Dataset Information

Phospholipase C Beta 1: a Candidate Signature Gene for Proneural Subtype High-Grade Glioma.

ABSTRACT: Phospholipase C beta 1 (PLCβ1) expresses in gliomas and cultured glial cells, but its expression is barely detectable in normal glial cells. We analyzed data from Gene Expression Omnibus (GEO-GDSxxx), The Cancer Genome Atlas (TCGA), and the Repository for Molecular Brain Neoplasia Data (REMBRANDT) to explore the potential role of PLCβ1 as a biomarker in high-grade glioma (HGG). PLCβ1 expression is significantly higher in grade III gliomas than that in grade IV gliomas from GDS1815 (n = 24 vs. 76), GDS1962 (n = 19 vs. 81), and GDS1975 (n = 26 vs. 59). In GDS1815, PLCβ1 expression correlates with several known proneural (PN) signature genes; its expression from PN subtype (n = 15) is significantly higher than that from mesenchymal (Mes) subtype (n = 33) HGG. In GDS1962, PLCβ1 expression is the highest in nontumor brain tissue (n = 23) and is significantly higher than its expression in grade II gliomas [astrocytomas (n = 7) and oligodendrogliomas (n = 37)]. A Kaplan-Meier survival curve from a REMBRANDT cohort demonstrates that glioma patients with intermediate PLCβ1 expression (n = 103) survived significantly longer than PLCβ1 downregulated (2X) groups (n = 226). From TCGA data, PLCβ1 RNA-Seq signal inversely correlates with the pathological grades, and PLCβ1 expression in PN (n = 8) is of significantly higher levels than that in Mes (n = 8) subtypes of glioblastoma. The top 50 % of PLCβ1 expression subgroup (n = 294) of gliomas (grades II to IV merged) survived significantly longer than the low 50 percentile of the PLCβ1 expression subgroup (n = 293). p values are less than 0.05 for all these analyses. We conclude that PLCβ1 is a candidate signature gene for PN subtype HGG, and its expression inversely correlates with glioma pathological grade and is a potential prognostic factor.

SUBMITTER: Lu G

PROVIDER: S-EPMC5085994 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Phospholipase C Beta 1: a Candidate Signature Gene for Proneural Subtype High-Grade Glioma.

Lu Guangrong G Chang Jeffrey T JT Liu Zheyu Z Chen Yong Y Li Min M Zhu Jay-Jiguang JJ

Molecular neurobiology 20151128 9

Phospholipase C beta 1 (PLCβ1) expresses in gliomas and cultured glial cells, but its expression is barely detectable in normal glial cells. We analyzed data from Gene Expression Omnibus (GEO-GDSxxx), The Cancer Genome Atlas (TCGA), and the Repository for Molecular Brain Neoplasia Data (REMBRANDT) to explore the potential role of PLCβ1 as a biomarker in high-grade glioma (HGG). PLCβ1 expression is significantly higher in grade III gliomas than that in grade IV gliomas from GDS1815 (n = 24 vs. 76 ...[more]

PMID: 26614510

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Project description:BackgroundLower grade glioma (LGG) are a heterogeneous tumor that may develop into high-grade malignant glioma seriously shortens patient survival time. The clinical prognostic biomarker of lower-grade glioma is still lacking. The aim of our study is to explore novel biomarkers for LGG that contribute to distinguish potential malignancy in low-grade glioma, to guide clinical adoption of more rational and effective treatments.MethodsThe RNA-seq data for LGG was downloaded from UCSC Xena and the Chinese Glioma Genome Atlas (CGGA). By a robust likelihood-based survival model, least absolute shrinkage and selection operator regression and multivariate Cox regression analysis, we developed a three-gene signature and established a risk score to predict the prognosis of patient with LGG. The three-gene signature was an independent survival predictor compared to other clinical parameters. Based on the signature related risk score system, stratified survival analysis was performed in patients with different age group, gender and pathologic grade. The prognostic signature was validated in the CGGA dataset. Finally, weighted gene co-expression network analysis (WGCNA) was carried out to find the co-expression genes related to the member of the signature and enrichment analysis of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were conducted for those co-expression network. To prove the efficiency of the model, time-dependent receiver operating characteristic curves of our model and other models are constructed.ResultsIn this study, a three-gene signature (WEE1, CRTAC1, SEMA4G) was constructed. Based on the model, the risk score of each patient was calculated with LGG (low-risk vs. high-risk, hazard ratio (HR) = 0.198 (95% CI [0.120-0.325])) and patients in the high-risk group had significantly poorer survival results than those in the low-risk group. Furthermore, the model was validated in the CGGA dataset. Lastly, by WGCNA, we constructed the co-expression network of the three genes and conducted the enrichment of GO and KEGG. Our study identified a three-gene model that showed satisfactory performance in predicting the 1-, 3- and 5-year survival of LGG patients compared to other models and may be a promising independent biomarker of LGG.

Project description:Pediatric high-grade glioma (HGG) is a type of malignancy that carries a poor prognosis. The genetic analysis of HGGs has previously identified useful mutations, the targeting of which has improved prognosis. Thus, further research into the more common mutations, such as H3 histone variants (HIST1H3B and H3F3A) and BRAF V600E, may be useful in identifying tumors with different prognoses, as the mutations are considered to drive two distinct oncogenic programs. The present study performed a retrospective analysis of pediatric HGGs. In total, 42 cases of HGG, including 32 cases (76.1%) of anaplastic astrocytoma and 10 cases (23.8%) of glioblastoma multiforme (GBM), were assessed. The median age of the patients was 7 years (range, 0-32 years). Mutations on histone H3, in particular the K27M and G34R mutations in the distinct variants HIST1H3B and H3F3A, in addition to the presence of the BRAF V600E mutation, were analyzed in 24 patients. The H3F3A K27M mutation was identified in 7 patients (29.1%), while the HIST1H3B K27M mutation was only observed in 1 patient with GBM. In addition, 5 patients harbored a BRAF V600E mutation (21%), while the H3F3A G34R mutation was not recorded in any of the patients. The overall survival of the wild-type patients at 20 months was 68% [confidence interval (CI): 38-85%] compared with 28% (CI: 0.4-60%) in patients with the H3F3A K27M mutation. These results suggested that patients with the H3F3A K27M mutation had a worse prognosis compared with wild-type patients (P=0.0045). Moreover, 3/5 patients with the BRAF V600E mutation had HGGs that were derived from a previous low-grade glioma (LGG; P=0.001). In conclusion, these results suggested that histone H3 mutations may help predict the outcome in patients with HGG. In addition, the BRAF V600E mutation was found to be associated with an increased risk of anaplastic progression. The novel data of the present study may help better define the clinical and radiological characteristics of glioma.

Dataset Information

Phospholipase C Beta 1: a Candidate Signature Gene for Proneural Subtype High-Grade Glioma.

Publications

Phospholipase C Beta 1: a Candidate Signature Gene for Proneural Subtype High-Grade Glioma.

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