1p19q co-deletion is an independent prognostic factor in glioma with TERT promoter mutations

1p19q co-deletion is an independent prognostic factor in glioma with TERT promoter mutations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article 1p19q co-deletion is an independent prognostic factor in glioma with TERT promoter mutations Dan Wan, Benyan Zhang, Jialing Xie, Yutao Zhang, Xianwei Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4516259/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Various genetic variants, such as telomerase reverse transcriptase (TERT) promoter mutations (TERTmut) and 1p/19q co-deletion, are linked to gliomas; however, their prognostic significance remains uncertain. Here, we investigated the prevalence of TERTmut in gliomas, their correlation with clinicopathological features and molecular abnormalities, and prognostic implications of molecular abnormalities. Clinicopathological data were retrospectively collected from 161 patients diagnosed with glioma. An increased incidence of TERTmut was found in patients older than 50 years. Oligodendrogliomas and glioblastomas exhibited a higher susceptibility to TERT promoter mutations than astrocytomas. TERT promoter mutation rates were higher in WHO grade 3 and 4 tumors than in grade 1 and 2 tumors. The TERTmut group demonstrated a higher incidence of 1p19q co-deletion than the TERT wild-type group. Prognosis within the TERTmut group was closely correlated with histological type and glioma grade, along with IDH1/2 mutation, 1p19q co-deletion, and MGMT methylation, all indicative of a favorable prognosis. 1p19q co-deletion, and not IDH1/2 mutation, was identified as an independent prognostic factor for TERTmut glioma. The ensemble prognostic signature, incorporating 1p19q co-deletion, could aid in risk stratification and survival prediction in gliomas with TERTmut. Our findings establish a reliable and practical protocol for developing individualized surgical and treatment strategies. Biological sciences/Cancer/Cns cancer Biological sciences/Neuroscience/Diseases of the nervous system/Cancer in the nervous system Glioma TERT promoter mutation 1p/19q co-deletion prognostic factor Figures Figure 1 Figure 2 Figure 3 Introduction Gliomas are complex diseases involving multiple genes. The discovery of molecular markers provides a foundation for the targeted treatment and molecular typing of gliomas 1 , 2 . Gliomas are categorized into five molecular groups based on three tumor markers: mutations in the telomerase reverse transcriptase ( TERT ) promoter, mutations in isocitrate dehydrogenase 1 and 2 ( IDH 1/2), and co-deletion of chromosome arms 1p and 19q (1p/19q co-deletion) 3 . These groups exhibit variations in overall survival (OS), age at onset, and associations with germline variants, suggesting distinct underlying pathogenic mechanisms 3 . The 2021 World Health Organization (WHO) Classification of Central Nervous System Tumors incorporates numerous molecular markers closely related to diagnosis and prognosis 4 . However, the factors influencing the prognosis of patients with glioma are unclear. TERT activation represents the rate-limiting step in telomerase production. Following mutation, TERT can generate two promoter-binding domains with identical structures, thereby doubling transcriptional activity. It can undergo reverse transcription to synthesize telomere repeat sequences at the chromosome ends, playing a crucial role in the onset and progression of glioma 5 . The 1p/19q co-deletion has long been recognized as a characteristic molecular marker of oligodendroglioma 6 . Moreover, compared with those lacking the 1p/19q variant, patients with glioma harboring 1p/19q co-deletion exhibit substantially increased sensitivity to chemotherapy 7 . However, the association between 1p/19q co-deletion and survival in gliomas remains debatable. TERT promoter mutations ( TERT mut) are predominantly identified in glioblastomas and oligodendroglioma, typically associated with an unfavorable prognosis. The OS of patients with oligodendroglioma ( IDH mutation) presenting TERT mut and 1p/19q co-deletion is considerably higher than that of patients lacking these mutations 8 . An association between TERT mut and 1p/19q co-deletion has been suggested in certain glioma types. Nonetheless, the clinical significance of TERT mut and 1p/19q co-deletion in gliomas remains unclear. The objective of our study was to examine the prognostic implications of TERT mut in patients with glioma and its interactions with other molecular markers, particularly 1p/19q co-deletion, with the aim of contributing insights that may facilitate personalized treatment strategies and enhance overall patient outcomes. Materials and methods Glioma samples and patient characteristics This study was conducted with the approval of the Institutional Review Board of Ruijin Hospital (ID:2020 − 192), and written informed consent was obtained from all patients or their families. We confirmed that all methods were performed in accordance with the relevant guidelines and regulations. Patients with a clear pathological diagnosis of glioma and those who have undergone TERT mut testing were included in this experiment. Samples from patients who died of other diseases and were younger than 15 years of age were excluded. We enrolled 161 patients with gliomas, comprising 90 men and 71 women, admitted to Ruijin Hospital affiliated with Shanghai Jiao Tong University, between January 2018 and December 2022. The median age was 53.9 years (15–85 years). Following the fifth edition of the WHO classification criteria for central nervous system tumors in 2021 4 , the distribution included five cases classified as grade 1, 33 cases as grade 2, 17 cases as grade 3, and 106 cases as grade 4 tumors. DNA extraction Five to ten sections of paraffin-embedded tissue were cut 3–4-µm thick and then dewaxed and hydrated. One section was stained with hematoxylin and eosin to observe the tumor enrichment area. The corresponding area of the remaining white slices was scraped into an Eppendorf test tube, and lysate, protease K, and RNA enzyme were added. A DNA extraction kit (QIAamp DNA FFPE Tissue Handbook, catalog number 56404) was used to extract DNA through an automated extraction instrument, as per the manufacturer’s instructions. A NanoDrop2000 ultramicro spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) was used to detect its concentration and optical density value. Sanger sequencing The extracted DNA was amplified using polymerase chain reaction (PCR) for IDH1 exon 4, IDH2 exon 4, and TERT core promoter fragments (including C288T and C250T sites). The PCR volume was 25 µL, and the reaction conditions were as follows: pre-denaturation at 94°C for 10 min, denaturation at 94°C for 45 s, annealing at 59°C for 45 s, extension at 72°C for 45 s for 40 cycles, extension at 72°C for 7 min, and termination at 4°C. Five microliters of the product was used for agarose gel electrophoresis and purified using PCR. The purified product was sequenced using a sequencing kit (GenomePrecision, Beijing, China) according to the product manual. Each PCR product was sequenced bidirectionally, and the sequencing results were analyzed using Chromas software. Fluorescence in situ hybridization After dewaxing and hydration, the 3–4-µm paraffin specimens were pretreated in pure water at 88–92°C for 30 min and then digested using pepsin for 15–20 min. Next, two-color probe hybridization was performed using 1p36 and 19q13 probe kits (FISH kit for the detection of 1p36/1q21 and 19q13/19p13 gene, Beijing GP Medical Technologies, Ltd., Beijing, China). Denaturation was conducted for 5 min at 73°C, followed by incubation in a water tank at 45–50°C; the specimens were removed before hybridization. After hybridization, specimens were washed and dried. Subsequently, 15 µL 