Dataset Information

Deep Sequencing of Small RNAs from Neurosurgical Extracellular Vesicles Substantiates miR-486-3p as a Circulating Biomarker that Distinguishes Glioblastoma from Lower-Grade Astrocytoma Patients.

ABSTRACT: Extracellular vesicles (EVs) play key roles in glioblastoma (GBM; astrocytoma grade IV) biology and are novel sources of biomarkers. EVs released from GBM tumors can cross the blood-brain-barrier into the periphery carrying GBM molecules, including small non-coding RNA (sncRNA). Biomarkers cargoed in circulating EVs have shown great promise for assessing the molecular state of brain tumors in situ. Neurosurgical aspirate fluids captured during tumor resections are a rich source of GBM-EVs isolated directly from tumor microenvironments. Using density gradient ultracentrifugation, EVs were purified from cavitron ultrasonic surgical aspirate (CUSA) washings from GBM (n = 12) and astrocytoma II-III (GII-III, n = 5) surgeries. The sncRNA contents of surgically captured EVs were profiled using the Illumina® NextSeqTM 500 NGS System. Differential expression analysis identified 27 miRNA and 10 piRNA species in GBM relative to GII-III CUSA-EVs. Resolved CUSA-EV sncRNAs could discriminate serum-EV sncRNA profiles from GBM and GII-III patients and healthy controls and 14 miRNAs (including miR-486-3p and miR-106b-3p) and cancer-associated piRNAs (piR_016658, _016659, _020829 and _204090) were also significantly expressed in serum-EVs. Circulating EV markers that correlate with histological, neuroradiographic and clinical parameters will provide objective measures of tumor activity and improve the accuracy of GBM tumor surveillance.

SUBMITTER: Hallal S

PROVIDER: S-EPMC7404297 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Deep Sequencing of Small RNAs from Neurosurgical Extracellular Vesicles Substantiates miR-486-3p as a Circulating Biomarker that Distinguishes Glioblastoma from Lower-Grade Astrocytoma Patients.

Hallal Susannah S Ebrahim Khani Saeideh S Wei Heng H Lee Maggie Yuk Ting MYT Sim Hao-Wen HW Sy Joanne J Shivalingam Brindha B Buckland Michael E ME Alexander-Kaufman Kimberley L KL

International journal of molecular sciences 20200713 14

Extracellular vesicles (EVs) play key roles in glioblastoma (GBM; astrocytoma grade IV) biology and are novel sources of biomarkers. EVs released from GBM tumors can cross the blood-brain-barrier into the periphery carrying GBM molecules, including small non-coding RNA (sncRNA). Biomarkers cargoed in circulating EVs have shown great promise for assessing the molecular state of brain tumors in situ. Neurosurgical aspirate fluids captured during tumor resections are a rich source of GBM-EVs isolat ...[more]

PMID: 32668808

Similar Datasets

Project description:Astrocytomas are the most common and aggressive type of primary brain tumors in adults. The World Health Organization (WHO) assorts them into grades, from I to IV, based on histopathological features that reflect their malignancy [1]. Alongside with tumor progression, comes an increased proliferation, genomic instability, infiltration in normal brain tissue and resistance to treatments. The high genomic instability forges tumor cells enhancing key proteins that avoid cells from collapsing and favor therapy resistance [2]. To explore genes and pathways associated with tumor progression phenotypes we analyzed gene expression in a panel of non-tumor and glioma cell lines, namely: ACBRI371, non-tumor human astrocytes; HDPC, fibroblasts derived from dental pulp; Res186, Res259, Res286 and UW467 that include grade I, II and III astrocytoma cell lines derived from pediatric tumors; and T98G, U343MG, U87MG, U138MG and U251MG, all derived from GBM (grade IV). We also profiled gene expression changes caused by exogenously induced replicative stress, performing RNA sequencing with camptothecin (CPT)-treated cells. Here we describe the RNA-sequencing data set acquired, including quality of reads and sequencing consistency, as well as the bioinformatics strategy used to analyze it. We also compared gene expression patterns and pathway enrichment between non-tumor versus lower-grade (LGG), non-tumor versus GBM, LGG versus GBM, and CPT-treated versus non-treated cells. In brief, a total of 6467 genes showed differential expression and 5 pathways were enriched in tumor progression, while 2279 genes and 7 pathways were altered under the replication stress condition. The raw data was deposited in the NCBI BioProject database under the accession number PRJNA631805. Our dataset is valuable for researchers interested in differential gene expression among different astrocytoma grades and in expression changes caused by replicative stress, facilitating studies that seek novel biomarkers of glioma progression and treatment resistance.

Project description:Accumulating evidence suggests that hypoxia microenvironment and long non-coding lncRNAs (lncRNAs) exert critical roles in tumor development. Herein, we aim to develop a hypoxia-related lncRNA (HRL) model to predict the survival outcomes of patient with lower-grade glioma (LGG). The RNA-sequencing data of 505 LGG samples were acquired from The Cancer Genome Atlas (TCGA). Using consensus clustering based on the expression of hypoxia-related mRNAs, these samples were divided into three subsets that exhibit distinct hypoxia content, clinicopathologic features, and survival status. The differentially expressed lncRNAs across the subgroups were documented as candidate HRLs. With LASSO regression analysis, eight informative lncRNAs were selected for constructing the prognostic HRL model. This signature had a good performance in predicting LGG patients' overall survival in the TCGA cohort, and similar results could be achieved in two validation cohorts from the Chinese Glioma Genome Atlas. The HRL model also showed correlations with important clinicopathologic characteristics such as patients' age, tumor grade, IDH mutation, 1p/19q codeletion, MGMT methylation, and tumor progression risk. Functional enrichment analysis indicated that the HLR signature was mainly involved in regulation of inflammatory response, complement, hypoxia, Kras signaling, and apical junction. More importantly, the signature was related to immune cell infiltration, estimated immune score, tumor mutation burden, neoantigen load, and expressions of immune checkpoints and immunosuppressive cytokines. Finally, a nomogram was developed by integrating the HRL signature and clinicopathologic features, with a concordance index of 0.852 to estimate the survival probability of LGG patients. In conclusion, our study established an effective HRL model for prognosis assessment of LGG patients, which may provide insights for future research and facilitate the designing of individualized treatment.

Dataset Information

Deep Sequencing of Small RNAs from Neurosurgical Extracellular Vesicles Substantiates miR-486-3p as a Circulating Biomarker that Distinguishes Glioblastoma from Lower-Grade Astrocytoma Patients.

Publications

Deep Sequencing of Small RNAs from Neurosurgical Extracellular Vesicles Substantiates miR-486-3p as a Circulating Biomarker that Distinguishes Glioblastoma from Lower-Grade Astrocytoma Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets