherapy, targeted therapy, or immunotherapy, ensuring that the tissue samples were free from treatment-induced alterations. Following surgical excision, the tumor tissues and cerebral cortex tissues were rapidly frozen in liquid nitrogen to facilitate subsequent molecular analysis. The protocol was reviewed and approved by the Ethics Committee of Second hospital of Shanxi medical university. Glioma tissues and cerebral cortex were subjected to RNA extraction using TRIzol Reagent (Invitrogen), followed by reverse transcription into cDNA using the Reverse Transcription Kit (Qiagen, Hilden, Germany). The cDNA was then analyzed by qPCR using Green Premix Ex Taq II (TaKaRa, Japan) on Applied Biosystems Real-Time PCR System (Foster City, CA, USA). Gene expression levels were quantified using the 2 − ΔΔCt method, with GAPDH serving as a housekeeping gene for normalization purposes. The primers of TYMS and CNEPF are listed as following: TYMS forward primer, 5’-CTGGGGCAGATCCAACACAT-3’, TYMS reverse primer: 5’-GCCCAAGTCCCCTTCTTCTC-3’, CENPF forward primer: 5’-CTCCGAGAGGTCGTTTTCCC-3’, CENPF reverse primer: 5’-CGCAGCTTGTTGGCTTCTTT-3’. Results Relevant function states of TYMS and CENPF in glioma Given the lack of exploring function relevant to pan-cancer, our study was the first to comprehensively assess functional signatures of TYMS and CENPF at the single-cell level via CancerSEA database. The c emphasized the positive correlation between TYMS and several functional states, including cell cycle, EMT, invasion, metastasis and proliferation in glioma (Fig. 1 A). Additionally, CENPF showed a strong correlation with glioma cell proliferation, cell cycle and cell invasion (Fig. 1 B). The results highlighted a novel associated functional heterogeneity of glioma cells and reflected the functional states of TYMS and CENPF with tumorigenesis and progression. TYMS and CENPF mRNA expression levels and clinical characteristics in glioma To clarify the distinct characteristics between non-tumor tissues and glioma samples, we conducted RNA-sequencing analysis using TCGA-GBMLGG cohort. Normal GTEx sample was utilized as control for comparison. A noteworthy finding was that when focusing on gene differential expression of TYMS and CENPF, both log2(TPM + 1) of TYMS and CENPF in glioma tissues (n = 701) was substantially higher than that in non-tumor samples (n = 5) (p < 0.01, Fig. 2 ). Furthermore, higher TYMS and CENPF expression levels was associated with advanced clinical histological type (glioblastoma vs astrocytoma, glioblastoma vs oligodendroglioma, glioblastoma vs oligoastrocytoma) (p < 0.001, Fig. 3 A- 3 B). For patients with glioma graded in G4/G3, TYMS and CENPF levels were upregulated in high grade glioma tissues compared to those without WHO G2 grade glioma tissues (p < 0.001, Fig. 3 C- 3 D), suggesting that TYMS and CENPF might correlate with tumor malignant degree. Additionally, baseline information including clinical characteristics of glioma patients (699 samples) are summarized in Table 1 . Clinical variable analysis showed that TYMS and CENPF expression in glioma tissues was positively associated with age, IDH status, 1p/19q codeletion and primary therapy outcome (all p < 0.001). Table 1 Baseline clinical characteristics data of glioma patients. TYMS expression CENPF expression Characteristics Low expression (n = 349) High expression (n = 350) p value Low expression (n = 349) High expression (n = 350) p value Age n (%) 60 35 (5%) 108 (15.5%) 46 (6.6%) 97 (13.9%) Gender n (%) Female 157 (22.5%) 141 (20.2%) 0.21 149 (21.3%) 149 (21.3%) 0.97 Male 192 (27.5%) 209 (29.9%) 200 (28.6%) 201 (28.8%) IDH status n (%) WT 34 (4.9%) 212 (30.8%) 1.19E-45 59 (8.6%) 187 (27.1%) 1.86E-24 Mut 311 (45.1%) 132 (19.2%) 286 (41.5%) 157 (22.8%) 1p/19q codeletion n (%) Non-codel 236 (34.1%) 284 (41%) 7.24E-06 223 (32.2%) 297 (42.9%) 1.26E-11 Codel 112 (16.2%) 60 (8.7%) 125 (18.1%) 47 (6.8%) Primary therapy outcome n (%) PD 54 (11.6%) 58 (12.5%) 0.0006 44 (9.5%) 68 (14.6%) 9.69E-06 SD 98 (21.1%) 50 (10.8%) 87 (18.7%) 61 (13.1%) PR 47 (10.1%) 18 (3.9%) 45 (9.7%) 20 (4.3%) CR 99 (21.3%) 41 (8.8%) 96 (20.6%) 44 (9.5%) Prognostic values of TYMS and CENPF in glioma To appraise the prognostic implications of TYMS and CENPF upregulation in glioma samples, we performed Kaplan-Meier analysis with glioma patients. The presence of obvious aberrant TYMS gene expression upregulation, as confirmed by gene expression grouping analysis, was related to significantly reduced survival probability, including OS, DSS and PRI, compared to those with low gene expression (p < 0.001, Fig. 4 ). Moreover, glioma patients with high expressing CENPF had a significant shorter survival than those with lower CENPF expression (p < 0.001, Fig. 4 ). Univariate (p < 0.001) and multivariate (p = 0.019) Cox regression analysis indicated that high CENPF expression was one of the independent risk factors patients with glioma (Table 2 ). In addition, with univariate Cox regression analysis, the expression of TYMS (p < 0.001) also did appear to be an independent prognostic factor, like IDH status and 1p/19q codeletion (p < 0.001) (Table 2 ). The results suggested that the identified TYMS and CENPF have high clinical values as prognostic factors for predicting worse outcomes in glioma. Table 2 Univariate and multivariate cox regression analysis Univariate analysis Multivariate analysis Characteristics Total(N) HR(95% CI) P value HR(95% CI) P value TYMS Low 349 4.798 (3.626–6.347) < 0.001 1.177 (0.700–1.979) 0.539 High 349 CENPF Low 349 3.188 (2.439–4.168) < 0.001 1.761 (1.097–2.826) 0.019 High 349 Age <= 60 555 4.696 (3.620–6.093) < 0.001 3.996 (2.461–6.489) 60 143 Gender Female 297 1.250 (0.979–1.595) 0.073 1.535 (1.024–2.303) 0.038 Male 401 IDH status WT 246 0.116 (0.089–0.151) < 0.001 0.422 (0.253–0.705) < 0.001 Mut 442 1p/19q codeletion Non-codel 520 0.225 (0.147–0.346) < 0.001 0.821 (0.446–1.510) 0.526 Codel 171 Histological type Astrocytoma 196 - - - - Oligodendroglioma 199 0.578 (0.393–0.849) 0.005 0.621 (0.381–1.011) 0.056 Oligoastrocytoma 135 0.646 (0.412–1.013) 0.057 0.933 (0.556–1.565) 0.793 Glioblastoma 168 6.791 (4.931–9.352) < 0.001 2.921 (0.995–8.579) 0.051 Primary therapy outcome PD 112 - - - - SD 148 0.440 (0.294–0.658) < 0.001 0.502 (0.319–0.791) 0.003 PR 65 0.167 (0.073–0.385) < 0.001 0.217 (0.092–0.515) < 0.001 CR 139 0.131 (0.063–0.273) < 0.001 0.160 (0.074–0.347) < 0.001 PPI network analysis To explore the downstream regulatory network of TYMS and CENPF in glioma, and to better elucidate gene interaction mechanisms, single gene differential expression analysis was performed to identify the genes that have strong correlation with TYMS/CENPF expression in glioma. Co-expressed genes were screened with the criteria of |Pearson’s R| >= 0.75, |Spearman’s R| >= 0.75 and p < 0.05. A total of top 10 co-expressed genes, including TK1, PCLAF, RRM2, CENPK, E2F7, KIF14, ASPM, BUB1B, TOP2A and TPX2, were highly correlated with TYMS/CENPF expression levels in glioma (Fig. 5 A). Furthermore, in order to classify the protein alterations induced by RRAS2 overexpression, we conducted PPI analysis with the top 10 co-expressed genes. We found that 94.09% had similar co-expression network among the co-expressed 30 proteins (Fig. 5 B). GSEA analysis in glioma To determine the underlying mechanism by which TYMS/CENPF mediates glioma, GSEA enrichment analysis was carried out in TCGA-GBMLGG datasets. The results revealed an obvious activation of PI3K-AKT signaling pathway (NES = 1.283, p = 0.025, FDR = 