Comprehensive Analysis to Identify the Vasohibin1 (VASH1) Emerges as a Novel Prognosis Biomarker in High-Risk Low-Grade Glioma

Yirizhati aili The First A liated Hospital of Xinjiang Medical University Aierpati maimaiti The First A liated Hospital of Xinjiang Medical University Nuersimanguli maimaitiming The First A liated Hospital of Xinjiang Medical University Hu qin The First A liated Hospital of Xinjiang Medical University Wenyu Ji The First A liated Hospital of Xinjiang Medical University Yusufu mahemuti The First A liated Hospital of Xinjiang Medical University Wen liu The First A liated Hospital of Xinjiang Medical University Yongxin wang The First A liated Hospital of Xinjiang Medical University Zengliang Wang (  wzl3ng@126.com ) The First A liated Hospital of Xinjiang Medical University


Introduction
Low-grade G1ioma (LGG) is a common primary intracranial tumor. There is huge heterogeneity among patients with different low-grade gliomas, which results in some low-grade gliomas often progressing to high-grade Glioma, and the prognosis is very poor. More aggressive interventions are needed [1]. Although many attempts have been made on risk strati cation of glioma based on many clinical characteristics, accurate risk strati cation and prediction for patients with low-grade glioma are still not possible [2].
Large-scale genomic studies in recent years have shown that the heterogeneity of glioma extends to a deeper molecular level, and it is di cult to accurately serialize the risk of glioma from the macro clinical characteristics, so we need to explore the risk strati cation of low-grade glioma from the heterogeneity of molecular level [3]. In recent years, researchers have discovered some promising biomarkers, some emerging markers include isocitrate dehydrogenase (IDH) mutations, co-deletion of 1p and 19q in chromosome arms (1p/19q codeletion), And 0-6 methylguanine-DNA methyltransferase (MGMT) methylation status have been included in 2021 WHO glioma classi cation to clarify its biological characteristics and guide treatment [4]. However, these widely used biomarkers do not fully accurately elucidate individual variation, and the exploration of glioma risk strati cation at the molecular level needs to continue.
As is known to all, LGG patients in good physical condition can obtain a good prognosis after surgery or radiotherapy and chemotherapy, and 50-75% of patients die due to progression and deterioration, so we believe that the characteristics of tumor invasion and metastasis become a key factor affecting the prognosis of patients [5]. VASH1, as a newly discovered angiogenic inhibitor, has been found to play an important biological role in the development and progression of various tumors. VASH1 belongs to a class of angiogenesis regulatory proteins in the angiogenesis inhibitor family, which can inhibit the proliferation of vascular endothelial cells and the formation of neovascularization network and is the rst discovered endothelium-derived factor that negatively regulates angiogenesis [6].VASH1 can be selectively expressed not only in endothelial cells, but also in tumor cells and some immune cells, directly inhibiting the migration, proliferation, endothelial net and promoting apoptosis of endothelial cells, and indirectly inhibiting angiogenesis through negative feedback regulation of vascular endothelial growth factor(VEGF) [7].In addition, according to literature reports, VASH1 can also enhance stress resistance of endothelial cells by inducing the expressions of superoxide dismutase2 (SOD2) and sirtuin1 (SIRT1) [8].
With the continuous progress of research on VASH1, more and more scholars at home and abroad have developed the special biological characteristics of VASH1 and applied them to clinical treatment as a tumor target. At present, much literature has discussed the clinical role of VASH1 in gastric cancer [9], ovarian cancer [10], colorectal cancer [11], esophageal cancer [12], prostate cancer [13], and non-small cell lung cancer [14]. There are few reports on the role of VASH1 in LGG. Further studies on the molecular mechanism of VASH1 affecting the genesis and development of LGG will help to identify molecular targets for tumor therapy and provide clues for the development of new and more powerful anti-tumor tools.
In the present study, we rst discovered that VASH1 mRNA expression was up-regulated in LGG samples in the TCGA databases. We used TIMER and ESTIMATE to further understand the correlation between VASH1 and in ltrating immune cells in LGG. In addition, we conducted GO and KEGG pathway enrichment analysis on genes related to VASH1 expression in LGG through GSEA, to determine the potential mechanism of VASH1 in the occurrence and development of LGG. Therefore, in our follow-up study, the expression of VASH1 in our cohort study was determined by immunohistochemistry, and a clinical prediction model was constructed. Finally, VASH1 was tested in vitro. Our study provides a new therapeutic target and Prognostic method for patients with LGG.