4,6-diamidino-2-phenylindole was added to the specimens, and they were incubated at room temperature for 10–20 min. The results were observed under a fluorescence microscope. At least 100 qualified cells were counted, the red and green signals in the cells were observed, and the ratios of red and green signals were calculated. When the total number of red signals divided by the number of green signals was less than 0.75, the result was established as positive. Real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) According to the instructions of the human MGMT methylation test kit (Genetech, Shanghai, China), the extracted DNA samples were transformed by heavy sulfite, and the products were purified. The RTFQ-PCR solution was prepared according to the dosage and amplified in the RTFQ-PCR instrument. The following amplification parameters were used: 95°C for 3 min; 95°C for 15 s, 60°C for 60 s, with 45 cycles; and fluorescent signal detection. The interpretation criteria were as follows: when the ΔCt value was ≤ 7, the MGMT methylation content in the sample was ≥ 1%, indicating positive MGMT methylation; when no FAM signal was detected in the MGMT reaction tube of the sample and Ct ≤ 32 in the control group, it was indicated that MGMT methylation was negative; when the ΔCt > 7, the MGMT methylation content in the sample was less than 1%, indicating that it was lower than the lower limit of detection by the kit. Statistical analysis The χ2 test was used to detect both the relationships between TERT expression and clinicopathological features and the relationships between TERT expression and other molecular markers. Kaplan–Meier survival curves were used to analyze the OS, and the log-rank test was used to analyze the relationship between clinicopathological features, TERT , other molecular indicators, and OS. The Cox regression model was used for performing multivariate prognostic analyses. Factors identified as significant in univariate analyses were included in the model. OS referred to the time from the initial surgery date to the death of the patient, with a longer OS indicating a higher survival benefit for the patient group. Data processing and statistical analyses were conducted using SPSS (version 26.0) and GraphPad Prism 5. Statistical significance was set at P < 0.05. Results Relationship between TERT and clinicopathological features of patients with glioma The TERT mut status, assessed using Sanger sequencing in 161 patients, revealed positive rates of 40.74% (22/54) in patients younger than 50 years and 68.22% (73/107) in those older than 50 years, with a significant difference ( P < 0.05, Table 1 ). Mutation rates in the TERT promoter were elevated in oligodendroglioma (94.44%) and glioblastoma (65.14%) compared with those in astrocytoma (23.08%; P < 0.05, Table 1 ). Additionally, the TERT mut rate was higher in patients with WHO grade 3 and 4 tumors than in patients with grade 1 and 2 tumors, with no significant difference observed based on gender ( P > 0.05, Table 1 ). Table 1 Correlations between TERT mut and clinicopathological characteristics in patients with glioma Characteristics TERT mut TERTwt χ 2 P-value Sex 1.005 0.316 Male 50 40 Female 45 26 Age in years 11.207 0.001 < 50 22 32 ≥ 50 73 34 Tumor histological type 35.141 < 0.001 Astrocytoma 6 20 Oligodendroglioma 17 1 Glioblastoma 71 38 Others 1 7 WHO grade 1 0 5 13.585 0.004 2 15 18 3 10 7 4 70 36 Correlations between TERT and other molecular markers Patients were categorized into a TERT mutation group ( TERT mut; n = 95) and a TERT wild-type group ( TERT wt; n = 66). In the TERT mut group, the incidence of 1p19q co-deletion was 20.9%, whereas in the TERT wt group, it was 4.8%, indicating a significant difference ( P 0.05, Table 2 ). Table 2 Comparison of molecular pathological indicator mutations between TERT mut and TERT wt groups Molecular characteristics TERT mut TERT wt χ 2 P-value IDH 1 mut 1.397 0.237 + 22 21 - 72 45 NA 1 0 IDH2 mut 1.413 0.512 + 2 0 - 92 66 NA 1 0 1p19q co-deletion 7.897 0.005 + 19 3 - 72 60 NA 4 3 MGMT met 0.734 0.392 + 41 33 - 54 33 NA 0 0 BRAF 1.845 0.309 + 1 3 - 88 61 NA 6 2 NA: Not available. Univariate analysis of prognostic factors in patients with glioma Kaplan–Meier survival analysis of relationships between TERT mut, 1p19q co-deletion, and prognosis revealed that TERT mut was not associated with OS (P = 0.9925, Fig. 1 a), whereas patients with 1p19q co-deletion exhibited significantly higher OS than those without the co-deletion (P = 0.0007, Fig. 1 b). Subsequently, we analyzed the associations between various factors (including age, histological type, WHO grade, IDH 1/2 mutation status, 1p19q co-deletion status, and MGMT methylation status) and prognosis in the TERT mut (Fig. 2 ) and TERT wt groups (Fig. 3 ). In the TERTmut group, prognosis was closely correlated with histological type ( P = 0.0031, Fig. 2 b) and glioma grade ( P = 0.0031, Fig. 2 c). Favorable prognostic indicators included IDH 1/2 mutation ( P < 0.0001, Fig. 2 d), 1p19q co-deletion ( P = 0.0010, Fig. 2 e), and MGMT methylation ( P = 0.0019, Fig. 2 f). In the TERT wt group, patient prognosis was significantly related to age ( P = 0.0488, Fig. 3 a) and grade ( P = 0.0132, Fig. 3 c), whereas molecular changes, such as IDH 1/2 mutation ( P = 0.1010, Fig. 3 d), 1p19q co-deletion ( P = 0.3861, Fig. 3 e), and MGMT methylation ( P = 8158, Fig. 3 f), were not significantly associated with prognosis. Multivariate analysis of prognostic factors in patients with glioma Factors identified as statistically significant in univariate analyses were subjected to a multivariate Cox regression analysis. The 1p19q co-deletion was identified as an independent prognostic factor for TERT mut glioma (Table 3 ), whereas WHO grade was identified as an independent prognostic factor for TERT wt glioma (Table 4 ). Table 3 Results of a multivariate Cox regression analysis of the prognosis of patients with TERT mut glioma Prognostic factor β SE Wald P -value Exp(β) 95% CI Histological type 0.743 0.417 3.172 0.075 2.103 0.928–4.765 WHO grade 0.036 0.265 0.019 0.891 1.037 0.617–1.742 1p19q co-deletion -1.393 0.576 5.848 0.016 0.248 0.080–0.768 MGMT status -0.264 0.338 0.608 0.435 0.768 0.396–1.491 IDH status -0.064 0.486 0.017 0.895 0.938 0.361–2.433 Table 4 Results of a multivariate COX regression analysis of the prognosis of patients with TERT wt glioma Prognostic factor β SE Wald P -value Exp(β) 95% CI Age 0.003 0.013 0.050 0.823 1.003 0.978–1.028 WHO grade 0.644 0.278 5.349 0.021 1.904 1.103–3.287 Discussion Glioma, constituting 45–50% of all intracranial tumors, is a prevalent malignant tumor of the central nervous system. Glioma is characterized by aggressive growth, frequent recurrence, challenges in treatment, and high mortality rates. Despite therapeutic interventions, including surgery, radiotherapy, and chemotherapy, the median survival time for patients with glioma remains at 15 months 9 , 10 . The WHO classification of central nervous system tumors integrates molecular markers that are closely related to diagnosis and prognosis 11 , with TERT being a pivotal marker, thereby highlighting the need for an accurate analysis of its association with pathological features and other molecular changes. While numerous studies have indicated the predictive role of TERT mutations in survival 12 , 13 , its correlation with clinicopathological features and its impact on patient prognosis remain unclear 14 , 15 . In our retrospective analysis of 161 patients with glioma, TERT mut frequency was observed to be notably higher in patients older than 50 years than in patients younger than 50 years, in oligodendroglioma and glioblastoma than in astrocytoma, and in WHO grade 3 and 4 tumors than in grade 1 and 2 tumors (Table 1 ). Univariate survival analyses revealed that the prognosis of the TERT mut group was closely