0.019) in the TYMS-high expression group (Fig. 6 A). PI3K-AKT pathway has been identified within glioma, indicating the increased activity of GBM mutations and glioma malignancy [ 11 ]. In addition, we found a hallmark of promoting cell motility induced by MET in CENPF-expressing glioma (NES = 1.957, p < 0.001, FDR < 0.001) (Fig. 6 B). The GSEA enrichment results suggested that TYMS and CENPF expression was significantly related to enhanced glioma cell motility and tumor progression. Drug interaction network in glioma To investigate the drug interaction targeting TYMS/CENPF in glioma, gene-drug network was constructed via the Comparative Toxicogenomics Database (CTD). As shown in Fig. 7 A, a total of 18 drugs have influences on the expression of TYMS in glioma. The levels of TYMS were positively increased by 10 drugs, including camptothecin, cisplatin, fluorouracil, indomethacin and etc. The remaining 8 drugs could inhibit TYMS expression in glioma. A lower expression of CENPF expression was observed in 1,3-butadiene and quercetin-treated glioma samples (Fig. 7 B). Moreover, 10 drugs have the function of promotion on CENPF levels in glioma. TYMS and CENPF was upregulated in glioma tissues The bioinformatics analysis of TYMS/CENPF encouraged us to further investigate the expression levels in glioma clinical specimens. When compared with cerebral cortex tissues, immunohistochemical analysis of glioma revealed the upregulation of TYMS and CENPF proteins (Fig. 8 A- 8 B). Next, 20 clinical tissues were collected from glioma patients and their TYMS/CENPF expression was assessed using qPCR analysis. In glioma tissues, TYMS/CENPF levels were expressed 3-fold more highly than in non-tumor tissues, indicating an upregulation of TYMS/CENPF mRNA expression after tumor initiation event (p < 0.001, Fig. 8 C). Discussion Our study evaluated the potential role of TYMS and CENPF in glioma and explored the downstream mechanism regulated by TYMS and CENPF. Here, we show that patients expressing high TYMS/CENPF genes have a poor survival than those with low TYMS/CENPF expression. The analysis of TCGA data revealed that TYMS and CENPF expression levels were the highest in WHO G4 grade (GBM) tissues and lower in low-grade glioma samples. Mechanistically, TYMS/CENPF directly interacted with 10 top hub genes and are involved in cell cycle in glioma. More importantly, TYMS/CENPF-related genes activated the PI3K/AKT and MET signaling pathways in glioma, participating in glioma malignant process. TYMS-expressing xenograft model has been identified to show genomic instability, DNA damage and tumorigenesis acceleration [ 5 ]. For example, downregulation of TYMS inhibited breast cancer cell proliferation and invasion via EMT pathways [ 7 ]. Additionally, CENPF acts as a novel regulator of tumor cell metabolism, including cell cycle and metastasis, in prostate cancer [ 12 ] and triple-negative breast cancer [ 13 ]. To elucidate the functional states regulated by TYMS/CENPF, we performed the single cells analysis based TYMS/CENPF expression levels. Our results revealed that enrichment of cell cycle, DNA damage, proliferation and EMT process are also found in TYMS/CENPF-expressed glioma, suggesting the potential functional status to be further elucidated. IDH1/2 mutation is observed in approximately 65–90% of LGG patients, indicating a relatively favorable outcome and a low invasiveness in comparison with IDH-wild type glioma [ 14 ]. Targeted anti-IDH-mutation therapies are the key strategies for low-grade glioma (LGG), aiming to inhibit tumor procession [ 1 , 15 ]. Recent studies show that IDH is a unique therapeutic target, however, selective inhibitors targeting IDH mutation is challenging as there is drug resistance to IDH inhibitors in glioma cells [ 16 ]. We demonstrate here that IDH wild type is found at a significantly higher proportion than mutated type in high TYMS/CENPF expression groups, indicating that TYMS/CENPF expression levels might be related to IDH status in glioma. Our data also show that TYMS/CENPF was overexpressed across all glioma histological types but is more highly expressed in patients with high grade glioma than in low grade ones. Given that high grade glioma overexpressing TYMS/CENPF promote tumor progression and malignancy grade, TYMS/CENPF-coexpressed genes seems to be preferentially linked to glioma developing. Therefore, our research further explored the PPI network and GSEA enrichment score of TYMS/CENPF-coexpressed genes in glioma. PI3K/AKT has been confirmed as an essential signaling pathway in regulating glioma progression and malignant metastasis [ 17 ]. The dysregulation of PI3K/AKT pathway activates growth factors and influences glioma cell growth via promoting biosynthetic pathways [ 18 ]. Several literatures have demonstrated that therapeutic agents, targeting PI3K/AKT pathway, such as temozolomide, are currently in clinical development for improving blood-brain barrier and reducing systemic toxicity [ 19 ]. Accumulating studies indicated that MET is a pivotal oncogenic driver in cell biology and stemness of glioma [ 20 ]. MET is amplificated in transgenic mouse models and then accelerated GBM formation in vivo [ 21 ]. Copy number amplification and overexpression of MET often results in promoting glioma development and a shorter overall survival [ 22 ]. Here, we suggest, for the first time, that the 10 co-expressed genes with TYMS/CENPF participated in activating PI3K/AKT and MET signaling pathways to maintain glioma cell motility and malignance. Collectively, the study shows that TYMS/CENPF is overexpressed in the vast majority of glioma samples regardless of WHO grade, histological type, IDH mutation and1p/19q codeletion. Moreover, the human data suggests that high TYMS/CENPF expression in glioma is associated with shorter survival and worse prognosis in glioma. Our research elucidated the intricate interplay between TYMS/CENPF and ten proteins in glioma, underscoring their significant contribution to cell cycle and motility via PI3K/AKT and MET signaling pathways. The precise mechanisms by which TYMS contributes to glioma development and progression remain unclear, with cell-based experiments providing incomplete insights that necessitate further investigation. In conclusion, we have identified TYMS and CENPF as key druggable targets that hold promise for the treatment of glioma, thereby providing insights into potential therapeutic strategies for glioma treatment and poor prognosis. Declarations Acknowledgements Data availability statement The Cancer Genome Altas tumor cohorts analyzed in this research can be available at https://portal.gdc.cancer.gov/. Ethical approval statement The Ethics Review Committee of Second Hospital of Shanxi Medical University reviewed and approved this study. Written informed consent was obtained from all subjects before their participation in the study. Author contributions Conceptualization: XY and SW. Methodology: XY, QW, QL. Software: QW, QL, RD. Validation: XY, QW, QL. Formal analysis: QL, RD. Investigation: XY, LC, MJ. Resources: MJ, SW. Data Curation: XY, QW, QL. Visualization: RD, LC. Supervision: LC. Project administration: LC. Writing - Original Draft: XY, MJ, SW. 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Wang, D., et al., CENPF knockdown inhibits adriamycin chemoresistance in triple-negative breast cancer via the Rb-E2F1 axis. Sci Rep, 2023. 13 (1): p. 1803. Miller, J.J., Targeting IDH-Mutant Glioma. Neurotherapeutics, 2022. 