Method And Materials
Data collection and preprocessing From the cancer genome atlas (TCGA) database (https://portal.gdc.cancer.gov/) and genotypeorganization express project (GTEx) database (https://gtexportal.org/) download 33 kinds of tumor gene expression data and normal tissue and tumor tissue Clinical information. Transcriptome (fragments per kilobase million, FPKM), somatic mutation data, copy number variation (CNV), and clinical phenotype data for LGG were downloaded from the TCGA database. Corresponding to heavy annotation in gene chip RNA probe, we download the appropriate RNA genome sequence information and data from the GENECODE database (https://www.gencodegenes.org/human/). The RNA expression pro le of the reannotated microarray was constructed by matching the sequence information of the probe with that of RNA. The human genome annotation le (GRCh38/hg38) from the UCSC database (http://hgdownload.cse.ucsc.edu/) to download. In addition, the department of cancer cells encyclopedia (CCLE) database downloaded 21 tumor cell lines (such as breast, thyroid, and uterine) information (https://portals.broadinstitute.org/). Finally, based on the FTO expression levels of 33 cancers, univariate survival analysis was used to study the prognosis of patients in terms of overall survival (OS) and disease-speci c survival (DSS). Kaplan-Meier curves and forest maps were visualized for cancer with signi cant statistical differences.
Correlation between tumor immune cell in ltration and VASH1 gene expression Tumor immune to assess resource (TIMER, https://cistrome.shinyapps.io/timer/) is a comprehensive database, can be systematically analyzed of various types of cancer of the immune in ltrating [15]. Spearman correlation was used to estimate the correlation between VASH1 expression and levels of 47 immune checkpoint genes in tumor immune in ltrating cells (CD4 + T cells, B cells, CD8 + T cells, macrophages, neutrophils, and dendritic cells) in 33 cancers. In addition, association analysis of VASH1 with stroma scores for multiple cancers was evaluated by software estimation. At the same time, the relationship between gene expression and immune score was analyzed in 33 tumor samples using the R package ESTIMATE. Secondly, TMB is de ned as the total number of somatic gene coding mutations existing in tumor tissues, such as deletion errors or gene insertions [16]. MSI refers to a strongly mutated phenotype caused by loss of DNA mismatch repair activity [17]. Both TMB and MSI are potential predictive biomarkers of immune checkpoint therapy. We extracted TMB and MSI data from the TCGA database. Spearman analysis was used to estimate the correlation between VASH1 expression level and TMB or MSI status.

VASH1-related gene enrichment analysis
We rst searched the STRING (https://string-db.org/)[18] and GeneMANIA (https://genemania.org/) [19] website using the query of a single protein name ("VASH1") and organism ("Homo sapiens"). Subsequently, we set the following main parameters: minimum required interaction score ["Low con dence (0.150)"], meaning of network edges ("evidence"), max number of interactors to show ("no more than 50 interactors" in 1st shell) and active interaction sources ("experiments"). Finally, the available experimentally determined VASH1-binding proteins were obtained Gene Oncology (GO) Annotation and KEGG Pathway Enrichment Analysis Differentially expressed genes (DEGs) between two groups were screened by using the "DESeq2" package in R software according to the thresholds of |log2FoldChange| > 1 and adjusted p< 0.05. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to annotate the biological functions of DEGs and VASH1-related genes through "clusterPro ler" package.
With the annotated gene sets in "h.all.v7.4.symbols.gmt" chosen as the reference gene sets, gene set enrichment analysis (GSEA) was conducted to investigate the potential regulatory mechanisms of VASH1.
External Validation of genes in the VASH1 mRNA risk score Model The feature model genes were veri ed by CGGA mRNA seq-693 and CGGA mRNA seq-325 in The Chinese Glioma Genome Atlas (CGGA) database and GSE16011 in the Gene Expression Summary Database (GEO). The same formula was used to calculate the risk score, and Boxplot was used to compare the gene expression of different genders, tumor stage ( and ), tumor types (primary and recurrent), and VASH1 expression status.

Management of tissue specimens
All LGG patients and tissue samples involved in this study were from the neurosurgery sample bank of the First A liated Hospital of Xinjiang Medical University. 204 cases of intracranial tumor resection in the First A liated Hospital of Xinjiang Medical University from January 2013 to December 2019 were randomly selected. Excluding meningioma, patients who received preoperative chemoradiotherapy, and patients with incomplete follow-up information, the remaining 94 LGG, and 68 GBM patients underwent para n-embedded surgical tissue samples for immunohistochemical staining. Postoperative intracranial tumors were independently diagnosed as low-grade glioma (grade (12 cases), grade (52 cases), and grade (31 cases)) and high-grade glioma (grade (68 cases) by 2 pathologists according to WHO grading standards. Basic clinical data and standard clinical follow-up of 94 patients were included. The follow-up period of the study was up to the end of December 2020. In addition, we also collected 16 fresh pathological specimens and adjacent normal brain tissue samples from 8 LGG patients who underwent surgical treatment in the First A liated Hospital of Xinjiang Medical University from January 2021 to September 2021 for PCR detection. The medical Research Ethics Committee of the First A liated Hospital of Xinjiang Medical University approved the study. According to the Declaration of Helsinki, the samples and case data used in this study were approved by the Ethics Committee of the First A liated Hospital of Xinjiang Medical University.
The expression of VASH1 was detected by immunohistochemistry Immunohistochemical analysis, LGG pathological tissue was embedded in para n and sectioned on a 4μm microtome. Slices were placed on slides and dehydrated with different concentrations of alcohol solutions (75%, 80%, 90%, 95%, 100%) at different times and cleaned with xylene. A two-step indirect immunohistochemical staining was used in this study. Rabbit antibodies against human VASH1 (Abcam, United Kingdom) were diluted to 1:200 and 1:250, respectively. Antibody staining was performed overnight at 4℃. The reaction of 3,3'-Diaminobenzoaniline (DAB) substrate-chromogen with peroxidaseconjugated secondary antibody was used to x para n-embedded tissue sections with formalin. DAB can react with the slices to produce brown products insoluble in ethanol and xylene at the antigen site. The sections were rinsed with phosphate buffer solution 3 times, and then the expression of target proteins in the tissues was observed with a light microscope at 200 times magni cation. Five high-power elds were randomly selected, 500 cells were counted, and the percentage of immunohistochemical cells in the total number of cells was calculated. The percentage≥50% was the high expression, and <50% was the low expression. According to the expression level of VASH1, the cells were divided into a high expression group of VASH1 and a low expression group of VASH1. Finally, we divided LGG patients into high expression groups and low expression groups according to the median value of VASH1 as the risk cutoff point. The Kaplan-Meier method was used to draw survival curves of the two groups to predict their prognostic signi cance in OS and DFS, and P<0.05 indicated a signi cant statistical difference.

