Literature DB >> 19610612

Differential protein expressions in renal cell carcinoma: new biomarker discovery by mass spectrometry.

K W Michael Siu1, Leroi V DeSouza, Andreas Scorilas, Alexander D Romaschin, R John Honey, Robert Stewart, Kenneth Pace, Youssef Youssef, Tsz-fung F Chow, George M Yousef.   

Abstract

Renal cell carcinoma (RCC) is the most common neoplasm in the adult kidney. Unfortunately, there are currently no biomarkers for the diagnosis of RCC. In addition to early detection, biomarkers have a potential use for prognosis, for monitoring recurrence after treatment, and as predictive markers for treatment efficiency. In this study, we identified proteins that are dysregulated in RCC, utilizing a quantitative mass spectrometry analysis. We compared the protein expression of kidney cancer tissues to their normal counterparts from the same patient using LC-MS/MS. iTRAQ labeling permitted simultaneous quantitative analysis of four samples (cancer, normal, and two controls) by separately tagging the peptides in these samples with four cleavable mass-tags (114, 115, 116, and 117 Da). The samples were then pooled, and the tagged peptides resolved first by strong cation exchange chromatography and then by nanobore reverse phase chromatography coupled online to nanoelectrospray MS/MS. We identified a total of 937 proteins in two runs. There was a statistically significant positive correlation of the proteins identified in both runs (r(p) = 0.695, p < 0.001). Using a cutoff value of 0.67 fold for underexpression and 1.5 fold for overexpression, we identified 168 underexpressed proteins and 156 proteins that were overexpressed in RCC compared to normal tissues. These dysregulated proteins in RCC were statistically significantly different from those of transitional cell carcinoma and end-stage glomerulonephritis. We performed an in silico validation of our results using different tools and databases including Serial Analysis of Gene Expression (SAGE), UniGene EST ProfileViewer, Cancer Genome Anatomy Project, and Gene Ontology consortium analysis.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19610612     DOI: 10.1021/pr800389e

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  30 in total

Review 1.  The Renal Gene Ontology Annotation Initiative.

Authors:  Yasmin Alam-Faruque; Emily C Dimmer; Rachael P Huntley; Claire O'Donovan; Peter Scambler; Rolf Apweiler
Journal:  Organogenesis       Date:  2010 Apr-Jun       Impact factor: 2.500

2.  Discovery and verification of gelsolin as a potential biomarker of colorectal adenocarcinoma in the Chinese population: Examining differential protein expression using an iTRAQ labelling-based proteomics approach.

Authors:  Nai-Jun Fan; Chun-Fang Gao; Chang-Song Wang; Jing-Jing Lv; Guang Zhao; Xin-Hua Sheng; Xiu-Li Wang; Dong-Hui Li; Qing-Yin Liu; Jian Yin
Journal:  Can J Gastroenterol       Date:  2012-01       Impact factor: 3.522

3.  Alpha-enolase is a potential prognostic marker in clear cell renal cell carcinoma.

Authors:  Nicole M White-Al Habeeb; Ashley Di Meo; Andreas Scorilas; Fabio Rotondo; Olena Masui; Annetta Seivwright; Manal Gabril; Andrew H A Girgis; Michael A Jewett; George M Yousef
Journal:  Clin Exp Metastasis       Date:  2015-06-03       Impact factor: 5.150

Review 4.  DIGE and iTRAQ as biomarker discovery tools in aquatic toxicology.

Authors:  Christopher J Martyniuk; Sophie Alvarez; Nancy D Denslow
Journal:  Ecotoxicol Environ Saf       Date:  2011-11-05       Impact factor: 6.291

5.  Expression, circulation, and excretion profile of microRNA-21, -155, and -18a following acute kidney injury.

Authors:  Janani Saikumar; Dana Hoffmann; Tae-Min Kim; Victoria Ramirez Gonzalez; Qin Zhang; Peter L Goering; Ronald P Brown; Vanesa Bijol; Peter J Park; Sushrut S Waikar; Vishal S Vaidya
Journal:  Toxicol Sci       Date:  2012-06-15       Impact factor: 4.849

6.  Quantitative tissue proteomics of esophageal squamous cell carcinoma for novel biomarker discovery.

Authors:  Harsh Pawar; Manoj Kumar Kashyap; Nandini A Sahasrabuddhe; Santosh Renuse; H C Harsha; Praveen Kumar; Jyoti Sharma; Kumaran Kandasamy; Arivusudar Marimuthu; Bipin Nair; Sudha Rajagopalan; Jagadeesha Maharudraiah; Chennagiri Shrinivasamurthy Premalatha; Kariyanakatte Veeraiah Veerendra Kumar; M Vijayakumar; Raghothama Chaerkady; Thotterthodi Subrahmanya Keshava Prasad; Rekha V Kumar; Rekha V Kumar; Akhilesh Pandey
Journal:  Cancer Biol Ther       Date:  2011-09-15       Impact factor: 4.742

7.  Linkage of microRNA and proteome-based profiling data sets: a perspective for the priorization of candidate biomarkers in renal cell carcinoma?

Authors:  Barbara Seliger; Simon Jasinski; Sven P Dressler; Francesco M Marincola; Christian V Recktenwald; Ena Wang; Rudolf Lichtenfels
Journal:  J Proteome Res       Date:  2011-01-07       Impact factor: 4.466

8.  Protein composition of bronchoalveolar lavage fluid and airway surface liquid from newborn pigs.

Authors:  Jennifer A Bartlett; Matthew E Albertolle; Christine Wohlford-Lenane; Alejandro A Pezzulo; Joseph Zabner; Richard K Niles; Susan J Fisher; Paul B McCray; Katherine E Williams
Journal:  Am J Physiol Lung Cell Mol Physiol       Date:  2013-05-24       Impact factor: 5.464

9.  Imaging the clear cell renal cell carcinoma proteome.

Authors:  Todd M Morgan; Erin H Seeley; Oluwole Fadare; Richard M Caprioli; Peter E Clark
Journal:  J Urol       Date:  2012-09-23       Impact factor: 7.450

10.  Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance.

Authors:  Olena Masui; Nicole M A White; Leroi V DeSouza; Olga Krakovska; Ajay Matta; Shereen Metias; Bishoy Khalil; Alexander D Romaschin; R John Honey; Robert Stewart; Kenneth Pace; Georg A Bjarnason; K W Michael Siu; George M Yousef
Journal:  Mol Cell Proteomics       Date:  2012-10-17       Impact factor: 5.911

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.