19 (6): p. 1724-1732. Lukas, R.V. and C. Horbinski, Glioma Response to IDH Inhibition: Real-World Experience. Clin Cancer Res, 2023. 29 (23): p. 4709-4710. Alshiekh Nasany, R. and M.I. de la Fuente, Therapies for IDH-Mutant Gliomas. Curr Neurol Neurosci Rep, 2023. 23 (5): p. 225-233. Mohamed, E., et al., PI3K/AKT/mTOR signaling pathway activity in IDH-mutant diffuse glioma and clinical implications. Neuro Oncol, 2022. 24 (9): p. 1471-1481. Obrador, E., et al., Glioblastoma Therapy: Past, Present and Future. Int J Mol Sci, 2024. 25 (5). Wang, D., et al., Apigenin and Temozolomide Synergistically Inhibit Glioma Growth Through the PI3K/AKT Pathway. Cancer Biother Radiopharm, 2024. 39 (2): p. 125-132. Awad, A.J., et al., Targeting MET for glioma therapy. Neurosurg Focus, 2014. 37 (6): p. E10. Fischer, U., et al., Amplification of the MET gene in glioma. Genes Chromosomes Cancer, 1995. 12 (1): p. 63-5. Mulcahy, E.Q.X., R.R. Colόn, and R. Abounader, HGF/MET Signaling in Malignant Brain Tumors. Int J Mol Sci, 2020. 21 (20). Additional Declarations No competing interests reported. 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4997083","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":359668248,"identity":"7303647a-ec11-44db-affe-bb9c01b01687","order_by":0,"name":"Xiaofeng Yin","email":"","orcid":"","institution":"Second hospital of Shanxi medical university","correspondingAuthor":false,"prefix":"","firstName":"Xiaofeng","middleName":"","lastName":"Yin","suffix":""},{"id":359668249,"identity":"9c98f55f-3b50-4e1b-baf6-9aed81701e6b","order_by":1,"name":"Quansheng Wu","email":"","orcid":"","institution":"Second hospital of Shanxi medical university","correspondingAuthor":false,"prefix":"","firstName":"Quansheng","middleName":"","lastName":"Wu","suffix":""},{"id":359668252,"identity":"57ddf4dd-9f20-4ae5-a684-78fceb8ab5b9","order_by":2,"name":"Qi Liu","email":"","orcid":"","institution":"Second hospital of Shanxi medical university","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Liu","suffix":""},{"id":359668253,"identity":"ac8479d0-13a3-4ba6-9840-aeeb079410cf","order_by":3,"name":"Rui Ding","email":"","orcid":"","institution":"Second hospital of Shanxi medical university","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Ding","suffix":""},{"id":359668259,"identity":"ad1fcf01-190f-4d76-9539-57a16c530760","order_by":4,"name":"Laizhao Chen","email":"","orcid":"","institution":"Second hospital of Shanxi medical university","correspondingAuthor":false,"prefix":"","firstName":"Laizhao","middleName":"","lastName":"Chen","suffix":""},{"id":359668260,"identity":"3df8321e-73d6-438d-9d91-30606dc787df","order_by":5,"name":"Mingliang Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYBACg8MMDMwMNhIM/MzMhx8QpcUSrIVHgkGynS3NgCgt9gfAWoDWnedRkCBKi9lx3sOvGXgs8owP8zAYMNTYRBPWcpgvzRrosGKzw7wHHjAcS8ttIKyFx8wYqCVx22G+BAPGhsOEtRjAtGxu5jGQIFaL8WOGHonEDcwkaDFjZrghkTjjMDCQE4jxi8H5M8affxTUJfb3Hz784EONDWEtQMCGiI4EIpSDAPMHIhWOglEwCkbBSAUAy8I6ULDSlpYAAAAASUVORK5CYII=","orcid":"","institution":"Taiyuan central hospital","correspondingAuthor":true,"prefix":"","firstName":"Mingliang","middleName":"","lastName":"Jin","suffix":""},{"id":359668264,"identity":"c281a50f-fb17-496e-8ec9-27b2a778386e","order_by":6,"name":"Songquan Wang","email":"","orcid":"","institution":"Second hospital of Shanxi medical university","correspondingAuthor":false,"prefix":"","firstName":"Songquan","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-08-29 10:57:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4997083/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4997083/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66869659,"identity":"9b045237-d527-4a74-a9b7-0b546a9d6d84","added_by":"auto","created_at":"2024-10-17 09:34:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6485859,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional status of TYMS and CENPF in pan-cancer.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCancerSEA analysis showed the correlation between functional status and (A) TYMS or (B) CENPF genes in pan-cancer.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/6165c9bb55cba12a0e95ca73.png"},{"id":66869650,"identity":"714b1490-becb-4293-864a-8075612848c2","added_by":"auto","created_at":"2024-10-17 09:34:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2173772,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTYMS and CENPF expression is upregulated in TCGA-GBM/LGG cohorts.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) TYMS and (B) CENPF expression in glioma TCGA and GTEx datasets. **p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/d580b319e71a471c6883a6ff.png"},{"id":66869656,"identity":"f60b289c-0e18-4f02-8dcf-aa0342020f68","added_by":"auto","created_at":"2024-10-17 09:34:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2387399,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe correlation analysis between TYMS/CENPF expression levels and clinical characteristics in glioma.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe box plot chart indicates the mRNA expression levels of TYMS/CENPF in different (A-B) histological types and (C-D) WHO grades of glioma. ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/761923f3f22cc4188c3d12ab.png"},{"id":66869652,"identity":"6d66d817-eec6-4b15-8c19-8cd99638e644","added_by":"auto","created_at":"2024-10-17 09:34:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3643131,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrognostic values of TYMS and CENPF in glioma.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaplan-Meier analysis of overall survival (OS), disease specific survival (DSS) and progress free interval (PFI) in high or low TYMS/CENPF expressing glioma patients.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/f4c798dd53405673cbcc1b58.png"},{"id":66871158,"identity":"979bef64-b556-4095-9ee1-0769f3587b8f","added_by":"auto","created_at":"2024-10-17 09:42:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2430053,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePPI network analysis of TYMS/CENPF-related proteins in glioma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmaps showing the top 10 upregulated genes in TYMS/CENPF-expressed glioma. (B) PPI analysis identifying 10 hub genes in the interaction proteins related to TYMS/CENPF.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/902caa2b9e9fa0a538fe2399.png"},{"id":66869651,"identity":"d3a290de-719f-406e-8c74-443ce1386d2e","added_by":"auto","created_at":"2024-10-17 09:34:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1752864,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGSEA analysis in glioma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGSEA analysis reveals the enrichment of signaling pathway related to high(A) TYMS and (B) CENPF expression in glioma.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/49f224ab6e0c6c2d1a80d528.png"},{"id":66869658,"identity":"94f3f856-05ab-4694-b0e1-05789e6ec477","added_by":"auto","created_at":"2024-10-17 09:34:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":4874429,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDrug interaction network in glioma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe chemical-gene interaction network showing the drugs increased mRNA expression of (A) TYMS and (B) CENPF. The red line represents the drugs that increased TYMS/CENPF expression. The green line represents the drugs that decreased TYMS/CENPF expression. The gray line represents the drugs that have none effects on TYMS/CENPF expression.