Construction and validation of gene prognostic nomogram
To test whether VASH1 is a prognostic risk factor independent of other clinicopathological features, we performed univariate and multivariate Cox regression analyses using R software for each variable in our 94 LGG cohort. Statistical signi cance was set at P<0.05. Will the single factor and multiple factors Cox proportional hazards regression analysis of all independent prognostic parameters build a composite nomogram, according to the characteristics of the different variables to draw a straight and level to determine the points of each variable, by taking the point of all variables to calculate the sum of the total points of each patient, and the distribution of its normalization to 0 to 100. The OS values of patients with low-grade glioma at 3 years were calculated between the total score and each prognostic axis. We used the "rms" R software package to draw calibration diagrams to verify the performance of the row diagram in the 94 LGG queues we were able to collect. In addition, we plotted tROC curves to assess the predictive accuracy of independent prognostic parameters using the R package "survivalROC".
Cell line and cell culture All cell lines including U-87, U-251, and A-172 were purchased from the Cell Bank of Chinese Academy of Sciences (China). All cell lines were cultured in DMEM medium with 10% newborn bovine serum, supplemented with penicillin 100u/mL and streptomycin 100μg/mL, in a 5% C02 incubator with saturated humidity and 37℃ constant temperature.

RNA Extraction and qRT-PCR
Total RNA was extracted from tissues and cells according to TRIzol reagent instructions, and cDNA reverse transcription was performed according to the instructions of the RT-PCR kit (Invitrogen, United States). GAPDH and VASH1 expression levels were detected by qRT-PCR using SYBR Green qPCR Master Mix (High ROX) (Servicebio, Wuhan, China). Results The expression level of GAPDH was taken as standard. Results The expression level of GAPDH was taken as standard. The PCR primer sequence was designed and synthesized by Servicebio (Wuhan). GAPDH-F:5′-GGAAGCTTGTCATCAATGGAAATC-3′, GAPDH-R:5′-TGATGACCCTTTTGGCTCCC-3′, VASH1-F:5′-GTTTGGAGACCAGCGAAGGAA-3′, VASH1-R:5′-ACAGGTGTAGACGGCTGGAAC-3′, The relative expression levels of VASH1 were quantitatively calculated by the 2 (−ΔΔCT) method. The ampli cation reaction included the following steps: Pre-denaturation at 95°C for 10 min, denaturation at 95°C for 15 s over 40 cycles, and extension at 60℃ for 30 s. From 65℃ to 95℃, the uorescence signal was collected every 0.3℃.

Western-Blot
Collecting cells, cell lysis solution treatment, the supernatant, centrifuge after Coomassie brilliant blue method to determine protein concentration, polypropylene phthalic amide gel electrophoresis, The protein electricity is transferred to the nitrate ber membrane, combined with VASH1 antibody (1:10 dilution degrees 00, Abcam), combined with horseradish peroxide enzyme after two combinations, ECL method after color photograph. Finally, the gray values of each band were determined by Image-Pro Plus 4.5 Image analysis system to re ect the expression level of VASH1 protein.

Construction and transfection of lentivirus
The relevant information of the VASH1 gene was searched through the Genbank database, and the online design software of Ambion was applied to select the human VASH1 gene (gene serial number: The sequence of siRNA was 5 '-CGACCGGaAGaAGGATGTTTC-3' at 1307-1331 of cDNA. BLAST search con rmed no homology with known human gene sequences other than VASH1. DNA Oligo of VASH1 shRNA was designed and synthesized, double-stranded DNA was formed by annealing, HpaI and EcoRI were digested and ligated, and transformed into PGCL-GFP expression plasmid of Ecoli DH5a. Recombinant positive clones were selected for PCR and sent for sequencing identi cation (Shanghai genechem Technology). 293T cells were co-transfected with pgCL-GFP vector 20μg, pHelper 1.0 vector 15μg, pHelper 2.0 vector 10μg. 8h after transfection, the cells were replaced with a complete culture medium. After 48 h of culture, cell supernatant rich in lentivirus particles was collected and -80% was stored for future use.

Transwell assay
Transwell cell was placed in a 24-well plate, the substrate glue was added to the Transwell cell, and the complete culture medium was added to the substrate. After digestion and resuspension, the cells of each group were inoculated in the upper chamber of Transwell, and the number of cells was 3×104. After 48 h culture, the cells that did not invade the subchamber were washed away. Then it was xed with 4% polymethanol and stained with 0.1% crystal violet for 20 min. The number of cells invading the subcompartment in each eld was counted under an inverted microscope.

Wound-healing assay
The cells in each group were digested by trypsin and inoculated into 6-well plates with 1×106 cells in each well. Then the cells were cultured at 37℃, 5% CO2, and 100% relative humidity until the cells reached about 90% con uence. Then make scratches from top to bottom with 200μL pipette tip and wash away the scratched cells with PBS buffer. Then the culture was continued for 24 h under the same conditions. The single-layer images were observed by an inverted microscope, and the migration ability of cells was analyzed by measuring the movement distance of the cell front and the width of the scratch.

