Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma

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(a) Camera, (b) patient location and (c) physiotherapist." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "L.M.D. Luiz, I.A. Marques, J.P. Folador, A.O. Andrade" "autores" => array:4 [ 0 => array:2 [ "nombre" => "L.M.D." "apellidos" => "Luiz" ] 1 => array:2 [ "nombre" => "I.A." "apellidos" => "Marques" ] 2 => array:2 [ "nombre" => "J.P." "apellidos" => "Folador" ] 3 => array:2 [ "nombre" => "A.O." "apellidos" => "Andrade" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0213485321001304?idApp=UINPBA00004N" "url" => "/02134853/0000003900000004/v1_202404170527/S0213485321001304/v1_202404170527/en/main.assets" ] "en" => array:19 [ "idiomaDefecto" => true "cabecera" => "Original article" "titulo" => "Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "353" "paginaFinal" => "360" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "A. You, J. Gu, J. Wang, J. Li, Y. Zhang, G. Rao, X. Ge, K. Zhang, X. Gao, D. Wang" "autores" => array:10 [ 0 => array:3 [ "nombre" => "A." "apellidos" => "You" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "J." "apellidos" => "Gu" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "J." "apellidos" => "Wang" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "J." "apellidos" => "Li" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "Y." "apellidos" => "Zhang" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 5 => array:3 [ "nombre" => "G." "apellidos" => "Rao" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 6 => array:3 [ "nombre" => "X." "apellidos" => "Ge" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 7 => array:3 [ "nombre" => "K." "apellidos" => "Zhang" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 8 => array:3 [ "nombre" => "X." "apellidos" => "Gao" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 9 => array:4 [ "nombre" => "D." "apellidos" => "Wang" "email" => array:1 [ 0 => "docwangdc1981@163.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Operating Theatre, Tangshan Central Hospital, 063000 Tangshan, China" "etiqueta" => "b" "identificador" => "aff0010" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "El valor de ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico del glioma" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0020" "etiqueta" => "Figure 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 1779 "Ancho" => 2500 "Tamanyo" => 119724 ] ] "descripcion" => array:1 [ "en" => "Effect of HAS2-AS1 expression on OS and PFS in glioma patients and corresponding prognostic value. The (A) OS and (B) PFS of patients with high HAS2-AS1 expression were compared with those of patients with low expression; the predictive value of HAS2-AS1 expression in (C) OS (sensitivity of 75%, specificity of 97.5%) and (D) PFS (sensitivity of 95%, specificity of 85%) of glioma patients." ] ] ] "textoCompleto" => "IntroductionGlioma is one of the most common primary tumors in the central nervous system, accounting for about 40–50% of primary intracranial tumors. Glioma includes a variety of histologic features and the world health organization (WHO) has classified glioma using phenotypic and genotypic parameters since 2016 to make a more objective diagnosis of glioma.<a class="elsevierStyleCrossRef" href="#bib0005">1</a> Furthermore, the tumor is graded from the lowest to the highest malignancy degree (I, II, III, and IV) according to its expected biological behavior. Grade I is characterized by benign cytology, grade II is characterized by medium cellularity without dysplasia or mitotic activity, and grade III is characterized by cellularity with hypoplasia and mitosis, grade IV is the same as grade III with additional proliferation and necrosis of microvessels.<a class="elsevierStyleCrossRef" href="#bib0010">2</a> Besides grade I tumor can be cured by surgery, the rest of the glioma is hard to be cured by the existing treatment, and most patients experience relapse. Generally, patients with early diagnosis have a better prognosis, with a 5-year survival rate of 42–92%.<a class="elsevierStyleCrossRefs" href="#bib0015">3–5</a>It is found that one of the main reasons for the unsatisfactory survival of glioma after treatment is that currently, the detection indexes for glioma are generally still on the patient's age and tumor histology, leading to huge challenges in clinical prognosis, treatment identification and early diagnosis of patients.<a class="elsevierStyleCrossRef" href="#bib0030">6</a> Therefore, a reliable biomarker for diagnosis and prognosis of glioma is urgently needed in clinic. Long non-coding RNAs (lncRNAs) are a type of RNAs whose transcript length is greater than 200 nucleotides. Studies have reported that lncRNAs can regulate gene expression at epigenetic, transcriptional and post-transcriptional levels through chromosome modification, transcriptional activation or interference.<a class="elsevierStyleCrossRef" href="#bib0035">7</a> Some studies have indicated that lncRNAs are closely related to tumors, and there are significant differences in the expression of some lncRNAs in normal tissues and tumor tissues. Abnormally expressed lncRNAs may play an important role in the occurrence of tumors, and lncRNAs may become new markers for tumor diagnosis and evaluation of prognosis as well as therapeutic effect.<a class="elsevierStyleCrossRef" href="#bib0040">8</a>Hyaluronan (HA) is one of the commonest glycosaminoglycan (GAG) in extracellular matrix (ECM), wherein hyaluronan synthase 2 (HAS2) is the main HAS participating in HA synthesis.<a class="elsevierStyleCrossRef" href="#bib0045">9</a> Recent reports pointed out that HAS2 antisense 1 (HAS2-AS1) is a kind of lncRNA belonging to natural antisense transcript, and controls HAS2 via epigenetics.<a class="elsevierStyleCrossRef" href="#bib0050">10</a> For instance, a study<a class="elsevierStyleCrossRef" href="#bib0055">11</a> manifested that Sirtuin 1 represses nuclear translocation of NF-κB and lncRNA HAS2-AS1 expression to decrease HAS2 expression. HAS2-AS1 as a natural antisense RNA can generate heterodimer of HAS2 mRNA/HAS2-AS1 to foster HAS2 expression.<a class="elsevierStyleCrossRef" href="#bib0060">12</a> Besides, HAS2-AS1 as a lncRNA is proved to impose an oncogenic role in multiple cancers including glioblastoma,<a class="elsevierStyleCrossRef" href="#bib0065">13</a> oral squamous cell carcinoma,<a class="elsevierStyleCrossRef" href="#bib0070">14</a> and epithelial ovarian cancer.<a class="elsevierStyleCrossRef" href="#bib0075">15</a> A study<a class="elsevierStyleCrossRef" href="#bib0080">16</a> authenticated that transcription factor USF1 binds to lncRNA HAS2-AS1 promotor, thereby facilitating invasive and migratory capabilities of glioma. The other study also exhibited that transcription factor C/EBPβ stimulates human fetal lung fibroblast-1 (HFL-1) cell migration, proliferation, and inflammation through activating lncRNA HAS2-AS1 in hypoxia.