ArticleBioMed research international2019
A Potential Prognostic Gene Signature for Predicting Survival for Glioblastoma Patients.
Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- A strategy for multimodal integration of transcriptomics, proteomics, and radiomics data for the prediction of recurrence in patients with IDH-mutant gliomas.International journal of cancer · 2025Article
- Genomic profiling of thymoma using a targeted high-throughput approach.Archives of medical science : AMS · 2024Article
- Brain radiotoxicity-related 15CAcBRT gene expression signature predicts survival prognosis of glioblastoma patients.Neuro-oncology · 2023Article
- Integrative genomic analysis facilitates precision strategies for glioblastoma treatment.iScience · 2022Article
- Paradoxical Association Between Relative Cerebral Blood Volume Dynamics Following Chemoradiation and Increased Progression-Free Survival in Newly Diagnosed IDH Wild-Type MGMT Promoter Methylated Glioblastoma With Measurable Disease.Frontiers in oncology · 2022Article
- Characterization of the Survival Influential Genes in Carcinogenesis.International journal of molecular sciences · 2021Article
- Article
- Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma.Computational and mathematical methods in medicine · 2021Article
- High expression of CPNE5 and CPNE9 predicts positive prognosis in multiple myeloma.Cancer biomarkers : section A of Disease markers · 2021Article
- The CPNE Family and Their Role in Cancers.Frontiers in genetics · 2021Review
- Promoting Prognostic Model Application: A Review Based on Gliomas.Journal of oncology · 2021Review
- A SEMA3 Signaling Pathway-Based Multi-Biomarker for Prediction of Glioma Patient Survival.International journal of molecular sciences · 2020Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to screen prognostic gene signature of glioblastoma (GBM) to construct prognostic model.
methodsBased on the GBM information in the Cancer Genome Atlas (TCGA, training set), prognostic genes (Set X) were screened by Cox regression. Then, the optimized prognostic gene signature (Set Y) was further screened by the Cox-Proportional Hazards (Cox-PH). Next, two prognostic models were constructed: model A was based on the Set Y; model B was based on part of the Set X. The samples were divided into low- and high-risk groups according to the median prognosis index (PI). GBM datasets in Gene Expression Ominous (GEO, GSE13041) and Chinese Glioma Genome Atlas (CGGA) were used as the testing datasets to confirm the prognostic models constructed based on TCGA.
resultsWe identified that the prognostic 14-gene signature was significantly associated with the overall survival (OS) in the TCGA. In model A, patients in high- and low-risk groups showed the significantly different OS (P = 7.47 × 10
conclusionThe prognostic model which was constructed based on the prognostic 14-gene signature presented a high predictive ability for GBM. The 14-gene signature may have clinical implications in the subclassification of GBM.
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