Survival Of Lower Grade Glioma Patients Research Articles

ITGA1 Promotes Glioma Cell Proliferation and Affects Immune Cell Infiltration in Low-Grade Glioma.

Background: Low-grade glioma (LGG) is a commonly occurring type of central nervous system cancer. Integrin α1 (ITGA1), a family member of integrins, is implied in the malignant development of cancers, but the fundamental role of ITGA1 has not been illustrated yet in glioma. This study aimed to evaluate the prognostic value of ITGA1. Methods: Correlations between ITGA1 and relevant clinical features were analyzed in the LGG datasets based on Chinese Glioma Genome Atlas (CGGA) and Tumor Genome Atlas (TCGA). Glioma clinical samples and glioma cell lines were identified at the level of mRNA and protein level by Western blot. Cox regression were developed to assess the involvement of ITGA1 expression in predicting survival in LGG patients. Application of GSEA enrichment analysis to reveal ITGA1-mediated biological functions in LGG. Using TIMER 2.0 to analyze correlations between immune cell infiltration. In addition, ITGA1 high expression was analyzed for correlation with immune checkpoint-related genes and cumulative survival time. Results: ITGA1 was significantly more expressed in LGG than in normal samples. Cox regression indicated that ITGA1 was a risk factor independently for prognosis in LGG patients. GSEA enrichment analysis indicated that ITGA1 was engaged in several immunomodulatory processes. ITGA1 expression was shown to be highly correlated with the immune score, stromal score, and estimate score in LGG. ITGA1 was significantly related to the immune checkpoint-associated gene expression. In vivo experiments showed that overexpression of ITGA1 promoted glioma cell invasion. Conclusion: High ITGA1 expression is correlated with immune infiltration of the low-grade tumor, leading to poor prognoses in LGG patients.

A prognostic signature based on snoRNA predicts the overall survival of lower-grade glioma patients.

Small nucleolar RNAs (snoRNAs) are a group of non-coding RNAs enriched in the nucleus which direct post-transcriptional modifications of rRNAs, snRNAs and other molecules. Recent studies have suggested that snoRNAs have a significant role in tumor oncogenesis and can be served as prognostic markers for predicting the overall survival of tumor patients. We screened 122 survival-related snoRNAs from public databases and eventually selected 7 snoRNAs that were most relevant to the prognosis of lower-grade glioma (LGG) patients for the establishment of the 7-snoRNA prognostic signature. Further, we combined clinical characteristics related to the prognosis of glioma patients and the 7-snoRNA prognostic signature to construct a nomogram. The prognostic model displayed greater predictive power in both validation set and stratification analysis. Results of enrichment analysis revealed that these snoRNAs mainly participated in the post-transcriptional process such as RNA splicing, metabolism and modifications. In addition, 7-snoRNA prognostic signature were positively correlated with immune scores and expression levels of multiple immune checkpoint molecules, which can be used as potential biomarkers for immunotherapy prediction. From the results of bioinformatics analysis, we inferred that SNORD88C has a major role in the development of glioma, and then performed in vitro experiments to validate it. The results revealed that SNORD88C could promote the proliferation, invasion and migration of glioma cells. We established a 7-snoRNA prognostic signature and nomogram that can be applied to evaluate the survival of LGG patients with good sensitivity and specificity. In addition, SNORD88C could promote the proliferation, migration and invasion of glioma cells and is involved in a variety of biological processes related to DNA and RNA.

PSRC1 Regulated by DNA Methylation Is a Novel Target for LGG Immunotherapy.

Proline and serine-rich coiled-coil 1 (PSRC1) has been reported to function as an oncogene in several cancers by regulating mitosis, while there are few reports on the role of PSRC1 in lower-grade glioma (LGG). Thus, this study collected 22 samples and 1126 samples from our institution and several databases, respectively, to explore the function of PSRC1 in LGG. First, the analysis of clinical characteristics showed that PSRC1 was always highly expressed in more malignant clinical characteristics of LGG, such as higher WHO grade, recurrence type, and IDH wild type. Second, the prognosis analysis revealed that the high expression of PSRC1 was an independent risk factor contributing to the shorter overall survival of LGG patients. Third, the analysis of DNA methylation showed that the expression of PSRC1 was associated with its 8 DNA methylation sites, overall negatively regulated by its DNA methylation level in LGG. Fourth, the analysis of immune correlation revealed that the expression of PSRC1 was positively correlated with the infiltration of 6 immune cells and the expression of 4 well-known immune checkpoints in LGG, respectively. Finally, co-expression analysis and KEGG analysis showed the 10 genes most related to PSRC1 and the signaling pathways involved by PSRC1 in LGG, respectively, such as MAPK signaling pathway and focal adhesion. In conclusion, this study identified the pathogenic role of PSRC1 in the pathological progression of LGG, expanding the molecular understanding of PSRC1, and provided a biomarker and potential immunotherapeutic target for the treatment of LGG.

