In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 74, No. 19_Supplement ( 2014-10-01), p. 2487-2487
Abstract:
Lung cancer is the leading cause of cancer-related mortality worldwide. Comprehensive genetic studies revealed multiple subgroups of lung cancer of which each comprises a distinct mutational pattern. Moreover, it was shown that genetic alterations in genes encoding for kinases like EGFR and ALK induce constitutive kinase activity which in turn makes these kinases promising drug targets. However, as the correlation between genetic alterations and protein-expression/ -activity is strongly influenced by co- and post-transcriptional as well as post-translational regulation, we characterized a broad panel of lung cancer cell lines and primary patient-derived lung cancer tissues by quantitative proteomic techniques to identify diagnostic biomarkers and potential drug targets. To this end we established a work-flow to extract large amounts of proteins from formalin fixed paraffin embedded (FFPE) tissues by using the FASP method. Purified proteins were subsequently subjected to a Super-SILAC-based experimental set-up that allows for identification and quantification of thousands of proteins and their post-translational modifications by high-end mass spectrometry. In this study we quantitatively characterized the proteomes of 60 FFPE lung cancer specimens and 20 lung cancer cell lines including squamous cell carcinoma, adenocarcinoma and small cell carcinoma of the lung, and moreover squamous cell carcinoma metastases derived from head-neck tumors and adenocarcinoma metastases from colorectal cancer in the lung. Using the Super-SILAC-based mass spectrometric approach we were able to identify and quantify around 4000 proteins per sample. Unsupervised clustering- and principal component analyses revealed that the detected protein expression patterns show a strong correlation with the histological subtypes of lung cancer. Furthermore, also squamous cell cancer metastases could be distinguished from primary lung cancers with similar histological morphology using their protein expression profiles. Collectively, this study provides a large set of proteomic biomarkers that can be used in future to improve lung cancer diagnostics including the discrimination of metastases in the lung. In particular the differential diagnosis of squamous cell carcinoma/metastases in the lung which was so far difficult due to a lack of appropriate biomarkers will be improved by the biomarker panels presented here. Moreover, the expression patterns of kinases discovered in our study is of interest regarding potential novel lung cancer therapies as overexpression of kinases such as FGFR can contribute to the malignant phenotype of lung cancer cells. Citation Format: Hanibal Bohnenberger, Philipp Ströbel, Hannah Henric-Petri, Christof Lenz, Alexander Emmert, Felix Bremmer, Jasmin Strecker, Rainer Holland, Marc Hinterthaner, Jasmin Corso, Sebastian Wagner, Stefan Küffer, Martin Sebastian, Lothar Bergmann, Bernd Danner, Friedrich A. Schöndube, Henning Urlaub, Hubert Serve, Thomas Oellerich. Comprehensive quantitative proteomic profiling of lung cancers reveals novel biomarkers and potential drug targets. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2487. doi:10.1158/1538-7445.AM2014-2487
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2014-2487
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2014
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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