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Open AccessJournal ArticleDOI

Identification of potential biomarkers and candidate small molecule drugs in glioblastoma

TLDR
The 10 most vital small molecule drugs of GBM, which potentially imitate or reverse GBM carcinogenic status, were predicted by using Connectivity Map (CMAP) database and validated in silico.
Abstract
Glioblastoma (GBM) is a common and aggressive primary brain tumor, and the prognosis for GBM patients remains poor. This study aimed to identify the key genes associated with the development of GBM and provide new diagnostic and therapies for GBM. Three microarray datasets (GSE111260, GSE103227, and GSE104267) were selected from Gene Expression Omnibus (GEO) database for integrated analysis. The differential expressed genes (DEGs) between GBM and normal tissues were identified. Then, prognosis-related DEGs were screened by survival analysis, followed by functional enrichment analysis. The protein–protein interaction (PPI) network was constructed to explore the hub genes associated with GBM. The mRNA and protein expression levels of hub genes were respectively validated in silico using The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases. Subsequently, the small molecule drugs of GBM were predicted by using Connectivity Map (CMAP) database. A total of 78 prognosis-related DEGs were identified, of which10 hub genes with higher degree were obtained by PPI analysis. The mRNA expression and protein expression levels of CETN2, MKI67, ARL13B, and SETDB1 were overexpressed in GBM tissues, while the expression levels of CALN1, ELAVL3, ADCY3, SYN2, SLC12A5, and SOD1 were down-regulated in GBM tissues. Additionally, these genes were significantly associated with the prognosis of GBM. We eventually predicted the 10 most vital small molecule drugs, which potentially imitate or reverse GBM carcinogenic status. Cycloserine and 11-deoxy-16,16-dimethylprostaglandin E2 might be considered as potential therapeutic drugs of GBM. Our study provided 10 key genes for diagnosis, prognosis, and therapy for GBM. These findings might contribute to a better comprehension of molecular mechanisms of GBM development, and provide new perspective for further GBM research. However, specific regulatory mechanism of these genes needed further elaboration.

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MiR-196: emerging of a new potential therapeutic target and biomarker in colorectal cancer.

TL;DR: The potential utilization of miR-196 and its targets as therapeutic targets and novel biomarkers in early detection and prediction of prognosis in CRC patients is highlighted.
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Integrated Gene Expression and Methylation Analyses Identify DLL3 as a Biomarker for Prognosis of Malignant Glioma

TL;DR: In this article, the expression level of Delta-like ligand 3 (DLL3), an inhibitory ligand-driven activation of the Notch pathway, has been shown to be significantly associated with overall survival in patients with glioma.
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Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer

- 01 Jan 2022 - 
TL;DR: Wang et al. as discussed by the authors presented a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer, which was validated using tenfold cross-validation and in two independent confirmation cohorts.
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DNA Damage Repair-Related Genes Signature for Immune Infiltration and Outcome in Cervical Cancer

TL;DR: In cervical cancer, DNA damage repair related genes and immune cell infection characteristics have certain association, and DNA damage Repair related gene and immunecell infection characteristics can effectively predict the prognosis.
Journal ArticleDOI

Different Approaches for the Profiling of Cancer Pathway-Related Genes in Glioblastoma Cells

TL;DR: The present study aimed to characterise the expression of cancer pathway-related genes in glial tumour cell lines (A172, SW1088, and T98G) using the qRT-PCR method and presents the original multicriterial decision making (MCDM) for the possible characterization of gene expression profiles.
References
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Journal ArticleDOI

Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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limma powers differential expression analyses for RNA-sequencing and microarray studies

TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
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Exploration, normalization, and summaries of high density oligonucleotide array probe level data

TL;DR: There is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities, and the exploratory data analyses of the probe level data motivate a new summary measure that is a robust multi-array average (RMA) of background-adjusted, normalized, and log-transformed PM values.
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A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

TL;DR: Three methods of performing normalization at the probe intensity level are presented: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure and the simplest and quickest complete data method is found to perform favorably.
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