Novel methylation-related long non-coding RNA clinical outcome prediction method: the clinical phenotype and immune infiltration research in low-grade gliomas.

Recent studies have suggested that long non-coding RNAs (lncRNAs) may play crucial role in low-grade glioma; however, the underlying mechanisms linking them to epigenetic methylation remain unclear. We downloaded expression level data for regulators associated with N1 methyladenosine (m1A), 5-methyladenine (m5C), and N6 methyladenosine (m6A) (M1A/M5C/M6A) methylation from the Cancer Genome Atlas-low-grade glioma (TCGA-LGG) database. We identified the expression patterns of lncRNAs, and selected methylation-related lncRNAs using Pearson correlation coefficient>0.4. Non-negative matrix dimensionality reduction was then used to determine the expression patterns of the methylation-associated lncRNAs. We constructed a weighted gene co-expression network analysis (WGCNA) network to explore the co-expression networks between the two expression patterns. Functional enrichment of the co-expression network was performed to identify biological differences between the expression patterns of different lncRNAs. We also constructed prognostic networks based on the methylation presence in lncRNAs in low-grade gliomas. We identified 44 regulators by literature review. Using a correlation coefficient greater than 0.4, we identified 2330 lncRNAs, among which 108 lncRNAs with independent prognostic values were further screened using univariate Cox regression at P< 0.05. Functional enrichment of the co-expression networks revealed that regulation of trans-synaptic signaling, modulation of chemical synaptic transmission, calmodulin binding, and SNARE binding were mostly enriched in the blue module. The calcium and CA2 signaling pathways were associated with different methylation-related long non-coding chains. Using the Least Absolute Shrinkage Selector Operator (LASSO) regression analysis, we analyzed a prognostic model containing four lncRNAs. The model's risk score was 1.12 *AC012063+0.74 * AC022382+0.32 * AL049712+0.16 * GSEC. Gene set variation analysis (GSVA) revealed significant differences in mismatch repair, cell cycle, WNT signaling pathway, NOTCH signaling pathway, Complement and Cascades, and cancer pathways at different GSEC expression levels. Thus, these results suggest that GSEC may be involved in the proliferation and invasion of low-grade glioma, making it a prognostic risk factor for low-grade glioma. Our analysis identified methylation-related lncRNAs in low-grade gliomas, providing a foundation for further research on lncRNA methylation. We found that GSEC could serve as a candidate methylation marker and a prognostic risk factor for overall survival in low-grade glioma patients. These findings shed light on the underlying mechanisms of low-grade glioma development and may facilitate the development of new treatment strategies.

Expression and prognosis of GNG5 in lower-grade glioma using public database

Background: Glioma is the most common primary brain tumor, but its therapeutic effect is not very ideal up to now. The point of this study was to recognize the potential gene involved in lower-grade glioma (LGG) and to promote the treatment and prognosis for LGG patients. Method: During the investigation, we first studied the differential expression and the survival analysis of GNG5 in patients with glioma, LGG, and GBM, respectively. Then, independent prognostic analysis, the clinical relevance characteristics and the differential expressed genes (DEGs) were also evaluated. In addition, Metascape and GSEA analyses were carried out to achieve potential mechanism. Co-expression and immune infiltration analysis were finally conducted. Results: The results indicated that GNG5 as an independent prognostic indicator was negatively associated with the overall survival of LGG patients. Metascape and GSEA analyses showed that GNG5 may participate in complement and coagulation cascades pathway. The co-expression analysis was concluded that GNG5 was positively correlated with the following factors: C4B, PLAU, C1R, C1QC, C4A, SERPINA1, C1QB, CFI, C3. Conclusions: This study demonstrated that the highly expression of GNG5 in LGG may lead to poor prognosis. Besides, our research also revealed that GNG5 may be a promising immune-related biomarker for LGG patients.

