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Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples
We previously demonstrated that amplified in breast cancer 1 (AIB1) and eukaryotic initiation factor 2 (EIF5A2) overexpression was an independent predictor of poor clinical outcomes for patients with bladder cancer (BCa). In this study, we evaluated the usefulness of AIB1 and EIF5A2 alone and in com...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5173089/ https://www.ncbi.nlm.nih.gov/pubmed/27203388 http://dx.doi.org/10.18632/oncotarget.9406 |
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author | Zhou, Bang-Fen Wei, Jin-Huan Chen, Zhen-Hua Dong, Pei Lai, Ying-Rong Fang, Yong Jiang, Hui-Ming Lu, Jun Zhou, Fang-Jian Xie, Dan Luo, Jun-Hang Chen, Wei |
author_facet | Zhou, Bang-Fen Wei, Jin-Huan Chen, Zhen-Hua Dong, Pei Lai, Ying-Rong Fang, Yong Jiang, Hui-Ming Lu, Jun Zhou, Fang-Jian Xie, Dan Luo, Jun-Hang Chen, Wei |
author_sort | Zhou, Bang-Fen |
collection | PubMed |
description | We previously demonstrated that amplified in breast cancer 1 (AIB1) and eukaryotic initiation factor 2 (EIF5A2) overexpression was an independent predictor of poor clinical outcomes for patients with bladder cancer (BCa). In this study, we evaluated the usefulness of AIB1 and EIF5A2 alone and in combination with nuclear matrix protein 22 (NMP22) as noninvasive diagnostic tests for BCa. Using urine samples from 135 patients (training set, controls [n = 50] and BCa [n = 85]), we detected the AIB1, EIF5A2, and NMP22 concentrations using enzyme-linked immunosorbent assay. We applied multivariate logistic regression analysis to build a model based on the three biomarkers for BCa diagnosis. The diagnostic accuracy of the three biomarkers and the model were assessed and compared by the area under the curve (AUC) of the receiver operating characteristic. We validated the diagnostic accuracy of these biomarkers and the model in an independent validation cohort of 210 patients. In the training set, urinary concentrations of AIB1, EIF5A2, and NMP22 were significantly elevated in BCa. The AUCs of AIB1, EIF5A2, NMP22, and the model were 0.846, 0.761, 0.794, and 0.919, respectively. The model had the highest diagnostic accuracy when compared with AIB1, EIF5A2, or NMP22 (p < 0.05 for all). The model had 92% sensitivity and 92% specificity. We obtained similar results in the independent validation cohort. AIB1 and EIF5A2 show promise for the noninvasive detection of BCa. The model based on AIB1, EIF5A2, and NMP22 outperformed each of the three individual biomarkers for detecting BCa. |
format | Online Article Text |
id | pubmed-5173089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-51730892016-12-23 Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples Zhou, Bang-Fen Wei, Jin-Huan Chen, Zhen-Hua Dong, Pei Lai, Ying-Rong Fang, Yong Jiang, Hui-Ming Lu, Jun Zhou, Fang-Jian Xie, Dan Luo, Jun-Hang Chen, Wei Oncotarget Research Paper We previously demonstrated that amplified in breast cancer 1 (AIB1) and eukaryotic initiation factor 2 (EIF5A2) overexpression was an independent predictor of poor clinical outcomes for patients with bladder cancer (BCa). In this study, we evaluated the usefulness of AIB1 and EIF5A2 alone and in combination with nuclear matrix protein 22 (NMP22) as noninvasive diagnostic tests for BCa. Using urine samples from 135 patients (training set, controls [n = 50] and BCa [n = 85]), we detected the AIB1, EIF5A2, and NMP22 concentrations using enzyme-linked immunosorbent assay. We applied multivariate logistic regression analysis to build a model based on the three biomarkers for BCa diagnosis. The diagnostic accuracy of the three biomarkers and the model were assessed and compared by the area under the curve (AUC) of the receiver operating characteristic. We validated the diagnostic accuracy of these biomarkers and the model in an independent validation cohort of 210 patients. In the training set, urinary concentrations of AIB1, EIF5A2, and NMP22 were significantly elevated in BCa. The AUCs of AIB1, EIF5A2, NMP22, and the model were 0.846, 0.761, 0.794, and 0.919, respectively. The model had the highest diagnostic accuracy when compared with AIB1, EIF5A2, or NMP22 (p < 0.05 for all). The model had 92% sensitivity and 92% specificity. We obtained similar results in the independent validation cohort. AIB1 and EIF5A2 show promise for the noninvasive detection of BCa. The model based on AIB1, EIF5A2, and NMP22 outperformed each of the three individual biomarkers for detecting BCa. Impact Journals LLC 2016-05-17 /pmc/articles/PMC5173089/ /pubmed/27203388 http://dx.doi.org/10.18632/oncotarget.9406 Text en Copyright: © 2016 Zhou et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Zhou, Bang-Fen Wei, Jin-Huan Chen, Zhen-Hua Dong, Pei Lai, Ying-Rong Fang, Yong Jiang, Hui-Ming Lu, Jun Zhou, Fang-Jian Xie, Dan Luo, Jun-Hang Chen, Wei Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples |
title | Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples |
title_full | Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples |
title_fullStr | Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples |
title_full_unstemmed | Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples |
title_short | Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples |
title_sort | identification and validation of aib1 and eif5a2 for noninvasive detection of bladder cancer in urine samples |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5173089/ https://www.ncbi.nlm.nih.gov/pubmed/27203388 http://dx.doi.org/10.18632/oncotarget.9406 |
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