associated with the histological type ( P = 0.0031, Fig. 2 b) and grade ( P = 0.0031, Fig. 2 c) of glioma but not age ( P = 0.1276, Fig. 2 a). As per the WHO 2021 standards 11 , IDH 1/2 wild-type diffuse astrocytic glioma with TERT mut is classified as glioblastoma, highlighting the association of TERT mut with tumor aggressiveness. However, the pathogenesis of glioma is complex, and the molecular changes influencing prognosis have been extensively debated. While most studies suggest that TERT mut is associated with poor prognosis in gliomas, research in mouse tumor transplantation models has shown that RAS , TERT , and p53 mutations or abnormal expression are implicated in glioma occurrence. These genes contribute to a fully malignant and rapid transformation, with mutations and specific combinations of susceptible cell types playing pivotal roles in the development of gliomas 16 . Fujimoto et al. 17 analyzed 46 patients with IDH wild-type/ TERT mut low-grade gliomas and 85 patients with IDH wild-type/ TERT wt low-grade gliomas, demonstrating that the analysis of TERT mut status is necessary and sufficient to diagnose IDH wild-type diffuse astrocytic gliomas with the molecular features of glioblastoma. Further studies have indicated that mutations near TERT and TERC impact telomere length, increasing the risk of high-grade gliomas 17 . Similarly, variants near TERT and TERC , influencing telomere length, are associated with the risk of high-grade gliomas 18 . However, Muench et al. 19 proposed that TERT mut cannot serve as a prognostic factor for IDH wild-type gliomas. They provided evidence that TERT mut in diffuse gliomas without further morphological or molecular signs of high-grade glioma should be interpreted in the context of clinicopathological presentation, as well as the epigenetic profile, and TERT mut may not be suitable as a standalone marker for IDH wild-type glioblastoma. Our Kaplan–Meier survival analysis revealed that OS was shorter in the TERT mut group than in the IDH wild-type and IDH mutant groups ( P < 0.0001, Fig. 2 d). Additionally, we observed no significant difference between the IDH mutation status and prognosis of patients with TERT wt glioma ( P = 0.1010, Fig. 3 d). Multivariate Cox regression analyses demonstrated that the IDH mutation was not an independent prognostic factor for TERT mut or TERT wt glioma (Tables 3 and 4 ). Therefore, we believe that TERT mut cannot be used as an independent prognostic factor for IDH wild-type gliomas, consistent with the results of Muench et al. 19 As mentioned earlier, TERT mut, a predictor of highly aggressive gliomas in most studies, typically relies on a histological diagnosis of diffuse astrocytoma or anaplastic astrocytoma with IDH wild-type and without 1p19q co-deletion 17 . However, the significance of TERT mut with 1p19q co-deletion in the integrative diagnosis of glioma remains unclear. 1p19q serves as a crucial marker for the classification, treatment, and prognosis of glioma 3 , 20 , 21 . 1p19q co-deletion is prevalent in all glioma subtypes, especially in patients with oligodendroglioma. Following an IDH mutation, the tumor progresses to oligodendroglioma in cases where 1p19q combined deletion occurs. This co-deletion holds significance in differentiating oligodendrogliomas from astrocytomas and serves as a basis for differential diagnosis. Killela et al. 22 reported that 78% (35/45) of oligodendrogliomas exhibited TERT mut. In our study, 17 of 18 oligodendrogliomas had TERT mut (Table 1 ). Furthermore, among the 22 patients with glioma harboring a 1p19q co-deletion, 19 cases were accompanied by TERT mut (Table 2 ). Simultaneously, we observed no correlation between TERT mut and patient survival (Fig. 1 a). The OS of patients with 1p19q co-deletion was significantly longer than that of patients without 1p19q co-deletion, consistent with previously reported results 6 , 23 , 24 . However, in the TERT mut group, 1p19q co-deletion was identified as an independent prognostic factor in patients with glioma (Fig. 2 and Table 3 ). Conversely, in the TERT wt group, 1p19q co-deletion was not an independent prognostic factor for patients with glioma (Fig. 3 and Table 4 ). Therefore, when TERT is not mutated, the increased survival associated with 1p19 co-deletion disappears. We propose that improved survival in patients with 1p19q co-deletion is dependent on TERT promoter mutations. However, the mechanism by which 1p19 co-deletion affects the prognosis of patients with gliomas is complex. According to Lv et al. 25 , the effect of 1p/19q co-deletion on the immune microenvironment in low-grade glioma plays a crucial role in tumor progression and prognosis. Immune cell infiltration of 281 low-grade gliomas from The Cancer Genome Atlas and 543 low-grade gliomas from the Chinese Glioma Genome Atlas were analyzed for immune cell infiltration using the ESTIMATE algorithm, TIMER, and xCell. Low-grade gliomas with 1p/19q co-deletion exhibit lesser immune cell infiltration and lower expression of immune checkpoint genes than those in 1p/19q non-co-deletion cases. Similarly, some studies have shown that a higher risk is associated with an increase in various factors in the tumor microenvironment, such as protein acetylation and inflammatory responses 26 . Furthermore, pathway analysis suggested that prostaglandins, N-terminal acetyltransferases, and responses to copper ions may be involved in 1p/19q glioma progression 27 – 29 . Collectively, we propose that better survival of patients with 1p19q co-deletion is dependent on TERT promoter mutations; however, the specific mechanism remains to be further investigated. We acknowledge that our study has certain limitations. Patients in our cohort were treated using various modalities, and treatment annotations were lacking for a substantial portion of the dataset. In the future, we plan to conduct a confirmatory study that replicates and validates the findings for patients with a consistent treatment strategy, accounting for other prognostic factors, such as tumor size, location, and degree of resection. In summary, TERT promoter mutations exhibit distinct patterns in patients with glioma, associated with age, histological type, and WHO grade. TERT mut is positively correlated with 1p19q co-deletion and is insufficient as an independent prognostic factor for IDH wild-type gliomas. Notably, the ensemble prognostic signature featuring 1p19q co-deletion could serve as a valuable tool for risk stratification and survival prediction in gliomas with TERT promoter mutations. As our understanding of the optimal classification of adult diffuse gliomas evolves, biomarkers for risk-based classification may enhance clinical strategies. Collectively, our findings present a reliable protocol for neurosurgeons to devise personalized surgical and treatment strategies in patients with glioma. Declarations Author information Authors and Affiliations Department of Pathology, The First People’s Hospital of Zigong, shang yi hao yi zhi lu 42#, Zigong 643099, Sichuan province, China. Dan Wan & Yutao Zhang Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China. Benyan Zhang & Jialing Xie & Xianwei Yang Author contributions Xianwei Yang and Dan Wan performed the sample collection and research and wrote the paper. Jialing Xie performed the experiments. Benyan Zhang contributed to the research design. Yutao Zhang and Benyan Zhang gave the final approval of the manuscript. Corresponding author Correspondence to Xianwei Yang. Data availability The raw sequencing data are available under controlled access at the National Center for Biotechnology Information (NCBI) database under accession number: PQ002189, PQ002190, PQ002191, and PQ002192. Competing interests The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article. References Mörén, L. et al . Metabolomic screening of tumor tissue and serum in glioma patients reveals diagnostic and prognostic information. Metabolites 5 , 502–520 (2015). Dang, L., Yen, K. & Attar, E. C. 