An automated approach for predicting glioma grade and survival of LGG patients using CNN and radiomics.

ObjectivesTo develop and validate an efficient and automatically computational approach for stratifying glioma grades and predicting survival of lower-grade glioma (LGG) patients using an integration of state-of-the-art convolutional neural network (CNN) and radiomics.MethodThis retrospective study reviewed 470 preoperative MR images of glioma from BraTs public dataset (n=269) and Jinling hospital (n=201). A fully automated pipeline incorporating tumor segmentation and grading was developed, which can avoid variability and subjectivity of manual segmentations. First, an integrated approach by fusing CNN features and radiomics features was employed to stratify glioma grades. Then, a deep-radiomics signature based on the integrated approach for predicting survival of LGG patients was developed and subsequently validated in an independent cohort.ResultsThe performance of tumor segmentation achieved a Dice coefficient of 0.81. The intraclass correlation coefficients (ICCs) of the radiomics features between the segmentation network and physicians were all over 0.75. The performance of glioma grading based on integrated approach achieved the area under the curve (AUC) of 0.958, showing the effectiveness of the integrated approach. The multivariable Cox regression results demonstrated that the deep-radiomics signature remained an independent prognostic factor and the integrated nomogram showed significantly better performance than the clinical nomogram in predicting overall survival of LGG patients (C-index: 0.865 vs. 0.796, P=0.005).ConclusionThe proposed integrated approach can be noninvasively and efficiently applied in prediction of gliomas grade and survival. Moreover, our fully automated pipeline successfully achieved computerized segmentation instead of manual segmentation, which shows the potential to be a reproducible approach in clinical practice.

NCAPG2 Is a Novel Prognostic Biomarker and Promotes Cancer Stem Cell Maintenance in Low-Grade Glioma.

Gliomas account for 75% of all primary malignant brain tumors in adults and are associated with high mortality. Mounting evidence has shown that NCAPG2 is differentially expressed in various cancers. However, the prognostic value and immune functions of NCAPG2 in low-grade glioma (LGG) remain unresolved. In the present study, we revealed that NCAPG2 was up-regulated in LGG, and its higher expression was associated with adverse clinical outcomes and poor clinical characteristics, including WHO grade, IDH mutation, 1p/19q codeletion, and primary therapy outcome. The results of the Cox regression analysis revealed that NCAPG2 was an independent factor for the prognosis of low-grade glioma. Meanwhile, we also established a nomogram based on NCAPG2 to predict the 1-, 3-, or 5-year survival in LGG patients. Furthermore, we found that Copy number variation (CNV) and DNA hypomethylation results in its overexpression in LGG. In addition, functional annotation confirmed that NCAPG2 was mainly involved in the immune regulation and WNT signaling pathways. Finally, we determined that increased expression of NCAPG2 was correlated with infiltration levels of various immune cells and immune checkpoint in LGG. Importantly, we found that NCAPG2 was highly expressed in glioma stem cells lines and knockdown of NCAPG2 significantly inhibited the self-renewal ability of GSC. This is the first study to identify NCAPG2 as a new potential prognostic biomarker and characterize the functional roles of NCAPG2 in the progression of LGG, and provides a novel potential diagnostic and therapeutic biomarker for LGG in the future.

Genome-wide CRISPR screens reveal metabolic and transcriptional regulation of BTN3A and cancer susceptibility to Vγ9Vδ2 T cell targeting

