Abstract
Objectives. The purpose of this study is to discover potential biomarkers for the detection and monitoring of adjuvant chemotherapy for ovarian cancer. Methods. Serum samples from ovarian cancers and non-cancer controls were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). To discover the possible diagnostic biomarker for ovarian cancer, a preliminary training set of spectra derived from 31 primary ovarian cancer patients, 16 patients with benign ovarian diseases, and 25 healthy women was used to develop a proteomic model that discriminated cancer from non-cancer effectively. A blind test set, including 43 new cases, was used to validate the sensitivity and specificity of this multivariate model. To explore treatment-induced serum protein change, the protein profiles generated from 16 postoperative patients before chemotherapy are compared with those obtained after chemotherapy. Results. A Four-peak model was established in the training set that discriminated cancer from non-cancer with sensitivity of 90.8% and specificity of 93.5%. A sensitivity of 87.0% and a specificity of 95.0% for the blind test were obtained, compared with 60.7%, 55% for CA125 for the same samples. These 4 markers performed significantly better than the current standard marker, CA125 ( P < 0.05). One protein peak (mass/charge ratio [ m/ z], 4475) was identified in 12 of 16 (75%) postoperative patients after chemotherapy, but was absent before chemotherapy. Conclusion. The proteins represented by these peaks are candidate biomarkers for ovarian cancer diagnosis and/or monitoring treatment response.
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