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Goodman, V. L., Brewer, G. J. & Merajver, S. D. Copper deficiency as an anti-cancer strategy. Endocr. Relat. Cancer 11 , 255–263 (2004). 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-4516259","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":336133235,"identity":"ea9d98f5-a17f-4395-bfa9-e986bcca890d","order_by":0,"name":"Dan Wan","email":"","orcid":"","institution":"The First People’s Hospital of Zigong","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Wan","suffix":""},{"id":336133237,"identity":"a8c754b1-41e7-4516-b26c-d03217b6f8d1","order_by":1,"name":"Benyan Zhang","email":"","orcid":"","institution":"Ruijin Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Benyan","middleName":"","lastName":"Zhang","suffix":""},{"id":336133239,"identity":"7ae3ce0e-d40b-4877-86ed-9eabc553307f","order_by":2,"name":"Jialing Xie","email":"","orcid":"","institution":"Ruijin Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jialing","middleName":"","lastName":"Xie","suffix":""},{"id":336133241,"identity":"c367d205-282e-42cc-80dd-1148003ab5a3","order_by":3,"name":"Yutao Zhang","email":"","orcid":"","institution":"The First People’s Hospital of Zigong","correspondingAuthor":false,"prefix":"","firstName":"Yutao","middleName":"","lastName":"Zhang","suffix":""},{"id":336133243,"identity":"6378726e-9b3c-479c-8ad0-fe69c1f7a0e1","order_by":4,"name":"Xianwei Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYJCCAxIGNnb8DAxpROtgfGBRkJYs2UCCFmaDig+HGTccYGAjTr3BjRwziRsGh5mNbx949oChxiaagf3sAfxazpwxk5xhkM5ndi4h3YDhWFpuA09eAn4tx3u3SUsYWDObnWFIk2BsOJzbIMFjgF/LYd5t0n8MmBk39xCt5XjvZgMJA2fGDTzEapE8c/7jAwmDtGQJkMMSgH5p48nBr4XvRlrCAYk/wKjs4UmT+FBjk9vPfga/FoUDcCZPAkMCkCIYO/INcCb7AZyqRsEoGAWjYGQDAFz/RP3zHplMAAAAAElFTkSuQmCC","orcid":"","institution":"Ruijin Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Xianwei","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2024-06-02 08:29:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4516259/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4516259/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62654684,"identity":"8bd52faa-35ea-48a3-8cba-2a13804974b3","added_by":"auto","created_at":"2024-08-17 01:26:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1107261,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between \u003cem\u003eTERT\u003c/em\u003emut and 1p19q co-deletion and prognosis.\u003c/p\u003e\n\u003cp\u003ea: \u003cem\u003eTERT\u003c/em\u003emut demonstrated no correlation with the overall survival (OS) of patients (\u003cem\u003eP\u003c/em\u003e=0.9925); b: The OS of patients with 1p19q co-deletion was significantly prolonged (\u003cem\u003eP\u003c/em\u003e=0.0007).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4516259/v1/ef7b22947560b78e0870bd0d.png"},{"id":62654683,"identity":"cf3b962b-11ae-4397-9687-c6986b2b0932","added_by":"auto","created_at":"2024-08-17 01:26:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1417189,"visible":true,"origin":"","legend":"\u003cp\u003eUnivariate analysis of prognostic factors in patients with \u003cem\u003eTERT\u003c/em\u003emut glioma.\u003c/p\u003e\n\u003cp\u003ea: The OS of patients with \u003cem\u003eTERT\u003c/em\u003emut glioma was not correlated to age (\u003cem\u003eP\u003c/em\u003e=0.1276); b, c: The prognosis of patients in the \u003cem\u003eTERT\u003c/em\u003emut group was closely associated with the histological type and glioma grade (\u003cem\u003eP\u003c/em\u003e=0.0031 and\u003cem\u003e P\u003c/em\u003e=0.0031, respectively); d, e, f: The OS of patients with \u003cem\u003eIDH\u003c/em\u003e1/2 mutation, 1p19q co-deletion, and MGMT methylation was significantly prolonged (\u003cem\u003eP\u003c/em\u003e＜0.0001, \u003cem\u003eP\u003c/em\u003e=0.0010, and \u003cem\u003eP\u003c/em\u003e=0.0019, respectively). NA: Not available.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4516259/v1/b8db8e11b473b7cce1de5347.png"},{"id":62653845,"identity":"61af7d84-0ce3-4ca5-b95d-d596ba0cc15d","added_by":"auto","created_at":"2024-08-17 01:18:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1225532,"visible":true,"origin":"","legend":"\u003cp\u003eUnivariate analysis of prognostic factors in patients with \u003cem\u003eTERT\u003c/em\u003ewt glioma.\u003c/p\u003e\n\u003cp\u003ea: The OS of patients with \u003cem\u003eTERT\u003c/em\u003ewt glioma correlated with age (\u003cem\u003eP\u003c/em\u003e=0.0488); b: The OS of \u003cem\u003eTERT\u003c/em\u003ewt glioma patients did not correlate with histological type (\u003cem\u003eP\u003c/em\u003e=0.0561); c: The prognosis of patients in the \u003cem\u003eTERT\u003c/em\u003ewt group closely associated with glioma grade (\u003cem\u003eP\u003c/em\u003e=0.0132); d, e, and f: The OS of patients with \u003cem\u003eTERT\u003c/em\u003ewt glioma and \u003cem\u003eIDH\u003c/em\u003e1/2 mutation, 1p19q co-deletion, and\u003cem\u003e MGMT\u003c/em\u003e methylation were not significantly related to prognosis (\u003cem\u003eP\u003c/em\u003e=0.1010, \u003cem\u003eP\u003c/em\u003e=0.3861, and \u003cem\u003eP\u003c/em\u003e=0.8158, respectively).. NA: Not available.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4516259/v1/6cd20ac51c3f7af3735fdfb8.png"},{"id":63348622,"identity":"f7a001bb-0930-4ced-a0b1-a614db4d0d49","added_by":"auto","created_at":"2024-08-27 07:54:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3997938,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4516259/v1/9f869e42-be12-4a0b-a51a-5a5f6e1afb43.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"1p19q co-deletion is an independent prognostic factor in glioma with TERT promoter mutations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGliomas are complex diseases involving multiple genes. The discovery of molecular markers provides a foundation for the targeted treatment and molecular typing of gliomas\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Gliomas are categorized into five molecular groups based on three tumor markers: mutations in the telomerase reverse transcriptase (\u003cem\u003eTERT\u003c/em\u003e) promoter, mutations in isocitrate dehydrogenase 1 and 2 (\u003cem\u003eIDH\u003c/em\u003e1/2), and co-deletion of chromosome arms 1p and 19q (1p/19q co-deletion)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. These groups exhibit variations in overall survival (OS), age at onset, and associations with germline variants, suggesting distinct underlying pathogenic mechanisms\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The 2021 World Health Organization (WHO) Classification of Central Nervous System Tumors incorporates numerous molecular markers closely related to diagnosis and prognosis\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, the factors influencing the prognosis of patients with glioma are unclear.\u003c/p\u003e \u003cp\u003e \u003cem\u003eTERT\u003c/em\u003e activation represents the rate-limiting step in telomerase production. Following mutation, \u003cem\u003eTERT\u003c/em\u003e can generate two promoter-binding domains with identical structures, thereby doubling transcriptional activity. It can undergo reverse transcription to synthesize telomere repeat sequences at the chromosome ends, playing a crucial role in the onset and progression of glioma\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe 1p/19q co-deletion has long been recognized as a characteristic molecular marker of oligodendroglioma\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Moreover, compared with those lacking the 1p/19q variant, patients with glioma harboring 1p/19q co-deletion exhibit substantially increased sensitivity to chemotherapy\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, the association between 1p/19q co-deletion and survival in gliomas remains debatable. \u003cem\u003eTERT\u003c/em\u003e promoter mutations (\u003cem\u003eTERT\u003c/em\u003emut) are predominantly identified in glioblastomas and oligodendroglioma, typically associated with an unfavorable prognosis. The OS of patients with oligodendroglioma (\u003cem\u003eIDH\u003c/em\u003e mutation) presenting \u003cem\u003eTERT\u003c/em\u003emut and 1p/19q co-deletion is considerably higher than that of patients lacking these mutations\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. An association between \u003cem\u003eTERT\u003c/em\u003emut and 1p/19q co-deletion has been suggested in certain glioma types. Nonetheless, the clinical significance of \u003cem\u003eTERT\u003c/em\u003emut and 1p/19q co-deletion in gliomas remains unclear.