Literature DB >> 22490897

[Evaluation of novel gene UCA1 as a tumor biomarker for the detection of bladder cancer].

Zheng Zhang1, Han Hao, Cui-jian Zhang, Xin-yu Yang, Qun He, Jian Lin.   

Abstract

OBJECTIVE: To evaluate the clinical utility of novel gene urothelial carcinoma antigen 1 (UCA1) as a urinary tumor marker for the diagnosis of bladder urothelial carcinoma.
METHODS: A cohort of 180 cases of bladder cancer (including 94 cases in previous study), 144 cases of non-bladder-cancer individuals as control group (including 85 cases in previous study) from 2005 to 2009 were recruited. Reverse transcription PCR (RT-PCR) of urinary sediments was performed to detect the expression of UCA1. RNasin was added to the urinary sediments collected after 2007 from 86 cases of bladder cancer and 59 cases in control group to improve the quantity and quality of RNA isolation. The parameters of sensitivity, specificity, area under curve (AUC) of ROC and its 95%CI were calculated.χ(2) test was used to compare the sensitivity of UCA1 with NMP22 and cytology in 116 cases of bladder cancer with the parallel data of UCA1 and NMP22 and in 108 cases with the parallel data of UCA1 and cytology.
RESULTS: 95.4% of RNA was isolated successfully from urinary sediments after the addition of RNasin UCA1 was highly specific (92.4%, 133/144) and quite sensitive (84.4%, 152/180) in the diagnosis of bladder cancer with a favorable AUC-ROC of 0.898 (95%CI: 0.851 - 0.945). It was especially valuable for superficial G(2)-G(3) patients (sensitivity: 86.4%, 92.3%) at a high risk for muscular invasion.
CONCLUSION: With a high level of sensitivity and specificity, UCA1 is a promising urinary marker for the diagnosis of bladder cancer.

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Year:  2012        PMID: 22490897

Source DB:  PubMed          Journal:  Zhonghua Yi Xue Za Zhi        ISSN: 0376-2491


  15 in total

1.  Appraisal of diagnostic ability of UCA1 as a biomarker of carcinoma of the urinary bladder.

Authors:  A K Srivastava; P K Singh; S K Rath; D Dalela; M M Goel; M L B Bhatt
Journal:  Tumour Biol       Date:  2014-08-15

Review 2.  Long Noncoding RNAs as Innovative Urinary Diagnostic Biomarkers.

Authors:  Giulia Brisotto; Roberto Guerrieri; Francesca Colizzi; Agostino Steffan; Barbara Montico; Elisabetta Fratta
Journal:  Methods Mol Biol       Date:  2021

3.  Diagnostic value of the UCA1 test for bladder cancer detection: a clinical study.

Authors:  Dina Milowich; Marie Le Mercier; Nancy De Neve; Flavienne Sandras; Thierry Roumeguere; Christine Decaestecker; Isabelle Salmon; Sandrine Rorive
Journal:  Springerplus       Date:  2015-07-16

4.  Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity.

Authors:  Xing Chen; Chenggang Clarence Yan; Cai Luo; Wen Ji; Yongdong Zhang; Qionghai Dai
Journal:  Sci Rep       Date:  2015-06-10       Impact factor: 4.379

Review 5.  The complexity of bladder cancer: long noncoding RNAs are on the stage.

Authors:  Quanan Zhang; Mo Su; Guangming Lu; Jiangdong Wang
Journal:  Mol Cancer       Date:  2013-09-05       Impact factor: 27.401

6.  Accuracy of the urine UCA1 for diagnosis of bladder cancer: a meta-analysis.

Authors:  Xiangrong Cui; Xuan Jing; Chunlan Long; Qin Yi; Jie Tian; Jing Zhu
Journal:  Oncotarget       Date:  2017-05-23

7.  LncRNADisease: a database for long-non-coding RNA-associated diseases.

Authors:  Geng Chen; Ziyun Wang; Dongqing Wang; Chengxiang Qiu; Mingxi Liu; Xing Chen; Qipeng Zhang; Guiying Yan; Qinghua Cui
Journal:  Nucleic Acids Res       Date:  2012-11-21       Impact factor: 16.971

8.  Long Non-Coding RNAs Embedded in the Rb and p53 Pathways.

Authors:  Murugan Subramanian; Matthew F Jones; Ashish Lal
Journal:  Cancers (Basel)       Date:  2013-12-04       Impact factor: 6.639

Review 9.  Long Non-coding RNAs in Urologic Malignancies: Functional Roles and Clinical Translation.

Authors:  Jiajia Chen; Zhijun Miao; Boxin Xue; Yuxi Shan; Guobin Weng; Bairong Shen
Journal:  J Cancer       Date:  2016-08-15       Impact factor: 4.207

Review 10.  Long non-coding RNAs and complex diseases: from experimental results to computational models.

Authors:  Xing Chen; Chenggang Clarence Yan; Xu Zhang; Zhu-Hong You
Journal:  Brief Bioinform       Date:  2017-07-01       Impact factor: 11.622

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