<a class="elsevierStyleCrossRef" href="#bib0085">17</a> Nonetheless, the specific role of lncRNA HAS2-AS1 in glioma is not clear.Here, we analyzed the expression level of HAS2-AS1 in 80 clinical samples, constructed receiver operating characteristic (ROC) curves to evaluate the diagnostic and prognostic value of HAS2-AS1 in glioma, and provided a new direction for the clinical treatment of glioma.MethodsBioinformatics analysisGene Expression Quantification data and miRNA Expression Quantification data of TCGA_LGG and TCGA_GBM were downloaded from TCGA database (<a href="https://portal.gdc.cancer.gov/">https://portal.gdc.cancer.gov/</a>), and glioma tissues along with normal tissues of 670 patients were obtained. EdgeR was used for differential analysis with |logFC|>2 and padj<0.05 as the threshold to find out the differentially expressed lncRNAs (DElncRNAs), and survival analysis was carried out on DElncRNAs.Sample selectionThis study collected tumor and adjacent normal tissue samples from 80 patients with glioma admitted to Tangshan Gongren Hospital from January 2015 to January 2018. All patients had not received any treatment before the operation. The tissue samples of the patients were obtained during the operation and all specimens were stored in liquid nitrogen for rapid freezing after resection. The tumor histology of each sample was assessed by senior pathologists. The specimens were obtained with the approval and consent of the ethics committee of Tangshan Gongren Hospital, and all patients had signed the informed consent. The patients were classified into the WHO (I–II) grade and the WHO (III–IV) grade according to the WHO classification standard. The pathological factors of the patients including gender, age, tumor size, pathological classification, tissue type and WHO grade were listed in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>qRT-PCRTwo μg of total RNA was isolated from tissue samples or cultured cells using Trizol reagent (Invitrogen, Carlsbad, California) following manufacturer's instructions. The isolated RNA was treated using PrimeScript RT Master Mix (Takara, Dalian, China) to prepare complementary DNA (cDNA) for PCR analysis. PCR reaction was performed on LightCycler 480 system using TB GreenPremix Ex Taq II (Takara). The corresponding primers were as follows: HAS2-AS1: 5′-GACAGGACCTTGAAGACTGGG-3′ (forward) and 5′-GGGATGGAGGTCAGCAACAA-3′ (reverse); GAPDH: 5′-ACAACTTTGGTATCGTGGAAGG-3′ (forward) and 5′-GCCATCACGCCACA GTTTC-3′ (reverse). GAPDH was the internal reference of HAS2-AS1. HAS2-AS1 expression level was calculated by 2−ΔΔCt method.Statistical analysisGraphPad Prism (version 7.0, GraphPad software, Inc., La Jolla, CA, USA) and SPSS software (version 23.0, SPSS Inc., Chicago, IL) were used for data analysis. Kaplan–Meier curve was used to analyze the overall survival (OS) of glioma patients. Chi-square test was used to examine the correlation between HAS2-AS1 expression level and clinicopathological parameters. P<0.05 indicated a statistically significant difference. The diagnostic ability of HAS2-AS1 in glioma was detected by ROC curve. ROC curve was drawn by using SPSS 23.0, and the area under the curve (AUC) was calculated using rank-sum test. The larger the area, the higher the judgment value. The “Youden index” was determined using the best cutoff value. The maximum value of the index was the best boundary value.Follow-up visit80 patients were followed up at least once. The follow-up was mainly to detect the expression of HAS2-AS1 in the patients and observe the prognostic effect. The follow-up period began from the first day of treatment to May 31, 2018. A total of 80 patients were followed up for 6–36 months and the median follow-up time was 12.3 months. One patient was lost to follow-up, with a total follow-up rate of 98.75%. OS refers to the duration time from the first day after surgery to death or from the last follow-up time to the time of loss of follow-up. Progression-free survival (PFS) is the period from the first day of surgery to recurrence and metastasis of patients.ResultsResults of bioinformatics analysisEdgeR differential analysis results showed that a total of 557 DElncRNAs were obtained (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>A), among which HAS2-AS1 was highly expressed in glioma (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>B). Survival analysis indicated that high expression of HAS2-AS1 indicated an extremely high survival risk, suggesting that HAS2-AS1 was of great survival significance (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>C). Hence, HAS2-AS1 was likely to be a potential diagnostic and prognostic marker for glioma.<elsevierMultimedia ident="fig0005"></elsevierMultimedia>HAS2-AS1 is up-regulated in glioma tissue with good diagnostic valueThe expression level of HAS2-AS1 in clinical glioma tissue and normal tissue of 80 patients was evaluated by qRT-PCR. The results revealed that the relative mRNA expression of HAS2-AS1 in glioma tissues was significantly higher than that in normal tissues (P<0.0001, <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>A). ROC curves were plotted based on HAS2-AS1 expression in glioma and normal tissues in the study. It could be concluded from the ROC curves that AUC value was 0.863 with the cut-off value of 5.3, sensitivity of 75%, specificity of 92.5% and Youden index of 67.5%. HAS2-AS1 was confirmed to possess good sensitivity and specificity in the diagnosis of glioma, along with good diagnostic value indicated by the AUC and Youden index. Furthermore, glioma tissues could be distinguished from normal tissues according to the expression level of HAS2-AS1 (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>B).<elsevierMultimedia ident="fig0010"></elsevierMultimedia>The relationship between HAS2-AS1 expression and the clinicopathological characteristics of glioma patientsHere, glioma patients were divided into high-expression group (n=40) and low-expression group (n=40) according to median HAS2-AS1 expression level, and the correlation between HAS2-AS1 expression level and clinicopathological factors in glioma patients was detected by chi-square test. There was no significant correlation between HAS2-AS1 expression level and age, gender, pathological classification, and tissue type (P>0.05). While tumor size (P=0.002) and WHO grade (P=0.01) were remarkably correlated with HAS2-AS1 expression (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).Tumor size and WHO grade are significantly correlated with HAS2-AS1 expression in gliomaIt had been concluded from <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> that tumor size and WHO grade were dramatically correlated with HAS2-AS1 expression level. Box plots were used to demonstrate the specific correlation. It could be observed that the expression level of HAS2-AS1 in glioma tissues with a tumor size of more than 4cm was obviously higher than that in glioma tissues with a size of less than 4cm (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>A). Additionally, the expression of HAS2-AS1 in WHO grade III–IV glioma tissues was also significantly higher than that in the I–II glioma tissues (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>B).<elsevierMultimedia ident="fig0015"></elsevierMultimedia>High expression of HAS2-AS1 indicates poor prognosis and poor survival rateSurvival analysis revealed that patients with low HAS2-AS1 expression share an relatively optimal survival (P<0.01), suggesting that high HAS2-AS1 expression was related to poor OS (<a class="elsevierStyleCrossRef" href="#fig0020">Fig. 4</a>A). PFS curves exhibited that patients with low HAS2-AS1 expression had significantly higher PFS, revealing that high expression of HAS2-AS1 suggested poor PFS (<a class="elsevierStyleCrossRef" href="#fig0020">Fig. 4</a>B). ROC analysis for the prognostic value of HAS2-AS1 in OS of glioma patients showed the AUC value of 0.906, cut-off value of 5.3, sensitivity of 75%, specificity of 97.5%, and Youden index of 72.5% (<a class="elsevierStyleCrossRef" href="#fig0020">Fig. 4</a>C). ROC analysis for the prognostic value of HAS2-AS1 in PFS of glioma patients showed the AUC value of 0.88, cut-off value of 4.9, sensitivity of 95%, specificity of 85%, and Youden index of 65.5% (<a class="elsevierStyleCrossRef" href="#fig0020">Fig. 4</a>D). The above data suggested that high expression of HAS2-AS1 was associated with poor prognosis in glioma patients and had good prognostic value.<elsevierMultimedia ident="fig0020"></elsevierMultimedia>ConclusionGlioma is a disease in the central nervous system with the highest mortality and is the leading cause of brain diseases related deaths in children and adults.