ArticlePloS one2014
A 16-gene signature distinguishes anaplastic astrocytoma from glioblastoma.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 22 citations in OpenAlex.
- Genetic Discrimination of Grade 3 and Grade 4 Gliomas by Artificial Neural Network.Cellular and molecular neurobiology · 2023Article
- The Transcriptomic Landscape of Pediatric Astrocytoma.International journal of molecular sciences · 2022Article
- The Risk of Heart Disease-Related Death Among Anaplastic Astrocytoma Patients After Chemotherapy: A SEER Population-Based Analysis.Frontiers in oncology · 2022Article
- Evidence for age-related contributions of DNA damage and epigenetics in brain tumorigenesis.International journal of experimental pathology · 2021Article
- Diosmin Inhibits Glioblastoma Growth through Inhibition of Autophagic Flux.International journal of molecular sciences · 2021Article
- Article
- Computational analysis of the mesenchymal signature landscape in gliomas.BMC medical genomics · 2017Article
- DNA methylation signatures for 2016 WHO classification subtypes of diffuse gliomas.Clinical epigenetics · 2017Article
- Anaplastic astrocytoma: prognostic factors and survival in 4807 patients with emphasis on receipt and impact of adjuvant therapy.Journal of neuro-oncology · 2016Article
- A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients.Oncotarget · 2015Article
- KITENIN promotes glioma invasiveness and progression, associated with the induction of EMT and stemness markers.Oncotarget · 2015Article
- An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals.PloS one · 2015Article
- Neuro-oncology: Novel biomarkers for high-grade astrocytoma.Nature reviews. Neurology · 2014Article
- Indian data on central nervous tumors: A summary of published work.South Asian journal of cancerReview
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.
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