Integrative Bioinformatics and Experimental Investigation Introduces OBI1-AS1 as a Key LncRNA in the Progression of Low-grade Glioma to Glioblastoma

Abstract Background:Long non-coding RNAs (LncRNAs) are widely known for their multiple functions in the context of cancer from tumor initiation to tumor progression and metastasis. Gliomas are the most prevalent primary forms of brain tumor, classed from grades I to IV according to their malignant histological features with grade IV also known as Glioblastoma Multiforme (GBM) displaying the highest level of malignancy. This fact intensifies the importance of searching for Differentially Expressed LncRNAs (DELncRNAs) between GBM and Low-Grade Glioma in the hope of finding new targets for diagnostic and therapeutic measures. Methods: In the current study, we performed bioinformatics analysis to obtain a list of DELncRNAs and further chose the unprecedentedly studied OBI1-AS1 for further investigations. We also carried out Real-Time PCR to validate our bioinformatics findings.Results:Both analyses were in concordance and pinpointed downregulated expression of OBI1-AS1 in GBM compared to LGG samples. Additional supplementary bioinformatics studies exhibited OBI1-AS1 role in synaptic signal transduction and neural differentiation in addition to its role in pluripotency and maintenance of stemness. Conclusion:All the aforementioned findings introduce OBI1-AS1 as a new attractive lncRNA to be further studied for a better clarification of its roles in glioma progression and a deeper understanding of malignant transformation of LGG to GBM.

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OS5.3 Quantitative signaling pathway analysis of Diffuse Intrinsic Pontine Glioma identifies two subtypes, respectively high TGFβ/MAPK-AP1 and high PI3K/HH pathway activity, which are potentially clinically actionable

Neuro-Oncology ◽

10.1093/neuonc/noz126.036 ◽

2019 ◽

Vol 21 (Supplement_3) ◽

pp. iii11-iii11

Author(s):

A van de Stolpe ◽

W Verhaegh ◽

L Holtzer

Keyword(s):

Signal Transduction ◽

Signaling Pathways ◽

Signaling Pathway ◽

Pi3k Pathway ◽

Diffuse Intrinsic Pontine Glioma ◽

Low Grade Glioma ◽

Signal Transduction Pathways ◽

Low Grade ◽

Pontine Glioma ◽

Pathway Activity

Abstract BACKGROUND Diffuse Intrinsic Pontine Glioma (DIPG) is a pediatric brain tumor (glioma), resistant to chemotherapy, with only a temporary response to radiotherapy and an extremely bad prognosis. Genomic abnormalities have been found, indicating abnormal activation of certain growth factor signaling pathways, while expression analysis suggests involvement of developmental signaling pathways.10–15 signal transduction pathways can drive cancer growth and metastasis. We have developed, and biologically validated, a method which enables quantitative measurements of functional activity of signal transduction pathways in individual cell/tissue samples, based on Bayesian computational model inference of pathway activity from measurements of mRNA levels of target genes of the transcription factor associated with the respective signalling pathway. A major envisioned clinical utility is prediction of therapy response. MATERIAL AND METHODS For signaling pathway analysis, Affymetrix expression microarray data were available (GEO dataset GSE26576) from 2 normal brain stem samples and from 6 low grade glioma and 26 DIPG samples (post-mortem after therapy). Of one DIPG patient samples were available before and after therapy. Signaling pathway activity scores were calculated for estrogen and androgen receptor, PI3K-FOXO, MAPK-AP1, JAK-STAT, NFκB, Hedgehog (HH), TGFβ, NOTCH and Wnt pathways. PI3K pathway activity is the reverse of FOXO activity, in the absence of oxidative stress (measured by SOD2 expression). Pathway activity scores were compared between normal tissue and low grade glioma samples and DIPG, and k-means cluster analysis was performed on the DIPG pathway activity scores. RESULTS After treatment, HH pathway activity was increased in DIPG compared to low grade glioma (p=0.0003), PI3K pathway activity scores showed large variations in activity in the DIPG group. Tumors with cell cycle (CDK4/6, CCND1-3) or Receptor Tyrosine Kinase-related gene amplifications had higher PI3K and HH pathway activity compared to tumors without identified amplifications (p<0.05) which, in contrast, had higher MAPK-AP1 pathway activity (p<0.002). Pathway-based clustering analysis revealed two DIPG clusters, C1: high TGFβ/MAPK-AP1 and low PI3K/HH pathway activity; C2: low TGFβ/MAPK-AP1, high PI3K/HH pathway activity. C1 best resembled low grade glioma. In the patient with pre/post treatment samples, a C1 pathway profile switched to a C2 profile after treatment. CONCLUSION Using our quantitative analysis of signaling pathway activity in post-treatment DIPG, two pathway activity subtypes were identified, of which the HH/PI3K high, TGFβ low activity subtype was associated with defined gene amplifications, and may have been induced by chemoradiation therapy. Clusters are supported by a clear biological rationale. Identified signaling pathways are potentially drug targetable.

