Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Promising Prognosis Marker Candidates on the Status of Epithelial–Mesenchymal Transition and Glioma Stem Cells in Glioblastoma

24 Oct 2019

Abstract excerpt

Multivariable analyses of global expression profiling are valid indicators of the prognosis of various diseases including brain cancers. To identify the candidates for markers of prognosis of glioblastoma, we performed multivariable analyses on the status of epithelial (EPI)–mesenchymal (MES) transition (EMT), glioma (GLI) stem cells (GSCs), molecular target therapy (MTT), and potential glioma biomarkers (PGBs)...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cancer Cells and Metastasis
Share to Glioma Diagnosis and Treatment
Share to MicroRNA in disease regulation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 31653034
DOI: 10.3390/cells8111312

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Promising Prognosis Marker Candidates on the Status of Epithelial–Mesenchymal Transition and Glioma Stem Cells in GlioblastomaPMID 31653034Read ↗

Identification of EMT-related gene signatures in glioblastoma to aid immunotherapy and prognosisSemantic proximity Read ↗

Identification of An Epithelial-Mesenchymal Transition-Related lncRNA Prognostic Signature For Patients With GlioblastomaSemantic proximity Read ↗

Identification of Prognostic Model and Biomarkers for Cancer Stem Cell Characteristics in Glioblastoma by Network Analysis of Multi-Omics Data and Stemness IndicesSemantic proximity Read ↗

Comprehensive understanding of glioblastoma molecular phenotypes: classification, characteristics, and transition.Semantic proximity Read ↗

Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker CandidatesSemantic proximity Read ↗

In Silico Analysis and Characterization of Differentially Expressed Genes to Distinguish Glioma Stem Cells from Normal Neural Stem CellsSemantic proximity Read ↗

In silico identification of the prognostic biomarkers and therapeutic targets associated with cancer stem cell characteristics of glioma.Semantic proximity Read ↗

Glioblastoma multiforme: a multi-omics analysis of driver genes and tumour heterogeneitySemantic proximity Read ↗

Machine learning and multi-omics analysis reveal key regulators of proneural–mesenchymal transition in glioblastomaSemantic proximity Read ↗

Genomics and Prognosis Analysis of Epithelial-Mesenchymal Transition in GliomaSemantic proximity Read ↗

Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics AnalysisSemantic proximity Read ↗

Investigating the Link between Molecular Subtypes of Glioblastoma, Epithelial-Mesenchymal Transition, and CD133 Cell Surface ProteinSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.