TTF2 as a Potential Biomarker and Immunotherapy Target in Glioma Diagnosis and Prognosis

TTF2 as a Potential Biomarker and Immunotherapy Target in Glioma Diagnosis and Prognosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article TTF2 as a Potential Biomarker and Immunotherapy Target in Glioma Diagnosis and Prognosis Dongliang Shi, Feng Chen, Zhenhua Chen, Hongqiao yang, Wei lin, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6821327/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Glioma is one of the common brain tumors in the central nervous system, with a poor prognosis and a serious threat to the life and health of patients. Exploring effective prognostic markers and conducting in-depth studies on related molecular mechanisms are of great significance for improving the prognosis of glioma patients. TTF2 (Transcription Termination Factor 2) has initially demonstrated its value as a potential prognostic factor in various cancers. However, its specific role in glioma remains unclear. Materials and Methods: We evaluated the expression preference, prognostic value and clinical characteristics of TTF2 from the Tumor Genome Atlas (TCGA) database and the Chinese Glioma Genome Atlas (CGGA) dataset. We constructed clinical prognostic models using independent prognostic risk factors and TTF2, and evaluated the accuracy of the models using calibration curves. The biological functions of TTF2 were explored by GO/KEGG/GSEA enrichment analysis. The relationship between TTF2 expression and immune infiltration was analyzed by ssGSEA (Single Sample Gene Set Enrichment Analysis), and the expression of TTF2 mRNA in glioma samples was verified by tissue specimens. Result: TTF2 was highly expressed in glioma. Multivariate analysis showed that TTF2 mRNA expression was an independent prognostic factor for Overall survival rate (OS) (HR = 2.113, 95%CI:1.393-3.204). Effective prognostic models can be constructed by using WHO classification, IDH status, age and the expression level of TTF2. Enrichment analysis and GSEA analysis showed that the expression of TTF2 was related to the production of immunoglobulins, adaptive immune responses, immune regulation, and the transmission of immune cell signaling factors, etc. ssGSEA showed that the expression of TTF2 was positively correlated with the infiltration level of Th2 cells. Conclusion: TTF2 is expressed in glioma and is associated with OS. TTF2 is a potential biomarker for the diagnosis and prognosis of glioma and may be a potential target for immunotherapy. Glioma TTF2 Prognosis Biomarker Biological Function Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Glioma, as the most aggressive malignant tumor of the central nervous system, accounts for approximately 80% of adult primary brain tumors 1 . Its clinical heterogeneity and treatment resistance have always been important challenges in the field of neuro-oncology 2 – 4 . Although the current standard treatment regimens combine maximum surgical resection, temozolomide chemotherapy and radiotherapy 5 – 7 , the high recurrence rate and drug resistance of glioma still exist, and the prognosis of patients is poor 8 – 10 . Studies have shown that the heterogeneity of the tumor microenvironment, the limitation of the blood-brain barrier, and abnormal epigenetic regulation jointly constitute the three core obstacles in the treatment of glioma, resulting in a five-year survival rate of less than 5% for patients 11 , 12 . Therefore, exploring new biomarkers with both diagnostic sensitivity and therapeutic targeting can become a strategic breakthrough for improving the prognosis of glioma. Recent research has highlighted the potential regulatory role of the Transcription Termination Factors (TTFs) family in tumorigenesis and disease progression. For example, TTF1 (RNA Polymerase I - Specific Transcription Termination Factor 1) drives ribosomal biosynthesis by regulating ribosomal RNA (rRNA) transcription termination, thereby promoting the abnormal proliferation of hepatocellular carcinoma. Clinical data analysis has revealed that high TTF1 expression is significantly associated with a shortened overall survival in liver cancer patients (hazard ratio HR = 1.89, p < 0.001) 13 . Similarly, TTF1 is markedly overexpressed in tumors such as thyroid cancer and lung cancer, with its expression levels correlating with adverse prognoses 14 , 15 . However, TTF2 is another member of this family, an ATP-dependent DNA translocase belonging to the SWI2/SNF2 superfamily, and is related to mitosis. The high expression of TTF2 may promote cell proliferation 16 , 17 , and it has received relatively less attention in the field of oncology. The expression pattern and functional mechanism of TTF2 in glioma remain unclear. This study sets out to investigate the potential role of TTF2 in glioma and its association with patient prognosis. Using the TCGA database and the CGGA dataset, we aim to evaluate the expression levels of TTF2 and its prognostic value in glioma. Through univariate and multivariate Cox analyses, we strive to identify independent prognostic factors and construct clinical prediction models. Additionally, bioinformatics analyses, including GO/KEGG/GSEA enrichment analyses, will be employed to elucidate the biological functions of TTF2 in glioma pathogenesis. Finally, PCR validation will be conducted to assess TTF2 mRNA expression in glioma. Our goal is to clarify the role of TTF2 in glioma progression and to explore its potential as a novel biomarker for early diagnosis and a promising therapeutic target for glioma treatment. Materials and methods Data Sets Patient clinical annotations and gene expression data were used in this study from public databases. TCGA gliomas data set ( https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga ), including genetic and phenotypic data, WHO Classification, IDH mutation status, 1P / 19q codeletion were missing from Ceccarelli, from the UCSC XENA ( https://xenabrowser.net/datapages/ ) by the Toil process unified handling TCGA GTEx and TPM RNAseq data format. Glioma from TCGA and corresponding normal tissue data from GTEx were extracted. Glioma genome from China (CGGA, http://www.cgga.org.cn/ ) from the other patients with gliomas, the download mRNA sequencing data (RSEM) and clinical data 18 – 20 . Analysis of the TTF2 Expression Level Between Cancer Tissue and Corresponding Normal Tissue The Xena browser at the University of California, Santa Cruz ( https://xenabrowser.net/ ) is an interactive web platform for gene expression that includes tumor and normal samples from TCGA and GTEx databases. Its gene expression data were recalculated based on the RNA-Seq data (TPM) of the UCSC Xena project, and a unified pipeline was used to address the imbalance between tumor and normal data. Meanwhile, tumor samples and normal samples in the CGGA database were used for result verification, and the R language pack (ggplot2) was used for the differential expression analysis of TTF2 in glioma and normal brain tissues. Survival Analysis of TTF2 in Glioma The study employed Kaplan–Meier survival analysis and the Cox proportional hazard model to evaluate the prognostic value of TTF2 in glioma. These statistical methods were implemented using R language packages, including the survival package for performing the survival analysis and the survminer package for creating survival plots. The analysis utilized data from the TCGA and CGGA datasets. Analysis of Differentially Expressed Genes (DEGs) Between the High and Low TTF2 Expression Groups in Patients With Gliomas The analysis of differentially expressed genes (DEGs) between the high and low TTF2 expression groups in patients with gliomas was performed. The expression profiles (HTSeq-FPKM) of the two groups were compared using the unpaired Student’s t-test within the limma package software. Specifically, the criteria of a |log2Fold Change| >2 and adjusted P < 0.05 were set as the threshold to identify the DEGs, ensuring the selection of genes with significant expression differences between the groups for further analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis The functional enrichment analysis, including gene ontology (GO) analysis comprised of cellular component (CC), molecular function (MF), biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, were performed via the cluster Profiler package in R language.Enriched ontological terms with an adjusted P value < 0.05 were regarded as statistically significant. Gene Set Enrichment Analysis (GSEA) GSEA is an analytical method that can determine whether a previously defined genome has a statistically significant and consistent difference between the two phenotypes. In this study, GSEA was performed using the R packet cluster profiler to clarify the significant functional and pathway differences between the high TTF2 group and the low TTF2 group. The gene set alignment was performed 1000 times. The expression level of TTF2 mRNA is used as a phenotypic marker. In this study, h.all.v7.0.symbols.gmt [Hallmarks] was selected as the reference gene set in the MSigDB collection. P < 0.05, and false discovery rate (FDR) 1 are regarded as significant enrichment. Analysis of the Connection of TTF2 Expression Level and Immune Infiltrates Using the R by applying the ssGSEA method in the GSVA package, we quantified the relative tumor infiltration level of immune cell types by integrating the gene expression levels in the published signature gene list. In order to evaluate the relationship between immune cell infiltration and different TTF2 mRNA expression groups, Wilcoxon rank sum test and Pearson correlation test were performed. Prognostic Model Generation and Prediction Univariate and multivariate analyses were performed using Cox proportional risk models to estimate mortality risk, where P < 0.05 was considered statistically significant. The WHO grade,1P/19q codeletion, IDH status, and Age variables were included to construct the clinical risk profile column diagram to predict the incidence of OS at 1, 3, and 5 years. RNA Isolation and qRT-PCR The expression levels of TTF2 mRNA were quantified using quantitative polymerase chain reaction (QPCR). The primers used for amplification were as follows: TTF2-F (homo) 5'-GCCAGTGTTGCTGTCATCTT-3' and TTF2-R (homo) 5'-GCTCTGAGTCACGGAGTTCT-3'; GAPDH-F (homo) 5'-GGTGTGAACCATGAGAAGTATGA-3' and GAPDH-R (homo) 5'-GAGTCCTTCCACGATACCAAAG-3'. Following the