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/3691a21820398ba2fca581c1.png"},{"id":66869654,"identity":"28c813e9-fda4-436a-a7d6-7d82d62674be","added_by":"auto","created_at":"2024-10-17 09:34:43","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":5520476,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTYMS and CENPF was upregulated in glioma tissues\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Immunohistochemical analysis of TYMS and CENPF protein expression levels in glioma and cerebral cortex tissues.\u003c/p\u003e\n\u003cp\u003e(B) qPCR analysis of TYMS and CENPF mRNA expression in glioma and non-tumor tissues. ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/a3710311e5bb799a61b39933.png"},{"id":68246683,"identity":"3646970a-129d-4e63-97e4-27e0a233b4b1","added_by":"auto","created_at":"2024-11-05 09:18:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":41457876,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4997083/v1/7fc5da08-351c-47a2-b669-62c4ec4659cd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"TYMS and CENPF emerge as key oncogenes and prognostic markers in glioma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlioma is a common brain malignancy originating from the central nervous system, with glioblastoma (GBM) being one of the most aggressive WHO glioma grades [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Due to the aggressive biological characteristics of glioma, the 5-years overall survival rate for patients with GBM is 15\u0026ndash;18 months [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Furthermore, the prognosis for glioma recurrence is particularly grim, with a median survival duration of only 6\u0026ndash;9 months, underscoring the need for more effective treatment strategies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Malignant cancer recurrence and metastasis after surgery resection followed by chemotherapy and/or radiation are the primary cause of mortality in glioma patients [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The current clinical evaluation of gene-directed therapies underscores the importance of continued research into new molecular targets, which could ultimately lead to the creation of more potent and targeted treatments.\u003c/p\u003e \u003cp\u003eThymidylate synthetase (TYMS) is a cofactor which catalyzes the methylation of deoxyuridylate to deoxythymidylate in the regulation of DNA replication and repair [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Functionally, the polymorphism of TYMS gene is a kind of etiopathogenesis in tumorigenesis, including hepatocellular carcinoma [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and colorectal cancer [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Increasing evidence suggests that TYMS improves cancer cell responsiveness to chemotherapy, such as functioning as a key target of 5-FU treatment and inhibiting tumor cell proliferation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Centromere protein F (CENPF) encodes a protein that related to the centromere-kinetochore complex and maintains cell cycle in the G2 phase [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In cancer, it has been reported that CENPF positively regulates cell growth, inhibits cell apoptosis and tumor metastasis in papillary thyroid cancer [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Nevertheless, the specific function of TYMS and CENPF gene in glioma remains unknown and needs to be explored.\u003c/p\u003e \u003cp\u003eIn this research, we aimed to investigate the function of TYMS and CENPF accompanied by the underlying regulatory mechanism in glioma. To achieve this, we performed RNA-seq analysis using TCGA-GBMLGG cohorts, allowing for a comprehensive investigation of TYMS/CENPF-regulated proteins and signaling pathways. Collectively, these results highlighted that TYMS and CENPF were related to decreased overall survival in patients with glioma, suggesting their clinical values as prognostic and therapeutic target in glioma. Mechanistically, we also investigated the co-expressed genes regulated by TYMS and CENPF and the specific regulatory signaling pathways in glioma.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCancer cell function analysis\u003c/h2\u003e \u003cp\u003eWe employed the CancerSEA platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://biocc.hrbmu.edu.cn/CancerSEA/home.jsp\u003c/span\u003e\u003cspan address=\"http://biocc.hrbmu.edu.cn/CancerSEA/home.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to conduct a comprehensive analysis of cancer cell function at the single-cell level. Subsequent correlation analysis revealed the relationships between TYMS/CENPF expression and various functional states, including angiogenic potential, metastatic capacity, cell cycle progression, and invasive behavior.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExpression levels of TYMS/CENPF and clinical significance in glioma\u003c/h2\u003e \u003cp\u003eWe analyzed individual TYMS/CENPF expression levels in normal and glioma tissue samples using TCGA clinical data and the R package. Our analysis included data from the TCGA-GBMLGG dataset for glioma samples, while normal tissue data were obtained from the Genotype-Tissue Expression (GTEx) project. The Wilcoxon test was used to compare data between normal and HCC tissue samples, and the Kruskal-Wallis test was employed to analyze the relationships between multiple clinical parameters, including age, histological types, and WHO grade, with statistical significance defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSurvival analysis of TYMS and CENPF in glioma\u003c/h2\u003e \u003cp\u003eTo assess the relationship between TYMS/CENPF expression and glioma patient survival, we created Kaplan-Meier survival curves for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). Patients were divided into two groups based on the median value of TYMS/CENPF mRNA transcripts. To further understand the relationship between clinical risk factors and overall survival, we conducted univariate and multivariate analysis to assess the individual and combined effects of these factors on patient survival.\"\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePPI network analysis and gene set enrichment analysis (GSEA)\u003c/h2\u003e \u003cp\u003eTCGA-GBMLGG cohorts were divided into two groups based on the high/low expression levels of TYMS or CENPF. The genes that coded with proteins were screened with both of Pearson and Spearman correlation R\u0026thinsp;\u0026gt;\u0026thinsp;0.75. Then, TYMS, CENPF and other ten proteins were subjected to PPI network analysis using GeneMAINA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genemania.org/\u003c/span\u003e\u003cspan address=\"http://genemania.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In addition, gene sets or signaling pathways were considered to be significantly enriched if normalized enrichment score (NES)\u0026thinsp;\u0026gt;\u0026thinsp;1, p.adjust\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and qvalue\u0026thinsp;\u0026lt;\u0026thinsp;0.25.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eGene-chemicals interaction network analysis\u003c/h2\u003e \u003cp\u003eWe employed the Comparative Toxicogenomics Database (CTD, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ctdbase.org/\u003c/span\u003e\u003cspan address=\"http://ctdbase.