Abstract γδ T cells are potent anti-cancer effectors with potential to target tumors broadly, independent of neoantigens or HLA-background. γδ T cells can sense conserved cell stress signals prevalent in transformed cells, although the mechanisms governing how γδ T cells sense and kill stressed target cells remain poorly characterized. Vγ9Vδ2 T cells – the most abundant subset of human γδ T cells – recognize a protein complex containing butyrophilin 3A1 (BTN3A1), a ubiquitously expressed cell surface protein that is activated by phosphoantigens abundantly produced by tumor cells. Here we performed genome-wide CRISPR screens in target cancer cells to identify pathways that regulate: (1) γδ T cell activity with a functional co-culture killing screen, and (2) BTN3A1 cell surface expression in a phenotypic screen. Multilayered regulation of BTN3A1 expression was uncovered: transcriptional regulation (IRF1, CTBP1, ZNF217, RUNX1), intracellular trafficking, sialylation, oxidative phosphorylation (OXPHOS), purine metabolism, and other metabolic pathways. Consistent with these results, we found upregulated BTN3A1 on cells undergoing an energy crisis due to glucose deprivation, glycolysis inhibition, or OXPHOS inhibition. Furthermore, we discovered that this BTN3A1 upregulation was induced by activation of the AMP-activated protein kinase (AMPK). Also, CRISPR screen-derived gene expression signatures correlated with higher survival in low-grade glioma patients whose tumors had high Vγ9Vδ2 T cell infiltration. Uncovering this AMPK-dependent mechanism of metabolic stress-induced ligand activation deepens our understanding of γδ T cell stress surveillance and suggests new avenues to enhance γδ T cell anti-cancer activity. M.R.M. is a Cancer Research Institute (CRI) Irvington Fellow supported by CRI and was funded by the Human Vaccines Project Michelson Prize for Human Immunology.

The persistence of seizures after tumor resection negatively affects survival in low-grade glioma patients: a clinical retrospective study.

Seizures are the most common clinical manifestation of low-grade glioma (LGG). Many papers hypothesized an influence of epilepsy on glioma progression. To our knowledge, no clinical study demonstrated a direct relationship between persistence of epileptic seizures after surgery and overall survival (OS) in LGG patients. The present study aims at investigating the correlation between post-operative seizure outcome and survival in tumor-related epilepsy (TRE) patients. We performed a retrospective analysis of adult patients affected by TRE who underwent surgery for resection of LGG in a single high-volume neurosurgical center. Seizure outcome was assessed 1year after surgery and categorized according to Engel classification. Clinical, molecular and radiological features were evaluated in univariate and multivariate analyses to investigate the correlation with OS. A total of 146 patients met the inclusion criteria. Histopathological diagnosis was Diffuse Astrocytoma isocitrate dehydrogenase (IDH) wild type in 16 patients (11%), Diffuse astrocytoma IDH mutated in 89 patients (61%) and oligodendroglioma IDH mutated, 1p 19q codeleted in 41 patients (28%). 1year after surgery, 103 (70.6%) patients were in Engel class 1. Median duration of follow-up period was 69.5months. Median OS was 79.3 (72.2-86.4) months in the whole population, while it was 86.8 (78.4-95.2), 63.9 (45.7-82), 63.7 (45.2-82.2) and 47.5 (18.3-76.6) months for patients in Engel class 1, 2, 3 and 4, respectively. In a univariate analysis, Engel class evaluated 1year after surgery significantly influenced OS (p < 0.01). Multivariate analysis showed that OS was independently associated with extent of resection (p = 0.02), molecular class (p < 0.01) and Engel class (p = 0.04). Seizure control 1year after surgery significantly predicted survival of patients affected by LGG-related epilepsy in a large monocentric retrospective series. Future studies are needed to confirm these results and to assess if an epilepsy-surgical therapeutic approach may improve OS.

Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma.

Lower-grade glioma (LGG) is characterized by genetic and transcriptional heterogeneity, and a dismal prognosis. Iron metabolism is considered central for glioma tumorigenesis, tumor progression and tumor microenvironment, although key iron metabolism-related genes are unclear. Here we developed and validated an iron metabolism-related gene signature LGG prognosis. RNA-sequence and clinicopathological data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were downloaded. Prognostic iron metabolism-related genes were screened and used to construct a risk-score model via differential gene expression analysis, univariate Cox analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO)-regression algorithm. All LGG patients were stratified into high- and low-risk groups, based on the risk score. The prognostic significance of the risk-score model in the TCGA and CGGA cohorts was evaluated with Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analysis. Risk- score distributions in subgroups were stratified by age, gender, the World Health Organization (WHO) grade, isocitrate dehydrogenase 1 (IDH1) mutation status, the O6‐methylguanine‐DNA methyl‐transferase (MGMT) promoter-methylation status, and the 1p/19q co-deletion status. Furthermore, a nomogram model with a risk score was developed, and its predictive performance was validated with the TCGA and CGGA cohorts. Additionally, the gene set enrichment analysis (GSEA) identified signaling pathways and pathological processes enriched in the high-risk group. Finally, immune infiltration and immune checkpoint analysis were utilized to investigate the tumor microenvironment characteristics related to the risk score. We identified a prognostic 15-gene iron metabolism-related signature and constructed a risk-score model. High risk scores were associated with an age of > 40, wild-type IDH1, a WHO grade of III, an unmethylated MGMT promoter, and 1p/19q non-codeletion. ROC analysis indicated that the risk-score model accurately predicted 1-, 3-, and 5-year overall survival rates of LGG patients in the both TCGA and CGGA cohorts. KM analysis showed that the high-risk group had a much lower overall survival than the low-risk group (P < 0.0001). The nomogram model showed a strong ability to predict the overall survival of LGG patients in the TCGA and CGGA cohorts. GSEA analysis indicated that inflammatory responses, tumor-associated pathways, and pathological processes were enriched in high-risk group. Moreover, a high risk score correlated with the infiltration immune cells (dendritic cells, macrophages, CD4+ T cells, and B cells) and expression of immune checkpoint (PD1, PDL1, TIM3, and CD48). Our prognostic model was based on iron metabolism-related genes in LGG, can potentially aid in LGG prognosis, and provides potential targets against gliomas.

