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Diagnostic protein marker patterns in squamous cervical cancer
Author(s) -
Lomnytska Marta I.,
Becker Susanne,
Hellman Kristina,
Hellström AnnCathrin,
Souchelnytskyi Serhiy,
Mints Miriam,
Hellman Ulf,
Andersson Sonia,
Auer Gert
Publication year - 2010
Publication title -
proteomics – clinical applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.948
H-Index - 54
eISSN - 1862-8354
pISSN - 1862-8346
DOI - 10.1002/prca.200900086
Subject(s) - cytokeratin , malignancy , cancer , cervical cancer , pathology , squamous carcinoma , medicine , immunohistochemistry , biology , cancer research , carcinoma
Purpose: Cervical cancer is the second most prevalent malignancy of women. Our aim was to identify additional marker protein patterns for objective diagnosis of squamous cervical cancer (SCC). Experimental design: Collected tissue biopsies of SCC, squamous vaginal cancer (SVC), normal cervical and vaginal mucosa were subjected to 2‐DE, SameSpot analysis, MALDI‐TOF‐MS protein identification, and analysis of the expression of selected proteins by immunohistochemistry. Results: In 148 protein spots selected by the difference in expression 99 proteins were identified. A differential protein pattern for SCC was, e.g. over‐expressed (OE) eukaryotic translation initiation factor 3‐2β, neutrophil cytosolic factor 2, annexin A6 (ANXA6), for SVC it was OE cathepsin D, γ‐catenin, RAB2A, for both cancers it was OE apolipoprotein E, tropomyosin 3, HSPA8, and underexpressed cytokeratin 13, osteoglycin. In SCC nuclear expression of neutrophil cytosolic factor 2, PRDX2, HSP27 (nine of ten cases), ANXA6 (nine of ten cases) was observed while tropomyosin 4 was expressed only in two of ten cases. There was 81.1% (43/53) agreement between the expression of protein spots and the immune expression of proteins ( www.proteinatlas.org ). Conclusions and clinical relevance: SCC is characterized by specific tissue marker protein patterns that allow objective detection of the disease. They can become a basis for objective automated cytology‐based screening and improve current diagnostics of SCC.