manufacturers' protocols, total RNA was meticulously extracted from both glioma tissues and normal control samples utilizing TRIzol reagent (Invitrogen, Carlsbad, CA, USA). Subsequently, complementary DNA (cDNA) was synthesized from 1 µg of the extracted total RNA, employing the PrimeScript TM RT reagent kit (Takara, Japan). To assess the expression of TTF2 mRNA, quantitative real-time PCR (qRT-PCR) was executed using the Eraser TM qPCR kit (Takara, Dalian, China). Throughout this process, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was utilized as the endogenous reference gene for normalization purposes, ensuring accurate quantification of TTF2 mRNA levels across different samples. Statistical Analysis Kruskal-wallis test, Wilcoxon signature test and Chi-square test were used to analyze the relationship between clinicopathological features and TTF2 expression. The survival curve was drawn by Kaplan-Meier method, and the difference between groups was evaluated by logarithmic rank test. Univariate and multivariate analyses were performed using Cox proportional risk models to estimate mortality risk. A P < 0.05 was considered statistically significant. Results TTF2 Overexpression in Glioma and Its Link to Poor Prognosis Compared to normal tissue, TTF2 for almost all tumor types in the TCGA database mRNA expression was significantly overexpressed in invasive glioma (GBM and LGG), breast carcinoma (BRCA), colonic adenocarcinoma (COAD), cholangiocarcinoma (CHOL), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), and renal Chromophobe (KICH), hepatocellular carcinoma (LIHC), Lung adenocarcinoma (LUAD), Lung squamous cell carcinoma (LUSC), pheochromocytoma, paraganglioma (PCPG), Rectal adenocarcinoma (READ), Gastric adenocarcinoma (STAD), Thymic carcinoma, prostate carcinoma (PRAD)(Fig. 1 A). Kaplan-meier survival analysis showed that the high expression of TTF2 was significantly associated with a poor prognosis (Fig. 1 D). The prognosis of glioma patients was analyzed using the expression level of TTF2mRNA, and the AUC value was 0.7–0.8 (Fig. 1 E). High TTF2 Expression Linked to Poor Prognosis and a Predictive Model for Glioma Survival The total sample size was 698 cases, among which 401 were male and 297 were female. According to the median expression level of TTF2 in low-grade gliomas, the total samples were divided into the low-expression group and the high-expression group. The detailed clinicopathological features are shown in Table 1 . Univariate and multivariate Cox analyses of clinical data showed that: WHO classification (HR = 9.538, 95%CI:7.243–12.560, P < 0.001), 1p/19q coding (HR = 0.225, 95%CI:0.147–0.346), IDH status (HR = 0.116, 95%CI: 0.089–0.151, P < 0.001), Age(HR = 4.696, 95%CI: 3.620–6.093, P < 0.001), TTF2 (HR = 4.645, 95%CI:3.494–6.177, P < 0.001), multivariate analysis showed: WHO classification (HR = 2.571, 95%CI:1.795–3.682, P < 0.001), IDH status (HR = 0.266, 95%CI: 0.179–0.396, P < 0.001), Age(HR = 1.489, 95%CI: 1.090–2.035, P < 0.001) and TTF2 (HR = 1.608, 95%CI:1.113–2.323, P = 0.011) were independent prognostic factors(Table 2 ) (Fig. 2 A-B). We verified this result by fitting TTF2 mRNA expression and other clinicopathological parameters, and established an OS prediction model in TCGA data, including TTF2 and other independent prognostic factors, such as WHO grade, IDH mutation status and age (Fig. 2 C). The higher the point on the chart is, the worse the indicative factor is. The performance of the model diagram is evaluated using the calibration curve (Fig. 2 D). Interestingly, using TCGA data analysis, we found that the expression of TTF2 was significantly increased in high-grade gliomas (Fig. 3 A). In the analyses of PD (Progressive disease), SD (StableDisease), PR (PartialResponse), and CR (CompleteResponse), it was found that the expression of TTF2 was inversely proportional to the treatment correlation (Fig. 3 B). The relationship between progression-free survival (PFI), disease-specific survival (DSS) and the expression of TTF2 also proves this point (Fig. 3 C-D) Functional enrichment analysis of samples with high and low TTF2 expression To explore the potential mechanism by which TTF2 promotes tumor progression, we analyzed samples with high and low expression of TTF2 and subsequently presented genes co-expressed with TTF2, including up-regulated genes and down-regulated genes (Fig. 4 A-B). The correlations of co-expressed genes were demonstrated, with red representing positive correlations and blue representing negative correlations (Fig. 4 C). Subsequently, GO enrichment analysis was used to predict the co-expression function of glioma patients. The Top go bioenrichment program (BP), molecular function (MF), and cellular component (CC) groups, including immunoglobulin complexes, signal receptor activation, receptory-ligand activity, cell recognition, etc. (Fig. 4 D), KEGG analysis revealed that TTF2 may be involved in a variety of pathways including cell adhesion, the PI3K-AKT signaling pathway, the AGE-RAGE signaling pathway, etc. (Fig. 4 E) (Table 3 ), and the key pathways related to TTF2 were determined through GSEA analysis. GSEA analysis revealed that the data set satisfied FDR < 0.25, P < 0.05. Enrichment analysis and GSEA analysis showed that the expression of TTF2 was related to the production of immunoglobulins, adaptive immune responses, immune regulation, and the transmission of immune cell signaling factors, etc (Fig. 4 F-I). The expression of TTF2 in glioma is related to the level of immune infiltration Considering that both KEGG and GSEA enrichment analyses found that TTF2 might be involved in the tumor immune response, we further used ssGSEA to analyze the relationship between TTF2 mRNA expression and the infiltration level of immune cells. The correlation between immune cell infiltration and TTF2 mRNA expression (Fig. 5 A). The results showed that the expression level of TTF2 mRNA was higher than that of Th2 Cells (R = 0.595, P < 0.001) and macrophages (R = 0.509, P < 0.001;) (Fig. 5 B-C), neutrophils (R = 0.422, P < 0.001; (Fig. 5 D) shows a positive correlation. Additionally, ssGSEA also indicates that the expression of TTF2 is negatively correlated with pDC (R=-0.455, P < 0.001) (Fig. 5 E). To verify the clinical characteristics and expression levels of TTF2 in glioma The results showed that after dividing the samples into two groups with high and low expression of TTF2, the expression of TTF2 was inversely proportional to 1/19q (Fig. 6 A). The expression of TTF2 in mutant IDH was also lower than that in wild-type IDH (Fig. 6 B). However, in terms of gender (Fig. 6 C), there was no significant difference in the expression of TTF2. In those over 60 years old (Fig. 6 D), the expression of TTF2 was significantly increased. The expression of TTF2 was verified using brain tissue and glioma, and it was found that the expression in tumor tissue was significantly higher than that in normal tissue (P < 0.001;) (Fig. 6 E). Discussion This study found that TTF2 was significantly overexpressed in glioma. Functional enrichment analysis indicated that it was related to immunoglobulin complexes, signal receptor activation, receptor-ligand activity, cell recognition, etc. It was involved in multiple pathways and immune pathways such as cell adhesion, PI3K-AKT signaling pathway, AGE-RAGE signaling pathway, etc. And it increased the infiltration level of various immune cells. Therefore, our research has revealed the potential role of TTF2 in the pathogenesis of glioma and demonstrated its application prospects as a potential biomarker for glioma. This study found that TTF2 was significantly overexpressed in most tumors in the TCGA data. These results suggest that TTF2 has the potential to become a diagnostic marker for various cancers. Furthermore, we also found that TTF2 is related to clinical characteristics such as the pathological type of glioma, IDH mutation, 1P/19q coding status, and age, further supporting that the expression of TTF2 may be related to the malignancy degree of glioma. This study indicates that patients with high expression of TTF2 mRNA have a poorer OS and it is an independent prognostic factor for OS. This result was verified in the CGGA dataset. Considering that TTF2 is a strong prognostic factor, we combined TTF2 expression with clinical data to construct a chart that can predict the OS of TTF2 patients at 1 year, 3 years and 5 years. This chart can help screen high-risk patients and determine more aggressive treatment plans for high-risk glioma patients. Meanwhile, this study combined with tissue specimens verified that TTF2 was highly expressed in gliomas. This result is consistent with previous studies, which also found that the TTF2 protein is highly expressed in various types of cancer, including papillary thyroid carcinoma, colorectal adenocarcinoma and breast cancer, etc 21 – 25 . TTF2 is the core regulatory factor of the transcription termination process mediated by RNA polymerase II. Its domain promotes chromatin unwinding and the dissociation of RNA-DNA heterozygotes by hydrolyzing ATP 26 . Some studies have shown that the protein level of the transcription termination-related factor TTF2 is regulated by APC/ C-mediated ubiquitin-proteasome in a cyclic-dependent manner 27 . Knockout of TTF2 activates the spindle assembly checkpoint (SAC), leading to chromosomal separation errors and cytoplasmic division failure. This may be a possible mechanism of TTF2 in tumors 17 . Our enrichment analysis and GSEA found that TTF2 may be involved in some immune pathways. ssGSEA also showed that TTF2 was positively correlated with the infiltration of Th2 cells, macrophages and neutrophils, but negatively correlated with the infiltration of pDC cells. It has been found in previous studies that Th2 cell infiltration is associated with Th2 cell immunosuppression and poor survival in various tumors. In this study, we found a significant increase in Th2 cells, suggesting that TTF2 may be involved in glioma-mediated immune escape. A similar situation also occurs on the tumor-associated antigen EpCAM, which promotes Th2 cell-mediated immune escape 28 – 30 . Therefore, TTF2 has great value as a possible immunotherapy target in the future. In this study, although we have gained a deeper understanding of the relationship between TTF2 and glioma, there are still certain limitations. First of all, due to the lack of experience in both in vivo and in vitro