Integrated Analysis Reveals Prognostic Value and Immune Correlates of CD86 Expression in Lower Grade Glioma

BackgroundCD86 has great potential to be a new target of immunotherapy by regulating cancer immune response. However, it remains unclear whether CD86 is a friend or foe in lower-grade glioma (LGG).MethodsThe prognostic value of CD86 expression in pan-cancer was analyzed using Cox regression and Kaplan-Meier analysis with data from the cancer genome atlas (TCGA). Cancer types where CD86 showed prognostic value in overall survival and disease-specific survival were identified for further analyses. The Chinese Glioma Genome Atlas (CGGA) dataset were utilized for external validation. Quantitative real-time PCR (qRT-PCR), Western blot (WB), and Immunohistochemistry (IHC) were conducted for further validation using surgical samples from Jiangsu Province hospital. The correlations between CD86 expression and tumor immunity were analyzed using the Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm, Tumor IMmune Estimation Resource (TIMER) database, and expressions of immune checkpoint molecules. Gene Set Enrichment Analysis (GSEA) was performed using clusterprofiler r package to reveal potential pathways.ResultsPan-cancer survival analysis established CD86 expression as an unfavorable prognostic factor in tumor progression and survival for LGG. CD86 expression between Grade-II and Grade-III LGG was validated using qRT-PCR and WB. Additionally, CD86 expression in LGG with unmethylated O(6)-methylguanine-DNA-methyltransferase (MGMT) promoter was significantly higher than those with methylated MGMT (P<0.05), while in LGG with codeletion of 1p/19q it was significantly downregulated as opposed to those with non-codeletion (P<2.2*10-16). IHC staining validated that CD86 expression was correlated with MGMT status and X1p/19q subtypes, which was independent of tumor grade. Multivariate regression validated that CD86 expression acts as an unfavorable prognostic factor independent of clinicopathological factors in overall survival of LGG patients. Analysis of tumor immunity and GSEA revealed pivotal role of CD86 in immune response for LGG.ConclusionsIntegrated analysis shows that CD86 is an unfavorable prognostic biomarker in LGG patients. Targeting CD86 may become a novel approach for immunotherapy of LGG.

A Novel 10-Gene Signature Predicts Poor Prognosis in Low Grade Glioma.

Aim:Low grade glioma (LGG) is a lethal brain cancer with relatively poor prognosis in young adults. Thus, this study was performed to develop novel molecular biomarkers to effectively predict the prognosis of LGG patients and finally guide treatment decisions.Methods:survival-related genes were determined by Kaplan-Meier survival analysis and multivariate Cox regression analysis using the expression and clinical data of 506 LGG patients from The Cancer Genome Atlas (TCGA) database and independently validated in a Chinese Glioma Genome Atlas (CGGA) dataset. A prognostic risk score was established based on a linear combination of 10 gene expression levels using the regression coefficients of the multivariate Cox regression models. GSEA was performed to analyze the altered signaling pathways between the high and low risk groups stratified by median risk score.Results:We identified a total of 1489 genes significantly correlated with patients’ prognosis in LGG. The top 5 protective genes were DISP2, CKMT1B, AQP7, GPR162 and CHGB, the top 5 risk genes were SP1, EYA3, ZSCAN20, ITPRIPL1 and ZNF217 in LGG. The risk score was predictive of poor overall survival and relapse-free survival in LGG patients. Pathways of small cell lung cancer, pathways in cancer, chronic myeloid leukemia, colorectal cancer were the top 4 most enriched pathways in the high risk group. SP1, EYA3, ZSCAN20, ITPRIPL1, ZNF217 and GPR162 were significantly up-regulated, while DISP2, CKMT1B, AQP7 were down-regulated in 523 LGG tissues as compared to 1141 normal brain controls.Conclusions:The 10-gene signature may become novel prognostic and diagnostic biomarkers to considerably improve the prognostic prediction in LGG.