\u003c/p\u003e \u003cp\u003eThe objective of our study was to examine the prognostic implications of \u003cem\u003eTERT\u003c/em\u003emut in patients with glioma and its interactions with other molecular markers, particularly 1p/19q co-deletion, with the aim of contributing insights that may facilitate personalized treatment strategies and enhance overall patient outcomes.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGlioma samples and patient characteristics\u003c/h2\u003e \u003cp\u003eThis study was conducted with the approval of the Institutional Review Board of Ruijin Hospital (ID:2020\u0026thinsp;\u0026minus;\u0026thinsp;192), and written informed consent was obtained from all patients or their families. We confirmed that all methods were performed in accordance with the relevant guidelines and regulations. Patients with a clear pathological diagnosis of glioma and those who have undergone \u003cem\u003eTERT\u003c/em\u003emut testing were included in this experiment. Samples from patients who died of other diseases and were younger than 15 years of age were excluded. We enrolled 161 patients with gliomas, comprising 90 men and 71 women, admitted to Ruijin Hospital affiliated with Shanghai Jiao Tong University, between January 2018 and December 2022. The median age was 53.9 years (15\u0026ndash;85 years). Following the fifth edition of the WHO classification criteria for central nervous system tumors in 2021\u003csup\u003e4\u003c/sup\u003e, the distribution included five cases classified as grade 1, 33 cases as grade 2, 17 cases as grade 3, and 106 cases as grade 4 tumors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction\u003c/h2\u003e \u003cp\u003eFive to ten sections of paraffin-embedded tissue were cut 3\u0026ndash;4-\u0026micro;m thick and then dewaxed and hydrated. One section was stained with hematoxylin and eosin to observe the tumor enrichment area. The corresponding area of the remaining white slices was scraped into an Eppendorf test tube, and lysate, protease K, and RNA enzyme were added. A DNA extraction kit (QIAamp DNA FFPE Tissue Handbook, catalog number 56404) was used to extract DNA through an automated extraction instrument, as per the manufacturer\u0026rsquo;s instructions. A NanoDrop2000 ultramicro spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) was used to detect its concentration and optical density value.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSanger sequencing\u003c/h2\u003e \u003cp\u003eThe extracted DNA was amplified using polymerase chain reaction (PCR) for IDH1 exon 4, IDH2 exon 4, and TERT core promoter fragments (including C288T and C250T sites). The PCR volume was 25 \u0026micro;L, and the reaction conditions were as follows: pre-denaturation at 94\u0026deg;C for 10 min, denaturation at 94\u0026deg;C for 45 s, annealing at 59\u0026deg;C for 45 s, extension at 72\u0026deg;C for 45 s for 40 cycles, extension at 72\u0026deg;C for 7 min, and termination at 4\u0026deg;C. Five microliters of the product was used for agarose gel electrophoresis and purified using PCR. The purified product was sequenced using a sequencing kit (GenomePrecision, Beijing, China) according to the product manual. Each PCR product was sequenced bidirectionally, and the sequencing results were analyzed using Chromas software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eFluorescence in situ hybridization\u003c/h2\u003e \u003cp\u003eAfter dewaxing and hydration, the 3\u0026ndash;4-\u0026micro;m paraffin specimens were pretreated in pure water at 88\u0026ndash;92\u0026deg;C for 30 min and then digested using pepsin for 15\u0026ndash;20 min. Next, two-color probe hybridization was performed using 1p36 and 19q13 probe kits (FISH kit for the detection of 1p36/1q21 and 19q13/19p13 gene, Beijing GP Medical Technologies, Ltd., Beijing, China). Denaturation was conducted for 5 min at 73\u0026deg;C, followed by incubation in a water tank at 45\u0026ndash;50\u0026deg;C; the specimens were removed before hybridization. After hybridization, specimens were washed and dried. Subsequently, 15 \u0026micro;L 4,6-diamidino-2-phenylindole was added to the specimens, and they were incubated at room temperature for 10\u0026ndash;20 min. The results were observed under a fluorescence microscope. At least 100 qualified cells were counted, the red and green signals in the cells were observed, and the ratios of red and green signals were calculated. When the total number of red signals divided by the number of green signals was less than 0.75, the result was established as positive.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eReal-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR)\u003c/h2\u003e \u003cp\u003eAccording to the instructions of the human \u003cem\u003eMGMT\u003c/em\u003e methylation test kit (Genetech, Shanghai, China), the extracted DNA samples were transformed by heavy sulfite, and the products were purified. The RTFQ-PCR solution was prepared according to the dosage and amplified in the RTFQ-PCR instrument. The following amplification parameters were used: 95\u0026deg;C for 3 min; 95\u0026deg;C for 15 s, 60\u0026deg;C for 60 s, with 45 cycles; and fluorescent signal detection. The interpretation criteria were as follows: when the ΔCt value was \u0026le;\u0026thinsp;7, the \u003cem\u003eMGMT\u003c/em\u003e methylation content in the sample was \u0026ge;\u0026thinsp;1%, indicating positive \u003cem\u003eMGMT\u003c/em\u003e methylation; when no FAM signal was detected in the \u003cem\u003eMGMT\u003c/em\u003e reaction tube of the sample and Ct\u0026thinsp;\u0026le;\u0026thinsp;32 in the control group, it was indicated that \u003cem\u003eMGMT\u003c/em\u003e methylation was negative; when the ΔCt \u0026gt; 7, the \u003cem\u003eMGMT\u003c/em\u003e methylation content in the sample was less than 1%, indicating that it was lower than the lower limit of detection by the kit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe χ2 test was used to detect both the relationships between \u003cem\u003eTERT\u003c/em\u003e expression and clinicopathological features and the relationships between \u003cem\u003eTERT\u003c/em\u003e expression and other molecular markers. Kaplan\u0026ndash;Meier survival curves were used to analyze the OS, and the log-rank test was used to analyze the relationship between clinicopathological features, \u003cem\u003eTERT\u003c/em\u003e, other molecular indicators, and OS. The Cox regression model was used for performing multivariate prognostic analyses. Factors identified as significant in univariate analyses were included in the model. OS referred to the time from the initial surgery date to the death of the patient, with a longer OS indicating a higher survival benefit for the patient group. Data processing and statistical analyses were conducted using SPSS (version 26.0) and GraphPad Prism 5. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eRelationship between\u003c/strong\u003e \u003cstrong\u003eTERT\u003c/strong\u003e \u003cstrong\u003eand clinicopathological features of patients with glioma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eTERT\u003c/em\u003emut status, assessed using Sanger sequencing in 161 patients, revealed positive rates of 40.74% (22/54) in patients younger than 50 years and 68.22% (73/107) in those older than 50 years, with a significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Mutation rates in the \u003cem\u003eTERT\u003c/em\u003e promoter were elevated in oligodendroglioma (94.44%) and glioblastoma (65.14%) compared with those in astrocytoma (23.08%; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, the \u003cem\u003eTERT\u003c/em\u003emut rate was higher in patients with WHO grade 3 and 4 tumors than in patients with grade 1 and 2 tumors, with no significant difference observed based on gender (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelations between \u003cem\u003eTERT\u003c/em\u003emut and clinicopathological characteristics in patients with glioma\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTERT\u003c/em\u003emut\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTERTwt\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge in years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor histological type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAstrocytoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOligodendroglioma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlioblastoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWHO grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelations between\u003c/strong\u003e \u003cstrong\u003eTERT\u003c/strong\u003e \u003cstrong\u003eand other molecular markers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients were categorized into a \u003cem\u003eTERT\u003c/em\u003e mutation group (\u003cem\u003eTERT\u003c/em\u003emut; n\u0026thinsp;=\u0026thinsp;95) and a \u003cem\u003eTERT\u003c/em\u003e wild-type group (\u003cem\u003eTERT\u003c/em\u003ewt; n\u0026thinsp;=\u0026thinsp;66). In the \u003cem\u003eTERT\u003c/em\u003emut group, the incidence of 1p19q co-deletion was 20.9%, whereas in the \u003cem\u003eTERT\u003c/em\u003ewt group, it was 4.8%, indicating a significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). No significant correlations were observed between \u003cem\u003eTERT\u003c/em\u003emut and \u003cem\u003eIDH\u003c/em\u003e1 mutations, IDH2 mutations, \u003cem\u003eMGMT\u003c/em\u003e promoter methylation, or \u003cem\u003eBRAF\u003c/em\u003e mutations (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of molecular pathological indicator mutations between \u003cem\u003eTERT\u003c/em\u003emut and \u003cem\u003eTERT\u003c/em\u003ewt groups\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMolecular characteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTERT\u003c/em\u003emut\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTERT\u003c/em\u003ewt\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIDH\u003c/em\u003e1 mut\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIDH2\u003c/em\u003e mut\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.512\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1p19q co-deletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMGMT\u003c/em\u003emet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNA: Not available.\u003c/p\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eUnivariate analysis of prognostic factors in patients with glioma\u003c/h2\u003e\n \u003cp\u003eKaplan\u0026ndash;Meier survival analysis of relationships between \u003cem\u003eTERT\u003c/em\u003emut, 1p19q co-deletion, and prognosis revealed that \u003cem\u003eTERT\u003c/em\u003emut was not associated with OS (P\u0026thinsp;=\u0026thinsp;0.9925, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea), whereas patients with 1p19q co-deletion exhibited significantly higher OS than those without the co-deletion (P\u0026thinsp;=\u0026thinsp;0.0007, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb). Subsequently, we analyzed the associations between various factors (including age, histological type, WHO grade, \u003cem\u003eIDH\u003c/em\u003e1/2 mutation status, 1p19q co-deletion status, and \u003cem\u003eMGMT\u003c/em\u003e methylation status) and prognosis in the \u003cem\u003eTERT\u003c/em\u003emut (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) and \u003cem\u003eTERT\u003c/em\u003ewt groups (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In the TERTmut group, prognosis was closely correlated with histological type (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0031, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb) and glioma grade (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0031, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec). Favorable prognostic indicators included \u003cem\u003eIDH\u003c/em\u003e 1/2 mutation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed), 1p19q co-deletion (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0010, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ee), and \u003cem\u003eMGMT\u003c/em\u003e methylation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0019, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef). In the \u003cem\u003eTERT\u003c/em\u003ewt group, patient prognosis was significantly related to age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0488, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea) and grade (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0132, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec), whereas molecular changes, such as \u003cem\u003eIDH\u003c/em\u003e1/2 mutation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1010, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed), 1p19q co-deletion (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3861, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ee), and \u003cem\u003eMGMT\u003c/em\u003e methylation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8158, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ef), were not significantly associated with prognosis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eMultivariate analysis of prognostic factors in patients with glioma\u003c/h2\u003e\n \u003cp\u003eFactors identified as statistically significant in univariate analyses were subjected to a multivariate Cox regression analysis. The 1p19q co-deletion was identified as an independent prognostic factor for \u003cem\u003eTERT\u003c/em\u003emut glioma (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), whereas WHO grade was identified as an independent prognostic factor for \u003cem\u003eTERT\u003c/em\u003ewt glioma (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResults of a multivariate Cox regression analysis of the prognosis of patients with \u003cem\u003eTERT\u003c/em\u003emut glioma\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrognostic factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWald\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExp(\u0026beta;)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%\u0026emsp;CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHistological type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.928\u0026ndash;4.765\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWHO grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.617\u0026ndash;1.742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1p19q co-deletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.080\u0026ndash;0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMGMT status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.396\u0026ndash;1.491\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDH status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.361\u0026ndash;2.433\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResults of a multivariate COX regression analysis of the prognosis of patients with \u003cem\u003eTERT\u003c/em\u003ewt glioma\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrognostic factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWald\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExp(\u0026beta;)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%\u0026emsp;CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.978\u0026ndash;1.