<a class="elsevierStyleCrossRef" href="#bib0090">18</a> Its incidence increases with age and peaks between 75 and 84.<a class="elsevierStyleCrossRef" href="#bib0095">19</a> Despite that most aggressive treatment methods have been applied for glioma, the survival and prognosis remain poor, with a median survival of 12–15 months and a low 5-year survival rate.<a class="elsevierStyleCrossRefs" href="#bib0100">20,21</a> The traditional treatment methods for glioma include surgical treatment, radiotherapy and chemotherapy, etc. However, due to the invasive growth of glioma, the boundary of tumor tissues and adjacent normal brain tissues is unclear, so it is difficult to completely resect the glioma tumor, resulting in poor treatment and common recurrence. Radiotherapy and chemotherapy are often used as adjuvant means after the surgery, but they could not specifically kill tumor cells, and may also produce toxic and side effects on the central nervous system, so the treatment of glioma is one of the difficulties in neurosurgical research.<a class="elsevierStyleCrossRefs" href="#bib0110">22–24</a> In order to change the clinical status that diagnosis and prognosis prediction of glioma disease can only depend on patient's age and tumor histological phenotypes, a reliable biomarker is in need for clinical diagnosis of glioma and the prognosis prediction after surgical treatment. LncRNAs can be applied in glioma and it has been reported that LINC00599 is down-regulated in glioma tissues and cell lines, and is related to WHO grade and prognosis of glioma patients.<a class="elsevierStyleCrossRef" href="#bib0125">25</a> Increased expression of lncRNA AB073614 may be a biomarker of poor prognosis in glioma.<a class="elsevierStyleCrossRef" href="#bib0130">26</a> LncRNA MEG3 plays an important role in glioma cell proliferation, apoptosis and autophagy, and this gene is also significantly associated with the prognosis of glioma patients.<a class="elsevierStyleCrossRef" href="#bib0135">27</a> All the above studies have proved that 1ncRNAs play a vital role in glioma.Abnormal expression of the human hyaluronan synthase 2 (HAS2) gene has been linked to malignant tumors, pulmonary arterial hypertension, osteoarthritis, asthma, thyroid dysfunction, and large organ fibrosis.<a class="elsevierStyleCrossRef" href="#bib0140">28</a> Studies have indicated that HAS2-AS1 knockout can functionally inhibit the proliferation, invasion and tumor growth of ovarian cancer cells in vitro and in vivo, while overexpression of HAS2-AS1 indicates poor clinical prognosis of patients with ovarian cancer.<a class="elsevierStyleCrossRef" href="#bib0075">15</a> It is found that the reduction of HAS2-AS1 inhibits the migration and invasion of glioma cells in vivo and in vitro.<a class="elsevierStyleCrossRef" href="#bib0065">13</a> In addition, many investigations reported that HAS2-AS1 is involved in the regulation mechanism of ceRNA network to modulate the proliferation and migration of tumor cells.<a class="elsevierStyleCrossRefs" href="#bib0145">29,30</a>Glioma tissues and adjacent normal tissues from 80 patients were involved in the study. The results exhibited that the expression of HAS2-AS1 in glioma tissues was significantly higher than that in normal tissues, which was consistent with the bioinformatics analysis results of HAS2-AS1 and glioma.<a class="elsevierStyleCrossRef" href="#bib0150">30</a> Moreover, the tumor size and WHO grade of glioma were correlated with the expression of HAS2-AS1 in tumors, which was consistent with the results of the review and meta-analysis of lncRNAs and glioma.<a class="elsevierStyleCrossRef" href="#bib0155">31</a> The OS of patients with high HAS2-AS1 expression was remarkably lower than that of patients with low expression. The ROC curves proved that HAS2-AS1 had better diagnostic and prognostic value in glioma. The survival curves suggested that high expression of HAS2-AS1 was associated with poor survival. However, only 80 patients were included in this study, and the sample size was small, leading to the inaccuracy of HAS2-AS1 expression in glioma. In addition, isocitrate dehydrogenase (IDH) 1/2 mutation is the golden standard for glioma diagnosis. Nevertheless, this study was limited by the absence of discussion about the relationship between HAS2-AS1 and IDH1/2. In future studies, the sample size should be enlarged to determine a more accurate value for the diagnosis and prognosis of glioma.In summary, HAS2-HA1 can be used as a clinical biomarker for the diagnosis and prognosis prediction of glioma.Authors’ contributionsAW Y and X G mainly contributed to revising the article. JS G, XH G and AW Y contributed to data analysis. J L, YY Z and GM R contributed to drafting and modifying the article. JT W and K Z contributed to final approval of the version to be published. DC W agreed to be accountable for all aspects of the work.Ethics approval and consent to participateThis study was conducted in accordance with the Helsinki Declaration II and was approved by the Research Ethics Committee of Tangshan Gongren Hospital. Written informed consent was obtained from individual or guardian participants. (GRYY-LL-2019-66).Consent for publicationAll authors consent to submit the manuscript for publication.Availability of data and materialsThe data used to support the findings of this study are included within the article. The data and materials in the current study are available from the corresponding author on reasonable request.FundingNot applicable.Conflict of interestThe authors declare no conflicts of interest." "textoCompletoSecciones" => array:1 [ "secciones" => array:16 [ 0 => array:3 [ "identificador" => "xres2130763" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1809599" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "xpalclavsec1809597" "titulo" => "Abbreviations" ] 3 => array:3 [ "identificador" => "xres2130762" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 4 => array:2 [ "identificador" => "xpalclavsec1809598" "titulo" => "Palabras clave" ] 5 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 6 => array:3 [ "identificador" => "sec0010" "titulo" => "Methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Bioinformatics analysis" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Sample selection" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "qRT-PCR" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Follow-up visit" ] ] ] 7 => array:3 [ "identificador" => "sec0040" "titulo" => "Results" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0045" "titulo" => "Results of bioinformatics analysis" ] 1 => array:2 [ "identificador" => "sec0050" "titulo" => "HAS2-AS1 is up-regulated in glioma tissue with good diagnostic value" ] 2 => array:2 [ "identificador" => "sec0055" "titulo" => "The relationship between HAS2-AS1 expression and the clinicopathological characteristics of glioma patients" ] 3 => array:2 [ "identificador" => "sec0060" "titulo" => "Tumor size and WHO grade are significantly correlated with HAS2-AS1 expression in glioma" ] 4 => array:2 [ "identificador" => "sec0065" "titulo" => "High expression of HAS2-AS1 indicates poor prognosis and poor survival rate" ] ] ] 8 => array:2 [ "identificador" => "sec0070" "titulo" => "Conclusion" ] 9 => array:2 [ "identificador" => "sec0075" "titulo" => "Authors’ contributions" ] 10 => array:2 [ "identificador" => "sec0080" "titulo" => "Ethics approval and consent to participate" ] 11 => array:2 [ "identificador" => "sec0085" "titulo" => "Consent for publication" ] 12 => array:2 [ "identificador" => "sec0090" "titulo" => "Availability of data and materials" ] 13 => array:2 [ "identificador" => "sec0095" "titulo" => "Funding" ] 14 => array:2 [ "identificador" => "sec0100" "titulo" => "Conflict of interest" ] 15 