Statistical Analysis
All bioinformatics and clinical characters analyses were performed in R version 4.0.3, and all experimental data analysis was carried out in GraphPad Prism 9. The signi cance of the differences between the groups was assessed by the Student`s t-test. The Chi-square test or Fisher test was used for categorical variables, and the Wilcoxon test was used for continuous data. Survival differences were calculated using K-M and logarithmic rank tests. In addition, the use of interactive gene expression pro le analysis GEPIA2 (http://gepia2.cancer-pku.cn/) and UALCAN (http://ualcan.path.uab.edu/index.html), Different expression analyses were further performed on LGG samples from TCGA and normal samples from matched TCGA normal and genotype-tissue expression (GTEx) data. P<0.05 was statistically signi cant.

Expression and Prognostic Potential of FTO Was Altered in Human Pan-Cancer
First, we used AVSH1 expression levels in cancer and normal tissue samples from the TCGA database. Given the limited number of normal samples in the TCGA database, we integrated the expression of VASH1 in cancer and normal tissue samples from the GTEx and TCGA databases and found that  (Table.1). Meanwhile, we used the CCLE database to calculate VASH1 expression in different tumor cell lines. The results showed that VASH1 showed different expression levels in different tumor cell lines (Fig.1B). In short, the present results suggest that VASH1 is expressed differentially in multiple cancers. To explore the relationship between VASH1 and clinical outcomes in 33 cancer patients, a univariate analysis was performed using the TCGA dataset. Forest map showed that VASH1 had signi cant effects on OS and DSS of speci c tumor types in 33 cancers evaluated (Fig1C,1D), where KIRC, LGG, there were signi cant statistical differences in PAAD and LIHC cancers (P<0.05), and the results were visualized using Venny diagram ( Supplementary Fig.1).
Secondly, Kaplan-Meier survival analysis was performed for the four selected cancers, and the results showed that high expression of VASH1 indicated a good correlation between KIRC and OS in PAAD (P<0.001). The high expression of VASH1 was signi cantly correlated with bad OS in LGG (P=0.015) and LIHC (P<0.001) (Fig.1E). Next, we found that high expression of VASH1 signi cantly prolonged DSS in KIRC (P<0.0001), while high expression of VASH1 was signi cantly correlated with shorter DSS of LGG (P=0.016), LIHC (P=0.024), and PAAD (P=0.013) (Fig.1F). Overall, these results suggest that VASH1 expression is signi cantly associated with patient prognosis, especially in patients with KIRC, LGG, LIHC, and PAAD.