experiments, we were unable to verify our results. Furthermore, due to the design limitations of our study, other key signaling pathways related to TTF2 may be omitted, which requires further research. To further study the mechanism of action of TTF2 in glioma, we need to conduct further cell and animal experiments. Conclusion TTF2 mRNA is overexpressed in glioma, and high TTF2 mRNA expression is OS-related. TTF2 is a potential biomarker for the diagnosis and prognosis of glioma and may be a potential target for immunotherapy. Declarations Data availability The following publicly available datasets were analyzed in this study: TCGA, https://portal.gdc.cancer.gov; CGGA, http://www.cgga.org.cn; Acknowledgements We would like to thank the investigators, clinicians, technical personnel, and funding bodies who contributed to the TCGA, CGGA databases and made the information public. Without these data, the present study would not have been possible. Funding This study was funded by the Development Foundation Wuxi Municipal Bureau on Science and Technology (Grant No: N20201008). Author information Authors and Affiliations Department of Neurosurgery, Wuxi Clinical College of Anhui Medical University, 904th Hospital of Joint Logistic Support Force of PLA, Wuxi, China. Dongliang Shi,Hongqiao yang,Wei lin,Yuhai wang Department of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China Feng Chen, Department of Neurosurgery, Affiliated Hospital 2 of Nantong University and First People’s Hospital of Nantong City, Nantong, China Zhenhua Chen Contributions Research conception and design: Dongliang Shi, Data acquisition: Dongliang Shi, Feng Chen, Zhenhua Chen , Data analysis and interpretation: Dongliang Shi, Feng Chen, Zhenhua Chen Drafting of the manuscript: Dongliang Shi Hongqiao yang,Wei lin, Critical revision of the manuscript: Yuhai wang Approval of the final manuscript: Dongliang Shi, Feng Chen, Zhenhua Chen, Yuhai wang. Corresponding authors Correspondence to Yuhai wang Ethics declarations Ethics approval and consent to participate The studies involving humans were approved by the Ethics Committee of 904th Hospital of Joint Logistic Support Force of PLA ,Wuxi Clinical College of Anhui Medical University (Nos. 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Combinational Immunotherapy for Hepatocellular Carcinoma: Radiotherapy, Immune Checkpoint Blockade and Beyond. Front Immunol. 2020;11:568759. Tables Table 1 Basic clinical baseline table of Glioma Characteristics Low expression of TTF2 High expression of TTF2 P value n 297 312 WHO grade, n (%) < 0.001 G2 169 (27.8%) 46 (7.6%) G3 117 (19.2%) 125 (20.5%) G4 11 (1.8%) 141 (23.2%) IDH status, n (%) < 0.001 WT 30 (4.9%) 199 (32.7%) Mut 267 (43.8%) 113 (18.6%) Age, n (%) < 0.001 60 35 (5.7%) 103 (16.9%) OS event, n (%) < 0.001 Alive 245 (40.2%) 125 (20.5%) Dead 52 (8.5%) 187 (30.7%) 1p/19q codeletion, n (%) < 0.001 Non-codel 167 (27.4%) 292 (47.9%) Codel 130 (21.3%) 20 (3.3%) Gender, n (%) 0.497 Female 128 (21%) 126 (20.7%) Male 169 (27.8%) 186 (30.5%) Race, n (%) 0.183 Asian&Black or African American 15 (2.5%) 24 (3.9%) White 282 (46.3%) 288 (47.3%) Table 2 Univariate and multivariate Cox regression analysis Characteristics Total(N) Univariate analysis Multivariate analysis Hazard ratio (95% CI) P value Hazard ratio (95% CI) P value WHO grade 636 G2&G3 468 Reference Reference G4 168 9.538 (7.243–12.560) < 0.001 2.571 (1.795–3.682) < 0.001 IDH status 688 WT 246 Reference Reference Mut 442 0.116 (0.089–0.151) < 0.001 0.266 (0.179–0.396) < 0.001 Age 698 60 143 4.696 (3.620–6.093) < 0.001 1.489 (1.090–2.035) 0.012 Gender 698 Female 297 Reference Reference Male 401 1.250 (0.979–1.595) 0.073 1.229 (0.937–1.611) 0.136 1p/19q codeletion 691 Non-codel 520 Reference Reference Codel 171 0.225 (0.147–0.346) < 0.001 0.750 (0.448–1.257) 0.275 Race 685 Asian&Black or African American 46 Reference White 639 0.817 (0.499–1.337) 0.421 TTF2 698 Low 348 Reference Reference High 350 4.645 (3.494–6.177) < 0.001 1.608 (1.113–2.323) 0.011 Table 3 GO and KEGG enrichment analysis Ontology ID Description GeneRatio BgRatio pvalue p.adjust BP GO:0009952 anterior/posterior pattern specification 39/581 214/18800 2.28e-19 7.15e-16 BP GO:0007389 pattern specification process 57/581 463/18800 3.52e-19 7.15e-16 BP GO:0048568 embryonic organ development 54/581 449/18800 9.2e-18 1.24e-14 BP GO:0003002 regionalization 47/581 354/18800 2.72e-17 2.76e-14 BP GO:0050853 B cell receptor signaling pathway 29/581 131/18800 4.28e-17 3.02e-14 CC GO:0019814 immunoglobulin complex 48/599 167/19594 2.32e-33 8.82e-31 CC GO:0042571 immunoglobulin complex, circulating 24/599 77/19594 3.39e-18 6.44e-16 CC GO:0009897 external side of plasma membrane 43/599 455/19594 5.8e-11 7.35e-09 CC GO:0062023 collagen-containing extracellular matrix 41/599 429/19594 1.17e-10 1.11e-08 CC GO:0072562 blood microparticle 21/599 147/19594 4.3e-09 3.26e-07 MF GO:0003823 antigen binding 44/570 174/18410 6.98e-28 4.21e-25 MF GO:0034987 immunoglobulin receptor binding 24/570 80/18410 1.2e-17 3.62e-15 MF GO:0005201 extracellular matrix structural constituent 24/570 172/18410 6.97e-10 1.4e-07 MF GO:0048018 receptor ligand activity 40/570 489/18410 2.42e-08 3.65e-06 MF GO:0030546 signaling receptor activator activity 40/570 496/18410 3.58e-08 4.31e-06 KEGG hsa04080 Neuroactive ligand-receptor interaction 32/234 362/8164 9.82e-09 2.42e-06 KEGG hsa04512 ECM-receptor interaction 13/234 88/8164 1.13e-06 0.0001 KEGG hsa05033 Nicotine addiction 9/234 40/8164 1.41e-06 0.0001 KEGG hsa04060 Cytokine-cytokine receptor interaction 24/234 295/8164 3.52e-06 0.0002 KEGG hsa05202 Transcriptional misregulation in cancer 18/234 193/8164 9.73e-06 0.0005 Additional Declarations No competing interests reported. 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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-6821327","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484953561,"identity":"b6a899f6-3e32-41d7-9f2c-3ccbdc60d44d","order_by":0,"name":"Dongliang Shi","email":"","orcid":"","institution":"Department of Neurosurgery, Wuxi Clinical College of Anhui Medical University, 904th Hospital of Joint Logistic Support Force of PLA","correspondingAuthor":false,"prefix":"","firstName":"Dongliang","middleName":"","lastName":"Shi","suffix":""},{"id":484953564,"identity":"86ae05ab-bb6b-4266-a219-49c1dd6f334e","order_by":1,"name":"Feng Chen","email":"","orcid":"","institution":"Department of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Chen","suffix":""},{"id":484953566,"identity":"0c641165-0c51-4323-9a60-675c9774b064","order_by":2,"name":"Zhenhua Chen","email":"","orcid":"","institution":"Department of Neurosurgery, Affiliated Hospital 2 of Nantong University and First People’s Hospital of Nantong City","correspondingAuthor":false,"prefix":"","firstName":"Zhenhua","middleName":"","lastName":"Chen","suffix":""},{"id":484953568,"identity":"614628b9-e305-4419-ba97-0aaa76042fab","order_by":3,"name":"Hongqiao yang","email":"","orcid":"","institution":"Department of Neurosurgery, Wuxi Clinical College of Anhui Medical University, 904th Hospital of Joint Logistic Support Force of PLA","correspondingAuthor":false,"prefix":"","firstName":"Hongqiao","middleName":"","lastName":"yang","suffix":""},{"id":484953569,"identity":"a00a7c8e-6a03-4ded-9a07-be9dadee72c4","order_by":4,"name":"Wei lin","email":"","orcid":"","institution":"Department of Neurosurgery, Wuxi Clinical College of Anhui Medical University, 904th Hospital of Joint Logistic Support Force of PLA","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"lin","suffix":""},{"id":484953570,"identity":"c6debcfd-c23a-4030-b2ee-be72ca005c5f","order_by":5,"name":"Yuhai wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIie3PMQrCMBSA4RcCcYmtY0ShV9BFEBSv0iLoUm+gohTiFVocvEV1VARdPEChDrp0bhZxNK3oZuMomJ9ASHgfJAA63S/G0IzJjRqAD/kFKX1LCJABgC0JVpJ8yUmgrZyAilhLbx6JzaROmHu7iHtoGRhQKtzPpHHeee3gdKSEjdZN346bHAOuBmEBYQ6vlfkhI2GN2jGShOByAbH8N3GTjPSUBKKcjDNCMuIoSSNy5F/4lhKatKr+IO5zjLzCv1j+8BoJPu2ZpX7C0k7cXS28XSqKHvZsD1CxXwc0U87LpgDm9ptBnU6n+8ceHk5KL8hRTMkAAAAASUVORK5CYII=","orcid":"","institution":"Department of Neurosurgery, Wuxi Clinical College of Anhui Medical University, 904th Hospital of Joint Logistic Support Force of PLA","correspondingAuthor":true,"prefix":"","firstName":"Yuhai","middleName":"","lastName":"wang","suffix":""}],"badges":[],"createdAt":"2025-06-04 14:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6821327/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6821327/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87030803,"identity":"0ccb24b7-88b9-4448-8c92-e5f9bb2b4287","added_by":"auto","created_at":"2025-07-18 12:46:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75598,"visible":true,"origin":"","legend":"\u003cp\u003eTTF2 mRNA in Glioma and other types of human cancers from TCGA and CGGA data:(A) The expression level of TTF2 in different tumor types in the TCGA database. (B) UCSC Xena analyzed the expression levels of TTF2 in Glioma and normal tissues. The expression of TTF2 in glioma was significantly higher than the normal level. (C) The CCGA database shows the expression levels of TTF2 in Glioma and normal tissues. (D)TCGA data analysis showed that high expression of TTF2 was associated with poor prognosis. (E) Relationship between the expression level of TTF2 and the AUC curve.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6821327/v1/ec2437f136971d755d1cd667.png"},{"id":87030800,"identity":"9d233f37-97a5-4adb-8b04-175614c66dc3","added_by":"auto","created_at":"2025-07-18 12:46:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46193,"visible":true,"origin":"","legend":"\u003cp\u003eUnivariate and multivariate cox regression analysis of glioma and construction of TTF2 prognostic model: (A-B) Univariate and multivariate Cox regression analysis was conducted using the TCGA database to explore the independent risk factors in glioma. WHO grade, IDH status, Age, and TTF2 were the independent risk factors related to prognosis. (C) nomogram integrating TTF2 and other prognostic factors from TCGA data. (D) Calibration curves of the prediction models for 1/3/5 years.