Protein expression patterns in primary carcinoma of the vagina View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2004-07

AUTHORS

K Hellman, A A Alaiya, K Schedvins, W Steinberg, A-C Hellström, G Auer

ABSTRACT

Protein patterns in six samples from primary vaginal cancers, in five from normal vaginal tissue and in five primary cervical cancers, were analysed using two-dimensional polyacrylamide gel electrophoresis (2-DE). Protein expression profile was evaluated by computer-assisted image analysis (PDQUEST) and proteins were subsequently identified using matrix-assisted laser desorption/ionisation mass spectrometry. The aim was to analyse the protein expression profiles using the hierarchical clustering method in vaginal carcinoma and to compare them with the protein pattern in cervical carcinoma in order to find a helpful tool for correct classification and for increased biomedical knowledge. Protein expression data of a distinct set of 33 protein spots were differentially expressed. These differences were statistically significant (Mann-Whitney signed-Ranked Test, P<0.05) between normal tissue, vaginal and cervical cancer. Furthermore, protein profiles of pairs of primary vaginal and cervical cancers were found to be very similar. Some of the protein spots that have so far been identified include Tropomyosin 1, cytokeratin 5, 15 and 17, Apolipoprotein A1, Annexin V, Glutathione-S-transferase. Others are the stress-related proteins, calreticulin, HSP 27 and HSP 70. We conclude that cluster analysis of proteomics data allows accurate discrimination between normal vaginal mucosa, primary vaginal and primary cervical cancer. However, vaginal and cervical carcinomas also appear to be relatively homogeneous in their gene expression, indicating similar carcinogenic pathways. There might, further, be a possibility to identify tumour-specific markers among the proteins that are differentially expressed. The results from this study have to be confirmed by more comprehensive studies in the future. More... »

PAGES

319

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/sj.bjc.6601944

DOI

http://dx.doi.org/10.1038/sj.bjc.6601944

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029972850

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/15199389


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