N6-Methylandenosine-Related lncRNAs Are Potential Biomarkers for Predicting the Overall Survival of Lower-Grade Glioma Patients.

The prognostic value of N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) was investigated in 646 lower-grade glioma (LGG) samples from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. We implemented Pearson correlation analysis to explore the m6A-related lncRNAs, and then univariate Cox regression analysis was performed to screen their prognostic roles in LGG patients. Twenty-four prognostic m6A-related lncRNAs were identified as prognostic lncRNAs and they were inputted in a least absolute shrinkage and selection operator (LASSO) Cox regression to establish a m6A-related lncRNA prognostic signature (m6A-LPS, including 9 m6A-related prognostic lncRNAs) in the TCGA dataset. Corresponding risk scores of patients were calculated and divided LGG patients into low- and high-risk subgroups by the median value of risk scores in each dataset. The m6A-LPS was validated in the CGGA dataset and it showed a robust prognostic ability in the stratification analysis. Principal component analysis showed that the low- and high-risk subgroups had distinct m6A status. Enrichment analysis indicated that malignancy-associated biological processes, pathways and hallmarks were more common in the high-risk subgroup. Moreover, we constructed a nomogram (based on m6A-LPS, age and World Health Organization grade) that had a strong ability to forecast the overall survival (OS) of the LGG patients in both datasets. We also establish a competing endogenous RNA (ceRNA) network based on seven of the twenty-four m6A-related lncRNAs. Besides, we also detected five m6A-related lncRNA expression levels in 22 clinical samples using quantitative real-time polymerase chain reaction assay.

SYT16 is a prognostic biomarker and correlated with immune infiltrates in glioma: A study based on TCGA data

BackgroundGlioma is the most lethal primary brain tumor. Lower-grade glioma (LGG) is the crucial pathological type of Glioma. Immune-infiltration of the tumor microenvironment positively associated with overall survival in LGG. SYT16 is a gene has not been reported in cancer. We assess the role of SYT16 in LGG, via the publicly available TCGA database. MethodsGene Expression Profiling Interactive Analysis (GEPIA) was used to analyze the expression of SYT16 in LGG. We evaluated the influence of SYT16 on survival of LGG patients by survival module. Then, datasets of LGG were downloaded from TCGA. The correlations between the clinical information and SYT16 expression were analyzed using logistic regression. Univariable survival and Multivariate Cox analysis was used to compare several clinical characteristics with survival. we also explore the correlation between SYT16 and cancer immune infiltrates using CIBERSORT and correlation module of GEPIA. Gene set enrichment analysis (GSEA) was performed using the TCGA dataset. In addition, we use TIMER to explore the collection of SYT16 Expression and Immune Infiltration Level in LGG and to explore cumulative survival in LGG. ResultsThe univariate analysis using logistic regression, indicated that increased SYT16 expression significantly correlated with the tumor grade. Moreover, multivariate analysis revealed that the up-regulated SYT16 expression is an independent prognostic factor for good prognosis. Specifically, SYT16 expression level has significant negative correlations with infiltrating levels of B cell, CD4+ T cells, Macrophages, Neutrophils and DCs in LGG. In addition, GSEA identified ingle organism behavior, gated channel activity, cognition, transporter complex and ligand gated channel activity in Gene Ontology (GO) were differentially enriched in the high SYT16 expression phenotype pathway. Neuroactive ligand receptor interaction, calcium signaling pathway, long term potentiation, type II diabetes mellitus and long term depression were identified as differentially enriched pathway in Kyoto Encyclopedia of Genes and Genomes (KEGG). ConclusionSYT16 is a Prognostic Biomarker and Correlated with Immune Infiltrates in LGG.

Prognostic significance of age related genes in patients with lower grade glioma.

