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- Publisher Website: 10.1016/j.radonc.2015.07.024
- Scopus: eid_2-s2.0-84946482759
- PMID: 26253951
- WOS: WOS:000364247700013
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Article: Use a survival model to correlate single-nucleotide polymorphisms of DNA repair genes with radiation dose-response in patients with non-small cell lung cancer
Title | Use a survival model to correlate single-nucleotide polymorphisms of DNA repair genes with radiation dose-response in patients with non-small cell lung cancer |
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Authors | |
Keywords | Radiosensitivity Dose survival model Biomarker Single-nucleotide-polymorphisms (SNPs) Personalized radiotherapy ERCC1 and ERCC2 |
Issue Date | 2015 |
Citation | Radiotherapy and Oncology, 2015, v. 117, n. 1, p. 77-82 How to Cite? |
Abstract | © 2015 Elsevier Ireland Ltd. All rights reserved. Purpose This study utilizes a survival model and clinical data with various radiation doses from prospective trials to determine radiation dose-response parameters, such as radiosensitivity, and identify single-nucleotide-polymorphism (SNP) biomarkers that can potentially predict the dose response and guide personalized radiotherapy. Methods The study included 92 consecutive stage-III NSCLC patients with doses varying from 60 to 91 Gy. Logistic regression analysis of survival varying with SNP genotype and radiation dose was used to screen candidates for dose-response analysis. The dose-response parameter, represented by D50, was derived by fitting survival data into a model that takes into account both tumor control and treatment mortality. A candidate would be considered as a predictor if the 90% confident intervals (90% CIs) of D50for the 2 groups stratified by the SNP genotype were separated. Results One SNP-signature (combining ERCC2:rs238406 and ERCC1:rs11615) was found to predict dose-response. D50values are 63.7 (90% CI: 53.5-66.3) Gy and 76.1 (90% CI: 71.3, 84.6) Gy for the 2 groups stratified by the genotypes. Using this biomarker-based model, a personalized dose prescription may be generated to improve 2-year survival from ∼50% to 85% and ∼3% to 73% for hypothetical sensitive and resistant patients, respectively. Conclusions We have developed a survival model that may be used to identify genomic markers, such as ERCC1/2 SNPs, to predict radiation dose-response and potentially guide personalized radiotherapy. |
Persistent Identifier | http://hdl.handle.net/10722/267015 |
ISSN | 2023 Impact Factor: 4.9 2023 SCImago Journal Rankings: 1.702 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Jin, Jian Yue | - |
dc.contributor.author | Wang, Weili | - |
dc.contributor.author | Ten Haken, Randall K. | - |
dc.contributor.author | Chen, Jie | - |
dc.contributor.author | Bi, Nan | - |
dc.contributor.author | Sadek, Ramses | - |
dc.contributor.author | Zhang, Hong | - |
dc.contributor.author | Lawrence, Theodore S. | - |
dc.contributor.author | Kong, F. M. | - |
dc.date.accessioned | 2019-01-31T07:20:15Z | - |
dc.date.available | 2019-01-31T07:20:15Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Radiotherapy and Oncology, 2015, v. 117, n. 1, p. 77-82 | - |
dc.identifier.issn | 0167-8140 | - |
dc.identifier.uri | http://hdl.handle.net/10722/267015 | - |
dc.description.abstract | © 2015 Elsevier Ireland Ltd. All rights reserved. Purpose This study utilizes a survival model and clinical data with various radiation doses from prospective trials to determine radiation dose-response parameters, such as radiosensitivity, and identify single-nucleotide-polymorphism (SNP) biomarkers that can potentially predict the dose response and guide personalized radiotherapy. Methods The study included 92 consecutive stage-III NSCLC patients with doses varying from 60 to 91 Gy. Logistic regression analysis of survival varying with SNP genotype and radiation dose was used to screen candidates for dose-response analysis. The dose-response parameter, represented by D50, was derived by fitting survival data into a model that takes into account both tumor control and treatment mortality. A candidate would be considered as a predictor if the 90% confident intervals (90% CIs) of D50for the 2 groups stratified by the SNP genotype were separated. Results One SNP-signature (combining ERCC2:rs238406 and ERCC1:rs11615) was found to predict dose-response. D50values are 63.7 (90% CI: 53.5-66.3) Gy and 76.1 (90% CI: 71.3, 84.6) Gy for the 2 groups stratified by the genotypes. Using this biomarker-based model, a personalized dose prescription may be generated to improve 2-year survival from ∼50% to 85% and ∼3% to 73% for hypothetical sensitive and resistant patients, respectively. Conclusions We have developed a survival model that may be used to identify genomic markers, such as ERCC1/2 SNPs, to predict radiation dose-response and potentially guide personalized radiotherapy. | - |
dc.language | eng | - |
dc.relation.ispartof | Radiotherapy and Oncology | - |
dc.subject | Radiosensitivity | - |
dc.subject | Dose survival model | - |
dc.subject | Biomarker | - |
dc.subject | Single-nucleotide-polymorphisms (SNPs) | - |
dc.subject | Personalized radiotherapy | - |
dc.subject | ERCC1 and ERCC2 | - |
dc.title | Use a survival model to correlate single-nucleotide polymorphisms of DNA repair genes with radiation dose-response in patients with non-small cell lung cancer | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.radonc.2015.07.024 | - |
dc.identifier.pmid | 26253951 | - |
dc.identifier.scopus | eid_2-s2.0-84946482759 | - |
dc.identifier.volume | 117 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 77 | - |
dc.identifier.epage | 82 | - |
dc.identifier.eissn | 1879-0887 | - |
dc.identifier.isi | WOS:000364247700013 | - |
dc.identifier.issnl | 0167-8140 | - |