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2021-02-07" "fechaAceptado" => "2021-06-11" "PalabrasClave" => array:2 [ "en" => array:2 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1809599" "palabras" => array:3 [ 0 => "lncRNA HAS2-AS1" 1 => "Glioma" 2 => "Biomarker" ] ] 1 => array:4 [ "clase" => "abr" "titulo" => "Abbreviations" "identificador" => "xpalclavsec1809597" "palabras" => array:5 [ 0 => "lncRNAs" 1 => "ROC" 2 => "OS" 3 => "WHO" 4 => "PFS" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1809598" "palabras" => array:3 [ 0 => "ARNncl HAS2-AS1" 1 => "Glioma" 2 => "Biomarcador" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "BackgroundGlioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. MethodsThe miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan–Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. ResultsHAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis. ConclusionsNormal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients. Therefore, HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "IntroducciónLos gliomas presentan una alta incidencia y un mal pronóstico, por lo que es necesario un tratamiento más efectivo. Algunos estudios han confirmado que los ARN no codificantes de cadena larga (ARNncl) regulan diferentes enfermedades, entre las que se incluyen los gliomas. Se ha postulado que HAS2-AS1 actúa como un ARNncl, con un efecto oncogénico en diferentes tipos de cáncer. Este estudio tiene como objetivo analizar el valor del ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico de glioma. MétodosDescargamos los datos clínicos y de expresión de micro-ARN de la base de datos del Atlas del Genoma del Cáncer (TCGA) para realizar el análisis diferencial y de supervivencia. También analizamos la expresión de HAS2-AS1 en muestras patológicas y muestras de tejido adyacente normal de 80 pacientes con glioma. Para analizar la capacidad diagnóstica y el valor pronóstico de HAS2-AS1 en el glioma, recurrimos a la curva ROC. También utilizamos curvas de Kaplan-Meier para evaluar la supervivencia de los pacientes con glioma con diferentes niveles de expresión de HAS2-AS1. ResultadosLa expresión de HAS2-AS1 era significativamente mayor en las muestras patológicas que en el tejido normal. Las curvas de supervivencia demostraron que la sobreexpresión de HAS2-AS1 estaba relacionada con una menor supervivencia general y supervivencia libre de progresión. Algunos factores clínico-patológicos de los pacientes con glioma, como el tamaño del tumor y su grado, según la clasificación de la OMS, mostraron una correlación significativa con la expresión de HAS2-AS1 en los tejidos afectados. La curva ROC mostró un área bajo la curva de 0,863, lo que indica que la expresión de HAS2-AS1 posee un importante valor diagnóstico. El área bajo la curva de la supervivencia general estimada fue de 0,906; para la supervivencia libre de progresión estimada, de 0,88. Ambos valores muestran que la sobreexpresión de HAS2-AS1 se asocia con un mal pronóstico. ConclusiónLos tejidos normales pueden distinguirse claramente de los tejidos afectados por glioma en función de la expresión de HAS2-AS1. Además, la sobreexpresión de HAS2-HS1 fue indicativa de mal pronóstico en los pacientes con glioma. Por tanto, HAS2-AS1 podría utilizarse como marcador diagnóstico y pronóstico en el manejo del glioma." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "multimedia" => array:5 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1013 "Ancho" => 2917 "Tamanyo" => 163596 ] ] "descripcion" => array:1 [ "en" => "TCGA expression profile analysis reveals that lncRNA HAS2-AS1 is significantly overexpressed in glioma and of great survival significance. (A) The volcano map of edgeR differential analysis results; (B) HAS2-AS1 expression level in glioma and normal tissues in TCGA; (C) Survival rate of patients with high or low HAS2-AS1 expression were compared." ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1033 "Ancho" => 2917 "Tamanyo" => 97355 ] ] "descripcion" => array:1 [ "en" => "Expression level of HAS2-AS1 in normal tissues and glioma tissues and its diagnostic value. (A) The expression level of HAS2-AS1 in clinical normal tissues (n=80) and glioma tissues (n=80); (B) The ROC curves were plotted for evaluation of the diagnostic value of HAS2-AS1 expression in glioma (the sensitivity is 75% and the specificity is 92.5%). AUC refers to area under the curve. **** P<0.0001." ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 962 "Ancho" => 2917 "Tamanyo" => 86612 ] ] "descripcion" => array:1 [ "en" => "Tumor size and WHO grade are significantly correlated with HAS2-AS1 expression. Box plots were used to display the relationship between HAS2-AS1 expression and (A) tumor size or (B) WHO grade. **** P<0.0001." ] ] 3 => array:7 [ "identificador" => "fig0020" "etiqueta" => "Figure 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 1779 "Ancho" => 2500 "Tamanyo" => 119724 ] ] "descripcion" => array:1 [ "en" => "Effect of HAS2-AS1 expression on OS and PFS in glioma patients and corresponding prognostic value. The (A) OS and (B) PFS of patients with high HAS2-AS1 expression were compared with those of patients with low expression; the predictive value of HAS2-AS1 expression in (C) OS (sensitivity of 75%, specificity of 97.5%) and (D) PFS (sensitivity of 95%, specificity of 85%) of glioma patients." ] ] 4 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Characteristics \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">(N=80) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">HAS2-AS1</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">P value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">High(40) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Low(40) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years)</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.50 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≧60 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">39 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><60 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gender</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.26 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Male \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Female \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tumor size</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.002 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≧4cm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><4cm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Pathological classification</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.83 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Astrocytoma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Glioblastoma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Oligodendroglioma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tissue type</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.63 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mixed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Other \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">WHO grade</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">I–II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">III–IV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3512591.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Clinicopathologic characteristics of the glioma patient." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:31 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "D.N. 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El valor de ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico del glioma

A. Youa, J. Gua, J. Wanga, J. Lia, Y. Zhanga, G. Raoa, X. Gea, K. Zhanga, X. Gaob, D. Wanga,

Corresponding author

docwangdc1981@163.com

Corresponding author.