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6821327/v1/692cb260b047acd0136c99ec.png"},{"id":87032910,"identity":"47e38124-da95-4881-bb2a-5b90a540358a","added_by":"auto","created_at":"2025-07-18 13:02:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":52923,"visible":true,"origin":"","legend":"\u003cp\u003eHigh TTF2 expression is inversely proportional to the therapeutic effect: (A) The expression of TTF2 significantly increases in high-grade gliomas. (B) In PD (progressive disease), SD (stable disease), PR (partial response), and CR (complete response), the expression of TTF2 is inversely proportional to the therapeutic correlation. (C-D)The relationship between progression-free survival (PFI), disease-specific survival (DSS) and the expression of TTF2 also proves this point.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6821327/v1/0622da93ac10210f382018db.png"},{"id":87032911,"identity":"6b8c2bf4-d909-473a-a361-84c5197a61fc","added_by":"auto","created_at":"2025-07-18 13:02:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":140231,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional enrichment of TTF2 in Glioma：(A-B) The samples were divided into high-expression and low-expression groups using the median of TTF2 to explore the co-expressed genes of TTF2. The heat maps respectively showed the top 20 genes positively correlated with TTF2 expression and the top 20 genes negatively correlated with TTF2 expression. (C) The correlation matrix diagram shows the genes associated with TTF2. (D) GO enrichment analysis diagram. (E) KEGG analysis revealed that TTF2 might be involved in multiple pathways such as cell adhesion, the PI3K-AKT signaling pathway, and the AGE-RAGE signaling pathway. (F-I)GSEA analysis showed a correlation with immune responses, such as the production of immunoglobulins, adaptive immune responses, immune regulation, and the transmission of immune cell signaling factors.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6821327/v1/77b05e0a275c446db1045a3d.png"},{"id":87032185,"identity":"14e38980-9c60-4ca1-8947-260d46052280","added_by":"auto","created_at":"2025-07-18 12:54:29","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79010,"visible":true,"origin":"","legend":"\u003cp\u003eTTF2 immune correlation analysis: (A) ssGSEA was used to analyze the relationship between TTF2 mRNA expression and the infiltration level of immune cells. (B) The expression of TTF2 was positively correlated with that of Th2 cells, p\u0026lt;0.001. (C) The expression of TTF2 was positively correlated with that of macrophages. (D) The expression of TTF2 was positively correlated with that of neutrophils, p\u0026lt;0.001. (E) The expression of TTF2 was negatively correlated with that of pDC cells, p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6821327/v1/bbfb5471a1ea52325281c81b.png"},{"id":87034626,"identity":"3bc352f5-b5e6-46a4-8124-e3d94cf2c681","added_by":"auto","created_at":"2025-07-18 13:10:29","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":59078,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of TTF2 expression with clinical characteristics and verification of tissue specimens: (A) In 1p/19q codeletion, the expression of TTF2 was higher in the Non-codel group. (B) In IDH status, TTF2 is expressed higher in WT. (C) In terms of gender, there was no significant difference in the expression of TTF2. \\ n (D) In terms of age, the expression of TTF2 was significantly increased in those over 60 years old. (E) The expression of TTF2 was verified using glioma and normal tissue samples. The expression of TTF2 was significantly increased in glioma tumor samples.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6821327/v1/7e4e2fda619edf23ab7917f0.png"},{"id":91616742,"identity":"dca18d60-c397-48ce-b097-cba244136bd9","added_by":"auto","created_at":"2025-09-18 10:40:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1698717,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6821327/v1/e1744b36-1667-45ac-b34d-a9c38a1fd026.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"TTF2 as a Potential Biomarker and Immunotherapy Target in Glioma Diagnosis and Prognosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlioma, as the most aggressive malignant tumor of the central nervous system, accounts for approximately 80% of adult primary brain tumors\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Its clinical heterogeneity and treatment resistance have always been important challenges in the field of neuro-oncology\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Although the current standard treatment regimens combine maximum surgical resection, temozolomide chemotherapy and radiotherapy\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, the high recurrence rate and drug resistance of glioma still exist, and the prognosis of patients is poor\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Studies have shown that the heterogeneity of the tumor microenvironment, the limitation of the blood-brain barrier, and abnormal epigenetic regulation jointly constitute the three core obstacles in the treatment of glioma, resulting in a five-year survival rate of less than 5% for patients \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Therefore, exploring new biomarkers with both diagnostic sensitivity and therapeutic targeting can become a strategic breakthrough for improving the prognosis of glioma.\u003c/p\u003e\u003cp\u003eRecent research has highlighted the potential regulatory role of the Transcription Termination Factors (TTFs) family in tumorigenesis and disease progression. For example, TTF1 (RNA Polymerase I - Specific Transcription Termination Factor 1) drives ribosomal biosynthesis by regulating ribosomal RNA (rRNA) transcription termination, thereby promoting the abnormal proliferation of hepatocellular carcinoma. Clinical data analysis has revealed that high TTF1 expression is significantly associated with a shortened overall survival in liver cancer patients (hazard ratio HR\u0026thinsp;=\u0026thinsp;1.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003csup\u003e13\u003c/sup\u003e. Similarly, TTF1 is markedly overexpressed in tumors such as thyroid cancer and lung cancer, with its expression levels correlating with adverse prognoses\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. However, TTF2 is another member of this family, an ATP-dependent DNA translocase belonging to the SWI2/SNF2 superfamily, and is related to mitosis. The high expression of TTF2 may promote cell proliferation\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and it has received relatively less attention in the field of oncology. The expression pattern and functional mechanism of TTF2 in glioma remain unclear.\u003c/p\u003e\u003cp\u003eThis study sets out to investigate the potential role of TTF2 in glioma and its association with patient prognosis. Using the TCGA database and the CGGA dataset, we aim to evaluate the expression levels of TTF2 and its prognostic value in glioma. Through univariate and multivariate Cox analyses, we strive to identify independent prognostic factors and construct clinical prediction models. Additionally, bioinformatics analyses, including GO/KEGG/GSEA enrichment analyses, will be employed to elucidate the biological functions of TTF2 in glioma pathogenesis. Finally, PCR validation will be conducted to assess TTF2 mRNA expression in glioma. Our goal is to clarify the role of TTF2 in glioma progression and to explore its potential as a novel biomarker for early diagnosis and a promising therapeutic target for glioma treatment.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Sets\u003c/h2\u003e\u003cp\u003ePatient clinical annotations and gene expression data were used in this study from public databases. TCGA gliomas data set (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga\u003c/span\u003e\u003cspan address=\"https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), including genetic and phenotypic data, WHO Classification, IDH mutation status, 1P / 19q codeletion were missing from Ceccarelli, from the UCSC XENA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xenabrowser.net/datapages/\u003c/span\u003e\u003cspan address=\"https://xenabrowser.net/datapages/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) by the Toil process unified handling TCGA GTEx and TPM RNAseq data format. Glioma from TCGA and corresponding normal tissue data from GTEx were extracted. Glioma genome from China (CGGA, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cgga.org.cn/\u003c/span\u003e\u003cspan address=\"http://www.cgga.org.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) from the other patients with gliomas, the download mRNA sequencing data (RSEM) and clinical data\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAnalysis of the TTF2 Expression Level Between Cancer Tissue and Corresponding Normal Tissue\u003c/h3\u003e\n\u003cp\u003eThe Xena browser at the University of California, Santa Cruz (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xenabrowser.net/\u003c/span\u003e\u003cspan address=\"https://xenabrowser.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is an interactive web platform for gene expression that includes tumor and normal samples from TCGA and GTEx databases. Its gene expression data were recalculated based on the RNA-Seq data (TPM) of the UCSC Xena project, and a unified pipeline was used to address the imbalance between tumor and normal data. Meanwhile, tumor samples and normal samples in the CGGA database were used for result verification, and the R language pack (ggplot2) was used for the differential expression analysis of TTF2 in glioma and normal brain tissues.\u003c/p\u003e\n\u003ch3\u003eSurvival Analysis of TTF2 in Glioma\u003c/h3\u003e\n\u003cp\u003eThe study employed Kaplan\u0026ndash;Meier survival analysis and the Cox proportional hazard model to evaluate the prognostic value of TTF2 in glioma. These statistical methods were implemented using R language packages, including the survival package for performing the survival analysis and the survminer package for creating survival plots. The analysis utilized data from the TCGA and CGGA datasets.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnalysis of Differentially Expressed Genes (DEGs) Between the High and Low TTF2 Expression Groups in Patients With Gliomas\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe analysis of differentially expressed genes (DEGs) between the high and low TTF2 expression groups in patients with gliomas was performed. The expression profiles (HTSeq-FPKM) of the two groups were compared using the unpaired Student\u0026rsquo;s t-test within the limma package software. Specifically, the criteria of a |log2Fold Change| \u0026gt;2 and adjusted P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were set as the threshold to identify the DEGs, ensuring the selection of genes with significant expression differences between the groups for further analysis.