Geburtshilfe Frauenheilkd 2008; 68 - FV_Onko_02_16
DOI: 10.1055/s-0028-1088688

Expression of VEGFR and PDGFR in ovarian cancer tissue in the era of tryosine kinase inhibitors (TKI)

DO Bauerschlag 1, D Schaaf 1, C Schem 2, I Meinhold-Heerlein 1, W Jonat 1, N Maass 2
  • 1Klinik für Gynäkologie und Geburtshilfe, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Kiel
  • 2Universitätsfrauenklinik Kiel, UK-SH, Campus Kiel, Kiel

Aims:

TKI are newly emerging drugs rushing into daily clinical use. Vascular endothelial growth factor receptor (VEGFR) and platelet derived growth factor (PDGFR) are prevalent targets of small molecules which precisely block TKI activation. In ovarian cancer the expression levels of these receptors could be indicative for the use of TKI.

Material and Method:

98 ovarian cancer tissues were arranged in a tissue micro array and stained with monoclonal antibodies directed against VEGF-R1,-R2 and PDGFR-α and -β. Protein expression levels were scored using an IRS scoring system. Expression levels were correlated to tumor biological factors.

Results:

VEGF-R1,–2 and PDGFR-α were generally expressed across the entire set within the tumor areas; however the staining for PDGFR-β was negative. We did find a statistical significant correlation between grading and VEGFR–2 expression, showing higher expression for G1 and G2 differentiated tumors when compared to G3 tumors. The PDGFR-α expression was significantly higher in poorly differentiated tumors.

Conclusion:

VEGFR–1 and 2 are expressed in ovarian cancers, as well as PDGFR-α. We did find a statistical significant correlation between grading and VEGFR–2 expression as well as between PDGFR- α and grading. These findings allow two interpretations, first inhibitors of VEGFR and PDGFR could be used in the treatment of ovarian cancer because the TKI are expressed. Secondly, although we do find significant correlations the solely determination of protein levels might by not accurate enough to classify tumors to predict potential response. In cases of resistance to TKI other techniques such as SNP analysis could be of great information.