ArticleOncotarget2014
A radiosensitivity gene signature in predicting glioma prognostic via EMT pathway.
Article in Oncotarget, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
47 citing papers in PubMed.
- Clinical Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy: A Systematic Review.Cancers · 2024Review
- Understanding Glioblastoma Signaling, Heterogeneity, Invasiveness, and Drug Delivery Barriers.International journal of molecular sciences · 2023Review
- Roles of NExperimental hematology & oncology · 2022Review
- Integrating Radiosensitivity Gene Signature Improves Glioma Outcome and Radiotherapy Response Prediction.Medicina (Kaunas, Lithuania) · 2022Article
- Association of the tissue infiltrated and peripheral blood immune cell subsets with response to radiotherapy for rectal cancer.BMC medical genomics · 2022Article
- Development and validation of an immune-related gene signature for predicting the radiosensitivity of lower-grade gliomas.Scientific reports · 2022Article
- How to Improve SBRT Outcomes in NSCLC: From Pre-Clinical Modeling to Successful Clinical Translation.Cancers · 2022Review
- RadSigBench: a framework for benchmarking functional genomics signatures of cancer cell radiosensitivity.Briefings in bioinformatics · 2022Article
- Establishment of a nomogram with EMP3 for predicting clinical outcomes in patients with glioma: A bi-center study.CNS neuroscience & therapeutics · 2021Article
- Elevated Asparagine Biosynthesis Drives Brain Tumor Stem Cell Metabolic Plasticity and Resistance to Oxidative Stress.Molecular cancer research : MCR · 2021Article
- More evidence for prediction model of radiosensitivity.Bioscience reports · 2021Article
- Prognostic and predictive value of FCER1G in glioma outcomes and response to immunotherapy.Cancer cell international · 2021Article
- Developing ZNF Gene Signatures Predicting Radiosensitivity of Patients with Breast Cancer.Journal of oncology · 2021Article
- A Radiosensitivity Gene Signature and XPO1 Predict Clinical Outcomes for Glioma Patients.Frontiers in oncology · 2020Article
- Machine Learning Based on a Multiparametric and Multiregional Radiomics Signature Predicts Radiotherapeutic Response in Patients with Glioblastoma.Behavioural neurology · 2020Article
- Association between breast cancer cell migration and radiosensitivityOncology letters · 2019Article
- Proton Therapy and Src Family Kinase Inhibitor Combined Treatments on U87 Human Glioblastoma Multiforme Cell Line.International journal of molecular sciences · 2019Article
- Article
- Review
- PD-1 and PD-L1 Expression Predicts Radiosensitivity and Clinical Outcomes in Head and Neck Cancer and is Associated with HPV Infection.Journal of Cancer · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A 31-gene signature derived by integrating four different microarray experiments, has been found to have a potential for predicting radiosensitivity of cancer cells, but it was seldom validated in clinical cancer samples. We proposed that the gene signature may serve as a predictive biomarker for estimating the overall survival of radiation-treated patients. The significance of gene signature was tested in two previously published datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Altas (TCGA), respectively. In GEO data set, patients predicted to be radiosensitive(RS) had an improved overall survival when compared with radioresistant(RR) patients in either radiotherapy(RT)-treated or non radiotherapy(RT)-treated subgroups(p<0.0001 in the RT-treated group). Multivariate Cox regression analysis showed that the gene signature is the strongest predictor(p=0.0093) in the RT-treated subgroup of patients. However, it does not remain significant (p=0.7668) in non radiotherapy-treated group when adjusting for age and Karnofsky performance score (KPS) as covariates. Similarly, in the TCGA data set, radiotherapy-treated glioblastoma multiforme(GBM) patients assigned to RS group had an improved overall survival compared with RR group(p<0.0001). Geneset enrichment analysis(GSEA) analysis revealed that enrichment of epithelial mesenchymal transition(EMT) pathway was observed with radioresistant phenotype. These results suggest that the signature is a predictive biomarker for radiation-treated glioma patients' prognostic.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.