Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-53099
Ziegler, A; Cerciello, F; Bigosch, C; Bausch-Fluck, D; Felley-Bosco, E; Ossola, R; Soltermann, A; Stahel, R A; Wollscheid, B (2012). Proteomic surfaceome analysis of mesothelioma. Lung Cancer, 75(2):189-196.
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Identification of new markers for malignant pleural mesothelioma (MPM) is a challenging clinical need. Here, we propose a quantitative proteomics primary screen of the cell surface exposed MPM N-glycoproteins, which provides the basis for the development of new protein-based diagnostic assays. Using the antibody-independent mass-spectrometry based cell surface capturing (CSC) technology, we specifically investigated the N-glycosylated surfaceome of MPM towards the identification of protein-marker candidates discriminatory between MPM and lung adenocarcinoma (ADCA). Relative quantitative CSC analysis of MPM cell line ZL55 in comparison with ADCA cell line Calu-3 revealed a bird's eye view of their respective surfaceomes. In a secondary screen of fifteen MPM and six ADCA, we used high throughput low density microarrays (LDAs) to verify specificity and sensitivity of nineteen N-glycoproteins overregulated in the surfaceome of MPM. This proteo-transcriptomic approach revealed thy-1/CD90 (THY1) and teneurin-2 (ODZ2) as protein-marker candidates for the discrimination of MPM from ADCA. Thy-1/CD90 was further validated by immunohistochemistry on frozen tissue sections of MPM and ADCA samples. Together, we present a combined proteomic and transcriptomic approach enabling the relative quantitative identification and pre-clinical selection of new MPM marker candidates.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||04 Faculty of Medicine > University Hospital Zurich > Institute of Surgical Pathology|
04 Faculty of Medicine > University Hospital Zurich > Clinic for Oncology
|DDC:||610 Medicine & health|
|Deposited On:||15 Dec 2011 08:43|
|Last Modified:||29 May 2014 17:24|
|Citations:||Web of Science®. Times Cited: 7|
Scopus®. Citation Count: 8
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