a The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China

b Operating Theatre, Tangshan Central Hospital, 063000 Tangshan, China

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and grade III is characterized by cellularity with hypoplasia and mitosis&#44; grade IV is the same as grade III with additional proliferation and necrosis of microvessels&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> Besides grade I tumor can be cured by surgery&#44; the rest of the glioma is hard to be cured by the existing treatment&#44; and most patients experience relapse&#46; Generally&#44; patients with early diagnosis have a better prognosis&#44; with a 5-year survival rate of 42&#8211;92&#37;&#46;<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3&#8211;5</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">It is found that one of the main reasons for the unsatisfactory survival of glioma after treatment is that currently&#44; the detection indexes for glioma are generally still on the patient&#39;s age and tumor histology&#44; leading to huge challenges in clinical prognosis&#44; treatment identification and early diagnosis of patients&#46;<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> Therefore&#44; a reliable biomarker for diagnosis and prognosis of glioma is urgently needed in clinic&#46; Long non-coding RNAs &#40;lncRNAs&#41; are a type of RNAs whose transcript length is greater than 200 nucleotides&#46; Studies have reported that lncRNAs can regulate gene expression at epigenetic&#44; transcriptional and post-transcriptional levels through chromosome modification&#44; transcriptional activation or interference&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> Some studies have indicated that lncRNAs are closely related to tumors&#44; and there are significant differences in the expression of some lncRNAs in normal tissues and tumor tissues&#46; Abnormally expressed lncRNAs may play an important role in the occurrence of tumors&#44; and lncRNAs may become new markers for tumor diagnosis and evaluation of prognosis as well as therapeutic effect&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Hyaluronan &#40;HA&#41; is one of the commonest glycosaminoglycan &#40;GAG&#41; in extracellular matrix &#40;ECM&#41;&#44; wherein hyaluronan synthase 2 &#40;HAS2&#41; is the main HAS participating in HA synthesis&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> Recent reports pointed out that HAS2 antisense 1 &#40;HAS2-AS1&#41; is a kind of lncRNA belonging to natural antisense transcript&#44; and controls HAS2 <span class="elsevierStyleItalic">via</span> epigenetics&#46;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> For instance&#44; a study<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a> manifested that Sirtuin 1 represses nuclear translocation of NF-&#954;B and lncRNA HAS2-AS1 expression to decrease HAS2 expression&#46; HAS2-AS1 as a natural antisense RNA can generate heterodimer of HAS2 mRNA&#47;HAS2-AS1 to foster HAS2 expression&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> Besides&#44; HAS2-AS1 as a lncRNA is proved to impose an oncogenic role in multiple cancers including glioblastoma&#44;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> oral squamous cell carcinoma&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> and epithelial ovarian cancer&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> A study<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> authenticated that transcription factor USF1 binds to lncRNA HAS2-AS1 promotor&#44; thereby facilitating invasive and migratory capabilities of glioma&#46; The other study also exhibited that transcription factor C&#47;EBP&#946; stimulates human fetal lung fibroblast-1 &#40;HFL-1&#41; cell migration&#44; proliferation&#44; and inflammation through activating lncRNA HAS2-AS1 in hypoxia&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> Nonetheless&#44; the specific role of lncRNA HAS2-AS1 in glioma is not clear&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">Here&#44; we analyzed the expression level of HAS2-AS1 in 80 clinical samples&#44; constructed receiver operating characteristic &#40;ROC&#41; curves to evaluate the diagnostic and prognostic value of HAS2-AS1 in glioma&#44; and provided a new direction for the clinical treatment of glioma&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Bioinformatics analysis</span><p id="par0025" class="elsevierStylePara elsevierViewall">Gene Expression Quantification data and miRNA Expression Quantification data of TCGA&#95;LGG and TCGA&#95;GBM were downloaded from TCGA database &#40;<a href="https://portal.gdc.cancer.gov/">https&#58;&#47;&#47;portal&#46;gdc&#46;cancer&#46;gov&#47;</a>&#41;&#44; and glioma tissues along with normal tissues of 670 patients were obtained&#46; EdgeR was used for differential analysis with &#124;logFC&#124;<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>2 and padj<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 as the threshold to find out the differentially expressed lncRNAs &#40;DElncRNAs&#41;&#44; and survival analysis was carried out on DElncRNAs&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Sample selection</span><p id="par0030" class="elsevierStylePara elsevierViewall">This study collected tumor and adjacent normal tissue samples from 80 patients with glioma admitted to Tangshan Gongren Hospital from January 2015 to January 2018&#46; All patients had not received any treatment before the operation&#46; The tissue samples of the patients were obtained during the operation and all specimens were stored in liquid nitrogen for rapid freezing after resection&#46; The tumor histology of each sample was assessed by senior pathologists&#46; The specimens were obtained with the approval and consent of the ethics committee of Tangshan Gongren Hospital&#44; and all patients had signed the informed consent&#46; The patients were classified into the WHO &#40;I&#8211;II&#41; grade and the WHO &#40;III&#8211;IV&#41; grade according to the WHO classification standard&#46; The pathological factors of the patients including gender&#44; age&#44; tumor size&#44; pathological classification&#44; tissue type and WHO grade were listed in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">qRT-PCR</span><p id="par0035" class="elsevierStylePara elsevierViewall">Two &#956;g of total RNA was isolated from tissue samples or cultured cells using Trizol reagent &#40;Invitrogen&#44; Carlsbad&#44; California&#41; following manufacturer&#39;s instructions&#46; The isolated RNA was treated using PrimeScript RT Master Mix &#40;Takara&#44; Dalian&#44; China&#41; to prepare complementary DNA &#40;cDNA&#41; for PCR analysis&#46; PCR reaction was performed on LightCycler 480 system using TB GreenPremix Ex Taq II &#40;Takara&#41;&#46; The corresponding primers were as follows&#58; HAS2-AS1&#58; 5&#8242;-GACAGGACCTTGAAGACTGGG-3&#8242; &#40;forward&#41; and 5&#8242;-GGGATGGAGGTCAGCAACAA-3&#8242; &#40;reverse&#41;&#59; GAPDH&#58; 5&#8242;-ACAACTTTGGTATCGTGGAAGG-3&#8242; &#40;forward&#41; and 5&#8242;-GCCATCACGCCACA GTTTC-3&#8242; &#40;reverse&#41;&#46; GAPDH was the internal reference of HAS2-AS1&#46; HAS2-AS1 expression level was calculated by 2<span class="elsevierStyleSup">&#8722;&#916;&#916;Ct</span> method&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Statistical analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">GraphPad Prism &#40;version 7&#46;0&#44; GraphPad software&#44; Inc&#46;&#44; La Jolla&#44; CA&#44; USA&#41; and SPSS software &#40;version 23&#46;0&#44; SPSS Inc&#46;&#44; Chicago&#44; IL&#41; were used for data analysis&#46; Kaplan&#8211;Meier curve was used to analyze the overall survival &#40;OS&#41; of glioma patients&#46; Chi-square test was used to examine the correlation between HAS2-AS1 expression level and clinicopathological parameters&#46; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 indicated a statistically significant difference&#46; The diagnostic ability of HAS2-AS1 in glioma was detected by ROC curve&#46; ROC curve was drawn by using SPSS 23&#46;0&#44; and the area under the curve &#40;AUC&#41; was calculated using rank-sum test&#46; The larger the area&#44; the higher the judgment value&#46; The &#8220;Youden index&#8221; was determined using the best cutoff value&#46; The maximum value of the index was the