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWHO grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.103\u0026ndash;3.287\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGlioma, constituting 45\u0026ndash;50% of all intracranial tumors, is a prevalent malignant tumor of the central nervous system. Glioma is characterized by aggressive growth, frequent recurrence, challenges in treatment, and high mortality rates. Despite therapeutic interventions, including surgery, radiotherapy, and chemotherapy, the median survival time for patients with glioma remains at 15 months\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The WHO classification of central nervous system tumors integrates molecular markers that are closely related to diagnosis and prognosis\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, with \u003cem\u003eTERT\u003c/em\u003e being a pivotal marker, thereby highlighting the need for an accurate analysis of its association with pathological features and other molecular changes. While numerous studies have indicated the predictive role of \u003cem\u003eTERT\u003c/em\u003e mutations in survival\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, its correlation with clinicopathological features and its impact on patient prognosis remain unclear\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In our retrospective analysis of 161 patients with glioma, \u003cem\u003eTERT\u003c/em\u003emut frequency was observed to be notably higher in patients older than 50 years than in patients younger than 50 years, in oligodendroglioma and glioblastoma than in astrocytoma, and in WHO grade 3 and 4 tumors than in grade 1 and 2 tumors (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Univariate survival analyses revealed that the prognosis of the \u003cem\u003eTERT\u003c/em\u003emut group was closely associated with the histological type (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0031, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) and grade (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0031, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) of glioma but not age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1276, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eAs per the WHO 2021 standards\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eIDH\u003c/em\u003e1/2 wild-type diffuse astrocytic glioma with \u003cem\u003eTERT\u003c/em\u003emut is classified as glioblastoma, highlighting the association of \u003cem\u003eTERT\u003c/em\u003emut with tumor aggressiveness. However, the pathogenesis of glioma is complex, and the molecular changes influencing prognosis have been extensively debated. While most studies suggest that \u003cem\u003eTERT\u003c/em\u003emut is associated with poor prognosis in gliomas, research in mouse tumor transplantation models has shown that \u003cem\u003eRAS\u003c/em\u003e, \u003cem\u003eTERT\u003c/em\u003e, and \u003cem\u003ep53\u003c/em\u003e mutations or abnormal expression are implicated in glioma occurrence. These genes contribute to a fully malignant and rapid transformation, with mutations and specific combinations of susceptible cell types playing pivotal roles in the development of gliomas\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Fujimoto et al.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e analyzed 46 patients with \u003cem\u003eIDH\u003c/em\u003e wild-type/\u003cem\u003eTERT\u003c/em\u003emut low-grade gliomas and 85 patients with \u003cem\u003eIDH\u003c/em\u003e wild-type/\u003cem\u003eTERT\u003c/em\u003ewt low-grade gliomas, demonstrating that the analysis of \u003cem\u003eTERT\u003c/em\u003emut status is necessary and sufficient to diagnose \u003cem\u003eIDH\u003c/em\u003e wild-type diffuse astrocytic gliomas with the molecular features of glioblastoma. Further studies have indicated that mutations near \u003cem\u003eTERT\u003c/em\u003e and \u003cem\u003eTERC\u003c/em\u003e impact telomere length, increasing the risk of high-grade gliomas\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Similarly, variants near \u003cem\u003eTERT\u003c/em\u003e and \u003cem\u003eTERC\u003c/em\u003e, influencing telomere length, are associated with the risk of high-grade gliomas\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. However, Muench et al.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e proposed that \u003cem\u003eTERT\u003c/em\u003emut cannot serve as a prognostic factor for \u003cem\u003eIDH\u003c/em\u003e wild-type gliomas. They provided evidence that \u003cem\u003eTERT\u003c/em\u003emut in diffuse gliomas without further morphological or molecular signs of high-grade glioma should be interpreted in the context of clinicopathological presentation, as well as the epigenetic profile, and \u003cem\u003eTERT\u003c/em\u003emut may not be suitable as a standalone marker for \u003cem\u003eIDH\u003c/em\u003e wild-type glioblastoma. Our Kaplan\u0026ndash;Meier survival analysis revealed that OS was shorter in the \u003cem\u003eTERT\u003c/em\u003emut group than in the IDH wild-type and \u003cem\u003eIDH\u003c/em\u003e mutant groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Additionally, we observed no significant difference between the \u003cem\u003eIDH\u003c/em\u003e mutation status and prognosis of patients with \u003cem\u003eTERT\u003c/em\u003ewt glioma (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1010, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). Multivariate Cox regression analyses demonstrated that the \u003cem\u003eIDH\u003c/em\u003e mutation was not an independent prognostic factor for \u003cem\u003eTERT\u003c/em\u003emut or \u003cem\u003eTERT\u003c/em\u003ewt glioma (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Therefore, we believe that \u003cem\u003eTERT\u003c/em\u003emut cannot be used as an independent prognostic factor for \u003cem\u003eIDH\u003c/em\u003e wild-type gliomas, consistent with the results of Muench et al.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAs mentioned earlier, \u003cem\u003eTERT\u003c/em\u003emut, a predictor of highly aggressive gliomas in most studies, typically relies on a histological diagnosis of diffuse astrocytoma or anaplastic astrocytoma with \u003cem\u003eIDH\u003c/em\u003e wild-type and without 1p19q co-deletion\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, the significance of \u003cem\u003eTERT\u003c/em\u003emut with 1p19q co-deletion in the integrative diagnosis of glioma remains unclear. 1p19q serves as a crucial marker for the classification, treatment, and prognosis of glioma\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. 1p19q co-deletion is prevalent in all glioma subtypes, especially in patients with oligodendroglioma. Following an \u003cem\u003eIDH\u003c/em\u003e mutation, the tumor progresses to oligodendroglioma in cases where 1p19q combined deletion occurs. This co-deletion holds significance in differentiating oligodendrogliomas from astrocytomas and serves as a basis for differential diagnosis. Killela et al.