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to explore the interactions between TYMS/CENPF and anti-glioma chemicals. By utilizing Cytoscape software, we created a gene-chemical interaction network to visualize the relationships between TYMS/CENPF and various compounds. Our analysis aimed to identify chemicals that influence the expression of TYMS/CENPF, either by increasing or decreasing their mRNA or protein levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eqRT-PCR analysis of TYMS/CENPF expression levels in glioma tissues\u003c/h2\u003e \u003cp\u003eA total of 20 glioma patients who underwent surgery between 2021 and 2023 was included in this study. None of these patients had undergone preoperative radiotherapy, chemotherapy, targeted therapy, or immunotherapy, ensuring that the tissue samples were free from treatment-induced alterations. Following surgical excision, the tumor tissues and cerebral cortex tissues were rapidly frozen in liquid nitrogen to facilitate subsequent molecular analysis. The protocol was reviewed and approved by the Ethics Committee of Second hospital of Shanxi medical university. Glioma tissues and cerebral cortex were subjected to RNA extraction using TRIzol Reagent (Invitrogen), followed by reverse transcription into cDNA using the Reverse Transcription Kit (Qiagen, Hilden, Germany). The cDNA was then analyzed by qPCR using Green Premix Ex Taq II (TaKaRa, Japan) on Applied Biosystems Real-Time PCR System (Foster City, CA, USA). Gene expression levels were quantified using the 2\u0026thinsp;\u0026minus;\u0026thinsp;ΔΔCt method, with GAPDH serving as a housekeeping gene for normalization purposes. The primers of TYMS and CNEPF are listed as following: TYMS forward primer, 5\u0026rsquo;-CTGGGGCAGATCCAACACAT-3\u0026rsquo;, TYMS reverse primer: 5\u0026rsquo;-GCCCAAGTCCCCTTCTTCTC-3\u0026rsquo;, CENPF forward primer: 5\u0026rsquo;-CTCCGAGAGGTCGTTTTCCC-3\u0026rsquo;, CENPF reverse primer: 5\u0026rsquo;-CGCAGCTTGTTGGCTTCTTT-3\u0026rsquo;.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eRelevant function states of TYMS and CENPF in glioma\u003c/h2\u003e \u003cp\u003eGiven the lack of exploring function relevant to pan-cancer, our study was the first to comprehensively assess functional signatures of TYMS and CENPF at the single-cell level via CancerSEA database. The c emphasized the positive correlation between TYMS and several functional states, including cell cycle, EMT, invasion, metastasis and proliferation in glioma (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Additionally, CENPF showed a strong correlation with glioma cell proliferation, cell cycle and cell invasion (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The results highlighted a novel associated functional heterogeneity of glioma cells and reflected the functional states of TYMS and CENPF with tumorigenesis and progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTYMS and CENPF mRNA expression levels and clinical characteristics in glioma\u003c/h2\u003e \u003cp\u003eTo clarify the distinct characteristics between non-tumor tissues and glioma samples, we conducted RNA-sequencing analysis using TCGA-GBMLGG cohort. Normal GTEx sample was utilized as control for comparison. A noteworthy finding was that when focusing on gene differential expression of TYMS and CENPF, both log2(TPM\u0026thinsp;+\u0026thinsp;1) of TYMS and CENPF in glioma tissues (n\u0026thinsp;=\u0026thinsp;701) was substantially higher than that in non-tumor samples (n\u0026thinsp;=\u0026thinsp;5) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, higher TYMS and CENPF expression levels was associated with advanced clinical histological type (glioblastoma vs astrocytoma, glioblastoma vs oligodendroglioma, glioblastoma vs oligoastrocytoma) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). For patients with glioma graded in G4/G3, TYMS and CENPF levels were upregulated in high grade glioma tissues compared to those without WHO G2 grade glioma tissues (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD), suggesting that TYMS and CENPF might correlate with tumor malignant degree. Additionally, baseline information including clinical characteristics of glioma patients (699 samples) are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Clinical variable analysis showed that TYMS and CENPF expression in glioma tissues was positively associated with age, IDH status, 1p/19q codeletion and primary therapy outcome (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\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\u003eBaseline clinical characteristics data of glioma patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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=\"left\" 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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eTYMS expression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eCENPF expression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow expression\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh expression\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eLow expression\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh expression\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;= 60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e314 (44.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e242 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e8.76E-12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e303 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e253 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e1.91E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108 (15.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e46 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157 (22.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e141 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e149 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e149 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e209 (29.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e200 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e201 (28.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIDH status\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e212 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e1.19E-45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e59 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e187 (27.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e1.86E-24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMut\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311 (45.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132 (19.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e286 (41.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e157 (22.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1p/19q codeletion\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-codel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e236 (34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e284 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e7.24E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e223 (32.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e297 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e1.26E-11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCodel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e125 (18.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePrimary therapy outcome\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e0.0006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e44 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e9.69E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e87 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61 (13.