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Identification and validation of a novel eight mutant-derived long non-coding RNAs signature as a prognostic biomarker for genome instability in low-grade glioma

Aging ◽

10.18632/aging.203079 ◽

2021 ◽

Author(s):

Aierpati Maimaiti ◽

Xixian Wang ◽

Yinan Pei ◽

Nuerbiye Nuermaimaiti ◽

Abudireheman Tuersunniyazi ◽

...

Keyword(s):

Genome Instability ◽

Prognostic Biomarker ◽

Low Grade Glioma ◽

Low Grade ◽

Non Coding Rnas

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Prediction and analysis of hub genes between glioblastoma and low-grade glioma using bioinformatics analysis

Medicine ◽

10.1097/md.0000000000023513 ◽

2021 ◽

Vol 100 (3) ◽

pp. e23513

Author(s):

Baowei Xu

Keyword(s):

Bioinformatics Analysis ◽

Low Grade Glioma ◽

Low Grade ◽

Hub Genes

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Serine Incorporator 2 (SERINC2) Expression Predicts an Unfavorable Prognosis of Low-Grade Glioma (LGG): Evidence from Bioinformatics Analysis

Journal of Molecular Neuroscience ◽

10.1007/s12031-020-01620-w ◽

2020 ◽

Vol 70 (10) ◽

pp. 1521-1532

Author(s):

Chunxiao Qi ◽

Lei Lei ◽

Jinqu Hu ◽

Gang Wang ◽

Jiyuan Liu ◽

...

Keyword(s):

Bioinformatics Analysis ◽

Cox Regression ◽

Membrane Lipids ◽

Transmembrane Protein ◽

Low Grade Glioma ◽

The Cancer Genome Atlas ◽

Low Grade ◽

Normal Brain ◽

Hub Genes ◽

Cox Regression Analysis

Abstract Serine Incorporator 2 (SERINC2) is a transmembrane protein that incorporates serine into membrane lipids. The function of SERINC2 in tumors has been reported, but the role of SERINC2 in gliomas is not fully understood. RNA-sequencing data from The Cancer Genome Atlas (TCGA) (530 cases of low-grade glioma (LGG) and 173 cases of glioblastoma multiforme (GBM)) and microarray data from Gene Expression Omnibus (GEO) (Accession No. GSE16011, 284 cases gliomas were included) were acquired. Bioinformatics analysis was performed as the primary method to examine the function of SERINC2 and its correlated genes in glioma. SERINC2 was highly expressed in GBM compared with LGG and normal brain tissues. Elevated SERINC2 expression predicted shorter 5-, 10-, and 15-year overall survival (OS) of LGG patients and isocitrate dehydrogenase-1 (IDH-1) mutation-type LGG patients but had no effect on the OS of GBM patients. Cox regression analysis showed that SERINC2 was an independent factor in LGG OS. Methylation analysis found that 13 CpG methylation sites (methylation450k) correlated with SERINC2 expression in LGG. The mRNA expression level of SERINC2 was significant lower in the DNA deletion group than in the intact and amplification groups. A total of 390 copositive and 244 conegative correlation genes with SERINC2 were obtained from LGG in TCGA-LGG and GSE16011. Gene ontology (GO) category and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed that the copositive correlation genes were primarily enriched in the mitotic process and cell cycle. Combining the results from the protein-protein interaction (PPI) network of SERINC2 correlation genes and CytoHubba led to the selection of 10 hub genes (CDC20, FN1, AURKB, AURKA, KIF2C, BIRC5, CCNB2, UBE2C, CCNA2, and CENPE). OncoLnc analysis confirmed that high expression levels of these hub genes were associated with poor OS in LGG. Our results suggested that aberrant SERINC2 expression existed in glioma and that its expression might be a potential prognostic marker in LGG patients. CDC20, FN1, AURKB, AURKA, KIF2C, BIRC5, CCNB2, UBE2C, CCNA2, and CENPE may be potential biomarkers and therapeutic targets for LGG.

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