\u003c/p\u003e\n\u003ch3\u003eGene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis\u003c/h3\u003e\n\u003cp\u003eThe functional enrichment analysis, including gene ontology (GO) analysis comprised of cellular component (CC), molecular function (MF), biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, were performed via the cluster Profiler package in R language.Enriched ontological terms with an adjusted P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were regarded as statistically significant.\u003c/p\u003e\n\u003ch3\u003eGene Set Enrichment Analysis (GSEA)\u003c/h3\u003e\n\u003cp\u003eGSEA is an analytical method that can determine whether a previously defined genome has a statistically significant and consistent difference between the two phenotypes. In this study, GSEA was performed using the R packet cluster profiler to clarify the significant functional and pathway differences between the high TTF2 group and the low TTF2 group. The gene set alignment was performed 1000 times. The expression level of TTF2 mRNA is used as a phenotypic marker. In this study, h.all.v7.0.symbols.gmt [Hallmarks] was selected as the reference gene set in the MSigDB collection. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.25, meanwhile, standardized enrichment score (|NES|)\u0026thinsp;\u0026gt;\u0026thinsp;1 are regarded as significant enrichment.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of the Connection of TTF2 Expression Level and Immune Infiltrates\u003c/h2\u003e\u003cp\u003eUsing the R by applying the ssGSEA method in the GSVA package, we quantified the relative tumor infiltration level of immune cell types by integrating the gene expression levels in the published signature gene list. In order to evaluate the relationship between immune cell infiltration and different TTF2 mRNA expression groups, Wilcoxon rank sum test and Pearson correlation test were performed.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePrognostic Model Generation and Prediction\u003c/h3\u003e\n\u003cp\u003eUnivariate and multivariate analyses were performed using Cox proportional risk models to estimate mortality risk, where P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. The WHO grade,1P/19q codeletion, IDH status, and Age variables were included to construct the clinical risk profile column diagram to predict the incidence of OS at 1, 3, and 5 years.\u003c/p\u003e\n\u003ch3\u003eRNA Isolation and qRT-PCR\u003c/h3\u003e\n\u003cp\u003eThe expression levels of TTF2 mRNA were quantified using quantitative polymerase chain reaction (QPCR). The primers used for amplification were as follows: TTF2-F (homo) 5'-GCCAGTGTTGCTGTCATCTT-3' and TTF2-R (homo) 5'-GCTCTGAGTCACGGAGTTCT-3'; GAPDH-F (homo) 5'-GGTGTGAACCATGAGAAGTATGA-3' and GAPDH-R (homo) 5'-GAGTCCTTCCACGATACCAAAG-3'. Following the manufacturers' protocols, total RNA was meticulously extracted from both glioma tissues and normal control samples utilizing TRIzol reagent (Invitrogen, Carlsbad, CA, USA). Subsequently, complementary DNA (cDNA) was synthesized from 1 \u0026micro;g of the extracted total RNA, employing the PrimeScript TM RT reagent kit (Takara, Japan). To assess the expression of TTF2 mRNA, quantitative real-time PCR (qRT-PCR) was executed using the Eraser TM qPCR kit (Takara, Dalian, China). Throughout this process, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was utilized as the endogenous reference gene for normalization purposes, ensuring accurate quantification of TTF2 mRNA levels across different samples.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eKruskal-wallis test, Wilcoxon signature test and Chi-square test were used to analyze the relationship between clinicopathological features and TTF2 expression. The survival curve was drawn by Kaplan-Meier method, and the difference between groups was evaluated by logarithmic rank test. Univariate and multivariate analyses were performed using Cox proportional risk models to estimate mortality risk. A P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eTTF2 Overexpression in Glioma and Its Link to Poor Prognosis\u003c/h2\u003e\u003cp\u003eCompared to normal tissue, TTF2 for almost all tumor types in the TCGA database mRNA expression was significantly overexpressed in invasive glioma (GBM and LGG), breast carcinoma (BRCA), colonic adenocarcinoma (COAD), cholangiocarcinoma (CHOL), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), and renal Chromophobe (KICH), hepatocellular carcinoma (LIHC), Lung adenocarcinoma (LUAD), Lung squamous cell carcinoma (LUSC), pheochromocytoma, paraganglioma (PCPG), Rectal adenocarcinoma (READ), Gastric adenocarcinoma (STAD), Thymic carcinoma, prostate carcinoma (PRAD)(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Kaplan-meier survival analysis showed that the high expression of TTF2 was significantly associated with a poor prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). The prognosis of glioma patients was analyzed using the expression level of TTF2mRNA, and the AUC value was 0.7\u0026ndash;0.8 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eHigh TTF2 Expression Linked to Poor Prognosis and a Predictive Model for Glioma Survival\u003c/h2\u003e\u003cp\u003eThe total sample size was 698 cases, among which 401 were male and 297 were female. According to the median expression level of TTF2 in low-grade gliomas, the total samples were divided into the low-expression group and the high-expression group. The detailed clinicopathological features are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Univariate and multivariate Cox analyses of clinical data showed that: WHO classification (HR\u0026thinsp;=\u0026thinsp;9.538, 95%CI:7.243\u0026ndash;12.560, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 1p/19q coding (HR\u0026thinsp;=\u0026thinsp;0.225, 95%CI:0.147\u0026ndash;0.346), IDH status (HR\u0026thinsp;=\u0026thinsp;0.116, 95%CI: 0.089\u0026ndash;0.151, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Age(HR\u0026thinsp;=\u0026thinsp;4.696, 95%CI: 3.620\u0026ndash;6.093, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), TTF2 (HR\u0026thinsp;=\u0026thinsp;4.645, 95%CI:3.494\u0026ndash;6.177, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), multivariate analysis showed: WHO classification (HR\u0026thinsp;=\u0026thinsp;2.571, 95%CI:1.795\u0026ndash;3.682, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), IDH status (HR\u0026thinsp;=\u0026thinsp;0.266, 95%CI: 0.179\u0026ndash;0.396, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Age(HR\u0026thinsp;=\u0026thinsp;1.489, 95%CI: 1.090\u0026ndash;2.035, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and TTF2 (HR\u0026thinsp;=\u0026thinsp;1.608, 95%CI:1.113\u0026ndash;2.323, P\u0026thinsp;=\u0026thinsp;0.011) were independent prognostic factors(Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-B). We verified this result by fitting TTF2 mRNA expression and other clinicopathological parameters, and established an OS prediction model in TCGA data, including TTF2 and other independent prognostic factors, such as WHO grade, IDH mutation status and age (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The higher the point on the chart is, the worse the indicative factor is. The performance of the model diagram is evaluated using the calibration curve (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Interestingly, using TCGA data analysis, we found that the expression of TTF2 was significantly increased in high-grade gliomas (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In the analyses of PD (Progressive disease), SD (StableDisease), PR (PartialResponse), and CR (CompleteResponse), it was found that the expression of TTF2 was inversely proportional to the treatment correlation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The relationship between progression-free survival (PFI), disease-specific survival (DSS) and the expression of TTF2 also proves this point (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eFunctional enrichment analysis of samples with high and low TTF2 expression\u003c/h2\u003e\u003cp\u003eTo explore the potential mechanism by which TTF2 promotes tumor progression, we analyzed samples with high and low expression of TTF2 and subsequently presented genes co-expressed with TTF2, including up-regulated genes and down-regulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). The correlations of co-expressed genes were demonstrated, with red representing positive correlations and blue representing negative correlations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Subsequently, GO enrichment analysis was used to predict the co-expression function of glioma patients. The Top go bioenrichment program (BP), molecular function (MF), and cellular component (CC) groups, including immunoglobulin complexes, signal receptor activation, receptory-ligand activity, cell recognition, etc. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), KEGG analysis revealed that TTF2 may be involved in a variety of pathways including cell adhesion, the PI3K-AKT signaling pathway, the AGE-RAGE signaling pathway, etc. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and the key pathways related to TTF2 were determined through GSEA analysis. GSEA analysis revealed that the data set satisfied FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.25, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Enrichment analysis and GSEA analysis showed that the expression of TTF2 was related to the production of immunoglobulins, adaptive immune responses, immune regulation, and the transmission of immune cell signaling factors, etc (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF-I).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eThe expression of TTF2 in glioma is related to the level of immune infiltration\u003c/h2\u003e\u003cp\u003eConsidering that both KEGG and GSEA enrichment analyses found that TTF2 might be involved in the tumor immune response, we further used ssGSEA to analyze the relationship between TTF2 mRNA expression and the infiltration level of immune cells. The correlation between immune cell infiltration and TTF2 mRNA expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The results showed that the expression level of TTF2 mRNA was higher than that of Th2 Cells (R\u0026thinsp;=\u0026thinsp;0.595, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and macrophages (R\u0026thinsp;=\u0026thinsp;0.509, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001;) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-C), neutrophils (R\u0026thinsp;=\u0026thinsp;0.422, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) shows a positive correlation. Additionally, ssGSEA also indicates that the expression of TTF2 is negatively correlated with pDC (R=-0.455, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eTo verify the clinical characteristics and expression levels of TTF2 in glioma\u003c/h2\u003e\u003cp\u003eThe results showed that after dividing the samples into two groups with high and low expression of TTF2, the expression of TTF2 was inversely proportional to 1/19q (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The expression of TTF2 in mutant IDH was also lower than that in wild-type IDH (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). However, in terms of gender (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), there was no significant difference in the expression of TTF2. In those over 60 years old (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD), the expression of TTF2 was significantly increased. The expression of TTF2 was verified using brain tissue and glioma, and it was found that the expression in tumor tissue was significantly higher than that in normal tissue (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001;) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study found that TTF2 was significantly overexpressed in glioma. Functional enrichment analysis indicated that it was related to immunoglobulin complexes, signal receptor activation, receptor-ligand activity, cell recognition, etc. It was involved in multiple pathways and immune pathways such as cell adhesion, PI3K-AKT signaling pathway, AGE-RAGE signaling pathway, etc. And it increased the infiltration level of various immune cells. Therefore, our research has revealed the potential role of TTF2 in the pathogenesis of glioma and demonstrated its application prospects as a potential biomarker for glioma.\u003c/p\u003e\u003cp\u003eThis study found that TTF2 was significantly overexpressed in most tumors in the TCGA data. These results suggest that TTF2 has the potential to become a diagnostic marker for various cancers. Furthermore, we also found that TTF2 is related to clinical characteristics such as the pathological type of glioma, IDH mutation, 1P/19q coding status, and age, further supporting that the expression of TTF2 may be related to the malignancy degree of glioma. This study indicates that patients with high expression of TTF2 mRNA have a poorer OS and it is an independent prognostic factor for OS. This result was verified in the CGGA dataset. Considering that TTF2 is a strong prognostic factor, we combined TTF2 expression with clinical data to construct a chart that can predict the OS of TTF2 patients at 1 year, 3 years and 5 years. This chart can help screen high-risk patients and determine more aggressive treatment plans for high-risk glioma patients. Meanwhile, this study combined with tissue specimens verified that TTF2 was highly expressed in gliomas. This result is consistent with previous studies, which also found that the TTF2 protein is highly expressed in various types of cancer, including papillary thyroid carcinoma, colorectal adenocarcinoma and breast cancer, etc\u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTTF2 is the core regulatory factor of the transcription termination process mediated by RNA polymerase II. Its domain promotes chromatin unwinding and the dissociation of RNA-DNA heterozygotes by hydrolyzing ATP\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Some studies have shown that the protein level of the transcription termination-related factor TTF2 is regulated by APC/ C-mediated ubiquitin-proteasome in a cyclic-dependent manner\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Knockout of TTF2 activates the spindle assembly checkpoint (SAC), leading to chromosomal separation errors and cytoplasmic division failure. This may be a possible mechanism of TTF2 in tumors\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Our enrichment analysis and GSEA found that TTF2 may be involved in some immune pathways. ssGSEA also showed that TTF2 was positively correlated with the infiltration of Th2 cells, macrophages and neutrophils, but negatively correlated with the infiltration of pDC cells. It has been found in previous studies that Th2 cell infiltration is associated with Th2 cell immunosuppression and poor survival in various tumors. In this study, we found a significant increase in Th2 cells, suggesting that TTF2 may be involved in glioma-mediated immune escape. A similar situation also occurs on the tumor-associated antigen EpCAM, which promotes Th2 cell-mediated immune escape\u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Therefore, TTF2 has great value as a possible immunotherapy target in the future.\u003c/p\u003e\u003cp\u003eIn this study, although we have gained a deeper understanding of the relationship between TTF2 and glioma, there are still certain limitations. First of all, due to the lack of experience in both in vivo and in vitro experiments, we were unable to verify our results. Furthermore, due to the design limitations of our study, other key signaling pathways related to TTF2 may be omitted, which requires further research. To further study the mechanism of action of TTF2 in glioma, we need to conduct further cell and animal experiments.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTTF2 mRNA is overexpressed in glioma, and high TTF2 mRNA expression is OS-related. TTF2 is a potential biomarker for the diagnosis and prognosis of glioma and may be a potential target for immunotherapy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following publicly available datasets were analyzed in this study: TCGA, https://portal.gdc.cancer.gov; CGGA, http://www.cgga.org.cn;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the investigators, clinicians, technical personnel, and funding bodies who contributed to the TCGA, CGGA databases and made the information public. Without these data, the present study would not have been possible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Development Foundation Wuxi Municipal Bureau on Science and Technology (Grant No: N20201008).\u003c/p\u003e\n\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 Neurosurgery, Wuxi Clinical College of Anhui Medical University, 904th Hospital of Joint Logistic Support Force of PLA, Wuxi, China.\u003c/p\u003e\n\u003cp\u003eDongliang Shi,Hongqiao yang,Wei lin,Yuhai wang\u003c/p\u003e\n\u003cp\u003eDepartment of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China\u003c/p\u003e\n\u003cp\u003eFeng Chen,\u003c/p\u003e\n\u003cp\u003eDepartment of Neurosurgery, Affiliated Hospital 2 of Nantong University and First People’s Hospital of Nantong City, Nantong, China\u003c/p\u003e\n\u003cp\u003eZhenhua Chen\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch conception and design: Dongliang Shi, Data acquisition: Dongliang Shi, Feng Chen, Zhenhua Chen , Data analysis and interpretation: Dongliang Shi, Feng Chen, Zhenhua Chen Drafting of the manuscript: Dongliang Shi Hongqiao yang,Wei lin, Critical revision of the manuscript: Yuhai wang Approval of the final manuscript: Dongliang Shi, Feng Chen, Zhenhua Chen, Yuhai wang.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Yuhai wang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving humans were approved by the Ethics Committee of 904th Hospital of Joint Logistic Support Force of PLA ,Wuxi Clinical College of Anhui Medical University (Nos. LB-KY2025028). The studies were conducted in accordance with the local legislation and institutional requirements. The patients provided their written informed consent to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eConsent to publication was obtained by all the participants\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSaunders CN, et al. Lack of association between modifiable exposures and glioma risk: a Mendelian randomization analysis. Neuro Oncol. 2020;22:207\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi D, et al. (68)Ga-PRGD2 PET/CT in the evaluation of Glioma: a prospective study. Mol Pharm. 2014;11:3923\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAuffinger B, Ahmed AU, Lesniak MS. 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Cytokine. 2010;50:229\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi F, et al. Identification of ARGLU1 as a potential therapeutic target for gastric cancer based on genome-wide functional screening data. EBioMedicine. 2021;69:103436.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCan G et al. TTF2 promotes replisome eviction from stalled forks in mitosis. \u003cem\u003ebioRxiv\u003c/em\u003e 2024.\u003cdiv class=\"ExternalRefDOI\"\u003e11.30.626186\u003c/div\u003e (2024) doi:10.1101/2024.11.30.626186.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMan J, et al. Hypoxic Induction of Vasorin Regulates Notch1 Turnover to Maintain Glioma Stem-like Cells. Cell Stem Cell. 2018;22:104\u0026ndash;e1186.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKessler T, et al. Molecular differences in IDH wildtype glioblastoma according to MGMT promoter methylation. Neuro Oncol. 2018;20:367\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang J, et al. Disease-Causing Mutations in SF3B1 Alter Splicing by Disrupting Interaction with SUGP1. Mol Cell. 2019;76:82\u0026ndash;e957.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSaruwatari K, et al. Prognostic Factor Analysis in Patients With Small-Cell Lung Cancer Treated With Third-Line Chemotherapy. Clin Lung Cancer. 2016;17:581\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShi Q, et al. Forkhead box E1, frequently downregulted by promoter methylation, inhibits colorectal cancer cell growth and migration. Cancer Cell Int. 2024;24:169.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGr\u0026auml;nsmark E, et al. Real World Evidence on Second-Line Palliative Chemotherapy in Advanced Pancreatic Cancer. Front Oncol. 2020;10:1176.