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e45 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e96 (20.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic values of TYMS and CENPF in glioma\u003c/h2\u003e \u003cp\u003eTo appraise the prognostic implications of TYMS and CENPF upregulation in glioma samples, we performed Kaplan-Meier analysis with glioma patients. The presence of obvious aberrant TYMS gene expression upregulation, as confirmed by gene expression grouping analysis, was related to significantly reduced survival probability, including OS, DSS and PRI, compared to those with low gene expression (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Moreover, glioma patients with high expressing CENPF had a significant shorter survival than those with lower CENPF expression (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Univariate (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and multivariate (p\u0026thinsp;=\u0026thinsp;0.019) Cox regression analysis indicated that high CENPF expression was one of the independent risk factors patients with glioma (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, with univariate Cox regression analysis, the expression of TYMS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) also did appear to be an independent prognostic factor, like IDH status and 1p/19q codeletion (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The results suggested that the identified TYMS and CENPF have high clinical values as prognostic factors for predicting worse outcomes in glioma.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate cox regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" 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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTYMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.798 (3.626\u0026ndash;6.347)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.177 (0.700\u0026ndash;1.979)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCENPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.188 (2.439\u0026ndash;4.168)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.761 (1.097\u0026ndash;2.826)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;= 60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.696 (3.620\u0026ndash;6.093)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.996 (2.461\u0026ndash;6.489)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.250 (0.979\u0026ndash;1.595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.535 (1.024\u0026ndash;2.303)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIDH status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.116 (0.089\u0026ndash;0.151)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.422 (0.253\u0026ndash;0.705)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMut\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1p/19q codeletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-codel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.225 (0.147\u0026ndash;0.346)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.821 (0.446\u0026ndash;1.510)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCodel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eHistological type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAstrocytoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOligodendroglioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.578 (0.393\u0026ndash;0.849)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.621 (0.381\u0026ndash;1.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOligoastrocytoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.646 (0.412\u0026ndash;1.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.933 (0.556\u0026ndash;1.565)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlioblastoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.791 (4.931\u0026ndash;9.352)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.921 (0.995\u0026ndash;8.579)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePrimary therapy outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.440 (0.294\u0026ndash;0.658)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.502 (0.319\u0026ndash;0.791)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.167 (0.073\u0026ndash;0.385)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.217 (0.092\u0026ndash;0.515)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.131 (0.063\u0026ndash;0.273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.160 (0.074\u0026ndash;0.347)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePPI network analysis\u003c/h2\u003e \u003cp\u003eTo explore the downstream regulatory network of TYMS and CENPF in glioma, and to better elucidate gene interaction mechanisms, single gene differential expression analysis was performed to identify the genes that have strong correlation with TYMS/CENPF expression in glioma. Co-expressed genes were screened with the criteria of |Pearson\u0026rsquo;s R| \u0026gt;= 0.75, |Spearman\u0026rsquo;s R| \u0026gt;= 0.75 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. A total of top 10 co-expressed genes, including TK1, PCLAF, RRM2, CENPK, E2F7, KIF14, ASPM, BUB1B, TOP2A and TPX2, were highly correlated with TYMS/CENPF expression levels in glioma (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Furthermore, in order to classify the protein alterations induced by RRAS2 overexpression, we conducted PPI analysis with the top 10 co-expressed genes. We found that 94.09% had similar co-expression network among the co-expressed 30 proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGSEA analysis in glioma\u003c/h2\u003e \u003cp\u003eTo determine the underlying mechanism by which TYMS/CENPF mediates glioma, GSEA enrichment analysis was carried out in TCGA-GBMLGG datasets. The results revealed an obvious activation of PI3K-AKT signaling pathway (NES\u0026thinsp;=\u0026thinsp;1.283, p\u0026thinsp;=\u0026thinsp;0.025, FDR\u0026thinsp;=\u0026thinsp;0.019) in the TYMS-high expression group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). PI3K-AKT pathway has been identified within glioma, indicating the increased activity of GBM mutations and glioma malignancy [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In addition, we found a hallmark of promoting cell motility induced by MET in CENPF-expressing glioma (NES\u0026thinsp;=\u0026thinsp;1.957, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The GSEA enrichment results suggested that TYMS and CENPF expression was significantly related to enhanced glioma cell motility and tumor progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDrug interaction network in glioma\u003c/h2\u003e \u003cp\u003eTo investigate the drug interaction targeting TYMS/CENPF in glioma, gene-drug network was constructed via the Comparative Toxicogenomics Database (CTD). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, a total of 18 drugs have influences on the expression of TYMS in glioma. The levels of TYMS were positively increased by 10 drugs, including camptothecin, cisplatin, fluorouracil, indomethacin and etc. The remaining 8 drugs could inhibit TYMS expression in glioma. A lower expression of CENPF expression was observed in 1,3-butadiene and quercetin-treated glioma samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Moreover, 10 drugs have the function of promotion on CENPF levels in glioma.