best boundary value&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Follow-up visit</span><p id="par0045" class="elsevierStylePara elsevierViewall">80 patients were followed up at least once&#46; The follow-up was mainly to detect the expression of HAS2-AS1 in the patients and observe the prognostic effect&#46; The follow-up period began from the first day of treatment to May 31&#44; 2018&#46; A total of 80 patients were followed up for 6&#8211;36 months and the median follow-up time was 12&#46;3 months&#46; One patient was lost to follow-up&#44; with a total follow-up rate of 98&#46;75&#37;&#46; OS refers to the duration time from the first day after surgery to death or from the last follow-up time to the time of loss of follow-up&#46; Progression-free survival &#40;PFS&#41; is the period from the first day of surgery to recurrence and metastasis of patients&#46;</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Results of bioinformatics analysis</span><p id="par0050" class="elsevierStylePara elsevierViewall">EdgeR differential analysis results showed that a total of 557 DElncRNAs were obtained &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>A&#41;&#44; among which HAS2-AS1 was highly expressed in glioma &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>B&#41;&#46; Survival analysis indicated that high expression of HAS2-AS1 indicated an extremely high survival risk&#44; suggesting that HAS2-AS1 was of great survival significance &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>C&#41;&#46; Hence&#44; HAS2-AS1 was likely to be a potential diagnostic and prognostic marker for glioma&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">HAS2-AS1 is up-regulated in glioma tissue with good diagnostic value</span><p id="par0055" class="elsevierStylePara elsevierViewall">The expression level of HAS2-AS1 in clinical glioma tissue and normal tissue of 80 patients was evaluated by qRT-PCR&#46; The results revealed that the relative mRNA expression of HAS2-AS1 in glioma tissues was significantly higher than that in normal tissues &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#44; <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>A&#41;&#46; ROC curves were plotted based on HAS2-AS1 expression in glioma and normal tissues in the study&#46; It could be concluded from the ROC curves that AUC value was 0&#46;863 with the cut-off value of 5&#46;3&#44; sensitivity of 75&#37;&#44; specificity of 92&#46;5&#37; and Youden index of 67&#46;5&#37;&#46; HAS2-AS1 was confirmed to possess good sensitivity and specificity in the diagnosis of glioma&#44; along with good diagnostic value indicated by the AUC and Youden index&#46; Furthermore&#44; glioma tissues could be distinguished from normal tissues according to the expression level of HAS2-AS1 &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>B&#41;&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">The relationship between HAS2-AS1 expression and the clinicopathological characteristics of glioma patients</span><p id="par0060" class="elsevierStylePara elsevierViewall">Here&#44; glioma patients were divided into high-expression group &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>40&#41; and low-expression group &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>40&#41; according to median HAS2-AS1 expression level&#44; and the correlation between HAS2-AS1 expression level and clinicopathological factors in glioma patients was detected by chi-square test&#46; There was no significant correlation between HAS2-AS1 expression level and age&#44; gender&#44; pathological classification&#44; and tissue type &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41;&#46; While tumor size &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;002&#41; and WHO grade &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;01&#41; were remarkably correlated with HAS2-AS1 expression &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Tumor size and WHO grade are significantly correlated with HAS2-AS1 expression in glioma</span><p id="par0065" class="elsevierStylePara elsevierViewall">It had been concluded from <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> that tumor size and WHO grade were dramatically correlated with HAS2-AS1 expression level&#46; Box plots were used to demonstrate the specific correlation&#46; It could be observed that the expression level of HAS2-AS1 in glioma tissues with a tumor size of more than 4<span class="elsevierStyleHsp" style=""></span>cm was obviously higher than that in glioma tissues with a size of less than 4<span class="elsevierStyleHsp" style=""></span>cm &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>A&#41;&#46; Additionally&#44; the expression of HAS2-AS1 in WHO grade III&#8211;IV glioma tissues was also significantly higher than that in the I&#8211;II glioma tissues &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>B&#41;&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">High expression of HAS2-AS1 indicates poor prognosis and poor survival rate</span><p id="par0070" class="elsevierStylePara elsevierViewall">Survival analysis revealed that patients with low HAS2-AS1 expression share an relatively optimal survival &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;01&#41;&#44; suggesting that high HAS2-AS1 expression was related to poor OS &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>A&#41;&#46; PFS curves exhibited that patients with low HAS2-AS1 expression had significantly higher PFS&#44; revealing that high expression of HAS2-AS1 suggested poor PFS &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>B&#41;&#46; ROC analysis for the prognostic value of HAS2-AS1 in OS of glioma patients showed the AUC value of 0&#46;906&#44; cut-off value of 5&#46;3&#44; sensitivity of 75&#37;&#44; specificity of 97&#46;5&#37;&#44; and Youden index of 72&#46;5&#37; &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>C&#41;&#46; ROC analysis for the prognostic value of HAS2-AS1 in PFS of glioma patients showed the AUC value of 0&#46;88&#44; cut-off value of 4&#46;9&#44; sensitivity of 95&#37;&#44; specificity of 85&#37;&#44; and Youden index of 65&#46;5&#37; &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>D&#41;&#46; The above data suggested that high expression of HAS2-AS1 was associated with poor prognosis in glioma patients and had good prognostic value&#46;</p><elsevierMultimedia ident="fig0020"></elsevierMultimedia></span></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conclusion</span><p id="par0075" class="elsevierStylePara elsevierViewall">Glioma is a disease in the central nervous system with the highest mortality and is the leading cause of brain diseases related deaths in children and adults&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> Its incidence increases with age and peaks between 75 and 84&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> Despite that most aggressive treatment methods have been applied for glioma&#44; the survival and prognosis remain poor&#44; with a median survival of 12&#8211;15 months and a low 5-year survival rate&#46;<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20&#44;21</span></a> The traditional treatment methods for glioma include surgical treatment&#44; radiotherapy and chemotherapy&#44; <span class="elsevierStyleItalic">etc&#46;</span> However&#44; due to the invasive growth of glioma&#44; the boundary of tumor tissues and adjacent normal brain tissues is unclear&#44; so it is difficult to completely resect the glioma tumor&#44; resulting in poor treatment and common recurrence&#46; Radiotherapy and chemotherapy are often used as adjuvant means after the surgery&#44; but they could not specifically kill tumor cells&#44; and may also produce toxic and side effects on the central nervous system&#44; so the treatment of glioma is one of the difficulties in neurosurgical research&#46;<a class="elsevierStyleCrossRefs" href="#bib0110"><span class="elsevierStyleSup">22&#8211;24</span></a> In order to change the clinical status that diagnosis and prognosis prediction of glioma disease can only depend on patient&#39;s age and tumor histological phenotypes&#44; a reliable biomarker is in need for clinical diagnosis of glioma and the prognosis prediction after surgical treatment&#46; LncRNAs can be applied in glioma and it has been reported that