Dataset Information

Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples.

ABSTRACT: 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.

SUBMITTER: Zhou BF

PROVIDER: S-EPMC5173089 | biostudies-other | 2016 Jul

REPOSITORIES: biostudies-other

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Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples.

Zhou Bang-Fen BF Wei Jin-Huan JH Chen Zhen-Hua ZH Dong Pei P Lai Ying-Rong YR Fang Yong Y Jiang Hui-Ming HM Lu Jun J Zhou Fang-Jian FJ Xie Dan D Luo Jun-Hang JH Chen Wei W

Oncotarget 20160701 27

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, ...[more]

PMID: 27203388

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Project description:Purpose:Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ?7) in a Russian cohort. Patients and Methods:We analyzed urine samples of patients with a total serum PSA ?2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3, AMACR, PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis. Results:There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p=0.0088, prebiopsy cohort p=0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511-0.752), the AMACR score AUC was 0.711 (95%CI: 0.617-0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58-0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p=6.542e-09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Conclusion:The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.

Project description:Background: Current standard methods used to detect and monitor bladder cancer (BC) are invasive or have low sensitivity. We have previously reported in an international European study four non-invasive tests for BC diagnosis based on the gene expression patterns of urine. Objective: to validate the tests in an independent Asian cohort. Design, setting and participants: Prospective blinded study in which consecutive voided urine samples from BC patients and controls (n=520) were collected in the Fudan University Shanghai Cancer Center from 2014-2016. Gene expression values were quantified using TaqMan Arrays. The same cut-off as previously reported for discrimination between tumours and controls was used in this validation study. Results and limitations: Finally, a total of 257 tumour and 132 control urine samples were analysed. We found a high accuracy for the four gene classifiers in this independent Asian set, the classifiers composed of 5 and 10 genes achieved the best sensitivity (80.54% and 81.32%, respectively) maintaining a high specificity (91.67% and 85.61%, respectively). Sensitivity of 5-gene (GS_D5) and 10-gene (GS_D10) expression classifiers in recurrent BC cases (78 and 79%, respectively) is comparable to that of primary BC cases (82%). Cytology and NMP22 identified 67% and 40%, respectively, of tumours that have been diagnosed with our tests. In addition, influence of each studied gene was analyzed and showed similar gene rank between Chinese and Caucasian population. Conclusions: Our study proves that our non-invasive diagnostic BC tests can be reproduced in independent cohorts and in an external laboratory. All the four gene classifiers have shown equal or superior performance to the current gold standard in the present and previously reported validation studies. Consequently, they may be taken for consideration as molecular tests applicable to clinical practice in the management of BC. Patient summary: Our gene classifiers achieve sensitivities up to 90% in HR NMIBC and MIBC patients, while this achievement is comparatively lower in LR NMIBC ones.

Dataset Information

Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples.

Publications

Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples.

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