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTYMS and CENPF was upregulated in glioma tissues\u003c/h2\u003e \u003cp\u003eThe bioinformatics analysis of TYMS/CENPF encouraged us to further investigate the expression levels in glioma clinical specimens. When compared with cerebral cortex tissues, immunohistochemical analysis of glioma revealed the upregulation of TYMS and CENPF proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA-\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Next, 20 clinical tissues were collected from glioma patients and their TYMS/CENPF expression was assessed using qPCR analysis. In glioma tissues, TYMS/CENPF levels were expressed 3-fold more highly than in non-tumor tissues, indicating an upregulation of TYMS/CENPF mRNA expression after tumor initiation event (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study evaluated the potential role of TYMS and CENPF in glioma and explored the downstream mechanism regulated by TYMS and CENPF. Here, we show that patients expressing high TYMS/CENPF genes have a poor survival than those with low TYMS/CENPF expression. The analysis of TCGA data revealed that TYMS and CENPF expression levels were the highest in WHO G4 grade (GBM) tissues and lower in low-grade glioma samples. Mechanistically, TYMS/CENPF directly interacted with 10 top hub genes and are involved in cell cycle in glioma. More importantly, TYMS/CENPF-related genes activated the PI3K/AKT and MET signaling pathways in glioma, participating in glioma malignant process.\u003c/p\u003e \u003cp\u003eTYMS-expressing xenograft model has been identified to show genomic instability, DNA damage and tumorigenesis acceleration [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For example, downregulation of TYMS inhibited breast cancer cell proliferation and invasion via EMT pathways [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additionally, CENPF acts as a novel regulator of tumor cell metabolism, including cell cycle and metastasis, in prostate cancer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and triple-negative breast cancer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. To elucidate the functional states regulated by TYMS/CENPF, we performed the single cells analysis based TYMS/CENPF expression levels. Our results revealed that enrichment of cell cycle, DNA damage, proliferation and EMT process are also found in TYMS/CENPF-expressed glioma, suggesting the potential functional status to be further elucidated.\u003c/p\u003e \u003cp\u003eIDH1/2 mutation is observed in approximately 65\u0026ndash;90% of LGG patients, indicating a relatively favorable outcome and a low invasiveness in comparison with IDH-wild type glioma [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Targeted anti-IDH-mutation therapies are the key strategies for low-grade glioma (LGG), aiming to inhibit tumor procession [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Recent studies show that IDH is a unique therapeutic target, however, selective inhibitors targeting IDH mutation is challenging as there is drug resistance to IDH inhibitors in glioma cells [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. We demonstrate here that IDH wild type is found at a significantly higher proportion than mutated type in high TYMS/CENPF expression groups, indicating that TYMS/CENPF expression levels might be related to IDH status in glioma. Our data also show that TYMS/CENPF was overexpressed across all glioma histological types but is more highly expressed in patients with high grade glioma than in low grade ones. Given that high grade glioma overexpressing TYMS/CENPF promote tumor progression and malignancy grade, TYMS/CENPF-coexpressed genes seems to be preferentially linked to glioma developing. Therefore, our research further explored the PPI network and GSEA enrichment score of TYMS/CENPF-coexpressed genes in glioma.\u003c/p\u003e \u003cp\u003ePI3K/AKT has been confirmed as an essential signaling pathway in regulating glioma progression and malignant metastasis [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The dysregulation of PI3K/AKT pathway activates growth factors and influences glioma cell growth via promoting biosynthetic pathways [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Several literatures have demonstrated that therapeutic agents, targeting PI3K/AKT pathway, such as temozolomide, are currently in clinical development for improving blood-brain barrier and reducing systemic toxicity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Accumulating studies indicated that MET is a pivotal oncogenic driver in cell biology and stemness of glioma [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. MET is amplificated in transgenic mouse models and then accelerated GBM formation in vivo [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Copy number amplification and overexpression of MET often results in promoting glioma development and a shorter overall survival [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Here, we suggest, for the first time, that the 10 co-expressed genes with TYMS/CENPF participated in activating PI3K/AKT and MET signaling pathways to maintain glioma cell motility and malignance.\u003c/p\u003e \u003cp\u003eCollectively, the study shows that TYMS/CENPF is overexpressed in the vast majority of glioma samples regardless of WHO grade, histological type, IDH mutation and1p/19q codeletion. Moreover, the human data suggests that high TYMS/CENPF expression in glioma is associated with shorter survival and worse prognosis in glioma. Our research elucidated the intricate interplay between TYMS/CENPF and ten proteins in glioma, underscoring their significant contribution to cell cycle and motility via PI3K/AKT and MET signaling pathways. The precise mechanisms by which TYMS contributes to glioma development and progression remain unclear, with cell-based experiments providing incomplete insights that necessitate further investigation. In conclusion, we have identified TYMS and CENPF as key druggable targets that hold promise for the treatment of glioma, thereby providing insights into potential therapeutic strategies for glioma treatment and poor prognosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Cancer Genome Altas tumor cohorts analyzed in this research can be available at https://portal.gdc.cancer.gov/.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Ethics Review Committee of Second Hospital of Shanxi Medical University reviewed and approved this study. Written informed consent was obtained from all subjects before their participation in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: XY and SW. Methodology: XY, QW, QL. Software: QW, QL, RD. Validation: XY, QW, QL. Formal analysis: QL, RD. Investigation: XY, LC, MJ. Resources: MJ, SW. Data Curation: XY, QW, QL. Visualization: RD, LC. Supervision: LC. Project administration: LC. Writing - Original Draft: XY, MJ, SW. Writing - Review \u0026amp; Editing: XY, MJ, SW. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no competing interest exists.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen, R., et al., \u003cem\u003eGlioma Subclassifications and Their Clinical Significance.\u003c/em\u003e Neurotherapeutics, 2017. \u003cstrong\u003e14\u003c/strong\u003e(2): p. 284-297.\u003c/li\u003e\n\u003cli\u003eXu, S., et al., \u003cem\u003eImmunotherapy for glioma: Current management and future application.