de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Protein expression profiles in adenocarcinomas and squamous cell carcinomas of the lung generated using tissue microarrays

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50606

Ullmann,  Reinhard
Molecular Cytogenetics (Reinhard Ullmann), Dept. of Human Molecular Genetics (Head: Hans-Hilger Ropers), Max Planck Institute for Molecular Genetics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Ullmann, R., Morbini, P., Halbwedl, I., Bongiovanni, M., Gogg-Kammerer, M., Papotti, M., et al. (2004). Protein expression profiles in adenocarcinomas and squamous cell carcinomas of the lung generated using tissue microarrays. Journal of Pathology: an Official Journal of the Pathological Society, 203(3), 798-807. doi:10.1002/path.1584.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-8804-7
Abstract
With the appearance of defect-targeted therapies, the definition of tumour protein expression profiles has gained increasing importance. Two lung carcinoma tissue microarrays, one including 75 primary adenocarcinomas (ACs) and the other comprising 67 primary squamous cell carcinomas (SQCCs), were generated in the present study. On both arrays, each tumour was represented by an average of five cores. In addition, one punch of normal lung parenchyma adjacent to each tumour was included in the array. Immunohistochemical expression of 86 proteins was evaluated and the results were analysed by non-parametric tests, hierarchical clustering, and principal component analysis. In both tumour entities, parenchyma and tumours were clearly separated by hierarchical clustering. By the same statistical approach, it was possible to distinguish ACs from SQCCs with 98% accuracy and to distinguish parenchyma adjacent to ACs from that adjacent to SQCCs with 96% accuracy. It was also possible to separate ACs into three groups that significantly differed in survival. Cathepsin E and hsp105 were identified as previously unknown predictors of survival in lung AC. In summary, this study has shown that protein profiles are feasible tools for anticipating biological behaviour. Copyright © 2004 Pathological Society of Great Britain and Ireland.