Literature DB >> 26396676

Development of a test to identify bladder cancer in the urine of patients using mass spectroscopy and subcellular localization of the detected proteins.

Stephen W Wilz1, Dong Liu2, Chaoxu Liu2, Jinghua Yang2.   

Abstract

The survival rate for bladder cancer is much better when the disease is detected early, so improvements in methodology for early detection would be beneficial. When urine contains neoplastic urothelial cells, it carries biomarkers of the disease. This study aims to develop a test for the detection of urothelial carcinoma in the urine. The sediments from urines of ten patients with carcinoma and ten randomly selected normal controls were tested for cancer biomarkers using high-resolution mass spectroscopy. 212 unique individual proteins were identified. Most of them occurred only once or twice in the entire cohort of cases. When sorting the detected proteins by their subcellular compartments, we were able to develop a test that differentiates between the two sets. When the combination of nuclear and red blood cell proteins was used as the discriminating function, the level of statistical significance was p=0.003, the sensitivity was 90%, the specificity 67% and the area under the Receiver-Operating Characteristic curve (ROC) was 94%. When the lack of any detectible proteins, which includes nuclear proteins, was included as a criterion indicating benign urine, the specificity increased to 80%. This use of cellular compartment localization of the detected proteins in the discriminating function is less restrictive than requiring the presence of specific proteins, and we were able to develop a screening test with this less stringent criterion. This approach can be applied to other tumors, such as breast, lung and colon cancers, where the need for a simple screening test is even greater.

Entities:  

Keywords:  Bladder cancer; mass spectroscopy; urine; urothelial carcinoma

Year:  2015        PMID: 26396676      PMCID: PMC4568801     

Source DB:  PubMed          Journal:  Am J Transl Res            Impact factor:   4.060


  33 in total

Review 1.  Proteomics: current techniques and potential applications to lung disease.

Authors:  Jan Hirsch; Kirk C Hansen; Alma L Burlingame; Michael A Matthay
Journal:  Am J Physiol Lung Cell Mol Physiol       Date:  2004-07       Impact factor: 5.464

2.  High-resolution serum proteomic features for ovarian cancer detection.

Authors:  T P Conrads; V A Fusaro; S Ross; D Johann; V Rajapakse; B A Hitt; S M Steinberg; E C Kohn; D A Fishman; G Whitely; J C Barrett; L A Liotta; E F Petricoin; T D Veenstra
Journal:  Endocr Relat Cancer       Date:  2004-06       Impact factor: 5.678

3.  SILAC-based proteomic analysis to dissect the "histone modification signature" of human breast cancer cells.

Authors:  Alessandro Cuomo; Simona Moretti; Saverio Minucci; Tiziana Bonaldi
Journal:  Amino Acids       Date:  2010-07-09       Impact factor: 3.520

4.  Serum proteomic patterns for detection of prostate cancer.

Authors:  Emanuel F Petricoin; David K Ornstein; Cloud P Paweletz; Ali Ardekani; Paul S Hackett; Ben A Hitt; Alfredo Velassco; Christian Trucco; Laura Wiegand; Kamillah Wood; Charles B Simone; Peter J Levine; W Marston Linehan; Michael R Emmert-Buck; Seth M Steinberg; Elise C Kohn; Lance A Liotta
Journal:  J Natl Cancer Inst       Date:  2002-10-16       Impact factor: 13.506

5.  Use of proteomic patterns in serum to identify ovarian cancer.

Authors:  Emanuel F Petricoin; Ali M Ardekani; Ben A Hitt; Peter J Levine; Vincent A Fusaro; Seth M Steinberg; Gordon B Mills; Charles Simone; David A Fishman; Elise C Kohn; Lance A Liotta
Journal:  Lancet       Date:  2002-02-16       Impact factor: 79.321

6.  Comparative analysis of the membrane proteome of closely related metastatic and nonmetastatic tumor cells.

Authors:  Christoph Roesli; Beatrice Borgia; Christoph Schliemann; Maja Gunthert; Heidi Wunderli-Allenspach; Raffaella Giavazzi; Dario Neri
Journal:  Cancer Res       Date:  2009-06-02       Impact factor: 12.701

7.  An integrated approach to the detection of colorectal cancer utilizing proteomics and bioinformatics.

Authors:  Jie-Kai Yu; Yi-Ding Chen; Shu Zheng
Journal:  World J Gastroenterol       Date:  2004-11-01       Impact factor: 5.742

Review 8.  The application of SELDI-TOF-MS in clinical diagnosis of cancers.

Authors:  Chibo Liu
Journal:  J Biomed Biotechnol       Date:  2011-05-23

9.  Discovery of tumor markers for gastric cancer by proteomics.

Authors:  Jeng-Yih Wu; Chun-Chia Cheng; Jaw-Yuan Wang; Deng-Chyang Wu; Jan-Sing Hsieh; Shui-Cheng Lee; Wen-Ming Wang
Journal:  PLoS One       Date:  2014-01-03       Impact factor: 3.240

10.  Mass spectrometry-based proteomics for the analysis of chromatin structure and dynamics.

Authors:  Monica Soldi; Alessandro Cuomo; Michael Bremang; Tiziana Bonaldi
Journal:  Int J Mol Sci       Date:  2013-03-06       Impact factor: 5.923

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  3 in total

1.  Detection of Bladder Cancer in Urine Sediments by a Novel Multicolor Fluorescence In Situ Hybridization (Quartet) Test.

Authors:  Shizhen Zhang; Yan Wang; Jolanta Bondaruk; Tadeusz Majewski; Hui Yao; Sangkyou Lee; June Goo Lee; David Cogdell; Yair Lotan; Colin Dinney; Peng Wei; Keith Baggerly; Bogdan Czerniak
Journal:  Eur Urol Focus       Date:  2018-02-07

2.  Discoidin domain receptor 1 activity drives an aggressive phenotype in bladder cancer.

Authors:  Xin Xie; Wenbin Rui; Wei He; Yuan Shao; Fukang Sun; Wenlong Zhou; Yuxuan Wu; Yu Zhu
Journal:  Am J Transl Res       Date:  2017-05-15       Impact factor: 4.060

Review 3.  Proteomics and peptidomics: moving toward precision medicine in urological malignancies.

Authors:  Ashley Di Meo; Maria D Pasic; George M Yousef
Journal:  Oncotarget       Date:  2016-08-09
  3 in total

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