Objective: To analyze the prognostic effects of age in different tumor types and determine the prognostic significance of age related genes in patients with lower grade glioma (LGG).Methods: The relationships between age and tumor overall survival were determined by Kaplan-Meier survival analysis using The Cancer Genome Atlas (TCGA) dataset. The age related genes were identified using TCGA RNA-seq data. Univariate and multivariate cox regression were used to determine the prognostic significance of age related genes. The results derived from TCGA dataset were further validated using Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA) datasets.Results: Age at initial pathologic diagnosis was most associated with the overall survival of LGG patients than other types of tumor patients. Age related genes EMP3, IGFBP2, TIMP1 and SERPINE1 were highly expressed in old LGG patients. The hypo-methylations of EMP3 and SERPINE1 were contributing to the high expressions of EMP3 and SERPINE1 in old LGG patients. Also, EMP3, IGFBP2, TIMP1 and SERPINE1 were highly expressed in LGG tumor tissues, compared with normal brain tissues. Moreover, high expressions of IGFBP2, EMP3, TIMP1 and SERPINE1 were associated with the worse prognosis of LGG patients. Furthermore, we demonstrated that EMP3 and SERPINE1 were connected with each other and the combination of EMP3 and SERPINE1 had better prognostic effects in glioma patients.Conclusions: Age related genes IGFBP2, EMP3, TIMP1 and SERPINE1 have significant prognostic effects in LGG patients.

Impact of adjuvant treatments on survival in Korean patients with WHO grade II gliomas: KNOG 15-02 and KROG 16-04 intergroup study.

Optimal treatment strategies for low-grade glioma (LGG) remain controversial. We analyzed treatment outcomes and evaluated prognostic factors of adult LGG patients in Korea. We reviewed the medical records of 555 patients diagnosed with WHO grade II LGG (astrocytoma 37.8%, oligoastrocytoma 15.3%, and oligodendroglioma 46.8%) at 14 institutions between 2000 and 2010. Primary and secondary endpoints were progression-free survival (PFS) and overall survival (OS). Propensity-score matching (PSM) analyses were performed to correct imbalances in patient/tumor characteristics among adjuvant treatment groups. The median follow-up time was 83.4 months, and the 5-year PFS and OS rates were 52.2% and 83.0%, respectively. Male, older age, poorer performance status, multiple lobe involvement, and astrocytoma histology were associated with poorer survival. Among the treatment factors, gross total resection (GTR) was associated with better PFS and OS, and adjuvant chemotherapy with improved PFS. Interestingly, adjuvant radiotherapy (RT) did not improve PFS; rather, it was related with poorer OS. Regarding patient/tumor characteristics, the RT group had poorer characteristics than the non-RT group. After PSM, we detected a tendency for improved PFS in the matched RT group, and no significant difference in OS compared with the matched non-RT group. The achievement of GTR is important to improve survival in LGG patients. Adjuvant chemotherapy may enhance PFS, but adjuvant RT did not improve survival outcomes. After PSM, we observed potential impacts of adjuvant RT on PFS. Our results may reflect real-world practice and consequently may help to optimize treatment strategies for LGG.

Spatial and temporal evolution of distal 10q deletion, a prognostically unfavorable event in diffuse low-grade gliomas

BackgroundThe disease course of patients with diffuse low-grade glioma is notoriously unpredictable. Temporal and spatially distinct samples may provide insight into the evolution of clinically relevant copy number aberrations (CNAs). The purpose of this study is to identify CNAs that are indicative of aggressive tumor behavior and can thereby complement the prognostically favorable 1p/19q co-deletion.ResultsGenome-wide, 50 base pair single-end sequencing was performed to detect CNAs in a clinically well-characterized cohort of 98 formalin-fixed paraffin-embedded low-grade gliomas. CNAs are correlated with overall survival as an endpoint. Seventy-five additional samples from spatially distinct regions and paired recurrent tumors of the discovery cohort were analyzed to interrogate the intratumoral heterogeneity and spatial evolution. Loss of 10q25.2-qter is a frequent subclonal event and significantly correlates with an unfavorable prognosis. A significant correlation is furthermore observed in a validation set of 126 and confirmation set of 184 patients. Loss of 10q25.2-qter arises in a longitudinal manner in paired recurrent tumor specimens, whereas the prognostically favorable 1p/19q co-deletion is the only CNA that is stable across spatial regions and recurrent tumors.ConclusionsCNAs in low-grade gliomas display extensive intratumoral heterogeneity. Distal loss of 10q is a late onset event and a marker for reduced overall survival in low-grade glioma patients. Intratumoral heterogeneity and higher frequencies of distal 10q loss in recurrences suggest this event is involved in outgrowth to the recurrent tumor.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0471-6) contains supplementary material, which is available to authorized users.

