ArticleBMC genomics2012
Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 2 of them syntheses that pooled it.
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Who cites it
89 citing papers in PubMed, 2 syntheses or guidelines pooled it, 135 citations in OpenAlex.
- Robustness of Clonogenic Assays as a Biomarker for Cancer Cell Radiosensitivity.International journal of molecular sciences · 2019Pooled it
- Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis.PloS one · 2016Pooled it
- Phospholipase A2 enhances the cytotoxic activity of membranolytic peptideBiochemistry and biophysics reports · 2026Article
- Toward genomic personalization of breast cancer radiotherapy: foundations, challenges, and a roadmap for clinical integration.Breast (Edinburgh, Scotland) · 2026Review
- Identification of a Novel Radiosensitivity-Related Signature and Validation of GPX8 in Regulating the Radiosensitivity of Glioma.CNS neuroscience & therapeutics · 2026Article
- Evaluating glycolysis-associated biomarkers for radiotherapy sensitivity in head and neck squamous cancer.Frontiers in immunology · 2026Article
- Integrating Radiosensitivity Index and Radiation Resistance Related Index Improves Prostate Cancer Outcome Prediction.Advances in radiation oncology · 2025Article
- Discovery of a DNA repair-associated radiosensitivity index for predicting radiotherapy efficacy in breast cancer.Frontiers in oncology · 2025Article
- Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity.Frontiers in immunology · 2025Article
- NRG Oncology White Paper on the Relative Biological Effectiveness in Proton Therapy.International journal of radiation oncology, biology, physics · 2025Review
- Glycolysis-related radiosensitivity signature for predicting radiotherapy response in breast cancer.Frontiers in immunology · 2025Article
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- Clinical Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy: A Systematic Review.Cancers · 2024Review
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- Predicting radiotherapy efficacy and prognosis in tongue squamous cell carcinoma through an in-depth analysis of a radiosensitivity gene signature.Frontiers in oncology · 2024Article
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- A genomic score to predict local control among patients with brain metastases managed with radiation.Neuro-oncology · 2023Article
- Validation of In Vitro Trained Transcriptomic Radiosensitivity Signatures in Clinical Cohorts.Cancers · 2023Article
- Machine Learning & Molecular Radiation Tumor Biomarkers.Seminars in radiation oncology · 2023Review
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy.
resultsRadiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2 Gy (SF2, range from 0 to 1) was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2). Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM) and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway.
conclusionsIntegration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that integrin signaling via adhesion molecules could be a target for radiosensitization.
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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.