VASH1 Was Associated with Tumor Immune In ltration, Immune Checkpoint Biomarkers, and TMB in Multiple Cancers
Based on the TIMER database, we analyzed the immune cell in ltration levels of the four cancers (KIRC, LGG, PAAD, and LIHC) screened above, As shown in Figure 2A. Therefore, we explored whether VASH1 expression is associated with the level of immune invasion in these four cancers. We found that the expression level of VASH1 was signi cantly correlated with the degree of immune in ltrating cells in KIRC, LGG, PAAD, and LIHC, ranking LGG, KIRC, LIHC, and PAAD in sequence (Fig.2B). In addition, we used R package estimation to assess the stroma score for each tumor sample. VASH1 expression was positively correlated with matrix score for LGG (R= 0.165, P <0.020), LIHC (R=0.03, P=0.637) and KIRC (R= 0.027, P=0.596) (FI.2C).
Since immunotherapy is a key therapy for tumor reduction and eradication, the relationship between VASH1 expression and 47 immune checkpoint gene expression was further analyzed. Interestingly, the analysis showed that VASH1 expression was positively correlated with immune checkpoint genes common in a variety of cancers, especially in LGG (Fig.2D). VASH1 is important for the complex pattern of modulating tumor immune responses by modulating immune checkpoint genes. In addition, tumor cells with high TMB have high levels of neoantigens, which are thought to stimulate the anti-tumor response of lymphocytes and help the immune system recognize tumors. Our analysis showed that VASH1 expression was positively correlated with TMB in LGG, THYM, UCEC, BLCA, BRCA, CESC, COAD, LUAD, LUSC, SKCM, and STAD. In contrast, VASH1 expression was negatively correlated with PRAD and THCA (Fig.2E). Taken together, our study suggests that VASH1 may play an important role in tumor immune response.
We used R software (Version 3.6.4) to calculate the expression differences of the VASH1 gene in the genome and non-mutant samples in each tumor, and Wilcoxon Rank and Signed Rank Tests were used for signi cance analysis of the differences. We found that there were signi cant expression differences in GBM-LGG, LGG, KIPAN, MESO, and SKCM samples (Fig.3A). Combined with the above analysis, we believed that VASH1 expression level was closely correlated with LGG. At present, immune checkpoint blocking (ICB) therapy has been applied in a variety of tumor diseases, improving the overall survival rate of patients. Many studies have shown that this tumor mutation load (TMB) can be used to predict the e cacy of ICB, and it has become a biomarker for various cancer types to identify patients who will bene t from immunotherapy. Based on the clinical signi cance of TMB in immunotherapy, we further explored the internal relationship between TMB and VASH1 expression to clarify the genetic information related to VASH1. Correlation analysis showed that TMB was positively correlated with VASH1 (R=0.095, P=0.035, Fig.3B). We found the optimal threshold through the "SurvMiner" R package and divided the patients into the high group and low group, and conducted a box plot (P=0.008, Fig.3C). The expression levels of TMB and VASH1 in patients were combined for analysis. The results showed that patients with high VASH1 and high TMB had the worst prognosis, while patients with low VASH1 expression and low TMB had the best prognosis (P <0.001, Fig.3D).
We obtained the LGG driver gene and evaluated somatic mutations in VASH1 patients with different expression levels. Fig.3E and 3F respectively showed the mutation distribution of the 20 driver genes with the highest change frequency in the high and low VASH1 groups. These results may provide new directions for the study of immunotherapy mechanisms, gene mutations, and molecular mechanisms of VASH1 in LGG.
The Aberrant Expression and Prognostic Value of VASH1 in LGG Patients miRNA expression levels in RNA-seq data and corresponding clinical data from 510 LGG samples obtained from TCGA. To explore the prognostic signi cance of VASH1 in LGG patients, we divided LGG patients into high VASH1 high expression group and low VASH1 low expression group based on the optimal cutoff point calculation of the expression group through "Survival" and "SurvMiner" software package. VASH1 expression distribution and survival status of LGG are shown in FIG. 4A. In addition, we veri ed online GPEIA and UALCAN data and found that VASH1 expression was signi cantly different in LGG (n=518) patients compared to normal tissue (n=207) (Fig.4B, 4C). At the same time, k-M survival analysis was performed, and the results showed that high expression of VASH1 in GPEIA and UALCAN was associated with poor prognosis. Further above results were obtained (Fig.4D, 4E). Finally, we analyzed the correlation between clinical prognostic factors and VASH1 expression levels at different time points of LGG patients by ROC and tROC curves, and the results showed that VASH1 expression had a certain predictive ability, and LGG patients with high VASH1 expression had poor clinical prognosis in 3year OS (Fig.4F, 4H). In conclusion, VASH1 may be a potential prognostic biomarker for LGG patients.
The biological function of VASH1 in LGG To further explore the potential function of VASH1 in PATIENTS with LGG, differentially expressed genes were analyzed between the groups with high VASH1 expression and low VASH2 expression. The most important GO terms for biological processes (BP), cellular composition (CC), and molecular function (MF), as well as KEGG pathways, were analyzed to reveal the underlying biological function of differentially expressed genes, and the top 30 signi cant GO terms were selected. It is mainly involved in potassium channel activity, DNA binding, cholesterol biosynthetic process, and labyrinthine Layer blood vessel Development, Negative regulation of Blood Vessel Endothelial cell migration and stabilization of membrane Potential are related to angiogenesis regulation, cholesterol metabolism, and microtubule formation (Fig.5A). Meanwhile, KEGG pathway analysis showed that the Cholesterol metabolism and Folate biosynthesis pathways of VASH1 were mainly involved (Fig.5B). These signaling pathways are related to core biological carcinogenic processes, most of which involve the regulation of carcinogenic activation pathways, cell cycle, angiogenesis, and immune cell in ltration. Then, we constructed different protein and gene co-expression networks associated with VASH1 expression through the String and GeneMANIA online databases (Fig.5C, 5D). In addition, to further explore the correlation between VASH1 expression level and prognosis of LGG, Through GSEA, we found that VASH1 expression was closely related to Glioma, ECM-receptor-interaction, Cell Cycle, TGF-β, P53, and Notch signaling pathways (Fig.5E). This may provide a new molecular mechanism for exploring the genesis and development of LGG.
Veri cation of the VASH1 in two external independent LGG datasets To cross-platform validation of VASH1 expression level and clinical prognosis of LGG in other independent data sets from different platforms, VASH1 was covered by CGGA mRNA seq-693 and CGGA mRNA seq-325, with a large sample size and common clinicopathological features. Therefore, we selected CGGA mRNA seq-693 and CGGA mRNA seq-325 data to study the correlation between VASH1 expression level and gender, age, WHO grade, chemotherapy status, IDH status, 1p/19q chromosome codeletion, and tumor type of LGG patients. In the CGGA mRNA seq-693 dataset VASH1 was signi cantly correlated with gender and tumor type (P<0.05) (Fig6A,6B). In addition, the correlation with these indicators was also observed in VASH1 in the CGGA mRNA seq-325 dataset. The results showed that VASH1 was closely correlated with WHO grade in low-grade gliomas (P<0.05) (Fig.6C). At the same time, survival analysis was performed on LGG patients with complete clinical data from CGGA mRNA seq-693 and CGGA mRNA seq-325 data sets respectively, and the results showed that VASH1 expression was signi cantly correlated with the prognosis of LGG patients, that is, high VASH1 expression was correlated with poor prognosis (HR=1.39, P=0.04, HR=1.42, P=0.02) (Fig.6D,6E). This result further con rms our above results. Experimental results con rmed that the expression level of VASH1 in LGG tissues was signi cantly higher than that in normal tissues Then, 94 cases of LGG and 68 cases of GBM hospitalized in the Neurosurgery Department of the First A liated Hospital of Xinjiang Medical University from January 2014 to December 2019 were collected for postoperative para n specimens for pathological sections, and the expression of VASH1 in tumor tissues and adjacent normal tissues was detected by immunohistochemistry. According to the observation of two pathologists (with unknown patient information), immunohistochemical results showed that VASH1 protein was mainly expressed in the nucleus and cytoplasm of glioma cells and endothelial cells and showed brown positive expression (Fig.7A). At the same time, most of VASH1 was positively expressed in LGG tissues (57/94,60.6%), and the expression level was statistically signi cant (P<0.05) compared with normal adjacent tissues and GBM tissues (Fig.7B). Subsequently, to continue to explore the expression of VASH1 in freshly frozen LGG tissues and adjacent tissues, we randomly selected 8 patients who underwent glioma resection in the First A liated Hospital of Xinjiang Medical University from January 2021 to September 2021 and considered that LGG tissues and corresponding adjacent normal tissues after surgery were taken. Total RNA proteins were extracted from tumor tissues and normal tissues, and the relative expression level of VASH1 mRNA was detected by real-time PCR, and the relative expression level of VASH1 was calculated by the deta CT method. The results showed that the expression of VASH1 mRNA in LGG in most specimens was signi cantly higher than that in the corresponding normal brain tissue (P<0.01) (Fig.7C,7D).