LINC00599 is down-regulated in glioma tissues and cell lines&#44; and is related to WHO grade and prognosis of glioma patients&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> Increased expression of lncRNA AB073614 may be a biomarker of poor prognosis in glioma&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> LncRNA MEG3 plays an important role in glioma cell proliferation&#44; apoptosis and autophagy&#44; and this gene is also significantly associated with the prognosis of glioma patients&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> All the above studies have proved that 1ncRNAs play a vital role in glioma&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">Abnormal expression of the human hyaluronan synthase 2 &#40;HAS2&#41; gene has been linked to malignant tumors&#44; pulmonary arterial hypertension&#44; osteoarthritis&#44; asthma&#44; thyroid dysfunction&#44; and large organ fibrosis&#46;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a> Studies have indicated that HAS2-AS1 knockout can functionally inhibit the proliferation&#44; invasion and tumor growth of ovarian cancer cells <span class="elsevierStyleItalic">in vitro</span> and in <span class="elsevierStyleItalic">vivo</span>&#44; while overexpression of HAS2-AS1 indicates poor clinical prognosis of patients with ovarian cancer&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> It is found that the reduction of HAS2-AS1 inhibits the migration and invasion of glioma cells <span class="elsevierStyleItalic">in vivo</span> and <span class="elsevierStyleItalic">in vitro</span>&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> In addition&#44; many investigations reported that HAS2-AS1 is involved in the regulation mechanism of ceRNA network to modulate the proliferation and migration of tumor cells&#46;<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">29&#44;30</span></a></p><p id="par0085" class="elsevierStylePara elsevierViewall">Glioma tissues and adjacent normal tissues from 80 patients were involved in the study&#46; The results exhibited that the expression of HAS2-AS1 in glioma tissues was significantly higher than that in normal tissues&#44; which was consistent with the bioinformatics analysis results of HAS2-AS1 and glioma&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> Moreover&#44; the tumor size and WHO grade of glioma were correlated with the expression of HAS2-AS1 in tumors&#44; which was consistent with the results of the review and meta-analysis of lncRNAs and glioma&#46;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">31</span></a> The OS of patients with high HAS2-AS1 expression was remarkably lower than that of patients with low expression&#46; The ROC curves proved that HAS2-AS1 had better diagnostic and prognostic value in glioma&#46; The survival curves suggested that high expression of HAS2-AS1 was associated with poor survival&#46; However&#44; only 80 patients were included in this study&#44; and the sample size was small&#44; leading to the inaccuracy of HAS2-AS1 expression in glioma&#46; In addition&#44; isocitrate dehydrogenase &#40;IDH&#41; 1&#47;2 mutation is the golden standard for glioma diagnosis&#46; Nevertheless&#44; this study was limited by the absence of discussion about the relationship between HAS2-AS1 and IDH1&#47;2&#46; In future studies&#44; the sample size should be enlarged to determine a more accurate value for the diagnosis and prognosis of glioma&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">In summary&#44; HAS2-HA1 can be used as a clinical biomarker for the diagnosis and prognosis prediction of glioma&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Authors&#8217; contributions</span><p id="par0095" class="elsevierStylePara elsevierViewall">AW Y and X G mainly contributed to revising the article&#46; JS G&#44; XH G and AW Y contributed to data analysis&#46; J L&#44; YY Z and GM R contributed to drafting and modifying the article&#46; JT W and K Z contributed to final approval of the version to be published&#46; DC W agreed to be accountable for all aspects of the work&#46;</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Ethics approval and consent to participate</span><p id="par0100" class="elsevierStylePara elsevierViewall">This study was conducted in accordance with the Helsinki Declaration II and was approved by the Research Ethics Committee of Tangshan Gongren Hospital&#46; Written informed consent was obtained from individual or guardian participants&#46; &#40;GRYY-LL-2019-66&#41;&#46;</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Consent for publication</span><p id="par0110" class="elsevierStylePara elsevierViewall">All authors consent to submit the manuscript for publication&#46;</p></span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0155">Availability of data and materials</span><p id="par0115" class="elsevierStylePara elsevierViewall">The data used to support the findings of this study are included within the article&#46; The data and materials in the current study are available from the corresponding author on reasonable request&#46;</p></span><span id="sec0095" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0160">Funding</span><p id="par0120" class="elsevierStylePara elsevierViewall">Not applicable&#46;</p></span><span id="sec0100" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0165">Conflict of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">The authors declare no conflicts of interest&#46;</p></span></span>"
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          "palabras" => array:5 [
            0 => "lncRNAs"
            1 => "ROC"
            2 => "OS"
            3 => "WHO"
            4 => "PFS"
          ]
        ]
      ]
      "es" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Palabras clave"
          "identificador" => "xpalclavsec1809598"
          "palabras" => array:3 [
            0 => "ARNncl HAS2-AS1"
            1 => "Glioma"
            2 => "Biomarcador"
          ]
        ]
      ]
    ]
    "tieneResumen" => true
    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Glioma presents high incidence and poor prognosis&#44; and therefore more effective treatments are needed&#46; Studies have confirmed that long non-coding RNAs &#40;lncRNAs&#41; basically regulate various human diseases including glioma&#46; It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers&#46; This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis&#46; In addition&#44; pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1&#46; The receiver operating characteristic &#40;ROC&#41; curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma&#46; Meanwhile&#44; a Kaplan&#8211;Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue&#46; The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival &#40;OS&#41; and progression-free survival &#40;PFS&#41;&#46; Several clinicopathological factors of glioma patients&#44; including tumor size and WHO grade&#44; were significantly correlated with HAS2-AS1 expression in tissues&#46; The ROC curve showed an area under the curve &#40;AUC&#41; value of 0&#46;863&#44; indicating that HAS2-AS1 had good diagnostic value&#46; The ROC curve for the predicted OS showed an AUC of 0&#46;906&#44; while the ROC curve for predicted PFS showed an AUC of 0&#46;88&#46; Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression&#46; Moreover&#44; overexpression of HAS2-AS1 indicated poor prognosis in glioma patients&#46; Therefore&#44; HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0005"
            "titulo" => "Background"
          ]
          1 => array:2 [
            "identificador" => "abst0010"
            "titulo" => "Methods"
          ]
          2 => array:2 [
            "identificador" => "abst0015"
            "titulo" => "Results"
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          3 => array:2 [
            "identificador" => "abst0020"
            "titulo" => "Conclusions"
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      "es" => array:3 [