\u003c/em\u003e Cancer Lett, 2020. \u003cstrong\u003e476\u003c/strong\u003e: p. 1-12.\u003c/li\u003e\n\u003cli\u003eWeller, M., et al., \u003cem\u003eGlioma.\u003c/em\u003e Nat Rev Dis Primers, 2015. \u003cstrong\u003e1\u003c/strong\u003e: p. 15017.\u003c/li\u003e\n\u003cli\u003eYasinjan, F., et al., \u003cem\u003eImmunotherapy: a promising approach for glioma treatment.\u003c/em\u003e Front Immunol, 2023. \u003cstrong\u003e14\u003c/strong\u003e: p. 1255611.\u003c/li\u003e\n\u003cli\u003eGuijarro, M.V., et al., \u003cem\u003eTYMS promotes genomic instability and tumor progression in Ink4a/Arf null background.\u003c/em\u003e Oncogene, 2023. \u003cstrong\u003e42\u003c/strong\u003e(23): p. 1926-1939.\u003c/li\u003e\n\u003cli\u003eWang, L., et al., \u003cem\u003eFOXM1-induced TYMS upregulation promotes the progression of hepatocellular carcinoma.\u003c/em\u003e Cancer Cell Int, 2022. \u003cstrong\u003e22\u003c/strong\u003e(1): p. 47.\u003c/li\u003e\n\u003cli\u003eZhang, F., et al., \u003cem\u003eTYMS-TM4SF4 axis promotes the progression of colorectal cancer by EMT and upregulating stem cell marker.\u003c/em\u003e Am J Cancer Res, 2022. \u003cstrong\u003e12\u003c/strong\u003e(3): p. 1009-1026.\u003c/li\u003e\n\u003cli\u003eXu, H., et al., \u003cem\u003eTherapeutic potential of Clostridium butyricum anticancer effects in colorectal cancer.\u003c/em\u003e Gut Microbes, 2023. \u003cstrong\u003e15\u003c/strong\u003e(1): p. 2186114.\u003c/li\u003e\n\u003cli\u003eXu, P., et al., \u003cem\u003eN6-methyladenosine modification of CENPF mRNA facilitates gastric cancer metastasis via regulating FAK nuclear export.\u003c/em\u003e Cancer Commun (Lond), 2023. \u003cstrong\u003e43\u003c/strong\u003e(6): p. 685-705.\u003c/li\u003e\n\u003cli\u003eHan, Y., et al., \u003cem\u003eCENPF promotes papillary thyroid cancer progression by mediating cell proliferation and apoptosis.\u003c/em\u003e Exp Ther Med, 2021. \u003cstrong\u003e21\u003c/strong\u003e(4): p. 401.\u003c/li\u003e\n\u003cli\u003eLudwig, K. and H.I. Kornblum, \u003cem\u003eMolecular markers in glioma.\u003c/em\u003e J Neurooncol, 2017. \u003cstrong\u003e134\u003c/strong\u003e(3): p. 505-512.\u003c/li\u003e\n\u003cli\u003eShahid, M., et al., \u003cem\u003eDownregulation of CENPF Remodels Prostate Cancer Cells and Alters Cellular Metabolism.\u003c/em\u003e Proteomics, 2019. \u003cstrong\u003e19\u003c/strong\u003e(11): p. e1900038.\u003c/li\u003e\n\u003cli\u003eWang, D., et al., \u003cem\u003eCENPF knockdown inhibits adriamycin chemoresistance in triple-negative breast cancer via the Rb-E2F1 axis.\u003c/em\u003e Sci Rep, 2023. \u003cstrong\u003e13\u003c/strong\u003e(1): p. 1803.\u003c/li\u003e\n\u003cli\u003eMiller, J.J., \u003cem\u003eTargeting IDH-Mutant Glioma.\u003c/em\u003e Neurotherapeutics, 2022. \u003cstrong\u003e19\u003c/strong\u003e(6): p. 1724-1732.\u003c/li\u003e\n\u003cli\u003eLukas, R.V. and C. Horbinski, \u003cem\u003eGlioma Response to IDH Inhibition: Real-World Experience.\u003c/em\u003e Clin Cancer Res, 2023. \u003cstrong\u003e29\u003c/strong\u003e(23): p. 4709-4710.\u003c/li\u003e\n\u003cli\u003eAlshiekh Nasany, R. and M.I. de la Fuente, \u003cem\u003eTherapies for IDH-Mutant Gliomas.\u003c/em\u003e Curr Neurol Neurosci Rep, 2023. \u003cstrong\u003e23\u003c/strong\u003e(5): p. 225-233.\u003c/li\u003e\n\u003cli\u003eMohamed, E., et al., \u003cem\u003ePI3K/AKT/mTOR signaling pathway activity in IDH-mutant diffuse glioma and clinical implications.\u003c/em\u003e Neuro Oncol, 2022. \u003cstrong\u003e24\u003c/strong\u003e(9): p. 1471-1481.\u003c/li\u003e\n\u003cli\u003eObrador, E., et al., \u003cem\u003eGlioblastoma Therapy: Past, Present and Future.\u003c/em\u003e Int J Mol Sci, 2024. \u003cstrong\u003e25\u003c/strong\u003e(5).\u003c/li\u003e\n\u003cli\u003eWang, D., et al., \u003cem\u003eApigenin and Temozolomide Synergistically Inhibit Glioma Growth Through the PI3K/AKT Pathway.\u003c/em\u003e Cancer Biother Radiopharm, 2024. \u003cstrong\u003e39\u003c/strong\u003e(2): p. 125-132.\u003c/li\u003e\n\u003cli\u003eAwad, A.J., et al., \u003cem\u003eTargeting MET for glioma therapy.\u003c/em\u003e Neurosurg Focus, 2014. \u003cstrong\u003e37\u003c/strong\u003e(6): p. E10.\u003c/li\u003e\n\u003cli\u003eFischer, U., et al., \u003cem\u003eAmplification of the MET gene in glioma.\u003c/em\u003e Genes Chromosomes Cancer, 1995. \u003cstrong\u003e12\u003c/strong\u003e(1): p. 63-5.\u003c/li\u003e\n\u003cli\u003eMulcahy, E.Q.X., R.R. Colόn, and R. Abounader, \u003cem\u003eHGF/MET Signaling in Malignant Brain Tumors.\u003c/em\u003e Int J Mol Sci, 2020. \u003cstrong\u003e21\u003c/strong\u003e(20).\u003c/li\u003e\n\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":"Glioma, WHO grade, therapeutic target, prognosis, drug interaction","lastPublishedDoi":"10.21203/rs.3.rs-4997083/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4997083/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGlioma is a prevalent malignant tumor of central neural system. The high mortality rate among glioma patients is largely attributed to tumor metastasis and unfavorable prognosis. Diverse analysis of genomic and transcriptomic alterations is found in glioma, posing an urgent need for identifying novel therapeutic and prognostic targets with underlying molecular mechanisms.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe functional status relevant to TYMS and CENPF in pan-cancer was analyzed using CancerSEA database. We assessed the expression levels and clinical characteristics of TYMS and CENPF in TCGA-glioma data. The prognostic potential of TYMS and CENPF was assessed through Kaplan-Meier survival curve analysis and Cox proportional hazards modeling. To identify co-expressed genes, we applied a correlation analysis with a high R-value threshold, followed by PPI network construction and GSEA. Additionally, a gene-chemical interaction network was built using data from the Comparative Toxicogenomics Database (CTD), providing a framework for exploring potential therapeutic relationships. Furthermore, we collected clinical glioma tissue samples and detected mRNA and protein expression levels using qPCR and HPA analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe showed that TYMS and CENPF overexpression were notably higher in glioma patients, and related to histological types and glioma WHO grades. TYMS and CENPF were clinically correlated with worse prognosis in glioma and could be potential independent prognostic factors. GSEA analysis indicated that TYMS/CENPF and ten co-expressed genes regulated glioma cell motility and other cell behaviors via PI3K/AKT and MET signaling pathways.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur findings suggested that aberrant TYMS/CENPF expression was significantly linked to glioma WHO grades and poor survival rates, contributing to a more comprehensive understanding of glioma therapeutic targets.\u003c/p\u003e","manuscriptTitle":"TYMS and CENPF emerge as key oncogenes and prognostic markers in glioma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-17 09:34:38","doi":"10.21203/rs.3.rs-4997083/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":"879437ef-c074-45bd-ba75-14852f1eb409","owner":[],"postedDate":"October 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-05T09:09:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-17 09:34:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4997083","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4997083","identity":"rs-4997083","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}