Relationship between VASH1 expression and pathological parameters and prognosis of LGG patients
First, according to the expression level of VASH1, we analyzed the clinicopathological parameters and prognostic factors of 94 LGG patients in our hospital and found that there was no statistically signi cant difference in age, gender, histology, tumor size, location, and KPS score between the two groups. However, tumor recurrence, WHO grade, epilepsy, and IDH1 wild type were signi cantly correlated with VASH1 expression (P<0.05) ( Table.2). We found that VASH1 expression was closely related to the grade of LGG malignancy and tumor recurrence, so does VASH1 expression affect the prognosis of LGG patients? In this regard, we systematically followed up the postoperative prognosis of each LGG patient and analyzed the overall survival rate (OS) and Disease-Free Survival (DFS) of the patient according to our follow-up results. The results showed that the 3-year OS and DFS of patients with high VASH1 expression group were signi cantly lower than those of patients with low VASH1 expression (P<0.05). Then, the K-M survival curve was drawn based on overall survival time and disease-free survival time, and the log-rank test was used to analyze the differences between the two groups. The results showed that the survival time of patients with a high VASH1 expression group was signi cantly lower than that of patients with a low VASH1 expression group (P=0.0352) (Fig.7E). The disease-free survival time of patients with a high VASH1 expression group was signi cantly lower than that of patients with a high VASH1 expression group (P=0.0071) (Fig.7F). This Nomogram should be established to predict the prognosis of LGG for high VASH1 expression Pathological features and VASH1 expression affecting the prognosis of LGG patients were included in Cox proportional risk regression models for univariate and multivariate regression analyses, respectively.
Univariate results are shown in Figure 8A. For LGG patients, tumor recurrence (HR=3.70, P<0.001), WHO grade (HR=2.81, P<0.001) and high VASH1 expression (HR=1.54, P=0.03) are the single prognostic risk factors for OS (Table.3). Further multi-factor analysis shows that: Tumor recurrence (HR=3.47, P<0.001), WHO grade (HR=3.13, P<0.001), and high VASH1 expression (HR=1.65, P=0.02) were independent risk factors for OS in LGG patients (Fig.8B). There was no correlation between age, gender, and IDH1 type and prognosis of LGG (Table.3). In addition, a Nomogram model for LGG patients with age, gender, tumor type, WHO grade, IDH1 type, and VASH1 expression was established using R software based on relevant research results at home and abroad. By constructing nomograms, the prognostic factors can be applied clinically to predict the 3-year survival rate of patients (Fig.8C). The calibration diagram (Fig.8D) shows that the topograph has a good prediction effect. Compared with the risk scoring model, the prediction performance of the line chart is signi cantly improved. Finally, according to the expression of VASH1 in 94 LGG patients, we conducted ROC curve analysis with time changes for 3 years and obtained AUC values of 0.82 (95%CI: 0.93-0.72) (Fig.8E). Therefore, it is believed that the high expression of VASH1 provides a new risk molecular strati cation for the diagnosis of high-risk LGG.
Human glioma cell lines with VASH1 knockdown were constructed To further understand the effect of VASH1 expression on the biological behavior of LGG, we constructed glioma cell lines with VASH1 knockdown for functional experiments. Firstly, we used real-time PCR and Western-blot to detect the expression of VASH1 mRNA and protein in common human glioma cell lines (A-172, U-251, and U-87) and found that the expression of VASH1 mRNA and protein was the highest in the U-251 cell line. Therefore, we planned to select U-251 cells to knock down VASH1 for subsequent VASH1 expression and function experiments (Fig.9A,9B,9C). In this experiment, VASH1 short hairpin RNA designed by genechem (Shang Hai) and control nonfunctional shRNA plasmid lentivirus were transfected into U-251 cells to construct U-251 Si-Vash1 , U-251 Si-NC , and their control cell line U-251 Normal . In order to determine the expression of VASH1 after infection, the mRNA and protein expression of VASH1 in U-251 Si-VASH1 cells were detected by real-time PCR and Western-blot, and the results con rmed that the mRNA and protein expression of VASH1 in U-251 Si-VASH1 cells were signi cantly decreased compared with the control group and normal U-251 cell line. The difference was statistically signi cant (P<0.05) (Fig.9E,9F,9G). The above experiments con rmed that the interference effect of the designed knockout plasmid was satisfactory, so we carried out subsequent functional experiments on U-251 Si-VASH1 , U-251 Si-NC , and U-251 Normal cell lines.

