While
ovarian cancer remains the most lethal gynecological
malignancy in the United States, there are no
biomarkers available that are able to predict therapeutic responses to ovarian
malignancies. One major hurdle in the identification of useful
biomarkers has been the ability to obtain enough
ovarian cancer cells from primary tissues diagnosed in the early stages of serous
carcinomas, the most deadly subtype of ovarian
tumor. In order to detect
ovarian cancer in a state of hyperproliferation, we analyzed the implications of molecular signaling cascades in the
ovarian cancer cell line OVCAR3 in a temporal manner, using a mass-spectrometry-based proteomics approach. OVCAR3 cells were treated with
EGF(1), and the time course of cell progression was monitored based on Akt phosphorylation and growth dynamics.
EGF-stimulated Akt phosphorylation was detected at 12 h post-treatment, but an effect on proliferation was not observed until 48 h post-exposure. Growth-stimulated cellular lysates were analyzed for
protein profiles between treatment groups and across time points using iTRAQ labeling and mass spectrometry. The
protein response to
EGF treatment was identified via iTRAQ analysis in
EGF-stimulated lysates relative to vehicle-treated specimens across the treatment time course. Validation studies were performed on one of the differentially regulated
proteins,
lysosomal-associated membrane protein 1 (LAMP-1), in human tissue lysates and ovarian
tumor tissue sections. Further, tissue microarray analysis was performed to demarcate LAMP-1 expression across different stages of
epithelial ovarian cancers. These data support the use of this approach for the efficient identification of tissue-based markers in
tumor development related to specific signaling pathways. LAMP-1 is a promising
biomarker for studies of the progression of
EGF-stimulated
ovarian cancers and might be useful in predicting treatment responses involving
tyrosine kinase inhibitors or
EGF receptor monoclonal antibodies.