A t(1;19)(q10;p10) Mediates the Combined Deletions of 1p and 19q and Predicts a Better Prognosis of Patients with Oligodendroglioma

Combined deletion of chromosomes 1p and 19q is associated with improved prognosis and responsiveness to therapy in patients with anaplastic oligodendroglioma. The deletions usually involve whole chromosome arms, suggesting a t(1;19)(q10;p10). Using stem cell medium, we cultured a few tumors. Paraffin-embedded tissue was obtained from 21 Mayo Clinic patients and 98 patients enrolled in 2 North Central Cancer Treatment Group (NCCTG) low-grade glioma trials. Interphase fusion of CEP1 and 19p12 probes detected the t(1;19). 1p/19q deletions were evaluated by fluorescence in situ hybridization. Upon culture, one oligodendroglioma contained an unbalanced 45,XX,t(1;19)(q10;p10). CEP1/19p12 fusion was observed in all metaphases and 74% of interphase nuclei. Among Mayo Clinic oligodendrogliomas, the prevalence of fusion was 81%. Among NCCTG patients, CEP1/19p12 fusion prevalence was 55%, 47%, and 0% among the oligodendrogliomas, mixed oligoastrocytomas, and astrocytomas, respectively. Ninety-one percent of NCCTG gliomas with 1p/19q deletion and 12% without 1p/19q deletion had CEP1/19p12 fusion (P < 0.001, chi(2) test). The median overall survival (OS) for all patients was 8.1 years without fusion and 11.9 years with fusion (P = 0.003). The median OS for patients with low-grade oligodendroglioma was 9.1 years without fusion and 13.0 years with fusion (P = 0.01). Similar significant median OS differences were observed for patients with combined 1p/19q deletions. The absence of alterations was associated with a significantly shorter OS for patients who received higher doses of radiotherapy. Our results strongly suggest that a t(1;19)(q10;p10) mediates the combined 1p/19q deletion in human gliomas. Like combined 1p/19q deletion, the 1;19 translocation is associated with superior OS and progression-free survival in low-grade glioma patients.

Depression in Relation to Survival among Neurosurgical Patients with a Primary Brain Tumor: A 5-year Follow-up Study

The adverse impact of depression in relation to survival among cancer patients is currently a subject of great interest in research. In a 5-year follow-up study, we investigated the association of depression with survival of patients with a primary brain tumor. The study population consisted of 75 patients with a solitary primary brain tumor treated surgically at the Oulu Clinic for Neurosurgery, Oulu University Hospital, in Northern Finland. The patients were interviewed during admission to the hospital for the tumor surgery. Assessment of depression was made using the Beck Depression Inventory and the Crown-Crisp Experiential Index. Information on all deaths within 60 months after tumor operation was collected from the Cause of Death Register, provided by Statistics Finland. The patients with a high-grade glioma had a survival time of 22.5 months (standard deviation, 21.4 mo), whereas the corresponding time was 50.2 months (standard deviation, 19.9 mo) for patients with a low-grade glioma and 58.2 months (standard deviation, 9.4 mo) for the patients with a histologically benign tumor (P < 0.001, difference between groups, Kruskal-Wallis test). In the subgroup of patients with low-grade gliomas, depressive patients had a significantly shorter survival time compared with nondepressive subjects (P = 0.031, Kaplan-Meier survival analysis). A corresponding difference was not found in patients with high-grade gliomas or benign tumors. Tumor location in one hemisphere compared with bilateral location and wider extent of tumor surgery was associated with better survival in patients with low-grade gliomas and benign tumors but not in patients with high-grade gliomas. Preoperative depression seemed to be a significant prognostic factor for worse survival in low-grade glioma patients. In clinical practice, an evaluation of depression among brain tumor patients by structured and standardized diagnostic methods is needed to distinguish the patients whose depression actually needs treatment. The effective treatment of clinical depression among brain tumor patients and the impact of treatment on the patients' chances of survival should be a focus of future research.