Effects of VASH1 on migration and invasion of U-251 cells
The invasion and migration ability of tumor cells is a key characteristic affecting tumor invasion and recurrence, and current studies have shown that the high expression of VASH1 is signi cantly correlated with LGG WHO grade and recurrence. Therefore, we further studied the effect of VASH1 on the migration and invasion ability of glioma cells through in vitro experiments. First, we used a scratch test to detect the migration ability of abnormal VASH1 expression to U-251 cells. The results showed that u-251 Si-VASH1 , U-251 Si-NC , and U-251 Normal cells were scratched 48 hours after VASH1 expression was interfered with by monolayers fusion. The speed of scratch healing in U-251 Si-VASH1 was signi cantly faster than that in U-251 Si-NC and U-251 Normal cell groups (P<0.01) (Fig.9H,9I). Then, we carried out the Tranwell invasion experiment on the above three groups of cell lines. U-251 Si-VASH1 , U-251 Si-NC , and U-251 Normal cells were inoculated in the upper chamber of the Transwell chamber, and a complete medium was added in the lower chamber. After 12-24h incubation, It was observed that the number of cells passing through the bottom of the Transwell chamber in U-251 Si-VASH1 cells was signi cantly higher than that in the other two groups (P<0.001), while there was no signi cant difference between U-251 Si-NC and U-251 Normal cells (P>0.05) (Fig.9J, 9K).