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e reported that 78% (35/45) of oligodendrogliomas exhibited \u003cem\u003eTERT\u003c/em\u003emut. In our study, 17 of 18 oligodendrogliomas had \u003cem\u003eTERT\u003c/em\u003emut (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, among the 22 patients with glioma harboring a 1p19q co-deletion, 19 cases were accompanied by \u003cem\u003eTERT\u003c/em\u003emut (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Simultaneously, we observed no correlation between \u003cem\u003eTERT\u003c/em\u003emut and patient survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The OS of patients with 1p19q co-deletion was significantly longer than that of patients without 1p19q co-deletion, consistent with previously reported results\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. However, in the \u003cem\u003eTERT\u003c/em\u003emut group, 1p19q co-deletion was identified as an independent prognostic factor in patients with glioma (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Conversely, in the \u003cem\u003eTERT\u003c/em\u003ewt group, 1p19q co-deletion was not an independent prognostic factor for patients with glioma (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Therefore, when \u003cem\u003eTERT\u003c/em\u003e is not mutated, the increased survival associated with 1p19 co-deletion disappears. We propose that improved survival in patients with 1p19q co-deletion is dependent on \u003cem\u003eTERT\u003c/em\u003e promoter mutations. However, the mechanism by which 1p19 co-deletion affects the prognosis of patients with gliomas is complex. According to Lv et al. \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, the effect of 1p/19q co-deletion on the immune microenvironment in low-grade glioma plays a crucial role in tumor progression and prognosis. Immune cell infiltration of 281 low-grade gliomas from The Cancer Genome Atlas and 543 low-grade gliomas from the Chinese Glioma Genome Atlas were analyzed for immune cell infiltration using the ESTIMATE algorithm, TIMER, and xCell. Low-grade gliomas with 1p/19q co-deletion exhibit lesser immune cell infiltration and lower expression of immune checkpoint genes than those in 1p/19q non-co-deletion cases. Similarly, some studies have shown that a higher risk is associated with an increase in various factors in the tumor microenvironment, such as protein acetylation and inflammatory responses\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Furthermore, pathway analysis suggested that prostaglandins, N-terminal acetyltransferases, and responses to copper ions may be involved in 1p/19q glioma progression\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Collectively, we propose that better survival of patients with 1p19q co-deletion is dependent on \u003cem\u003eTERT\u003c/em\u003e promoter mutations; however, the specific mechanism remains to be further investigated.\u003c/p\u003e \u003cp\u003eWe acknowledge that our study has certain limitations. Patients in our cohort were treated using various modalities, and treatment annotations were lacking for a substantial portion of the dataset. In the future, we plan to conduct a confirmatory study that replicates and validates the findings for patients with a consistent treatment strategy, accounting for other prognostic factors, such as tumor size, location, and degree of resection.\u003c/p\u003e \u003cp\u003eIn summary, \u003cem\u003eTERT\u003c/em\u003e promoter mutations exhibit distinct patterns in patients with glioma, associated with age, histological type, and WHO grade. \u003cem\u003eTERT\u003c/em\u003emut is positively correlated with 1p19q co-deletion and is insufficient as an independent prognostic factor for \u003cem\u003eIDH\u003c/em\u003e wild-type gliomas. Notably, the ensemble prognostic signature featuring 1p19q co-deletion could serve as a valuable tool for risk stratification and survival prediction in gliomas with \u003cem\u003eTERT\u003c/em\u003e promoter mutations. As our understanding of the optimal classification of adult diffuse gliomas evolves, biomarkers for risk-based classification may enhance clinical strategies. Collectively, our findings present a reliable protocol for neurosurgeons to devise personalized surgical and treatment strategies in patients with glioma.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Pathology, The First People’s Hospital of Zigong, shang yi hao yi zhi lu 42#, Zigong 643099, Sichuan province, China.\u003c/p\u003e\n\u003cp\u003eDan Wan \u0026amp; Yutao Zhang\u003c/p\u003e\n\u003cp\u003eDepartment of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.\u003c/p\u003e\n\u003cp\u003eBenyan Zhang \u0026amp; Jialing Xie \u0026amp; Xianwei Yang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXianwei Yang and Dan Wan performed the sample collection and research and wrote the paper. Jialing Xie performed the experiments. Benyan Zhang contributed to the research design. Yutao Zhang and Benyan Zhang gave the final approval of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Xianwei Yang.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequencing data are available under controlled access at the National Center for Biotechnology Information\u0026nbsp;(NCBI)\u0026nbsp;database\u0026nbsp;under accession number: PQ002189, PQ002190, PQ002191, and PQ002192.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eM\u0026ouml;r\u0026eacute;n, L. \u003cem\u003eet al\u003c/em\u003e. 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Cancer\u003c/em\u003e\u003cstrong\u003e11\u003c/strong\u003e, 255\u0026ndash;263 (2004). \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, TERT promoter mutation, 1p/19q co-deletion, prognostic factor","lastPublishedDoi":"10.21203/rs.3.rs-4516259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4516259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVarious genetic variants, such as telomerase reverse transcriptase (TERT) promoter mutations (TERTmut) and 1p/19q co-deletion, are linked to gliomas; however, their prognostic significance remains uncertain. Here, we investigated the prevalence of TERTmut in gliomas, their correlation with clinicopathological features and molecular abnormalities, and prognostic implications of molecular abnormalities. Clinicopathological data were retrospectively collected from 161 patients diagnosed with glioma. An increased incidence of TERTmut was found in patients older than 50 years. Oligodendrogliomas and glioblastomas exhibited a higher susceptibility to TERT promoter mutations than astrocytomas. TERT promoter mutation rates were higher in WHO grade 3 and 4 tumors than in grade 1 and 2 tumors. The TERTmut group demonstrated a higher incidence of 1p19q co-deletion than the TERT wild-type group. Prognosis within the TERTmut group was closely correlated with histological type and glioma grade, along with IDH1/2 mutation, 1p19q co-deletion, and MGMT methylation, all indicative of a favorable prognosis. 1p19q co-deletion, and not IDH1/2 mutation, was identified as an independent prognostic factor for TERTmut glioma. The ensemble prognostic signature, incorporating 1p19q co-deletion, could aid in risk stratification and survival prediction in gliomas with TERTmut. Our findings establish a reliable and practical protocol for developing individualized surgical and treatment strategies.\u003c/p\u003e","manuscriptTitle":"1p19q co-deletion is an independent prognostic factor in glioma with TERT promoter mutations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-17 01:18:37","doi":"10.21203/rs.3.rs-4516259/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":"c4f09874-c53a-4505-8eb7-a91361356b5c","owner":[],"postedDate":"August 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":35599515,"name":"Biological sciences/Cancer/Cns cancer"},{"id":35599516,"name":"Biological sciences/Neuroscience/Diseases of the nervous system/Cancer in the nervous system"}],"tags":[],"updatedAt":"2024-08-27T07:46:40+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-17 01:18:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4516259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4516259","identity":"rs-4516259","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}