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark E, Gong E-Y, Romanelli MG, Lee K. Suppression of estrogen receptor-alpha transactivation by thyroid transcription factor-2 in breast cancer cells. Biochem Biophys Res Commun. 2012;421:532\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZheng X, et al. Construction and Analysis of the Tumor-Specific mRNA-miRNA-lncRNA Network in Gastric Cancer. Front Pharmacol. 2020;11:1112.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo J, Turek ME, Price DH. Regulation of RNA polymerase II termination by phosphorylation of Gdown1. J Biol Chem. 2014;289:12657\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu Y, et al. Mutual regulation between cell cycle and transcription termination factor TTF2. Sci China Life Sci. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11427-023-2538-2\u003c/span\u003e\u003cspan address=\"10.1007/s11427-023-2538-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZuo S, Wei M, Wang S, Dong J, Wei J. Pan-Cancer Analysis of Immune Cell Infiltration Identifies a Prognostic Immune-Cell Characteristic Score (ICCS) in Lung Adenocarcinoma. Front Immunol. 2020;11:1218.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChakravarthy A, et al. Pan-cancer deconvolution of tumour composition using DNA methylation. Nat Commun. 2018;9:3220.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee YH, Tai D, Yip C, Choo SP, Chew V. Combinational Immunotherapy for Hepatocellular Carcinoma: Radiotherapy, Immune Checkpoint Blockade and Beyond. Front Immunol. 2020;11:568759.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cdiv class=\"SimplePara\"\u003eBasic clinical baseline table of Glioma\u003c/div\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCharacteristics\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eLow expression of TTF2\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eHigh expression of TTF2\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003eP value\u003c/div\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003en\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e297\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e312\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eWHO grade, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eG2\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e169 (27.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e46 (7.6%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eG3\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e117 (19.2%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e125 (20.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eG4\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e11 (1.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e141 (23.2%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eIDH status, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eWT\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e30 (4.9%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e199 (32.7%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMut\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e267 (43.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e113 (18.6%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAge, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;= 60\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e262 (43%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e209 (34.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026gt;\u0026thinsp;60\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e35 (5.7%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e103 (16.9%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eOS event, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAlive\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e245 (40.2%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e125 (20.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eDead\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e52 (8.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e187 (30.7%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003e1p/19q codeletion, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNon-codel\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e167 (27.4%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e292 (47.9%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCodel\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e130 (21.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e20 (3.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eGender, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.497\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eFemale\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e128 (21%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e126 (20.7%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMale\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e169 (27.8%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e186 (30.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eRace, n (%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.183\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAsian\u0026amp;Black or African American\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e15 (2.5%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e24 (3.9%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eWhite\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e282 (46.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e288 (47.3%)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003cbr/\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cdiv class=\"SimplePara\"\u003eUnivariate and multivariate Cox regression analysis\u003c/div\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cdiv class=\"SimplePara\"\u003eCharacteristics\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cdiv class=\"SimplePara\"\u003eTotal(N)\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eUnivariate analysis\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eMultivariate analysis\u003c/div\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eHazard ratio (95% CI)\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003eP value\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eHazard ratio (95% CI)\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003eP value\u003c/div\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eWHO grade\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e636\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eG2\u0026amp;G3\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e468\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eG4\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e168\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e9.538 (7.243\u0026ndash;12.560)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e2.571 (1.795\u0026ndash;3.682)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eIDH status\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e688\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eWT\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e246\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMut\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e442\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.116 (0.089\u0026ndash;0.151)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.266 (0.179\u0026ndash;0.396)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAge\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e698\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026lt;= 60\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e555\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u0026gt;\u0026thinsp;60\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e143\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e4.696 (3.620\u0026ndash;6.093)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.489 (1.090\u0026ndash;2.035)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e0.012\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eGender\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e698\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eFemale\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e297\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMale\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e401\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.250 (0.979\u0026ndash;1.595)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.073\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.229 (0.937\u0026ndash;1.611)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.136\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003e1p/19q codeletion\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e691\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eNon-codel\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e520\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCodel\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e171\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.225 (0.147\u0026ndash;0.346)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.750 (0.448\u0026ndash;1.257)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.275\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eRace\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e685\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAsian\u0026amp;Black or African American\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e46\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eWhite\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e639\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.817 (0.499\u0026ndash;1.337)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.421\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eTTF2\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e698\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eLow\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e348\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eHigh\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003e350\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003e4.645 (3.494\u0026ndash;6.177)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.608 (1.113\u0026ndash;2.323)\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e0.011\u003c/span\u003e\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003cbr/\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO and KEGG enrichment analysis\u003c/div\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eOntology\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eID\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eDescription\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003eGeneRatio\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003eBgRatio\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003epvalue\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003ep.adjust\u003c/div\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eBP\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0009952\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eanterior/posterior pattern specification\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e39/581\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e214/18800\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e2.28e-19\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e7.15e-16\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eBP\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0007389\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003epattern specification process\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e57/581\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e463/18800\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e3.52e-19\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e7.15e-16\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eBP\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0048568\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eembryonic organ development\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e54/581\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e449/18800\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e9.2e-18\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.24e-14\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eBP\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0003002\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eregionalization\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e47/581\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e354/18800\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e2.72e-17\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e2.76e-14\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eBP\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0050853\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eB cell receptor signaling pathway\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e29/581\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e131/18800\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e4.28e-17\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e3.02e-14\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCC\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0019814\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eimmunoglobulin complex\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e48/599\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e167/19594\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e2.32e-33\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e8.82e-31\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCC\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0042571\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eimmunoglobulin complex, circulating\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e24/599\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e77/19594\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e3.39e-18\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e6.44e-16\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCC\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0009897\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eexternal side of plasma membrane\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e43/599\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e455/19594\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e5.8e-11\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e7.35e-09\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCC\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0062023\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003ecollagen-containing extracellular matrix\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e41/599\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e429/19594\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.17e-10\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.11e-08\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCC\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0072562\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eblood microparticle\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e21/599\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e147/19594\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e4.3e-09\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e3.26e-07\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMF\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0003823\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eantigen binding\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e44/570\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e174/18410\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e6.98e-28\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e4.21e-25\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eMF\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eGO:0034987\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eimmunoglobulin receptor binding\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e24/570\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e80/18410\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv 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class=\"SimplePara\"\u003ehsa05033\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eNicotine addiction\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e9/234\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e40/8164\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e1.41e-06\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.0001\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eKEGG\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003ehsa04060\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eCytokine-cytokine receptor interaction\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e24/234\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e295/8164\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e3.52e-06\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.0002\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eKEGG\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003ehsa05202\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cdiv class=\"SimplePara\"\u003eTranscriptional misregulation in cancer\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cdiv class=\"SimplePara\"\u003e18/234\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cdiv class=\"SimplePara\"\u003e193/8164\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cdiv class=\"SimplePara\"\u003e9.73e-06\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cdiv class=\"SimplePara\"\u003e0.0005\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003cbr/\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, TTF2, Prognosis, Biomarker, Biological Function","lastPublishedDoi":"10.21203/rs.3.rs-6821327/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6821327/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eGlioma is one of the common brain tumors in the central nervous system, with a poor prognosis and a serious threat to the life and health of patients. Exploring effective prognostic markers and conducting in-depth studies on related molecular mechanisms are of great significance for improving the prognosis of glioma patients. TTF2 (Transcription Termination Factor 2) has initially demonstrated its value as a potential prognostic factor in various cancers. However, its specific role in glioma remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Methods:\u003c/strong\u003e We evaluated the expression preference, prognostic value and clinical characteristics of TTF2 from the Tumor Genome Atlas (TCGA) database and the Chinese Glioma Genome Atlas (CGGA) dataset. We constructed clinical prognostic models using independent prognostic risk factors and TTF2, and evaluated the accuracy of the models using calibration curves. The biological functions of TTF2 were explored by GO/KEGG/GSEA enrichment analysis. The relationship between TTF2 expression and immune infiltration was analyzed by ssGSEA (Single Sample Gene Set Enrichment Analysis), and the expression of TTF2 mRNA in glioma samples was verified by tissue specimens.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult: \u003c/strong\u003eTTF2 was highly expressed in glioma. Multivariate analysis showed that TTF2 mRNA expression was an independent prognostic factor for Overall survival rate (OS) (HR = 2.113, 95%CI:1.393-3.204). Effective prognostic models can be constructed by using WHO classification, IDH status, age and the expression level of TTF2. Enrichment analysis and GSEA analysis showed that the expression of TTF2 was related to the production of immunoglobulins, adaptive immune responses, immune regulation, and the transmission of immune cell signaling factors, etc. ssGSEA showed that the expression of TTF2 was positively correlated with the infiltration level of Th2 cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eTTF2 is expressed in glioma and is associated with OS. TTF2 is a potential biomarker for the diagnosis and prognosis of glioma and may be a potential target for immunotherapy.\u003c/p\u003e","manuscriptTitle":"TTF2 as a Potential Biomarker and Immunotherapy Target in Glioma Diagnosis and Prognosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 12:46:24","doi":"10.21203/rs.3.rs-6821327/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":"5286e5dc-5dce-428c-8334-1ef471eba7b6","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-31T03:23:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-18 12:46:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6821327","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6821327","identity":"rs-6821327","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}