Discussion
Glioma is the most common intracranial primary tumor, accounting for 81% of central nervous system malignancies. Low-grade glioma (LGG) is a group of heterogeneous tumors, accounting for nearly 20% of all primary brain tumors, and median overall survival (median overall survival, mOS) (5.6 ~ 13.3) years [20]. Although surgery, radiotherapy, and chemotherapy are the main treatment modalities for LGG, the optimal combination therapy for a speci c patient has not been determined based on individual symptoms and the risk of toxicity caused by treatment [21]. Although a number of clinical trials have shown that high-risk LGG shows positive effects in postoperative radiotherapy and chemotherapy, there are still many debates [22]. Although risk strati cation for high-risk LGG has been carried out clinically and molecularly, various strati cation standards have their advantages and disadvantages, and their role in the prognosis of LGG is still controversial [23]. In this study, we further explored the prognostic factors of LGG patients. We rst found through TCGA, GTEx, CCLE, GENECODE single-cell RNA-seq datasets, and our cohort that VASH1 expression was signi cantly up-regulated in LGG tumor tissues compared with normal tissues. Further Cox proportional risk regression model showed that VASH1 expression level had an independent prognostic value for LGG. The results con rmed the correlation between VASH1 expression level and the progression and prognosis of LGG.
At present, a large number of studies have con rmed that VASH1 expression level is correlated with the prognosis of various solid tumors. Yan et al. [24] reported A positive correlation between VASH1 expression level and VEGF-A and microvascular density (MVD) in colon cancer tissues. VASH1 expression was signi cantly positively correlated with pathological TNM stage, tumor stromal invasion, lymph node involvement, distant metastasis, and shorter survival. After follow-up, Cox proportional risk regression model analysis showed that VASH1 and lymph node metastasis were independent risk factors for the prognosis of colon cancer patients, respectively. It is noteworthy that, in contrast to the colon cancer study, Zhao et al. [25] showed that high VASH1 expression was associated with a better prognosis in renal cell carcinoma. This further indicates that VASH1 has different types of regulatory effects in different types of tumors and tissues. We analyzed the expression levels of VASH1 in different types of cancer and cells through the TCGA database, and the results showed that VASH1 was strongly correlated with LGG. Compared with normal tissues, VASH1 expression was signi cantly increased in LGG, and its high expression could be used as an independent risk factor for the prognosis of LGG. Then, immunohistochemistry and real-time PCR results were performed on LGG, GBM, and normal tissues to further con rm that the expression level of VASH1 in LGG was signi cantly higher than that in normal tissues, and it was mainly expressed in tumor cells and endothelial cells. Meanwhile, the VASH1 expression level was positively correlated with tumor recurrence, WHO grade, epilepsy, and IDH1 wild type.
These results further con rmed the strong speci city of VASH1 in gliomas, and further re ected the progression and deterioration of tumors.
Tumor-in ltrating immune cells are closely related to tumorigenesis, angiogenesis, and tumor cell growth, thus regulating the number and differentiation of immune cells [26]. There is evidence that tumor progression may be caused by the escape of cancer cells from host immune monitoring [27]. Therefore, elucidating the in ltrating immune cells in TME may help elucidate the underlying mechanisms of VASH1 in LGG. We found that the proportion of anti-tumor immune cells was higher in the high expression group, and VASH1 was positively correlated with B cells, CD4+T cells, macrophages, neutrophils, and dendritic cells. In addition, we also found differential genes mediated by VASH1 and abundant immune pathways.
VASH1 is positively correlated with KLHL-1, PAXX, and CXXC4 in LGG, and is related to the Natural killer cell-mediated cytotoxicity pathway. They are associated with inhibition of NK cells and macrophage in ltration, inducing immune escape of tumor cells, thereby promoting tumor growth. At the same time, we found that VASH1 was positively correlated with various immune checkpoints in LGG, and VASH1 mutations in LGG immune microenvironment can promote tumor growth and lead to poor prognosis. Therefore, VASH1 alone or in combination with other targets may serve as a potential biomarker for immunotherapy.
So far, the molecular mechanism of VASH1 in tumor genesis and development is not completely clear [28]. It has been reported that VASH1 is transported extracellularly by binding with a molecular chaperone, and then binds to vascular growth factor receptor-2 (VEGFR-2) on the surface of endothelial cells to inhibit the activation of downstream pathways after VEGFR-2 binding, thus inhibiting angiogenesis [29].
Ninomiya et al. [30] performed immunostaining on postoperative surgical specimens of esophageal cancer patients and found that VASH1 and VASH2 expressions were related to tumor progression and prognosis, among which VASH1 positive esophageal cancer patients had a poor prognosis. However, due to the lack of a typical secretory signaling sequence for these two regulatory factors, VASH1 needs to bind to a small Vasohibin-binding protein (SVBP) in order to be secreted effectively and increase the stability of protein structure while promoting the secretion of VASH2. It also plays an important role in the regulation of tumor angiogenesis [31]. In addition, studies have reported that after endothelial cells interfere with the expression of VASH1, high expression of VASH1 can not only inhibit endothelial cell tubulogenesis activity but also enhance the stress ability of cells. After low expression of VASH1, cells are easy to be killed by external stimuli. It is suspected that the expression of SIRTl and SOD2 is activated by VASH1. Miyashita et al. [8] also con rmed this result by interfering with the expression of VASH1 with lentivirus and found that endothelial cells would show autophagy and premature senescence after VASH1 knockdown, and endothelial cells were very easy to die due to external stimulation. Therefore, VASH1 regulates the activity of tumor cells and endothelial cells through a variety of signaling pathways in different tissues.
In the nervous system, Vincent et al. [32] demonstrated that binding VASH1 to SVBP could speci cally inhibit tubulin tyrosine/phenylalanine carboxypeptidase activity, thus further promoting glial cell differentiation and migration. In addition, VASH1-SVBP was initially identi ed as a secreted protein that regulates angiogenesis, acting together to inhibit tumor angiogenesis. In our study, through differential gene and protein PPI maps, we found that VASH1 expression in LGG is closely related to SVBP and the αtubulin family, and VASH1 mutation speci cally leads to abnormal tyrosine and de-tyrosine dynamic cycles of α-tubulin. Thus, it is closely related to cell transformation and tumor invasion. Meanwhile, GSEA enrichment analysis showed that VASH1 was closely related to cell cycle, P53, Notch, and TGF-β signaling pathways. P53 signaling pathway plays an important role in many biological processes that regulate a variety of gene expression, including apoptosis, growth inhibition, inhibiting cell cycle progression, differentiation and accelerate DNA repair, genome instability, and cell stress after aging, it had been hit by methylation, phosphorylation, acetylation, ubiquitin modi cation after translation, such as control. Wu [33] et al showed that VASH1 was strongly correlated with P53 and TAp53, and inhibited angiogenesis in NSCLC. It is noteworthy that, although some studies have shown that VASH1 mainly plays a role in regulating VEGF through the angiogenesis pathway in esophageal cancer, prostate cancer, and small cell lung cancer. Zhou [34] et al showed that in cervical cancer, VASH1 is regulated by miR-221-3p to activate the ERK-Akt pathway, and has nothing to do with VEGF. Similarly, no correlation between VASH1 and VEGA was found in LGG in this study, which requires more studies to further con rm its molecular mechanism.
In order to further study the speci c biological role of VASH1 in LGG, we detected the expression of VASH1 in several human glioma cell lines commonly used in the laboratory and screened them according to the results, and then established the U-251 cell line with VASH1 knockdown. By Transwell invasion assay and scratch healing assay, we found that knocking down VASH1 signi cantly improved the migration and invasion ability of U-251 cells. It is concluded that VASH1 can inhibit the progression of glioma under certain conditions. According to Zhao [35] et al., VASH1 overexpression can inhibit the proliferation and apoptosis of human umbilical cord endothelial cells and 786-0 cells, but it cannot inhibit tumor invasion. We believe that this may be due to different internal microenvironments of different tumor tissues, resulting in changes in the interaction of cytokines such as VASH1. Finally, the biological function of VASH1 is different. To sum up, we found that the progress VASH1 expression can promote tumor cell lines, instead of in-person LGG in the patient's body, when the tumor mass in the rapid growth stage, through the feedback mechanism produces lots of VASH1 secretion, thus a further re ection of tumor progression and prognosis of patients, which can be used as independent risk factors for the prognosis of patients with LGG. However, since the changes after VASH1 overexpression and related molecular pathways were not veri ed in this study, more in vivo studies are needed to further verify these ndings. In addition, more detailed mechanisms of VASH1 in LGG genesis and development must be further explored.

Conclusion
Based on the above results, we found for the rst time that VASH1 was highly expressed in LGG, and the high expression of VASH1 was closely related to the poor prognosis of LGG patients. Meanwhile, bioinformatics and experiments con rmed the high speci city and biological characteristics of VASH1 in LGG and further found that VASH1 may regulate tumor progression through immune-related signaling pathways, P53 signaling pathways, and SVBP/α-tubulin. In conclusion, this study preliminarily suggests that VASH1 can be used as an important prognostic biomarker and potential therapeutic target for LGG, and provides a new molecular layer for screening high-risk LGG.       LGG prognostic analysis. (A) value, risk factor HR, and con dence interval for univariate analysis of age, epilepsy, relapse, IDH1, stage, and VASH1 expression. (B) value, risk factor HR, and con dence interval for multivariable analysis of age, epilepsy, relapse, IDH1, stage, and VASH1 expression.