        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducci&#243;n</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Los gliomas presentan una alta incidencia y un mal pron&#243;stico&#44; por lo que es necesario un tratamiento m&#225;s efectivo&#46; Algunos estudios han confirmado que los ARN no codificantes de cadena larga &#40;ARNncl&#41; regulan diferentes enfermedades&#44; entre las que se incluyen los gliomas&#46; Se ha postulado que HAS2-AS1 act&#250;a como un ARNncl&#44; con un efecto oncog&#233;nico en diferentes tipos de c&#225;ncer&#46; Este estudio tiene como objetivo analizar el valor del ARNncl HAS2-AS1 como marcador diagn&#243;stico y pron&#243;stico de glioma&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Descargamos los datos cl&#237;nicos y de expresi&#243;n de micro-ARN de la base de datos del Atlas del Genoma del C&#225;ncer &#40;TCGA&#41; para realizar el an&#225;lisis diferencial y de supervivencia&#46; Tambi&#233;n analizamos la expresi&#243;n de HAS2-AS1 en muestras patol&#243;gicas y muestras de tejido adyacente normal de 80 pacientes con glioma&#46; Para analizar la capacidad diagn&#243;stica y el valor pron&#243;stico de HAS2-AS1 en el glioma&#44; recurrimos a la curva ROC&#46; Tambi&#233;n utilizamos curvas de Kaplan-Meier para evaluar la supervivencia de los pacientes con glioma con diferentes niveles de expresi&#243;n de HAS2-AS1&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">La expresi&#243;n de HAS2-AS1 era significativamente mayor en las muestras patol&#243;gicas que en el tejido normal&#46; Las curvas de supervivencia demostraron que la sobreexpresi&#243;n de HAS2-AS1 estaba relacionada con una menor supervivencia general y supervivencia libre de progresi&#243;n&#46; Algunos factores cl&#237;nico-patol&#243;gicos de los pacientes con glioma&#44; como el tama&#241;o del tumor y su grado&#44; seg&#250;n la clasificaci&#243;n de la OMS&#44; mostraron una correlaci&#243;n significativa con la expresi&#243;n de HAS2-AS1 en los tejidos afectados&#46; La curva ROC mostr&#243; un &#225;rea bajo la curva de 0&#44;863&#44; lo que indica que la expresi&#243;n de HAS2-AS1 posee un importante valor diagn&#243;stico&#46; El &#225;rea bajo la curva de la supervivencia general estimada fue de 0&#44;906&#59; para la supervivencia libre de progresi&#243;n estimada&#44; de 0&#44;88&#46; Ambos valores muestran que la sobreexpresi&#243;n de HAS2-AS1 se asocia con un mal pron&#243;stico&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Los tejidos normales pueden distinguirse claramente de los tejidos afectados por glioma en funci&#243;n de la expresi&#243;n de HAS2-AS1&#46; Adem&#225;s&#44; la sobreexpresi&#243;n de HAS2-HS1 fue indicativa de mal pron&#243;stico en los pacientes con glioma&#46; Por tanto&#44; HAS2-AS1 podr&#237;a utilizarse como marcador diagn&#243;stico y pron&#243;stico en el manejo del glioma&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0025"
            "titulo" => "Introducci&#243;n"
          ]
          1 => array:2 [
            "identificador" => "abst0030"
            "titulo" => "M&#233;todos"
          ]
          2 => array:2 [
            "identificador" => "abst0035"
            "titulo" => "Resultados"
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          3 => array:2 [
            "identificador" => "abst0040"
            "titulo" => "Conclusi&#243;n"
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        ]
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        "etiqueta" => "Figure 1"
        "tipo" => "MULTIMEDIAFIGURA"
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        "mostrarDisplay" => false
        "figura" => array:1 [
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        "descripcion" => array:1 [
          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">TCGA expression profile analysis reveals that lncRNA HAS2-AS1 is significantly overexpressed in glioma and of great survival significance&#46; &#40;A&#41; The volcano map of edgeR differential analysis results&#59; &#40;B&#41; HAS2-AS1 expression level in glioma and normal tissues in TCGA&#59; &#40;C&#41; Survival rate of patients with high or low HAS2-AS1 expression were compared&#46;</p>"
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        "identificador" => "fig0010"
        "etiqueta" => "Figure 2"
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        "figura" => array:1 [
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Expression level of HAS2-AS1 in normal tissues and glioma tissues and its diagnostic value&#46; &#40;A&#41; The expression level of HAS2-AS1 in clinical normal tissues &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>80&#41; and glioma tissues &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>80&#41;&#59; &#40;B&#41; The ROC curves were plotted for evaluation of the diagnostic value of HAS2-AS1 expression in glioma &#40;the sensitivity is 75&#37; and the specificity is 92&#46;5&#37;&#41;&#46; AUC refers to area under the curve&#46; &#42;&#42;&#42;&#42; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#46;</p>"
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        "identificador" => "fig0015"
        "etiqueta" => "Figure 3"
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        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr3.jpeg"
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        "descripcion" => array:1 [
          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Tumor size and WHO grade are significantly correlated with HAS2-AS1 expression&#46; Box plots were used to display the relationship between HAS2-AS1 expression and &#40;A&#41; tumor size or &#40;B&#41; WHO grade&#46; &#42;&#42;&#42;&#42; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#46;</p>"
        ]
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      3 => array:7 [
        "identificador" => "fig0020"
        "etiqueta" => "Figure 4"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr4.jpeg"
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        "descripcion" => array:1 [
          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Effect of HAS2-AS1 expression on OS and PFS in glioma patients and corresponding prognostic value&#46; The &#40;A&#41; OS and &#40;B&#41; PFS of patients with high HAS2-AS1 expression were compared with those of patients with low expression&#59; the predictive value of HAS2-AS1 expression in &#40;C&#41; OS &#40;sensitivity of 75&#37;&#44; specificity of 97&#46;5&#37;&#41; and &#40;D&#41; PFS &#40;sensitivity of 95&#37;&#44; specificity of 85&#37;&#41; of glioma patients&#46;</p>"
        ]
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            "identificador" => "at1"
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                  \t\t\t\t" scope="col">Characteristics&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">HAS2-AS1</th><th class="td" title="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8807;60&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">41&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " colspan="5" align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
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                  \t\t\t\t">0&#46;26&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Male&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">45&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">20&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">25&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Female&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Mixed&nbsp;\t\t\t\t\t\t\n
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Article information

ISSN: 02134853
Original language: English

DOI:10.1016/j.nrl.2021.06.006

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Year/Month	Html	Pdf	Total

2024 November	6	0	6
2024 October	23	4	27
2024 September	39	14	53
2024 August	39	13	52
2024 July	30	3	33
2024 June	29	6	35
2024 May	56	8	64
2024 April	63	8	71
2024 March	17	6	23
2024 February	25	21	46
2024 January	35	19	54
2023 December	20	9	29
2023 November	22	14	36
2023 October	20	6	26
2023 September	24	5	29
2023 August	21	3	24
2023 July	19	2	21
2023 June	26	3	29
2023 May	48	2	50
2023 April	33	2	35
2023 March	6	0	6
2023 February	8	4	12
2023 January	5	4	9
2022 December	6	8	14
2022 November	9	9	18
2022 October	6	5	11
2022 September	7	8	15
2022 August	6	10	16
2022 July	5	8	13
2022 June	6	8	14
2022 May	6	12	18
2022 April	17	15	32
2022 March	13	8	21
2022 February	8	6	14
2022 January	7	6	13
2021 December	9	13	22
2021 November	7	13	20
2021 October	9	5	14

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